Sample processing to enrich for microbial cell-free DNA using markers of oxidative stress

Abstract

Disclosed herein are methods of processing a sample comprising cell-free NA which can comprise microbial cell-free NA. Microbial cell-free NA can be differentiated from host NA via analysis of oxidative stress markers. Analysis of oxidative stress markers comprised in microbial cell-free NA can be utilized to characterize an infection and / or determine a diagnosis and / or a course of treatment for an infection.

Description

WSGR Docket No. 47697-746601SAMPLE PROCESSING TO ENRICH FOR MICROBIAL CELL-FREE DNA USING MARKERS OF OXIDATIVE STRESSCROSS-REFERENCE

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 724,981, filed November 26, 2024, all is which is incorporated herein by reference.BACKGROUND

[0002] The detection and sequencing of microbial cell-free DNA (mcfDNA) in a patient sample is a powerful diagnostic tool. Although methods have been developed which are capable of identifying and quantifying the amount of microbes in a patient sample, potentially uncovering an infection, many methods fall short of understanding the impact of exposure to a particular microbe. For example, simply identifying the presence of a microbe cannot reveal how a patient’s immune system has responded to the microbe, or whether it has responded at all. New methods are needed for quantifying the immune response to both infectious and non-infectious microbes.SUMMARY

[0003] This Summary introduces a selection of concepts that are described further below in the Detailed Description. This Summary is not intended to limit the scope of the claimed subject matter.

[0004] Aspects disclosed herein provide methods of processing cell-free nucleic acids (cfNA) in a sample, the method comprising: providing a sample derived from a subject, wherein the sample comprises cell-free nucleic acids (cfNA); and (a) detecting an oxidative stress marker present in the cfNA; (b) conducting a nucleic acid (NA) library preparation to enrich the sample for either cfNA comprising an oxidative stress marker or for cfNA that does not comprise an oxidative stress marker; or a combination of (a) and (b). In some embodiments, the oxidative stress marker comprises a member selected from the group consisting of (a) a nick in a strand of the cfNA; (b) a gap in a strand of the cfNA; (c) a substitution of a nucleotide or a component thereof in the cfNA for: (i) an 8-hydroxydeoxyguanosine; (ii) an 8-hydroxyguanine; (iii) an 8- hydroxy 2-deoxyguanosine; (iv) a thymine glycol; (v) a 5-hydroxymethyluracil; (vi) a formylamidopyrimidine; (vii) a 8-hydroxydeoxyadenine; (viii) an 8-oxo-adenine (8-oxoA); (ix) an isoguanine; (x) a formamidopyrimidine-A (FapyA); (xi) a 5' -Phosphoglycolate (5' -PG); (xii) a 5' -Hydroxyl (5' -OH); (xiii) a 5' -Phosphate (5' -P); (xiv) a 5' -Aldehyde; (xv) a 5' - Deoxyribonolactone-Derived Termini; or (xvi) any combination of (i) - (xv); or (d) a non-WSGR Docket No. 47697-746601Watson-Crick base pair; and (e) any combination of (a) - (d). In some embodiments, the cfNA comprises host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA). In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the mcfNA. In some embodiments, the conducting the NA library preparation comprises enriching the sample for mcfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the hcfNA. In some embodiments, the conducting the nucleic acid library preparation comprises enriching the sample for hcfNA by enriching for cfNA that does not comprise an oxidative stress marker. In some embodiments, the detecting comprises a binding reaction. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a chemical reagent. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a binding agent. In some embodiments, the binding agent comprises a protein, an antibody, an antibody fragment, a portion of an antibody, a functionally active fragment of an antibody, a ligase, an aptamer, or a combination thereof. In some embodiments, the antibody, the antibody fragment, or the combination thereof binds to 8-hydroxy deoxy guanosine, 8-hydroxy guanine, 8-hydroxy 2- deoxyguanosine, thymine glycol, 5-hydroxymethyluracil, formylamidopyrimidine, or 8- hydroxydeoxyadenine. In some embodiments, the binding agent comprises a NA binding domain. In some embodiments, the binding agent comprises a zinc-finger domain. In some embodiments, the method further comprises sequencing the cfNA to generate sequence reads. In some embodiments, the sequencing is performed prior to the detecting the oxidative stress marker present in the cfNA. In some embodiments, the sequencing comprises massively parallel sequencing. In some embodiments, the sequencing comprises high-throughput sequencing. In some embodiments, the high-throughput sequencing comprises sequencing by synthesis. In some embodiments, the high-throughput sequencing comprises nanopore sequencing. In some embodiments, the detecting comprises using a computer readable memory communicatively coupled to a processor configured to detect the sequence reads indicative of the oxidative stress marker in the sequence reads. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a Hoogstein base pair. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a noncanonical nucleotide. In some embodiments, the noncanonical nucleotide is detected by identifying a mis-match between a forward read and a reverse read at a locus. In some embodiments, the mis-match comprises a non-Watson-Crick base pairing. In some embodiments, the non-Watson-Crick base pairing comprises a Hoogstein base pairing. In some embodiments, the Hoogstein base pairing isWSGR Docket No. 47697-746601 selected from a member of the group consisting of: a G: A base pair, an A:U base pair, a G:G base pair, and a C:C base pair. In some embodiments, the method further comprises detecting noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing. In some embodiments, the method further comprises using a machine learning model configured to detect noncanonical nucleotides incorporated into at least one strand of a NA and outputting an indication of Hoogstein base pairing. In some embodiments, the detecting comprises performing an enzyme linked immunosorbent assay (ELISA). In some embodiments, the detecting comprises performing an immunofluorescence assay. In some embodiments, the binding reaction comprises a binding at approximately at a site associated with the oxidative stress marker. In some embodiments, the aptamer comprises RNA. In some embodiments, the aptamer comprises DNA. In some embodiments, the detecting comprises adding an oxidative stress tag to the cfNA at or near a site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 3' direction from the site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 5' direction from the site of oxidative stress. In some embodiments, the method further comprises identifying mcfNA based at least on the presence of an increased amount of an oxidative stress marker as compared to hcfNA. In some embodiments, the method further comprises determining an infection status of the subject based at least in part on the presence of mcfNA comprising an oxidative stress marker. In some embodiments, the method comprises: (a) sequencing the mcfNA to produce mcfNA sequence reads; and (b) using a computer readable memory communicatively coupled to a processor configured to determine an infection status of the subject based at least in part on the mcfNA sequence reads. In some embodiments, the computer readable memory encodes a machine learning model. In some embodiments, the machine learning model comprises a logistic regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method, or any combination thereof. In some embodiments, the machine learning model comprises the neural network, and wherein the neural network comprises a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, a generative adversarial network, or any combination thereof. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising an oxidative stress marker. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker. In some embodiments, the conducting the NA library preparation to enrich the sample for hcfNA orWSGR Docket No. 47697-746601 mcfNA comprising an oxidative stress marker comprises enriching for mcfNA derived from an infectious agent. In some embodiments, the mcfNA derived from the infectious agent comprises a higher proportion or quantity of an oxidative stress marker relative to mcfNA derived from a commensal organism. In some embodiments, the conducting the NA library preparation to enrich the sample comprises enriching for mcfNA comprising the oxidative stress marker. In some embodiments, the enriching comprises determining a quality of an immune response against an infectious agent. In some embodiments, an increase in mcfNA comprising an oxidative stress marker over a time period indicates an increased immune response. In some embodiments, a decrease in mcfNA comprising an oxidative stress marker over a time period indicates a decreased immune response. In some embodiments, the determining the infection status of the subject comprises determining the infection status to be active or latent. In some embodiments, the method further comprises determining an infection status of the subject at least in part by determining an immune response. In some embodiments, the host comprises a human. In some embodiments, the sample comprises a plasma sample. In some embodiments, the sample is selected from the group consisting of: blood, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardial fluid, rectal swab, bone, skin tissue, soft tissue, tears, and a nasal sample. In some embodiments, the method further comprises enriching for mitochondrial cfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, the method further comprises detecting an immune response by detecting cfNA comprising an oxidative stress marker. In some embodiments, the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA). In some embodiments, the nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA). In some embodiments, the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell-free DNA (cfDNA) and cell-free RNA (cfRNA).

[0005] Aspects disclosed herein comprise methods, the methods comprising a method of distinguishing between a commensal organism and an infectious agent by processing the cell- free nucleic acids (cfNA) in a sample by performing the methods disclosed herein. In some embodiments, the method further comprises sequencing the cfNA to generate sequence reads, and wherein the distinguishing comprises quantifying a number of sequence reads comprising an oxidative stress marker. In some embodiments, the method further comprises processing cell-WSGR Docket No. 47697-746601 free nucleic acids (cfNA) in a sample, the method comprising: providing a sample derived from a subject, wherein the sample comprises cell-free nucleic acids (cfNA); and (a) detecting an oxidative stress marker present in the cfNA; (b) conducting a nucleic acid (NA) library preparation to enrich the sample for either cfNA comprising an oxidative stress marker or for cfNA that does not comprise an oxidative stress marker; or a combination of (a) and (b). In some embodiments, the oxidative stress marker comprises a member selected from the group consisting of: (a) a nick in a strand of the cfNA; (b) a gap in a strand of the cfNA; (c) a substitution of a nucleotide or a component thereof in the cfNA for: (i) an 8- hydroxydeoxyguanosine; (ii) an 8-hydroxyguanine; (iii) an 8-hydroxy 2-deoxyguanosine; (iv) a thymine glycol; (v) a 5-hydroxymethyluracil; (vi) a formylamidopyrimidine; (vii) a 8- hydroxydeoxyadenine; (viii) an 8-oxo-adenine (8-oxoA); (ix) an isoguanine; (x) a formamidopyrimidine-A (FapyA); (xi) a 5' -Phosphoglycolate (5' -PG); (xii) a 5' -Hydroxyl (5' - OH); (xiii) a 5' -Phosphate (5' -P); (xiv) a 5' -Aldehyde; (xv) a 5' -Deoxyribonolactone-Derived Termini; or (xvi) any combination of (i) - (xv); or (d) a non-Watson-Crick base pair; and (e) any combination of (a) - (d). In some embodiments, the cfNA comprises host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA). In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the mcfNA. In some embodiments, the conducting the NA library preparation comprises enriching the sample for mcfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the hcfNA. In some embodiments, the conducting the nucleic acid library preparation comprises enriching the sample for hcfNA by enriching for cfNA that does not comprise an oxidative stress marker. In some embodiments, the detecting comprises a binding reaction. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a chemical reagent. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a binding agent. In some embodiments, the binding agent comprises a protein, an antibody, an antibody fragment, a portion of an antibody, a functionally active fragment of an antibody, a ligase, an aptamer, or a combination thereof. In some embodiments, the antibody, the antibody fragment, or the combination thereof binds to 8- hydroxydeoxyguanosine, 8-hydroxyguanine, 8-hydroxy 2-deoxyguanosine, thymine glycol, 5- hydroxymethyluracil, formylamidopyrimidine, or 8-hydroxydeoxyadenine. In some embodiments, the binding agent comprises a NA binding domain. In some embodiments, the binding agent comprises a zinc-finger domain. In some embodiments, the method further comprises sequencing the cfNA to generate sequence reads. In some embodiments, theWSGR Docket No. 47697-746601 sequencing is performed prior to the detecting the oxidative stress marker present in the cfNA. In some embodiments, the sequencing comprises massively parallel sequencing. In some embodiments, the sequencing comprises high-throughput sequencing. In some embodiments, the high-throughput sequencing comprises sequencing by synthesis. In some embodiments, the high-throughput sequencing comprises nanopore sequencing. In some embodiments, the detecting comprises using a computer readable memory communicatively coupled to a processor configured to detect the sequence reads indicative of the oxidative stress marker in the sequence reads. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a Hoogstein base pair. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a noncanonical nucleotide. In some embodiments, the noncanonical nucleotide is detected by identifying a mis-match between a forward read and a reverse read at a locus. In some embodiments, the mis-match comprises a non-Watson-Crick base pairing. In some embodiments, the non-Watson-Crick base pairing comprises a Hoogstein base pairing. In some embodiments, the Hoogstein base pairing is selected from a member of the group consisting of: a G: A base pair, an A:U base pair, a G:G base pair, and a C:C base pair. In some embodiments, the method further comprises detecting noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing. In some embodiments, the method further comprises using a machine learning model configured to detect noncanonical nucleotides incorporated into at least one strand of a NA and outputting an indication of Hoogstein base pairing. In some embodiments, the detecting comprises performing an enzyme linked immunosorbent assay (ELISA). In some embodiments, the detecting comprises performing an immunofluorescence assay. In some embodiments, the binding reaction comprises a binding at approximately at a site associated with the oxidative stress marker. In some embodiments, the aptamer comprises RNA. In some embodiments, the aptamer comprises DNA. In some embodiments, the detecting comprises adding an oxidative stress tag to the cfNA at or near a site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 3' direction from the site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 5' direction from the site of oxidative stress. In some embodiments, the method further comprises identifying mcfNA based at least on the presence of an increased amount of an oxidative stress marker as compared to hcfNA. In some embodiments, the method further comprises determining an infection status of the subject based at least in part on the presence of mcfNA comprising an oxidative stress marker. In some embodiments, the method comprises: (a) sequencing the mcfNA to produce mcfNA sequence reads; and (b) using a computer readable memory communicatively coupled toWSGR Docket No. 47697-746601 a processor configured to determine an infection status of the subject based at least in part on the mcfNA sequence reads. In some embodiments, the computer readable memory encodes a machine learning model. In some embodiments, the machine learning model comprises a logistic regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method, or any combination thereof. In some embodiments, the machine learning model comprises the neural network, and wherein the neural network comprises a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, a generative adversarial network, or any combination thereof. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising an oxidative stress marker. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker. In some embodiments, the conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker comprises enriching for mcfNA derived from an infectious agent. In some embodiments, the mcfNA derived from the infectious agent comprises a higher proportion or quantity of an oxidative stress marker relative to mcfNA derived from a commensal organism. In some embodiments, the conducting the NA library preparation to enrich the sample comprises enriching for mcfNA comprising the oxidative stress marker. In some embodiments, the enriching comprises determining a quality of an immune response against an infectious agent. In some embodiments, an increase in mcfNA comprising an oxidative stress marker over a time period indicates an increased immune response. In some embodiments, a decrease in mcfNA comprising an oxidative stress marker over a time period indicates a decreased immune response. In some embodiments, the determining the infection status of the subject comprises determining the infection status to be active or latent. In some embodiments, the method further comprises determining an infection status of the subject at least in part by determining an immune response. In some embodiments, the host comprises a human. In some embodiments, the sample comprises a plasma sample. In some embodiments, the sample is selected from the group consisting of blood, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardial fluid, rectal swab, bone, skin tissue, soft tissue, tears, and a nasalWSGR Docket No. 47697-746601 sample. In some embodiments, the method further comprises enriching for mitochondrial cfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, the method further comprises detecting an immune response by detecting cfNA comprising an oxidative stress marker. In some embodiments, the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA). In some embodiments, the nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA). In some embodiments, the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell-free DNA (cfDNA) and cell-free RNA (cfRNA).

[0006] Aspects disclosed herein comprise methods, the methods comprising a method of determining a quality of an immune response in a subject, the method comprising performing the methods disclosed herein. In some embodiments, the method further comprises collecting the series of samples over a time period. In some embodiments, the time period ranges from about one day to about one month, from about one day to about two months, from about one day to about three months, from about one day to about four months, from about one day to about five months, from about one day to about six months, or from about one day to about one year. In some embodiments, the method further comprises processing cell-free nucleic acids (cfNA) in a sample, the method comprising: providing a sample derived from a subject, wherein the sample comprises cell-free nucleic acids (cfNA); and (a) detecting an oxidative stress marker present in the cfNA; (b) conducting a nucleic acid (NA) library preparation to enrich the sample for either cfNA comprising an oxidative stress marker or for cfNA that does not comprise an oxidative stress marker; or a combination of (a) and (b). In some embodiments, the oxidative stress marker comprises a member selected from the group consisting of: (a) a nick in a strand of the cfNA; (b) a gap in a strand of the cfNA; (c) a substitution of a nucleotide or a component thereof in the cfNA for: (i) an 8-hydroxydeoxyguanosine; (ii) an 8-hydroxyguanine; (iii) an 8-hydroxy 2- deoxyguanosine; (iv) a thymine glycol; (v) a 5-hydroxymethyluracil; (vi) a formylamidopyrimidine; (vii) a 8-hydroxydeoxyadenine; (viii) an 8-oxo-adenine (8-oxoA); (ix) an isoguanine; (x) a formamidopyrimidine-A (FapyA); (xi) a 5' -Phosphoglycolate (5' -PG); (xii) a 5' -Hydroxyl (5' -OH); (xiii) a 5' -Phosphate (5' -P); (xiv) a 5' -Aldehyde; (xv) a 5' - Deoxyribonolactone-Derived Termini; or (xvi) any combination of (i) - (xv); or (d) a non- Watson-Crick base pair; and (e) any combination of (a) - (d). In some embodiments, the cfNA comprises host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA). In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the mcfNA. In some embodiments, the conducting the NA library preparation comprises enriching the sample for mcfNA by enriching for cfNAWSGR Docket No. 47697-746601 comprising an oxidative stress marker. In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the hcfNA. In some embodiments, the conducting the nucleic acid library preparation comprises enriching the sample for hcfNA by enriching for cfNA that does not comprise an oxidative stress marker. In some embodiments, the detecting comprises a binding reaction. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a chemical reagent. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a binding agent. In some embodiments, the binding agent comprises a protein, an antibody, an antibody fragment, a portion of an antibody, a functionally active fragment of an antibody, a ligase, an aptamer, or a combination thereof. In some embodiments, the antibody, the antibody fragment, or the combination thereof binds to 8-hydroxy deoxy guanosine, 8-hydroxy guanine, 8-hydroxy 2- deoxyguanosine, thymine glycol, 5-hydroxymethyluracil, formylamidopyrimidine, or 8- hydroxydeoxyadenine. In some embodiments, the binding agent comprises a NA binding domain. In some embodiments, the binding agent comprises a zinc-finger domain. In some embodiments, the method further comprises sequencing the cfNA to generate sequence reads. In some embodiments, the sequencing is performed prior to the detecting the oxidative stress marker present in the cfNA. In some embodiments, the sequencing comprises massively parallel sequencing. In some embodiments, the sequencing comprises high-throughput sequencing. In some embodiments, the high-throughput sequencing comprises sequencing by synthesis. In some embodiments, the high-throughput sequencing comprises nanopore sequencing. In some embodiments, the detecting comprises using a computer readable memory communicatively coupled to a processor configured to detect the sequence reads indicative of the oxidative stress marker in the sequence reads. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a Hoogstein base pair. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a noncanonical nucleotide. In some embodiments, the noncanonical nucleotide is detected by identifying a mis-match between a forward read and a reverse read at a locus. In some embodiments, the mis-match comprises a non-Watson-Crick base pairing. In some embodiments, the non-Watson-Crick base pairing comprises a Hoogstein base pairing. In some embodiments, the Hoogstein base pairing is selected from a member of the group consisting of: a G: A base pair, an A:U base pair, a G:G base pair, and a C:C base pair. In some embodiments, the method further comprises detecting noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing. In some embodiments, the method further comprises using a machine learning model configured to detect noncanonical nucleotides incorporated into atWSGR Docket No. 47697-746601 least one strand of a NA and outputting an indication of Hoogstein base pairing. In some embodiments, the detecting comprises performing an enzyme linked immunosorbent assay (ELISA). In some embodiments, the detecting comprises performing an immunofluorescence assay. In some embodiments, the binding reaction comprises a binding at approximately at a site associated with the oxidative stress marker. In some embodiments, the aptamer comprises RNA. In some embodiments, the aptamer comprises DNA. In some embodiments, the detecting comprises adding an oxidative stress tag to the cfNA at or near a site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 3' direction from the site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 5' direction from the site of oxidative stress. In some embodiments, the method further comprises identifying mcfNA based at least on the presence of an increased amount of an oxidative stress marker as compared to hcfNA. In some embodiments, the method further comprises determining an infection status of the subject based at least in part on the presence of mcfNA comprising an oxidative stress marker. In some embodiments, the method comprises: (a) sequencing the mcfNA to produce mcfNA sequence reads; and (b) using a computer readable memory communicatively coupled to a processor configured to determine an infection status of the subject based at least in part on the mcfNA sequence reads. In some embodiments, the computer readable memory encodes a machine learning model. In some embodiments, the machine learning model comprises a logistic regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method, or any combination thereof. In some embodiments, the machine learning model comprises the neural network, and wherein the neural network comprises a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, a generative adversarial network, or any combination thereof. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising an oxidative stress marker. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker. In some embodiments, the conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker comprises enriching for mcfNA derived from an infectious agent. In some embodiments, the mcfNA derived from the infectious agent comprises a higher proportion or quantity of an oxidative stress marker relative to mcfNA derived from a commensal organism. In some embodiments, the conducting the NA library preparation to enrich the sample comprises enriching for mcfNA comprising the oxidative stress marker. InWSGR Docket No. 47697-746601 some embodiments, the enriching comprises determining a quality of an immune response against an infectious agent. In some embodiments, an increase in mcfNA comprising an oxidative stress marker over a time period indicates an increased immune response. In some embodiments, a decrease in mcfNA comprising an oxidative stress marker over a time period indicates a decreased immune response. In some embodiments, the determining the infection status of the subject comprises determining the infection status to be active or latent. In some embodiments, the method further comprises determining an infection status of the subject at least in part by determining an immune response. In some embodiments, the host comprises a human. In some embodiments, the sample comprises a plasma sample. In some embodiments, the sample is selected from the group consisting of: blood, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardial fluid, rectal swab, bone, skin tissue, soft tissue, tears, and a nasal sample. In some embodiments, the method further comprises enriching for mitochondrial cfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, the method further comprises detecting an immune response by detecting cfNA comprising an oxidative stress marker. In some embodiments, the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA). In some embodiments, the nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA). In some embodiments, the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell-free DNA (cfDNA) and cell-free RNA (cfRNA).

[0007] Aspects disclosed herein comprise methods, the methods comprising a method of treating a subject for an infection, comprising: (a) diagnosing an infection of the subject at least in part using the methods disclosed herein; and (b) administering a therapy to the subject, wherein the therapy is selected to treat the infection. In some embodiments, the therapy is selected from the group consisting of antibiotics, antivirals, antifungals, antiparasitics, immunotherapies, vaccines, antimicrobials, probiotics, and supportive therapies. In some embodiments, the method further comprises processing cell-free nucleic acids (cfNA) in a sample, the method comprising: providing a sample derived from a subject, wherein the sample comprises cell-free nucleic acids (cfNA); and detecting an oxidative stress marker present in the cfNA; conducting a nucleic acid (NA) library preparation to enrich the sample for either cfNA comprising an oxidative stress marker or for cfNA that does not comprise an oxidative stressWSGR Docket No. 47697-746601 marker; or a combination of (a) and (b). In some embodiments, the oxidative stress marker comprises a member selected from the group consisting of: (a) a nick in a strand of the cfNA; (b) a gap in a strand of the cfNA; (c) a substitution of a nucleotide or a component thereof in the cfNA for: (i) an 8-hydroxydeoxyguanosine; (ii) an 8-hydroxyguanine; (iii) an 8-hydroxy 2- deoxyguanosine; (iv) a thymine glycol; (v) a 5-hydroxymethyluracil; (vi) a formylamidopyrimidine; (vii) a 8-hydroxydeoxyadenine; (viii) an 8-oxo-adenine (8-oxoA); (ix) an isoguanine; (x) a formamidopyrimidine-A (FapyA); (xi) a 5' -Phosphoglycolate (5' -PG); (xii) a 5' -Hydroxyl (5' -OH); (xiii) a 5' -Phosphate (5' -P); (xiv) a 5' -Aldehyde; (xv) a 5' - Deoxyribonolactone-Derived Termini; or (xvi) any combination of (i) - (xv); or (d) a non- Watson-Crick base pair; and (e) any combination of (a) - (d). In some embodiments, the cfNA comprises host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA). In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the mcfNA. In some embodiments, the conducting the NA library preparation comprises enriching the sample for mcfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the hcfNA. In some embodiments, the conducting the nucleic acid library preparation comprises enriching the sample for hcfNA by enriching for cfNA that does not comprise an oxidative stress marker. In some embodiments, the detecting comprises a binding reaction. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a chemical reagent. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a binding agent. In some embodiments, the binding agent comprises a protein, an antibody, an antibody fragment, a portion of an antibody, a functionally active fragment of an antibody, a ligase, an aptamer, or a combination thereof. In some embodiments, the antibody, the antibody fragment, or the combination thereof binds to 8-hydroxydeoxyguanosine, 8-hydroxyguanine, 8-hydroxy 2- deoxyguanosine, thymine glycol, 5-hydroxymethyluracil, formylamidopyrimidine, or 8- hydroxydeoxyadenine. In some embodiments, the binding agent comprises a NA binding domain. In some embodiments, the binding agent comprises a zinc-finger domain. In some embodiments, the method further comprises sequencing the cfNA to generate sequence reads. In some embodiments, the sequencing is performed prior to the detecting the oxidative stress marker present in the cfNA. In some embodiments, the sequencing comprises massively parallel sequencing. In some embodiments, the sequencing comprises high-throughput sequencing. In some embodiments, the high-throughput sequencing comprises sequencing by synthesis. In some embodiments, the high-throughput sequencing comprises nanopore sequencing. In someWSGR Docket No. 47697-746601 embodiments, the detecting comprises using a computer readable memory communicatively coupled to a processor configured to detect the sequence reads indicative of the oxidative stress marker in the sequence reads. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a Hoogstein base pair. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a noncanonical nucleotide. In some embodiments, the noncanonical nucleotide is detected by identifying a mis-match between a forward read and a reverse read at a locus. In some embodiments, the mis-match comprises a non-Watson-Crick base pairing. In some embodiments, the non-Watson-Crick base pairing comprises a Hoogstein base pairing. In some embodiments, the Hoogstein base pairing is selected from a member of the group consisting of a G: A base pair, an A:U base pair, a G:G base pair, and a C:C base pair. In some embodiments, the method further comprises detecting noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing. In some embodiments, the method further comprises using a machine learning model configured to detect noncanonical nucleotides incorporated into at least one strand of a NA and outputting an indication of Hoogstein base pairing. In some embodiments, the detecting comprises performing an enzyme linked immunosorbent assay (ELISA). In some embodiments, the detecting comprises performing an immunofluorescence assay. In some embodiments, the binding reaction comprises a binding at approximately at a site associated with the oxidative stress marker. In some embodiments, the aptamer comprises RNA. In some embodiments, the aptamer comprises DNA. In some embodiments, the detecting comprises adding an oxidative stress tag to the cfNA at or near a site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 3' direction from the site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 5' direction from the site of oxidative stress. In some embodiments, the method further comprises identifying mcfNA based at least on the presence of an increased amount of an oxidative stress marker as compared to hcfNA. In some embodiments, the method further comprises determining an infection status of the subject based at least in part on the presence of mcfNA comprising an oxidative stress marker. In some embodiments, the method comprises: (a) sequencing the mcfNA to produce mcfNA sequence reads; and (b) using a computer readable memory communicatively coupled to a processor configured to determine an infection status of the subject based at least in part on the mcfNA sequence reads. In some embodiments, the computer readable memory encodes a machine learning model. In some embodiments, the machine learning model comprises a logistic regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method,WSGR Docket No. 47697-746601 or any combination thereof. In some embodiments, the machine learning model comprises the neural network, and wherein the neural network comprises a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, a generative adversarial network, or any combination thereof. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising an oxidative stress marker. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker. In some embodiments, the conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker comprises enriching for mcfNA derived from an infectious agent. In some embodiments, the mcfNA derived from the infectious agent comprises a higher proportion or quantity of an oxidative stress marker relative to mcfNA derived from a commensal organism. In some embodiments, the conducting the NA library preparation to enrich the sample comprises enriching for mcfNA comprising the oxidative stress marker. In some embodiments, the enriching comprises determining a quality of an immune response against an infectious agent. In some embodiments, an increase in mcfNA comprising an oxidative stress marker over a time period indicates an increased immune response. In some embodiments, a decrease in mcfNA comprising an oxidative stress marker over a time period indicates a decreased immune response. In some embodiments, the determining the infection status of the subject comprises determining the infection status to be active or latent. In some embodiments, the method further comprises determining an infection status of the subject at least in part by determining an immune response. In some embodiments, the host comprises a human. In some embodiments, the sample comprises a plasma sample. In some embodiments, the sample is selected from the group consisting of: blood, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardial fluid, rectal swab, bone, skin tissue, soft tissue, tears, and a nasal sample. In some embodiments, the method further comprises enriching for mitochondrial cfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, the method further comprises detecting an immune response by detecting cfNA comprising an oxidative stress marker. In some embodiments, the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA). In some embodiments, theWSGR Docket No. 47697-746601 nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA). In some embodiments, the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell-free DNA (cfDNA) and cell-free RNA (cfRNA).

[0008] Aspects disclosed herein comprise methods, the methods comprising a method of processing a sample, comprising: (a) providing the sample comprising cell-free nucleic acids (cfNA); and (b) conducting an enrichment reaction on the sample that differentially affects cfNA comprising an oxidative stress marker as compared to cfNA that does not comprise the oxidative stress marker to generate an enriched cfNA library; and (c) sequencing the enriched cfNA library. In some embodiments, the cfNA comprises microbial cell-free DNA (mcfNA) and host cell-free DNA (hcfNA). In some embodiments, the method further comprises processing cell- free nucleic acids (cfNA) in a sample, the method comprising: providing a sample derived from a subject, wherein the sample comprises cell-free nucleic acids (cfNA); and (a) detecting an oxidative stress marker present in the cfNA; (b) conducting a nucleic acid (NA) library preparation to enrich the sample for either cfNA comprising an oxidative stress marker or for cfNA that does not comprise an oxidative stress marker; or a combination of (a) and (b). In some embodiments, the oxidative stress marker comprises a member selected from the group consisting of: (a) a nick in a strand of the cfNA; (b) a gap in a strand of the cfNA; (c) a substitution of a nucleotide or a component thereof in the cfNA for: (i) an 8- hydroxydeoxyguanosine; (ii) an 8-hydroxyguanine; (iii) an 8-hydroxy 2-deoxyguanosine; (iv) a thymine glycol; (v) a 5-hydroxymethyluracil; (vi) a formylamidopyrimidine; (vii) a 8- hydroxydeoxyadenine; (viii) an 8-oxo-adenine (8-oxoA); (ix) an isoguanine; (x) a formamidopyrimidine-A (FapyA); (xi) a 5' -Phosphoglycolate (5' -PG); (xii) a 5' -Hydroxyl (5' - OH); (xiii) a 5' -Phosphate (5' -P); (xiv) a 5' -Aldehyde; (xv) a 5' -Deoxyribonolactone-Derived Termini; or (xvi) any combination of (i) - (xv); or (d) a non-Watson-Crick base pair; and (e) any combination of (a) - (d). In some embodiments, the cfNA comprises host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA). In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the mcfNA. In some embodiments, the conducting the NA library preparation comprises enriching the sample for mcfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the hcfNA. In some embodiments, the conducting the nucleic acid library preparation comprises enriching the sample for hcfNA by enriching for cfNA that does not comprise an oxidative stress marker. In some embodiments, the detecting comprises a binding reaction. In some embodiments, the binding reaction comprises binding the oxidativeWSGR Docket No. 47697-746601 stress marker with a chemical reagent. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a binding agent. In some embodiments, the binding agent comprises a protein, an antibody, an antibody fragment, a portion of an antibody, a functionally active fragment of an antibody, a ligase, an aptamer, or a combination thereof. In some embodiments, the antibody, the antibody fragment, or the combination thereof binds to 8- hydroxydeoxyguanosine, 8-hydroxyguanine, 8-hydroxy 2-deoxyguanosine, thymine glycol, 5- hydroxymethyluracil, formylamidopyrimidine, or 8-hydroxydeoxyadenine. In some embodiments, the binding agent comprises a NA binding domain. In some embodiments, the binding agent comprises a zinc-finger domain. In some embodiments, the method further comprises sequencing the cfNA to generate sequence reads. In some embodiments, the sequencing is performed prior to the detecting the oxidative stress marker present in the cfNA. In some embodiments, the sequencing comprises massively parallel sequencing. In some embodiments, the sequencing comprises high-throughput sequencing. In some embodiments, the high-throughput sequencing comprises sequencing by synthesis. In some embodiments, the high-throughput sequencing comprises nanopore sequencing. In some embodiments, the detecting comprises using a computer readable memory communicatively coupled to a processor configured to detect the sequence reads indicative of the oxidative stress marker in the sequence reads. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a Hoogstein base pair. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a noncanonical nucleotide. In some embodiments, the noncanonical nucleotide is detected by identifying a mis-match between a forward read and a reverse read at a locus. In some embodiments, the mis-match comprises a non-Watson-Crick base pairing. In some embodiments, the non-Watson-Crick base pairing comprises a Hoogstein base pairing. In some embodiments, the Hoogstein base pairing is selected from a member of the group consisting of: a G: A base pair, an A:U base pair, a G:G base pair, and a C:C base pair. In some embodiments, the method further comprises detecting noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing. In some embodiments, the method further comprises using a machine learning model configured to detect noncanonical nucleotides incorporated into at least one strand of a NA and outputting an indication of Hoogstein base pairing. In some embodiments, the detecting comprises performing an enzyme linked immunosorbent assay (ELISA). In some embodiments, the detecting comprises performing an immunofluorescence assay. In some embodiments, the binding reaction comprises a binding at approximately at a site associated with the oxidative stress marker. In some embodiments, the aptamer comprises RNA. In some embodiments, theWSGR Docket No. 47697-746601 aptamer comprises DNA. In some embodiments, the detecting comprises adding an oxidative stress tag to the cfNA at or near a site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 3' direction from the site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 5' direction from the site of oxidative stress. In some embodiments, the method further comprises identifying mcfNA based at least on the presence of an increased amount of an oxidative stress marker as compared to hcfNA. In some embodiments, the method further comprises determining an infection status of the subject based at least in part on the presence of mcfNA comprising an oxidative stress marker. In some embodiments, the method comprises: (a) sequencing the mcfNA to produce mcfNA sequence reads; and (b) using a computer readable memory communicatively coupled to a processor configured to determine an infection status of the subject based at least in part on the mcfNA sequence reads. In some embodiments, the computer readable memory encodes a machine learning model. In some embodiments, the machine learning model comprises a logistic regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method, or any combination thereof. In some embodiments, the machine learning model comprises the neural network, and wherein the neural network comprises a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, a generative adversarial network, or any combination thereof. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising an oxidative stress marker. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker. In some embodiments, the conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker comprises enriching for mcfNA derived from an infectious agent. In some embodiments, the mcfNA derived from the infectious agent comprises a higher proportion or quantity of an oxidative stress marker relative to mcfNA derived from a commensal organism. In some embodiments, the conducting the NA library preparation to enrich the sample comprises enriching for mcfNA comprising the oxidative stress marker. In some embodiments, the enriching comprises determining a quality of an immune response against an infectious agent. In some embodiments, an increase in mcfNA comprising an oxidative stress marker over a time period indicates an increased immune response. In some embodiments, a decrease in mcfNA comprising an oxidative stress marker over a time period indicates a decreased immune response. In some embodiments, the determining the infection status of the subject comprises determining theWSGR Docket No. 47697-746601 infection status to be active or latent. In some embodiments, the method further comprises determining an infection status of the subject at least in part by determining an immune response. In some embodiments, the host comprises a human. In some embodiments, the sample comprises a plasma sample. In some embodiments, the sample is selected from the group consisting of: blood, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardial fluid, rectal swab, bone, skin tissue, soft tissue, tears, and a nasal sample. In some embodiments, the method further comprises enriching for mitochondrial cfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, the method further comprises detecting an immune response by detecting cfNA comprising an oxidative stress marker. In some embodiments, the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA). In some embodiments, the nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA). In some embodiments, the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell-free DNA (cfDNA) and cell-free RNA (cfRNA).

[0009] Aspects disclosed herein comprise non-transitory computer-readable storage mediums, wherein the non-transitory computer-readable storage mediums comprise a set of instructions recorded thereon, which, when executed by a processor, cause the processor to implement a method for detecting microbial cell-free nucleic acids (mcfNA), such as the methods disclosed throughout this disclosure. In some embodiments, the method further comprises processing cell-free nucleic acids (cfNA) in a sample, the method comprising: providing a sample derived from a subject, wherein the sample comprises cell-free nucleic acids (cfNA); and (a) detecting an oxidative stress marker present in the cfNA; (b) conducting a nucleic acid (NA) library preparation to enrich the sample for either cfNA comprising an oxidative stress marker or for cfNA that does not comprise an oxidative stress marker; or a combination of (a) and (b). In some embodiments, the oxidative stress marker comprises a member selected from the group consisting of: (a) a nick in a strand of the cfNA; (b) a gap in a strand of the cfNA; (c) a substitution of a nucleotide or a component thereof in the cfNA for: (i) an 8-hydroxydeoxyguanosine; (ii) an 8-hydroxyguanine; (iii) an 8-hydroxy 2-deoxyguanosine; (iv) a thymine glycol; (v) a 5-hydroxymethyluracil; (vi) a formylamidopyrimidine; (vii) a 8- hydroxydeoxyadenine; (viii) an 8-oxo-adenine (8-oxoA); (ix) an isoguanine; (x) aWSGR Docket No. 47697-746601 formamidopyrimidine-A (FapyA); (xi) a 5' -Phosphoglycolate (5' -PG); (xii) a 5' -Hydroxyl (5' - OH); (xiii) a 5' -Phosphate (5' -P); (xiv) a 5' -Aldehyde; (xv) a 5' -Deoxyribonolactone-Derived Termini; or (xvi) any combination of (i) - (xv); or (d) a non-Watson-Crick base pair; and (e) any combination of (a) - (d). In some embodiments, the cfNA comprises host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA). In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the mcfNA. In some embodiments, the conducting the NA library preparation comprises enriching the sample for mcfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the hcfNA. In some embodiments, the conducting the nucleic acid library preparation comprises enriching the sample for hcfNA by enriching for cfNA that does not comprise an oxidative stress marker. In some embodiments, the detecting comprises a binding reaction. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a chemical reagent. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a binding agent. In some embodiments, the binding agent comprises a protein, an antibody, an antibody fragment, a portion of an antibody, a functionally active fragment of an antibody, a ligase, an aptamer, or a combination thereof. In some embodiments, the antibody, the antibody fragment, or the combination thereof binds to 8- hydroxydeoxyguanosine, 8-hydroxyguanine, 8-hydroxy 2-deoxyguanosine, thymine glycol, 5- hydroxymethyluracil, formylamidopyrimidine, or 8-hydroxydeoxyadenine. In some embodiments, the binding agent comprises a NA binding domain. In some embodiments, the binding agent comprises a zinc-finger domain. In some embodiments, the method further comprises sequencing the cfNA to generate sequence reads. In some embodiments, the sequencing is performed prior to the detecting the oxidative stress marker present in the cfNA. In some embodiments, the sequencing comprises massively parallel sequencing. In some embodiments, the sequencing comprises high-throughput sequencing. In some embodiments, the high-throughput sequencing comprises sequencing by synthesis. In some embodiments, the high-throughput sequencing comprises nanopore sequencing. In some embodiments, the detecting comprises using a computer readable memory communicatively coupled to a processor configured to detect the sequence reads indicative of the oxidative stress marker in the sequence reads. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a Hoogstein base pair. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a noncanonical nucleotide. In some embodiments, the noncanonical nucleotide is detected by identifying a mis-match between a forward read and aWSGR Docket No. 47697-746601 reverse read at a locus. In some embodiments, the mis-match comprises a non-Watson-Crick base pairing. In some embodiments, the non-Watson-Crick base pairing comprises a Hoogstein base pairing. In some embodiments, the Hoogstein base pairing is selected from a member of the group consisting of: a G: A base pair, an A:U base pair, a G:G base pair, and a C:C base pair. In some embodiments, the method further comprises detecting noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing. In some embodiments, the method further comprises using a machine learning model configured to detect noncanonical nucleotides incorporated into at least one strand of a NA and outputting an indication of Hoogstein base pairing. In some embodiments, the detecting comprises performing an enzyme linked immunosorbent assay (ELISA). In some embodiments, the detecting comprises performing an immunofluorescence assay. In some embodiments, the binding reaction comprises a binding at approximately at a site associated with the oxidative stress marker. In some embodiments, the aptamer comprises RNA. In some embodiments, the aptamer comprises DNA. In some embodiments, the detecting comprises adding an oxidative stress tag to the cfNA at or near a site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 3' direction from the site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 5' direction from the site of oxidative stress. In some embodiments, the method further comprises identifying mcfNA based at least on the presence of an increased amount of an oxidative stress marker as compared to hcfNA. In some embodiments, the method further comprises determining an infection status of the subject based at least in part on the presence of mcfNA comprising an oxidative stress marker. In some embodiments, the method comprises: (a) sequencing the mcfNA to produce mcfNA sequence reads; and (b) using a computer readable memory communicatively coupled to a processor configured to determine an infection status of the subject based at least in part on the mcfNA sequence reads. In some embodiments, the computer readable memory encodes a machine learning model. In some embodiments, the machine learning model comprises a logistic regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method, or any combination thereof. In some embodiments, the machine learning model comprises the neural network, and wherein the neural network comprises a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, a generative adversarial network, or any combination thereof. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising an oxidative stress marker. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprisingWSGR Docket No. 47697-746601 conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker. In some embodiments, the conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker comprises enriching for mcfNA derived from an infectious agent. In some embodiments, the mcfNA derived from the infectious agent comprises a higher proportion or quantity of an oxidative stress marker relative to mcfNA derived from a commensal organism. In some embodiments, the conducting the NA library preparation to enrich the sample comprises enriching for mcfNA comprising the oxidative stress marker. In some embodiments, the enriching comprises determining a quality of an immune response against an infectious agent. In some embodiments, an increase in mcfNA comprising an oxidative stress marker over a time period indicates an increased immune response. In some embodiments, a decrease in mcfNA comprising an oxidative stress marker over a time period indicates a decreased immune response. In some embodiments, the determining the infection status of the subject comprises determining the infection status to be active or latent. In some embodiments, the method further comprises determining an infection status of the subject at least in part by determining an immune response. In some embodiments, the host comprises a human. In some embodiments, the sample comprises a plasma sample. In some embodiments, the sample is selected from the group consisting of: blood, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardial fluid, rectal swab, bone, skin tissue, soft tissue, tears, and a nasal sample. In some embodiments, the method further comprises enriching for mitochondrial cfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, the method further comprises detecting an immune response by detecting cfNA comprising an oxidative stress marker. In some embodiments, the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA). In some embodiments, the nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA). In some embodiments, the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell-free DNA (cfDNA) and cell-free RNA (cfRNA).

[0010] In some aspects, the present disclosure provides a non-transitory computer-readable storage medium comprising a set of instructions recorded thereon, which, when executed by a processor, cause the processor to implement a method for detecting microbial cell-free nucleicWSGR Docket No. 47697-746601 acids (mcfNA), wherein the method comprises: (i) obtaining a plurality of sequence reads derived from cell-free nucleic acids (cfNA) of a sample; (ii) processing the plurality of sequence reads to identify sequences comprising an oxidative stress marker; and (iii) detecting the mcfNA based at least a presence of the sequences comprising the oxidative stress marker. In some embodiments, the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA). In some embodiments, the nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA). In some embodiments, the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell -free DNA (cfDNA) and cell- free RNA (cfRNA). In some embodiments, the method further comprises processing cell-free nucleic acids (cfNA) in a sample, the method comprising: providing a sample derived from a subject, wherein the sample comprises cell-free nucleic acids (cfNA); and (a) detecting an oxidative stress marker present in the cfNA; (b) conducting a nucleic acid (NA) library preparation to enrich the sample for either cfNA comprising an oxidative stress marker or for cfNA that does not comprise an oxidative stress marker; or a combination of (a) and (b). In some embodiments, the oxidative stress marker comprises a member selected from the group consisting of: (a) a nick in a strand of the cfNA; (b) a gap in a strand of the cfNA; (c) a substitution of a nucleotide or a component thereof in the cfNA for: (i) an 8- hydroxydeoxyguanosine; (ii) an 8-hydroxyguanine; (iii) an 8-hydroxy 2-deoxyguanosine; (iv) a thymine glycol; (v) a 5-hydroxymethyluracil; (vi) a formylamidopyrimidine; (vii) a 8- hydroxydeoxyadenine; (viii) an 8-oxo-adenine (8-oxoA); (ix) an isoguanine; (x) a formamidopyrimidine-A (FapyA); (xi) a 5' -Phosphoglycolate (5' -PG); (xii) a 5' -Hydroxyl (5' - OH); (xiii) a 5' -Phosphate (5' -P); (xiv) a 5' -Aldehyde; (xv) a 5' -Deoxyribonolactone-Derived Termini; or (xvi) any combination of (i) - (xv); or (d) a non-Watson-Crick base pair; and (e) any combination of (a) - (d). In some embodiments, the cfNA comprises host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA). In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the mcfNA. In some embodiments, the conducting the NA library preparation comprises enriching the sample for mcfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the hcfNA. In some embodiments, the conducting the nucleic acid library preparation comprises enriching the sample for hcfNA by enriching for cfNA that does not comprise an oxidative stress marker. In some embodiments, the detecting comprises a binding reaction. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a chemical reagent. In some embodiments, the binding reaction comprisesWSGR Docket No. 47697-746601 binding the oxidative stress marker with a binding agent. In some embodiments, the binding agent comprises a protein, an antibody, an antibody fragment, a portion of an antibody, a functionally active fragment of an antibody, a ligase, an aptamer, or a combination thereof. In some embodiments, the antibody, the antibody fragment, or the combination thereof binds to 8- hydroxydeoxyguanosine, 8-hydroxyguanine, 8-hydroxy 2-deoxyguanosine, thymine glycol, 5- hydroxymethyluracil, formylamidopyrimidine, or 8-hydroxydeoxyadenine. In some embodiments, the binding agent comprises a NA binding domain. In some embodiments, the binding agent comprises a zinc-finger domain. In some embodiments, the method further comprises sequencing the cfNA to generate sequence reads. In some embodiments, the sequencing is performed prior to the detecting the oxidative stress marker present in the cfNA. In some embodiments, the sequencing comprises massively parallel sequencing. In some embodiments, the sequencing comprises high-throughput sequencing. In some embodiments, the high-throughput sequencing comprises sequencing by synthesis. In some embodiments, the high-throughput sequencing comprises nanopore sequencing. In some embodiments, the detecting comprises using a computer readable memory communicatively coupled to a processor configured to detect the sequence reads indicative of the oxidative stress marker in the sequence reads. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a Hoogstein base pair. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a noncanonical nucleotide. In some embodiments, the noncanonical nucleotide is detected by identifying a mis-match between a forward read and a reverse read at a locus. In some embodiments, the mis-match comprises a non-Watson-Crick base pairing. In some embodiments, the non-Watson-Crick base pairing comprises a Hoogstein base pairing. In some embodiments, the Hoogstein base pairing is selected from a member of the group consisting of: a G: A base pair, an A:U base pair, a G:G base pair, and a C:C base pair. In some embodiments, the method further comprises detecting noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing. In some embodiments, the method further comprises using a machine learning model configured to detect noncanonical nucleotides incorporated into at least one strand of a NA and outputting an indication of Hoogstein base pairing. In some embodiments, the detecting comprises performing an enzyme linked immunosorbent assay (ELISA). In some embodiments, the detecting comprises performing an immunofluorescence assay. In some embodiments, the binding reaction comprises a binding at approximately at a site associated with the oxidative stress marker. In some embodiments, the aptamer comprises RNA. In some embodiments, the aptamer comprises DNA. In some embodiments, the detecting comprises adding an oxidativeWSGR Docket No. 47697-746601 stress tag to the cfNA at or near a site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 3' direction from the site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 5' direction from the site of oxidative stress. In some embodiments, the method further comprises identifying mcfNA based at least on the presence of an increased amount of an oxidative stress marker as compared to hcfNA. In some embodiments, the method further comprises determining an infection status of the subject based at least in part on the presence of mcfNA comprising an oxidative stress marker. In some embodiments, the method comprises: (a) sequencing the mcfNA to produce mcfNA sequence reads; and (b) using a computer readable memory communicatively coupled to a processor configured to determine an infection status of the subject based at least in part on the mcfNA sequence reads. In some embodiments, the computer readable memory encodes a machine learning model. In some embodiments, the machine learning model comprises a logistic regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method, or any combination thereof. In some embodiments, the machine learning model comprises the neural network, and wherein the neural network comprises a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, a generative adversarial network, or any combination thereof. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising an oxidative stress marker. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker. In some embodiments, the conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker comprises enriching for mcfNA derived from an infectious agent. In some embodiments, the mcfNA derived from the infectious agent comprises a higher proportion or quantity of an oxidative stress marker relative to mcfNA derived from a commensal organism. In some embodiments, the conducting the NA library preparation to enrich the sample comprises enriching for mcfNA comprising the oxidative stress marker. In some embodiments, the enriching comprises determining a quality of an immune response against an infectious agent. In some embodiments, an increase in mcfNA comprising an oxidative stress marker over a time period indicates an increased immune response. In some embodiments, a decrease in mcfNA comprising an oxidative stress marker over a time period indicates a decreased immune response. In some embodiments, the determining the infection status of the subject comprises determining the infection status to be active or latent. In some embodiments, the method further comprisesWSGR Docket No. 47697-746601 determining an infection status of the subject at least in part by determining an immune response. In some embodiments, the host comprises a human. In some embodiments, the sample comprises a plasma sample. In some embodiments, the sample is selected from the group consisting of: blood, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardial fluid, rectal swab, bone, skin tissue, soft tissue, tears, and a nasal sample. In some embodiments, the method further comprises enriching for mitochondrial cfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, the method further comprises detecting an immune response by detecting cfNA comprising an oxidative stress marker. In some embodiments, the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA). In some embodiments, the nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA). In some embodiments, the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell-free DNA (cfDNA) and cell-free RNA (cfRNA).

[0011] Aspects disclosed herein comprise methods, the methods comprising a method of preparing a nucleic acid library useful for analyzing oxidative stress markers, the method comprising performing the methods of processing cell-free nucleic acids (cfNA) disclosed herein. In some embodiments, the method further comprises processing cell-free nucleic acids (cfNA) in a sample, the method comprising: providing a sample derived from a subject, wherein the sample comprises cell-free nucleic acids (cfNA); and (a) detecting an oxidative stress marker present in the cfNA; (b) conducting a nucleic acid (NA) library preparation to enrich the sample for either cfNA comprising an oxidative stress marker or for cfNA that does not comprise an oxidative stress marker; or a combination of (a) and (b). In some embodiments, the oxidative stress marker comprises a member selected from the group consisting of: (a) a nick in a strand of the cfNA; (b) a gap in a strand of the cfNA; (c) a substitution of a nucleotide or a component thereof in the cfNA for: (i) an 8-hydroxydeoxyguanosine; (ii) an 8-hydroxyguanine; (iii) an 8- hydroxy 2-deoxyguanosine; (iv) a thymine glycol; (v) a 5-hydroxymethyluracil; (vi) a formylamidopyrimidine; (vii) a 8-hydroxydeoxyadenine; (viii) an 8-oxo-adenine (8-oxoA); (ix) an isoguanine; (x) a formamidopyrimidine-A (FapyA); (xi) a 5' -Phosphoglycolate (5' -PG); (xii) a 5' -Hydroxyl (5' -OH); (xiii) a 5' -Phosphate (5' -P); (xiv) a 5' -Aldehyde; (xv) a 5' - Deoxyribonolactone-Derived Termini; or (xvi) any combination of (i) - (xv); or (d) a non-WSGR Docket No. 47697-746601Watson-Crick base pair; and (e) any combination of (a) - (d). In some embodiments, the cfNA comprises host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA). In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the mcfNA. In some embodiments, the conducting the NA library preparation comprises enriching the sample for mcfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the hcfNA. In some embodiments, the conducting the nucleic acid library preparation comprises enriching the sample for hcfNA by enriching for cfNA that does not comprise an oxidative stress marker. In some embodiments, the detecting comprises a binding reaction. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a chemical reagent. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a binding agent. In some embodiments, the binding agent comprises a protein, an antibody, an antibody fragment, a portion of an antibody, a functionally active fragment of an antibody, a ligase, an aptamer, or a combination thereof. In some embodiments, the antibody, the antibody fragment, or the combination thereof binds to 8-hydroxy deoxy guanosine, 8-hydroxy guanine, 8-hydroxy 2- deoxyguanosine, thymine glycol, 5-hydroxymethyluracil, formylamidopyrimidine, or 8- hydroxydeoxyadenine. In some embodiments, the binding agent comprises a NA binding domain. In some embodiments, the binding agent comprises a zinc-finger domain. In some embodiments, the method further comprises sequencing the cfNA to generate sequence reads. In some embodiments, the sequencing is performed prior to the detecting the oxidative stress marker present in the cfNA. In some embodiments, the sequencing comprises massively parallel sequencing. In some embodiments, the sequencing comprises high-throughput sequencing. In some embodiments, the high-throughput sequencing comprises sequencing by synthesis. In some embodiments, the high-throughput sequencing comprises nanopore sequencing. In some embodiments, the detecting comprises using a computer readable memory communicatively coupled to a processor configured to detect the sequence reads indicative of the oxidative stress marker in the sequence reads. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a Hoogstein base pair. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a noncanonical nucleotide. In some embodiments, the noncanonical nucleotide is detected by identifying a mis-match between a forward read and a reverse read at a locus. In some embodiments, the mis-match comprises a non-Watson-Crick base pairing. In some embodiments, the non-Watson-Crick base pairing comprises a Hoogstein base pairing. In some embodiments, the Hoogstein base pairing isWSGR Docket No. 47697-746601 selected from a member of the group consisting of: a G: A base pair, an A:U base pair, a G:G base pair, and a C:C base pair. In some embodiments, the method further comprises detecting noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing. In some embodiments, the method further comprises using a machine learning model configured to detect noncanonical nucleotides incorporated into at least one strand of a NA and outputting an indication of Hoogstein base pairing. In some embodiments, the detecting comprises performing an enzyme linked immunosorbent assay (ELISA). In some embodiments, the detecting comprises performing an immunofluorescence assay. In some embodiments, the binding reaction comprises a binding at approximately at a site associated with the oxidative stress marker. In some embodiments, the aptamer comprises RNA. In some embodiments, the aptamer comprises DNA. In some embodiments, the detecting comprises adding an oxidative stress tag to the cfNA at or near a site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 3' direction from the site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 5' direction from the site of oxidative stress. In some embodiments, the method further comprises identifying mcfNA based at least on the presence of an increased amount of an oxidative stress marker as compared to hcfNA. In some embodiments, the method further comprises determining an infection status of the subject based at least in part on the presence of mcfNA comprising an oxidative stress marker. In some embodiments, the method comprises: (a) sequencing the mcfNA to produce mcfNA sequence reads; and (b) using a computer readable memory communicatively coupled to a processor configured to determine an infection status of the subject based at least in part on the mcfNA sequence reads. In some embodiments, the computer readable memory encodes a machine learning model. In some embodiments, the machine learning model comprises a logistic regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method, or any combination thereof. In some embodiments, the machine learning model comprises the neural network, and wherein the neural network comprises a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, a generative adversarial network, or any combination thereof. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising an oxidative stress marker. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker. In some embodiments, the conducting the NA library preparation to enrich the sample for hcfNA orWSGR Docket No. 47697-746601 mcfNA comprising an oxidative stress marker comprises enriching for mcfNA derived from an infectious agent. In some embodiments, the mcfNA derived from the infectious agent comprises a higher proportion or quantity of an oxidative stress marker relative to mcfNA derived from a commensal organism. In some embodiments, the conducting the NA library preparation to enrich the sample comprises enriching for mcfNA comprising the oxidative stress marker. In some embodiments, the enriching comprises determining a quality of an immune response against an infectious agent. In some embodiments, an increase in mcfNA comprising an oxidative stress marker over a time period indicates an increased immune response. In some embodiments, a decrease in mcfNA comprising an oxidative stress marker over a time period indicates a decreased immune response. In some embodiments, the determining the infection status of the subject comprises determining the infection status to be active or latent. In some embodiments, the method further comprises determining an infection status of the subject at least in part by determining an immune response. In some embodiments, the host comprises a human. In some embodiments, the sample comprises a plasma sample. In some embodiments, the sample is selected from the group consisting of: blood, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardial fluid, rectal swab, bone, skin tissue, soft tissue, tears, and a nasal sample. In some embodiments, the method further comprises enriching for mitochondrial cfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, the method further comprises detecting an immune response by detecting cfNA comprising an oxidative stress marker. In some embodiments, the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA). In some embodiments, the nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA). In some embodiments, the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell-free DNA (cfDNA) and cell-free RNA (cfRNA).

[0012] Aspects disclosed herein comprise methods, the methods comprising a method of improving nucleic acid data processing, the method comprising performing the methods disclosed herein. In some embodiments, the method further comprises processing cell-free nucleic acids (cfNA) in a sample, the method comprising: providing a sample derived from a subject, wherein the sample comprises cell-free nucleic acids (cfNA); and (a) detecting an oxidative stress marker present in the cfNA; (b) conducting a nucleic acid (NA) libraryWSGR Docket No. 47697-746601 preparation to enrich the sample for either cfNA comprising an oxidative stress marker or for cfNA that does not comprise an oxidative stress marker; or a combination of (a) and (b). In some embodiments, the oxidative stress marker comprises a member selected from the group consisting of: (a) a nick in a strand of the cfNA; (b) a gap in a strand of the cfNA; (c) a substitution of a nucleotide or a component thereof in the cfNA for: (i) an 8- hydroxydeoxyguanosine; (ii) an 8-hydroxyguanine; (iii) an 8-hydroxy 2-deoxyguanosine; (iv) a thymine glycol; (v) a 5-hydroxymethyluracil; (vi) a formylamidopyrimidine; (vii) a 8- hydroxydeoxyadenine; (viii) an 8-oxo-adenine (8-oxoA); (ix) an isoguanine; (x) a formamidopyrimidine-A (FapyA); (xi) a 5' -Phosphoglycolate (5' -PG); (xii) a 5' -Hydroxyl (5' - OH); (xiii) a 5' -Phosphate (5' -P); (xiv) a 5' -Aldehyde; (xv) a 5' -Deoxyribonolactone-Derived Termini; or (xvi) any combination of (i) - (xv); or (d) a non-Watson-Crick base pair; and (e) any combination of (a) - (d). In some embodiments, the cfNA comprises host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA). In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the mcfNA. In some embodiments, the conducting the NA library preparation comprises enriching the sample for mcfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the hcfNA. In some embodiments, the conducting the nucleic acid library preparation comprises enriching the sample for hcfNA by enriching for cfNA that does not comprise an oxidative stress marker. In some embodiments, the detecting comprises a binding reaction. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a chemical reagent. In some embodiments, the binding reaction comprises binding the oxidative stress marker with a binding agent. In some embodiments, the binding agent comprises a protein, an antibody, an antibody fragment, a portion of an antibody, a functionally active fragment of an antibody, a ligase, an aptamer, or a combination thereof. In some embodiments, the antibody, the antibody fragment, or the combination thereof binds to 8- hydroxydeoxyguanosine, 8-hydroxyguanine, 8-hydroxy 2-deoxyguanosine, thymine glycol, 5- hydroxymethyluracil, formylamidopyrimidine, or 8-hydroxydeoxyadenine. In some embodiments, the binding agent comprises a NA binding domain. In some embodiments, the binding agent comprises a zinc-finger domain. In some embodiments, the method further comprises sequencing the cfNA to generate sequence reads. In some embodiments, the sequencing is performed prior to the detecting the oxidative stress marker present in the cfNA. In some embodiments, the sequencing comprises massively parallel sequencing. In some embodiments, the sequencing comprises high-throughput sequencing. In some embodiments, theWSGR Docket No. 47697-746601 high-throughput sequencing comprises sequencing by synthesis. In some embodiments, the high-throughput sequencing comprises nanopore sequencing. In some embodiments, the detecting comprises using a computer readable memory communicatively coupled to a processor configured to detect the sequence reads indicative of the oxidative stress marker in the sequence reads. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a Hoogstein base pair. In some embodiments, the detecting comprises detecting the oxidative stress marker by detecting a noncanonical nucleotide. In some embodiments, the noncanonical nucleotide is detected by identifying a mis-match between a forward read and a reverse read at a locus. In some embodiments, the mis-match comprises a non-Watson-Crick base pairing. In some embodiments, the non-Watson-Crick base pairing comprises a Hoogstein base pairing. In some embodiments, the Hoogstein base pairing is selected from a member of the group consisting of a G: A base pair, an A:U base pair, a G:G base pair, and a C:C base pair. In some embodiments, the method further comprises detecting noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing. In some embodiments, the method further comprises using a machine learning model configured to detect noncanonical nucleotides incorporated into at least one strand of a NA and outputting an indication of Hoogstein base pairing. In some embodiments, the detecting comprises performing an enzyme linked immunosorbent assay (ELISA). In some embodiments, the detecting comprises performing an immunofluorescence assay. In some embodiments, the binding reaction comprises a binding at approximately at a site associated with the oxidative stress marker. In some embodiments, the aptamer comprises RNA. In some embodiments, the aptamer comprises DNA. In some embodiments, the detecting comprises adding an oxidative stress tag to the cfNA at or near a site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 3' direction from the site of oxidative stress. In some embodiments, the oxidative stress tag is from 1 to 10 base pairs in the 5' direction from the site of oxidative stress. In some embodiments, the method further comprises identifying mcfNA based at least on the presence of an increased amount of an oxidative stress marker as compared to hcfNA. In some embodiments, the method further comprises determining an infection status of the subject based at least in part on the presence of mcfNA comprising an oxidative stress marker. In some embodiments, the method comprises: (a) sequencing the mcfNA to produce mcfNA sequence reads; and (b) using a computer readable memory communicatively coupled to a processor configured to determine an infection status of the subject based at least in part on the mcfNA sequence reads. In some embodiments, the computer readable memory encodes a machine learning model. In some embodiments, the machine learning model comprises a logisticWSGR Docket No. 47697-746601 regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method, or any combination thereof. In some embodiments, the machine learning model comprises the neural network, and wherein the neural network comprises a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, a generative adversarial network, or any combination thereof. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising an oxidative stress marker. In some embodiments, the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker. In some embodiments, the conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker comprises enriching for mcfNA derived from an infectious agent. In some embodiments, the mcfNA derived from the infectious agent comprises a higher proportion or quantity of an oxidative stress marker relative to mcfNA derived from a commensal organism. In some embodiments, the conducting the NA library preparation to enrich the sample comprises enriching for mcfNA comprising the oxidative stress marker. In some embodiments, the enriching comprises determining a quality of an immune response against an infectious agent. In some embodiments, an increase in mcfNA comprising an oxidative stress marker over a time period indicates an increased immune response. In some embodiments, a decrease in mcfNA comprising an oxidative stress marker over a time period indicates a decreased immune response. In some embodiments, the determining the infection status of the subject comprises determining the infection status to be active or latent. In some embodiments, the method further comprises determining an infection status of the subject at least in part by determining an immune response. In some embodiments, the host comprises a human. In some embodiments, the sample comprises a plasma sample. In some embodiments, the sample is selected from the group consisting of: blood, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardial fluid, rectal swab, bone, skin tissue, soft tissue, tears, and a nasal sample. In some embodiments, the method further comprises enriching for mitochondrial cfNA by enriching for cfNA comprising an oxidative stress marker. In some embodiments, the method further comprises detecting an immune response by detecting cfNA comprising an oxidativeWSGR Docket No. 47697-746601 stress marker. In some embodiments, the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA). In some embodiments, the nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA). In some embodiments, the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell-free DNA (cfDNA) and cell-free RNA (cfRNA).INCORPORATION BY REFERENCE

[0013] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference in their entireties to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The novel features of the disclosure are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present disclosure will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the disclosure are utilized, and the accompanying drawings of which:

[0015] FIG. 1 shows a computer control system that is programmed or otherwise configured to implement methods provided herein.

[0016] FIGs. 2A-D show graphs of levels of 8-oxoG from human plasma samples. FIG. 2A shows the microbial EDR versus the concentration of 8-oxoG. FIG. 2B shows the microbial MPM versus the concentration of 8-oxoG. FIG. 2C shows the human MPM versus the concentration of 8-oxoG. FIG. 2D shows the human MPM versus the microbial MPM.

[0017] FIG. 3 shows a graph of enrichment of 8-oxodG in microbial samples.

[0018] FIG. 4 shows a graph of the percentage recovery of 8-oxodG labeled control molecules in different samples.

[0019] FIG. 5 shows a graph of enrichment of 8-oxoG in mitochondrial DNA.

[0020] FIG. 6 shows an exemplary workflow of the methods described herein.

[0021] FIG. 7 shows a comparison of the pulldown assay described herein and two control assays for three samples with different microbes.

[0022] FIG. 8 shows a comparison of the pull-down assay described herein and two control assays for a sample with multiple microbes.

[0023] FIG. 9 shows an analysis the fraction of reads at varying lengths from the pulldown assay described and a control assay.WSGR Docket No. 47697-746601

[0024] FIG. 10 shows an analysis of mutations identified in samples based on the conversion of the base pair for the pull-down assay described and a control assay.

[0025] FIG. 11 shows the concentration of 8-oxoG as compared to the microbial MPM, the microbial EDR, and the human MPM.DETAILED DESCRIPTION

[0026] The following passages describe different aspects of the disclosure in greater detail. Each aspect, embodiment, or feature of the disclosure can be combined with any other aspect, embodiment, or feature of the disclosure unless clearly indicated to the contrary.

[0027] Disclosed herein in some embodiments are methods and compositions for processing nucleic acids, such as cell-free nucleic acids (cfNA) (e.g., cell-free DNA (cfDNA) or cell-free RNA (cfRNA)). In some embodiments, the cfNA are host cfNA. In some embodiments, the cfNA are microbial cfNA. In some embodiments, the cfNA are plant cfNA. In some embodiments, the cfNA are mitochondrial cfNA. In some embodiments, the cfNA comprises a mixture of cfNA. The mixture of cfNA can be from different types of nucleic acids (e.g., cfDNA or cfRNA). The mixture of cfNA can be from different sources (e.g., host, microbial, plant, or mitochondrial). In some embodiments, cfNA can comprise a mixture of host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA). Disclosed herein in some embodiments are methods and compositions for processing or detecting hcfNA or mcfNA from a mixture thereof. In some embodiments, mcfNA can be processed via detection of an oxidative stress marker. In some embodiments, hcfNA can be processed via detection of an oxidative stress marker. In some embodiments, an oxidative stress marker can be detected in mcfNA. In some embodiments, an oxidative stress marker can be detected in hcfNA. In some embodiments, one or more oxidative stress markers can be detected in mcfNA. In some embodiments, one or more oxidative stress markers can be detected in hcfNA. In some embodiments, hcfNA can be detected or enriched by detecting or enriching for an absence of oxidative stress markers. In some embodiments, oxidative stress markers can occur at a higher frequency in mcfNA as compared to hcfNA. In some embodiments, mcfDNA can be detected by enriching for cell-free NA (cfNA) comprising oxidative stress markers. In some embodiments, cfNA comprises mcfNA and hcfNA. In some embodiments, mcfNA can be detected by enriching for cfNA comprising oxidative stress markers. In some embodiments, hcfNA can be detected by enriching for cfNA which does not comprise oxidative stress markers. In some embodiments, cfNA can be processed via preparation of a NA library. In some embodiments, mcfNA can be processed via preparation of a NA library. In some embodiments, hcfNA can be processed via preparation of a NA library. InWSGR Docket No. 47697-746601 some embodiments, preparation of a NA library can enrich a sample for NA comprising one or more oxidative stress markers. In some embodiments, mcfNA can be sequenced prior to an enrichment. In some embodiments, hcfNA can be sequenced prior to an enrichment. In some embodiments, mcfNA can be enriched prior to a sequencing. In some embodiments, mcfNA can be sequenced before enrichment, after enrichment, or both. In some embodiments, hcfNA can be sequenced before enrichment, after enrichment, or both. In some embodiments, a sequencing can generate sequence reads. In some embodiments, sequence reads can be analyzed. In some embodiments, an analysis of sequencing reads can determine one or more of an identity, a distribution, a quantity, a diversity, or a type of oxidative stress marker present in a sample. In some embodiments, an analysis of sequence reads can identify an oxidative stress marker in a sample. In some embodiments, an oxidative stress marker can be present in cfNA. In some embodiments, an oxidative stress marker can be present in mcfNA. In some embodiments, an oxidative stress marker can be present in hcfNA. In some embodiments, one or more oxidative stress markers can be present in cfNA. In some embodiments, one or more oxidative stress markers can be present in hcfNA. In some embodiments, analysis of an oxidative stress marker can identify an infection, an immune response, a response to a treatment, or any combination thereof. In some embodiments, analysis of one or more oxidative stress markers can identify an infection, an immune response, a response to a treatment, or any combination thereof.Oxidative stress

[0028] Disclosed herein are compositions and methods for detecting oxidative stress in a sample. In some embodiments, detecting oxidative stress can comprise detecting an oxidative stress marker. In some embodiments, oxidative stress can refer to a disturbance in equilibrium between oxidants and antioxidants in which oxidants fail to be neutralized by antioxidants. In some embodiments, oxidants can non-enzymatically damage macromolecules including proteins, nucleic acids, and lipids. In some embodiments, oxidants can include but are not limited to 02’", H2O2, and lipid hydroperoxides. In some embodiments, oxidative stress markers as defined herein can comprise any one of the following results, products, side-effects, lesions, or damages mediated by, caused by, or resulting from oxidative stress as described herein.

[0029] In some embodiments, an immune-inflammatory response is associated with an increase in oxidative stress. In some embodiments, recognition of an invading pathogen by the innate immune response can activate a cascade of multiple processes to fight the infection. In some embodiments, a process utilized by the immune system to fight pathogens involves the generation of reactive oxygen species (ROS). In some embodiments, a cell type recruited by the innate immune response to generate reactive oxygen species is a phagocyte. In someWSGR Docket No. 47697-746601 embodiments, phagocytes include but are not limited to neutrophils and macrophages. In some embodiments, phagocytes recognize microbes through pattern recognition receptors (PRRs).In some embodiments, PRRs recognize pathogen-associated molecular patterns (PAMPs) displayed by pathogenic microbes. In some embodiments, phagocytic cells engulf pathogenic microbes. In some embodiments, phagocytes utilize a process known as respiratory burst by which NADPH oxidase generates ROS in response to microbe recognition. In some embodiments, a fungus is phagocytosed by a phagocyte. In some embodiments, a bacterium is phagocytosed by a phagocyte. In some embodiments, a microorganism is phagocytosed by a phagocyte. In some embodiments, NADPH oxidase 2 (N0X2) assembles at the phagosome membrane. In some embodiments, N0X2 discharges high amounts of superoxide (02 ') into the phagosome. In some embodiments, ROS damage a fungus, bacterium, or microorganism through oxidative stress. In some embodiments, oxidative stress results in microbe elimination. In some embodiments, ROS can indirectly contribute to elimination of pathogenic microbes by activating various processes including but not limited to inflammation, NETosis (the formation of neutrophil extracellular traps (NETs)), triggering of an antiviral response by inhibition of mTOR kinase, autophagy, and proteolytic elimination. In some embodiments, mitochondria within immune cells can also generate ROS via the mitochondrial electron transport chain (ETC).

[0030] In some embodiments, reactive oxygen species are also known as free radicals. In some embodiments, reactive oxygen species serve as oxidizing agents. In some embodiments, reactive oxygen species include but are not limited to superoxide (O2-), peroxide (H2O2), singlet oxygen, and hydroxyl radicals (HO»). In some embodiments, oxidative stress can result from an imbalance between antioxidants and ROS. In some embodiments, an imbalance between antioxidants and ROS leads to damage of various cellular components including proteins, lipids, and nucleic acids. In some embodiments, an imbalance between antioxidants and ROS leads to damage of various cellular components including proteins, lipids, or nucleic acids.

[0031] In some embodiments, ROS can damage a cell through several mechanisms, including but not limited to lipid peroxidation, NA single or double strand breakage, base oxidation and deamination, and oxidation of methionine residues. In some embodiments, NA single or double strand breakage can result from direct interaction with ROS. In some embodiments, NA single or double strand breakage is generated as an intermediate of NA repair mechanisms. In some embodiments, base excision repair processes can result in NA breaks. In some embodiments, nucleotide excision repair processes can result in NA breaks.

[0032] In some embodiments, oxidative stress can lead to the formation of gaps in NA. In some embodiments, one or more of NA gaps, single strand or double strand breaks, apurinicWSGR Docket No. 47697-746601 lesions, or apyrimidinic lesions resulting from oxidative stress can occur. In some embodiments, one or more of NA gaps, single strand or double strand breaks, apurinic lesions, and apyrimidinic lesions resulting from oxidative stress can occur in coding or non-coding regions of NA. In some embodiments, one or more of NA gaps, single strand or double strand breaks, apurinic lesions, or apyrimidinic lesions resulting from oxidative stress can impact function. In some embodiments, one or more of NA gaps, single strand or double strand breaks, apurinic lesions, and apyrimidinic lesions resulting from oxidative stress can be silent.

[0033] In some embodiments, interaction with ROS can generate abasic sites in which a base is lost. In some embodiments, abasic sites result from spontaneous depurination mediated by interaction with ROS. In some embodiments, abasic sites can exist in a ring closed form. In some embodiments, abasic sites can exist in a ring opened form. In some embodiments, an abasic site in ring opened form has an active aldehyde group with can react specifically with an aldehyde-reactive probe (ARP), a biotinylated alkoxyamine.

[0034] In some embodiments, oxidative stress can damage NA by several mechanisms. In some embodiments, oxidative stress can cause double or single strand breaks in NA. In some embodiments, guanine is damaged by oxidative stress. In some embodiments, guanine is damaged by an attack from reactive oxygen species (ROS). In some embodiments, ROS attack guanine and leads to the conversion of a guanine base to 8-oxo-7,8-dihydroguanine (8-oxoG). In some embodiments, 8-oxoG can also be known as 8-hydroxyguanine (8-OH-dG), 8-hydroxy-2’- deoxy guanosine (8-OH-dG or 8-oxo-dG), 7,8-dihydro-8-oxoguanine, or 8-oxoguanine (8-oxodG or 8-oxoG), is formed. In some embodiments, 8-oxo-dG is formed in DNA. In some embodiments, 8-oxo-dG is formed in RNA. In some embodiments, 8-oxodG is found as a free nucleotide, 8-oxo-dGTP. In some embodiments, generation of 8-oxo-dG can result in an A > C mutation in DNA.

[0035] In some embodiments, ROS can generate lesions in NA. In some embodiments, ROS can generate lesions in NA bases. In some embodiments, ROS can generate lesions in DNA. In some embodiments, ROS can generate lesions in DNA bases. In some embodiments, ROS can generate lesions in RNA. In some embodiments, ROS can generate lesions in RNA bases. Other examples of base lesions generated by an interaction with ROS include but are not limited to 5,6-dihydroxythymine, 5-hydroxy-6-hydrothymine, thymine glycol, 5,6-dihydrothymine, 5- hydroxymethyluracil, 5-formyluracil, 5,6-dihydroxy-5,6-dihydrothymine, 5- hydroxymethylcytosine, 5-hydroxy-5-methyl-hydantoin, cytosine glycol, 5 -hydroxy cytosine, 5- hydroxy-6-hydrocytosine, trans-l-carbamoyl-2-oxo-4,5-dihydroxyimidazolidine, uracil glycol, 5-hydroxyuracil, 5,6-dihydroxyuracil, 5-hydroxy-6-uracil, 5 -hydroxy hydantoin, alloxan, 5,6-WSGR Docket No. 47697-746601 dihydrouracil, 8-hydroxyadenine, 4,6-diamino-5-formamidopyrimidine, 2-hydroxyadenine, 8- hydroxyguanine, 2,6-diamino-4-hydroxy-5-formamidopyrimidine, 6H,8H-3,4- dihydropyrimido[4,5-c][l,2]oxazin-7-one, N6-methoxy-2,6-diaminopurine (K), and oxazolone.

[0036] In some embodiments, base lesions can result from interaction of NA with hydroxyl radicals. In some embodiments, hydroxyl radicals (HO») can react with NA by addition to double bonds of NA bases, abstraction of an H atom from the methyl group of thymine, or abstraction of an H atom from the methyl group of each of the C-H bonds of 2’-deoxyribose. In some embodiments, addition to the C5-C6 double bonds of pyrimidines can lead to C5-OH or C6-OH adduct radicals. In some embodiments, H atom abstraction from thymine can result in an allyl radical. In some embodiments, pyrimidine radicals can be reduced or oxidized. In some embodiments, in the absence of oxygen, cytosine glycol or thymine glycol can be produced. In some embodiments, an allyl radical can yield 5-hydroxymethyluracil. In some embodiments, thymine peroxyl radicals can be reduced and then protonated to yield hydroxyhydroperoxides. In some embodiments, hydroxyhydroperoxides can decompose and yield one or more of thymine glycol, 5-hydroxymethyluracil, 5-formyluracil, or 5-hydroxy-5-methylhydantoin. In some embodiments, cytosine glycol can deaminate to yield one or more of uracil glycol, 5- hydroxycytosine, or 5-hydroxyuracil. In some embodiments, C5-OH adduct radicals can be reduced and then protonated.

[0037] In some embodiments, one or more of a non-canonical nucleotide, modified nucleotide, or base lesion as described above can be incorporated into DNA by DNA polymerase I. In some embodiments, one or more of a non-canonical nucleotide, modified nucleotide, or base lesion as described above can be incorporated into RNA by RNA polymerase. In some embodiments, a non-canonical nucleotide, a modified nucleotide, or a base lesion can be biotinylated.

[0038] In some embodiments, oxidative stress can result in non-Watson-Crick base pairing in DNA. In some embodiments, Watson-Crick base pairing refers to the canonical pairing of A:T and G:C. In some embodiments, oxidative stress can result in Hoogstein base pairing in DNA. In some embodiments, oxidative stress can result in Hoogstein base pairing in RNA. In some embodiments, Hoogstein base pairing can refer to non-Watson-Crick base pairing. In some embodiments, generation of 8-oxoguanine (8-oxoG) products by oxidative stress can lead to the base pairing of oxidized guanine with adenine to form a Hoogstein base pair. In some embodiments, formation of a Hoogstein base pair can lead to G:C and T:A transversion and can result in a point mutation. In some embodiments, Hoogstein base pairing can occur near the sites of mismatches, nicks, or lesions resulting from oxidative stress. In some embodiments,WSGR Docket No. 47697-746601Hoogstein base pairing can comprise a G: A base pair, an A:U base pair, a G:G base pair, or a C:C base pair.

[0039] Oxidative stress markers as described herein can occur at the site of oxidative stress. In some embodiments, one or more oxidative stress markers can occur 1 base pair, 2 base pairs, 3 base pairs, 4 base pairs, 5 base pairs, 6 base pairs, 7 base pairs, 8 base pairs, 9 base pairs, 10 base pairs, 11 base pairs, 12 base pairs, 13 base pairs, 14 base pairs, 15 base pairs, 16 base pairs, 17 base pairs, 18 base pairs, 19 base pairs, or 20 base pairs in the 3’ direction from a site of oxidative stress. In some embodiments, one or more oxidative stress markers can occur 1 base pair, 2 base pairs, 3 base pairs, 4 base pairs, 5 base pairs, 6 base pairs, 7 base pairs, 8 base pairs, 9 base pairs, 10 base pairs, 11 base pairs, 12 base pairs, 13 base pairs, 14 base pairs, 15 base pairs, 16 base pairs, 17 base pairs, 18 base pairs, 19 base pairs, or 20 base pairs in the 5’ direction from a site of oxidative stress.

[0040] In some embodiments, a nucleic acid as disclosed herein can comprise an oxidative stress marker. In some embodiments, an oxidative stress marker can occur in NA. In some embodiments, an oxidative stress marker can occur in DNA. In some embodiments, an oxidative stress marker can occur in RNA. In some embodiments, an oxidative stress marker can occur in cell-free DNA (cfDNA). In some embodiments, an oxidative stress marker can occur in host cfDNA (hcfDNA). In some embodiments, an oxidative stress marker can occur in microbial cfDNA (mcfDNA). In some embodiments, an oxidative stress marker can occur in cell-free RNA (cfRNA). In some embodiments, an oxidative stress marker can occur in host cfRNA (hcfRNA). In some embodiments, an oxidative stress marker can occur in microbial cfRNA (mcfRNA). In some embodiments, an oxidative stress marker can comprise one or more oxidative stress markers. In some embodiments, an oxidative stress marker can occur in a residue of a nucleic acid. In some embodiments, one or more oxidative stress markers can occur in 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 32%, 33%, 34%,35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43%, 44%, 45%, 46%, 47%, 48%, 49%, 50%,51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 66%,67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%,83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,99%, 100% of residues in a nucleic acid fragment. In some embodiments, one or more oxidative stress markers can occur in 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%,30%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43%, 44%, 45%,WSGR Docket No. 47697-74660146%, 47%, 48%, 49%, 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%,62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%,78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%,94%, 95%, 96%, 97%, 98%, 99%, 100% of residues in a cfNA fragment. In some embodiments, one or more oxidative stress markers can occur in 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%,27%, 28%, 29%, 30%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%,43%, 44%, 45%, 46%, 47%, 48%, 49%, 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%,59%, 60%, 61%, 62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%,75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%,91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 100% of residues in a cfDNA fragment. In some embodiments, one or more oxidative stress markers can occur in 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%,39%, 40%, 41%, 42%, 43%, 44%, 45%, 46%, 47%, 48%, 49%, 50%, 51%, 52%, 53%, 54%,55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%,71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%,87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 100% of residues in a cfRNA fragment. In some embodiments, one or more oxidative stress markers can occur in 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 32%, 33%, 34%,35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43%, 44%, 45%, 46%, 47%, 48%, 49%, 50%,51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 66%,67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%,83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,99%, 100% of residues in an mcfDNA fragment. In some embodiments, one or more oxidative stress markers can occur in 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%,30%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43%, 44%, 45%,46%, 47%, 48%, 49%, 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%,62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%,78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%,94%, 95%, 96%, 97%, 98%, 99%, 100% of residues in an hcfDNA fragment.Detection of oxidative stress markersWSGR Docket No. 47697-746601

[0041] Disclosed herein in some embodiments are methods and compositions for detecting oxidative stress markers. In some embodiments, a method of detecting an oxidative stress marker can comprise a sequencing to generate sequence reads. In some embodiments, sequence reads can comprise forward and reverse NA reads. In some embodiments, an oxidative stress marker can be detected by comparing forward and reverse NA reads covering a same locus to detect non-Watson-Crick base pairing, noncanonical base pairing, or Hoogstein base pairing. In some embodiments, forward and reverse reads can be aligned to a locus. In some embodiments, a different base call between forward reads at a locus and reverse reads at a locus can indicate non-Watson-Crick base pairing, noncanonical base pairing, or Hoogstein base pairing.

[0042] Disclosed herein in some embodiments are methods and compositions for analyzing sequencing data. In some embodiments, sequencing data can be analyzed with the use of machine learning algorithms. In some embodiments, machine learning algorithms can be utilized to detect noncanonical nucleotides, modified nucleotides, or base lesions. In some embodiments, machine learning algorithms can be utilized to detect Hoogstein base pairing or non-Watson- Crick base pairing.

[0043] Disclosed herein in some embodiments are methods and compositions for performing sequencing to detect oxidative stress markers. In some embodiments, sequencing to detect oxidative stress markers can comprise high-throughput sequencing. In some embodiments, high- throughput sequencing can comprise next-generation sequencing, next-next generation sequencing, third generation sequencing, or a combination thereof. In some embodiments, high- throughput sequencing can comprise sequencing by synthesis, nanopore sequencing, shotgun sequencing, metagenomic sequencing, or any combination thereof. In some embodiments, high- throughput sequencing can be utilized to indirectly detect modified nucleotides, non-canonical nucleotides, or base lesions through detection of changes in kinetics of reverse transcription reactions. In some embodiments, high-throughput sequencing can detect a NA methylation modification, a methylation derivative, a demethylation derivative, m6A modifications, 8-oxo- guanine and variants thereof, 7-cyano-7-deazaguanine, or any combination thereof. In some embodiments, nanopore sequencing can detect a nucleic acid modification by sensing a signal distortion as a nucleic acid passes through a nanopore sensor embedded within a charged membrane.

[0044] Disclosed herein in some embodiments are methods and compositions for detection of oxidative stress markers. In some embodiments, modified nucleotides or base lesions can be detected using the methods disclosed herein. In some embodiments, modified nucleotides or base lesions such as 8-oxoG can be recognized by antibodies. In some embodiments, a methodWSGR Docket No. 47697-746601 for detection and enrichment of sequences comprising 8-oxoG can utilize an 8-oxoG specific antibody which can be used to bind 8-oxoG within a sample of NA fragments. In some embodiments, these antibody -bound fragments can be enriched through binding to a solid support (e.g., bead, planar surface, slide). In some embodiments, these antibody-bound fragments can be enriched through binding to protein-G-coated magnetic beads. In some embodiments, these antibody -bound fragments can be enriched through binding to streptavidinbiotin beads. In some embodiments, the enriched NA can then be prepared for next-generation sequencing and alignment to a particular genome. In some embodiments, a method for detection and enrichment of sequences comprising 8-oxoG takes advantage of the tendency of 8-oxoG to become hyperoxidated in the presence of mild oxidants. Hyperoxidation of 8-oxoG causes it to become an acceptor for a biotin tag. In some embodiments, the biotin tag acts as an oxidative stress tag. In some embodiments, biotin-tagged NA can then be enriched through a biotinstreptavidin pull-down and subsequently sequenced. In some embodiments, mild oxidants include but are not limited to chlorine, compounds of chlorine such as calcium hypochloride, sodium hypochloride, ozone, and chlorine dioxide.

[0045] In some embodiments, a method for detection and enrichment of sequences comprising markers of oxidative stress uses enzymes. In some embodiments, the enzymes are endonucleases. In some embodiments, the endonucleases are repair endonucleases. Non-limiting examples of repair endonucleases includes endonuclease III (EndoIII), formamidopyrimidine DNA glycosylase (Fpg), uvrABC, T4 endonuclease V (T4endoV), uracil DNA glycosylase (Udg), exonuclease III (ExoIII), 3 -methyladenine DNA glycosylase II (AlkA), 8-oxoguanine DNA-glycosylase (hOGGl), endonuclease IV (EndoIV), endonuclease Ill-like protein 1 (NTH1), 3 -methyladenine DNA glycosylase (AlkD), or alkyladenine DNA glycosylase (hAAG). In some embodiments, the endonuclease is used to remove the marker of oxidative stress in the form of the removal of the associated base pair from a particular sequence. In some embodiments, following the removal of the base pair, the methods disclosed herein use an enzyme of the endonuclease IV family. In some embodiments, following the removal of the base pair, the methods disclosed herein use an apurinic / apyrimidinic endonuclease to create a strand break resulting in a single nucleotide gap. In some embodiments, the endonuclease is a bifunctional endonuclease. In some embodiments, the bifunctional endonuclease displays N- glycosylase and AP lyase activity (e.g., Endonuclease III (Nth) or formamidopyrimidine DNA glycosylase). In some embodiments, a method for detection and enrichment of sequences comprising 8-oxoG can utilize a specific glycosylase (e.g., formamidopyrimidine DNA glycosylase (FpG)). In some embodiments, the specific endonuclease is used to remove 8-oxoGWSGR Docket No. 47697-746601 from a particular sequence and then use apurinic / apyrimidinic endonuclease (APE1) to create a strand break resulting in a single nucleotide gap.

[0046] In some embodiments, the single nucleotide gap can then be refilled with a tagged guanine residue. In some embodiments, the tagged guanine acts as an oxidative stress tag. In some embodiments, the tagged guanine residue can serve as an adaptor for sequencing, for example through the addition of an oligonucleotide to the tagged guanine residue. In some embodiments, an example of such a method utilizes a Click reaction which takes advantage of the tagged guanine residue in the form of a Click-tagged guanine residue. In some cases, 8-oxoG can be excised via the base excision repair (BER) pathway. This process can occur on the order of minutes following generation of an 8-oxoG residue. The process can start with the excision of 8-oxoG by 8-oxoguanine NA glycosylase (OGGI), which leaves an apurinic site , which can then be processed into a single strand break via backbone incision of APE1. The single strand break can then remain or be repaired by the BER pathway.

[0047] In some embodiments, the methods disclosed herein comprise adding an oxidative stress tag. In some embodiments, the oxidative stress tag is a biotin tag. In some embodiments, the biotin tag may be used with streptavidin beads for enrichment or purification. In some embodiments, the oxidative stress tag is a His-tag. In some embodiments, the oxidative stress tag is a FLAG tag. In some embodiments, the oxidative stress tag is a HA tag. In some embodiments, the oxidative stress tag is a Myc tag. In some embodiments, the oxidative stress tag is a GST tag. In some embodiments, the oxidative stress tag is a fluorescence tag (e.g., Cy3, Cy5, Alexa Fluor, FITC). In some embodiments, the oxidative stress tag uses an azide-alkyne tag (e.g., CuAAC or SPAAC). In some embodiments, the oxidative stress tag is digoxigenin (DIG). In some embodiments, the oxidative stress tag is dinitrophenyl (DNP). In some embodiments, the oxidative stress tag is a SNAP -tag (6-benzylguanine-tag). In some embodiments, the oxidative stress tag is a CLIP -tag (02-benzylcytosine-tag). In some embodiments, the oxidative stress tag is a tagged guanine. In some embodiments, the tagged guanine can be detected using sequencing. As a non-limiting example, the tagged guanine can act as an adapter for sequencing. In some embodiments, the oxidative stress tag is added enzymatically. In some embodiments, the oxidative stress tag is added using a repair endonuclease. In some embodiments, the oxidative stress tag is added at a site of oxidative stress. In some embodiments, the oxidative stress tag is added near a site of oxidative stress. In some embodiments, the oxidative stress tag is added 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 base pairs in the 3' direction from the site of oxidative stress. In some embodiments, the oxidative stress tag is added 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 base pairs in the 5' direction from the site of oxidative stress.WSGR Docket No. 47697-746601In some embodiments, the oxidative stress tag is used for enrichment. In some embodiments, the oxidative stress tag is used for purification. In some embodiments, the oxidative stress tag is used for detection.

[0048] Disclosed herein in some embodiments are methods and compositions for assays to detect single or double strand breaks. In some embodiments, single cell gel electrophoresis (SCGE, also known as the comet assay) can be used to detect single or double strand breaks such as those generated by oxidative stress or resulting from pathways which repair oxidative stress damage and generate single or double strand break intermediates. In some embodiments, alkaline denaturation assays can be used to detect single or double strand breaks. In some embodiments, neutral electrophoresis assays can be used to detect double strand breaks. In some embodiments, non-Watson-Crick base pairing and Hoogstein base pairing resulting from oxidative stress can be detected using a variety of methods including but not limited to Hoog- finder, multidimensional dynamic nuclear polarization-enhanced solid-state nuclear magnetic resonance (NMR) spectroscopy, and NMR relaxation dispersion spectroscopy.

[0049] Disclosed herein in some embodiments are methods and compositions for detection of oxidative stress damage or markers through binding reactions. In some embodiments, oxidative stress damage in NA can be detected through a binding reaction. In some embodiments, a binding reaction can comprise a chemical reagent. In some embodiments, a binding reaction can comprise a binding reagent. In some embodiments, a chemical reagent or a binding reagent can bind an oxidative stress marker. In some embodiments, a binding agent can comprise an antibody, an antibody fragment, or a combination thereof. In some embodiments, an antibody or antibody fragment can bind to a noncanonical or modified base or a base lesion. In some embodiments, an antibody or an antibody fragment can bind to 8-hydroxydeoxyguanosine, 8- hydroxyguanine, 8-hydroxy 2-deoxyguanosine, thymine glycol, 5-hydroxymethyluracil, formylamidopyrimidine, or 8-hydroxydeoxyadenine. In some embodiments, an antibody or an antibody fragment can bind to 5,6-dihydroxythymine, 5-hydroxy-6-hydrothymine, thymine glycol, 5,6-dihydrothymine, 5-hydroxymethyluracil, 5-formyluracil, 5,6-dihydroxy-5,6- dihydrothymine, 5-hydroxymethylcytosine, 5-hydroxy-5-methyl-hydantoin, cytosine glycol, 5- hydroxycytosine, 5-hydroxy-6-hydrocytosine, trans-l-carbamoyl-2-oxo-4,5- dihydroxyimidazolidine, uracil glycol, 5-hydroxyuracil, 5,6-dihydroxyuracil, 5-hydroxy-6- uracil, 5 -hydroxy hydantoin, alloxan, 5,6-dihydrouracil, 8-hydroxyadenine, 4,6-diamino-5- formamidopyrimidine, 2-hydroxyadenine, 8 -hydroxy guanine, 2,6-diamino-4-hydroxy-5- formamidopyrimidine, 6H,8H-3,4-dihydropyrimido[4,5-c][l,2]oxazin-7-one, N6-methoxy-2,6- diaminopurine (K), or oxazolone. In some embodiments, an antibody or an antibody fragmentWSGR Docket No. 47697-746601 can bind to 8-oxo-G, 8-OH-dG, or 8-oxo-dG. In some embodiments, a binding agent can comprise a NA binding domain. In some embodiments, a binding agent can comprise a zinc- finger domain. In some embodiments, a binding agent can comprise a protein. In some embodiments, a binding agent can comprise an antibody. In some embodiments, a binding agent can comprise a fragment of an antibody. In some embodiments, a binding agent can comprise a functionally active fragment of an antibody. In some embodiments, a binding agent can comprise a protein. In some embodiments, a protein can comprise a ligase. In some embodiments, a binding agent can comprise an aptamer. In some embodiments, an aptamer can comprise an oligonucleotide. In some embodiments, an aptamer can comprise DNA or RNA. In some embodiments, an aptamer can comprise DNA. In some embodiments, an aptamer can comprise RNA.

[0050] Disclosed herein in some embodiments are methods and compositions for chemical detection methods of oxidative stress markers. In some embodiments, chemical detection methods can be utilized to detect or quantify the presence of modified nucleotides or base lesions in mcfNA. In some embodiments, chemical reagents can be utilized which are capable of labeling modified nucleotides. In some embodiments, chemical reagents can target certain functionalities in modified nucleotides. In some cases, the target of a chemical reagent is present in a modified nucleotide and not in a canonical nucleotide. In some embodiments, chemical detection of modified nucleotides via chemical reagents can be combined with primer extension assays or sequencing approaches. In some embodiments, abasic sites can be detected using chemical reagents. In some embodiments, a chemical reagent used to detect abasic sites can comprise ARP. In some embodiments, following treatment of NA comprising abasic sites with ARP, abasic sites can be tagged with a biotin residue. In some embodiments, biotinylated abasic sites can then be detected using standard methods such as an ELISA or ELISA-like assay. In some embodiments, ELISA assays or ELISA-like assays can utilize an avidin-biotin complex conjugated with horseradish peroxidase or an alkali phosphatase indicator system. In some embodiments, bisulfite treatment can be used to identify methylated cytosine residues. In some embodiments, methylation of cytosine C5 decreases the reactivity of cytosine with bisulfite while cytosine C6 readily reacts with bisulfite. In some embodiments, bisulfite and mock treated samples can be compared in order to locate 5 -methylated cytosines. In some embodiments, bisulfite treated 5-methylated cytosines continue to pair with guanosine. In some embodiments, bisulfite treated C6 cytosines are deaminated into uracil and pair with adenosine. In some embodiments, bisulfite treatment can be used to identify 5-hydroxymethylcytosine (hm5C), 5- formylcytosine (f5C) or 5-carboxy cytosine (ca5C) residues. In some embodiments, comparisonWSGR Docket No. 47697-746601 of oxidized and non-oxidized samples can allow for identification of modified residues. In some embodiments, additional methods for detection of oxidative stress markers can include but are not limited to immunofluorescence assays, ELISA assays, ELISA-like assays, immunohistochemistry assays, Western blot assays, immunoprecipitation assays, radioimmunoassays, or any variation or combination thereof.

[0051] As a non-limiting example, a sample comprising nucleic acids is contacted with a detection agent specific for markers of oxidative stress. When the detection agent binds to the marker for oxidative stress, the nucleic acids with oxidative stress are separated from the nucleic acids without oxidative stress. The sample may be a sample from a human. The sample from the human may be a biofluid sample. The biofluid sample may be a blood sample. The blood sample may be processed to a plasma sample. The blood sample may be processed to a serum sample. The nucleic acids may be DNA. The nucleic acids may be RNA. The nucleic acids may be a combination of DNA and RNA. The nucleic acids may be cell-free nucleic acids. The cell-free nucleic acids may be cfDNA. The cell-free nucleic acids may be cfRNA. The cell-free nucleic acids may be a combination of cfDNA and cfRNA. The nucleic acids may be from the human. The nucleic acids may be from microbes. The nucleic acids may be from a combination of the human and microbes. The detection agent may be an aptamer, an antibody, an antigen binding fragment, an oligonucleotide, or any combination thereof. The marker of oxidative stress may be a guanine damaged by oxidative stress. In some embodiments, the guanine damaged by oxidative stress results in the conversion of a guanine base to 8-oxo-7,8-dihydroguanine (8- oxoG), 8-hydroxyguanine (8-OH-dG), 8-hydroxy-2’ -deoxyguanosine (8-OH-dG or 8-oxo-dG), 7,8-dihydro-8-oxoguanine, or 8-oxoguanine (8-oxodG or 8-oxoG). In some embodiments, the conversion of the guanine base is in DNA. In some embodiments, the conversion of the guanine base is in RNA. In some embodiments, the conversion of the guanine base is in found as a free nucleotide. FIG. 6 provides a non-limiting overview of this procedure.

[0052] As shown in FIG. 6, there is a mix of nucleic acid fragments with and without markers of oxidative stress. These fragments are found in a sample (e.g., a biofluid sample). The sample may be from a host. The nucleic acids may comprise DNA, RNA, or both. The nucleic acids may be cell-free nucleic acids (e.g., cfDNA, cfRNA, or both). The nucleic acids may be from a host. The nucleic acids may be from a host and microbes. The sample is then contacted with an agent capable of detecting the markers of oxidative stress. The agent may be a chemical agent, an aptamer, an antibody, an antigen binding fragment, an oligonucleotide, or any combination thereof. The agent may bind with the marker of oxidative stress. The marker of oxidative stress may be a modified guanine. The modified guanine may be 8-oxo-7,8-WSGR Docket No. 47697-746601 dihydroguanine (8-oxoG), 8-hydroxyguanine (8-OH-dG), 8 -hydroxy-2’ -deoxy guanosine (8-OH- dG or 8-oxo-dG), 7,8-dihydro-8-oxoguanine, or 8-oxoguanine (8-oxodG or 8-oxoG). Once the oxidative stress marker is detected by the agent, the nucleic acid fragments with the oxidative stress marker may be able to be separated from the nucleic acid fragments that do not have markers of oxidative stress. The nucleic acid fragments with and without markers of oxidative stress may be able to be separated using a solid support (e.g., a bead). In this non-limiting example, the nucleic acid fragments with the markers of oxidative stress are bound to the sold support while the nucleic acid fragments without markers of oxidative stress remain unbound. These unbound nucleic acid fragments without markers of oxidative stress may be collected as flow-through. The bound nucleic acid fragments with markers of oxidative stress may be eluted from the solid support and collected in an elution.Processing of oxidative stress markers

[0053] Disclosed herein in some embodiments are methods and compositions for detection of oxidative damage or oxidative stress markers in a nucleic acid sample. In some embodiments, the number, variety, diversity, or distribution of oxidative stress markers can be detected or quantified in a nucleic acid sample. In some embodiments, a nucleic acid sample can comprise host NA and microbial NA. In some embodiments, a nucleic acid sample can comprise cell-free NA (cfNA). In some embodiments, cfNA in a nucleic acid sample can originate from host NA. In some embodiments, cfNA originating from a host can result from cell apoptosis releasing NA fragments along with cellular debris. In some embodiments, cfNA originating from host NA can result from nuclease-driven fragmentation of host NA. cfNA in a nucleic acid sample can comprise microbe cell-free NA (mcfNA). In some embodiments, mcfNA can result from an immune response responding to the presence of a microbe in a host. In some embodiments, mcfNA can result from a phagocyte phagocytosing a microbe and destroying said microbe. In some embodiments, a phagocyte can utilize oxidative stress to damage a microbe. In some embodiments, oxidative stress imparted upon a microbe via an immune system response can generate oxidative stress markers in mcfDNA. In some embodiments, mcfNA can comprise an increased number, variety, diversity, or distribution of oxidative stress markers relative to host cfNA.

[0054] Disclosed herein in some embodiments are methods and compositions for processing of mcfNA in a nucleic acid sample. In some embodiments, the processing can comprise providing a sample comprising cfNA. In some embodiments, the processing can comprise detecting of one or more oxidative stress markers. In some embodiments, the processing can comprise conducting a NA library preparation. In some embodiments, NA library preparationWSGR Docket No. 47697-746601 can be utilized to enrich a nucleic acid sample for NA comprising one or more oxidative stress markers. In some embodiments, the processing can comprise any combination of the processes disclosed herein and variations thereof. In some embodiments, oxidative stress markers detected in the processing of an mcfNA sample can comprise a nick in a strand of NA, a gap in a strand of NA, or a substitution of a nucleotide in NA. In some embodiments, a substitution in a nucleotide of NA can comprise an 8-hydroxydeoxyguanosine, an 8-hydroxyguanine, an 8- hydroxy 2-deoxyguanosine, a thymine glycol, a 5-hydroxymethyluracil, a formylamidopyrimidine, a 8-hydroxydeoxyadenine, and any combination thereof. In some embodiments, a substitution in a nucleotide of NA can comprise 8-hydroxydeoxyguanosine, 8- hydroxyguanine, 8-hydroxy 2-deoxyguanosine, thymine glycol, 5-hydroxymethyluracil, formylamidopyrimidine, 8-hydroxydeoxyadenine, or any combination thereof. In some embodiments, a substitution in a nucleotide of NA can comprise 5,6-dihydroxythymine, 5- hydroxy-6-hydrothymine, thymine glycol, 5,6-dihydrothymine, 5-hydroxymethyluracil, 5- formyluracil, 5,6-dihydroxy-5,6-dihydrothymine, 5-hydroxymethylcytosine, 5-hydroxy-5- methyl-hydantoin, cytosine glycol, 5 -hydroxy cytosine, 5-hydroxy-6-hydrocytosine, trans-1- carbamoyl-2-oxo-4,5-dihydroxyimidazolidine, uracil glycol, 5-hydroxyuracil, 5,6- dihydroxyuracil, 5-hydroxy-6-uracil, 5-hydroxyhydantoin, alloxan, 5,6-dihydrouracil, 8- hydroxyadenine, 4,6-diamino-5-formamidopyrimidine, 2-hydroxyadenine, 8-hydroxyguanine, 2,6-diamino-4-hydroxy-5-formamidopyrimidine, 6H,8H-3,4-dihydropyrimido[4,5-c][l,2]oxazin- 7-one, N6-methoxy-2,6-diaminopurine (K), oxazolone, an 8-hydroxydeoxyguanosine, an 8- hydroxyguanine, an 8-hydroxy 2-deoxyguanosine, a thymine glycol, a 5-hydroxymethyluracil, a formylamidopyrimidine, a 8-hydroxydeoxyadenine, an 8-oxo-adenine (8-oxoA), an isoguanine, a formamidopyrimidine-A (FapyA), a 5 '-Phosphoglycolate (5'-PG), a 5' -Hydroxyl (5' -OH), a 5' -Phosphate (5' -P), a 5' -Aldehyde, a 5' -Deoxyribonolactone-Derived Termini, or any combination thereof. In some embodiments, a substitution in a nucleotide of NA can comprise 8- oxo-G, 8-OH-dG, or 8-oxo-dG. In some embodiments, a substitution in a nucleotide of NA can comprise any combination of any one of the modified nucleotides, noncanonical nucleotides, or base lesions disclosed herein. In some embodiments, an oxidative stress marker detected in the processing of an mcfNA sample can comprise a non-Watson-Crick base pair or a Hoogstein base pair. In some embodiments, processing of mcfNA can comprise detecting cfNA comprising an oxidative stress marker. In some embodiments, processing of mcfNA can comprise detecting or enriching for oxidative stress markers prior to sequencing. In some embodiments, processing of mcfNA can comprise sequencing cfNA before detecting for oxidative stress markers. In some embodiments, detecting can comprise quantifying or analyzing oxidative stress markers. In someWSGR Docket No. 47697-746601 embodiments, processing of mcfNA can comprise sequencing cfNA to generate sequence reads. In some embodiments, sequencing can comprise next-generation sequencing. In some embodiments, sequencing can comprise next-next-generation sequencing. In some embodiments, sequencing can comprise high-throughput sequencing. In some embodiments, high-throughput sequencing can comprise sequencing by synthesis. In some embodiments, high-throughput sequencing can comprise nanopore sequencing. In some embodiments, detecting can comprise binding an oxidative stress marker with a binding agent, a protein, an oligonucleotide, or a chemical reagent. In some embodiments, a protein can comprise a ligase, an antibody, an antibody fragment, a functionally active fragment of an antibody, or any combination thereof. In some embodiments, a binding agent can comprise a NA binding domain. In some embodiments, a NA binding domain can comprise a zinc-finger domain. In some embodiments, a NA binding domain can comprise a TALEN. In some embodiments, a binding agent can comprise an aptamer. In some embodiments, an aptamer can comprise an oligonucleotide. In some embodiments, an aptamer can comprise DNA or RNA. In some embodiments, detecting can comprise an enzyme linked immunosorbent assay (ELISA). In some embodiments, detecting can comprise an immunofluorescence assay. In some embodiments, processing of mcfNA can comprise any combination of the detection or enrichment methods or techniques disclosed herein. The methods disclosed herein can be used to detect any combination of the oxidative stress markers disclosed herein.

[0055] Disclosed herein in some embodiments are methods and compositions for detecting which utilize computers and computer processes. In some embodiments, detecting can comprise using a computer readable memory communicatively coupled to a processor to run an algorithm to detect a sequence read indicative of one or more oxidative stress markers in a set of sequence reads. In some embodiments, an algorithm can be configured to detect noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing. In some embodiments, an algorithm can utilize machine learning algorithms or models. In some embodiments, an algorithm can be configured for the detection of a Hoogstein base pair, a noncanonical nucleotide, a modified nucleotide, a base lesion, a mis-match between a forward read and a reverse read at a locus, or any combination thereof. In some embodiments, a mismatch can comprise a non-Watson-Crick base pairing. In some embodiments, a mis-match can comprise a Hoogstein base pairing. In some embodiments, an algorithm can be configured to detect a non-canonical base pairing, a non-Watson-Crick base pairing, or a Hoogstein base pairing. In some embodiments, an algorithm can be configured to detect a non-canonical nucleotide, a modified nucleotide, or a base lesion and output a Hoogstein base pairing.WSGR Docket No. 47697-746601Analysis of oxidative stress markers

[0056] Disclosed herein in some embodiments are methods and compositions for analysis of oxidative stress markers. In some embodiments, analysis of oxidative stress markers can be used to determine an infection status. In some embodiments, the methods disclosed herein can be utilized to determine an infection status based at least in part on microbial cell-free nucleic acids (mcfNA). In some embodiments, mcfNA can be quantified in order to determine an infection status. In some embodiments, mcfNA can be sequenced in order to determine an infection status. In some embodiments, the methods disclosed herein can be utilized to determine an infection status based at least in part on mcfDNA. In some embodiments, mcfDNA can be quantified in order to determine an infection status. In some embodiments, mcfDNA can be sequenced in order to determine an infection status. In some embodiments, the methods disclosed herein can be utilized to determine an infection status based at least in part on mcfRNA. In some embodiments, mcfRNA can be quantified in order to determine an infection status. In some embodiments, mcfRNA can be sequenced in order to determine an infection status. In some embodiments, a computer implemented algorithm can be utilized in order to determine an infection status. In some embodiments, a computer implemented algorithm can utilize machine learning. In some embodiments, a computer implemented algorithm can comprise a machine learning model. In some embodiments, a machine learning model can comprise at least one of a logistic regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method, or any combination thereof. In some embodiments, a neural network can comprise at least one of a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, or a generative adversarial network.

[0057] Disclosed herein in some embodiments are methods and compositions for nucleic acid library preparation (e.g., DNA library, RNA library). In some embodiments, DNA library preparation can be utilized in order to enrich a nucleic acid sample for DNA comprising an oxidative stress marker. In some embodiments, enriching a nucleic acid sample can comprise enriching for mcfDNA derived from an infectious agent. In some embodiments, RNA library preparation can be utilized in order to enrich a nucleic acid sample for RNA comprising an oxidative stress marker. In some embodiments, enriching a nucleic acid sample can comprise enriching for mcfRNA derived from an infectious agent.

[0058] Disclosed herein in some embodiments are methods and compositions for differentiation between a commensal microbe and an infectious microbe. In some embodiments, the differentiation can comprise quantifying a number of reads comprising one or more oxidativeWSGR Docket No. 47697-746601 stress markers. In some embodiments, mcfNA obtained from an infectious microbe can comprise a higher proportion, quantity, variety, or distribution of oxidative stress markers as compared to mcfNA obtained from a commensal microbe. In some embodiments, analysis of oxidative stress markers in mcfNA can be utilized in order to determine the quality of an immune response against a pathogen or an infectious microbe. In some embodiments, the quality of an immune response can be compared between a series of samples. In some embodiments, the series of samples can be collected over a time period of days, weeks, or months. In some embodiments, an increase in quantity, distribution, or variety of oxidative stress markers in mcfDNA can indicate an increase in immune response. In some embodiments, a decrease in quantity, distribution, or variety of oxidative stress markers in mcfNA can indicate a decrease in immune response. In some embodiments, determination of an infection status can comprise determining that an infection is active or latent. In some embodiments, commensal microbes can include but are not limited to Bacteroides fragilis, Lactobacillus acidophilus, Bifidobacterium bifidum, Escherichia coli (non-pathogenic strains), Staphylococcus epidermidis, Streptococcus salivarius, Propionibacterium acnes, Candida albicans (under normal conditions), Enterococcus faecalis, Clostridium difficile (non-toxigenic strains), Rothia mucilaginosa, Fusobacterium nucleatum, Peptostreptococcus anaerobius, and Prevotella melaninogenica.

[0059] Disclosed herein in some embodiments are methods and compositions for treatment of a subject for an infection. In some embodiments, treatment of a subject can comprise diagnosing an infection at least in part using any one of the methods of detecting mcfNA as disclosed herein. In some embodiments, treatment of a subject can comprise administering a therapy to treat an infection. In some embodiments, a therapy can comprise one or more of an antibiotic, an antiviral, an antifungal, an antiparasitic, an immunotherapy, a vaccine, an antimicrobial, a probiotic, a supportive therapy, and any combination thereof. In some embodiments, methods disclosed herein can utilize a non-transitory computer-readable storage medium comprising a set of instructions recorded thereon which, when executed by a processor, cause the processor to implement a method for detecting microbial cell-free NA (mcfNA).

[0060] Disclosed herein in some embodiments are methods and compositions for assessing stress signals. In some embodiments, the stress signal can be in a subject (e.g., a human or a plant). In some embodiments, the stress signal can be from a patient. In some embodiments, the stress signal may be associated with a disease or condition of the patient. Non-limiting examples of a disease or condition of the patient include infection, cancer (e.g., lung cancer, breast cancer, colon cancer, brain cancer, liver cancer, pancreatic cancer, or skin cancer), autoimmune condition, chronic condition, or an acute condition. When the patient experiences the disease orWSGR Docket No. 47697-746601 condition, the patient may produce reactive oxygen species. In some embodiments, the reactive oxygen species are present in the mitochondria. In some embodiments, the ROS impacts mitochondrial nucleic acids. In some embodiments, the impacts of ROS on the mitochondrial nucleic acids results in mitochondrial nucleic acids with markers of oxidative stress. In some embodiments, the markers of oxidative stress on the mitochondrial nucleic acids are detected using the methods and compositions described herein. In some embodiments, the stress signal can be associated with the mitochondria (e.g., the mitochondria or the subject or patient). In some embodiments, the stress signal can be from a plant (e.g., a plant as a part of a crop or research). In some embodiments, the stress signal can be associated with the mitochondria (e.g., the mitochondria of the subject or plant). As a non-limiting example, a plant may be stressed from adverse environmental conditions or pathogens. Non-limiting examples of adverse environmental conditions include high-heat, drought, flooding, freezing, and high salinity. When the plant is stressed by such factors the plant may begin to produce reactive oxygen species (ROS). The ROS may be in the mitochondria. The ROS may be in other areas of the plant. The ROS may cause oxidative damage of the nucleic acids in the plant (e.g., plant nucleic acids, pathogen (microbial) nucleic acids). The oxidative damage to the nucleic acids may be detected by the methods and compositions described herein.Nucleic acid samples

[0061] Disclosed herein in some embodiments are methods and compositions comprising samples. In some embodiments, the sample comprises an initial sample. In some embodiments, the sample comprises a raw biological sample. In some embodiments, the sample comprises a biological sample. In some embodiments, biological sample can comprise nucleic acids. In some embodiments, nucleic acids can comprise DNA. In some embodiments, nucleic acids can comprise RNA. In some embodiments, nucleic acids can comprise cell-free nucleic acids. In some embodiments, cell-free nucleic acids can comprise cell-free DNA (cfDNA). In some embodiments, cfDNA can comprise microbial cfDNA (mcfDNA). In some embodiments, cfDNA can comprise plant cfDNA. In some embodiments, cfDNA can comprise host cfDNA (hcfDNA). In some embodiments, cell-free nucleic acids can comprise cell-free RNA (cfRNA). In some embodiments, cfRNA can comprise microbial cfRNA (mcfRNA). In some embodiments, cfDNA can comprise plant cfRNA. In some embodiments, cfRNA can comprise host cfRNA (hcfRNA).

[0062] Disclosed herein in some embodiments are methods and compositions for the detection and genetic analysis of various chemical and structural forms of nucleic acid found in a biological sample. In some embodiments, the biological sample is derived from a subject. InWSGR Docket No. 47697-746601 some embodiments, the subject is a human. In some embodiments, the subject is a plant. In some embodiments, detection of various chemical and structural forms of nucleic acid found in a biological sample can be concurrent, consecutive, or independent. In some embodiments, nucleic acids can include various chemical forms of a DNA molecule as well as various chemical forms of an RNA molecule. In some embodiments, nucleic acids can also include different structural forms of DNA and RNA found in a sample. In some embodiments, nucleic acids can comprise cell-free nucleic acids. In some embodiments, cell-free nucleic acids can comprise cell-free DNA (cfDNA). In some embodiments, cfDNA can comprise microbial cfDNA (mcfDNA). In some embodiments, cfDNA can comprise host cfDNA (hcfDNA).

[0063] In some embodiments, the nucleic acids can be located outside of cells. In some cases, the nucleic acids are derived from viral particles or spores. In some cases, the nucleic acids are cell-free nucleic acids. In some cases, the nucleic acids are circulating cell-free nucleic acids. In some embodiments, nucleic acids can be any type of nucleic acid including but not limited to: double-stranded (ds) nucleic acids, single stranded (ss) nucleic acids, DNA, RNA, cDNA, mRNA, cRNA, tRNA, ribosomal RNA, dsDNA, ssDNA, miRNA, siRNA, circulating nucleic acids, circulating cell-free nucleic acids, circulating DNA, circulating RNA, cell-free nucleic acids, cell-free DNA, cell-free RNA, circulating cell-free DNA, cell-free dsDNA, cell- free ssDNA, circulating cell-free RNA, genomic DNA, exosomes, cell-free pathogen nucleic acids, circulating microbe or pathogen nucleic acids, mitochondrial nucleic acids, non- mitochondrial nucleic acids, nuclear DNA, nuclear RNA, chromosomal DNA, circulating tumor DNA, circulating tumor RNA, circular nucleic acids, circular DNA, circular RNA, circular single-stranded DNA, circular double-stranded DNA, linear nucleic acids, linear DNA, linear RNA, linear single-stranded DNA, linear double-stranded DNA, plasmids, bacterial nucleic acids, fungal nucleic acids, parasite nucleic acids, viral nucleic acids, cell-free bacterial nucleic acids, cell-free fungal nucleic acids, cell-free parasite nucleic acids, viral particle- associated nucleic acids, mitochondrial DNA, intercellular signal nucleic acids, exogenous nucleic acids, DNA enzymes, RNA enzymes, food-derived nucleic acids, any metabolic form of nucleic acidbased therapeutics, or any combination thereof. In some embodiments, nucleic acids can be nucleic acids derived from microbes or pathogens including but not limited to viruses, bacteria, fungi, parasites, and any other microbe, particularly an infectious microbe or potentially infectious microbe. In some embodiments, nucleic acids can derive from archaea, bacteria, fungi, molds, prokaryotes, protists, protozoa, eukaryotes, or viruses. In some embodiments, nucleic acids can be derived directly from the subject, as opposed to a microbe or pathogen. In some embodiments, the subject can have, or is suspected of having, a pathogenic infection. InWSGR Docket No. 47697-746601 some embodiments, the sample from the host subject comprises host DNA and RNA, as well as DNA and RNA from a pathogen or microbe which can be in the chemical or structural form of ssRNA, ssDNA, dsRNA, or dsDNA.

[0064] Disclosed herein in some embodiments are methods and compositions for generation of a single-stranded nucleic acid library. In some embodiments, the single-stranded methods provided by the present disclosure can be applied for more efficient processing of shorter nucleic acid fragments as well as less biased processing of nucleic acids in respect to any of their properties (e.g., nucleic acid length, sequence, GC content, secondary or any higher order structure, degree of damage (such as nicking or the presence of gaps), or degree of chemical damage). In some embodiments, the single-stranded nucleic acid methods, composition, systems, or kits can be applied for a microbe or pathogen identification in samples that contain circulating or cell-free nucleic acids or highly degraded or low-quality samples such as ancient, formalin-fixed paraffin-embedded (FFPE) samples, or samples which have undergone many freeze-thaw cycles. In some embodiments, the present disclosure provides for analysis of both double-stranded and single-stranded nucleic acids in a sample. In some embodiments, doublestranded nucleic acids are denatured to form single-stranded nucleic acids. In some embodiments, the sample can comprise cell-free DNA and RNA (e.g., RNA or capsid-protected RNA). In such cases, the method can comprise obtaining denatured cell-free DNA as described herein, while also capturing RNA sequences. Since RNA is less stable than DNA, it can be desirable to convert the RNA to DNA using a reverse transcriptase, as further described herein. In some embodiments, as a result of this process, the sample can be enriched for microbial cell- free DNA using the dummy oligomer processes described herein, while still comprising cDNA derived from the RNA in the sample. In some embodiments, heat denaturation of samples reduces RNA fragment recovery in the library generation process. In some embodiments, heat in the presence of divalent cations (Ca2+or Mg2+) can cause strand cleavage of RNA molecules. In some embodiments, a sample comprising cell-free or viral particle protected RNA is incubated with reverse transcriptase. In some embodiments, the cell-free RNA is converted to cDNA which is stable in subsequent heat denaturation steps. In some embodiments, the heat denaturation releases particle protected RNA. In some embodiments, a second incubation with reverse transcriptase converts the released nucleic acids to cDNA. In some aspects of the methods disclosed herein, a polyadenylation process occurs before incubation with the reverse transcriptase. In some aspects of the methods disclosed herein, a thermolabile or deactivatable proteinase K is used. In some aspects, salts are removed or reduced to destabilize dsDNA. In some embodiments, in addition to reducing environmental contamination, protease incubationWSGR Docket No. 47697-746601 can reduce inhibitors of the direct to library process. Incubating with a protease can include any protease known in art including but not limited to proteinase K. In some embodiments, in the presence of detergents and shearing forces, proteases such as proteinase K can release nucleic acids present in viral capsids as well as bacterial and eukaryotic cells. In some embodiments, the released nucleic acids can be accessible for utilization in downstream library preparation. In some embodiments, the methods disclosed herein include conversion of cfRNA to cDNA prior to incubation with a protease, particularly proteinase K, and heat denaturation. In some embodiments, the protease and denaturation can be followed by an additional process to capture newly released RNA along with cfDNA and cDNA present in the sample. In some embodiments, an additional process can comprise A-tailing of the nucleic acid or a second round of cDNA synthesis. In some embodiments, an additional process can enable capture of particle protected and cell-free RNA in the same protocol.

[0065] Disclosed herein in some embodiments are methods and compositions for obtaining nucleic acid samples. In some embodiments, nucleic acid samples can be obtained from an organism including but not limited to a human, a dog, a cat, a cow, a pig, a sheep, a rat, a mouse, a monkey, a horse, or a plant. In some embodiments, nucleic acid samples can comprise microbial nucleic acids. In some embodiments, microbial nucleic acids can comprise DNA or RNA. In some embodiments, microbial nucleic acids can comprise microbial cell-free DNA (mcfDNA). In some embodiments, a sample such as human blood can comprise circulating mcfDNA. In some embodiments, mcfDNA in human blood can originate from bacteria. In some embodiments, mcfDNA can be detected in organisms that have been exposed to one or more infectious disease or one or more non-infectious diseases. In some embodiments, mcfDNA can be detected in healthy individuals. As aspect of the present disclosure is the detection of mcfDNA as a biomarker of infection. In some embodiments, mcfDNA can comprise fragments of double-stranded DNA. In some embodiments, fragments of double-stranded DNA can be approximately less than 100 bp, about 100 bp, about 110 bp, about 120 bp, about 130 bp, about 140 bp, about 150 bp, about 160 bp, about 170 bp, about 180 bp, about 190 bp, about 200 bp, or more than 200 bp long. In some embodiments, mcfDNA can be present in blood, plasma, serum, saliva, or other bodily fluids. In some embodiments, mcfDNA is not encapsulated by cells. In some embodiments, mcfDNA can be associated with communicable or non-communicable diseases. In some embodiments, mcfDNA can be associated with a range of diseases and conditions, including but not limited to inflammatory bowel disease (IBD), Kawasaki disease (KD), human immunodeficiency virus (HIV), cardiovascular diseases (CVD), cystic fibrosisWSGR Docket No. 47697-746601(CF), and pneumonia, sepsis, cancer, gastric cancer (GC), hepatocellular carcinoma (HCC), and melanoma.

[0066] Disclosed herein in some embodiments are methods and compositions for sequencing or quantifying mcfDNA before or after detection for or enrichment for oxidative stress markers. In some embodiments, mcfDNA can be sequenced and quantified before or after detection of oxidative stress markers. In some embodiments, mcfDNA comprising oxidative stress markers can be detected and enriched for prior to sequencing and quantification of the mcfDNA. In some embodiments, mcfDNA is obtained from a patient or a subject. In some embodiments, the patient or subject is human. In some embodiments, mcfDNA can be quantified in a patient sample in molecules / pL. In some embodiments, mcfDNA can be quantified in a patient blood plasma sample. In some embodiments, microbial taxa comprised within a sample can be identified using the methods of the present disclosure. In some embodiments, mcfDNA can comprise an increased amount of oxidative stress markers as compared to cfDNA not derived from a microbe.

[0067] Sequencing as described herein can be by any method known in the art. Sequencing methods include, but are not limited to, Maxam-Gilbert sequencing-based techniques, chain- termination-based techniques, shotgun sequencing, bridge PCR sequencing, single-molecule real-time sequencing, ion semiconductor sequencing (e.g., Ion Torrent sequencing), nanopore sequencing, pyrosequencing (454), sequencing by synthesis, sequencing by ligation (SOLiD sequencing), sequencing by electron microscopy, dideoxy sequencing reactions (Sanger method), massively parallel sequencing, polony sequencing, DNA nanoball sequencing or any variation thereof. The term “Next Generation Sequencing (NGS)” herein refers to sequencing methods that allow for massively parallel sequencing of nucleic acid molecules during which a plurality, e.g., millions, of nucleic acid fragments from a single sample or from multiple different samples are sequenced simultaneously. Non-limiting examples of NGS include sequencing-by-synthesis, sequencing-by-ligation, real-time sequencing, and nanopore sequencing. In some embodiments, sequencing involves hybridizing a primer to the template to form a template / primer duplex, contacting the duplex with a polymerase enzyme in the presence of detectably labeled or unlabeled nucleotides under conditions that permit the polymerase to add labeled or unlabeled nucleotides to the primer in a template-dependent manner, detecting a signal from the incorporated labeled nucleotide or detecting a signal resulting from the process of incorporating labeled or unlabeled nucleotide (e.g., proton release), and sequentially repeating the contacting or detecting at least once, wherein sequential detection of incorporated labeled or unlabeled nucleotide determines the sequence of the nucleic acid. In some embodiments, exemplaryWSGR Docket No. 47697-746601 detectable labels include radiolabels, fluorescent labels, protein labels, dye labels, and enzymatic labels. In some embodiments, the detectable label can be an optically detectable label, such as a fluorescent label. Exemplary fluorescent labels include cyanine, rhodamine, fluorescein, coumarin, BODIPY, Alexa Fluor™, or conjugated multi-dyes.

[0068] Disclosed herein in some embodiments are methods and compositions for identifying sequence reads obtained through sequencing a human or non-human. In some embodiments, sequence reads identified as non-human can then be aligned to a nucleotide database of microbial reference sequences. In some embodiments, the database can be selected for those microbial sequences known to be associated with the host, e.g., the set of human commensal and pathogenic microorganisms. In some embodiments, the microbial database can be optimized to mask or remove contaminating sequences. For example, many public database entries include artifactual sequences not derived from the microorganism, e.g., primer sequences, host sequences, and other contaminants. In some embodiments, sequence reads can be aligned to a reference sequence. In some embodiments, regions that show irregularities in read coverage when multiple samples are aligned can be masked or removed as an artifact. In some embodiments, the detection of such irregular coverage can be done by various metrics, such as the ratio between coverage of a specific nucleotide and the average coverage of the entire contig within which this nucleotide is found. In some embodiments, a sequence that is represented as greater than about 5*, about 10*, about 25*, about 50*, about 100* the average coverage of that reference sequence can be artifactual. In some embodiments, a binomial test can be applied to provide a per-base likelihood of coverage given the overall coverage of the contig. In some embodiments, each high confidence read can align to multiple organisms in the given microbial database. In some embodiments, to correctly assign organism abundance based upon this possible mapping redundancy, an algorithm can be used to compute the most likely organism (for example, see Lindner et al. Nucl. Acids Res. (2013) 41 (1): elO). For example, GRAMMy or GASiC algorithms can be used to compute the most likely organism that a given read came from. In some embodiments, alignments and assignment to a host sequence or to a non-host (e.g., microbial) sequence can be performed in accordance with art- recognized methods. For example, a read of 50 nt. can be assigned as matching a given genome if there is not more than 1 mismatch, not more than 2 mismatches, not more than 3 mismatches, not more than 4 mismatches, not more than 5 mismatches, etc. over the length of the read. In some embodiments, publicly available algorithms can be used for alignments and identification. A non-limiting example of such an alignment algorithm is the bowtie2 program (Johns Hopkins University). In some embodiments, these assignments of reads to an organism (e.g., host organism, non-hostWSGR Docket No. 47697-746601 organism, microbe, pathogen, etc.) can then totaled and used to compute the estimated number of reads assigned to each organism in a given sample, in a determination of the prevalence of the organism in the sample (for example, a cell-free nucleic acid sample). In some embodiments, this information can be used to determine an origin of a pathogen or contaminant. In some embodiments, the analysis described herein can be used to normalize the counts for the size of the microbial genome to provide a calculation of coverage for a microbe. In some embodiments, the normalized coverage for each microbe can be compared to the host sequence coverage in the same sample to account for differences in sequencing depth between samples. In some embodiments, a dataset of microbial organisms represented by sequences in the sample, and the prevalence of those microorganisms can be optionally aggregated and displayed for ready visualization, e.g., in the form of a report.Applications

[0069] Disclosed herein in some embodiments are methods and compositions for various purposes, such as to diagnose or detect an infection, to determine the biological relationship between a microbe and a host, to determine an infection stage of an infection, to predict if the infection will progress to an invasive disease stage, to monitor the efficacy and response to a treatment for infection, to modify or optimize a therapy for a better clinical response, to stop a treatment or therapy, or any combination thereof. In some embodiments, using the methods provided by the disclosure one can provide individualized treatment to a subject that is tailored according to the data obtained by the methods. In some embodiments, the methods disclosed herein can be used to detect, diagnose, treat, monitor, predict, or prognose an infection stage in a subject or patient. In some embodiments, the pathogen causing the infection can be a bacterium, virus, fungus, parasite, yeast, or other microbe. In some cases, the methods can be used to determine if a subject is in the colonization or invasive disease stage. In some cases, the methods can be used to detect if the subject is in the incubation stage, a prodromal stage, an illness stage, a decline stage, a convalescence stage, an eradication stage, chronic stage, or an invasive stage. In some cases, a method determines if an infection is at active or latent stage.

[0070] Disclosed herein in some embodiments are methods for preparing nucleic acid libraries that are useful for various applications. For example, the methods for preparing nucleic acid libraries may be useful for analyzing oxidative stress markers. For example, the methods for preparing nucleic acid libraries may be useful for analysis of an infection (e.g., to determine the biological relationship between a microbe and a host, to determine an infection stage of an infection, to predict if the infection will progress to an invasive disease stage, to monitor the efficacy and response to a treatment for infection) or analysis of a therapy (e.g., to modify orWSGR Docket No. 47697-746601 optimize a therapy for a better clinical response, to stop a treatment or therapy), or any combination thereof. The methods of preparing a nucleic acid libraries may be useful for analyzing oxidative stress markers and may allow for analysis of infection (e.g., to determine the biological relationship between a microbe and a host, to determine an infection stage of an infection, to predict if the infection will progress to an invasive disease stage, to monitor the efficacy and response to a treatment for infection) or analysis of a therapy (e.g., to modify or optimize a therapy for a better clinical response, to stop a treatment or therapy), or any combination thereof. For example, the detection or enrichment of an oxidative stress marker may allow for detection of an infection.

[0071] Disclosed herein in some embodiments are methods that can improve on technical aspects or technical fields. For example, the methods and systems disclosed herein may allow for an improvement in the specificity, sensitivity, or accuracy of the detection of various markers, or in the diagnosis or prognosis or a subject (e.g., diagnosis of an infection), as compared to other methods that do not use methods or compositions disclosed herein (e.g., enrichment of nucleic acids comprising an oxidative stress marker). The methods and systems may allow improvement in data processing or the working of computers components or algorithms. For example, the methods and systems disclosed herein may allow for improved data processing efficiency. In a non-limiting example, the methods may generate sequencing reads from nucleic acids of the subject. The sequencing read may be generated by performing sequencing on an enriched subset of nucleic acids (e.g., nucleic acids comprising oxidative stress markers or nucleic acids that do not comprise oxidative stress markers). The outputted sequencing reads may then be processed. The data processing or computation may be faster and more efficient, based at least in part that the sequence reads are enriched for a specific subset of nucleic acids, which may allow for less noise and more data that is of relevance for a given application. As another non-limiting example, the various systems may be tuned, optimized, or configured such to analyze specific types of sequence reads (e.g., reads from microbes, reads indicative of oxidative stress). The processing of nucleic acids to enrich for nucleic acids (e.g., microbial nucleic acids, nucleic acids comprising oxidative stress markers) may allow for the resulting sequence reads to be efficiently inputted into these tuned, optimized, or configured systems allowing for an improved downstream processes and outputs.

[0072] In some embodiments, methods disclosed herein can be used in conjunction with other medical tests. For example, the methods can be used before or after a stool antigen test, urea breath test, serology, urease testing, histology, bacterial culture and sensitivity testing, biopsy, or endoscopy is taken from a subject. In some cases, the method described herein isWSGR Docket No. 47697-746601 conducted without conducting a stool antigen test, urea breath test, serology, urease testing, histology, bacterial culture and sensitivity testing, biopsy, or endoscopy on the subject. In some embodiments, the method reduces the risk of an infection progressing to invasive disease stage by at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at 100%. In some embodiments, the method reduces the risk of mortality or morbidity related to complications in the invasive disease stage by at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at least 100%.

[0073] Disclosed herein in some embodiments are methods and compositions for individualized treatment for an infected subject or a subject who is susceptible or at risk for infections (e.g., immunosuppressed, immunocompromised, living conditions, or genetic variations resulting in increased susceptibility for infection). In some embodiments, individualized treatment can include predicting if an infection will progress to an invasive disease stage, monitoring the efficacy of a therapy in a subject, modifying a therapeutic regimen depending on the subject's response to the therapy, and determining a pathogen's resistance to a particular therapeutic. In some embodiments, the methods disclosed herein can be used to detect, diagnose, predict, or prognose a pathogen's resistance to a particular therapeutic. In some cases, the methods disclosed herein can further comprise sequencing of the subject's DNA for genetic variations that are associated with therapeutic resistance to therapeutics or to a particular therapeutic. In some cases, samples can be collected serially at various times before or during the course of the infection to determine the pathogen's and subject's response to a treatment, thereby providing a regimen that is individually tailored. In some cases, the serially-collected samples are compared to each other to determine whether the infection is improving or worsening in the subject. In some embodiments, a treatment can involve administering a drug or other therapy to reduce or eliminate the colonization or invasive disease associated with an infection. In some cases, the subject can be treated prophylactically to prevent the development of an infection. Any medical procedure or treatment including administration of a drug can be used to improve or reduce the symptoms of an infection. Some nonlimiting exemplary drugs that can be used are antibiotics (such as ampicillin, sulbactam, penicillin, vancomycin, gentamycin, aminoglycosides, clindamycin, cephalosporin, metronidazole, timentin, ticarcillin, clavulanic acid, cefoxitin), antiretroviral drugs (e.g., highly active antiretroviral therapy (HAART), reverse transcriptase inhibitors, nucleoside / nucleotide reverse transcriptase inhibitors (NRTIs), Non-nucleoside RT inhibitors, or protease inhibitors), immunoglobulins, or any variant or combination thereof.WSGR Docket No. 47697-746601

[0074] Disclosed herein in some embodiments are methods and compositions for adjusting a therapeutic regimen. For example, the subject can be administered a drug to treat an infection. In some embodiments, methods provided herein can be used to track or monitor the efficacy of the drug treatment. In some cases, the therapeutic regimen can be adjusted, depending on upward or downward course of the infection. For example, if the methods provided herein indicate that an infection is not improving with drug treatment, the therapeutic regimen can be adjusted by changing the type of drug or treatment, discontinuing the use of the drug, continuing the use of the drug, increasing the dose of the drug, or adding a new drug or treatment to the subject's therapeutic regimen.

[0075] The methods of the disclosure can be applied to any pathogen that has various stages of infection. The methods can be especially useful for pathogens that have a colonization stage and an invasive disease stage. In some cases, the invasive disease stage can be caused by the pathogen infection. In some cases, the invasive disease stage can be associated with the pathogen infection.

[0076] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by Heliobacter pylori (H. pylori). H. pylori colonization can be asymptomatic. In some cases, colonization can appear as an acute gastritis with abdominal pain (stomach ache) or nausea. The disclosure provides methods to detect, monitor, diagnose, prognose, treat, or prevent invasive H. pylori disease. Subjects with invasive H. pylori disease can develop complications such as, chronic gastritis, peptic ulcer disease, gastric adenocarcinoma, stomach cancers, and lymphoma.

[0077] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by Clostridium difficile (CDI). CDI can present as asymptomatic or symptomatic. The clinical spectrum of a CDI infection can range from mild-to-moderate, severe, or complicated disease. Subjects with mild-to-moderate CDI can present with diarrhea, colitis, including fever, leukocytosis, and cramps. The severity of CDI abdominal and systemic symptoms can increase with the severity of the infection. The methods can be used to detect, monitor, diagnose, prognose, treat, or prevent invasive CDI disease. Subjects with complicated or invasive CDI disease can develop pseudomembranous colitis, toxic megacolon, perforation of the colon, and sepsis.

[0078] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by Haemophilus influenza. Generally, Haemophilus influenza colonizes the upper respiratory tractWSGR Docket No. 47697-746601 of a subject. The disclosure provides methods to detect, monitor, diagnose, prognose, treat, or prevent invasive Haemophilus influenza disease. Subjects with invasive Haemophilus influenza disease can develop complications such as, sepsis or meningitis.

[0079] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by Salmonella. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive Salmonella disease. Some non-limiting examples of Salmonella serotypes that are associated with invasive disease include but are not limited to, Typhimurium, Typhi, Enteritidis, Heidelberg, Dublin, Paratyphi A, Choleraesuis, and Schwarzengrund. Subjects with invasive Salmonella disease can develop bacteremia, meningitis, enteric fever and / or invasive non-typhoidal Salmonella (iNTS) disease.

[0080] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by Streptococcus pneumoniae. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, or prevent invasive Streptococcus pneumoniae disease. Subjects with invasive pneumococcal disease can develop bacteremia and / or meningitis.

[0081] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by Cytomegalovirus (CMV). Subjects infected with CMV can have no symptoms as the virus can cycle to dormant periods. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive CMV disease. Subjects with invasive CMV disease can develop complications in their eyes, lungs, and / or digestive system.

[0082] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by Human Papilloma virus (HPV). Subjects with colonization by HPV can present as non-invasive cervical intraepithelial neoplasms and / or genital warts. The present disclosure also provides methods to detect, monitor, diagnose, prognose, treat, or prevent invasive HPV disease. Subjects with invasive HPV disease can develop cervical cancer, anal squamous cell carcinoma, and / or anal carcinoma in situ.

[0083] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by Epstein- Barr virus (EBV). Subjects colonized with EBV can be asymptomatic or present with fatigue, fever, inflamed throat, swollen lymph nodes in the neck, enlarged spleen, swollen liver, and / or a rash. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict,WSGR Docket No. 47697-746601 or prevent invasive EBV disease. Subjects with invasive EBV disease can develop infectious mononucleosis (e.g., glandular fever), have a higher risk of certain autoimmune diseases, develop cancers such as, Hodgkin's lymphoma, Burkitt's lymphoma, gastric cancer, nasopharyngeal carcinoma, hairy leukoplakia, and / or central nervous system lymphomas.

[0084] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by hepatitis B (HBV). HBV infections can be transient or chronic. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive disease associated with an HBV infection. Subjects with invasive HBV disease can develop cirrhosis, hepatocellular carcinoma, liver infection, and / or liver failure.

[0085] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by hepatitis C virus (HCV). HCV infection can be acute or chronic. Often, HCV colonization can be asymptomatic. When signs and symptoms are present, they can include jaundice, along with fatigue, nausea, fever and muscle aches. Some subjects can have spontaneous viral clearance where others can progress to a chronic stage. However, where an HCV infection becomes chronic it can result in invasive HCV disease. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive HCV disease. Subjects with an invasive HCV disease can develop cirrhosis, hepatocellular carcinoma, liver infection, and / or liver failure.

[0086] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by human T-cell lymphoma virus 1 (HTLV-1). HTLV-1 infects the T cells of a subject. Subjects infected with HTLV-1 can be asymptomatic for years. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive HTLV-1 disease. Subjects with an invasive HTLV-1 disease can develop cancer of the T-cell (ATL) leukemia, HTLV-1 associated myelopathy / tropical spastic paraparesis (HAM / TSP), or other conditions.

[0087] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by gonorrhea. Subjects with a colonization infection can have no symptoms, while others can present with symptoms such as, burning with urination, testicular or pelvic pain, and / or discharge from the genitals. The disclosure provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive gonorrhea disease. Subjects with invasive gonorrhea disease canWSGR Docket No. 47697-746601 develop skin lesions, joint infection (e.g., pain and swelling in the joints), endocarditis, and / or meningitis.

[0088] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by Syphilis. A syphilis infection can be divided into a primary, secondary, latent, and tertiary stages. A subject with primary stage can present with a sore. A subject with secondary stage can present with a skin rash, swollen lymph nodes, and / or a fever. During the latent or invisible stage of syphilis infection subjects are generally asymptomatic. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive syphilis disease. A subject with tertiary stage or invasive disease can develop complications in other organ systems including but not limited to the heart, blood vessels, brain, and / or nervous system.

[0089] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by trichomoniasis. Subjects with a colonization infection can be asymptomatic or they can develop inflammation in their genital area. The present disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive trichomoniasis disease. Subjects with invasive trichomoniasis disease can develop cervical cancer and / or prostate cancer.

[0090] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by human herpesvirus 8 (HHV-8), is also known as Kaposi sarcoma-associated herpesvirus, or KSHV. Healthy subjects with a colonization infection are generally asymptomatic. However, subjects with weakened immune systems can develop invasive HHV-8 disease. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive HHV-8 disease. Subjects with invasive HHV-8 disease can develop Kaposi sarcoma and / or several lymphoproliferative disorders such as, primary effusion lymphoma, multicentric Castleman disease, or B-cell lymphoma.

[0091] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization by Merkel cell polyomavirus. Subjects with a colonization infection can be asymptomatic. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive Merkel cell polyomavirus disease. Subjects with invasive Merkel cell polyomavirus disease can develop Merkel cell carcinoma (MCC) tumors, a rare but aggressive form of skin cancer.

[0092] Disclosed herein in some embodiments are methods and compositions for detection, monitoring, diagnosis, prognosis, treatment, prediction, or prevention of colonization byWSGR Docket No. 47697-746601Chlamydia. Subjects with a colonization infection can be asymptomatic or they can present with burning sensation when urinating or discharge from their genitals. The disclosure also provides methods to detect, monitor, diagnose, prognose, treat, predict, or prevent invasive Chlamydia disease. Untreated chlamydia can progress to invasive disease stage spreading to the uterus and / or fallopian tubes in female subjects. Subjects with invasive chlamydia disease can develop pelvic inflammatory disease (PID), which can result in long-term pelvic pain, inability to get pregnant, and ectopic pregnancy.

[0093] In some embodiments , the treatment may comprise a digital therapy. For example, a digital therapy may be a software-based intervention configured to prevent, manage, or treat a medical condition. Examples of digital therapies may include behavioral therapies (e.g., cognitive behavioral therapy), cognitive training, virtual or augmented reality, biofeedback, neurofeedback, medication management instructions, remote patient monitoring, speech therapy, etc. The digital therapy may be initiated at least in part in response to determining a patient satisfies a risk threshold for a certain medical condition. For example, the digital therapy may be initiated automatically in response to the determination the patient satisfies the risk threshold (e.g., provided a care giver or the patient consents).Data Management

[0094] In some embodiments, the methods and the systems disclosed herein may incorporate one or more data management techniques. For example, these techniques may include standardizing data across different patients, different studies, different data types, etc. Further, for example, these techniques may include sharing data (e.g., automatically) with different users in a network. These users may include, for example, the patient, a care provider (e.g., a doctor, a nurse, a parent, etc.), a pharmacy, a research study, etc. The data may, for example, be shared real-time (or near real-time) across these users.

[0095] Patients may often visit various care providers (e.g., doctors, nurses, etc.), pharmacies, researchers, etc. for diagnosis and treatment. It may be difficult for all these different individuals / entities to share updated information about a patient’s condition with each providers using patient management systems, due to, for example, issues with inconsistent data formatting, data types, data sizes, etc. This can lead to problems with managing treatments, research studies, prescriptions or having patients duplicate tests, for example.

[0096] Further, individuals / entities often continually monitor a patient’s medical records (e.g., biological, genealogical, phenological, demographic, etc.) for updated information, which is often-times incomplete as records across different individuals / entities are often not shared timely in useful data types, formats, sizes, etc.WSGR Docket No. 47697-746601

[0097] To address these challenges, the methods and the systems disclosed herein provide a network-based patient management that collects, converts, and consolidates patient information from various care providers, research studies, pharmacies, etc. into a standardized format for network-based storage and sharing.

[0098] In some embodiments, the methods and the systems disclosed herein provide a graphical user interface (GUI) by a content server, which is hardware or a combination of both hardware and software. A user, such as a care provider, a pharmacy, a researcher, or a patient, is given remote access through the GUI to view or update information about a patient’s medical condition using the user’s own local device (e.g., a personal computer or wireless handheld device). When a user wants to update the records, the user can input the update in any format used by the user’s local device. Whenever the patient information is updated, it may be converted into the standardized format and then stored in a collection of medical records on one or more of the network-based storage devices. After the updated information about the patient’s condition has been stored in the collection, the content server, which is connected to the network-based storage devices, a message may be generated containing the updated information about the patient’s condition. This message may be transmitted in a standardized format over the computer network to users (e.g., care providers) in a network that have access to the patient’s information (e.g., to a care provider the updated information about the patient’s medical condition) so that the users can quickly be notified of any changes (e.g., without having to manually look up or consolidate all of the updates of patient condition). This helps ensure each of a group of care providers is provided real-time notice and access to changes so they can readily adapt their own medical diagnostic and treatment strategy in accordance with other care providers’ actions. The message can be in the form of an email message, text message, a push notification, etc.

[0099] Accordingly, in some embodiments, data management may comprise: (A) obtaining, from a first source, first data corresponding to a patient condition for a patient; (B) obtaining, from a second source, second data corresponding to a patient condition for the patient; (C) standardizing the first data and the second data to generate standardized data; (D) generating (e.g., automatically) a message corresponding to the standardized data; and (E) transmitting the message to a plurality of users (e.g., care providers of the patient, pharmacists, researchers, the patient, etc.) over a computer network (e.g., in real time), so that each user of the plurality of users has access to the standardized data. For example, the first data and the second data may be of a different data format, different data size, different data type, etc.WSGR Docket No. 47697-746601[000100] In some embodiments , the methods and the systems disclosed herein help reduce data size. For example, this data size may correspond to data used in assays, research, medical, etc. contexts. In reducing data size, the methods and the systems disclosed herein may improve efficiency. This improved efficiency may help reduce the amounts of physical resources consumed, e.g., chemicals, devices, testing kits, etc. Further, this improved efficiency may help reduce computing resources, e.g., electricity consumption, heat loss, computing power etc. [000101] Still further advantageously, improved efficiency from the methods and the systems disclosed herein may help reduce traffic over a network by reducing data size. Accordingly, the methods and the systems disclosed herein may be useful in optimizing network performance, resolving network issues, and improving network security through reducing network traffic and burden on the network.[000102] In some embodiments, the methods and the systems disclosed herein help reduce network traffic. In some embodiments, the methods and the systems disclosed herein help reduce network traffic by varying (e.g., reducing) the amount of network data. For example, the methods and the systems disclosed herein may reduce data based at least in part on a threshold. This threshold may correspond too a risk threshold (e.g., a risk of a patient having a medical condition), an accuracy threshold (e.g., an accuracy threshold needed for a conclusion in a research study, assay, test, etc.), or a data threshold (e.g., a data size threshold, a network performance threshold, etc.). Accordingly, the methods and the systems disclosed herein may perform operations comprising: (A) collecting (e.g., over a network) data corresponding to a patient; (B) analyzing the data with respect to a threshold (e.g., risk threshold, accuracy threshold, data threshold, etc.); and (C) transmitting a subset of the data over the network, the subset of the data determined based at least in part on the threshold.[000103] Disclosed herein in some embodiments are methods and compositions for extraction of nucleic acids from a sample. In some embodiments, methods disclosed herein can comprise extracting nucleic acids or target nucleic acids from the sample or purification of nucleic acids or target nucleic acid from unwanted components in a reaction mixture (e.g., ligation, amplification, restriction enzyme, end repair). Any means of extracting nucleic acids known in the art can be used in the methods of the application. In some embodiments, the extraction can comprise separating the nucleic acids from other cellular components and contaminants that can be present in the sample. Nucleic acids can be extracted from a sample using liquid extraction (e.g., Trizol, DNAzol) techniques. In some cases, the extraction is performed by phenol chloroform extraction or precipitation by organic solvents (e.g., ethanol or isopropanol). In some cases, the extraction is performed using nucleic acid-binding columns. In some cases, the extraction is performed usingWSGR Docket No. 47697-746601 commercially available kits such as the Qiagen Qiamp Circulating Nucleic Acid Kit Qiagen Qubit dsDNA HS Assay kit, Agilent™ DNA 1000 kit, TruSeq™ Sequencing Library Preparation, QIAamp Circulating Nucleic Acid Kit, Qiagen DNeasy kit, QIAamp kit, Qiagen Midi kit, QIAprep spin kit) or nucleic acid-binding spin columns (e.g., Qiagen DNA mini-prep kit). In some cases, extraction of cell-free nucleic acids can involve filtration or ultra-filtration. In some embodiments, nucleic acids can be extracted or purified by the use of magnetic beads. For example, magnetic beads with an iron-oxide core and a surface coated with molecules containing a free carboxylic acid or a synthetic polymer can be used. The salt concentration or polyalkylene glycol can be adjusted to control the strength of the bonds between functional groups and nucleic acid, allowing for controlled and reversible binding. Finally, nucleic acids can be released from the magnetic particles with an elution buffer. In some cases, the extraction or purification is performed using commercially available kits such as Omega Bio-tek Mag- Bind® magnetic bead kit, Agencourt®, RNAClean®, or XP magnetic beads.[000104] The method can comprise purifying the target nucleic acids. Purification can be performed where a user desires to isolate the target nucleic acid from unwanted components in a reaction mixture. Nonlimiting exemplary purification methods include ethanol precipitation, isopropanol precipitation, phenol chloroform purification, and column purification (e.g., affinitybased column purification), dialysis, filtration, or ultrafiltration.[000105] In some embodiments, a method can comprise providing a biological sample from a human subject. In some embodiments, a microbe can be present in a human subject or suspected of being present in a human subject. In some embodiments, a method can comprise generating sequence reads associated with microbial cell-free DNA (mcfDNA) from a biological sample by performing massively parallel sequencing on cell-free nucleic acids in a biological sample. In some embodiments, a method can comprise aligning a sequence reads corresponding to sequences associated with microbial cell-free DNA (mcfDNA) with a reference sequence.[000106] In some embodiments, a massively parallel sequencing can comprise whole genome sequencing. In some embodiments, a massively parallel sequencing can comprise Next Generation Sequencing. In some embodiments, a Next Generation Sequencing can comprise a Next Next Generation sequencing. In some embodiments, a method can comprise determining a concentration or quantity of a mcfDNA. In some embodiments, a method can comprise monitoring a concentration or quantity of a mcfDNA over time. In some embodiments, a method can comprise identifying fragments of mcfDNA that vary during a course of treatment.[000107] In some embodiments, a cell-free nucleic acid (cfNA) can comprise cell-free DNA (cfDNA), a cell-free RNA (cfRNA), or a combination thereof. In some embodiments, a cfDNAWSGR Docket No. 47697-746601 can comprise microbial cfDNA (mcfDNA). In some embodiments, a cfRNA can comprise microbial cfRNA (mcfRNA). In some embodiments, measuring concentrations of cfDNA in a biological sample can comprise preparing a nucleic acid library. In some embodiments, determining a quantity or concentration of cfDNA in a biological sample can comprise next generation sequencing of cfDNA.[000108] In some embodiments, a biological sample can comprise a biological fluid sample. In some embodiments, a biological fluid sample can comprise a cell-free biological fluid sample. In some embodiments, a biological fluid sample can comprise a plasma sample, serum sample, blood sample, a lavage sample, a bronchoalveolar lavage sample, saliva sample, synovial fluid sample, cerebrospinal fluid sample, or urine sample. In some embodiments, a biological fluid sample can comprise a plasma sample.General methods[000109] Disclosed herein, in some embodiments, are methods and kits to distinguish or enrich populations of nucleic acids in a sample (e.g., bodily fluid sample, plasma sample, serum sample, bronchoalveolar lavage sample, blood sample, etc.). Generally, the methods and kits are for use in preparing a nucleic acid sequencing library that is enriched for a particular population of nucleic acids. In some cases, the methods disclosed can be used to enrich for populations of nucleic acids based on the source of the nucleic acids (e.g., human host vs. microbe; transplant donor vs. recipient; cancerous vs. non-cancerous; fetal vs. maternal). In some embodiments, the methods disclosed herein can be used to distinguish populations of nucleic acids comprising genomes with different genotypes, such as a human host versus a microbe.[000110] In some embodiments, the methods can be used to distinguish between two populations of nucleic acids based on the amenability or susceptibility of the nucleic acids to a particular chemical reaction. For example, as shown herein, microbial cell-free nucleic acids (e.g., microbial cell-free DNA (or “mcfDNA”)) tend to lack phosphorylated 5’ termini, in contrast with human cell-free nucleic acids (e.g., cell-free DNA), which tend to contain phosphorylated 5’ termini. (In some cases, synthetically-produced DNA, such as synthetically produced spike-in DNA also contains phosphorylated 5’ termini.) As such, human cell-free nucleic acids are naturally more amenable to certain chemical reactions such as ligation reactions, than microbial cell-free nucleic acids. This is because, generally, ligation reactions can involve ligating the phosphorylated 5’ terminus of one nucleic acid to the 3’ (unphosphorylated) terminus of a second nucleic acid. The 5’ termini of microbial cell-free nucleic acids thus tend to be resistant to ligation reactions unless they are further altered, such as by phosphorylating the 5’ termini with a kinase such as polynucleotide kinase (PNK).WSGR Docket No. 47697-746601[000111] In some cases, this disclosure provides sample processing methods that rely on a series of reversals. The method can involve providing a sample comprising a mixture of two different populations of nucleic acids, which can be differentiated in that one of the populations contains a chemical feature lacking in the other. In some instances, the chemical feature is a feature that permits the population of nucleic acids to be susceptible to a particular chemical reaction, such as a ligation reaction, a PCR reaction, a kinase reaction, or a sequencing reaction. The method can then involve selectively targeting the population with the chemical feature in order to block, inactivate or remove the chemical feature. The method can then involve adding or attaching the chemical feature to the population lacking the feature, so that the two populations have effectively switched places. The mixture of nucleic acids can then be subjected to a chemical reaction, such that the population newly modified to contain the chemical feature is preferentially enriched (e.g., by being preferentially ligated to an adapter, preferentially amplified, or preferentially sequenced).[000112] In some embodiments, the methods provided herein involve obtaining a mixture of two populations of nucleic acids and selectively modifying a first population of nucleic acids (e.g., human nucleic acids) by reducing or eliminating its amenability to a chemical reaction (e.g., a ligation reaction) followed by selectively modifying a second population of nucleic acids (e.g., microbial cell-free nucleic acids) in order to enhance its amenability to a chemical reaction (e.g., a ligation reaction). The methods allow selective enrichment of a population of nucleic acids (e.g., mcfDNA) by selectively targeting nucleic acids based on differential phosphorylation, or other chemical difference.[000113] In some instances, a first population of nucleic acids (e.g., human cell-free nucleic acids, synthetic spike-in nucleic acids) are altered by attaching them to a blocking group or oligonucleotide that selectively attaches to 5’ phosphorylated termini, e.g., by a ligation reaction. In some cases, the blocking group (also referred to herein as a “dummy oligo,” or a “decoy oligo”) can comprise a feature that renders the first population of nucleic acids impervious to a reaction, such as a ligation reaction or an amplification reaction. For example, a 5’ blocking group can be designed to lack a 5’ phosphate group and is thus impervious to additional ligation reactions after being ligated to the first population of nucleic acids. The 5’ blocking group can also be designed to have a 5’ terminus that is not capable of being phosphorylated by a kinase. Ligation of such a 5’ blocking group to a first population of nucleic acids (e.g., human cell-free DNA) prevents the 5’ termini from engaging in further ligation reactions, such as being ligated to an adapter (e.g., a sequencing adapter). In such cases, if the sequencing adapter is being used to amplify the nucleic acids (e.g., by using a primer that is specific for the sequencing adapter),WSGR Docket No. 47697-746601 any nucleic acids that are attached to the blocking group will not participate in the ligation reaction, will not attach to a 5’ sequencing adapter, and thus will be prevented from being amplified or being used in downstream processes such as a sequencing assay.[000114] After introduction of the blocking group, the mixture of nucleic acids can be subjected to a reaction that causes the second population of nucleic acids (e.g., mcfDNA) to become amenable to a chemical reaction. For example, the 5’ termini of the nucleic acids can be phosphorylated with a kinase such as polynucleotide kinase (PNK), rendering the mcfDNA amenable to a ligation reaction. Then, when 5’ adapters are added to the mixture of two populations of nucleic acids, the adapters selectively attach to the second population (e.g., the mcfDNA) over the first population (e.g., human cell-free DNA) given that the blocking group attached to the first population remains unphosphorylated even after addition of the kinase. Following amplification the second population of nucleic acids is selectively enriched over the first population.[000115] In some cases, the blocking group is used to tag or identify a population of nucleic acids in a mixture of populations. For example, a blocking group containing a known sequence can be used to tag and identify 5’ phosphorylated nucleic acids (e.g., human cell-free DNA) within the mixture. In such cases, the blocking group can or cannot be amenable to a further ligation reaction to a 5’ adapter. In some cases, where a blocking group that is not amenable to further ligation is used, the known sequence of the blocking group can be used to determine whether any first population nucleic acids (e.g., human cell-free DNA) ended up being sequenced in a later sequencing assay. In such case, the tag can be used as an internal control to assess the quality and efficiency of the blocking mechanism. In other cases, where a blocking group that is amenable to further ligation is used, then the known sequence tagged to the first population nucleic acids (e.g., human cell-free DNA) can be later used to identify human cell- free DNA in downstream processes such as NGS.[000116] In some cases, the first population can be selectively degraded based on its chemical difference from the second population. For example, in cases where the first population is more highly phosphorylated at its 5’ termini (e.g., human cell-free DNA) than the second population, the first population can be selectively degraded using a 5’ phosphorylation-specific exonuclease (e.g., Lambda exonuclease or Terminator exonuclease). Selective degradation of the first population can result in selective enrichment of the second population of cfDNA, which can go on to be PCR amplified or be subjected to other downstream processes (e.g., next-generation sequencing, massively-parallel sequencing).WSGR Docket No. 47697-746601[000117] In some cases, the methods provided herein are particularly useful to analyze singlestranded nucleic acids. In some cases, the methods can involve denaturing a mixture of nucleic acids to obtain single-stranded nucleic acids (e.g., single-stranded DNA). Adapters such as splint oligonucleotides can be used to enrich for a population of nucleic acids in the mixture of single-stranded nucleic acids. Generally, as provided herein, a splint oligonucleotide comprises a double-stranded region and a single-stranded region. The single-stranded region can contain random nucleotides or N-mers that randomly hybridize to genomic sequences within the mixture. The double-stranded region can be considered an adapter region containing a first strand and a second strand. The first strand can be connected to the single-stranded region, while the second strand can be hybridized to the first strand. The “splint” region of the oligonucleotide contains the first strand connected to the single-stranded region.[000118] The methods provided herein can involve use of a 3’ splint oligo, a 5’ splint oligo and / or a 5’ splint blocking group (or 5’ dummy oligo). In some cases, the 5 ’splint blocking group comprises a single-stranded region preferably comprising random nucleotides that have agnostic binding activity. The 5’ splint blocking group can comprise a splint region that comprises at least one uracil base in the random region, in the first strand, or in both the random region and the first strand. In some cases, the second strand of the double-stranded region comprises at least one uracil base. In some embodiments, the 5’ dummy (decoy) oligo is ligated to natively phosphorylated 5’ termini of the first population, but not to the second population which is not amenable to ligation. In some cases, the 3’ splint oligo and / or the 5’ splint oligo also comprise one or more uracil bases. In some cases, the uracil bases are present in the splint region (e.g., the single stranded region or the first strand of the double-stranded region). In some cases, in these splint oligo’ s, uracil bases are not present in the second strand of the double-stranded region.[000119] In some cases, the method comprises subjecting the sample to a uracil deglycosylase (UDG) enzyme or USER digestion in order to cleave the uracil bases within the splint oligo’ s or splint blocking groups. In some cases, the USER digestion removes the splint regions of the splint oligo’ s and splint blocking groups. In some cases, the USER digestion also removes the entire splint blocking group, including the strand directly ligated to the 5’ end of the first population (e.g., human cell-free DNA).[000120] This disclosure provides, in some embodiments, kits, particularly kits that can be used to distinguish or enrich for different populations of nucleic acids within a mixture of nucleic acids. In some cases, the kits comprise: (a) a 5’ splint oligonucleotide comprising (i) a doublestranded adapter region comprising a first adapter strand and a second adapter strand and (ii) aWSGR Docket No. 47697-746601 single-stranded region attached to the first strand of the double-stranded adapter region; and (b) a 5’ blocking splint oligonucleotide comprising (i) a double-stranded blocking adapter region comprising a first blocking adapter strand and a second blocking adapter strand and (ii) a singlestranded region attached to the first strand of the double-stranded blocking adapter region, wherein the second blocking adapter strand has a 5’ terminus that is not amenable to ligation. In some cases, the kit further comprises a 3’ splint oligonucleotide comprising (i) a doublestranded adapter region comprising a first adapter strand and a second adapter strand and (ii) a single-stranded random region attached to the first strand of the double-stranded adapter region. Initial Samples and Raw Biological Samples[000121] The disclosed methods, systems, compositions, and kits can be used for the analysis of a wide range of different sample types. The disclosure can be particularly useful in the evaluation of initial samples in which the nucleic acids are of low quality or quantity by allowing analysis of a larger fraction of the nucleic acids present in the initial sample, regardless of purification efficiencies or biases or chemical type or structure.[000122] In some embodiments, the initial sample can comprise a raw biological sample. In some embodiments, the initial sample can comprises a solid or a body fluid such as blood, plasma, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardia! fluid, rectal swab, bone, skin tissue, soft tissue, tears, and / or a nasal sample. In some embodiments, the initial sample comprises a solid or a body fluid selected from the group consisting of plasma, cerebrospinal fluid, bronchoalveolar lavage, urine, and synovial fluid. In some embodiments, the initial sample comprises plasma. In some embodiments, the initial sample comprises, consists of, or consists essentially of urine. In some embodiments, the initial sample comprises cerebrospinal fluid. In some embodiments, the initial sample is from a human subject. In some embodiments, an initial sample can comprise circulating tumor or fetal nucleic acids. In some embodiments, the initial sample comprises circulating donor nucleic acids.[000123] Cell-free nucleic acids can be present in any biological sample, including raw biological samples, raw samples, and initial samples. In some embodiments, an initial sample can be made up of, in whole or in part, cells and / or tissue. The initial sample can be cell-free or cell-depleted. The initial cell-free sample or initial sample can comprise nucleic acids that originated from a different site in the body, such as a site of pathogenic infection. In the case ofWSGR Docket No. 47697-746601 blood, serum, lymph, or plasma, the initial sample can contain “circulating” cell-free nucleic acids that originated at anatomic locations other than the site of bodily fluid collection of the fluid in question. The cell-free samples or cell-depleted initial samples can be obtained by depleting or removing cells, cell fragments, or exosomes by a known technique such as by centrifugation or filtration.[000124] In some embodiments, substances that can affect library generation are partially or completely removed. In some embodiments, the nucleic acid library is generated from the initial sample without prior partial or complete removal of any substance that can affect the library yield or inhibit the library generation. Examples of substances that can affect library generation that can be completely or partially removed include, but are not limited to, heparin or other oligo- / poly-saccharides, EDTA, fat, lipids, fatty acids, urea, hemoglobin, and other products of hemolysis, immunoglobulin, lactoferrin, buffy coat, components of the buffy coat, calcium, collagen, haematin, tannic acid, melanin, humic acids, antiviral substances (e.g., acyclovir), therapeutic drugs, human serum albumin, lipoproteins, triglyceride-rich lipoproteins, hemolysate, protein, conjugated bilirubin, unconjugated bilirubin, antibody, acetylcysteine, ampicillin, cefoxitin, doxycycline, theophylline, levodopa, methyldopa, metronidazole, acetylsalicylic acid, ibuprofen, phenylbutazone, rifampicin, cyclosporine, acetaminophen, creatinine, glucose, glycerol, lactate, pyruvate, uric acid, and / or biotin.Subjects[000125] An sample can be derived from any subject (e.g., a mammal such as a human subject or non-human subject, or a plant). The sample can comprise a bodily fluid e.g., a plasma, or other bodily fluid. The subject can be healthy. In some embodiments, the subject is a human host. In some embodiments, the subject is a human patient having, suspected of having, or at risk of having, a disease or infection.[000126] The sample can be from a subject who has a specific disease, condition, or infection, or is suspected of having (or at risk of having) a specific disease, condition, or infection. In some embodiments, the sample can be from a patient with an infection, a patient suspected of an infection, or a patient at risk of having an infection.[000127] A human subject can be a male or female. In some embodiments, the sample can be from a human embryo or a human fetus. In some embodiments, the human can be an infant, toddler, child, teenager, adult, or elderly person. In some embodiments, the subject is a female subject who is pregnant, suspected of being pregnant, or planning to become pregnant. In some embodiments, the female subject is not pregnant, or is not suspected of being pregnant or is not planning to become pregnant.WSGR Docket No. 47697-746601[000128] In some embodiments, the subject is a farm animal, a lab animal, a domestic pet, or any other animal. For example only, in some embodiments, the animal can be a primate, a rodent, an insect, a dog, a cat, a horse, a cow, a mouse, a rat, a pig, a fish, a bird, a chicken, or a monkey.Denaturation[000129] Provided herein in some embodiments are methods of denaturing nucleic acids. Denaturing nucleic acids can cause all, most, part, or a sufficient part for detection, of the double-stranded nucleic acids to become single-stranded. Denaturation can be performed at any point in the process. In some embodiments, denaturation can remove all, most, or part of the secondary, tertiary, or quaternary structure of double-stranded or single-stranded nucleic acids. As such, any type of sample can be subjected to the denaturation step, including samples that contain, or are suspected to contain, only double-stranded nucleic acids, only single-stranded nucleic acids, a mixture of double-stranded and single-stranded nucleic acids, or any higher order nucleic acid structure.[000130] The nucleic acids can be denatured using any method known in the art. In some embodiments, the nucleic acids are denatured using heat. In some embodiments, single-stranded nucleic acids in the sample arise as a result of being subjected to denaturation. In some embodiments, however, the nucleic acids in the sample are single-stranded because they were originally single-stranded when they were obtained from the subject, e.g., without limitation, as single-stranded viral genomic RNA, or single-stranded DNA or as a result of shipping and handling conditions.[000131] In some embodiments, denaturation is accomplished by applying heat to the sample for an amount of time sufficient to denature double-stranded nucleic acids of interest or to denature secondary, tertiary, or quaternary structures of double-stranded or single- stranded nucleic acids. In general, the sample can be denatured by heating at 95 °C, or within a range from about 65 to about 110 °C, such as from about 85 to about 100 °C. Similarly, the sample can be heated at any temperature between about 50 °C and about 110 °C for any length of time sufficient to effectuate the denaturation, e.g., from about 1 second to about 60 minutes. In some embodiments, long nucleic acids such as intact dsRNA viruses can require longer denaturation times. In general, denaturation is performed in order to ensure that all, most, or part of the nucleic acids or nucleic acids of interest within a sample are present in single-stranded form.[000132] In some embodiments, denaturation comprises denaturation to enrich certain nucleic acids. In some embodiments, selective denaturation comprises one or more denaturation processes effective for the selection of fragments of a certain length and / or GC- content. In someWSGR Docket No. 47697-746601 embodiments, selective denaturation comprises incubation at selected or elevated temperatures. In some embodiments, a selective denaturation can comprises incubation at a temperature of about 45°C, at a temperature of about 50°C, at a temperature of about 55°C, at a temperature of about 60°C, at a temperature of about 65°C, at a temperature of about 70°C, at a temperature of about 75°C, at a temperature of about 80°C, at a temperature of about 85°C, at a temperature of about 90°C, at a temperature of about 95 °C, at a temperature of about 100°C, at a temperature of about 105°C, at a temperature of about 110°C. In some embodiments, setting the temperature occurs at any of the denaturations such as, for example, without limitation, following dephosphorylation, preceding 3'-end adapter attachment, and / or during an elution step.[000133] In some embodiments, denaturation can remove all, most, part, or a sufficient part for detection of the secondary, tertiary, or quaternary structures in single-stranded DNA and / or RNA molecules. Non-limiting examples of domains of secondary structure that can be removed during a denaturation can include hairpin loops, hairpin stems, bulges, internal loops, and complexes of complementary nucleic acid sequences and any element contributing to folding of the molecule or complexes. In some embodiments, a method can comprise no denaturation process, for example when the sample is known to contain only single-stranded nucleic acids or when there is a desire to restrict the ultimate analysis to only the single-stranded and not the double-stranded nucleic acids in the sample.Chemical and Mechanical Denaturation[000134] In some embodiments, denaturation comprises adding one or more denaturing agents for a selective or controlled denaturation. In some embodiments, denaturation comprises a selective or controlled denaturation. Depending on the application, chemical or mechanical denaturation can be used (e.g., sonication, mechanical force applied by magnetic field (e.g., magnetic tweezers) or optical traps (e.g., optical tweezers) or the like) with the methods.[000135] Chemical denaturation agents that can be used with the methods of the disclosure include but are not limited to, alkaline agents (e.g., NaOH), formamide, guanidinium chloride, guanidine, sodium salicylate, dimethyl sulfoxide (DMSO), propylene glycol, betaine, or urea. In some embodiments, the one or more denaturing agents comprises for example, without limitation, one or more of formamide, urea, guanidinium chloride, salts, betaine, detergents, surfactants, and / or DMSO. Salts can comprise for example, without limitation, NaCl and MgCh. Examples of nucleic acid library preparation[000136] Disclosed herein is a method of preparing a nucleic acid library from a sample comprising a mixture of microbial nucleic acids and human nucleic acids, wherein the method comprises:WSGR Docket No. 47697-746601 a. receiving the sample comprising a mixture of microbial nucleic acids and human nucleic acids, wherein one or more of the human nucleic acids comprise a 5 ’-end phosphate moiety; b. attaching a blocking moiety to the 5 ’-end phosphate moiety to the one or more human nucleic acids of the mixture or degrading the human nucleic acids using a 5’ phosphorylationspecific exonuclease; c. phosphorylating the microbial nucleic acids of the mixture to produce 5’ phosphorylated microbial nucleic acids; and d. attaching 5’- end adapters to the 5’ phosphorylated microbial nucleic acids to produce a nucleic acid library enriched for microbial nucleic acids.[000137] In one embodiment, the method further comprises attaching 3 ’-end adapters to nucleic acids in the mixture of microbial nucleic acids and human nucleic acids. In another embodiment, 5 ’-end phosphorylation-blocking adapters are attached via the 5 ’-end phosphate moi eties and impede a reaction, resisting ligation, resisting phosphorylation, resisting amplification, or resisting sequencing. In another embodiment, the blocking adapters are splint oligonucleotides that comprise a double-stranded region preferably comprising a uracil base situated not directly connected to the single-stranded region; and a single-stranded region preferably comprising random nucleotides, or a sequence that hybridizes at an end of the human nucleic acids.[000138] In another embodiment the mixture of microbial nucleic acids and human nucleic acids are denatured; the 5 ’-end adapters are ligated to the 5 ’-end decoy adapters; and a uracil base or DNA backbone in the 5’-end decoy adapters are cleaved to disconnect the adapters from the human nucleic acids. In another embodiment the human nucleic acids are treated by a 5’ phosphorylation-specific exonuclease, preferably a lambda exonuclease or terminator exonuclease.[000139] In another embodiment, the method further comprises amplifying the microbial nucleic acids attached to 5 ’-end adapters to enrich for the mcfNA, preferably using primers that hybridize to the 3 ’-end adapters or the 5 ’-end adapters, preferably adapters that are doublestranded oligonucleotides, or splint oligonucleotides that comprise a double-stranded region and a single-stranded region, preferably where the single-stranded region comprises random nucleotides or a sequence that hybridizes to an end of the microbial nucleic acids.[000140] In another embodiment, the 5’- end adapters are ligated to the 5’ phosphorylated microbial nucleic acids by a T4 DNA ligase, a SplintR ligase, a PBCV-1 DNA ligase or a Chlorella virus DNA ligase.WSGR Docket No. 47697-746601[000141] In another embodiment the method further comprises denaturing the nucleic acids of the sample (preferably a sample of blood, serum, plasma, bronchial lavage, synovial fluid, bronchoalveolar lavage, or cerebrospinal fluid) to produce denatured nucleic acids prior to addition of the adapters; and results in a 2-fold enrichment of the mcfNA.[000142] Another aspect of the disclosure is a method of preparing a nucleic acid library from a sample comprising nucleic acids, wherein the method comprises: a. providing a sample comprising 5’-end phosphorylated nucleic acids and 5’-end nonphosphorylated nucleic acids; b. attaching a decoy 5' -end adapter to the 5’-end phosphorylated nucleic acids to produce nucleic acids attached to the 5’-end adapter, wherein the decoy 5' -end adapter is 5’-end nonphosphorylated and is modified to resist 5’-end phosphorylation; c. phosphorylating the 5 ’-end non-phosphorylated nucleic acids with a kinase to produce phosphorylated nucleic acids; d. attaching a 5'-end adapter to the 5’-end phosphorylated nucleic acids to produce nucleic acids attached to the 5 ’-end adapters; and e. amplifying the nucleic acids attached to the 5 ’-end adapters.[000143] In one embodiment of the method, 3 '-end adapters are attached to the nucleic acids that have been modified by 5 ’-end phosphorylation. In some embodiments, the 3’ end adapters are also attached to nucleic acids that have not been modified by 5’-end non-phosphorylation.[000144] Adapters, full length or partial, can be attached to the nucleic acids in a sample at one or more points during the sample preparation process. In some embodiments, adapters can be attached by ligation, by primer extension, by non-templated extension, by template switching, by the addition of nucleotides to the 3' terminus of a nucleic acid molecule, by hybridization, by amplification (e.g., PCR) or a combination of any of these reaction types. In some embodiments, adapters are attached by a ligation reaction method using a ligase enzyme that recognizes a particular nucleic acid form. In some embodiments, adapters are attached by a primer extension reaction method using, e.g., a PCR reaction, where the adapter also acts as a primer for a polymerase which acts on a particular nucleic acid form. In some embodiments, adapters are attached with a combination of a non-templated nucleic acid polymerase and primer extension off of non-templated sequences (e.g., template switching or template switching PCR).[000145] Depending on the type of nucleic acid molecule in the sample, the adapter attached can be either double-stranded or single-stranded such that the adapter is compatible with the nucleic acid molecules in the sample. For example, in some embodiments a double-stranded adapter is attached to a double-stranded nucleic acid. In some embodiments, it is desirable toWSGR Docket No. 47697-746601 protect adapter ends, for example by adding 5'-end and / or 3'-end protective groups, such as amino modifiers, C3 spacers, dideoxy nucleotides, and / or inverted nucleotides or by providing an adapter that is duplexed on one end (or double-stranded) and single-stranded on the other end. Any combination of protective methods and / or groups set forth herein can be used.[000146] Primer extension reactions can be carried out with a DNA-dependent polymerase, an RNA-dependent polymerase, polymerase with non-templated activity, a reverse transcriptase, or a combination thereof. In some embodiments, the primer extension reaction can be carried out by a DNA or RNA polymerase having strand displacing activity. In some embodiments, the primer extension reaction is carried out by a DNA or RNA polymerase that has non-templated activity. In some other embodiments, the primer extension reaction can be carried out by a DNA or RNA polymerase having strand displacing activity and a DNA or RNA polymerase that has non-templated activity. In some embodiments, primer extension is carried out with a Klenow fragment.Adapter Compositions[000147] Particular adapters can be used with the present disclosure. In general, the adapter compositions allow for the detection of different nucleic acid forms in a sample.[000148] Depending on the starting sample type, what nucleic acid(s) are being analyzed, the method, and what detection system is being used, an appropriate adapter can be employed (e.g., particular functional elements or modifications).[000149] In general, an adapter can comprise a polymerase priming sequence, a sequence required to initiate reading of a nucleic acid sequence in sequencing, a sequence required to initiate reading of identifying sequences, and / or one or more identifying sequences (e.g., such as an index, a barcode, a non-templated overhang, a random sequence, unique molecular identifiers, or a combination thereof). For other applications, an adapter can comprise at least one functional element selected from polymerase priming sequence, a sequencing priming sequence, binding sites for amplification primers, a recognition sequence or structural elements required by the sequencing method utilized, one or more identifying sequences, and a label (e.g., radioactive phosphates, biotin, fluorophores, or enzymes). Labels can be added to an adapter if a purification process or particular detection system is desired (e.g., digital PCR, ddPCR, quantitative PCR, microfluidic device, microarray, etcetera).[000150] The adapter can be single-stranded or double-stranded or can have both singlestranded and double-stranded regions. In some embodiments, the adapter comprises an RNA molecule, a DNA molecule, or a molecule that contains both DNA and RNA sections and / or strands, and / or a single strand that has both RNA and DNA components. In some embodiments,WSGR Docket No. 47697-746601 a double-stranded adapter can be blunt- ended. In some embodiments, a double-stranded adapter can contain nucleic acid residue overhang(s).[000151] Such nucleic acid residue overhangs (or tails) can be used to mark a molecule as originating from DNA or RNA in the starting sample, particularly when the overhangs are complementary to an overhang sequence deposited by a DNA nucleotidylexotransferase (e.g. TdT), Poly(A) Polymerase, a RT (e.g., SMART er RT, HIV RT), RNA-dependent polymerase (e.g. RdRP from turnip crinkle virus), and / or a DNA-dependent polymerase (e.g., Bst 2.0 DNA polymerase). For example, the adapter overhang can contain one or more T residues in order to hybridize to one or more overhang residues deposited by a DNA polymerase (e.g., Bst 2.0 DNA polymerase, TdT or the like). Similarly, the adapter overhang can contain one or more C residues in order to hybridize to one or more overhang residues deposited by an RT (e.g., SMART er RT, reverse transcriptases derived from Moloney Murine Leukemia Virus, or the like). HIV reverse transcriptase and the long terminal repeat retrotransposon also have non- templated activity but can add a different nucleotide other than C.Amplification Element[000152] An adapter can comprise an amplification primer that is a primer used to carry out a polymerase chain reaction (PCR). In some embodiments, the amplification primer comprises a random primer. In some embodiments, the amplification primer comprises a template-specific primer. In some embodiments, the amplification primer comprises a primer complementary to a known non-templated overhang known to be added by the polymerase. In some embodiments, the amplification primer comprises a standardized flow cell adapter sequence or a part thereof; standardized flow cell adapter sequences are known in the art and include but are not limited to P5 and P7. In some embodiments, the amplification primer comprises a P5 primer. In some embodiments, the amplification primer comprises a P7 primer. In some embodiments, the amplification primer comprises only part of a P5 or P7 primer. In some embodiments, depending on the method of detection, the amplification primer comprises one or more additional functional elements.Identifying Sequence Element[000153] Identifying sequences (e.g., barcode, index, or a combination thereof) can comprise a unique sequence. The identifying sequences can be added to a particular nucleic acid form by the methods provided herein (e.g., ligation, primer extension, amplification, non- templated extension, template switching, template switching PCR or a combination thereof) allowing the identification of each nucleic acid form in a sample or after sequencing. In some embodiments,WSGR Docket No. 47697-746601 the identifying sequences can also contain additional functional elements such as primer amplification sites, sequencing priming sites, or sample indexes.[000154] The identifying sequences can be completely scrambled (e.g., random ers of A, C, G, and T for DNA or A, C, G, and U for RNA) or they can have some regions of shared sequence. For example, a shared region on each end can reduce sequence biases in ligation events. In some embodiments, the adapter comprises shared region and the shared region comprises about or at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 common base pairs. [000155] Combinations of barcodes and / or indexes can be added to increase diversity. For example, barcodes and / or indexes can be used as identifiers for well position in a microtiter plate, array, or the like (e.g., 96 different barcodes for a 96-well plate), and another barcode can be used as an identifier for a plate number (e.g., 24 different barcodes for 24 different plates), giving 96x24 = 2,304 combinations using 96+24 = 120 sequences. Using three or more barcodes per sample can further increase achievable diversity.[000156] In some embodiments, the adapter comprises barcodes and / or indexes. In some embodiments, the barcodes and / or indexes are linked to sequencing reads. In some embodiments, particular barcodes and / or indexes can be linked to particular sequencing reads. In some embodiments, particular barcodes and / or indexes can be linked to particular sample. In some embodiments, barcodes comprise about 2, 3, 4, 5, 6, 7, 8 ,9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 200, 250, 300, 350, or 400, 500, or 1000 nucleotides (or base pairs) in length.Label Element and Other Components[000157] In some embodiments, the adapter comprises one or more labels. Labels can be added to an adapter when purification is desired or for using particular detection. Examples of labels that can be used with the disclosure include, but are not limited to, any of those known in the art, enzymes such as fluorophores, radioisotopes, stable free radicals, luminescers, such as chemliuminescers, bioluminescers, dyes, pigments, enzyme substrates, biotin, digoxigenin, antigens, antibodies, a His-tag, and other labels. One skilled in the art will choose a label that is compatible with the chosen detection method.Attaching Adapters & Ligase Enzymes[000158] In some embodiments, attaching comprises using a ligase; in other embodiments attaching comprises using a polymerase. In some embodiments, attaching an adapter comprises attaching an adapter to both DNA and RNA target molecules. When multiple different ligases are used (e.g., a dual ligase system), the ligases can each be specific for a target (e.g., DNA- specific, or RNA-specific). In some embodiments, attaching comprises using a dual ligaseWSGR Docket No. 47697-746601 system. In some embodiments, the dual ligase system comprises DNA-specific, RNA-specific, and / or ligases that ligate both DNA and RNA templates in any combination.[000159] In some embodiments, the ligase comprises a ligase specific for double-stranded nucleic acids (e.g., dsDNA, dsRNA, RNA / DNA duplex). An example of a ligase specific for double-stranded DNA and DNA / RNA hybrids is T4 DNA ligase. In some embodiments, the ligase is specific for single-stranded nucleic acids (e.g., ssDNA, ssRNA). An example of such ligase is CircLigase IL In some embodiments, the ligase comprises a ligase specific for RNA / DNA duplexes. In some embodiments, the ligase comprises a ligase that is able to work on single-stranded, double-stranded, and / or RNA / DNA nucleic acids in any combination.[000160] Both DNA or / and RNA ligases can be used with the disclosure. Ligases that can be used in the methods provided herein can include, but are not limited to, T4 DNA Ligase, T3 DNA Ligase, T7 DNA Ligase, E. coli DNA Ligase, HiFi Taq DNA Ligase, 9°N™ DNA Ligase, Taq DNA Ligase, SplintR® Ligase (also known as Splint-R ligase or PBCV-1 DNA Ligase or Chiarella virus DNA Ligase), Thermostable 5' AppDNA / RNA Ligase, T4 RNA Ligase, T4 RNA Ligase 2, T4 RNA Ligase 2 Truncated, T4 RNA Ligase 2 Truncated K227Q, T4 RNA Ligase 2, Truncated KQ, RtcB Ligase, CircLigase II, CircLigase ssDNA Ligase, CircLigase RNA Ligase, Ampligase® Thermostable DNA Ligase, T4 RNA ligase II and its modified or truncated derivatives, or a combination thereof.[000161] In some embodiments, the adapters are attached to nucleic acids, such as, for example, without limitation, a single-stranded RNA, comprising a 5'-end modification such as App (e.g., pre-adenylation). The presence of the 5' App modification can enable oligonucleotides to act as direct substrates for certain ligases and remove the need for ATP. Adapters to single-stranded RNA can contain a 5' adenylation (5' App) modification and / or an RNA-identifying code. [000162] Alternatively, or additionally, DNA and RNA in a sample can be specifically marked during an adapter attachment step. In some embodiments an adapter attachment can be performed by template switching or ligation. In some embodiments, the ligase comprises a ligase specific for one type of nucleic acids. For example, a DNA-specific ligase can be used so that adapters are only ligated to the DNA molecules in the sample. In another example, an RNA- specific ligase can be used so that adapters are only ligated to the RNA molecules in the sample. In some embodiments, ligation comprises successive ligation with a first ligase specific to one type of nucleic acid and a second ligase not discriminating between nucleic acids types. For example, successive ligation first with a DNA-specific ligase (e.g., CircLigase ssDNA ligase) followed by a ligase that can act on a DNA or RNA template (e.g., CircLigase II) can be used. Sequential or concurrent first adapter attachment and / or sequential or concurrent second adapterWSGR Docket No. 47697-746601 attachment can provide the ability to distinguish between chemical forms of nucleic acids (e.g., DNA and RNA). The choice of ligation method can depend on the ligase specificities and reaction conditions for each ligase used.[000163] In some embodiments, the ligase comprises ligase selected with an appropriate profile of contaminating nucleic acids so that the profile deters sufficiently from an expected signal of interest (e.g., endogenous microbe signal in cell-free nucleic acid pool) in order to recognize and filter contamination signal originating from ligase. In some embodiments, an appropriate profile of contaminating components (e.g., buffers, buffer components, oligonucleotides, enzymes, water, beadsis selected so that the profile deters sufficiently from an expected signal of interest in order to recognize and filter contamination signal originating from components.Successive Mode of Attachment[000164] In some embodiments, a method disclosed herein may be applied in a successive mode. In some embodiments, more than one enzymatic process can be applied at separate points of a method. In some embodiments, successive ligations may be utilized. In some embodiments when successive ligation is used, a wash can be performed between the two ligation reactions to remove the first ligase and excess adapters. For example, successive ligation can be used in the first adapter ligation step. Biotinylated first adapters with a code for DNA (e.g., la adapters) can be added to the sample nucleic acids and ligated to ssDNA using a DNA ligase. Ligation products can be immobilized on streptavidin beads.[000165] Excess la adapters can be washed off. First adapters with a code for RNA (lb adapters) can be added and ligated to ssRNA using an RNA ligase.[000166] In general, for each ligation (e.g., first ligation, second ligation, pre-denaturation ligation), a single general adapter or specific adapters can be used. In some embodiments, a single adapter is added to all nucleic acids in a ligation step. In some embodiments, a single adapter is added to a specific group of nucleic acids (e.g., only single- stranded or only doublestranded for a pre-denaturation ligation) in a ligation step. In some embodiments, different adapters can be added to specific groups of nucleic acids (e.g., ssDNA, ssRNA, dsDNA, or dsRNA). In some embodiments, selectivity can be achieved through enzymatic selectivity with a wash performed in between sequential enzymatic processes to remove excess unadapted adapters. In some embodiments, selectivity can be achieved through sequence-specific hybridization to different overhangs added by polymerases in the primer extension step. In some embodiments, a polymerase can attach an adapter sequence with a splint wherein a splint binds anywhere on the original strand and the polymerase performs the primer extension reaction, thus performing multiple processes concurrently.WSGR Docket No. 47697-746601Fragmentation & End Modification[000167] In some embodiments, the methods do not include fragmenting the nucleic acids, such as, in application with low quality samples or samples containing short fragments such as certain samples containing cell-free nucleic acids.[000168] In some embodiments, nucleic acids are fragmented. Fragmenting of the nucleic acids can be performed by e.g., mechanical shearing, passing the sample through a syringe, sonication, heat treatment, any other method in the art, or a combination thereof. In some embodiments, shearing can be performed by mechanical shearing (e.g., ultrasound, hydrodynamic shearing forces), enzymatic shearing (e.g., endonuclease), thermal fragmentation (e.g., incubation at high temperatures), chemical fragmentation (e.g., alkaline solutions, divalent ions). In some embodiments, fragmenting can be performed by using an enzyme, including a nuclease, or a transposase. Nucleases used for fragmenting comprise restriction endonucleases, homing endonucleases, nicking endonucleases, high fidelity restriction enzymes, or any enzyme disclosed herein.[000169] The ends of dsDNA fragments can be polished (e.g., blunt-ended). The ends of DNA fragments can be polished by treatment with a polymerase. Polishing can involve removal of 3' overhangs, fill-in of 5' overhangs, or a combination thereof. The polymerase can be a proofreading polymerase (e.g., comprising 3' to 5' exonuclease activity). The proofreading polymerase can be, e.g., a T4 DNA polymerase, Pol 1 Klenow fragment, or Pfu polymerase. Polishing can comprise removal of damaged nucleotides (e.g., abasic sites), using any means known in the art.Reduction of Adapter Dimers and Adapter By-Products[000170] Some methods can produce adapter dimers and adapter-derived by-products. Adapter dimers and adapter-derived by-products are two classes of unwanted products of a singlestranded library protocol that are generated by two distinct mechanisms.[000171] For example, the single-stranded nucleic acid library protocol developed by Gansauge et al. generates high concentration of adapter dimers and adapter-derived by- products, especially with input samples characterized by low nucleic acid concentration (See, Gansauge, MT and Meyer, M., Single-stranded DNA library preparation for the sequencing of ancient or damaged DNA, Nat Protoc. 2013 Apr;8(4):737-48 and Gansauge MT, Gerber T, Glocke I, Korlevic P, Lippik L, Nagel S, Riehl LM, Schmidt A, and Meyer M., Single- stranded DNA library preparation from highly degraded DNA using T4 DNA ligase, Nucleic Acids Res. 2017 Jun 2;45(10), each of which is incorporated by reference in their entirety herein, including any drawings).WSGR Docket No. 47697-746601[000172] One way to decrease adapter-derived by-products according to an embodiment of the disclosure comprises using an RNA splint oligonucleotide. In some embodiments, attaching a 3'- end adapter to the denatured nucleic acids and / or single-stranded nucleic acids comprises attaching said adapter with a splint oligonucleotide. In some embodiments, the splint oligonucleotide comprises a DNA splint oligonucleotide. In some embodiments, the splint oligonucleotide comprises an RNA splint oligonucleotide or a partial RNA splint oligonucleotide. In some embodiments, attaching a 3 '-end adapter to the denatured nucleic acids and / or single-stranded nucleic acids comprises ligating with a Splint-R ligase. In some embodiments, attaching a 3'-end adapter to the denatured nucleic acids further comprises adding an RNase inhibitor. In some embodiments, an adapter is attached through a primer extension reaction performed with a polymerase comprising DNA-dependent RNA-dependent polymerase, or a polymerase having non-templated activity.[000173] Some embodiments comprise preventing ligation of the 5' -end adapter to a complement synthesized during the primer extension reaction (set forth above) during a second ligation step. Some embodiments comprise preventing ligation of the 5' -end adapter to an adapter-derived side product. Digoxigenin can be introduced to the 5' -end of the splint oligo and an anti- digoxigenin antibody can be added to the bead-binding buffer during immobilization of adapted products. An anti-digoxigenin antibody can be added at any point prior to the second ligation. This will produce a bulky moiety at the 5' -end of any splint oligo attached to the biotinylated 3'-end adapter. This moiety will reduce the ability of T4 DNA ligase in a second ligation to ligate 5' -end adapter to splint oligo hybrid rendering it un-amplifiable in the final PCR step. It can also reduce the efficiency of primer-extension.[000174] Some embodiments comprise adding an antibody, such as an anti-digoxigenin antibody. In some embodiments, the anti-digoxigenin antibody is added after the 3'-end adapter is attached to the denatured nucleic acids and before a 5' -end adapter is attached. Some embodiments further comprise using beads comprising anti-digoxigenin antibody. Beads can be removed by, for example, without limitation, pelleting on a magnet. For example, an anti- digoxigenin antibody-coated magnetic bead can be added to deplete digoxiginated splint oligos as well as any unhybridized digoxiginated splint oligos. This can be followed by streptavidin- coated magnetic bead. In some embodiments, the anti-digoxigenin antibody is added during a separation step, annealing step, primary extension step, or second ligation step.Detection, Abundance, Bias, and Contamination[000175] Libraries of the disclosure can be used to distinguish populations or mixtures of nucleic acids, e.g. populations of cfDNA. Libraries of the disclosure can be used for detection.WSGR Docket No. 47697-746601Non-limiting examples of detection which can be used with the nucleic acid libraries set forth herein include various forms of sequencing, qPCR, ddPCR, microfluidic device, or microarray. Process Control Molecules[000176] One or more process control molecules can be added to a sample (e.g., initial sample, raw sample, etc.) for various reasons, for example, without limitation, in order to facilitate accuracy in the process of distinguishing one population of nucleic acids e.g. cfDNA from another (or multiple populations of nucleic acids from each other). In some cases, process control molecules can have special features such as specific sequences, lengths, GC content, degrees of degeneracy, degrees of diversity, secondary, tertiary, and quaternary structure, and / or known starting concentrations. In another embodiment, process control molecules can be used for normalizing signal in sample (e.g., an initial sample) in order to account for variations in sample processing. In some embodiments, process control molecules can be added during the library process itself, e.g., without limitation, dephosphorylation controls can be added before and after dephosphorylation or attachment control before and / or after the 3'-end adapter attachment step. Process control molecules can include, but are not limited to, ID Spike(s), Spanks, and / or Sparks or GC Spike-in Panel molecules. In some embodiments, process control molecules can comprise ID Spike(s), Spanks, and / or Sparks or GC Spike-in Panel molecules. [000177] ID Spike(s) refers to identification spikes used for sample identification tracking, distinguishing different populations of nucleic acids, e.g., distinguishing quantitatively or qualitatively, cross-contamination detection, reagent tracking, and / or reagent lot tracking (See, for example, US Patent no. 9,976,181). Spanks are degenerate pools of nucleic acids, or pools of nucleic acids with diverse sequences, used for diversity assessment and abundance calculation (id.). Sparks, “GC Spike-in Panel,” or “GC dSPARKS” are size or length markers which can be used for abundance, normalization, development and / or analysis purposes, process performance monitoring, and other purposes (id.).[000178] Process control molecules can additionally include molecules designed to monitor individual parts of a process. Process control molecules can additionally include dephosphorylation control molecules, denaturation control molecules, ligation control molecules, and / or control molecules for non-templated extension or template switching. Partially or fully phosphorylated control molecules (e.g., phosphorylated 5'-end and / or 3'-ends of the control nucleic acids), control molecules with adapter sequences pre-attached (e.g., an example of a control molecule that is added after 3'-end adapter attachment step) can be added during the library process itself, e.g., a dephosphorylation control performed post dephosphorylation, or an adapter attachment control performed post 3'-end adapter attachment step. In someWSGR Docket No. 47697-746601 embodiments, process control molecules comprise dephosphorylation control molecules, denaturation control molecules, and / or ligation control molecules.Sequencing[000179] Some embodiments comprise sequencing the nucleic acid libraries of the current disclosure to generate sequencing information. Some embodiments further comprise a computer comprising software that performs bioinformatics analysis on the sequence information. Bioinformatics analysis comprises without limitation, assembling sequence data, detecting and quantifying genetic variants in a sample, including germline variants and somatic cell variants (e.g., a genetic variation associated with cancer or a pre- cancerous condition, a genetic variation associated with infection), detecting species or strain of microbes, detecting microbes at a certain taxonomic level (e.g., order, family, genus, species, strain) detecting presence and measuring the abundance of microbe nucleic acids, detecting presence and measuring the abundance of therapeutic nucleic acids, detecting site of infection, detecting risk of transplant rejection, detecting state of infection, and / or detecting potential for drug resistance.[000180] Sequencing can be used to analyze nucleic acids; particularly different forms of nucleic acids present in the same sample. Such analytical methods include sequencing the nucleic acids as well as bioinformatics analysis of the sequencing results. Sequencing results can be analyzed to obtain various types of information including genomic and RNA expression. Generally, analyses provided herein allow for simultaneous analysis of DNA and RNA in a sample, as well as both single- and double-stranded nucleic acids in a sample.[000181] In some embodiments, the analysis detects both DNA and RNA yet does not distinguish between the two. In some embodiments, the analysis detects both DNA and RNA (or double- and single-stranded nucleic acids) and also identifies whether the originating molecules are DNA, RNA, ssDNA, dsDNA, ssRNA, dsRNA, or any combination of the molecules. Often, distinguishing is accomplished by detecting markers added by using a combination of adapters specific to a molecule type of interest and / or appropriate enzyme that facilitate and enhance discrimination between different nucleic acid types (RNA vs DNA, single- vs double-stranded). [000182] Sequencing can be by any method known in the art. Sequencing methods include, but are not limited to, Maxam-Gilbert sequencing-based techniques, chain- termination-based techniques, shotgun sequencing, bridge PCR sequencing, single-molecule real-time sequencing, ion semiconductor sequencing (e.g., Ion Torrent sequencing), nanopore sequencing, pyrosequencing (454), sequencing by synthesis, sequencing by ligation (SOLiD sequencing), sequencing by electron microscopy, dideoxy sequencing reactions (Sanger method), massively parallel sequencing, polony sequencing, and DNA nanoball sequencing. The term “NextWSGR Docket No. 47697-746601Generation Sequencing (NGS)” herein refers to sequencing methods that allow for massively parallel sequencing of nucleic acid molecules during which a plurality, e.g., millions, of nucleic acid fragments from a single sample or from multiple different samples are sequenced simultaneously. Non-limiting examples of NGS include sequencing- by-synthesis, sequencing- by-ligation, real-time sequencing, and nanopore sequencing. In some embodiments, sequencing involves hybridizing a primer to the template to form a template / primer duplex, contacting the duplex with a polymerase enzyme in the presence of detectably labeled or unlabeled nucleotides under conditions that permit the polymerase to add labeled or unlabeled nucleotides to the primer in a template-dependent manner, detecting a signal from the incorporated labeled nucleotide or detecting a signal resulting from the process of incorporating labeled or unlabeled nucleotide (e.g., proton release), and sequentially repeating the contacting and / or detecting at least once, wherein sequential detection of incorporated labeled or unlabeled nucleotide determines the sequence of the nucleic acid.[000183] Exemplary detectable labels include radiolabels, fluorescent labels, protein labels, dye labels, or enzymatic labels. In some embodiments, the detectable label can be an optically detectable label, such as a fluorescent label. Exemplary fluorescent labels include cyanine, rhodamine, fluorescein, coumarin, BODIPY, alexa, or conjugated multi-dyes.[000184] In some embodiments, the sequencing comprises obtaining paired end reads. In some embodiments, the sequencing comprises obtaining consensus reads.[000185] The accuracy or average accuracy of the sequence information can be greater than about 80%, about 90%, about 95%, about 99%, about 99.98%, or about 99.99%. The sequence accuracy or average accuracy can be greater than about 95% or about 99%. The sequence coverage can be greater than about 0.00001-fold, 0.0001-fold, 0.001-fold, about 0.01-fold, about 0.1-fold, about 0.5-fold, about 0.7-fold, or about 0.9-fold. The sequence coverage can be less than about 200,000-fold, about 100,000-fold, about 10,000-fold, about 1,000-fold, or about 500- fold.[000186] In some embodiments, the sequence information obtained per nucleic acid template is more than about 10 base pairs, about 15 base pairs, about 20 base pairs, about 50 base pairs, about 100 base pairs, or about 200 base pairs. The sequence information can be obtained in less than 1 month, 2 weeks, 1 week, 2 days, 1 day, 14 hours, 10 hours, 3 hours, 1 hour, 30 minutes, 10 minutes, or 5 minutes.[000187] Although the Examples (below) may use specific sequences for certain sequencing systems, e.g., Illumina systems, it will be understood that the reference to these sequences is for illustration purposes only. For example, the methods described herein are not exhaustive and canWSGR Docket No. 47697-746601 be configured for use with other sequencing systems incorporating specific priming, attachment, index, and other operational sequences used in those systems, e.g., systems available from Ion Torrent, Oxford Nanopore, Genia Technologies, Pacific Biosciences, Complete Genomics, and the like.Microbe or Pathogen Detection and Quantification[000188] Nucleic acid libraries set forth herein can be used for a variety of applications including personalized medicine. Specifically, the nucleic acid libraries can be used to detect, monitor, diagnose, prognose, guide treatment, or predict the risk of disease. Exemplary applications are provided below.[000189] The methods can be used for to distinguish populations of nucleic acids or for detecting a pathogenic infection in a subject, as well as the symbiotic presence of microbes in a host, such as commensals and a normal host microbiome. In some embodiments, the methods can provide a more comprehensive view of the state and diversity of the infection or symbiotic microbes in a subject. For example, the identification of both RNA and DNA in a sample can be useful to detect RNA and DNA type viruses, or to detect bacterial, protist, parasitic or fungal genomic DNA and / or gene expression products, e.g., mRNA. Such process can also be able to differentiate between latent infection e.g., which might be indicated by the presence of integrated retroviral DNA) versus active infection (e.g., which might be indicated by the presence of viral RNA from intact viral particles). Such processes can also be able to detect drug resistance and / or the origin of infection. Such processes can also be used to analyze host response. Such analyses can include analysis of cell-free, circulating nucleic acids, e.g., for microbial or viral infection identification.[000190] In an infected sample, nucleic acid forms within a given sample can include a variety of different structural forms and hybrids of those forms, including DNA and RNA, single and double-stranded forms of these, and structured and unstructured forms of these. By way of example, in the case of pathogen identification, it will be appreciated that pathogenic organisms can include a variety of chemical and / or structural forms of nucleic acids that can be used in their identification. As another example, pathogenic organisms can also include chemical modifications of DNA and RNA, some which can confer pathogenicity or make a pathogenic microbe harmless.[000191] In some embodiments, the nucleic acid library from the sample is sequenced and assessed for detecting a pathogenic infection in a subject, as well as the symbiotic presence of microbes in a host, such as commensals and a normal host microbiome.Kits and SystemsWSGR Docket No. 47697-746601[000192] In some cases, this disclosure provides kits and systems. The kits and / or systems can be used, for example, to enrich for a particular population of nucleic acids (e.g., microbial cell- free DNA) present in a mixture. In some cases, the kits and / or systems are used to identify a particular population of nucleic acids (e.g., microbial cell-free DNA) present in a mixture (e.g., a mixture of human and microbial cell-free DNA).[000193] In some instances, the kit further comprises a kinase. For example, the kit can comprise a PNK kinase. In some cases, the kit comprises a ligase (e.g., T4 ligase). In some cases, the kit further comprises a uracil DNA glycosylase (UDG). In some cases, the kit further comprises an endonuclease. In some cases, the endonuclease is DNA glycosylase-lyase Endonuclease VIII.[000194] In some cases, the kit comprises one or more process control molecules. For example, the kit can comprise SPANKs, SPARKs, ID SPIKEs, or other process control molecules described herein.[000195] In some cases, the oligonucleotides and / or reagents in a kit provided herein are present in a buffer. In some cases, they are lyophilized.[000196] The kit or system can further comprise a software package for data analysis, which can include reference profiles for comparison with the test profile from a clinical sample, and in particular can include reference databases.[000197] In some cases, the kit (or kits) can include instructions on how to use the kit; the instructions can be recorded on any suitable recording medium, including but not limited to paper, electronic format, etc. Instructions can be present in the kit as a package insert, in the labeling of the container of the kit, or kit components thereof (e.g., associated with the packaging or sub packaging), etc. In some embodiments, the instructions can be obtained virtually or remotely and can be downloadable or printable including but not limited to via the internet, email, fax, etcetera, process.[000198] The kit can comprise reagents that can be used to isolate the different population of nucleic acids. The kit can comprise specific instructions regarding use of each of the oligos, reagents and handling of such. The kit can provide instructions to direct the purification or isolation, purification of nucleic acids herein, e.g. the purification of cfDNA or sample DNA and further instructions on how to proceed with any amplification reactions, sequencing reactions etcetera including any analytical procedures.[000199] Such kits or systems can also include information, such as scientific literature references, package insert materials, clinical trial results, and / or summaries of these and the like. Such kits or systems can also include instructions to access a database. Kits or systems describedWSGR Docket No. 47697-746601 herein can be provided, marketed and / or promoted to health providers, including physicians, nurses, pharmacists, formulary officials, and the like. Kits or system can also be marketed directly to the consumer.[000200] The kit or system can further comprise an apparatus for detection and / or computer control systems with machine-executable instructions to implement the methods. In some embodiments, computer control systems are further programmed for conducting genetic analysis. Detection systems that can be used including, but are not limited to, sequencing, digital PCR, ddPCR, quantitative PCR (e.g., real-time PCR), or by a microfluidic device, microarray, or the like.Hardware Systems[000201] A kit or system can include a nucleic acid sequencer (e.g., DNA sequencer, RNA sequencer) for generating DNA or RNA sequence information. The kit or system can further include a computer comprising software that performs bioinformatics analysis on the DNA or RNA sequence information. Bioinformatics analysis can include, without limitation, assembling sequence data, detecting and quantifying genetic variants in a sample, including germline variants and somatic cell variants (e.g., a genetic variation associated with cancer or pre- cancerous condition, a genetic variation associated with infection), or used to distinguish populations of nucleic acids or in detecting the presence and measuring the abundance of microbe nucleic acids, detecting site of infection, detecting the state of infection, detecting the risk of organ rejection in a transplant patient, and / or detecting potential for drug resistance. One skilled in the art would appreciate other bioinformatics analysis.[000202] Sequencing data can be used to determine genetic sequence information, such as, for example, without limitation, species information, ploidy states, the identity of one or more genetic variants, as well as a quantitative measure of the variants, including relative and absolute relative measures. The sequencing can be unbiased and can involve sequencing all, substantially all, or some (e.g., greater than about 0.01%, about 0.1%, about 0.2%, about 0.3%, about 0.4%, about 0.5%, about 0.6%, about 0.7%, about 0.8%, about 0.9%, about 1%, about 2%, about 3%, about 4%, about 5%, about 6%, about 7%, about 8%, about 9%, about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, about 80%, or about 90%) of the nucleic acids in a sample. Sequencing can be selective, e.g., directed to portions of the genome of interest. For example, many select genes (and mutant forms of these genes) are known to be associated with antibiotic resistance, drug resistance, genetic disorders, and various cancers. Many select genes (and mutant forms of these genes) associated with antibiotic resistance, drug resistance, genetic disorders, and various cancers are also known to be amplified. Sequencing ofWSGR Docket No. 47697-746601 the select genes, portions of genes, or non- genes along with other genes or sequences can suffice for the analysis desired. Polynucleotides mapping to specific loci in the genome that are the subject of interest can be isolated for sequencing by, for example, sequence capture or sitespecific amplification.Computer Control Systems[000203] The kit or system can also include computer control systems with machine- executable instructions to implement the methods. FIG. 1 shows a computer system 1101 that is programmed or otherwise configured to implement methods of the present disclosure The computer system 1101 includes a central processing unit (CPU, also “processor” and “computer processor” herein) 1105, which can be a single core or multi core processor, or a plurality of processors for parallel processing. The computer system 1101 also includes memory or memory location 1110 (e.g., random-access memory, read-only memory, flash memory), electronic storage unit 1115 (e.g., hard disk), communication interface 1120 (e.g., network adapter) for communicating with one or more other systems, and peripheral devices 1125, such as cache, other memory, data storage and / or electronic display adapters.[000204] The memory 1110, storage unit 1115, interface 1120, and peripheral devices 1125 are in communication with the CPU 1105 through a communication bus (solid lines), such as a motherboard. The storage unit 1115 can be a data storage unit (or data repository) for storing data.[000205] The computer system 1101 can be operatively coupled to a computer network (“network”) 1130 with the aid of the communication interface 1120. The network 1130 can be the Internet, an internet and / or extranet, or an intranet and / or extranet that is in communication with the Internet. The network 1130 in some embodiments is a telecommunication and / or data network. The network 1130 can include one or more computer servers, which can enable distributed computing, such as cloud computing.[000206] The network 1130, in some embodiments with the aid of the computer system 1101, can implement a peer-to-peer network, which can enable devices coupled to the computer system 1101 to behave as a client or a server.[000207] The CPU 1105 can execute a sequence of machine-readable instructions, which can be embodied in a program or software. The instructions can be stored in a memory location, such as the memory 1110. The instructions can be directed to the CPU 1105, which can subsequently program or otherwise configure the CPU 1105 to implement methods of the present disclosure. Examples of operations performed by the CPU 1105 can include fetch, decode, execute, and writeback.WSGR Docket No. 47697-746601[000208] The CPU 1105 can be part of a circuit, such as an integrated circuit. One or more other components of the system 1101 can be included in the circuit. In some embodiments, the circuit is an application specific integrated circuit (ASIC).[000209] The storage unit 1115 can store files, such as drivers, libraries, and saved programs. The storage unit 1115 can store user data, e.g., user preferences and user programs. The computer system 1101 in some embodiments can include one or more additional data storage units that are external to the computer system 1101, such as located on a remote server that is in communication with the computer system 1101 through an intranet or the Internet.[000210] The computer system 1101 can communicate with one or more remote computer systems through the network 1130. For instance, the computer system 1101 can communicate with a remote computer system of a user. Examples of remote computer systems include personal computers (e.g., portable PC), slate or tablet PC's (e.g., APPLE® iPad, SAMSUNG® Galaxy Tab), telephones, Smart phones (e.g., APPLE® iPhone, Android- enabled device, BLACKBERRY®), or personal digital assistants. The user can access the computer system 1101 via the network 1130.[000211] The kit or system can be implemented by way of machine (e.g., computer processor) executable code stored on an electronic storage location of the computer system 1101, such as, for example, on the memory 1110 or electronic storage unit 1115. The machine executable or machine-readable code can be provided in the form of software. During use, the code can be executed by the processor 1105. In some embodiments, the code can be retrieved from the storage unit 1115 and stored on the memory 1110 for ready access by the processor 1105. In some situations, the electronic storage unit 1115 can be precluded, and machine-executable instructions are stored on memory 1110.[000212] The code can be pre-compiled and configured for use with a machine having a processor adapted to execute the code or can be compiled during runtime. The code can be supplied in a programming language that can be selected to enable the code to execute in a precompiled or as-compiled fashion.[000213] Parts of the kits and systems, such as the computer system 1101, can be embodied in programming. Various aspects of the technology can be thought of as “products” or “articles of manufacture” typically in the form of machine (or processor) executable code and / or associated data that is carried on or embodied in a type of machine readable medium. Machine-executable code can be stored on an electronic storage unit, such as memory (e.g., read-only memory, random-access memory, flash memory) or a hard disk. “Storage” type media can include any or all of the tangible memory of the computers, processors or the like, or associated modulesWSGR Docket No. 47697-746601 thereof, such as various semiconductor memories, tape drives, disk drives and the like, which can provide non-transitory storage at any time for the software programming. All or portions of the software can at times be communicated through the Internet or various other telecommunication networks. Such communications, for example, can enable loading of the software from one computer or processor into another, for example, from a management server or host computer into the computer platform of an application server. Thus, another type of media that can bear the software elements includes optical, electrical, and electromagnetic waves, such as used across physical interfaces between local devices, through wired and optical landline networks and over various air-links. The physical elements that carry such waves, such as wired or wireless links, optical links, or the like, also can be considered as media bearing the software. As used herein, unless restricted to non-transitory, tangible “storage” media, terms such as computer or machine “readable medium” refer to any medium that participates in providing instructions to a processor for execution.[000214] Hence, a machine readable medium, such as computer-executable code, can take many forms, including but not limited to, a tangible storage medium, a carrier wave medium or physical transmission medium. Non-volatile storage media include, for example, optical or magnetic disks, such as any of the storage devices in any computer(s) or the like, such as can be used to implement the databases, etc. shown in the drawings. Volatile storage media include dynamic memory, such as main memory of such a computer platform. Tangible transmission media include coaxial cables; copper wire and fiber optics, including the wires that comprise a bus within a computer system. Carrier-wave transmission media can take the form of electric or electromagnetic signals, or acoustic or light waves such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media therefore include for example: a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD- ROM, DVD or DVD-ROM, any other optical medium, punch cards paper tape, any other physical storage medium with patterns of holes, a RAM, a ROM, a PROM and EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave transporting data or instructions, cables or links transporting such a carrier wave, or any other medium from which a computer can read programming code and / or data. Many of these forms of computer readable media can be involved in carrying one or more sequences of one or more instructions to a processor for execution.[000215] The computer system 1101 can include or be in communication with an electronic display 1135 that comprises a user interface (UI) 1140 for providing, an output of a report, which can include a diagnosis of a subject or a therapeutic intervention for the subject. ExamplesWSGR Docket No. 47697-746601 of UI's include, without limitation, a graphical user interface (GUI) and web-based user interface. The analysis can be provided as a report. The report can be provided to a subject, to a health care professional, a lab-worker, or other individual.[000216] Methods and systems of the present disclosure can be implemented by way of one or more algorithms. An algorithm can be implemented by way of software upon execution by the central processing unit 1105. The algorithm can, for example, facilitate the enrichment, sequencing and / or detection of pathogen or microbe or other target nucleic acids.[000217] Information about a patient or subject can be entered into a computer system, for example, patient background, patient medical history, or medical scans. The computer system can be used to analyze results from a method described herein, report results to a patient or doctor, or come up with a treatment plan.[000218] In some embodiments, machine learning (ML) may be applied to the methods and the systems disclosed herein. For example, ML may be used in predicting a risk of a certain medical condition in a user. Further, for example, ML may be used in predicting symptoms in a user. Further, for example, ML may be used in predicting an effective treatment for a user. To accomplish these example predictions, ML may analyze one or more of: research data, genealogical data, medical data, demographic data, geographic data, assay data, etc.[000219] In some cases, ML may generally involve identifying and recognizing patterns in existing data in order to facilitate making predictions for subsequent data. ML may include a ML model (which may include, for example, a ML algorithm). Machine learning, whether analytical or statistical in nature, may provide deductive or abductive inference based on real or simulated data. The ML model may be a trained model. ML techniques may comprise one or more supervised, semi-supervised, self-supervised, or unsupervised ML techniques. For example, an ML model may be a trained model that is trained through supervised learning (e.g., various parameters are determined as weights or scaling factors). ML may comprise one or more of regression analysis, regularization, classification, dimensionality reduction, ensemble learning, meta learning, association rule learning, cluster analysis, anomaly detection, deep learning, or ultra-deep learning. ML may comprise: k-means, k-means clustering, k-nearest neighbors, learning vector quantization, linear regression, non-linear regression, least squares regression, partial least squares regression, logistic regression, stepwise regression, multivariate adaptive regression splines, ridge regression, principal component regression, least absolute shrinkage and selection operation (LASSO), least angle regression, canonical correlation analysis, factor analysis, independent component analysis, linear discriminant analysis, multidimensional scaling, non-negative matrix factorization, principal components analysis, principal coordinatesWSGR Docket No. 47697-746601 analysis, projection pursuit, Sammon mapping, t-distributed stochastic neighbor embedding, AdaBoosting, boosting, gradient boosting, bootstrap aggregation, ensemble averaging, decision trees, conditional decision trees, boosted decision trees, gradient boosted decision trees, random forests, stacked generalization, Bayesian networks, Bayesian belief networks, naive Bayes, Gaussian naive Bayes, multinomial naive Bayes, hidden Markov models, hierarchical hidden Markov models, support vector machines, encoders, decoders, auto-encoders, stacked autoencoders, perceptrons, multi-layer perceptrons, artificial neural networks, feedforward neural networks, convolutional neural networks, recurrent neural networks, residual neural networks, physics-informed neural networks, long short-term memory, deep belief networks, deep Boltzmann machines, deep convolutional neural networks, deep recurrent neural networks, large language models, transformer models, vision transformers, or generative adversarial networks. [000220] Training the ML model may include, in some cases, selecting one or more untrained data models to train using a training data set. The selected untrained data models may include any type of untrained ML models for supervised, semi-supervised, self-supervised, or unsupervised machine learning. The selected untrained data models may be specified based upon input (e.g., user input) specifying relevant parameters to use as predicted variables or other variables to use as potential explanatory variables. For example, the selected untrained data models may be specified to generate an output (e.g., a prediction) based upon the input. Conditions for training the ML model from the selected untrained data models may likewise be selected, such as limits on the ML model complexity or limits on the ML model refinement past a certain point. The ML model may be trained (e.g., via a computer system such as a server) using the training data set. In some cases, a first subset of the training data set may be selected to train the ML model. The selected untrained data models may then be trained on the first subset of training data set using appropriate ML techniques, based upon the type of ML model selected and any conditions specified for training the ML model. In some cases, due to the processing power requirements of training the ML model, the selected untrained data models may be trained using additional computing resources (e.g., cloud computing resources). Such training may continue, in some cases, until at least one aspect of the ML model is validated and meets selection criteria to be used as a predictive model.[000221] In some cases, one or more aspects of the ML model may be validated using a second subset of the training data set (e.g., distinct from the first subset of the training data set) to determine accuracy and robustness of the ML model. Such validation may include applying the ML model to the second subset of the training data set to make predictions derived from the second subset of the training data. The ML model may then be evaluated to determine whetherWSGR Docket No. 47697-746601 performance is sufficient based upon the derived predictions. The sufficiency criteria applied to the ML model may vary depending upon the size of the training data set available for training, the performance of previous iterations of trained models, or user-specified performance requirements. If the ML model does not achieve sufficient performance, additional training may be performed. Additional training may include refinement of the ML model or retraining on a different first subset of the training dataset, after which the new ML model may again be validated and assessed. When the ML model has achieved sufficient performance, in some cases, the ML may be stored for present or future use. The ML model may be stored as sets of parameter values or weights for analysis of further input (e.g., further relevant parameters to use as further predicted variables, further explanatory variables, further user interaction data, etc.), which may also include analysis logic or indications of model validity in some instances. In some cases, a plurality of ML models may be stored for generating predictions under different sets of input data conditions. In some cases, the ML model may be stored in a database (e.g., associated with a server).[000222] In some embodiments, the methods and the systems disclosed herein improve predictive power of ML by using a combination of features to more robustly form predictions. For example, the first feature may be an expanded training set to train a neural network. This expanded training set may be developed by applying mathematical transformation functions on an acquired set of training data. These transformations can include affine transformations, for example, rotating, shifting, or mirroring or filtering transformations, for example, smoothing or contrast reduction. The neural networks may then be trained with this expanded training set (e.g., using stochastic learning with backpropagation, which is a type of machine learning algorithm that uses the gradient of a mathematical loss function to adjust the weights of the network). The introduction of an expanded training set may however increase false positives when classifying data outside the training data. Accordingly, the second feature of the methods and the systems disclosed herein is the minimization of these false positives by performing an iterative training algorithm, in which the ML model may be retrained with an updated training set containing the false positives produced after prediction has been performed on a set of non-training data. This combination of features provides a robust prediction model with limited false positives.Accordingly, training the ML model may comprise: (A) obtaining a first set of training data; (B) training a machine learning model on the first set of training data; (C) obtaining a second set of training data; and (D) training the machine learning model on the second set of training data. For example, the second training data may comprise or correspond to at least some of the first training data. Further, for example, one or both of the first set of training data or the second setWSGR Docket No. 47697-746601 of training data may be transformed, such as by one or more operations: mirroring, rotating, smoothing, filtering, shifting, thresholding, contrast adjusting, etc.Definitions[000223] Unless defined otherwise, all technical and scientific terms used herein have the meaning commonly understood by a person skilled in the art to which this disclosure belongs. [000224] “A,” “an,” and “the”, as used herein, can include plural references unless expressly and unequivocally limited to one reference.[000225] As used herein, the term “or” is used to refer to a nonexclusive “or”; as such, “A or B” includes “A but not B,” “B but not A,” and “A and B,” unless otherwise indicated.[000226] As used throughout the specification herein, the term “about” when referring to a number or a numerical range means that the number or numerical range referred to is an approximation within experimental variability (or within statistical experimental error), and the number or numerical range can vary from, for example, from 10% to 25% of the stated number or numerical range. In examples, the term “about” refers to ±20% of a stated number or value. In other examples, the departure from equimolarity in the case of mixes intended to be equimolar, such as but not limited to, some control molecules in the spike-in mixes, is no more than a tenfold disparity, an eight-fold disparity, a six-fold disparity, a four-fold disparity or a two-fold disparity.[000227] As used herein, “abundance” refers to the quantity of something, such as, for example, the quantity or number of molecules, such as nucleic acids. As used herein, “relative abundance” is the abundance of a molecule or molecules of interest per abundance of a reference molecule or molecules of interest. For example, relative abundance of target nucleic acid molecules (e.g., pathogen nucleic acid molecules, fetal nucleic acid molecules, tumor-derived nucleic acid molecules, etc.) refers to abundance per reference nucleic acids (e.g., human nucleic acids, synthetic nucleic acid added to the sample, etc.). As used herein, “absolute abundance” is the abundance of molecules per a defined unit of sample or sample quantity. For example, absolute abundance of target nucleic acid molecules (e.g., microbe or pathogen molecules, fetal nucleic acid molecules, tumor-derived nucleic molecules, etc.) refers to the abundance per defined unit of sample quantity (e.g., sample volume, sample mass, etc.).[000228] As used herein, “antibody” refers to a type of immunoglobulin molecule and is used in the broadest sense to include intact antibodies as well as antibody fragments.[000229] As used herein, antibodies comprise at least one antigen-binding domain. For example, an antibody as described herein can have an antigen binding domain or antigen bindingWSGR Docket No. 47697-746601 region, the antigen binding domain or antigen binding region being specific for an antigen. In some embodiments, the antigen is a bulky moiety, such as digoxigenin.[000230] As used herein, “adapter” or “portions of an adapter” refers to a chemically synthesized, single-stranded, or double-stranded oligonucleotide that can be attached, e.g., covalently (e.g., ligation) or non-covalently (e.g., hybridization), to the ends of nucleic acid molecules, such as DNA or RNA molecules. Adapter can refer to either a full-length adapter or a portion of the adapter, e.g., partial adapters can be attached in some embodiments before the full-lengths are introduced by e.g., indexing primers in amplification steps. 3 '-end adapters and 5'-end adapters can be full-length or a portion of an adapter sequence that are attached to the opposite ends of a target nucleic acid, a copy of a target nucleic acid, or a target nucleic acid complement. 3'-end adapters and 5'-end adapters sequences end up being attached to the opposite ends of e.g., a template that can be sequenced that comprises target nucleic acid, a copy of a target nucleic acid, and / or a target nucleic acid complement. The 3'-end adapter and 5'- end adapter sequences can be the same or they can be different. Adapter sequences can be of any length.[000231] As used herein, “bulky moiety” refers to a molecule that takes up more space than is conventionally required or a molecule that forms a complex that takes up more space than is conventionally required. A bulky moiety can comprise any reactive group capable of forming covalent, non-covalent, or coordinating chemical bonds. In some embodiments, the bulky moiety comprises one or more azide groups and products of reactions with azide groups, one or more small molecules, one or more polyhistidine tags, one or more antigens, and / or one or more proteins. In some embodiments, the bulky moiety comprises digoxigenin. In some embodiments, the splint oligonucleotide with a bulky moiety comprises 5Sp9 / A / iDiGN / A / iSp9 / CTTCCGATCTNNNNNN / 3AmMO (SEQ ID: 1), using designations for oligomer modifications adopted from designation convention used by IDT (Coralville, IA; idtdna website). A bulky moiety for example, can include a functional group that is sterically hindering and can prevent certain enzymatic or chemical reactions from occurring. A bulky group can block a position. A bulky group can also affect a molecule's shape and reactivity and so prevent a reaction from occurring through the steric hindrance. Moieties attached to the groups by covalent, non-covalent or coordinating bonds can provide the bulkiness of the groups. For example, a bulky molecule such as a protein or polymer can be attached covalently to an azide group; a bulky entity such as a bead, protein or polymer can be attached to a his-tag through coordinating bonds using Ni ions; or an antigen antibody can be attached to an antigen attached to an adapter such as an anti-digoxigenin antibody can be attached to digoxigenin.WSGR Docket No. 47697-746601Examples of bulky moi eties can also include, but are not limited to, complexes between any of the molecules disclosed herein and their respective binding and reaction partners including, for example, without limitation, complexes between digoxigenin and an anti-digoxigenin antibody; polyhistidine tag and a Ni- NTA-containing polymer; a protein and a binding partner; an azide group and a covalently bound large molecule; and the biotin and streptavidin complex. Additional examples of bulky molecules include, for example, without limitation, biotin, azide groups and products of reactions with azide groups, one or more small molecules, one or more polyhistidine tags, and / or one or more proteins. Some embodiments further comprise introducing a bulky moiety into the splint oligonucleotide. Some embodiments further comprise introducing a bulky moiety on the template switching oligos; such bulky moieties can reduce concatemer formation. The bulky moiety can be introduced at a position that has the lowest effect on adapter attachment efficiency, such as the 5'-end region of the splint oligonucleotide, close to the 5'-end region of the splint oligonucleotide, or away from the ligation junction in ligation-based adapter attachment reactions.[000232] As used herein, “control” refers to a standard of comparison. A “negative control” refers to a standard of comparison that is used to identify contaminants from samples or to identify the nature of a signal in the absence of a sample. A “positive control” refers to a standard of comparison that is used to identify normal substances from a sample or sample. Some embodiments of the disclosure comprise a positive and / or negative control. Some embodiments of the disclosure comprise a sample or samples without a positive and / or negative control. Some embodiments of the disclosure comprise a sample or samples without a positive control. Some embodiments of the disclosure comprise a sample or samples without a negative control.[000233] As used herein, “denaturing” refers to a process in which biomolecules, such as proteins or nucleic acids, lose their native or higher order structure. Native and higher order structure can include, for example, without limitation, quaternary structure, tertiary structure, or secondary structure. For example, a double-stranded nucleic acid molecule can be denatured into two single-stranded molecules.[000234] As used herein, the term “dephosphorylation” or “dephosphorylating” refers to removal of a terminal phosphate group, such as the 5'- and / or 3'-end phosphate, from a nucleic acid, such as DNA to generate 5'- and / or 3'-hydroxyl groups.[000235] As used herein, “detect” refers to quantitative or qualitative detection, including, without limitation, detection by identifying the presence, absence, quantity, frequency, concentration, sequence, form, structure, origin, or amount of an analyte.WSGR Docket No. 47697-746601[000236] As used herein, “digoxigenin” refers to a bulky molecule or its complex comprising the structure:[000237] As used herein, “isolation” or “purification” and their cognates, of nucleic acids refers to processes (e.g., elution) performed after the start of and in the generation of a nucleic acid library that separate the nucleic acid from at least one component with which it is normally associated (e.g., a ligase or a polymerase).[000238] As used herein, “removal” or “extraction,” and their cognates, of nucleic acids refers to processes performed prior to the start of generating or preparing a nucleic acid library that separate nucleic acids from at least one component with which they are normally associated. Removal or extraction of nucleic acids can refer to the process of creating a sample from a raw biological sample. For example, without limitation, the fractionation of whole blood into its component parts, such as plasma, can be considered to involve removal or extraction. Similarly, purification or isolation of DNA from a sample (e.g., plasma sample) can be considered extraction.[000239] As used herein, “GC-bias” refers to differential performance (e.g., amplification) or treatment of nucleic acids having different GC content but identical length.[000240] As used herein, “GC-contenf ’ or “guanine-cytosine content” refer to the percentage or quantity of nitrogenous bases in a nucleic acid, such as a DNA or RNA molecule, that are either guanine or cytosine or their chemical modifications.[000241] As used herein, “host” refers to an organism that harbors another organism or microbe. For example, a living thing e.g. a mammal such as a human being can be a host that harbors a microbe or pathogen, the microbe or pathogen being the non-host.[000242] As used herein, the phrase “identifying sequence element” or “identifying tag” refers to an element of a sequence that identifies an index, a code, a barcode, a random sequence, an adapter, an overhang of non-templated nucleic acids, a tag comprising one or more non- templated nucleotides, a priming sequence, unique molecular identifiers, or any combination thereof.WSGR Docket No. 47697-746601[000243] As used herein, “KI enow fragment” refers to a large protein fragment of DNA polymerase I that retains the 5' - 3' polymerase activity and the 3' - 5' exonuclease activity for removal of precoding nucleotides and proofreading but loses its 5' - 3' exo...

Claims

1. WSGR Docket No. 47697-746601CLAIMSWHAT IS CLAIMED IS:

1. A method of processing cell-free nucleic acids (cfNA) in a sample, the method comprising: providing a sample derived from a subject, wherein the sample comprises cell-free nucleic acids (cfNA); and(a) detecting an oxidative stress marker present in the cfNA;(b) conducting a nucleic acid (NA) library preparation to enrich the sample for either cfNA comprising an oxidative stress marker or for cfNA that does not comprise an oxidative stress marker; or(c) a combination of (a) and (b).

2. The method of claim 1, wherein the oxidative stress marker comprises a member selected from the group consisting of:(a) a nick in a strand of the cfNA;(b) a gap in a strand of the cfNA;(c) a substitution of a nucleotide or a component thereof in the cfNA for:(i) an 8-hydroxydeoxyguanosine;(ii) an 8-hydroxyguanine;(iii) an 8-hydroxy 2-deoxyguanosine;(iv) a thymine glycol;(v) a 5-hydroxymethyluracil;(vi) a formylamidopyrimidine;(vii) a 8-hydroxydeoxyadenine;(viii) an 8-oxo-adenine (8-oxoA);(ix) an isoguanine;(x) a formamidopyrimidine-A (FapyA);(xi) a 5' -Phosphoglycolate (5' -PG);(xii) a 5' -Hydroxyl (5' -OH);(xiii) a 5' -Phosphate (5' -P);(xiv) a 5' -Aldehyde;(xv) a 5' -Deoxyribonolactone-Derived Termini; or(xvi) any combination of (i) - (xv); or(d) a non-Watson-Crick base pair; and(e) any combination of (a) - (d).WSGR Docket No. 47697-7466013. The method of claim 1 or 2, wherein the cfNA comprises host cell-free NA (hcfNA) and microbial cell-free NA (mcfNA).

4. The method of claim 3, wherein detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the mcfNA.

5. The method of claim 3 or 4, wherein the conducting the NA library preparation comprises enriching the sample for mcfNA by enriching for cfNA comprising an oxidative stress marker.

6. The method of any one of claims 3-5, wherein detecting an oxidative stress marker present in the cfNA comprises detecting an oxidative stress marker present in the hcfNA.

7. The method of any one of claims 3-6, wherein the conducting the nucleic acid library preparation comprises enriching the sample for hcfNA by enriching for cfNA that does not comprise an oxidative stress marker.

8. The method of any one of claims 1-7, wherein the detecting comprises a binding reaction.

9. The method of claim 8, wherein the binding reaction comprises binding the oxidative stress marker with a chemical reagent.

10. The method of claim 8, wherein the binding reaction comprises binding the oxidative stress marker with a binding agent.

11. The method of claim 10, wherein the binding agent comprises a protein, an antibody, an antibody fragment, a portion of an antibody, a functionally active fragment of an antibody, a ligase, an aptamer, or a combination thereof.

12. The method of claim 10, wherein the antibody, the antibody fragment, or the combination thereof binds to 8-hydroxy deoxy guanosine, 8-hydroxy guanine, 8-hydroxy 2- deoxyguanosine, thymine glycol, 5-hydroxymethyluracil, formylamidopyrimidine, or 8- hydroxydeoxy adenine.

13. The method of claim 10, wherein the binding agent comprises a NA binding domain.

14. The method of claim 10, wherein the binding agent comprises a zinc-finger domain.

15. The method of any one of the preceding claims, further comprising sequencing the cfNA to generate sequence reads.

16. The method of claim 15, wherein the sequencing is performed prior to the detecting the oxidative stress marker present in the cfNA.

17. The method of claim 15, wherein the sequencing comprises massively parallel sequencing.

18. The method of claim 15, wherein the sequencing comprises high-throughput sequencing.WSGR Docket No. 47697-74660119. The method of claim 18, wherein the high-throughput sequencing comprises sequencing by synthesis.

20. The method of claim 17, wherein the high-throughput sequencing comprises nanopore sequencing.

21. The method of any one of claims 15-20, wherein the detecting comprises using a computer readable memory communicatively coupled to a processor configured to detect the sequence reads indicative of the oxidative stress marker in the sequence reads.

22. The method of any one of the preceding claims, wherein the detecting comprises detecting the oxidative stress marker by detecting a Hoogstein base pair.

23. The method of any one of claims 1 to 21, wherein the detecting comprises detecting the oxidative stress marker by detecting a noncanonical nucleotide.

24. The method of claim 23, wherein the noncanonical nucleotide is detected by identifying a mis-match between a forward read and a reverse read at a locus.

25. The method of claim 24, wherein the mis-match comprises a non-Watson-Crick base pairing.

26. The method of claim 25, wherein the non- Watson- Crick base pairing comprises a Hoogstein base pairing.

27. The method of claim 22 or 26, wherein the Hoogstein base pairing is selected from a member of the group consisting of: a G: A base pair, an A:U base pair, a G:G base pair, and a C:C base pair.

28. The method of any one of claims 21-27, wherein the method further comprises detecting noncanonical nucleotides incorporated into at least one strand of NA and outputting an indication of Hoogstein base pairing.

29. The method of any one of claims 21-27, wherein the method further comprises using a machine learning model configured to detect noncanonical nucleotides incorporated into at least one strand of a NA and outputting an indication of Hoogstein base pairing.

30. The method of any one of claims 1-29, wherein the detecting comprises performing an enzyme linked immunosorbent assay (ELISA).

31. The method of any one of claims 1-30, wherein the detecting comprises performing an immunofluorescence assay.

32. The method of any one of claims 1-31, wherein the binding reaction comprises a binding at approximately at a site associated with the oxidative stress marker.

33. The method of claim 11, wherein the aptamer comprises RNA.

34. The method of claim 11, wherein the aptamer comprises DNA.WSGR Docket No. 47697-74660135. The method of any one of claims 1-34, wherein the detecting comprises adding an oxidative stress tag to the cfNA at or near a site of oxidative stress.

36. The method of claim 35, wherein the oxidative stress tag is from 1 to 10 base pairs in the 3' direction from the site of oxidative stress.

37. The method of claim 35, wherein the oxidative stress tag is from 1 to 10 base pairs in the 5' direction from the site of oxidative stress.

38. The method of any one of claims 3-37, further comprising identifying mcfNA based at least on the presence of an increased amount of an oxidative stress marker as compared to hcfNA.

39. The method of any one of claims 3-38, further comprising determining an infection status of the subject based at least in part on the presence of mcfNA comprising an oxidative stress marker.

40. The method of claim 39, wherein the method comprises:(a) sequencing the mcfNA to produce mcfNA sequence reads; and(b) using a computer readable memory communicatively coupled to a processor configured to determine an infection status of the subject based at least in part on the mcfNA sequence reads.

41. The method of claim 40, wherein the computer readable memory encodes a machine learning model.

42. The method of claim 41, wherein the machine learning model comprises a logistic regression model, a linear regression model, a support vector machine, a decision tree, a random forest, a neural network, a clustering method, or any combination thereof.

43. The method of claim 42, wherein the machine learning model comprises the neural network, and wherein the neural network comprises a convolutional neural network, a recurrent neural network, a transformer, a variational autoencoder, a generative adversarial network, or any combination thereof.

44. The method of any one of claims 1-43, wherein the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising an oxidative stress marker.

45. The method of claim 44, wherein the processing comprises conducting the NA library preparation to enrich the sample for cfNA comprising conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker.WSGR Docket No. 47697-74660146. The method of any one of claims 1-45, wherein the conducting the NA library preparation to enrich the sample for hcfNA or mcfNA comprising an oxidative stress marker comprises enriching for mcfNA derived from an infectious agent.

47. A method of distinguishing between a commensal organism and an infectious agent by processing the cell-free nucleic acids (cfNA) in a sample by performing the method of any one of the claims 1-46.

48. The method of claim 47, further comprising sequencing the cfNA to generate sequence reads, and wherein the distinguishing comprises quantifying a number of sequence reads comprising an oxidative stress marker.

49. The method of any one of claims 46-48, wherein the mcfNA derived from the infectious agent comprises a higher proportion or quantity of an oxidative stress marker relative to mcfNA derived from a commensal organism.

50. The method of any one of claims 44-47, wherein the conducting the NA library preparation to enrich the sample comprises enriching for mcfNA comprising the oxidative stress marker.

51. The method of claim 50, wherein the enriching comprises determining a quality of an immune response against an infectious agent.

52. A method of determining a quality of an immune response in a subject, the method comprising performing the method of any one of claims 1-51 in a series of samples.

53. The method of claim 52, comprising collecting the series of samples over a time period.

54. The method of claim 53, wherein the time period ranges from about one day to about one month, from about one day to about two months, from about one day to about three months, from about one day to about four months, from about one day to about five months, from about one day to about six months, or from about one day to about one year.

55. The method of claim 51 or 52, wherein an increase in mcfNA comprising an oxidative stress marker over a time period indicates an increased immune response.

56. The method of claim 51 or 52, wherein a decrease in mcfNA comprising an oxidative stress marker over a time period indicates a decreased immune response.

57. The method of any one of claims 39-56, wherein the determining the infection status of the subject comprises determining the infection status to be active or latent.

58. The method of any one of claims 1-57, further comprising determining an infection status of the subject at least in part by determining an immune response.

59. A method of treating a subject for an infection, comprising:WSGR Docket No. 47697-746601(a) diagnosing an infection of the subject at least in part using the method of processing cfNA of any one of claims 1-58;(b) administering a therapy to the subject, wherein the therapy is selected to treat the infection.

60. The method of claim 59, wherein the therapy is selected from the group consisting of antibiotics, antivirals, antifungals, antiparasitics, immunotherapies, vaccines, antimicrobials, probiotics, and supportive therapies.

61. The method of any one of claims 1-60, wherein the host comprises a human.

62. The method of any one of claims 1-61, wherein the sample comprises a plasma sample.

63. The method of any one of claims 1-61, wherein the sample is selected from the group consisting of: blood, serum, cerebrospinal fluid, synovial fluid, bronchoalveolar lavage, urine, stool, saliva, abdominal fluid, ascites fluid, peritoneal lavage, gastric fluid, interstitial fluid, lymph fluid, bile, abscess fluid, tissue, amniotic fluid, meconium, sinus aspirate, lymph node, bone marrow, hair, nails, cheek swab, skin swab, urethral swab, cervical swab, nasopharyngeal swab, nasopharyngeal aspirate, vaginal swab, epithelial cells, semen, vaginal discharge, intercellular fluid, pericardial fluid, rectal swab, bone, skin tissue, soft tissue, tears, and a nasal sample.

64. The method of any one of claims 1-63, wherein the method further comprises enriching for mitochondrial cfNA by enriching for cfNA comprising an oxidative stress marker.

65. The method of any one of claims 1-64, wherein the method further comprises detecting an immune response by detecting cfNA comprising an oxidative stress marker.

66. A method of processing a sample, comprising:(a) providing the sample comprising cell-free nucleic acids (cfNA); and(b) conducting an enrichment reaction on the sample that differentially affects cfNA comprising an oxidative stress marker as compared to cfNA that does not comprise the oxidative stress marker to generate an enriched cfNA library; and(c) sequencing the enriched cfNA library.

67. The method of claim 66, wherein the cfNA comprises microbial cell-free DNA (mcfNA) and host cell-free DNA (hcfNA).

68. A non-transitory computer-readable storage medium comprising a set of instructions recorded thereon, which, when executed by a processor, cause the processor to implement a method for detecting microbial cell-free nucleic acids (mcfNA), the method comprising:WSGR Docket No. 47697-746601(i) obtaining a plurality of sequence reads derived from cell-free nucleic acids (cfNA) of a sample;(ii) processing the plurality of sequence reads to identify sequences comprising an oxidative stress marker;(iii) detecting the mcfNA based at least a presence of the sequences comprising the oxidative stress marker.

69. The method of any one of claims 1-67 or the non-transitory computer-readable storage medium of claim 68, wherein the nucleic acid (NA) comprises DNA and the cfNA comprises cell-free DNA (cfDNA).

70. The method of any one of claims 1-67 or the non-transitory computer-readable storage medium of claim 68, wherein the nucleic acid (NA) comprises RNA and the cfNA comprises cell-free RNA (cfRNA).

71. The method of any one of claims 1-67 or the non-transitory computer-readable storage medium of claim 68, wherein the nucleic acid (NA) comprises a combination of DNA and RNA and the cfNA comprises a combination of cell-free DNA (cfDNA) and cell-free RNA (cfRNA).

72. A method of preparing a nucleic acid library useful for analyzing oxidative stress markers, the method comprising performing the methods of processing cell-free nucleic acids (cfNA) of any of claims 1-51.

73. A method of improving nucleic acid data processing, the method comprising performing the methods of any one of claims 1-72.

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