Cell-free nucleic acids for analysis of human microbiome and components thereof

Abstract

To provide sensitive, rapid, non-invasive methods of monitoring microbiome compositions in clinical samples.SOLUTION: The present invention provides a method of determining the presence and prevalence of microbial sequences in a sample of cell-free nucleic acids from a non-microbial host, the method comprising: (i) providing a sample of cell-free nucleic acids from an individual; (ii) performing high-throughput sequencing of the nucleic acids; (iii) performing bioinformatics analysis to subtract host sequences from the analysis; and (iv) determining the presence and prevalence of microbial sequences for a microbiome assessment of the non-microbial host.SELECTED DRAWING: None

Description

Technical Field

[0001] The present invention relates to cell-free nucleic acids for the analysis of the human microbiome and its components.

[0002] Government Rights This invention was made with government support under grant number RC4AI092673 awarded by the National Institutes of Health. The government has certain rights in the invention. Health).

Background Art

[0003] The human microbiome is currently recognized as an important component of human health. Community-level analysis has revealed factors that shape the structure of the bacterial and viral components of the microbiome, such as age, diet, geographical location, antibiotic treatment, and disease. For example, an individual's microbiome can be altered by infection with pathogenic organisms, resulting in an increased prevalence of those organisms systemically or in undesirable tissues. The microbiome can also be altered by changes in an individual's immune function.

[0004] For various purposes, it is desirable to obtain methods for the rapid identification and analysis of specific microbiome components, such as commensal, mutualistic, parasitic, opportunistic, and pathogenic organisms, and the overall microbiome structure, in an individual's microbiome. The present invention provides a sensitive, rapid, and non-invasive method for monitoring microbiome composition in clinical samples.

Summary of the Invention

[0005] Overview of the Invention The present invention relates to methods, devices and methods for the analysis of the microbiome or individual components thereof in an individual. The present invention provides compositions and kits for determining infection by using microbiome structure. These are useful in analyzing the immune system, determining the immune competence of an individual, and the like. In particular, the present invention provides a method for the preparation of nucleic acids, i.e., DNA and / or RNA, from an individual, comprising: (i) extracting cell-free nucleic acids, i.e., DNA and / or RNA, from an individual; (ii) preparing a sample, and (iii) performing high-throughput sequencing, e.g., about 10 5 ~about 10 9 pieces or more reads; and (iii) bioinformatics A cross-sectional analysis is performed and the host sequence (i.e., human, feline, canine, etc.) is subtracted from the analysis. (iv) e.g., coverage of sequences mapped to microbial reference sequences The presence of microbial sequences was determined by comparing the coverage of the host reference sequence with that of the host reference sequence. and determining the presence and prevalence of a microorganism in an individual. This provides a method for

[0006] Subtraction of host sequences is done by subtracting the host sequence from the reference host sequence. and masking microbial or microbial mimicking sequences present in the reference host genome. Similarly, determining the presence of a microbial sequence by comparison to a microbial reference sequence may include the steps of: Identify microbial sequences and mask host or host-mimicking sequences present in the reference microbial genome The method may include a step of detecting the presence of the

[0007] A feature of the present invention is the unbiased analysis of cell-free nucleic acid from an individual. The methods of the present invention generally include: For example, by performing PCR with universal primers or by activating the nucleic acid Unbiased amplification by ligating an adapter and amplifying with a primer specific to the adapter including the steps. The method of the present invention is typically performed in the absence of sequence-specific amplification of microbial sequences This approach has the advantage of including the analysis of all available microbiome sequences, but it requires bioinformatics analysis to identify the sequences of interest in complex datasets where host sequences are dominant

[0008] Another advantage of the present invention is that it can provide a rapid assessment of individual microbiomes For example, the analysis can be completed in less than about 3 days, less than about 2 days, less than 1 day, such as less than about 24 hours, less than about 2 0 hours, less than about 18 hours, less than about 14 hours, less than about 12 hours, less than about 6 hours, less than about 2 hours, less than about 30 minutes, less than about 15 minutes, less than about 1 minute

[0009] In some embodiments, the analysis of cell-free nucleic acids is used to calculate a pathogenicity score, where the pathogenicity score is a numerical or alphabetical value that summarizes the overall pathogenicity of the organism, for example, to facilitate interpretation by a practicing physician Microorganisms present in the microbiome can be assigned different scores depending on the microorganism

[0010] Analysis of the presence and prevalence of microbial sequences can be used to determine responses to antimicrobial therapies, such as antibiotics, antiviral agents, immunization, passive immunotherapy, etc., diet, immunosuppression, etc., responses in clinical trials The information obtained from the analysis can be used to diagnose a condition, monitor a treatment, select or modify a treatment regimen, and optimize a treatment This approach allows for the optimization of the treatment process ​​​​​​Treatment and / or diagnostic regimens can be individualized and adapted according to the specificity data obtained at various times over a period, thereby making it possible to obtain an individually adapted regimen. Also, for analysis, patient samples can be obtained at any time during the course of treatment, after exposure to a pathogen, during the course of an infection, etc. Analysis of the presence and prevalence of microbial sequences can be provided as a report. The report can be provided to an individual, a medical professional, etc. become possible, and thereby it becomes possible to obtain an individually adapted regimen. Also, for analysis, patient samples can be obtained at any time during the course of treatment, after exposure to a pathogen, during the course of an infection, etc. exposure, during the course of an infection, etc. Analysis of the presence and prevalence of microbial sequences can be provided as a report. The report can be provided to an individual, a medical professional, etc. exposure, during the course of an infection, etc. Analysis of the presence and prevalence of microbial sequences can be provided as a report. The report can be provided to an individual, a medical professional, etc. exposure, during the course of an infection, etc. Analysis of the presence and prevalence of microbial sequences can be provided as a report. The report can be provided to an individual, a medical professional, etc.

[0011] In some embodiments, the cell-free nucleic acid is obtained from a biological sample selected from the group consisting of blood, serum, cerebrospinal fluid, synovial fluid, urine, and feces. The nucleic acid is extracted from the cell-free portion of the sample, and for example, the serum or plasma portion of blood can be used. In some embodiments, the nucleic acid is selected from the group consisting of double-stranded DNA, single-stranded DNA, single-stranded DNA hairpin, DNA / RNA hybrid, single-stranded RNA, double-stranded RNA, and RNA hairpin. In some embodiments, the nucleic acid is selected from the group consisting of double-stranded DNA, single-stranded DNA, and cDNA. In some embodiments, the nucleic acid is mRNA. In some embodiments, the nucleic acid is circulating cell-free DNA. In some embodiments, the cell-free nucleic acid is obtained from a biological sample selected from the group consisting of blood, serum, cerebrospinal fluid, synovial fluid, urine, and feces. The nucleic acid is extracted from the cell-free portion of the sample, and for example, the serum or plasma portion of blood can be used. In some embodiments, the cell-free nucleic acid is obtained from a biological sample selected from the group consisting of blood, serum, cerebrospinal fluid, synovial fluid, urine, and feces. The nucleic acid is extracted from the cell-free portion of the sample, and for example, the serum or plasma portion of blood can be used. In some embodiments, the cell-free nucleic acid is obtained from a biological sample selected from the group consisting of blood, serum, cerebrospinal fluid, synovial fluid, urine, and feces. The nucleic acid is extracted from the cell-free portion of the sample, and for example, the serum or plasma portion of blood can be used. In some embodiments, the cell-free nucleic acid is obtained from a biological sample selected from the group consisting of blood, serum, cerebrospinal fluid, synovial fluid, urine, and feces. The nucleic acid is extracted from the cell-free portion of the sample, and for example, the serum or plasma portion of blood can be used. In some embodiments, the cell-free nucleic acid is obtained from a biological sample selected from the group consisting of blood, serum, cerebrospinal fluid, synovial fluid, urine, and feces. The nucleic acid is extracted from the cell-free portion of the sample, and for example, the serum or plasma portion of blood can be used. In some embodiments, the cell-free nucleic acid is obtained from a biological sample selected from the group consisting of blood, serum, cerebrospinal fluid, synovial fluid, urine, and feces. The nucleic acid is extracted from the cell-free portion of the sample, and for example, the serum or plasma portion of blood can be used. In some embodiments, the cell-free nucleic acid is obtained from a biological sample selected from the group consisting of blood, serum, cerebrospinal fluid, synovial fluid, urine, and feces. The nucleic acid is extracted from the cell-free portion of the sample, and for example, the serum or plasma portion of blood can be used.

[0012] In some embodiments, the method includes quantifying one or more nucleic acids to determine the prevalence of microorganisms in a sample. In some embodiments, the amount of one or more nucleic acids exceeding a predetermined threshold is an indicator of infection or a change in prevalence. In some embodiments, there are different predetermined thresholds depending on the microorganism. In some embodiments, a temporary difference in the amount of one or more nucleic acids is an indicator of a change in infection, a change in prevalence, a treatment response, etc. In some embodiments, the method includes quantifying one or more nucleic acids to determine the prevalence of microorganisms in a sample. In some embodiments, the amount of one or more nucleic acids exceeding a predetermined threshold is an indicator of infection or a change in prevalence. In some embodiments, the amount of one or more nucleic acids exceeding a predetermined threshold is an indicator of infection or a change in prevalence. In some embodiments, there are different predetermined thresholds depending on the microorganism. In some embodiments, the amount of one or more nucleic acids exceeding a predetermined threshold is an indicator of infection or a change in prevalence. In some embodiments, there are different predetermined thresholds depending on the microorganism. In some embodiments, the amount of one or more nucleic acids exceeding a predetermined threshold is an indicator of infection or a change in prevalence. In some embodiments, there are different predetermined thresholds depending on the microorganism. become.

[0013] In some embodiments, the present invention provides a computer readable medium, comprising: ) a high-throughput assay for one or more nucleic acids detected in a sample of cell-free nucleic acid from a subject; (ii) receiving the put sequencing data and performing bioinformatics analysis to identify (iii) subtracting host sequences (i.e., human, feline, canine, etc.) from the analysis, e.g. By comparing the coverage of sequences mapped to the organism reference sequence with the coverage of the host reference sequence. and configuring the computer to perform the steps of determining the presence and prevalence of a microbial sequence. The computer-readable medium includes a set of instructions recorded on the computer-readable medium.

[0014] In some embodiments, the present invention provides a method for the preparation of ... medicament for use in a pharmaceutical composition comprising the steps of: The present invention provides reagents and kits for carrying out the same.

[0015] In some embodiments, analysis of the microbiome, e.g., the virome, e. In vivo viral population analysis can be used to assess the immune competence of individuals, particularly individual humans. Compositions and methods are provided. In some embodiments of the invention, immunosuppressive regimens In some embodiments, the individual is treated with a drug, radiation therapy, etc. In some embodiments, the patient is a transplant recipient treated with an immunosuppressive regimen. In another embodiment, the individual has an autoimmune disease that is treated with an autoimmune regimen. evaluates individuals for immune competence in the absence of an immunosuppressive regimen.

[0016] In some embodiments, measurements are taken from an individual at two or more time points, where the viral load is The change in the S load serves as an indicator of the change in immune function. An individual can be treated according to the evaluation of immune function , for example, in this case, the indication of undesirably enhanced immune function in transplant patients increases and is treated with an increased level of immunosuppressive agent, or an undesired decrease in immune function is treated with a therapeutic agent, such as an antiviral agent, etc.

[0017] Nucleic acid analysis is used to identify and quantify non-human cell-free nucleic acids in samples collected from patients. The composition of the components of the microbiome is carried out as described above. The structure of the viral component (virome) of the microbiome enables prediction of immune function. In some embodiments , the method further includes establishing a virome profile before, at the start of, or during the course of an immunosuppressive regimen, which is used as a reference for changes in individual viromes. In some embodiments, the circulating cell-free DNA is anellovirus DNA. In particular, the load of viruses in the family Anelloviridae is a predictor of immune strength, which correlates with the probability of organ transplant rejection. Other viruses can also be predicted, but patients are generally treated with antiviral agents that affect the load of such viruses. In some embodiments, the present invention provides a method for diagnosing or predicting a transplantation status or outcome, comprising the steps of: (i) preparing a sample from a subject who has received a transplant from a donor; (ii) determining the presence or absence of one or more virome nucleic acids; and (iii) diagnosing or predicting the transplantation status or outcome based on the virome load. In some embodiments .

[0018]

[0019] ​​​​​​​, the graft status or outcome includes allograft injury, graft function, graft survival, chronic allograft injury, or titer pharmacologic immunosuppression based on rejection, tolerance, non-rejection. In some embodiments, the amount of one or more nucleic acids above a predetermined threshold is a marker of viral load and immune competence. In some embodiments, the threshold is a normative value for clinically stable post-transplant patients who do not show evidence of transplant rejection or other pathologies. In some embodiments, there are predetermined thresholds that vary depending on the outcome or status of the transplant. In some embodiments, a transient difference in the amount of one or more nucleic acids is an indicator of immune competence.

[0020] In any of the embodiments described herein, the graft can be any solid organ, bone marrow, or skin graft. In some embodiments, the transplant is selected from the group consisting of kidney transplant, heart transplant, liver transplant, pancreas transplant, lung transplant, intestine transplant, and skin transplant.

[0021] In some embodiments, the present invention provides reagents and kits for performing one or more of the methods described herein.

[0022] All publications and patent applications cited herein are hereby incorporated by reference as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference.

[0023] The novel features of the invention are set forth with particularity in the appended claims. A further understanding of the features and advantages of the invention will be obtained by reference to the following detailed description that illustrates exemplary embodiments in which the principles of the invention are utilized and the accompanying drawings hereinafter referred to.

[0024] Detailed Description of the Invention Hereinafter, particularly preferred embodiments of the present invention will be described in detail. Specific examples of the preferred embodiments are illustrated in the Examples section described below.

[0025] Unless otherwise indicated, all scientific and technical terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention pertains. All patents and publications referred to herein are hereby incorporated by reference in their entirety. When a range of values is indicated, each intervening value between the upper and lower limits of that range, to the extent of one tenth of the unit of the lower limit, and any other indicated or intervening value within the indicated range, is understood to be included in the present invention, unless clearly inconsistent with the context. The upper and lower limits of these smaller ranges can independently be included within the smaller range, provided there are no particular excluded limits within the indicated range, and are similarly included in the present invention. When the indicated range includes one or both of those limits, ranges excluding one or both of the included limits are also included in the present invention. In this specification, a range is indicated by a numerical value following the word "about". The word "about" is used herein to indicate a literal correspondence to the exact number following it, and numbers close to or approximating the number following it. When determining whether a number is close to or approximates a specifically listed number, an unlisted number that is close to or approximates is, in the context in which it is presented, a substantial equivalent of the specifically listed number.

[0026]

[0027] ​​​​​​​​​​​​It may be the number shown.

[0028] The practice of the present invention, unless otherwise indicated, uses conventional techniques of immunology, biochemistry, chemistry, molecular biology, microbiology, cell biology, genomics, and recombinant DNA, which are within the skill of the art. Sambrook, Fritsch and Maniatis , MOLECULAR CLONING: A LABORATORY MANUAL, 2 nd edition (1989); CURRENT PROTOCOLS IN MO LECULAR BIOLOGY (F.M. Ausubel et al. eds. (1987)); MET HODS IN ENZYMOLOGY series (Academic Press, I nc.): PCR 2: A PRACTICAL APPROACH (M.J. MacP herson, B.D. Hames and G.R. Taylor eds. (1995)), Ha rlow and Lane eds. (1988) ANTIBODIES, A LABORATOR Y MANUAL, and ANIMAL CELL CULTURE (R.I. Fre shney ed. (1987)) may be referred to.

[0029] The present invention provides methods, devices, compositions, and kits for the analysis of the microbiome or its individual components in an individual. The method is useful in determining the structure of the microbiome in the determination of infection, in the determination of the immune capacity of an individual, etc. In some embodiments, the present invention provides a method for determining whether a patient or subject exhibits immune capacity. As used herein, the terms "individual", "patient", or "subject" include humans and other mammals.

[0030] ​​​​Definition As used herein, the terms "diagnose" or "diagnosis" of a condition or result include predicting or diagnosing a condition or result, determining a predisposition to a condition or result, monitoring a patient's treatment, diagnosing a patient's treatment response, and prognosticating a condition or result, progression, and response to a particular treatment.

[0031] Microbiome. As used herein, the term microbiome refers to the collection of microorganisms present within an individual (usually an individual mammal, more usually a human individual). The microbiome includes pathogenic species; the commensal flora that constitute the normal flora of one tissue, such as the skin, oral cavity, etc., but may also include undesirable species in other tissues, such as the blood, lungs, etc.; symbionts found in the absence of disease, etc. One subset of the microbiome is the virome, which includes the viral component of the microbiome.

[0032] As used herein, the term "microbiome component" refers to an individual strain or species. The component can be a viral component, a bacterial component, a fungal component, etc.

[0033] In healthy animals, internal tissues, such as the brain, muscle, etc., are generally presumed to contain relatively few bacterial species, but the surface tissues, i.e., the skin and mucous membranes, are constantly in contact with environmental organisms and are readily colonized by various microbial species. The mixture of organisms known or presumed to be found in humans at any anatomical site is referred to as the normal microbiota and includes various components of the normal microbiota. In addition to the normal microbiota, there are various transient components, such as pathogenic or opportunistic infections. The reference sequences of the microorganisms described below are, for example, Genba ​​​​​​​​​​​​​​It is publicly available and known in the NK database.

[0034] The human gut microbiota is dominated by species found within two bacterial phyla, Bacteroidetes and Firmicutes, whose members make up more than 90% of the bacterial population. Among several other phyla, Actinobacteria (e.g., members of the Bifidobacterium genus) and Proteobacteria are not as dominant. Common species of interest include notable or less abundant members of this population, including, but not limited to, Bacteroides thetaiotaomicron, Bacteroides caccae, Bacteroides fragilis, Bacteroides melaninogenicus, Bacteroides oralis, Bacteroides uniformis, Lactobacillus, Clostridium perfringens, Clostridium septicum, Clostridium tetani, Bifidobacterium bifidum. Bacteroidetes and Firmicutes s) make up more than 90% of the bacterial population. Among several other phyla, Actinobacteria (e.g., members of the Bifidobacterium genus) and Proteobacteria are not as dominant. Common species of interest include notable or less abundant members of this population, including, but not limited to, Bacteroides thetaiotaomicron, Bacteroides caccae, Bacteroides fragilis, Bacteroides melaninogenicus, Bacteroides oralis, Bacteroides uniformis, Lactobacillus, Clostridium perfringens, Clostridium septicum, Clostridium tetani, Bifidobacterium bifidum. Actinobacteria (e.g., members of the Bifidobacterium genus) and Proteobacteria are not as dominant. Common species of interest include notable or less abundant members of this population, including, but not limited to, Bacteroides thetaiotaomicron, Bacteroides caccae, Bacteroides fragilis, Bacteroides melaninogenicus, Bacteroides oralis, Bacteroides uniformis, Lactobacillus, Clostridium perfringens, Clostridium septicum, Clostridium tetani, Bifidobacterium bifidum. Common species of interest include notable or less abundant members of this population, including, but not limited to, Bacteroides thetaiotaomicron, Bacteroides caccae, Bacteroides fragilis, Bacteroides melaninogenicus, Bacteroides oralis, Bacteroides uniformis, Lactobacillus, Clostridium perfringens, Clostridium septicum, Clostridium tetani, Bifidobacterium bifidum. Common species of interest include notable or less abundant members of this population, including, but not limited to, Bacteroides thetaiotaomicron, Bacteroides caccae, Bacteroides fragilis, Bacteroides melaninogenicus, Bacteroides oralis, Bacteroides uniformis, Lactobacillus, Clostridium perfringens, Clostridium septicum, Clostridium tetani, Bifidobacterium bifidum. Bacteroides thetaiotaomicron Bacteroides caccae, Bacteroides fragilis Bacteroides melaninogenicus Bacteroides oralis Bacteroides uniformis Lactobacillus Clostridium perfringens Clostridium septicum Clostridium tetani Bifidobacterium bifidum dum, Staphylococcus aureus us), Enterococcus faecalis s), Escherichia coli, Salmonella enterica Salmonella enteritidis, Klebsiella spp. Klebsiella sp., Enterobacter spp. sp.), Proteus mirabilis, Pseudomonas Pseudomonas aeruginosa, Peptostreptococcus Leptococcus sp., Peptococcus Peptococcus sp., Faecalibacterium sp. ibacterium sp., Roseburia sp., Ruminococcus sp., Dorea s p.), Alistipes sp., etc.

[0035] In the skin microbiome, most bacteria fall into four different phyla: Actinobacteria, Firmicutes utes, Bacteroidetes and Proteobacteria Proteobacteria. Microorganisms commonly considered to be skin colonizers include Coliformis, Corynebacteria (Actinobacteria) Genus Corynebacterium, Propionibacterium Genus Propionibacterium, such as Propionibacterium acnes and Brevibacterium genus], Micrococcus genus and Staphylococcus spp. are included. The most commonly isolated fungal species include Malassezia spp., which are particularly dominant in seborrheic areas. Demodex mites [e.g., Demodex folliculorum and Demodex brevis] may also be present. Other types of fungi thought to grow on the skin include Debaryomyces and Cryptococcus spp. As non-commensals, for burns, Streptococcus pyogenes , Enterococcus spp. or Pseudomonas aeruginosa may infect, and fungi and / or viruses may also infect. Staphylococcus epidermidis is a very common skin commensal, but it is also the most frequent cause of nosocomial infections on indwelling medical devices such as catheters or heart valves. For a general review, see Nat Rev Microbiol. (2011) Apr;9(4):2 44-53.

[0036] Pathogenic species can be bacteria, viruses, parasitic protozoa, fungal species, etc. Bacteria include Brucella Species of Brucella sp., Treponema sp., My cobacterium sp., Listeria sp., Legionella sp., Helicoba cter sp., Streptococcus sp., Neisseria sp., Clostridium sp., Staphylococcus sp. or Bacillus sp. are included, but not limited to, Treponema pallidum, Mycobacterium tuberculosis, Mycobacterium leprae, Listeria monocytoge nes, Legionella pneumophila, Helicobacter pylori, Strepto coccus pneumoniae, Neisseria meningitis, Clostridium novyi, Clostridium botulinum, Staphylococcus aureus, Bacillus anthracis, etc. are included.

[0037] Parasitic protozoa include Trichomonas, Toxoplasma, Giardia, Cryptosporidium, Plasmodium, Leishmania, Trypanosoma, Entamoeba, Schistosoma, Filariariae, Ascaria, Fasciola, including, but not limited to, Trichomonas vaginalis, Toxoplasma gondii, Giardia intestinalis, Cryptosporidium parva, Plasmodium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. plasma), Giardia, Cryptosporidium, Plasmodium, Leishmania, Trypanosoma, Entamoeba, Schistosoma, Filariariae, Ascaria, Fasciola, including, but not limited to, Trichomonas vaginalis, Toxoplasma gondii, Giardia intestinalis, Cryptosporidium parva, Plasmodium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. sporidium), Plasmodium, Leishmania, Trypanosoma, Entamoeba, Schistosoma, Filariariae, Ascaria, Fasciola, including, but not limited to, Trichomonas vaginalis, Toxoplasma gondii, Giardia intestinalis, Cryptosporidium parva, Plasmodium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. eishmania), Trypanosoma, Entamoeba, Schistosoma, Filariariae, Ascaria, Fasciola, including, but not limited to, Trichomonas vaginalis, Toxoplasma gondii, Giardia intestinalis, Cryptosporidium parva, Plasmodium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. Entamoeba), Schistosoma, Filariariae, Ascaria, Fasciola, including, but not limited to, Trichomonas vaginalis, Toxoplasma gondii, Giardia intestinalis, Cryptosporidium parva, Plasmodium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. ariae), Ascaria, Fasciola, including, but not limited to, Trichomonas vaginalis, Toxoplasma gondii, Giardia intestinalis, Cryptosporidium parva, Plasmodium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. are included, but not limited to, Trichomonas vaginalis, Toxoplasma gondii, Giardia intestinalis, Cryptosporidium parva, Plasmodium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. vaginalis), Toxoplasma gondii, Giardia intestinalis, Cryptosporidium parva, Plasmodium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. ), Giardia intestinalis, Cryptosporidium parva, Plasmodium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. riptosporidium parva, Plasmodium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. modium falciparum, Trypanosoma cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. cruzi, Entamoeba histolytica, Giardia lamblia, Fasciola hepatica, etc. histolytica, Giardia lamblia, Fasciola hepatica, etc. ardia lamblia, Fasciola hepatica, etc. tica), etc.

[0038] Viruses that infect humans include, for example, the following: adeno-associated virus, Aichi virus, Australian bat lyssavirus, BK polyomavirus, Bunyavirus, Barmah Forest virus, Bunyamwera virus, La Crosse bunyavirus, chivirus, Australian bat lyssavirus, BK polyomavirus, Bunyavirus, Barmah Forest virus, Bunyamwera virus, La Crosse bunyavirus, nna virus, Barmah Forest virus, Bunyamwera virus, La Crosse bunyavirus, La Crosse virus, cottontail rabbit bunyavirus (Snowshoe hare bunyavirus), rhesus monkey herpesvirus , Chandipura virus, chikungunya virus, Cosavirus (Cosavirus )A, vaccinia virus, coxsackievirus, Crimean-Congo hemorrhagic fever virus, dengue fever virus, Dhori virus, Junin virus, Dubin-Johnson virus, eastern equine encephalitis virus, Ebola virus, echovirus, encephalomyocarditis virus, Epstein-Barr virus, European bat lyssavirus, GB virus C / hepatitis G virus, Hantaan virus, Hendra virus, hepatitis A virus, hepatitis B virus, hepatitis C virus virus, hepatitis E virus, delta hepatitis virus, equinepox virus, human adenovirus, H uman astrovirus, human coronavirus, human cytomegalovirus, human enterovirus 68, 70, human herpesvirus 1, human herpesvirus 2, human herpesvirus 6, human herpesvirus 7, human herpesvirus 8, human immunodeficiency virus, human papillomavirus 1, human papillomavirus 2, human papillomavirus 16, 18, human parainfluenza, human parvovirus B19, human respiratory syncytial virus , human rhinovirus, human SARS coronavirus, human spumaretrovirus, H uman T-lymphotropic virus, human torovirus, influenza A virus, influenza B virus , influenza C virus, Isfahan virus, JC polyomavirus, Japanese encephalitis virus, Funiin arenavirus, KI polyomavirus, K unjin virus, Lagos bat virus, Lake Victoria marburgvirus, Langa virus Lassa virus, Rauscher virus, Lordsdale virus, Louping ill virus, Lymphocytic choriomeningitis virus, Machupo virus, Mayaro virus, MERS coronavirus, Measles virus, Mengo encephalomyelitis virus, Merkel cell polyomavirus, Mokola virus, Molluscum contagiosum virus, Monkeypox virus, Mumps virus, Murray Valley encephalitis virus, New York virus, Nipah virus, Norwalk virus, Onion yellow dwarf virus, Orf virus, Oropouche virus, Pichinde virus, Poliovirus, Punta Toro phlebovirus, Puumala virus, Rabies virus, Rift Valley fever virus, Rosavirus A, Ross River virus, Rotavirus A, Rotavirus B, Rotavirus C, Rubella virus, Sagiyama virus, Salivirus A, San Miguel sea lion virus, Sapporo virus, Semliki Forest virus, Seoul virus, Simian foamy virus, Simian virus 5, Sindbis virus, Southampton virus, Saint Louis encephalitis virus, Tick-borne Powassan virus, Torque teno synovitis virus, Toscana virus, Vaccinia virus, Varicella zoster virus, Variola virus, Venezuelan equine encephalitis virus, Vesicular stomatitis virus, Western equine encephalitis virus, WU polyomavirus, West Nile virus, Yaba tumor virus, Yaba-like disease virus, Yellow fever virus, Zika virus.

[0039] ​​​​​​​​​​​Anelloviridae. The Anelloviridae consists of non-enveloped circular single-stranded DNA viruses. Three genera of anelloviruses (referred to as TTV, TTMDV, and TTMV) are known to infect humans.

[0040] Torque teno virus (TTV) is a non-enveloped single-stranded DNA virus with a circular minus-sense genome. Smaller viruses, later named Torque Teno-like Mini Virus (TTMV), have also been characterized. A third virus with an intermediate genome size between those of TTV and TTMV was discovered and later named Torque Teno-like Midi Virus (TTMDV). Recent changes in nomenclature classify those three anelloviruses that can infect humans into the genera Alphatorquevirus (TTV), Betatorquevirus (TTMV), and Gammatorquevirus (TTMDV) of the family Anelloviridae. Currently, anelloviruses are still considered "orphan" viruses awaiting association with human disease. Human anelloviruses differ in genome size, ranging from 3.8 - 3.9 kb for TTV, 3.2 kb for TTMDV, and 2.8 - 2.9 kb for TTMV. Anelloviruses are characterized by extreme diversity found both within and between anellovirus species, which can show differences of up to 33% - 50% at the nucleotide level.

[0041] ​​​​​​​​​​Despite the diversity of nucleotide sequences, anelloviruses share a common virion structure and genome. Conserved genomic organization, transcriptional profile, and non-coding GC-rich regions confer gene function They share common domains and sequence motifs.

[0042] Anellovirus infections are highly prevalent in the general population. Between 75 and 100% of patients tested are infected with at least one of the three human anelloviruses. They found that anelloviruses are transmitted by viruses in young children, many of which infect multiple species. The earliest documented infection occurred within the first month after birth. The virus was detected in plasma, serum, peripheral blood mononuclear cells (PBMCs), nasopharyngeal aspirates, bone marrow, saliva, and uterine tissue. Milk, feces and various tissues including the thyroid, lymph nodes, lungs, liver, spleen, pancreas and kidneys It has been found in nearly every body site, fluid, and tissue tested, including human tissue. The replication kinetics of Neroviruses is essentially Positive-stranded TTV DNA, an indicator of local viral replication, is expressed in hepatocytes and bone marrow cells. , has been described in circulating PBMCs.

[0043] Anelloviruses are primarily transmitted via feces, although maternal-fetal and respiratory tract infections have also been reported. It is spread by oral infection. There are conflicting reports regarding the presence of TTV in cord blood samples. exist.

[0044] Reference sequences for anelloviruses are available in Genbank at: Available: Torque teno minivirus 1, Accession: NC 014097.1; Torque tenominivirus 6, Accession: NC 014095.1; Torque teno midi virus 2, accession: NC 014093.1; Torque teno midi virus 1 , accession: NC 009225.1; Torque teno virus 3, accession: NC 014081.1; Torque teno virus 19, accession: NC 01407 8.1; Torque teno mini virus 8, accession: NC 014068.1.

[0045] As used herein, the term "antibiotic" includes all commonly used bacteriostatic and bactericidal antibiotics, and usually those administered orally. Antibiotics include the following: aminoglycosides such as amikacin, gentamicin, kanamycin, neomycin, streptomycin and tobramycin; cephalosporins such as cephamandole, cefazolin, cephalexin, cephaloglycin, cephaloridine, cephalothin, cefapirin and cefradine; macrolides such as erythromycin and troleandomycin; penicillins such as penicillin G, amoxicillin, ampicillin, carbenicillin, cloxacillin, dicloxacillin, methicillin, nafcillin, oxacillin, phenethicillin and ticarcillin; polypeptide antibiotics such as bacitracin, colistimethate, colistin, polymyxin B; tetracyclines such as chlortetracycline, demeclocycline, doxycycline, methacycline, minocycline, tetracycline and oxytetracycline; and other miscellaneous substances such as chloramphenicol, clindamycin, cycloserine, lincomycin rifampin, spectinomycin, vancomycin and viromycin. The antibiotics are listed in "Remington's Pharmaceutical Sciences" es,”16th Ed.,(Mack Pub.Co.,1980),pp.1121 -1178.

[0046] Antiviral Agents. An individual may be receiving antiviral therapy. This may include the following: Examples of viral infections that can be treated in this way include These include: HIV, Bowenoid papulosis, chickenpox, childhood HIV disease, human-bovine Pox, Hepatitis C, Dengue fever, Enterovirus, Epidermodysplasia verruciformis, Erythema infectiosum (Fifth disease), Buschke-Lowenstein giant condyloma acuminata, hand, foot and mouth disease, herpes simplex, Herpes virus 6, shingles, Kaposi's varicelliform rash, measles, milker's nodule, molluscum contagiosum , Monkeypox, Orf, Roseola, Rubella, Smallpox, Viral Hemorrhagic Fever, Genital Warts and Non-Genital Warts Vessel warts.

[0047] Antiviral agents include: Azidouridine ), anasmycin, amantadine, Bromovinyldeoxusidine, Chloro Vinyldeoxusidine, cytabine (cytarbine), didanosine, deoxynojirimycin Deoxyjirimycin, dideoxycytidine idine, dideoxyinosine, dideoxynuc Dideoxynucleoside, Desciclovir vir), deoxyacyclovir, edoxuidine ( edoxuidine), enviroxime, fiacitabine fiacitabine, foscamet, fialuridine ialuridine, fluorothymidine, Floxuridine, hypericin, interleukin -feron, interleukin, isethionate, nevirapine nevirapine, pentamidine, ribavirin ribavirin), rimantadine, sitavirdine avirdine, sargramostin, suramin ramin), trichosanthin, tribromothymidine ( tribromothymidine, trichlorothymidine ymidine, vidarabine, zidoviridin ridine, zalcitabine and 3-azido-3-deoxyribonucleic acid Oxythymidine and its analogs, derivatives, pharma- ceutically acceptable salts, esters, prod- ucts Rags, codrugs and protected forms.

[0048] As used herein, immunosuppression or immunosuppressive regimen refers to immunosuppression against self antigens or grafts. The present invention relates to the treatment of an individual, such as a transplant recipient, with a substance that reduces the immune response of the host immune system to the Taste. Typical immunosuppressive regimens are described in more detail herein.

[0049] The main immunosuppressive agents include calcineurin inhibitors that bind to binding proteins and inhibit calcineurin activity, and these include, for example, tacrolimus, cyclosporine A, etc. The levels of both cyclosporine and tacrolimus need to be carefully monitored. Initially, the level can be maintained in the range of 10 - 20 ng / mL, but after 3 months, in order to reduce the risk of nephrotoxicity, the level can be maintained lower (5 - 10 ng / mL). imus), cyclosporine A, etc. The levels of both cyclosporine and tacrolimus need to be carefully monitored. Initially, the level can be maintained in the range of 10 - 20 ng / mL, but after 3 months, in order to reduce the risk of nephrotoxicity, the level can be maintained lower (5 - 10 ng / mL). The levels of both cyclosporine and tacrolimus need to be carefully monitored. Initially, the level can be maintained in the range of 10 - 20 ng / mL, but after 3 months, in order to reduce the risk of nephrotoxicity, the level can be maintained lower (5 - 10 ng / mL). The levels of both cyclosporine and tacrolimus need to be carefully monitored. Initially, the level can be maintained in the range of 10 - 20 ng / mL, but after 3 months, in order to reduce the risk of nephrotoxicity, the level can be maintained lower (5 - 10 ng / mL). The levels of both cyclosporine and tacrolimus need to be carefully monitored. Initially, the level can be maintained in the range of 10 - 20 ng / mL, but after 3 months, in order to reduce the risk of nephrotoxicity, the level can be maintained lower (5 - 10 ng / mL). The levels of both cyclosporine and tacrolimus need to be carefully monitored. Initially, the level can be maintained in the range of 10 - 20 ng / mL, but after 3 months, in order to reduce the risk of nephrotoxicity, the level can be maintained lower (5 - 10 ng / mL).

[0050] Usually, adjuvants are combined with calcineurin inhibitors and include steroids, azathioprine, mycophenolate mofetil, and sirolimus. Some protocols of interest include calcineurin inhibitors combined with mycophenolate mofetil. The use of adjuvants allows the clinician to achieve appropriate immunosuppression while reducing the dosage and toxicity of individual substances. After several clinical trials showed a significantly reduced incidence of acute cellular rejection and a decrease in treatment failure over one year compared to azathioprine, mycophenolate mofetil plays an important role in immunosuppression in kidney transplant recipients. azathioprine, mycophenolate mofetil, and sirolimus. Some protocols of interest include calcineurin inhibitors combined with mycophenolate mofetil. The use of adjuvants allows the clinician to achieve appropriate immunosuppression while reducing the dosage and toxicity of individual substances. After several clinical trials showed a significantly reduced incidence of acute cellular rejection and a decrease in treatment failure over one year compared to azathioprine, mycophenolate mofetil plays an important role in immunosuppression in kidney transplant recipients. azathioprine, mycophenolate mofetil, and sirolimus. Some protocols of interest include calcineurin inhibitors combined with mycophenolate mofetil. The use of adjuvants allows the clinician to achieve appropriate immunosuppression while reducing the dosage and toxicity of individual substances. After several clinical trials showed a significantly reduced incidence of acute cellular rejection and a decrease in treatment failure over one year compared to azathioprine, mycophenolate mofetil plays an important role in immunosuppression in kidney transplant recipients. azathioprine, mycophenolate mofetil, and sirolimus. Some protocols of interest include calcineurin inhibitors combined with mycophenolate mofetil. The use of adjuvants allows the clinician to achieve appropriate immunosuppression while reducing the dosage and toxicity of individual substances. After several clinical trials showed a significantly reduced incidence of acute cellular rejection and a decrease in treatment failure over one year compared to azathioprine, mycophenolate mofetil plays an important role in immunosuppression in kidney transplant recipients. azathioprine, mycophenolate mofetil, and sirolimus. Some protocols of interest include calcineurin inhibitors combined with mycophenolate mofetil. The use of adjuvants allows the clinician to achieve appropriate immunosuppression while reducing the dosage and toxicity of individual substances. After several clinical trials showed a significantly reduced incidence of acute cellular rejection and a decrease in treatment failure over one year compared to azathioprine, mycophenolate mofetil plays an important role in immunosuppression in kidney transplant recipients. azathioprine, mycophenolate mofetil, and sirolimus. Some protocols of interest include calcineurin inhibitors combined with mycophenolate mofetil. The use of adjuvants allows the clinician to achieve appropriate immunosuppression while reducing the dosage and toxicity of individual substances. After several clinical trials showed a significantly reduced incidence of acute cellular rejection and a decrease in treatment failure over one year compared to azathioprine, mycophenolate mofetil plays an important role in immunosuppression in kidney transplant recipients. azathioprine, mycophenolate mofetil, and sirolimus. Some protocols of interest include calcineurin inhibitors combined with mycophenolate mofetil. The use of adjuvants allows the clinician to achieve appropriate immunosuppression while reducing the dosage and toxicity of individual substances. After several clinical trials showed a significantly reduced incidence of acute cellular rejection and a decrease in treatment failure over one year compared to azathioprine, mycophenolate mofetil plays an important role in immunosuppression in kidney transplant recipients. azathioprine, mycophenolate mofetil, and sirolimus. Some protocols of interest include calcineurin inhibitors combined with mycophenolate mofetil. The use of adjuvants allows the clinician to achieve appropriate immunosuppression while reducing the dosage and toxicity of individual substances. After several clinical trials showed a significantly reduced incidence of acute cellular rejection and a decrease in treatment failure over one year compared to azathioprine, mycophenolate mofetil plays an important role in immunosuppression in kidney transplant recipients. azathioprine, mycophenolate mofetil, and sirolimus. Some protocols of interest include calcineurin inhibitors combined with mycophenolate mofetil. The use of adjuvants allows the clinician to achieve appropriate immunosuppression while reducing the dosage and toxicity of individual substances. After several clinical trials showed a significantly reduced incidence of acute cellular rejection and a decrease in treatment failure over one year compared to azathioprine, mycophenolate mofetil plays an important role in immunosuppression in kidney transplant recipients.

[0051] Antibody-based therapies are monoclonal (e.g., muromonab-C D3) or polyclonal antibodies or anti-CD25 antibodies (e.g., basiliximab (b It may be possible to use basiliximab and daclizumab, which are administered in the early post-transplant period (up to 8 weeks). Antibody-based therapies allow for the avoidance or dose reduction of calcineurin inhibitors and probably reduce the risk of nephrotoxicity. The side effect profiles of polyclonal and monoclonal antibodies limit their use in some patients. The term "nucleic acid" as used herein means a polynucleotide containing two or more nucleotides. It can be DNA or RNA. A "variant" nucleic acid is a polynucleotide having the same nucleotide sequence as the original nucleic acid except having at least one nucleotide that is modified (e.g., deleted, inserted, or substituted, respectively). The variant can have a nucleotide sequence that is at least about 80%, 90%, 95% or 99% identical to the nucleotide sequence of the original nucleic acid. Circulating, i.e., cell-free DNA was first detected in human plasma in 1948 (Mandel, P., Metais, P., C R Acad. Sci. Paris, 142, 241-243 (1948)). Since then, its association with diseases has been established in several areas (Tong, Y.K., Lo, Y.M., Clin Chim Acta, 363, 187-196 (2006)). As shown by research, most of the circulating nucleic acids in the blood are generated from necrotic or apoptotic cells (Giacona, M.B. et al., Pancreas, 17, 89-97 (1998)), and the levels of nucleic acids from apoptosis are significantly ... ...

[0052] ... ... ... ... ... ...

[0053] ... ... ... ... ... ... ... It should be noted that the content you provided seems to be incomplete in the middle part, which may affect the overall understanding and translation. If you can provide the complete content, it will be more conducive to a more accurate translation.Such an increase has been observed in diseases such as cancer (Giacona, M.B. et al., Pancr eas, 17, 89 - 97 (1998); Fournie, G.J. et al., Cancer Lett, 91, 221 - 227 (1995)). In particular, in the case of cancer, circulating DNA shows characteristic signs of the disease, including mutations in oncogenes, microsatellite changes, and in some cancers the viral genome sequence, and plasma DNA or RNA is increasingly being studied as a potential biomarker for the disease. For example, Diehl et al. recently showed that a quantitative assay for low levels of circulating tumor DNA in total circulating DNA can act as a better marker for detecting recurrence of colorectal cancer compared to carcinoembryonic antigen, a standard biomarker currently in clinical use (Diehl, F. et al., Proc Natl Acad Sci, 102, 16368 - 16373 (200 5); Diehl, F. et al., Nat Med, 14, 985 - 990 (2008)). Maheswaran et al. reported using genotyping of circulating cells in plasma to detect activating mutations in the epidermal growth factor receptor in lung cancer patients affected by drug treatment (Maheswaran, S. et al., N Engl J Med, 359, 366 - 377 (2008)). Collectively, these results establish cell-free circulating DNA in plasma as a useful species in cancer detection and treatment. Circulating DNA is also useful in healthy patients for prenatal diagnosis, where fetal DNA circulating in maternal blood serves as a marker for gender, Rh (rhesus) D status, fetal aneuploidy, and X-linked disorders. Fan et al. recently showed that shotgun sequencing of cell-free DNA collected from maternal blood samples ​​​​​​​​​​ We have presented a method for detecting fetal aneuploidies by tumor sequencing. It could replace aggressive and risky techniques such as amniocentesis or chorionic villus sampling. (Fan, HC, Blumenfeld, YJ, Chitkara, U., H udgins, L., Quake, SR, Proc Natl Acad Sci, 105,16266-16271(2008)).

[0054] As used herein, the term "derived" refers to a term referring to origin or source. and may include naturally occurring, recombinant, unpurified or purified molecules. The nucleic acid derived from the acid may contain, in part or in whole, the original nucleic acid, and may be Nucleic acid derived from a biological sample may be a fragment or variant of the nucleic acid. It can be purified.

[0055] The "target nucleic acid" in the method of the present invention is the nucleic acid, DNA or RNA, to be detected. A target nucleic acid derived from an organism is a nucleic acid specific for that organism that has a sequence derived from the sequence of that organism. The target nucleic acid from a pathogen is a specific polynucleotide derived from that specific pathogen. It means a polynucleotide having a polynucleotide sequence.

[0056] In some embodiments, 1 pg, 5 pg, 10 pg, 20 pg, 30 pg, 40 pg, pg, 50pg, 100pg, 200pg, 500pg, 1ng, 5ng, 10ng, 2 0ng, 30ng, 40ng, 50ng, 100ng, 200ng, 500ng, 1μg , 5μg, 10μg, 20μg, 30μg, 40μg, 50μg, 100μg, 200μg g. Obtain nucleic acid of less than 500 μg or 1 mg from the sample for analysis. In some embodiments it is about 1 - 5 pg, 5 - 10 pg, 10 - 100 pg, 100 pg - 1 ng, 1 - 5 ng, 5 - 10 ng, 10 - 100 ng, 100 ng - 1 μg of nucleic acid is obtained from the sample for analysis .

[0057] In some embodiments, the method described herein is used to detect and / or quantify nucleic acid sequences corresponding to the microorganism of interest or corresponding to the microbiome of an organism. The method described herein can analyze at least 1, 2, 3, 4, 5, 10 , 20, 50, 100, 200, 500, 1,000, 2,000, 5,000, 10, , 000, 20,000, 50,000, 100,000, 200,000, 300,00 0, 400,000, 500,000, 600,000, 700,000, 800,00 0, 900,000, 10 , 5×10 6 , 10 6 , 5×10 7 , 10 7 , 5×10 8 , 10 8 , 10 9 or more sequence reads.

[0058] In some embodiments, the method described herein is used to detect and / or quantify gene expression, for example, by determining the presence of mRNA from a microorganism with respect to the DNA from that microorganism. In some embodiments, the method described herein provides highly discriminable quantitative analysis of multiple genes. The method described herein can analyze at least 1, 2, 3, 4, 5, 10, 20, 50, 100 In some embodiments, the method described herein provides highly discriminable quantitative analysis of multiple genes. The method described herein can analyze at least 1, 2, 3, 4, 5, 10, 20, 50, 100 . . The method described herein can analyze at least 1, 2, 3, 4, 5, 10, 20, 50, 100 , 200, 500, 1,000, 2,000, 5,000, 10,000, 20,000 , can identify the expression of 50,000, 100,000 or more different target nucleic acids, and can be quantified.

[0059] A sample containing cell-free nucleic acid is obtained from a subject. Such a subject can be a human, livestock , for example, cows, chickens, pigs, horses, rabbits, dogs, cats, goats, etc. In some embodiments, the cells used in the present invention are collected from a patient. The sample may include, for example, whole blood, sweat, tears, saliva, ear exudate, sputum, lymph, bone marrow suspension, lymph fluid, urine, saliva, semen, vaginal exudate, cerebrospinal fluid, cerebral fluid, ascites, milk, airway, intestinal tract or urogenital tract secretions, washing fluids of tissues or organs (e.g., lungs), or cell-free fractions of tissues excised from organs such as the breast, uterus cervix, prostate, pancreas, heart, liver and stomach. Such samples can be separated by centrifugation, decantation, density gradient separation, apheresis, affinity selection, panning, FACS, centrifugation with Hypaque, etc. Once the sample is obtained, it can be used directly, can be frozen, or can be maintained in an appropriate medium for a short period of time.

[0060] To obtain a blood sample, any technique known in the art (e.g., a syringe or other vacuum aspiration device) can be used. The blood sample can be pretreated or processed before use, if desired. Samples such as blood samples can be used within 4 weeks, 2 weeks, 1 week, 6 days, 5 days, 4 days, 3 days, 2 days, 1 day, 12 hours, 6 hours, 3 hours, 2 hours or 1 hour from the time of sample acquisition, or after a longer time if frozen, as described herein. It can be analyzed in either the method or system described in . When obtaining a sample (e.g., a blood sample) from a subject, the amount can vary depending on the size of the subject and the conditions being screened. In some embodiments, at least 10 ml, 5 ml, 1 ml, 0.5 ml, 250, 200, 150, 100, 50, 4 0, 30, 20, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 μL of the sample is obtained. . In some embodiments, 1 - 50, 2 - 40, 3 - 30, or 4 - 20 μL of the sample is obtained. In some embodiments, 5, 10, 15, 20, 25, 30, 35 , 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 1 00 μL or more of the sample is obtained.

[0061] The cell-free fraction is preferably serum or plasma. The term "cell-free fraction" of a biological sample as used herein is a fraction of a biological sample that substantially does not contain cells. The term "substantially free of cells" as used herein refers to a preparation from a biological sample that contains less than about 20,000 cells / ml , preferably less than about 2,000 cells / ml, more preferably less than about 200 cells / ml , and most preferably less than about 20 cells / ml. In contrast to some prior art methods, genomic DNA is not excluded from the cell-free sample and typically comprises about 50% to about 90% of the nucleic acids present in the sample. The method of the present invention can further include preparing a cell-free fraction from a biological sample. The cell-free fraction

[0062] can be prepared using conventional techniques known in the art. For example, a blood sample The cell-free fraction of the pellet is stirred for about 3 to 30 minutes, preferably for about 3 to 15 minutes, more preferably for about 3 to 15 minutes. 10 minutes, most preferably about 3 to 5 minutes, at about 200 to 20,000 g, preferably about 20 0 to 10,000 g, more preferably about 200 to 5,000 g, most preferably about 350 It can be obtained by centrifuging a blood sample at a low speed of ~4,500 g. Samples are separated into cells and their fragments from the cell-free fraction, which contains soluble DNA or RNA. To achieve this, ultrafiltration can be used. Typically, ultrafiltration is performed using a 0.22 μm membrane filter. This is done using a filter.

[0063] The method of the present invention further comprises concentrating (or enriching) a target nucleic acid in a cell-free fraction of a biological sample. The target nucleic acid can be isolated using conventional techniques known in the art, for example by Solid-phase absorption in the presence of high salt concentrations, followed by organic extraction with phenol-chloroform Precipitation with ethanol or isopropyl alcohol, or high salt or 70-80% It can be concentrated by direct precipitation in the presence of 0% ethanol or isopropyl alcohol. The enriched target nucleic acid is at least about 2, 5, 10, 20 or more times greater than that in the cell-free fraction. The target nucleic acid, whether concentrated or not, can be concentrated by 100 times. , can be used for amplification according to the methods of the present invention.

[0064] In some embodiments, the present invention provides methods for diagnosing or predicting transplant rejection. The term "transplant rejection" includes both acute and chronic transplant rejection. "AR" is a type of immune response caused by the immune system of a tissue transplant recipient when the transplanted tissue is immunologically foreign. Acute rejection is characterized by infiltration of the transplanted tissue by the recipient's immune cells. are activated, and the immune cells perform their effector functions and destroy the transplanted tissue. The onset of acute rejection is rapid and generally occurs within a few weeks after transplantation in humans. Generally, acute rejection can be inhibited or suppressed by immunosuppressive drugs such as rapamycin, cyclosporine A, anti-CD40L monoclonal antibodies, etc.

[0065] "Chronic transplant rejection or CR" generally occurs within months to years of transplantation in humans, even if immunosuppression for acute rejection is successful. Fibrosis is a common factor in chronic rejection of all types of organ transplantation. Chronic rejection is typically characterized by certain ranges of specific disorders characteristic of individual organs. For example, in lung transplantation, such disorders include fibroproliferative destruction of the airway (bronchiolitis obliterans), in heart transplantation or transplantation of heart tissue, such as valve replacement, such disorders include fibroatherosclerosis, and in kidney transplantation, such disorders include obstructive nephropathy, nephrosclerosis, and tubulointerstitial nephritis and in liver transplantation, such disorders include vanishing bile duct syndrome. Chronic rejection can also be characterized by ischemic injury related to immunosuppressive drugs, denervation of the transplanted tissue, hyperlipidemia, and hypertension. In some embodiments, the present invention further includes a method for determining the effectiveness of an immunosuppressive regimen for a subject who has received a transplant, such as an allograft. In some embodiments, the present invention provides a method for predicting graft survival in a subject who has received a transplant. The present invention relates to whether a graft in a transplant patient or subject will survive or be lost.

[0066] In some embodiments, the present invention further includes a method for determining the effectiveness of an immunosuppressive regimen for a subject who has received a transplant, such as an allograft.

[0067] Certain embodiments of the present invention provide a method for predicting graft survival in a subject who has received a transplant. The present invention relates to whether a graft in a transplant patient or subject will survive or be lost. To provide a method for diagnosing or predicting. In certain embodiments, the present invention relates to long-term grafts To provide a method for diagnosing or predicting the presence of survival. "Long-term graft survival" means, despite the occurrence of one or more acute rejection episodes up to this point, at least more than the current sampling and also means graft survival of about 5 years. In certain embodiments, graft survival is determined for patients in whom at least one episode of acute rejection has occurred. Thus, these embodiments provide a method for determining or predicting graft survival in the presence of acute rejection. Graft survival , in certain embodiments, is determined or predicted in the case of transplantation therapy, such as immunosuppressive therapy (immunosuppressive therapy is known in the art ). In still other embodiments, a method is provided for determining (not just the mere presence of) the class and / or severity of acute rejection ). .

[0068] As is known in the transplantation field, transplanted organs, tissues or cells can be allogeneic or xenogeneic and thus the graft can be an allograft or a xenograft. The characteristics of the graft tolerance phenotype detected or identified by the present method are that it is a phenotype that occurs without accompanying immunosuppressive therapy, i.e., it is present in a host that has not received immunosuppressive therapy ( thus, no immunosuppressive agent has been administered to the host). The graft can be any solid organ and skin graft. Examples of organ transplants that can be analyzed by the methods described herein include, but are not limited to, kidney transplantation, pancreas transplantation , liver transplantation, heart transplantation, lung transplantation, intestine transplantation, pancreas after kidney transplantation, and simultaneous pancreas-kidney transplantation . . .

[0069] Detection and analysis of the microbiome The method of the present invention involves high-throughput sequencing of cell-free nucleic acid samples from an individual, and subsequent bioinformatics analysis to determine the presence and prevalence of microbiome sequences, where the sequences can be from indigenous organisms, e.g., from the normal microbiome of the gut, skin, etc., or can be from non-indigenous, e.g., opportunistic, pathogenic infections. The analysis can be performed on the entire microbiome or on components thereof, e.g., the virome, bacterial microbiome, fungal microbiome, parasitic protozoan microbiome, etc. Examples of nucleic acids include, but are not limited to, double-stranded DNA, single-stranded DNA, single-stranded DNA hairpins, DNA / RNA hybrids, RNA (e.g., mRNA or miRNA) and RNA hairpins. In some embodiments, the nucleic acid is DNA. In some embodiments, the nucleic acid is RNA. For example, cell-free RNA and DNA are present in human plasma. (e.g., mRNA or miRNA) and RNA hairpins. In some embodiments, the nucleic acid is DNA. In some embodiments, the nucleic acid is RNA. For example, cell-free RNA and DNA are present in human plasma. Genotyping of microbiome nucleic acids, and / or detection, identification, and / or quantification of microbiome-specific nucleic acids

[0070] generally involves an initial step of amplifying the sample. However, there may be cases where sufficient cell-free nucleic acid is available and can be directly sequenced. When the nucleic acid is RNA, a reverse transcriptase reaction to convert the RNA to DNA can be performed prior to the amplification step. Preferably, the amplification is unbiased, i.e., the amplification primers are universal primers or adapters are ligated to the nucleic acid being analyzed and the amplification primers are specific to the adapter. Examples of PCR techniques include, but are not limited to, the amplification primers are universal primers or adapters are ligated to the nucleic acid being analyzed and the amplification primers are specific to the adapter. Examples of PCR techniques include, but are not limited to, but hot start PCR, nested PCR, in situ polony (ony) PCR, in situ rolling circle amplification (RCA), bridge (br idge), picotiter PCR and emulsion PCR are included . Other suitable amplification methods include ligase chain reaction (LCR), transcription amplification, self-sustained sequence replication, selective amplification of target polynucleotide sequences, consensus sequence primed (con sensus sequence primed) polymerase chain reaction (CP-PCR ), arbitrarily primed polymerase chain reaction ( AP-PCR), degenerate oligonucleotide primed PCR (DOP-PCR) and nucleic acid-based sequence amplification (NABSA). Other amplification methods that can be used to amplify specific polymorphic loci include those described in U.S. Patent Nos. 5,242,794, 5,494,810 , 4,988,617 and 6,582,938 are included .

[0071] After amplification, the amplified nucleic acid is sequenced. Sequencing can be achieved using high-throughput systems . Some of these high-throughput systems allow detection of sequencing nucleotides immediately after or during their incorporation into the growing strand (i.e., real-time or substantially real-time sequence detection). In some cases, high-throughput sequencing can be at least 1,000, at least 5,000, at least 10,000, at least 20,000, at least 30,000, at least 40,0 00, at least 50,000, at least 100,000 or at least 500,0 00 sequences per hour Providing 0 array reads, where each read is at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, at least 120 or at least 150 bases per read. Sequencing can be performed using the nucleic acids, genomic DNA, cDNA or RNA derived from RNA transcripts described herein as templates. In some embodiments, high-throughput sequencing includes the use of technologies available from Helicos Bio Sciences Corporation (Cambridge, Massachusetts), such as Single

[0072] Molecule Sequencing by Synthesis (SMSS). SMSS is unique in that it enables whole-genome sequencing without the need for a pre-amplification step. Thus, non-linearity and distortion in nucleic acid measurements are reduced. SMSS is partially described in US Published Application Nos. 2006002471I, 20060024678, 20060012793, 20060012784 and 20050100932. In some embodiments, high-throughput sequencing includes the use of technologies available from 454 Life Sciences, Inc. (Branford, Connecticut), such as the use of a Pico Titer Plate device. The device transmits a chemiluminescent signal generated by a sequencing reaction recorded by a CCD camera within the device through a fiber optic plate.

[0073] ​​​​​​​​​​including. This use of the optical fiber enables detection within at least 20 million base pairs in 4.5 hours or less.

[0074] Methods for using bead amplification and subsequent optical fiber detection are described in Marguiles, M. et al., "Genome seque ncing in microfabricated high-density pr icolitre reactors", Nature, doi:10.1038 / na ture03959, as well as U.S. Published Application Nos. 20020012930, 200300 58629, 20030100102, 20030148344, 2004024816 1, 20050079510, 20050124022 and 20060078909. are described.

[0075] In some embodiments, high-throughput sequencing is performed using a Clonal Single Molecule Array (Solexa, Inc.) or sequencing-by-synthesis (SBS) that utilizes reversible terminator chemistry. These technologies are described in part in U.S. Patent Nos. 6,969,488, 6,897,023, 6,833,2 46, 6,787,308 and U.S. Published Application Nos. 20040106130, 2 0030064398, 20030022207 and Constans, A., The Scientist 2003, 17(13):36. are described.

[0076] In some embodiments of this aspect, high-throughput sequencing of RNA or DNA determination can be performed by using an AnyDot chip (Genovoxx, Germany). The AnyDot chip enables monitoring of biological processes, such as miRNA expression or allelic variability (SNP detection). In particular, the AnyDot chip enables a 10- to 50-fold enhancement of nucleotide fluorescence signal detection. The AnyDot . chip and its method of use are described in part in International Publication Nos. WO 02088382, WO 030 20968, WO 03031947, WO 2005044836, PCTEP 0 5105657, PCMEP 05105655 and German Patent Application Nos. DE 10 1 49 786, DE 102 14 395, DE 103 56 837, DE 10 2004 009 704, DE 10 2004 025 696, DE 10 2004 025 746, DE 10 2004 025 694, DE 10 2 004 025 695, DE 10 2004 025 744, DE 10 200 4 025 745 and DE 10 2005 012 301.

[0077] Other high-throughput sequencing systems include those disclosed in Venter, J. et al., Science 16 February 2001; Adams, M. et al., Science 24 March 2000; and M.J, Levene et al., Science 299:682-686 , January 2003; as well as U.S. Published Application Nos. 20030044781 and 2006 / 0078937. Collectively, such systems ​Sequencing a target nucleic acid molecule having a plurality of bases by time - addition of bases by a polymerization reaction measured on a nucleic acid molecule. That is, tracking in real - time the activity of a nucleic acid polymerase on the template nucleic acid molecule to be sequenced. Then, by identifying which base is incorporated into the growing complementary strand of the target nucleic acid by the catalytic activity of the nucleic acid polymerase in each step of a series of base additions, the sequence can be deduced. A polymerase on a target nucleic acid molecule complex is provided at a position suitable for moving along the target nucleic acid molecule and extending an oligonucleotide primer at the active site. A plurality of types of labeled nucleotide analogs are provided in the vicinity of the active site, and each distinguishable type of nucleotide analog is complementary to a different nucleotide in the target nucleic acid sequence. The growing nucleic acid strand is extended by using the polymerase to add a nucleotide analog to the nucleic acid strand at the active site, where the added nucleotide analog is complementary to the nucleotide of the target nucleic acid at the active site. Identify the nucleotide analog added to the oligonucleotide primer as a result of the polymerization step. The steps of providing a labeled nucleotide analog, polymerizing the growing nucleic acid strand, and identifying the added nucleotide analog are repeated to further extend the nucleic acid strand and determine the sequence of the target nucleic acid. In some embodiments, shotgun sequencing is performed. In shotgun sequencing, DNA is randomly fragmented into a number of small fragments, and these are sequenced using the chain - termination method to obtain reads. By performing several rounds of this fragmentation and sequencing, a plurality of overlapping reads regarding the target DNA are obtained. Then, a computer program is used to assemble the reads into a contiguous sequence. In some embodiments, the target nucleic acid molecule is an RNA molecule, and reverse transcriptase is used to convert the RNA into cDNA before sequencing. In some embodiments, the polymerase is a DNA polymerase or an RNA polymerase, depending on the nature of the target nucleic acid molecule. The nucleotide analogs may be fluorescently labeled, radiolabeled, or otherwise labeled to facilitate their identification. The computer program for assembling the reads may use algorithms such as the overlap - layout - consensus (OLC) algorithm or the de Bruijn graph algorithm. The method may further include validating the determined sequence by comparing it with known sequences in a database or by performing additional experimental verification. In some cases, errors in the sequence determination may occur, and error - correction techniques may be applied to improve the accuracy of the sequence. The target nucleic acid molecule may be obtained from various sources, such as biological samples (e.g., blood, tissue), environmental samples, or synthetic constructs. The method can be used for sequencing genomes, transcriptomes, or other nucleic acid - based molecules of interest. The efficiency of the sequencing process can be affected by factors such as the concentration of the polymerase, the nucleotide analogs, and the template nucleic acid molecule. Advantages of this sequencing method may include high throughput, real - time monitoring, and the ability to sequence long nucleic acid molecules without extensive fragmentation. Disadvantages may include potential errors in nucleotide addition, limitations in the types of nucleotide analogs available, and the complexity of data analysis. Future developments in this field may focus on improving the accuracy of nucleotide addition, developing new types of nucleotide analogs with better properties, and enhancing the efficiency of data analysis algorithms.

[0078] In some embodiments, shotgun sequencing is performed. In shotgun sequencing, DNA is randomly fragmented into a number of small fragments, and these are sequenced using the chain - termination method to obtain reads. By performing several rounds of this fragmentation and sequencing, a plurality of overlapping reads regarding the target DNA are obtained. Then, a computer program is used to assemble the reads into a contiguous sequence. The computer program for assembling the reads may use algorithms such as the overlap - layout - consensus (OLC) algorithm or the de Bruijn graph algorithm. The method may further include validating the determined sequence by comparing it with known sequences in a database or by performing additional experimental verification. Use the overlapping ends of different leads and join them into a continuous chain.

[0079] In some embodiments, the present invention provides a method for detecting and quantifying microbial sequences by sequencing. In this case, it is possible to estimate the detection sensitivity. There are two sensitivity components as follows: (i) the number of molecules being analyzed (depth of sequencing) and (ii) the error rate of the sequencing process. Regarding the depth of sequencing, a frequent estimate regarding the variation between individuals is that about 1 base differs per 1000 bases. Currently, sequencers such as the Illumina Genome Analyzer are reading lengths exceeding 36 base pairs. The fraction of host DNA in the blood can be variable depending on the individual's condition, but it is possible to adopt 90% as a baseline estimate. In this fraction of donor DNA, about 1 out of 10 molecules being analyzed will be of microbial origin. On the Genome Analyzer, it is possible to obtain about 10 million molecules per analysis channel, and there are 8 analysis channels per run of the device. Therefore, when loading 1 sample per channel, it should be possible to detect about 10 molecules that are informative regarding the microbiome state and can be identified as microbes. Higher sensitivity can be achieved simply by sequencing a larger number of molecules, i.e., by using a larger number of channels. 6 The sequencing error rate also affects the sensitivity of this technology. A typical sequencing error regarding base substitution

[0080] The fixed error rate varies between platforms but is 0.5 - 1.5%. This imposes potential limitations on the sensitivity of 0.1 6 - 0.50%. However, as demonstrated by Helicos BioSc iences (Harris, T.D. et al., Science, 320, 106 - 109( 2008)), it is possible to systematically reduce the sequencing error rate by re - sequencing the sample template multiple times. One application of re - sequencing will likely reduce the expected error rate.

[0081] After sequencing, the sequence dataset is uploaded to a data processor for bioinformatics analysis to subtract the host sequence (i.e., human, cat, dog, etc.), and to determine the presence and prevalence of microbial sequences by, for example, comparing the coverage of the sequences that map to the microbial reference sequences with the coverage of the host reference sequences. Subtraction of the host sequence may include the step of identifying the reference host sequence and masking microbial sequences or microbial mimic sequences present within the reference host genome. Similarly, determination of the presence of microbial sequences by comparison with the microbial reference sequences may include the step of identifying the reference microbial sequence and masking host sequences or host mimic sequences present within the reference microbial genome.

[0082] To confirm the quality of the sequences, remove residues of sequencer - specific nucleotides (adapter sequences), merge overlapping paired - end reads, and obtain a higher - quality consensus sequence with fewer read errors, the dataset may be optionally cleaned. Repetitive sequences are identified as having the same starting site and length, and duplicates may be removed from the analysis. ​

[0083] An important feature of the present invention is the subtraction of the human sequence from the analysis. Since the amplification / sequencing step is unbiased, the dominant sequence in the sample will be the host sequence. The subtraction process can be optimized in several ways to improve the speed and accuracy of the process. This is, for example, carried out by performing multiple subtractions, where the initial alignment is set to a coarse filter [i.e., using a fast aligner], and additional alignments are performed with a finer filter [i.e., a sensitive aligner]. Since the amplification / sequencing step is unbiased, the dominant sequence in the sample will be the host sequence. The subtraction process can be optimized in several ways to improve the speed and accuracy of the process. This is, for example, carried out by performing multiple subtractions, where the initial alignment is set to a coarse filter [i.e., using a fast aligner], and additional alignments are performed with a finer filter [i.e., a sensitive aligner]. Since the amplification / sequencing step is unbiased, the dominant sequence in the sample will be the host sequence. The subtraction process can be optimized in several ways to improve the speed and accuracy of the process. This is, for example, carried out by performing multiple subtractions, where the initial alignment is set to a coarse filter [i.e., using a fast aligner], and additional alignments are performed with a finer filter [i.e., a sensitive aligner]. Since the amplification / sequencing step is unbiased, the dominant sequence in the sample will be the host sequence. The subtraction process can be optimized in several ways to improve the speed and accuracy of the process. This is, for example, carried out by performing multiple subtractions, where the initial alignment is set to a coarse filter [i.e., using a fast aligner], and additional alignments are performed with a finer filter [i.e., a sensitive aligner]. Since the amplification / sequencing step is unbiased, the dominant sequence in the sample will be the host sequence. The subtraction process can be optimized in several ways to improve the speed and accuracy of the process. This is, for example, carried out by performing multiple subtractions, where the initial alignment is set to a coarse filter [i.e., using a fast aligner], and additional alignments are performed with a finer filter [i.e., a sensitive aligner]. Since the amplification / sequencing step is unbiased, the dominant sequence in the sample will be the host sequence. The subtraction process can be optimized in several ways to improve the speed and accuracy of the process. This is, for example, carried out by performing multiple subtractions, where the initial alignment is set to a coarse filter [i.e., using a fast aligner], and additional alignments are performed with a finer filter [i.e., a sensitive aligner].

[0084] The read database is initially aligned (aligned) against the human reference genome (including, but not limited to, the Genbank hg19 reference sequence) for subtracting host DNA by bioinformatics. Each sequence is aligned with the best fit sequence within the human reference sequence. Since humans have been removed from the analysis by bioinformatics, the sequences are positively identified. The read database is initially aligned (aligned) against the human reference genome (including, but not limited to, the Genbank hg19 reference sequence) for subtracting host DNA by bioinformatics. Each sequence is aligned with the best fit sequence within the human reference sequence. Since humans have been removed from the analysis by bioinformatics, the sequences are positively identified. The read database is initially aligned (aligned) against the human reference genome (including, but not limited to, the Genbank hg19 reference sequence) for subtracting host DNA by bioinformatics. Each sequence is aligned with the best fit sequence within the human reference sequence. Since humans have been removed from the analysis by bioinformatics, the sequences are positively identified. The read database is initially aligned (aligned) against the human reference genome (including, but not limited to, the Genbank hg19 reference sequence) for subtracting host DNA by bioinformatics. Each sequence is aligned with the best fit sequence within the human reference sequence. Since humans have been removed from the analysis by bioinformatics, the sequences are positively identified. The read database is initially aligned (aligned) against the human reference genome (including, but not limited to, the Genbank hg19 reference sequence) for subtracting host DNA by bioinformatics. Each sequence is aligned with the best fit sequence within the human reference sequence. Since humans have been removed from the analysis by bioinformatics, the sequences are positively identified.

[0085] The reference human sequence can also be optimized by adding contigs with a high hit rate that include (but are not limited to) highly repetitive sequences present in the genome that are not well represented in the reference database. When using a database containing a large set of human sequences (e.g., the entire NCBI NT database), a significant amount of the reads that do not align to hg19 are ultimately identified as human at a later stage in the process. Removing these reads earlier in the analysis The reference human sequence can also be optimized by adding contigs with a high hit rate that include (but are not limited to) highly repetitive sequences present in the genome that are not well represented in the reference database. When using a database containing a large set of human sequences (e.g., the entire NCBI NT database), a significant amount of the reads that do not align to hg19 are ultimately identified as human at a later stage in the process. Removing these reads earlier in the analysis The reference human sequence can also be optimized by adding contigs with a high hit rate that include (but are not limited to) highly repetitive sequences present in the genome that are not well represented in the reference database. When using a database containing a large set of human sequences (e.g., the entire NCBI NT database), a significant amount of the reads that do not align to hg19 are ultimately identified as human at a later stage in the process. Removing these reads earlier in the analysis The reference human sequence can also be optimized by adding contigs with a high hit rate that include (but are not limited to) highly repetitive sequences present in the genome that are not well represented in the reference database. When using a database containing a large set of human sequences (e.g., the entire NCBI NT database), a significant amount of the reads that do not align to hg19 are ultimately identified as human at a later stage in the process. Removing these reads earlier in the analysis The reference human sequence can also be optimized by adding contigs with a high hit rate that include (but are not limited to) highly repetitive sequences present in the genome that are not well represented in the reference database. When using a database containing a large set of human sequences (e.g., the entire NCBI NT database), a significant amount of the reads that do not align to hg19 are ultimately identified as human at a later stage in the process. Removing these reads earlier in the analysis The reference human sequence can also be optimized by adding contigs with a high hit rate that include (but are not limited to) highly repetitive sequences present in the genome that are not well represented in the reference database. When using a database containing a large set of human sequences (e.g., the entire NCBI NT database), a significant amount of the reads that do not align to hg19 are ultimately identified as human at a later stage in the process. Removing these reads earlier in the analysis This can be done by constructing an extended human reference. This reference is an initial human human sequence database other than the reference having a high coverage rate after read subtraction (e.g., , NCBI NT database) by identifying human contigs in and is made. Those contigs are added to the human reference to give a more comprehensive reference set. Furthermore, newly constructed human contigs from cohort studies can be used as additional masks for human-derived reads .

[0086] Regions of the human genome reference sequence containing non-human sequences, e.g., viral and bacterial sequences integrated within the genome of a reference sample, can be masked. For example, Epstein-Barr virus (EBV) has approximately 80% of its genome integrated within hg19. For example, Epstein-Barr virus (EBV) has approximately 80% of its genome integrated within hg19.

[0087] Subsequently, sequence reads identified as non-human are aligned against a nucleotide database of microbial reference sequences. The database can be selected for microbial sequences known to be associated with the host (e.g., human commensal and pathogenic microorganisms). Subsequently, sequence reads identified as non-human are aligned against a nucleotide database of microbial reference sequences. The database can be selected for microbial sequences known to be associated with the host (e.g., human commensal and pathogenic microorganisms). The database can be optimized such that contaminating sequences are masked or removed. For example, a number of public database entries have been found to contain artifact sequences not derived from the microorganism, e.g.,

[0088] primer sequences, host sequences, and other contaminants. It is desirable to perform an initial alignment or multiple alignments on the database. Regions showing irregularities in read coverage when multiple samples are aligned can be masked or removed as artifacts. Detection of such irregular coverages can be performed using various metrics, e.g., primer sequences, host sequences, and other contaminants. It is desirable to perform an initial alignment or multiple alignments on the database. Regions showing irregularities in read coverage when multiple samples are aligned can be masked or removed as artifacts. Detection of such irregular coverages can be performed using various metrics, e.g., are aligned can be masked or removed as artifacts. Detection of such irregular coverages can be performed using various metrics, e.g., such irregular coverages can be detected using various metrics, e.g., For example, it can be performed by the ratio of the coverage rate of a specific nucleotide to the average coverage rate of all contigs in which this nucleotide is found. Generally, sequences represented as being greater than about 5 times, about 10 times, about 25 times, about 50 times, about 100 times the average coverage rate of the reference sequence are artifacts. Alternatively, if the total coverage rate of the contig is given, a binomial test can be applied to obtain the per-base likelihood of the coverage rate. Removal of contaminating sequences from the reference database enables accurate identification of microorganisms. Improvement of the database by alignment of samples is an advantage of the method of the present invention. For example, the database can be aligned with 1, 10, 20, 50, 100 or more samples to improve the database before commercial or clinical use. Each high-confidence read can be aligned against multiple organisms within a given microbial database. Based on this possible mapping redundancy, an algorithm is used to calculate the most likely organism selected by the algorithm to accurately assign the organism abundance (see, for example, Lindner et al., Nucl. Acids Res. (2013) 41(1):e10). For example, the GRAMMy or GASic algorithm can be used to calculate the most likely organism from which a given read is derived. These data provide information regarding the presence of microorganisms in the cell-free nucleic acid sample. Alignment and assignment to host sequences or microbial coordinates can be performed by methods recognized in the art. For example, a 50 nt read can be aligned over the length of the read against a reference database. Removal of contaminating sequences from the reference database enables accurate identification of microorganisms. Improvement of the database by alignment of samples is an advantage of the method of the present invention. For example, the database can be aligned with 1, 10, 20, 50, 100 or more samples to improve the database before commercial or clinical use.

[0089] Each high-confidence read can be aligned against multiple organisms within a given microbial database. Based on this possible mapping redundancy, an algorithm is used to accurately assign the organism abundance by calculating the most likely organism selected by the algorithm (see, for example, Lindner et al., Nucl. Acids Res. (2 013) 41(1):e10). For example, the GRAMMy or GASic algorithm can be used to calculate the most likely organism from which a given read is derived. These data provide information regarding the presence of microorganisms in the cell-free nucleic acid sample. Alignment and assignment to host sequences or microbial coordinates can be performed by methods recognized in the art. For example, a 50 nt read can be

[0090] aligned over the length of the read against a reference database. If there are 1 or fewer mismatches, 2 or fewer mismatches, 3 or fewer mismatches, 4 or fewer mismatches, 5 or fewer mismatches, etc., it can be attributed as a match to the given genome. Commercially available algorithms are generally used for alignment and identification. Non-limiting examples of such alignment algorithms include the bowtie2 program (Johns Hopkins University). For example, based on the desired alignment speed, a preset option in end-to-end mode can be selected. ···Very fast: same as below: -D5 -R1 -N0 -L22 -iS,0,2.50 ···Fast: same as below: -D10 -R2 -N0 -L22 -iS,0,2.50 ···Sensitive: same as below: -D15 -R2 -L22 -iS,1,1.15 ···Very sensitive: same as below: -D20 -R3 -N0 -L20 -iS,1,0.50 In other alignment algorithms or software packages, equivalent settings can be used.

[0091] Then, these attributions of reads to organisms (i.e., host or microbiome components) are summed and used to calculate the estimated number of reads attributed to each organism in the given sample (in the case of determining the prevalence of organisms in a cell-free nucleic acid sample). The analysis normalizes the count with respect to the size of the microbial genome, resulting in the calculation of the coverage rate for that microbe. Taking into account the differences in sequencing depth between samples, the normalized coverage rate for each microbe is compared to the host sequence coverage rate in the same sample.

[0092]

[0093] ​​​​​​​​​​ The final determination provides a set of data on the prevalence of microorganisms and the microorganisms represented by the sequences in the sample. These data are optionally integrated and presented in a form of a report provided to, for example, an individual or a healthcare provider for immediate visualization, or presented in a browser form with hyperlinked data. The coverage estimate is integrated with the metadata from the sample and can be sorted into tables and drawings for each sample or cohort of samples.

[0094] Optionally, the host sequences removed by the filter can be used for other purposes, such as personalized medicine. For example, a certain SNP in the human genome can enable a physician to determine the drug sensitivity of a given patient. Human-derived sequences can represent the integration of viruses (e.g., EBV, HPV, polyomavirus) into the host genome. Alternatively, it can be used for synergistic clinical applications (e.g., cell-free tumor DNA can be used to monitor cancer progression in parallel with monitoring for infection in a patient who is highly susceptible to infection due to chemotherapy).

[0095] In some embodiments, the analysis of cell-free nucleic acids is used to calculate a pathogenicity score, where the pathogenicity score is a numerical or alphabetical value that summarizes the overall pathogenicity of the organism, for example, to facilitate interpretation by a healthcare practitioner. Different scores can be assigned to the microorganisms present in the microbiome. The final "pathogenicity score" is a combination of a number of different factors and is typically on an arbitrary scale, for example, in the range of 0 - 1, 0 - 10, or 0 - 100 for all observations regarding the microbiome of interest. ​​​​​​​​​​​​​​​It is provided as, for example, a percentile from the resulting pathogenicity score. Specific parameters and the weights of those parameters can be determined experimentally, for example, by fitting a function to the observed disease severity, or manually by setting the importance of various parameters and criteria. The weights of the parameters are, for example, experimentally determined by fitting a function to the observed disease severity, or manually by setting the importance of various parameters and criteria. and can be determined manually.

[0096] Factors important in calculating the pathogenicity score include, but are not limited to, for example, the abundance of a microorganism in a reference subject or subject group (e.g., a test population), compared to the number of reads in a human read compared to the abundance of the microorganism calculated by the number of reads, known infections, known uninfected individuals, etc. Specific mutations found within the microbial genome can be performed with reference to databases of microbial-related toxicity, pathogenicity, antibiotic resistance, etc., and include, but are not limited to, SNPs, indels, plasmids, etc. The co-occurrence of specific microorganisms, including, but not limited to, specific ratios and groups of organisms. The expression of a certain sequence (e.g., detection of mRNA) may be important for the pathogenicity score, providing information rich in, for example, whether the microorganism is actively replicating or latent. Geographic features (where geography serves as an indicator of exposure to the microorganism of interest), such as the host's travel history, interaction with infected individuals, etc., may also be included. For example, the abundance of a microorganism calculated by the number of reads compared to the number of reads in a human read compared to the abundance of the microorganism in a reference subject or subject group (e.g., a test population), known infections, known uninfected individuals, etc. can be included. Specific mutations found within the microbial genome can be performed with reference to databases of microbial-related toxicity, pathogenicity, antibiotic resistance, etc., and include, but are not limited to, SNPs, indels, plasmids, etc. and include, but are not limited to, SNPs, indels, plasmids, etc. The co-occurrence of specific microorganisms, including, but not limited to, specific ratios and groups of organisms. The expression of a certain sequence (e.g., detection of mRNA) may be important for the pathogenicity score, providing information rich in, for example, whether the microorganism is actively replicating or latent. Geographic features (where geography serves as an indicator of exposure to the microorganism of interest), such as the host's travel history, interaction with infected individuals, etc., may also be included. For example, the abundance of a microorganism calculated by the number of reads compared to the number of reads in a human read compared to the abundance of the microorganism in a reference subject or subject group (e.g., a test population), known infections, known uninfected individuals, etc. can be included.

[0097] Also provided are reagents and kits for performing one or more of the above methods. The reagents and kits can be of various types. Reagents of interest include reagents specially designed for use in the above production: (i) microbiome and individual profiles, (ii) identification of microbiome profiles, and (ii) obtained from an individual The reagents and kits can be of various types. Reagents of interest include reagents specially designed for use in the above production: (i) microbiome and individual profiles, (ii) identification of microbiome profiles, and (ii) obtained from an individual The reagents of interest include reagents specially designed for use in the above production: (i) microbiome and individual profiles, (ii) identification of microbiome profiles, and (ii) obtained from an individual ​​​ Detection and / or quantification of one or more nucleic acids from the microbiota in a sample. The kit may include reagents necessary to perform nucleic acid extraction and / or nucleic acid detection using the methods described herein, such as PCR and sequencing. The kit may further include a software package for data analysis, which may include a reference profile for comparison with a test profile, and in particular, may include an optimized reference database as described above. The kit may include reagents such as buffers and H2O. Such a kit may also include scientific references, package inserts, clinical trial results, and / or summaries thereof, etc., that demonstrate and / or establish the activity and / or advantages of the composition, and / or describe dosage, administration, side effects, drug interactions, or other information useful to a healthcare provider. Such a kit may also include instructions for accessing a database. Such information may be based on the results of various studies, such as studies using experimental animals, including in vivo models, and studies based on human clinical trials. The kits described herein may be provided, sold, and / or promoted to healthcare providers, including physicians, nurses, pharmacists, prescribing staff, etc. The kit may, in some embodiments, be sold directly to consumers.

[0098] Any of the above methods may be performed by a computer program product that includes computer-executable logic recorded on a computer-readable medium. For example, the computer program

[0099] The computer-executable logic can perform some or all of the following functions: (i) controlling the isolation of nucleic acids from a sample ; (ii) pre-amplifying nucleic acids from a sample; (iii) amplifying, sequencing, and aligning specific regions in a sample ; (iv) identifying and quantifying microbial sequences in a sample; (v) comparing data regarding the presence or prevalence of detected microorganisms from a sample to a predetermined threshold; (vi) determining infection, microbiome integrity, immune status, or outcome; (vi) indicating the sample status regarding infection, microbiome integrity, immunity, etc. ; (vi) indicating the sample status regarding infection, microbiome integrity, immunity, etc. .

[0100] The computer-executable logic can operate on any of a variety of types of general-purpose computers, such as a personal computer, a network server, a workstation, or other computer platform (whether currently being developed or subsequently developed). In some embodiments, a computer program product is described that includes a computer-usable medium having computer-executable logic (including computer software programs with program code) stored therein. The computer-executable logic is executed by a processor and can cause the processor to perform the functions described herein. In other embodiments, some functions are performed primarily in hardware, for example, using a hardware state machine. The implementation of a hardware state machine for performing the functions described herein will be apparent to those skilled in the relevant art. The computer-executable logic is executed by a processor and can cause the processor to perform the functions described herein. In other embodiments, some functions are performed primarily in hardware, for example, using a hardware state machine. The implementation of a hardware state machine for performing the functions described herein will be apparent to those skilled in the relevant art. The program is for microbiome and individual profiling and / or individual ; (iii) amplifying, sequencing, and aligning specific regions in a sample; (iv) identifying and quantifying microbial sequences in a sample; (v) comparing data regarding the presence or prevalence of detected microorganisms from a sample to a predetermined threshold; (vi) determining infection, microbiome integrity, immune status, or outcome; (vi) indicating the sample status regarding infection, microbiome integrity, immunity, etc. .

[0101] The program is for microbiome and individual profiling and / or individual Access to data reflecting the quantification of one or more nucleic acids from the microbiota during circulation of can provide a method for assessing the state of microorganisms in an individual.

[0102] In one embodiment, the computer that executes the computer logic of the present invention may also include a digital input device, such as a scanner. The digital input device can provide information regarding nucleic acids (e.g., presence or prevalence).

[0103] In some embodiments, the present invention provides a computer-readable medium that ( i) receives data from one or more nucleic acids detected in a sample, and (ii) causes a computer to perform a step of diagnosing or predicting a condition based on the quantification of the microbiota. The computer-readable medium includes a set of instructions recorded thereon for such purpose.

[0104] Also provided is a database of microbial reference sequences and a database of human reference sequences. Such databases will typically include the optimization data sets described above.

[0105] In some embodiments, the method of the present invention provides the state of an individual with respect to infection. In some such embodiments, the microbial infection is a pathogen, where the presence of the pathogen sequence indicates a clinically relevant infection. In other embodiments, the morbidity (prevalence) serves as an indicator of the microbial load, where a predetermined level serves as an indicator of clinical relevance. In some such embodiments, the individual is treated with an antimicrobial therapy, such as an antibiotic, passive or active immunotherapy, an antiviral agent, etc., or such treatment is considered. The individual can be tested before, during, and after treatment.

[0106] Microbial infections can also be indicated by the burden on symbiotic organisms, where the level of symbiotic organisms in a blood sample is an indicator of gut health (e.g., intestinal lumen disruption). The level of symbiotic organisms in a blood sample is an indicator of gut health (e.g., intestinal lumen disruption).

[0107] Comparison of microbial RNA can be done alone or in relation to microbial DNA, where excess RNA with respect to microbial sequences (e.g., about 5-fold, 10-fold, 15-fold, 20-fold, 25-fold of the coverage of microbial DNA) is an indicator of active infection. In some embodiments, the microbes analyzed in this way are microbes capable of latent infection, such as herpes virus, hepatitis virus, etc. Comparison of microbial RNA can be done alone or in relation to microbial DNA, where excess RNA with respect to microbial sequences (e.g., about 5-fold, 10-fold, 15-fold, 20-fold, 25-fold of the coverage of microbial DNA) is an indicator of active infection. In some embodiments, the microbes analyzed in this way are microbes capable of latent infection, such as herpes virus, hepatitis virus, etc. Comparison of microbial RNA can be done alone or in relation to microbial DNA, where excess RNA with respect to microbial sequences (e.g., about 5-fold, 10-fold, 15-fold, 20-fold, 25-fold of the coverage of microbial DNA) is an indicator of active infection. In some embodiments, the microbes analyzed in this way are microbes capable of latent infection, such as herpes virus, hepatitis virus, etc. Comparison of microbial RNA can be done alone or in relation to microbial DNA, where excess RNA with respect to microbial sequences (e.g., about 5-fold, 10-fold, 15-fold, 20-fold, 25-fold of the coverage of microbial DNA) is an indicator of active infection. In some embodiments, the microbes analyzed in this way are microbes capable of latent infection, such as herpes virus, hepatitis virus, etc. Comparison of microbial RNA can be done alone or in relation to microbial DNA, where excess RNA with respect to microbial sequences (e.g., about 5-fold, 10-fold, 15-fold, 20-fold, 25-fold of the coverage of microbial DNA) is an indicator of active infection. In some embodiments, the microbes analyzed in this way are microbes capable of latent infection, such as herpes virus, hepatitis virus, etc.

[0108] In other embodiments, there is interest in the overall estimation of the microbiome, in which case there is interest in the relative presence or prevalence of classes of microbes. Diet, and treatment with drugs such as statins, antibiotics, immunosuppressants, etc. are known in the art to be able to affect the overall health of the microbiome, and thus there is interest in determining the composition of the microbiome. In other embodiments, there is interest in the overall estimation of the microbiome, in which case there is interest in the relative presence or prevalence of classes of microbes. Diet, and treatment with drugs such as statins, antibiotics, immunosuppressants, etc. are known in the art to be able to affect the overall health of the microbiome, and thus there is interest in determining the composition of the microbiome. In other embodiments, there is interest in the overall estimation of the microbiome, in which case there is interest in the relative presence or prevalence of classes of microbes. Diet, and treatment with drugs such as statins, antibiotics, immunosuppressants, etc. are known in the art to be able to affect the overall health of the microbiome, and thus there is interest in determining the composition of the microbiome. In other embodiments, there is interest in the overall estimation of the microbiome, in which case there is interest in the relative presence or prevalence of classes of microbes. Diet, and treatment with drugs such as statins, antibiotics, immunosuppressants, etc. are known in the art to be able to affect the overall health of the microbiome, and thus there is interest in determining the composition of the microbiome. In other embodiments, there is interest in the overall estimation of the microbiome, in which case there is interest in the relative presence or prevalence of classes of microbes. Diet, and treatment with drugs such as statins, antibiotics, immunosuppressants, etc. are known in the art to be able to affect the overall health of the microbiome, and thus there is interest in determining the composition of the microbiome.

[0109] In some embodiments, differences in the amount of said one or more nucleic acids from the microbiome over time are used to monitor the effectiveness of antimicrobial treatment and / or to select a treatment. For example, the amount of one or more nucleic acids from the microbiome can be measured before and after treatment. A decrease in the amount of one or more nucleic acids from the microbiome after treatment can indicate that the treatment was successful. Also, the amount of one or more nucleic acids from the microbiome can be used for selection between treatments, e.g., for selection between treatments of different intensities. In some embodiments, differences in the amount of said one or more nucleic acids from the microbiome over time are used to monitor the effectiveness of antimicrobial treatment and / or to select a treatment. For example, the amount of one or more nucleic acids from the microbiome can be measured before and after treatment. A decrease in the amount of one or more nucleic acids from the microbiome after treatment can indicate that the treatment was successful. Also, the amount of one or more nucleic acids from the microbiome can be used for selection between treatments, e.g., for selection between treatments of different intensities. In some embodiments, differences in the amount of said one or more nucleic acids from the microbiome over time are used to monitor the effectiveness of antimicrobial treatment and / or to select a treatment. For example, the amount of one or more nucleic acids from the microbiome can be measured before and after treatment. A decrease in the amount of one or more nucleic acids from the microbiome after treatment can indicate that the treatment was successful. Also, the amount of one or more nucleic acids from the microbiome can be used for selection between treatments, e.g., for selection between treatments of different intensities. In some embodiments, differences in the amount of said one or more nucleic acids from the microbiome over time are used to monitor the effectiveness of antimicrobial treatment and / or to select a treatment. For example, the amount of one or more nucleic acids from the microbiome can be measured before and after treatment. A decrease in the amount of one or more nucleic acids from the microbiome after treatment can indicate that the treatment was successful. Also, the amount of one or more nucleic acids from the microbiome can be used for selection between treatments, e.g., for selection between treatments of different intensities. In some embodiments, differences in the amount of said one or more nucleic acids from the microbiome over time are used to monitor the effectiveness of antimicrobial treatment and / or to select a treatment. For example, the amount of one or more nucleic acids from the microbiome can be measured before and after treatment. A decrease in the amount of one or more nucleic acids from the microbiome after treatment can indicate that the treatment was successful. Also, the amount of one or more nucleic acids from the microbiome can be used for selection between treatments, e.g., for selection between treatments of different intensities. In some embodiments, differences in the amount of said one or more nucleic acids from the microbiome over time are used to monitor the effectiveness of antimicrobial treatment and / or to select a treatment. For example, the amount of one or more nucleic acids from the microbiome can be measured before and after treatment. A decrease in the amount of one or more nucleic acids from the microbiome after treatment can indicate that the treatment was successful. Also, the amount of one or more nucleic acids from the microbiome can be used for selection between treatments, e.g., for selection between treatments of different intensities.

[0110] In one aspect, the present invention provides a method for the treatment of immune deficiencies in a subject undergoing an immunosuppressive regimen. The present invention provides a method for diagnosing or predicting transplantation status or outcome after immunosuppression. A sample is taken from the patient and the presence or absence of one or more microbiomes containing virome nucleic acid is detected. In some embodiments, the sample is blood, plasma, Serum or urine. The proportion and / or amount of microbial nucleic acid is monitored over time. It is possible to determine whether the immune response is increased or decreased, and this increase in ratio can be used to determine immune competence. The amount can be determined by any suitable method known in the art, including the methods described herein. For example, this can be done by sequencing, nucleic acid arrays or PCR).

[0111] In some embodiments, one or more microorganisms in a sample from an immunosuppressed recipient are The amount of lobiome nucleic acid is used to determine the transplant status or outcome. In some embodiments, the methods further comprise determining one or more nucleic acids from the microbiome. In some embodiments, the method includes quantifying one or more nucleic acids from a donor sample. The amount is determined as a percentage of the total nucleic acid in the sample. For the purposes of the present invention, the amount of one or more nucleic acids from a donor sample is expressed as a ratio to the total nucleic acid in the sample. In some embodiments, the amount of one or more nucleic acids from a donor sample is determined. The nucleic acid sequence is determined as a ratio or proportion of one or more reference nucleic acids in a pool. The amount of one or more nucleic acids from the nucleic acid sequence is determined to be 10% of the total nucleic acids in the sample; or , the amount of one or more nucleic acids from the microbiome is in a ratio of 1:10 compared to the total nucleic acids in the sample. It is possible. Furthermore, the amount of one or more nucleic acids from the microbiome can be determined to be 10% of a reference gene such as β-globin or a ratio of 1:10. In some embodiments the amount of one or more nucleic acids from the microbiome can be determined as a concentration. For example, the amount of one or more nucleic acids from a donor sample can be determined to be 1 μg / mL.

[0112] In some embodiments, an amount of one or more nucleic acids from the microbiome that exceeds a predetermined threshold serves as an indicator of the immune status. For example, normative values can be determined for clinically stable patients who do not show evidence of transplant rejection or other medical conditions. An increase in the amount of one or more nucleic acids from the microbiome below the normative value for clinically stable post-transplant patients may indicate a stable outcome. On the other hand, an amount of one or more nucleic acids from the microbiome above the normative value for clinically stable post-transplant patients may indicate an enhanced immune function and an increased risk of transplant rejection.

[0113] In some embodiments, if the predetermined threshold is different, the transplant outcome or status it indicates is also different. For example, as described above, an increase in the amount of one or more nucleic acids from the microbiome above the normative value for clinically stable post-transplant patients may indicate a change in the post-transplant status or outcome such as transplant rejection or transplant injury. However, an increase in the amount of one or more nucleic acids from the microbiome above the normative value for clinically stable post-transplant patients and below a predetermined threshold level may indicate a condition that is less severe than transplant rejection, such as a viral infection. An increase in the amount of one or more nucleic acids from the microbiome above a higher threshold may indicate transplant rejection.

[0114] In some embodiments, the temporal differences in the amount of said one or more nucleic acids from the microbiome serve as an indicator of immune competence. For example, to determine the amount of one or more nucleic acids from the microbiome, transplanted patients can be monitored over time. If the amount of one or more nucleic acids from the microbiome decreases over time and then returns to normal levels, this may indicate a condition that is less severe than transplant rejection. On the other hand, a persistent decrease in the amount of one or more nucleic acids from the microbiome may indicate a serious condition, such as lack of effective immunosuppression and transplant rejection. In some embodiments, the temporal differences in the amount of said one or more nucleic acids from the microbiome can be used to monitor the effectiveness of immunosuppressive therapy or to select immunosuppressive therapy. For example, the amount of one or more nucleic acids from the microbiome can be determined before and after immunosuppressive therapy. A decrease in the amount of one or more nucleic acids from the microbiome after treatment may indicate that the treatment has been successful in preventing immune rejection. Also, the amount of one or more

[0115] nucleic acids from the microbiome can be used to select between immunosuppressive therapies, for example, between different intensities of immunosuppressive therapy. For example, a lower amount of one or more nucleic acids from the microbiome may indicate that very strong immunosuppression is required. On the other hand, a higher amount of one or more nucleic acids from the microbiome may indicate that less strong immunosuppression can be used. The present invention provides a highly sensitive and specific method. In some embodiments, the methods described herein for diagnosing or predicting transplant status or outcome have a sensitivity of at least 50 %, 60%, 70%, 80%, 90%, 95% or 100%. In some embodiments, the methods described herein for diagnosing or predicting transplant status or outcome have a specificity of at least 50 %, 60%, 70%, 80%, 90%, 95% or 100%. %, 60%, 70%, 80%, 90%, 95% or 100%. In some embodiments, the methods described herein for diagnosing or predicting transplant status or outcome have a specificity of at least 50 %, 60%, 70%, 80%, 90%, 95% or 100%. For example, a lower amount of one or more nucleic acids from the microbiome may indicate that very strong immunosuppression is required. On the other hand, a higher amount of one or more nucleic acids from the microbiome may indicate that less strong immunosuppression can be used.

[0116] The present invention provides a highly sensitive and specific method. In some embodiments, the methods described herein for diagnosing or predicting transplant status or outcome have a sensitivity of at least 50 %, 60%, 70%, 80%, 90%, 95% or 100%. In some embodiments, the methods described herein for diagnosing or predicting transplant status or outcome have a specificity of at least 50 In embodiments, the methods described herein have a sensitivity of at least 50% . In some embodiments, the methods described herein have a sensitivity of at least 78% . In some embodiments, the methods described herein have a specificity of about 70% to about 100%. In some embodiments, the methods described herein have a specificity of about 80% to about 100%. In some embodiments, the methods described herein have a specificity of about 90% to about 100%. In some embodiments, the methods described herein have a specificity of about 100%.

[0117] The present invention provides non-invasive diagnosis for individuals, including individuals being treated with an immunosuppressive regimen, an antimicrobial agent, etc., and the diagnosis is by monitoring the sequences of cell-free DNA or RNA derived from non-human sources. For example, an individual harbors several viruses, and it is shown herein that the viral load varies depending on the immune ability of the individual. A preferred virus for monitoring immune ability is an anellovirus, and in this case, it is shown herein that the viral load correlates with the immune ability of the individual.

[0118] In some embodiments, the present invention provides methods, devices, compositions and kits for detecting and / or quantifying circulating nucleic acids that are normally free in plasma or from viral particles, or for diagnosing, prognosticating, detecting and / or treating infections, immune ability, transplantation status or outcomes.

[0119] In some specific embodiments, the present invention relates to transplant patients by viroanalysis ​​​​​​​​​Provide an approach for non-invasive detection of immune function, which avoids potential problems of microchimerism from other exogenous sources of DNA and is universal for all organ recipients without consideration of gender. In some embodiments, a genetic fingerprint is created for the individual's virome. This approach enables reliable identification of sequences, which can be done regardless of the gender of the donor and recipient. After an immunosuppressive regimen (e.g., in combination with transplantation, treatment of autoimmune diseases), body fluids such as blood can be collected from a patient and analyzed for markers. Examples of body fluids include, but are not limited to, smear specimens, sputum, biopsies, secretions, cerebrospinal fluid, bile, blood, lymph fluid, saliva, and urine. Detection, identification (characterization), and / or quantification of virome sequences can be performed using real-time PCR, chips, high-throughput shotgun sequencing of circulating nucleic acids (e.g., cell-free DNA), and other methods known in the art (including the methods described herein). The viral load can be monitored over time, and an increase in this ratio can be used to determine the state or outcome of immune function. In any of the embodiments described herein, the graft can be any solid organ or a skin graft. Examples of organ transplants that can be analyzed by the methods described herein include, but are not limited to, kidney transplants, pancreas transplants, liver transplants, heart transplants, lung transplants, intestine transplants, pancreas after kidney transplantation, and simultaneous pancreas-kidney transplants. In some embodiments, the methods of the invention can be used for analysis at the individual level or of patient groups.

[0120] After an immunosuppressive regimen (e.g., in combination with transplantation, treatment of autoimmune diseases), body fluids such as blood can be collected from a patient and analyzed for markers. Examples of body fluids include, but are not limited to, smear specimens, sputum, biopsies, secretions, cerebrospinal fluid, bile, blood, lymph fluid, saliva, and urine. Detection, identification (characterization), and / or quantification of virome sequences can be performed using real-time PCR, chips, high-throughput shotgun sequencing of circulating nucleic acids (e.g., cell-free DNA), and other methods known in the art (including the methods described herein). The viral load can be monitored over time, and an increase in this ratio can be used to determine the state or outcome of immune function. After an immunosuppressive regimen (e.g., in combination with transplantation, treatment of autoimmune diseases), body fluids such as blood can be collected from a patient and analyzed for markers. Examples of body fluids include, but are not limited to, smear specimens, sputum, biopsies, secretions, cerebrospinal fluid, bile, blood, lymph fluid, saliva, and urine. Detection, identification (characterization), and / or quantification of virome sequences can be performed using real-time PCR, chips, high-throughput shotgun sequencing of circulating nucleic acids (e.g., cell-free DNA), and other methods known in the art (including the methods described herein). The viral load can be monitored over time, and an increase in this ratio can be used to determine the state or outcome of immune function. After an immunosuppressive regimen (e.g., in combination with transplantation, treatment of autoimmune diseases), body fluids such as blood can be collected from a patient and analyzed for markers. Examples of body fluids include, but are not limited to, smear specimens, sputum, biopsies, secretions, cerebrospinal fluid, bile, blood, lymph fluid, saliva, and urine. Detection, identification (characterization), and / or quantification of virome sequences can be performed using real-time PCR, chips, high-throughput shotgun sequencing of circulating nucleic acids (e.g., cell-free DNA), and other methods known in the art (including the methods described herein). The viral load can be monitored over time, and an increase in this ratio can be used to determine the state or outcome of immune function. After an immunosuppressive regimen (e.g., in combination with transplantation, treatment of autoimmune diseases), body fluids such as blood can be collected from a patient and analyzed for markers. Examples of body fluids include, but are not limited to, smear specimens, sputum, biopsies, secretions, cerebrospinal fluid, bile, blood, lymph fluid, saliva, and urine. Detection, identification (characterization), and / or quantification of virome sequences can be performed using real-time PCR, chips, high-throughput shotgun sequencing of circulating nucleic acids (e.g., cell-free DNA), and other methods known in the art (including the methods described herein). The viral load can be monitored over time, and an increase in this ratio can be used to determine the state or outcome of immune function. After an immunosuppressive regimen (e.g., in combination with transplantation, treatment of autoimmune diseases), body fluids such as blood can be collected from a patient and analyzed for markers. Examples of body fluids include, but are not limited to, smear specimens, sputum, biopsies, secretions, cerebrospinal fluid, bile, blood, lymph fluid, saliva, and urine. Detection, identification (characterization), and / or quantification of virome sequences can be performed using real-time PCR, chips, high-throughput shotgun sequencing of circulating nucleic acids (e.g., cell-free DNA), and other methods known in the art (including the methods described herein). The viral load can be monitored over time, and an increase in this ratio can be used to determine the state or outcome of immune function. After an immunosuppressive regimen (e.g., in combination with transplantation, treatment of autoimmune diseases), body fluids such as blood can be collected from a patient and analyzed for markers. Examples of body fluids include, but are not limited to, smear specimens, sputum, biopsies, secretions, cerebrospinal fluid, bile, blood, lymph fluid, saliva, and urine. Detection, identification (characterization), and / or quantification of virome sequences can be performed using real-time PCR, chips, high-throughput shotgun sequencing of circulating nucleic acids (e.g., cell-free DNA), and other methods known in the art (including the methods described herein). The viral load can be monitored over time, and an increase in this ratio can be used to determine the state or outcome of immune function. After an immunosuppressive regimen (e.g., in combination with transplantation, treatment of autoimmune diseases), body fluids such as blood can be collected from a patient and analyzed for markers. Examples of body fluids include, but are not limited to, smear specimens, sputum, biopsies, secretions, cerebrospinal fluid, bile, blood, lymph fluid, saliva, and urine. Detection, identification (characterization), and / or quantification of virome sequences can be performed using real-time PCR, chips, high-throughput shotgun sequencing of circulating nucleic acids (e.g., cell-free DNA), and other methods known in the art (including the methods described herein). The viral load can be monitored over time, and an increase in this ratio can be used to determine the state or outcome of immune function. After an immunosuppressive regimen (e.g., in combination with transplantation, treatment of autoimmune diseases), body fluids such as blood can be collected from a patient and analyzed for markers. Examples of body fluids include, but are not limited to, smear specimens, sputum, biopsies, secretions, cerebrospinal fluid, bile, blood, lymph fluid, saliva, and urine. Detection, identification (characterization), and / or quantification of virome sequences can be performed using real-time PCR, chips, high-throughput shotgun sequencing of circulating nucleic acids (e.g., cell-free DNA), and other methods known in the art (including the methods described herein). The viral load can be monitored over time, and an increase in this ratio can be used to determine the state or outcome of immune function.

[0121] In any of the embodiments described herein, the graft can be any solid organ or a skin graft. Examples of organ transplants that can be analyzed by the methods described herein include, but are not limited to, kidney transplants, pancreas transplants, liver transplants, heart transplants, lung transplants, intestine transplants, pancreas after kidney transplantation, and simultaneous pancreas-kidney transplants. In any of the embodiments described herein, the graft can be any solid organ or a skin graft. Examples of organ transplants that can be analyzed by the methods described herein include, but are not limited to, kidney transplants, pancreas transplants, liver transplants, heart transplants, lung transplants, intestine transplants, pancreas after kidney transplantation, and simultaneous pancreas-kidney transplants. In any of the embodiments described herein, the graft can be any solid organ or a skin graft. Examples of organ transplants that can be analyzed by the methods described herein include, but are not limited to, kidney transplants, pancreas transplants, liver transplants, heart transplants, lung transplants, intestine transplants, pancreas after kidney transplantation, and simultaneous pancreas-kidney transplants. In any of the embodiments described herein, the graft can be any solid organ or a skin graft. Examples of organ transplants that can be analyzed by the methods described herein include, but are not limited to, kidney transplants, pancreas transplants, liver transplants, heart transplants, lung transplants, intestine transplants, pancreas after kidney transplantation, and simultaneous pancreas-kidney transplants.

[0122] In some embodiments, the methods of the invention can be used for analysis at the individual level or of patient groups. is used in the determination of the effectiveness of a therapy for the treatment of a disease, including an infection, for example in a clinical trial setting. Such embodiments typically involve a comparison of two time points with respect to a patient or group of patients. As a result of the treatment agent, treatment regimen, or disease challenge to the patient being treated, the patient's condition is expected to differ between the two time points. Examples of forms of such embodiments can include, but are not limited to, analyzing microbiomes at two or more time points, where the first time point is a patient who has been diagnosed but not yet treated, and the second or additional time points are patients who have been treated with a candidate treatment agent or regimen. In another form, the first time point is a diagnosed patient in, for example, disease remission as confirmed by current clinical criteria, as a result of a candidate treatment agent or regimen. The second or additional time points are patients who have been treated with a candidate treatment agent or regimen and challenged with a disease inducer (e.g., in the case of a vaccine).

[0123] In such clinical trial settings, each set of time points can correspond to a single patient, a group of patients, such as a cohort group, or a mixture of individual and group data. As is known in the art, such clinical trial settings can also include additional control data, such as a placebo group, a disease-free group, etc. Embodiments of interest can include crossover studies, randomization, double blinding, placebo control, parallel group trials, and it is also possible to test the effectiveness of a drug, etc. For example, Clinical Trials: A Methodologic Perspective Secon

[0124]

[0125] Trials: A Methodologic Perspective Secon ​​​​​​​​​​d Edition, S. Piantadosi, Wiley-Interscienc e; 2005, ISBN-13: 978-0471727811; and Design and Analysis of Clinical Trials: Concept s and Methodologies, S. Chow and J. Liu, Wiley -Interscience; 2003; ISBN-13: 978-047124985 6 (each of which is specifically incorporated herein by reference) are referred to.

Brief Description of the Drawings

[0126]

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[0127] Example Temporal response of the human virome to immunosuppression and antiviral therapy The viral component of the microbiome, the human virome, is relatively understudied (Wylie et al. (2012) Transl Res 160, 283-290 ), and little is known about the effects of immunomodulatory and antiviral therapies on virome composition. Although the healthy gut virome has been shown to remain remarkably stable over time (Reyes et al. (2010) Nature 466, 334-338), and an association between diet and virome composition has been found, the major cause of variation is differences between subjects (Minot et al. (2011). Genome Research 21, 1616-

[0128] Immunosuppressive therapy significantly reduces the risk of transplant rejection in organ transplantation but increases the susceptibility of the recipient to infection. Infections caused by viral pathogens, particularly herpesviruses such as cytomegalovirus (CMV), occur frequently and increase the risk of transplant failure in the recipient. Therefore, organ transplant recipients are often subjected to antiviral prophylaxis or preemptive therapy against CMV. The inverse correlation between the level of immunosuppression and the risks of infection and rejection allows for only a narrow therapeutic window for the treatment of affected patients. The current availability of numerous constraints on methods for diagnosing infection and rejection further complicates post-transplant care. The diagnosis of rejection is mostly by invasive biopsies, which are observer-variable, costly, and unpleasant for the patient. The symptoms of infection disappear after immunosuppression, and current diagnostic methods, such as antigen detection and PCR-based molecular tests, are target-specific and thus pose a challenge for diagnosing infection, considering that they are based on empirical assumptions about the source of infection.

[0129] As a final complicating factor, variability between patients in sensitivity to immunosuppressive drugs can cause over- and under-immunosuppression, increasing the risk of infection or rejection, respectively. There are few essential methods for measuring the health of the immune system, and the relationship between immune competence and the viral components of the microbiome is not well understood. Organ transplant recipients are treated with post-transplant therapy that combines immunosuppression and antiviral drugs, which provides a means for the effect of immunomodulation on the human virome. The inventors have followed a cohort of organ transplant recipients with high-throughput sequencing of the virome to analyze the dynamics of the viral microbiome during the first year after transplantation. In particular, the inventors have analyzed the temporal dynamics of the viral microbiome in the plasma and gut mucosa of transplant recipients to identify potential biomarkers for predicting the risk of CMV infection and rejection. The present invention provides a method for predicting the risk of CMV infection or rejection in an organ transplant recipient

[0130] by analyzing the composition and dynamics of the viral microbiome in a biological sample obtained from the recipient. The method includes obtaining a biological sample from the recipient, analyzing the viral microbiome in the sample to determine the composition and dynamics of the viral microbiome, and

[0131] predicting the risk of CMV infection or rejection based on the determined composition and dynamics of the viral microbiome. The invention also provides a method for monitoring the effectiveness of immunosuppressive therapy or antiviral therapy in an organ transplant recipient by analyzing the composition and dynamics of the viral microbiome in a biological sample obtained from the recipient. The method includes obtaining a biological sample from the recipient, analyzing the viral microbiome in the sample to determine the composition and dynamics of the viral microbiome, and To investigate drug-virosphere interactions in 656 samples from 96 patients, and to find that antiviral and immunosuppressive agents strongly affect the structure of the plasma virosphere, cell-free DNA sequencing in plasma was used. The inventors have observed significant virosphere compositional dynamics at the start of treatment, finding that total viral load increases with immunosuppression while the bacterial component of the microbiome remains largely unaffected. The data provide insights into the relationship between the human virosphere, the state of the immune system and the effects of pharmacological treatment, and suggest

[0132] potential uses of the virosphere state for predicting immune competence. In this study, the inventors sequenced cell-free DNA circulating in plasma to investigate drug-microbiome interactions after organ transplantation. The inventors examined the infection patterns in heart and lung transplant recipients exposed to combinations of immunosuppressive and antiviral prophylactic agents. The inventors found that immunosuppressive and antiviral agents strongly affect the structure of the viral component of the microbiome but not the bacterial component. The virosphere compositions of various individuals converge to similar drug-defined states, with strong compositional dynamics observed at the start of drug therapy. Viruses,

[0133] 656 plasma samples from 96 solid organ recipients (41 adult hearts, 24 from pediatric hearts and 31 adult lungs over a long period. Cell-free DNA was purified from plasma and sequenced. A total of 820 gigabase pairs (Gbp) of sequencing data were obtained (average 1.2 5 Gbp / sample) (Illumina HiSeq, 1×50 bp reads, Figure 1B ). Organ transplant recipients were continuously enrolled in the study for over 2 years, and samples were collected from the recipients at regular time points after transplantation. Sample collection was highest in the first month after transplantation. Figure 1C shows the number of samples analyzed as a function of time after transplantation for various patient classes.

[0134] Patients within the cohort were treated with antiviral prophylaxis and immunosuppression as part of standard post-transplant therapy (Figure 1D). Maintenance immunosuppression was tacrolimus-based for adult heart and human transplant recipients, complemented with mycophenolate mofetil and prednisone. Pediatric patients were treated with cyclosporine-based rejection prophylaxis. CMV-positive transplant recipients (past CMV infection in recipient and / or donor) were treated with antiviral prophylaxis, and CMV-negative recipients were not. The protocol included high-dose immunosuppressive and antiviral medications in the first few months after transplantation, followed by a gradual reduction in dose as the risk of rejection and infection decreased. Given the narrow therapeutic window available for immunosuppression and the large inter-patient variability in the pharmacokinetics of tacrolimus, tacrolimus concentration was measured directly in blood, and the dose was adjusted to maintain the target drug level. Figure 1D shows the mean levels of tacrolimus measured in blood for tacrolimus- treated patients and illustrates the design of the drug treatment protocol.

[0135] DNA sequence analysis. After subtraction of human-derived sequences by computer (subtraction; subtraction), sequences derived from the microbiome were identified. For this purpose, duplicate and low-quality reads were removed, and the remaining reads were mapped to the human reference genome [build ) hg19 (see BWA (Li and Durbin, 2009), "Methods"). Then, unmapped reads were collected and low-complexity reads were removed . Figure 1E shows the distribution of the remaining read fraction (average 86%) after applying duplicate and quality filters, and the distribution of the remaining fraction after subtraction of human reads (average 2%).

[0136] To identify infectious agents, the remaining high-quality, unique, non-human reads were mapped using BLAST against reference databases of viral (n = 1401), bacterial (n = 1980), and fungal (n = 32) genomes (downloaded from NCBI, Figure 6A). 0.12% of the unique sequencing reads aligned to at least one of the target genomes (Figure 6B, C). We used quantitative PCR (qPCR) assays to target a subset of the targets (herpesviruses 4, 5, 6, and parvovirus) identified by sequencing to verify the positive hits identified by the sequencing-based approach. We found a quantitative agreement between the number of viruses measured by sequencing and qPCR.

[0137] We further show that the sensitivity of the sequencing assay for herpesvirus detection is qPC ​​​​​​​We found that the R measurements were comparable to those of the 1H-sequencer ... The large capture cross-sectional area (compared to the complete target genome and the PCR amplicon target region) is Due to limited efficiency in library preparation and library undersampling This is sufficient to overcome the signal drop in sequencing caused by the The highest CMV load measured using whole-sample sequencing in The study corresponded to two adult heart transplant patients with disseminated CMV infections that were successfully treated (see Figure 6E). (I want to be).

[0138] Potential contamination of reagents used for DNA extraction and sequencing library preparation To test this, we performed two control experiments. First, we used a known template (Lamb da gDNA, Pacbio Part no: 001-119-535) Samples were prepared and DNA purified for sequencing using the workflow described above (Ill umina Miseq, 3.4 million and 3.5 million reads). Lambda-derived sequences were excluded. The remaining sequences (0.4%) were aligned with the BLAST reference database. No evidence was found for the various infectious agents considered in this study, The present inventors have discovered that Enterobacteriaceae bacteria Family (phylum Proteobacteria), mainly E. coli li) and Enterobacteriaceae phages (<1%). These are likely In a second control, we found that the nuclease Sequencing samples were prepared from serum-free water. Along with the pull, it was used in the implementation of array determination, and only a limited number of arrays (a total of 15) were adopted and mapped to the genomes of two bacterial species. Again, no evidence of the infectious agent discussed below was found.

[0139] The inventors used Grammy, a tool that utilizes the sequence similarity data obtained by BLAST to perform maximum likelihood estimation of the relative abundance of species, to examine the microbiome composition in plasma at various levels of taxonomic classification. Grammy takes into account the ambiguity of read attribution and differences in the target genome size. It should be noted that this approach only enables the assessment of the abundance of species for which genomic data is available in the reference database. Figure 1F shows the relative abundance of species at various levels of taxonomic classification (average of all samples). The inventors have found that viruses (73%) are more abundantly represented than bacteria (25%) and fungi (2%) (Figure 1F, panel a). Among the viruses, the inventors have found that ssDNA viruses account for a larger proportion (72%) than dsDNA viruses (28%). Seven different viral families have been found (abundance > 0.75%), and one dominant family, the Anelloviridae, accounts for 68% of the entire population (Figure 1F, panel b). The majority (97%) of that Anelloviridae ratio is composed of viruses of the genus Alphatorquevirus (Figure 1F, panel c). The genus Alphatorquevirus is the genus of Torque teno virus (TTV), and sequences associated with 14 different Torque teno virotypes were identified (Figure 1, panel d). Infection by polyomavirus in the human population ​ is widespread, and polyomavirus DNAemia is not uncommon in the first year after solid organ transplantation. Polyomavirus-derived sequences were found in 75 samples (11%) corresponding to 36 patients in this cohort. Evidence of the presence of BK (41%), JC (27%), TS (4%), WU polyomavirus (6%), SV40 (6%), and the recently discovered H pyV6 (13%) was found (Schowalter et al., 2010) ( Figure 1F, panel e). Among the bacteria, Proteobacteria (36%), Firmicutes (50%), Actinobacteria (10%), and Bacteroidetes (4%) were the most abundant phyla (lineages) represented in the samples (Figure 1F, panel f).

[0140] To examine the potential inaccuracies in the relatively short reads (50 bp) available for this study, the inventors examined the dependence of abundance estimates on read length based on longer paired-end reads (2×100 bp) collected for a subset of the samples (n = 55). The inventors found that abundance estimates based on 50 bp subreads and 100 bp reads were similar for all levels of the taxonomic classifications described herein (Figure 6F).

[0141] Susceptibility of the virome composition to drug administration. Using available clinical data on drug administration, drug-microbiome interactions were analyzed. Here, the inventors Data on adult heart and lung transplant patients treated with a valganciclovir-based rejection protocol were examined (47 patients and 380 observations), thereby excluding pediatric patients treated with cyclosporine and patients switched from tacrolimus to cyclosporine immunosuppression due to drug intolerance issues. Data on prescribed antiviral drug dosages (valganciclovir) and measured levels of tacrolimus in the blood were collected from the records of individual patients, and the average composition of samples corresponding to various drug levels was extracted. To account for the delayed effects of the microbiome composition on dosage changes, drug level and dosage data were processed with a sliding window average filter (see Figures 1C and 7A - C; window size 45 days).

[0142] The inventors have found that the structure of the viral component of the microbiome is a sensitivity function of the drug dosage (47 patients, 380 samples, Figure 2A). However, as discussed further below, the structure of the bacterial component of the microbiome was not significantly changed by drug therapy (Figure 7D). When patients received low doses of valganciclovir and tacrolimus, herpesviridae and Caudovirales were dominant in the virome. In contrast, high doses of immunosuppressive and antiviral agents resulted in a virome structure dominated by Anelloviridae (occupying up to 94% at high drug levels). Antiviral prophylaxis is intended to prevent CMV disease, but other herpesviruses are also sensitive to the drug, and thus it is not surprising that higher doses of valganciclovir result in lower proportions of herpesvirus - order viruses. Anelloviruses The observation that the Picornavirus takes advantage of the suppression of the host immune system is consistent with various observations from the literature. That is, the incidence of Anelloviridae viruses increases with the progression to AIDS in HIV patients and the total load of Anellovirus TTV increases after liver transplantation has already been shown. Furthermore, an increase in the prevalence of Anelloviridae viruses in pediatric patients presenting with fever has recently been reported.

[0143] Next, the virome composition measured in organ transplant recipients is compared with the composition observed in healthy individuals (n = 9, sequencing data available from previous studies) who are not using either immunosuppressive or antiviral agents. Here, the healthy composition is measured for organ transplant recipients at the start of drug therapy (day 1 post - operation, n = 13) corresponding to minimal drug exposure, and for transplant recipients exposed to high drug levels (a considerable time after the transplant procedure, tacrolimus 9 ng / ml, valganciclovir > 600 mg, n = 68). > The inventors have found similar virome compositions for healthy reference samples and samples corresponding to minimal drug exposure (Figure 2B). However, the compositions of the healthy reference and minimal drug exposure samples are different from the Anellovirus - dominant composition measured for the high drug exposure samples.

[0144] Tacrolimus - based immunosuppressive therapy is complemented with induction therapy (anti - thymocyte globulin, daclizumab or basiliximab) during the first 3 days after transplantation, and patients also receive prednisone, a corticosteroid, throughout the course of post - transplant therapy. The time - dosing profiles of prednisone and tacrolimus are similar (high dose at the start of therapy, then dose tapering) (Figs. 7A - C). Thus, the data in Fig. 2A represent the combined effects of prednisone and tacrolimus. The analysis of the differential effects of prednisone and valganciclovir on the virome composition (Fig. 7E) shows the same trend as that observed in Fig. 2A, with higher prednisone doses resulting in a greater representation of anelloviruses. Finally, the inventors note that a portion of the patients were not treated with antiviral drugs. The corresponding data for this portion of the patients, as described below, enabled the inventors to further elucidate the differential effects of antiviral drugs and immunosuppressive agents on the virome composition. and then dose tapering) (Figs. 7A - C). Thus, the data in Fig. 2A represent the combined effects of prednisone and tacrolimus. The analysis of the differential effects of prednisone and valganciclovir on the virome composition (Fig. 7E) shows the same trend as that observed in Fig. 2A, with higher prednisone doses resulting in a greater representation of anelloviruses. Finally, the inventors note that a portion of the patients were not treated with antiviral drugs. The corresponding data for this portion of the patients, as described below, enabled the inventors to further elucidate the differential effects of antiviral drugs and immunosuppressive agents on the virome composition. and tacrolimus. The analysis of the differential effects of prednisone and valganciclovir on the virome composition (Fig. 7E) shows the same trend as that observed in Fig. 2A, with higher prednisone doses resulting in a greater representation of anelloviruses. Finally, the inventors note that a portion of the patients were not treated with antiviral drugs. The corresponding data for this portion of the patients, as described below, enabled the inventors to further elucidate the differential effects of antiviral drugs and immunosuppressive agents on the virome composition. and valganciclovir on the virome composition (Fig. 7E) shows the same trend as that observed in Fig. 2A, with higher prednisone doses resulting in a greater representation of anelloviruses. Finally, the inventors note that a portion of the patients were not treated with antiviral drugs. The corresponding data for this portion of the patients, as described below, enabled the inventors to further elucidate the differential effects of antiviral drugs and immunosuppressive agents on the virome composition. shows the same trend as that observed in Fig. 2A, with higher prednisone doses resulting in a greater representation of anelloviruses. Finally, the inventors note that a portion of the patients were not treated with antiviral drugs. The corresponding data for this portion of the patients, as described below, enabled the inventors to further elucidate the differential effects of antiviral drugs and immunosuppressive agents on the virome composition. resulting in a greater representation of anelloviruses. Finally, the inventors note that a portion of the patients were not treated with antiviral drugs. The corresponding data for this portion of the patients, as described below, enabled the inventors to further elucidate the differential effects of antiviral drugs and immunosuppressive agents on the virome composition. note that a portion of the patients were not treated with antiviral drugs. The corresponding data for this portion of the patients, as described below, enabled the inventors to further elucidate the differential effects of antiviral drugs and immunosuppressive agents on the virome composition. portion of the patients, as described below, enabled the inventors to further elucidate the differential effects of antiviral drugs and immunosuppressive agents on the virome composition. enabled the inventors to further elucidate the differential effects of antiviral drugs and immunosuppressive agents on the virome composition.

[0145] Partitioning of the microbiome diversity. The inventors examined the diversity of the bacterial and viral components of the microbiome. For both bacteria and viruses, within - subject diversity was lower than between - subject diversity (Bray - Curtis beta diversity, phylum - level bacterial composition, family and order - level viruses, Fig. 2C). Partitioning of the data by transplant type, heart or lung, or age of the patients did not reduce the diversity. Within subjects, for samples collected within a 1 - month period, again, diversity was lower for both bacteria and viruses. For viruses but not bacteria, the inventors found that diversity was lower when comparing samples collected at similar drug dosages (tacrolimus levels ±0.5 ng / ml, valganciclovir ±50 mg). Thus, in Fig. 2A, For both bacteria and viruses, within - subject diversity was lower than between - subject diversity (Bray - Curtis beta diversity, phylum - level bacterial composition, family and order - level viruses, Fig. 2C). Partitioning of the data by transplant type, heart or lung, or age of the patients did not reduce the diversity. Within subjects, for samples collected within a 1 - month period, again, diversity was lower for both bacteria and viruses. For viruses but not bacteria, the inventors found that diversity was lower when comparing samples collected at similar drug dosages (tacrolimus levels ±0.5 ng / ml, valganciclovir ±50 mg). Thus, in Fig. 2A, diversity was lower than between - subject diversity (Bray - Curtis beta diversity, phylum - level bacterial composition, family and order - level viruses, Fig. 2C). Partitioning of the data by transplant type, heart or lung, or age of the patients did not reduce the diversity. Within subjects, for samples collected within a 1 - month period, again, diversity was lower for both bacteria and viruses. For viruses but not bacteria, the inventors found that diversity was lower when comparing samples collected at similar drug dosages (tacrolimus levels ±0.5 ng / ml, valganciclovir ±50 mg). Thus, in Fig. 2A, phylum - level bacterial composition, family and order - level viruses, Fig. 2C). Partitioning of the data by transplant type, heart or lung, or age of the patients did not reduce the diversity. Within subjects, for samples collected within a 1 - month period, again, diversity was lower for both bacteria and viruses. For viruses but not bacteria, the inventors found that diversity was lower when comparing samples collected at similar drug dosages (tacrolimus levels ±0.5 ng / ml, valganciclovir ±50 mg). Thus, in Fig. 2A, Partitioning of the data by transplant type, heart or lung, or age of the patients did not reduce the diversity. Within subjects, for samples collected within a 1 - month period, again, diversity was lower for both bacteria and viruses. For viruses but not bacteria, the inventors found that diversity was lower when comparing samples collected at similar drug dosages (tacrolimus levels ±0.5 ng / ml, valganciclovir ±50 mg). Thus, in Fig. 2A, Within subjects, for samples collected within a 1 - month period, again, diversity was lower for both bacteria and viruses. For viruses but not bacteria, the inventors found that diversity was lower when comparing samples collected at similar drug dosages (tacrolimus levels ±0.5 ng / ml, valganciclovir ±50 mg). Thus, in Fig. 2A, again, diversity was lower for both bacteria and viruses. For viruses but not bacteria, the inventors found that diversity was lower when comparing samples collected at similar drug dosages (tacrolimus levels ±0.5 ng / ml, valganciclovir ±50 mg). Thus, in Fig. 2A, dosages (tacrolimus levels ±0.5 ng / ml, valganciclovir ±50 mg). Thus, in Fig. 2A, when comparing samples collected at similar drug dosages (tacrolimus levels ±0.5 ng / ml, valganciclovir ±50 mg). Thus, in Fig. 2A, When combined with the population-average sensitivity to drug administration, the inventors have found that the virome composition converges to a similar state for patients undergoing the same drug therapy. We have found that the virome composition converges to a similar state for patients undergoing the same drug therapy.

[0146] Dynamic response of the virome to drug dose changes. A strong temporal response of the virome to changes in drug dose was observed, which is consistent with the sensitivity of the virome composition to drug dose. A strong temporal response of the virome to changes in drug dose was observed, which is consistent with the sensitivity of the virome composition to drug dose. Figure 3A shows the time-dependence of the relative genomic abundance of ssDNA and dsDNA viruses (data from all patient groups and samples, n = 656). The ratio of ssDNA viruses increases rapidly in the first month after transplantation and then shows the opposite trend after 6 months. Figure 3A shows the time-dependence of the relative genomic abundance of ssDNA and dsDNA viruses (data from all patient groups and samples, n = 656). The ratio of ssDNA viruses increases rapidly in the first month after transplantation and then shows the opposite trend after 6 months. The ratio of ssDNA viruses increases rapidly in the first month after transplantation and then shows the opposite trend after 6 months. Figure 3B shows the time-dependent relative composition of the most abundant viruses classified at the family and order levels, showing further details regarding virome composition dynamics (data from all patient groups and samples, n = 656). The dsDNA ratio consists of Caudovirales, Adenoviridae, Polyomaviridae, and Herpesviridae, which together account for 95% of the virome at the first week after transplantation. Figure 3B shows the time-dependent relative composition of the most abundant viruses classified at the family and order levels, showing further details regarding virome composition dynamics (data from all patient groups and samples, n = 656). The dsDNA ratio consists of Caudovirales, Adenoviridae, Polyomaviridae, and Herpesviridae, which together account for 95% of the virome at the first week after transplantation. The dsDNA ratio consists of Caudovirales, Adenoviridae, Polyomaviridae, and Herpesviridae, which together account for 95% of the virome at the first week after transplantation. The ssDNA viruses account for only 5% of the initial virome and mainly consist of members of the Anelloviridae family. The ratios occupied by Adenoviridae, Caudovirales, and Herpesviridae decrease significantly in the first few months. The ssDNA viruses account for only 5% of the initial virome and mainly consist of members of the Anelloviridae family. The ratios occupied by Adenoviridae, Caudovirales, and Herpesviridae decrease significantly in the first few months. This is because these viral types are effectively targeted by antiviral prophylaxis. In contrast, the relative abundance of Anelloviridae viruses increases rapidly. This is because these viral types are effectively targeted by antiviral prophylaxis. In contrast, the relative abundance of Anelloviridae viruses increases rapidly. This is because these viral types are effectively targeted by antiviral prophylaxis. In contrast, the relative abundance of Anelloviridae viruses increases rapidly. This is because most of these viral types evade targeting by antiviral drugs and take advantage of the reduced immune ability of the patient (up to 84% at 4.5 - 6 months). This is because most of these viral types evade targeting by antiviral drugs and take advantage of the reduced immune ability of the patient (up to 84% at 4.5 - 6 months). This is because most of these viral types evade targeting by antiviral drugs and take advantage of the reduced immune ability of the patient (up to 84% at 4.5 - 6 months). Six months later, the opposite trend was observed, which is consistent with the reduction in antiviral and immunosuppressive drugs prescribed by the treatment protocol.

[0147] Compared with the viral component, the bacterial component of the microorganism remains relatively stable over time, which is the observation made at the taxonomic levels of phylum, order, and genus (Figure 3C, n = 656 and Figure S3). Figure 3D shows the within-sample alpha diversity of bacteria and viral genera as a function of time (Shannon entropy, 1-month period, 590 bacterial genera, 168 viral genera examined). The observed viral genus diversity decreased at the start of treatment (from 1.05 ± 0.5 in the first month to 0.31 ± 0.33 in the fourth to fifth months, p << 10 - 6 , Mann-Whitney U test), while the bacterial alpha diversity remained relatively invariant during the course of post-transplant therapy (from 2.2 ± 1.14 in the first month to 2. 6 ± 0.85 in the fourth to fifth months, p = 0.1, Mann-Whitney U test).

[0148] Increase in total viral load at the start of post-transplant therapy. To gain insights into the effect of therapeutic agents on the total viral load , the inventors extracted the absolute genomic abundance of total virus relative to the human genome copy number by normalizing the genomic coverage of viral targets against the coverage of the human genome. For the entire patient population of this study, an increase in total viral load was observed at the start of treatment , independent of the transplant type (heart or lung) or age (adult or pediatric) (Figure 4A) (change in load, 7.4 ± 3, sigmoid fit, black line). Combined with the relative abundance data , the total viral load data show that patients treated simultaneously with antiviral and immunosuppressive agents (Figure 4A) (change in load, 7.4 ± 3, sigmoid fit, black line). Combined with the relative abundance data, the total viral load data show that patients treated simultaneously with antiviral and immunosuppressive agents are For patients with HERPESV1 infection, the net reduction in herpesvirus load during the first 3 months after transplantation was and a net increase in Anelloviridae load.

[0149] Thus, the data suggest that combinations of antivirals and immunosuppressants against various virions may be beneficial. The data also show a reduction in total Adenoviridae load. This is consistent with previous studies, suggesting that Adenoviridae virus replication is associated with the Valgancilovirus. Figure 4B summarizes the data for all graft types. However, the same trends are observed when stratified by different transplant types [Adult Heart Transplant Recipes]. ent (n = 268, Fig. 9A), adult lung transplant recipients (n = 166, Fig. 8B), and pediatric patients treated with cyclosporine rather than tacrolimus (n = 99, Fig. 9C)].

[0150] All patients in the study cohort received both antiviral and immunosuppressant medications Both donor and recipient had previous CMV antibody assays. In transplant recipients without evidence of MV infection, the risk of complications from antiviral prophylaxis is emerging. The risk of CMV infection was deemed to be outweighed by the potential risk of subsequent CMV infection. They are not treated with antiviral prophylaxis; therefore, these patients are treated with immunosuppressants alone. Figure 9C shows the time-dependent viral load and composition of CMV-negative cases (n=75). The net effect of immunosuppressive therapy alone is to reduce the number of viruses, including herpesviruses and adenoviruses. The increase in all virions, including avian influenza A (AVH) virus, is consistent with the increase in avian influenza A (AVH) virus. Tapering of immunosuppression leads to a decrease in the total viral load.

[0151] Lower anelloviral loads in patients with transplant rejection episodes. Immunosuppression the correlation of the anellovirus load with the degree (see FIGS. 2A and 4), and, considering the relationship between the immune capacity and the risk of rejection, the inventors questioned whether the anellovirus load could be used for the classification of rejection and non-rejection transplant recipients. FIG. 5A shows the anellovirus load measured for rejecting and non-rejecting patients as a function of time after transplantation. Here, patients with at least 1 moderate or severe rejection episode determined by biopsy, biopsy grade 2R / 3A, are classified as rejecting (red; 20 patients, 177 data points). Non-rejecting patients correspond to patients who are not diagnosed with moderate or severe graft injury over the entire course of the post-transplant period (blue; biopsy grade <2R / 3A, 40 patients, 285 data points). > FIG. 5A shows that the anellovirus load is significantly lower at almost all time points for rejecting individuals. The inventors then directly compared the anellovirus load for patients at the time of rejection with the load measured for patients in the absence of rejection. Considering the time-dependence of the anellovirus load (FIG. 5A), the inventors extracted the anellovirus load relative to the mean load measured for all samples at the same time point. FIG. 5B shows the time-normalized load for non-rejecting patients (N = 208) compared to the load measured for patients with mild rejection events (biopsy grade 1R, N = 102) and patients with severe rejection episodes (biopsy grade

[0152] 2R / 3A, N = 22). This figure shows that the time-normalized load is significantly lower for patients with a greater risk of rejection. The p-value is measured for the anellovirus load directly compared the load measured for patients at the time of rejection with the load measured for patients in the absence of rejection. Considering the time-dependence of the anellovirus load (FIG. 5A), the inventors extracted the anellovirus load relative to the mean load measured for all samples at the same time point. FIG. 5B shows the time-normalized load for non-rejecting patients (N = 208) compared to the load measured for patients with mild rejection events (biopsy grade 1R, N = 102) and patients with severe rejection episodes (biopsy grade 2R / 3A, N = 22). This figure shows that the time-normalized load is significantly lower for patients with a greater risk of rejection. The p-value is measured > 2R / 3A, N = 22) compared to the load measured for non-rejecting patients (N = 208). This figure shows that the time-normalized load is significantly lower for patients with a greater risk of rejection. The p-value is measured risk of rejection. The p-value is measured Calculated by random extraction of a larger population of points. p = sum(median(A rej ) > median(A non-rej )) / N, where N = 10 4 and A rej and and A non-rej are the relative viral loads for the larger and smaller risk populations of rejection and non - rejection, respectively (p = 0.011, p = 0.0002 and p = 0.036).

[0153] These observations are consistent with the view that the risk of rejection and the occurrence of infection have an inverse relationship with the patient's immune ability (see inset Figure 5A). Thus, the lower viral load observed in rejection patients indicates a higher level of immune ability in this subset of patients, even if these patients are treated with the same immunosuppressive protocol . Variability among patients in susceptibility to immunosuppression is known to occur, and the lack of predictability in immunosuppression is an important risk factor in transplantation. The current commercial assays used for the measurement of immune ability have not been found to predict acute rejection or significant infection. Therefore, the development of methods for the direct measurement of immune ability that could replace or complement existing assays would be important. The total anellovirus load recorded in organ transplant recipients could act as an alternative marker. Figure 5C shows the receiver operating characteristic and tests the performance of the relative anellovirus load in classifying non - rejection and rejection patients (area under the curve = 0.72). We, the inventors, by sequencing cell - free DNA in the plasma of the recipient, substantially shows the receiver operating characteristic and tests the performance of the relative anellovirus load in classifying non - rejection and rejection patients (area under the curve = 0.72).

[0154] We, the inventors, by sequencing cell - free DNA in the plasma of the recipient, substantially ​The drug - microbiota interactions after organ transplantation were studied. The data show much about the basic structure of the human virome in plasma, and how it responds to pharmacological perturbation. They also show the relative insensitivity of the composition of the bacterial components of the microbiota to immunosuppression. These data are useful in the design and optimization of post - transplantation treatment protocols. For example, they show that the tapering of antiviral prophylaxis from an initial high dose induces the reactivation of the herpesviridae fraction. CMV DNA load has already been shown to predict CMV disease recurrence and rejection, and the question has arisen as to whether patients would benefit from longer - term prophylactic therapy. The marked increase in the prevalence of anelloviridae viruses during immunosuppression also merits further investigation. Anelloviruses are ubiquitous in the human population and, although their pathogenicity has not been confirmed, anelloviruses are currently being studied as potential co - factors in carcinogenesis. In particular, considering the increased carcinogenesis seen in transplant recipients, organ transplantation represents an ideal situation for studying the properties of anelloviridae viruses due to the sensitivity of anelloviridae viruses to immunosuppression. The observation of below - average anellovirus load in patients with rejection episodes is an indicator of insufficient immunosuppression in this patient subgroup, even if these patients were receiving immunosuppressive agents at the levels prescribed according to the protocol. This indicates the need to directly measure the level of a patient's immune competence in addition to measuring circulating drug levels. They also show that the tapering of antiviral prophylaxis from an initial high dose induces the reactivation of the herpesviridae fraction. CMV DNA load has already been shown to predict CMV disease recurrence and rejection, and the question has arisen as to whether patients would benefit from longer - term prophylactic therapy. They also show that the tapering of antiviral prophylaxis from an initial high dose induces the reactivation of the herpesviridae fraction. CMV DNA load has already been shown to predict CMV disease recurrence and rejection, and the question has arisen as to whether patients would benefit from longer - term prophylactic therapy. They also show that the tapering of antiviral prophylaxis from an initial high dose induces the reactivation of the herpesviridae fraction. CMV DNA load has already been shown to predict CMV disease recurrence and rejection, and the question has arisen as to whether patients would benefit from longer - term prophylactic therapy.

[0155] The marked increase in the prevalence of anelloviridae viruses during immunosuppression also merits further investigation. Anelloviruses are ubiquitous in the human population and, although their pathogenicity has not been confirmed, anelloviruses are currently being studied as potential co - factors in carcinogenesis. In particular, considering the increased carcinogenesis seen in transplant recipients, organ transplantation represents an ideal situation for studying the properties of anelloviridae viruses due to the sensitivity of anelloviridae viruses to immunosuppression. In particular, considering the increased carcinogenesis seen in transplant recipients, organ transplantation represents an ideal situation for studying the properties of anelloviridae viruses due to the sensitivity of anelloviridae viruses to immunosuppression. In particular, considering the increased carcinogenesis seen in transplant recipients, organ transplantation represents an ideal situation for studying the properties of anelloviridae viruses due to the sensitivity of anelloviridae viruses to immunosuppression. The observation of below - average anellovirus load in patients with rejection episodes is an indicator of insufficient immunosuppression in this patient subgroup, even if these patients were receiving immunosuppressive agents at the levels prescribed according to the protocol. The observation of below - average anellovirus load in patients with rejection episodes is an indicator of insufficient immunosuppression in this patient subgroup, even if these patients were receiving immunosuppressive agents at the levels prescribed according to the protocol. The observation of below - average anellovirus load in patients with rejection episodes is an indicator of insufficient immunosuppression in this patient subgroup, even if these patients were receiving immunosuppressive agents at the levels prescribed according to the protocol. This indicates the need to directly measure the level of a patient's immune competence in addition to measuring circulating drug levels. It is suggested that it is effective to design an assay that enables. Transplant recipients The total load of anellovirus identified in the blood of is one of the markers indicating the overall status of immunosuppression of such individual patients and can serve as.

[0156] High-throughput DNA sequencing is useful in hypothesis-free diagnosis. Infections occur frequently in transplantation and are difficult to diagnose in immunosuppressed individuals. Considering this, and considering that sequence analysis can further provide information regarding the integrity of the graft by quantifying donor-derived human DNA circulating in the blood this approach is particularly suitable for transplantation. In other areas of infectious diseases, it may be useful to develop a subtractive method to exclude host DNA and enrich virus- and microorganism-derived DNA ;subtractive method). In the case of, this approach is particularly suitable. In other areas of infectious diseases, it may be useful to develop a subtractive method to exclude host DNA and enrich virus- and microorganism-derived DNA ;subtractive method).

[0157] Experimental methods Collection of clinical samples: Patients were registered at Stanford University Hospit al (SUH) or Lucile Packard Children’s Hosp ital (LPCH), and were excluded if they were recipients of multi-organ transplantation. This study was approved by the Stanford University Institut ional Review Board (protocol # 17666), and recruitment began in March 2010. For details of patient recruitment and post-transplant treatment of patients, please refer to the section on detailed experimental methods

[0158] Plasma processing and DNA extraction: Plasma was processed as previously described (Fan et al., 200​​​​ 8) It was extracted from whole blood samples within 3 hours after sample collection and stored at -80°C. If required for analysis, plasma samples were thawed and circulating DNA was immediately extracted from 0. 5 - 1 ml of plasma using the QIAamp Circulating Nucleic Acid Kit (Qiagen).

[0159] Preparation of sequencing libraries and sequencing: Using the NEBNext DNA Library Prep Master Mix Set for Illumina with adapters with standard Illumina indexes (purchased from IDT), or using an automated library preparation platform based on microluidics (Mondriaan ST, Ovation SP Ultralow library system), a sequencing library was prepared from the purified plasma DNA of the patient. The library was characterized using an Agilent 2100 Bioanalyzer (High sensitivity DNA kit) and quantified by qPCR. The samples were part of 26 different sequencing runs and were sequenced over 22 months. On average, 6 samples were sequenced per lane. Post - transplantation monitoring and clinical sample collection. This analysis was funded by the National Institutes of Health (RC4 AI092673) to study the clinical utility of a donor - derived cell - free DNA assay for the diagnosis of acute and chronic rejection and allograft failure after thoracic organ transplantation.

[0160] vious ​​​​​​​​​This corresponds to a sub-study of a prospective cohort study. Stanford University H ospital (SUH) or Lucile Packard Children’s Hospital (LPCH) who received a heart or lung transplant were enrolled, and they were excluded if they were recipients of multiple organ transplants or if they were followed up at facilities outside of SUH or LPCH after transplantation. This study was approved by the Stanford University Institutional Review Board (protocol # 17666) and registration began in March 2010. Post-transplant treatment protocol, details of adult heart transplant recipients. Post-transplant immunosuppression consisted of methylprednisolone 500 mg administered immediately after surgery, followed by 125 mg given three times every 8 hours. Anti-thymocyte globulin (rATG) 1 mg / kg was administered on the 1st, 2nd, and 3rd days after surgery. Maintenance immunosuppression consisted of prednisone 2

[0161] 0 mg administered twice daily starting on the 1st day after surgery, gradually tapered to less than 0.1 mg / kg / day by the 6th month after surgery, and further tapered if endomyocardial biopsy did not show evidence of cellular rejection. Tacrolimus administration was started on the 1st day after surgery, with levels maintained at 10 - 15 ng / ml from months 0 - 6, 7 - 10 ng / ml from months 6 - 12, and then further adjusted to maintain levels of 5 - 10 ng / ml thereafter. Mycophenolate mofetil was administered twice daily starting on the 1st day after surgery, starting at 1,000 mg, and the dose was adjusted as needed to address leukopenia.

[0162] ​​​​​​​​Unless both the donor and recipient were CMV negative, all patients received standard CMV (anti-viral) prophylaxis consisting of 5 mg / kg (IV) ganciclovir, adjusted according to renal function, starting on the first postoperative day and given hourly. Recipients were started on valganciclovir 900 mg twice daily for two weeks if able to tolerate oral medications, then 900 mg daily until the sixth postoperative month, then 450 mg daily until the twelfth postoperative month, at which point anti-viral prophylaxis was discontinued. In cases of leukopenia, the dose of valganciclovir was reduced. CMV+ CMV- recipients of CMV+ allografts also received CMV hyperimmune globulin 150 mg / kg IV within 72 hours of transplantation, 100 mg / kg at postoperative weeks 2, 4, 6, and 8, and 50 mg / kg at postoperative weeks 12 and 16. CMV CMV recipients of allografts were not treated with anti-viral prophylaxis until May 2012. These recipients were then

[0163] treated with acyclovir 400 mg twice daily for one year. Anti-fungal prophylaxis consisted of daily itraconazole 300 mg for the first three months after transplantation, and prophylaxis against Pneumocystis jiroveci - infection consisted of daily trimethoprim / sulfamethoxazole, 80 mg TMP component. Prophylaxis against Pneumocystis infection was continued indefinitely, and patients intolerant to TMP-SMX received atovaquone, - dapsone, or inhaled pentamidine These recipients were then treated with acyclovir 400 mg twice daily for one year. Anti-fungal prophylaxis consisted of daily itraconazole 300 mg for the first three months after transplantation, and prophylaxis against Pneumocystis jiroveci infection consisted of daily trimethoprim / sulfamethoxazole, 80 mg TMP component. Prophylaxis against Pneumocystis infection was continued indefinitely, and patients intolerant to TMP-SMX received atovaquone, dapsone, or inhaled pentamidine infection consisted of daily trimethoprim / sulfamethoxazole, 80 mg TMP component. Prophylaxis against Pneumocystis infection was continued indefinitely, and patients intolerant to TMP-SMX received atovaquone, dapsone, or inhaled pentamidine ovaquone, dapsone, or inhaled pentamidine were treated with midine).

[0164] All heart transplant recipients were monitored for acute cellular rejection by scheduled surveillance endomyocardial biopsies at post-transplant intervals (weekly in the first month, bi-weekly until the third month, monthly until the sixth month, then at months 9, 12, 16, 20, and 24). Biopsies were graded according to the ISHLT 2004 revised grading scale (0, 1R, 2R, 3R) (29). Blood samples were collected from heart transplant recipients at the following post-transplant time points: weeks 2, 4, and 6; months 2, 2.5, 3, 4, 5, 6, 8, 10, 12, 16, 20, and 24. Blood samples were also collected from some heart transplant recipients on the first day post-transplant. When blood sample collection and endomyocardial biopsy were performed on the same day, care was taken to ensure that blood was collected before the biopsy procedure. Pediatric heart transplant recipients. Induction immunosuppression initially consisted of a total of 5 doses of daclizumab 1 mg / kg IV every 2 weeks, and from August 2011, basiliximab 10 - 20 mg IV was switched on postoperative days 0 and 4. Recipients were also immediately treated with pulse methylprednisolone 10 mg / kg IV in 3 doses every 8 hours, then prednisone 0.5 mg / kg twice daily for the first 14 days post-transplant, and then the corticosteroid was tapered over the first year post-transplant if there was no acute rejection. Calcineurin inhibition was mainly at 300 - 350 ng / ml from post-transplant months 0 - 3

[0165]

[0166] ​​​​​​​​​​​​, from the 4th to the 6th month, it was 275 - 325 ng / ml, from the 7th to the 12th month, it was 250 - 300 ng / ml, and after the 12th month after transplantation, the administration of cyclosporine at a target level of 200 - 250 was carried out. l, and patients intolerant to cyclosporine were treated with tacrolimus. The protocol for the prevention and surveillance of nosocomial infections and endomyocardial biopsy was the same as that for adult heart transplant recipients. For lung transplant recipients, post - transplant immunosuppression consisted of administering 500 - 1000 mg of methylprednisolone immediately after surgery, and then administering 0.5 mg / kg IV twice a day. Basiliximab 20 mg IV was administered on days 0 and 4 for induction immunosuppression. Maintenance immunosuppression consisted of administering 0.5 mg / kg IV of methylprednisolone twice a day from post - operative day 0 to day 3, then prednisone 0.5 mg / kg daily until day 30, and then tapering to 0.1 mg / kg (daily dose) every 2 - 3 months from the 6th to the 12th month after transplantation. The administration of tacrolimus was started on post - operative day 0, and the dose was adjusted so that levels of 12 - 15 ng / ml were maintained from the 0th to the 6th month, 10 - 15 ng / ml from the 6th to the 12th month, and 5 - 10 ng / ml thereafter. The administration of mycophenolate mofetil was started at 500 mg twice a day from post - operative day 0, and the dose was adjusted as needed in response to leukopenia. Antiviral, antifungal, and PCP prophylaxis were the same as for the adult heart transplant cohort.

[0167] All lung transplant recipients were examined at 1.5, 3, 6, 12, 18, and 24 months after transplantation. mg was administered immediately after surgery, and then it consisted of administering 0.5 mg / kg IV twice a day. Basiliximab 20 mg IV was administered on days 0 and 4 for induction immunosuppression. Maintenance immunosuppression consisted of administering 0.5 mg / kg IV of methylprednisolone twice a day from post - operative day 0 to day 3, then prednisone 0.5 mg / kg daily until day 30, and then tapering to 0.1 mg / kg (daily dose) every 2 - 3 months from the 6th to the 12th month after transplantation. The administration of tacrolimus was started on post - operative day 0, and the dose was adjusted so that levels of 12 - 15 ng / ml were maintained from the 0th to the 6th month, 10 - 15 ng / ml from the 6th to the 12th month, and 5 - 10 ng / ml thereafter. The administration of mycophenolate mofetil was started at 500 mg twice a day from post - operative day 0, and the dose was adjusted as needed in response to leukopenia. Antiviral, antifungal, and PCP prophylaxis were the same as for the adult heart transplant cohort. For the prevention and surveillance of nosocomial infections and endomyocardial biopsy was the same as that for adult heart transplant recipients. For lung transplant recipients, post - transplant immunosuppression consisted of administering 500 - 1000 mg of methylprednisolone immediately after surgery, and then administering 0.5 mg / kg IV twice a day. Basiliximab 20 mg IV was administered on days 0 and 4 for induction immunosuppression. Maintenance immunosuppression consisted of administering 0.5 mg / kg IV of methylprednisolone twice a day from post - operative day 0 to day 3, then prednisone 0.5 mg / kg daily until day 30, and then tapering to 0.1 mg / kg (daily dose) every 2 - 3 months from the 6th to the 12th month after transplantation. The administration of tacrolimus was started on post - operative day 0, and the dose was adjusted so that levels of 12 - 15 ng / ml were maintained from the 0th to the 6th month, 10 - 15 ng / ml from the 6th to the 12th month, and 5 - 10 ng / ml thereafter. The administration of mycophenolate mofetil was started at 500 mg twice a day from post - operative day 0, and the dose was adjusted as needed in response to leukopenia. Antiviral, antifungal, and PCP prophylaxis were the same as for the adult heart transplant cohort. For lung transplant recipients, post - transplant immunosuppression consisted of administering 500 - 1000 mg of methylprednisolone immediately after surgery, and then administering 0.5 mg / kg IV twice a day. Basiliximab 20 mg IV was administered on days 0 and 4 for induction immunosuppression. Maintenance immunosuppression consisted of administering 0.5 mg / kg IV of methylprednisolone twice a day from post - operative day 0 to day 3, then prednisone 0.5 mg / kg daily until day 30, and then tapering to 0.1 mg / kg (daily dose) every 2 - 3 months from the 6th to the 12th month after transplantation. The administration of tacrolimus was started on post - operative day 0, and the dose was adjusted so that levels of 12 - 15 ng / ml were maintained from the 0th to the 6th month, 10 - 15 ng / ml from the 6th to the 12th month, and 5 - 10 ng / ml thereafter. The administration of mycophenolate mofetil was started at 500 mg twice a day from post - operative day 0, and the dose was adjusted as needed in response to leukopenia. Antiviral, antifungal, and PCP prophylaxis were the same as for the adult heart transplant cohort. For lung transplant recipients, post - transplant immunosuppression consisted of administering 500 - 1000 mg of methylprednisolone immediately after surgery, and then administering 0.5 mg / kg IV twice a day. Basiliximab 20 mg IV was administered on days 0 and 4 for induction immunosuppression. Maintenance immunosuppression consisted of administering 0.5 mg / kg IV of methylprednisolone twice a day from post - operative day 0 to day 3, then prednisone 0.5 mg / kg daily until day 30, and then tapering to 0.1 mg / kg (daily dose) every 2 - 3 months from the 6th to the 12th month after transplantation. The administration of tacrolimus was started on post - operative day 0, and the dose was adjusted so that levels of 12 - 15 ng / ml were maintained from the 0th to the 6th month, 10 - 15 ng / ml from the 6th to the 12th month, and 5 - 10 ng / ml thereafter. The administration of mycophenolate mofetil was started at 500 mg twice a day from post - operative day 0, and the dose was adjusted as needed in response to leukopenia. Antiviral, antifungal, and PCP prophylaxis were the same as for the adult heart transplant cohort. For lung transplant recipients, post - transplant immunosuppression consisted of administering 500 - 1000 mg of methylprednisolone immediately after surgery, and then administering 0.5 mg / kg IV twice a day. Basiliximab 20 mg IV was administered on days 0 and 4 for induction immunosuppression. Maintenance immunosuppression consisted of administering 0.5 mg / kg IV of methylprednisolone twice a day from post - operative day 0 to day 3, then prednisone 0.5 mg / kg daily until day 30, and then tapering to 0.1 mg / kg (daily dose) every 2 - 3 months from the 6th to the 12th month after transplantation. The administration of tacrolimus was started on post - operative day 0, and the dose was adjusted so that levels of 12 - 15 ng / ml were maintained from the 0th to the 6th month, 10 - 15 ng / ml from the 6th to the 12th month, and 5 - 10 ng / ml thereafter. The administration of mycophenolate mofetil was started at 500 mg twice a day from post - operative day 0, and the dose was adjusted as needed in response to leukopenia. Antiviral, antifungal, and PCP prophylaxis were the same as for the adult heart transplant cohort. All lung transplant recipients were examined at 1.5, 3, 6, 12, 18, and 24 months after transplantation.

[0168] All lung transplant recipients were examined at 1.5, 3, 6, 12, 18, and 24 months after transplantation. Patients were monitored for acute cellular rejection by a transbronchial biopsy protocol. Biopsies were performed when clinically indicated based on the results of pulmonary function tests. Blood samples were collected from lung transplant recipients for research purposes at the following intervals: on day 1 after transplantation; 2 times, 2 times on the 2nd day and 1 time on the 3rd day, then 1st and 2nd weeks, and 1.5th, 2nd , 3, 4.5, 6, 9, 12, 18 and 24 months. Per protocol and clinically indicated Blood samples were taken prior to the performance of the designated biopsy.

[0169] Workflow for identifying pathogen-derived sequences. C-based utilities (C-bas Strict duplicates were removed using the fastq.cpp ed utility. stx package (fastq quality filter -Q33 -q21 - Use the quality filter that is part of p50 to filter out low quality The remaining reads were then aligned to the human reference genome build hg using BWA. Aligned to 19(bwaaln - q25). samtools(samt ools view -f4) to collect unmapped reads and Use eqclean (seqclean -l 40 -c 1) to clean low-complexity reads The reads were then matched against selected viral, bacterial and fungal reference genomes as well as Total reference body (ncbi Align the file against the one downloaded with fungi Ta.

[0170] Figure 6A shows the genome size distribution. The following parameters were used for BLAST alignment: Using tag: reward = 1, penalty = 3. Word Size = 1 2. Gap open = 5, gap extend = 2, e - value = 104. Percent identity (perc_identity) = 90, culling limit = 2. Blast hits with alignment lengths shorter than 45 were removed. For a subset of samples, longer reads are available (23 100bp, p, n = 55). To test the robustness of genome presence estimation, the length dependency of the composition assay was examined. Here, reads were trimmed to lengths of 40, 50, 65, 80, and 100bp (fastx trimmer) and analyzed using the workflow. Here, blast hits with alignment lengths shorter than 37, 45, 59, 72, and 80bp were removed for reads of 40, 50, 65, 80, and 100bp, respectively. Genome presence estimation. Relative genome presence estimation was calculated using GRAMMy. This tool uses BLAST - derived nucleic acid sequence similarity data to perform maximum - likelihood estimation of the relative presence of species in a sample. GRAMMy filters hits by the BLAST alignment matrix (E - score, alignment length, and identity rate) and takes into account the ambiguity of read assignment and the target genome size in the evaluation of relative presence of candidate reference genomes. GRAMMy was called using the following parameters: python grammy rd Input set; python grammy em.py -b 5 -t 0.0001 -n 100 input.mtx; grammy p ost.py input.est setinput.btp.

[0171] To obtain the abundance at a higher taxonomic level by combining the abundance evaluations at the strain level a custom script was used. Here, Taxtastic was used to construct the minimum taxonomy for the reference database.

[0172] Quantification of absolute viral load. To quantify the load of infectious agents in the samples, the results of the b last hits were collected and the best hit for each read was selected using a custom script (Bioperl). Figure 6B shows the distribution of the number of unique viral, bacterial, and fungal blast hits per million sequenced reads. Figure 6 C shows the number of viral, bacterial, and fungal genomic copies compared to the number of human genomic copies present in the samples. The coverage rate of the genomes of infectious agents was normalized against the human genome coverage rate.

[0173] qPCR verification of the sequencing results for the selected viral targets. Standard qPCR kits (PrimerDesign, genesig) for the quantification of human herpesviruses 4, 5, and 6 as well as parvovirus were used to verify the sequencing results for a subset of the cell-free DNA samples. qPCR was performed on cfDNA extracted from ~1 ml of plasma and eluted in 100 μl Tris buffer (50 mM [pH 8.1 - 8.2]). ​​​​​​An assay was performed. The plasma extraction and PCR experiments were conducted at different facilities. In each experiment, a no-template control was used to verify that the PCR reagent was included. Figure 6D shows the relative number of blast hits per million reads obtained, compared to the concentration of viral genomic copies determined using qPCR.

[0174] No-template control. A no-template control experiment was performed. The sequencing library was prepared from nuclease-free water (S01001, Nugen). The library was prepared together with seven additional sample libraries (cell-free human DNA) to test for possible interference between samples during library preparation. To ensure the formation of clusters with sufficient density on the Illumina flow cell, the samples were sequenced together with samples unrelated to the study. The samples unrelated to the study collected 16 million reads, but the no-template control library gave only 15 reads mapped to two species [Methanocaldococcus janaschii (9 hits) and Bacillus subtilis (5 hits)] in the reference database. No evidence for human-related sequences was found. This indicates that inter-sample contamination was low.

[0175] Example 2 Clinical monitoring of the microbiome Using the method described in Example 1, the reads mapped to the CMV genome were quantified for each sample. In samples that were clinically positive for infection, an increase in CMV abundance was observed (p = 7.10 ​-9 , Mann-Whitney U test, Figure 10C). The level of CMV-derived DNA in the samples of the present inventors was consistent with the clinical reports of CMV with an AUC of 0.91. This data indicates that CMV monitoring can be performed in parallel with rejection monitoring using the same sequence data, from which the present inventors investigated whether other viral infections can be similarly monitored.

[0176] The present inventors identified well-characterized pathogenic and oncoviruses (Figure 11A ) as well as the co-circulating Torque teno virus (TTV, genus Alphatorquevirus). This is consistent with previous observations of the relationship between immunosuppression and TTV prevalence. The frequency of clinical trials for these viruses varies considerably, and CMV (human herpesvirus 5, HHV-5, n = 1082 tests in the present inventors' cohort) was monitored more frequently compared to other pathogens (Figure 11A). The present inventors evaluated the incidence of infections (the number of samples in which a given virus was detected by sequencing) compared to the clinical screening frequency. CMV was the most frequently screened (335 samples), but its incidence determined by sequencing (detected in 22 samples) was similar to that of other pathogens that are not normally screened, including adenovirus and polyomavirus (clinically tested in 4 and 1 cases respectively; Figure 1 1A).

[0177] Adenovirus is a community-acquired respiratory pathogen that can cause graft loss in lung transplant recipients and poses a particularly high risk to pediatric patients. For adenovirus A sample was collected from one pediatric patient (L78, panel 1 of FIG. 11B) who showed a positive test result. This patient had the highest adenovirus-derived DNA load in the entire cohort. Since the test is typically limited to pediatric lung transplant cases, several other adult transplant patients (e.g., L34, panel 1 of FIG. 11B) who were not clinically screened showed a persistent adenovirus load.

[0178] Polyomavirus is a major cause of allograft rejection after kidney transplantation, but it is usually not included in post-lung transplant monitoring. The inventors detected polyomavirus in two patients (L57 and L15, panel 2 of FIG. 11B) who were not tested for this pathogen. In both cases, the clinical records showed persistent renal insufficiency that could have resulted from polyomavirus infection.

[0179] In the last example of the benefits of broad and hypothesis-free screening for infection, the inventors examined a patient (L58) who showed a high load of human herpesvirus (HHV) 8 (panel 3 of FIG. 11B), an oncovirus that can cause complications after solid organ transplantation. This patient showed positive test results for two other herpesviruses (HHV-4a and HHV-5) that have the potential to stimulate HHV-8 reactivation. Post-transplant monitoring for HHV-8 is only recommended in specific clinical situations, but the use of sequencing allows for the identification of the virus in cases where it would otherwise be suspected to be undetectable.

[0180] Clinical monitoring of the microbiome. In addition to the viruses measured in serum, other ​​​​​​​​Fungal or bacterial infections detected in body fluids [Klebsiella pneumoniae infection detected by urine culture (ROC = 0.98) and fungal infections detected in BAL] and the correlation with cell-free measurements are also observed by the present inventors. The characteristics regarding bacterial and fungal correlations were sensitive to both the infective type in question and the body fluid. The present inventors observed better characteristics regarding body fluids more closely associated with blood, and also observed sensitivity to background signal. For example, the most commonly cultured bacterial infection (Pseudomonas) was detected in cell-free measurements in over 80% of the inventors' patient samples. This was in stark contrast to the most commonly detected viral pathogenic species (CMV) which was detected in only 6% of the inventors' patient samples. This emphasizes the important difference between commensal infections (including Pseudomonas), which are part of the indigenous flora, and non-commensal infections, which are exclusively pathogenic and have a lower background signal. This difference may explain the difference in sensitivity and specificity measured for commonly cultured commensal infections

[0181] [e.g., Pseudomonas aeruginosa and Escherichia coli with AUC = 0.66 and 0.62 respectively] compared to non-commensals [AUC = 0.91 for CMV]. In the case of commensal bacteria, the clinical problem is not the presence or absence, but the presence or absence in an inappropriate body site.

[0182] ​​​​​In our cohort, we also detected cell-free DNA derived from Microsporidia, an opportunistic fungus that can cause intestinal infections in immunosuppressed patients. We measured the persistent microsporidia burden in patient L78 (panel 4 of Figure 11B), who presented with classic symptoms of microsporidiosis. Adenovirus infection (L78, panel 1 of Figure 11B) was suspected as the cause. However, the results of endoscopy and sigmoidoscopy were inconclusive, and stool samples were negative for C. diff and adenovirus. Based on our sequencing data, microsporidiosis is the most

[0183] plausible explanation for the patient's symptoms, as the microsporidia signal measured in this patient was similar to that of patient I6, who had a positive test result for microsporidia from an unrelated cohort. Circulating cell-free DNA with more than 10 billion fragments per milliliter of plasma is a rich source of information relevant to human physiology and has rapidly

[0184] expanding applications in cancer diagnosis and cancer treatment monitoring by "genome transplant dynamics" , First, the strong correlation between cfDNA derived from CMV, which is the main cause of graft injury after transplantation, and clinical trial results was shown. The inventors further compared patients with similar microbial cfDNA levels to those showing positive clinical trial results and related symptoms and demonstrated that hypothesis-free infection monitoring shows a number of untested pathogens including undetected cases of adenovirus, polyomavirus, HHV-8, and microsporidia. These examples illustrate the advantages of sequence-based broad-spectrum infection monitoring compared to pathogen-specific tests. This approach can be immediately used as a means to assist in determining the occurrence and source of infection. In the case of transplantation, the incidence of infection is high, rejection and infection may occur simultaneously, and it is difficult to distinguish between the symptoms of infection and rejection However, this approach may be particularly important in such transplantation cases. Although preferred embodiments of the present invention are shown and described herein, it will be apparent to those skilled in the art that such embodiments are merely illustrative. Many changes, variations, and substitutions will now be recognized by those skilled in the art without departing from the present invention. It should be understood that various alternatives to the embodiments of the present invention described herein can be used in the practice of the present invention. The following claims define the scope of the present invention, and methods and structures within the scope of these claims, as well as their equivalents, are intended to be included within the present invention.

[0185] Although preferred embodiments of the present invention are shown and described herein, it will be apparent to those skilled in the art that such embodiments are merely illustrative and are described only as examples. Many changes, variations, and substitutions will now be recognized by those skilled in the art without departing from the present invention. It should be understood that various alternatives to the embodiments of the present invention described herein can be used in the practice of the present invention. The following claims define the scope of the present invention, and methods and structures within the scope of these claims, as well as their equivalents, are intended to be included within the present invention. ​​​​​

Claims

Claim 1 A method for determining the presence and prevalence of microbial sequences in a sample of cell-free nucleic acids from a non-microbial host, comprising: (i) preparing a sample of cell-free nucleic acids from an individual; performing high-throughput sequencing of said nucleic acids; (iii) performing bioinformatics analysis to subtract host sequences from the analysis; and (iv) determining the presence and prevalence of microbial sequences for the microbiome assessment of said non-microbial host. Claim 2 The method according to claim 1, wherein the presence and prevalence of multiple microorganisms are determined. Claim 3 The method according to claim 1, wherein high-throughput sequencing is performed on a nucleic acid sample amplified by an unbiased method. Claim 4 Claim 5 The method according to claim 1, wherein step (iv) comprises comparing the coverage of sequences located in a microbial reference sequence with the coverage of a host reference sequence. Claim 6 At least 10 ６ The method according to claim 1, which performs at least 10 array readings. The method according to claim 1, wherein step (iii) comprises identifying a reference host sequence and masking microbial sequences or microbial mimic sequences present in the reference host genome. Claim 7 The method according to claim 1, wherein step (iii) comprises identifying a reference microbial sequence and masking host sequences or host mimic sequences present in the reference microbial genome. Claim 8 The method according to claim 1, wherein the presence of one or more pathogenic microorganisms is confirmed. Claim 9 The method according to claim 1, wherein the analysis is performed at two or more time points. Claim 10 The method according to claim 1, wherein the amount of said one or more microbial nucleic acids serves as an indicator of an infection status or treatment outcome. Claim 11 The method according to claim 10, wherein the amount of said one or more nucleic acids exceeding a predetermined threshold serves as an indicator of an infection status or treatment outcome. Claim 12 The method according to claim 1, wherein the sample is selected from the group consisting of blood, serum, urine, and feces. Claim 13 The method according to claim 1, wherein the nucleic acid is selected from the group consisting of double-stranded DNA, single-stranded DNA, single-stranded DNA hairpin, DNA / RNA hybrid, single-stranded RNA, double-stranded RNA, and RNA hairpin. Claim 14 The method according to claim 1, wherein the nucleic acid is selected from the group consisting of double-stranded DNA, single-stranded DNA, and cDNA. Claim 15 The method according to claim 1, further comprising providing the microbiome assessment to the individual. Claim 16 The method according to claim 1, wherein the microbiome assessment results in a determination of response to treatment. Claim 17 ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ The method according to claim 1, wherein the evaluation of the microbiome results in the measurement of human physiological functions.

18. The method according to claim 1, wherein the evaluation of the microbiome is used to calculate a pathogenicity score for microorganisms present in the non-microbial host.

19. A computer-readable medium comprising a set of instructions recorded thereon for a computer to perform the steps of: (i) receiving high-throughput data from one or more cell-free nucleic acids detected in a sample from a subject; (iii) performing bioinformatics analysis to subtract host sequences from the analysis; (iv) determining the presence and prevalence of microbial sequences.

20. A method for evaluating an individual's immune function, comprising: preparing a sample from a subject; determining the presence or absence of one or more microbiome nucleic acids in the sample; evaluating immune function based on the presence of the one or more microbiome nucleic acids.

21. The method according to claim 20, wherein the virome component of the microbiome is analyzed.

22. The method according to claim 21, wherein a temporal difference in the amount of the one or more virome nucleic acids is an indicator of the immune function state.

23. The method according to claim 21, further comprising quantifying the viral load in the individual.

24. The method according to claim 23, wherein the virome is analyzed with respect to the viral load of an anellovirus.

25. The method according to claim 20, wherein the individual is undergoing an immunosuppressive regimen.

26. The method according to claim 20, wherein the individual has received a transplant. 。

27. The method according to claim 26, wherein the transplant is selected from the group consisting of bone marrow transplant, kidney transplant, heart transplant, liver transplant, pancreas transplant, lung transplant, intestine transplant, and skin transplant.

28. The method according to claim 20, wherein the nucleic acid is cell-free circulating DNA.

29. The method according to claim 20, wherein the presence or absence of the one or more nucleic acids is determined by a method selected from the group consisting of sequencing, nucleic acid array, and PCR.

30. The method according to claim 20, wherein the amount of the one or more nucleic acids is an indicator of the transplant status or outcome.

31. The method according to claim 30, wherein an amount of the one or more nucleic acids exceeding a predetermined threshold is an indicator of the transplant status or outcome.

32. The method according to claim 30, wherein the threshold relates to clinically stable post-transplant patients showing no evidence of transplant rejection or other pathologies. ​ ​ ​ ​ ​ ​ ​ The method according to claim 30, which is a specified reference value. **Claim 33** The method according to claim 30, wherein there are predetermined threshold values that vary depending on the result or state of transplantation. **Claim 34** The method according to claim 30, further comprising treating the individual according to the evaluation of immune function.

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