Compositions, systems, and methods relating to predictive microbiome transplantation and clostridioides difficile therapies

Abstract

Described herein are systems, methods, and computer readable medium for, among other things, predictive platforms for novel microbial therapeutics. Such systems, methods, and computer readable medium can be utilized for identifying candidate microbiota for administration against a candidate bacterial infection in particular. In embodiment, the bacterial infection is a severe Clostridioides difficile (C. diff) infection. In embodiments, described herein are systems, methods and computer readable medium for, among other things, potential bacterial therapeutics for treating C. diff infection. An aspect of the present disclosure also provides a system, method and computer readable medium for, among other things, algorithms / models that enabled the predictions of the specific combinations of bacteria to enable the therapeutic intervention. Also described herein are compositions, pharmaceutical compositions, kits, and methods of administration relating to novel therapeutics for bacterial infections, for example, C. diff.

Description

[0001] COMPOSITIONS, SYSTEMS, AND METHODS RELATING TO PREDICTIVE MICROBIOME TRANSPLANTATION AND CLOSTRIDIOIDES DIFFICILE THERAPIES

[0002] CROSS REFERENCE TO RELATED APPLICATIONS]

[0003] This application claims priority to, and the benefit of, U.S. Provisional Patent Application Serial No. 63 / 517,567 filed on August 3, 2023, which is incorporated herein by reference in its entirety.

[0004] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0005] This invention was made with Government support under contracts AT010253 and AI124214 awarded by the National Institutes of Health. The Government has certain rights in the invention.

[0006] BACKGROUND

[0007] Fecal Microbiota Transplant (FMT) is an emerging therapy that has had remarkable success in treatment and prevention of bacterial infections that are resistant to traditional antibiotic therapies, for example, recurrent / recurring Clostridioides difficile (C. difficile or “C. diff”) infection (“rCDI”). However, there currently lacks guidance as to which particular samples make result in successful transplantation for a given bacterial infection. Additionally, FMT has recently been associated with adverse outcomes such as inadvertent transfer of antimicrobial resistance, necessitating development of more targeted bacteriotherapies. Accordingly, there is a need to address the aforementioned deficiencies and inadequacies.

[0008] SUMMARY

[0009] Described herein are systems, methods, compositions, pharmaceutical compositions, and methods of treatment relating to identifying and / or administering candidate bacterial microbiota ( / .e., also referred to herein as bacterial consortium, bacterial populations, and the like) for bacterial infections.

[0010] In an embodiment, described herein is a method of identifying candidate microbiota for administration against a candidate bacterial infection, comprising: determining, from provided successful bacterial administration metagenomic sequencing data and failed bacterial administration metagenomic sequencing data, taxonomic bacterial composition of one or more samples of a successful bacterial administration against the candidate bacterial infection and taxonomic composition one or more samples of a successful bacterial administration against a candidate bacterial infection; determining superorganism-level functional metabolic capacity from the successful bacterial administration metagenomic sequencing data and failed bacterial administration metagenomic sequencing data; identifying metabolic pathways with differential metabolic capacities between the successful and failed administrations from the determined capacities; clustering the successful bacterial administration samples and failed bacterial administration samples based on the identified determined functional metabolic capacities; annotating the gene content of each cluster; quantifying the annotated gene content; segregating the quantified gene content based on administration success or failure; identifying genes enriched in one or more metabolic pathways from the segregated quantified gene content of the successful administration; reconstructing the metabolism of the one or more metabolic pathways mapped onto one or more species from the determined taxonomic composition; segregating the reconstructed metabolism of the determined taxonomic composition into cooperative or competitive with the candidate bacterial infection; and identifying one or more bacterial species for administration from the determined taxonomic composition having cooperative or competitive metabolism with the candidate bacterial infection.

[0011] In embodiments of methods as described herein, the candidate bacterial infection can be a Clostridioides difficile (C. diff) infection. In embodiments of methods as described herein, the microbiota administration can be a fecal microbiota transplant. Embodiments of methods as described herein can further comprise, before determining the taxonomic composition providing one or more samples of a successful bacterial administration against the candidate bacterial infection from one or more donors and providing one or more samples of a failed bacterial administration against the candidate bacterial infection from one or more donors. Embodiments of methods as described herein can further comprise, before determining the taxonomic composition, sequencing the metagenome of the one or more successful bacterial administration samples and the metagenome of the one or more failed bacterial administration samples.

[0012] In embodiments of methods as described herein, the one or more successful administration samples and one or more failed administration samples can each be fecal sample. In embodiments of methods as described herein, successful administration can be determined by a reduction in bacterial {e.g., C. diff) toxin level compared to before administration, increased survival, or both. In embodiments of methods as described herein, failed administration can be determined by no change or increased bacterial {e.g., C. diff) toxin levels compared to before administration, reduced survival, or both. In embodiments of methods as described herein, metagenomic sequencing comprises shotgun sequencing, 16S rRNA sequencing, inferred from metatranscriptome, or other next-gen sequencing methods, e.g., using the 16S rRNA gene as a phylogenetic marker) or shotgun sequencing. Additional information relating to metagenomic sequencing can be found in the art, for example, in Perez- Cobas AE, Gomez-Valero L, Buchrieser C. Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses. Microb Genom. 2020 Aug;6(8):mgen000409. doi: 10.1099 / mgen.0.000409. Epub 2020 Jul 24. PMID: 32706331 ; PMCID: PMC7641418, the entirety of which is incorporated by reference as if fully set forth herein.

[0013] In embodiments of methods as described herein, the superorganism-level functional capacity can be determined by assembling contiguous genomic sequences from the metagenomic sequencing data; annotating gene content by assigning functional pathways to the assembled genomic sequences; mapping metagenomic reads to annotated genes; and differentiating functionalities of the mapped metagenomic reads. In embodiments of methods as described herein, segregating the quantified gene content can be using machine learning. In embodiments, the machine learning can be a random forest or support vector machine. In embodiments, the reconstructing the metabolism and segregating the reconstructed metabolism is with genome-scale metabolic network reconstructions.

[0014] In embodiments of methods as described herein, the one or more metabolic pathways can be one or more of amino acid biosynthesis, combined galactose metabolism, amino sugar metabolism, nucleotide sugar metabolism, starch metabolism, or sucrose metabolism, individually or in any combination thereof.

[0015] In embodiments, described herein are bacterial consortium (also referred to herein as a bacterial population. Bacterial consortium can comprise microbiota ( / .e., bacteria) that can be of one or more strains of bacteria. In embodiments of bacterial consortium as described herein, a bacterial consortium comprises one or more bacteria that cooperatively share amino acids and carbohydrates with a candidate bacteria of a candidate bacterial infection, for example, C. difficile. In embodiments, the shared amino acids can comprise one or more of leucine, phenylalanine, glucose-1-phosphase, L-proline, ornithine, fumarate, or glucose-6- phosphate, individually or in any combination of any thereof. In embodiments, the bacterial consortium comprises one or more of Bifidobacterium longum (B. longum), Escherichia coli (E. coli), Roseburia intestinalis (R. intestinal is), or Streptococcus thermophilus (S. thermophilus), individually or in any combination of any thereof. In embodiments, the bacterial consortium comprises Bifidobacterium longum (B. longum), Escherichia coli (E. coli), Roseburia intestinalis (R. intestinalis), and Streptococcus thermophilus (S. thermophilus). In embodiments, the bacterial consortium consists essentially of B. longum, E. coli, R. intestinalis, and S. thermophilus. In embodiments, the bacterial consortium consists of B. longum, E. coli, R. intestinalis, and S. thermophilus. In embodiments, each of the B. longum, E. coli, R. intestinalis, and S. thermophilus are at enriched levels (i.e., quantities) compared to any other bacteria present in the consortium. In embodiments, the B. longum can be ATCC 55813 B. longum. In embodiments, the E. coli can be K12 E. coli. In embodiments, the R. intestinalis can be DSM 14610 R. intestinalis. In embodiments, the S. thermophilus can be LMD-9 S. thermophilus. Described herein are methods of treatment. Methods of treatment as described herein can comprise administering a bacterial consortium as described herein to a subject in need thereof, for example a subject having bacterial infection. In embodiments, the bacterial infection can be a treatment-resistant infection or otherwise recurring infection. In embodiments, the bacterial infection can be a C. diff infection. In an embodiment, described herein is a method of treating a C. diff infection in a subject in need thereof, comprising administering a pharmaceutical composition as described herein to a subject having or suspected of having a C. diff infection. In embodiments, the bacterial infection or C. diff infection is not responsive to antibiotic treatment. In embodiments, the administration can be oral administration or one or more fecal transplants. In embodiments, the bacterial consortium can be administered in an effective amount to reduce one or more symptoms of C. diff infection. In embodiments, the effective amount can be about 106to about 1011. Methods as described herein can further comprise administering a bacterial consortium as described herein with a pharmaceutically acceptable carrier. In embodiments of methods as described herein, the composition can be sterilized prior to administration.

[0016] Also described herein are kits. In embodiments, described herein are kits comprising a bacterial consortium as described herein and instructions for use. In embodiments, kits can further comprise bacterial consortium in a dosage unit form. In embodiments, kits can further comprise a pharmaceutically acceptable carrier.

[0017] In an embodiment, described herein is a method for performing at least one of the following: a) design of a systems-ecology designed bacterial consortium to protect from severe Clostridioides difficile (C. diff) infection; b) potential bacterial therapeutics for treating C. diff infections; and c) algorithms / models that enabled the predictions and selections of the specific combinations of bacteria for successful therapeutic intervention, as described herein.

[0018] In embodiments, described herein are systems configured for performing at least one of the following: a) a systems-ecology designed bacterial consortium to protect from severe Clostridioides difficile (C. diff) infection; b) bacterial therapeutics for treating C. diff infection; and c) algorithms / models that can predict combinations of bacteria that allow for a therapeutic intervention (of a C. diff er other bacterial infection), as described herein.

[0019] In embodiments, described herein is a computer-readable storage medium having computer-executable instructions stored thereon which, when executed by one or more processors, cause one or more computers to perform functions for providing at least one of the following: a) a systems-ecology designed bacterial consortium to protect from severe Closttidioides difficile (C. diff) infection; b) potential bacterial therapeutic for treating (C. diff) infection; and c) algorithms / models that can predict combinations of bacteria that allow for a therapeutic intervention (of a C. diff er other bacterial infection), as described herein. In embodiment, described herein is method for using at least one of the following: a) a systems-ecology designed bacterial consortium to protect from (or otherwise treat) severe Clostridioides difficile (C. diff) infection; b) potential bacterial therapeutic for treating C. diff infection; and c) algorithms / models that enabled the predictions of the specific combinations of bacteria to enable the therapeutic intervention (of a C. diff or other bacterial infection), as described herein.

[0020] BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Many aspects of the disclosed devices and methods can be better understood with reference to the following drawings. The components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the relevant principles. Moreover, in the drawings, like reference numerals designate corresponding parts throughout the several views.

[0022] FIGs. 1A-1C: Shotgun metagenomic analysis from Fecal Microbiota Transplant FMT donors in local patient cohort. FIG. 1A is a human FMT sample schematic, following previous FMT study at UVA. Three individual donors with >14 donations each were selected for metagenomic profiling based on rates of successful rCDI resolution. Donor A had the highest rate of success with 30 of 33 donations resulting in resolved rCDI (90.9%). The other two donors had rates of Donor B 16 of 30 donations (53.3%) and Donor C 8 of 14 samples (57.1%), respectively. FIG. 1B shows a predicted Family-level classification using MetaPhlAn2. Donors, time, and associated outcomes labeled on lower axis according to panel A. FIG. 1C and FIG. 1D depict a superorganism-level analysis of metabolic capacity present in the microbiota of each donor grouping. Radar plots display relative abundance of genes in metabolic pathways with statistically-significant58 mean decrease accuracies differentiating between indicated groups by random forest supervised machine learning, with the associated out-of-bag error indicated below each key for comparing donor A against the donors B & C. Values below each pathway label indicate the number of unique genes identified as belonging to each pathway from all contributing species.

[0023] FIGs. 2A-2D: MAG-based analysis identified specific metabolism and contributing bacterial taxa that were associated with successful rCDI resolution. MAGs within each assembled metagenome were clustered and curated based on sequence composition and contig abundance. FIG. 2A is a plot of statistically significant features58 from random forest supervised machine learning discriminating metabolic pathway gene abundances for MAGs associated with either successful or failed rCDI resolution. Groups indicate which FMT response was associated with the higher median gene abundance in each pathway. The resultant model had an OOB error of 25.88%, a PPV of 66.67%, and an NPV of 81 .58%. FIG. 2B is a scatterplot of MAG pathway abundance for amino acid biosynthesis and select carbohydrate metabolism (consolidation of galactose metabolism, amino sugar and nucleotide metabolism, and starch and sucrose metabolism), identified by machine learning analysis. Ratio of total genes in each MAG was calculated for each MAG, and a 90thquantile cutoff was applied to highlight 84 MAGs, which are colored by donor of origin. FIG. 2C is a tree showing species-level classifications and phylogeny for the 26 GENREs used in downstream metabolic interaction simulations. To the left of the phylogeny are the percent of metabolic genes each pathway represents within the MAGs associated with each species. FIG. 2D is a plot showing an a example de novo GENRE reconstruction from a curated MAG annotated as Blautia producta. The platform utilizes KEGG ortholog with associated ModelSEED metabolic reaction annotations to assemble scaffold models. Below the schematic are quality metrics for all 26 draft GENREs created for this study: stoichiometric consistency, Reaction Mass Balance, and overall M EMOTE score.

[0024] FIGs. 3A-3E: Prediction and validation of metabolic interactions between candidate probiotic strains and C. difficile. FIG. 3A is a schematic and constraints for an embodiment of an in silico simulation of metabolic interactions between probiotic and C. difficile GENREs. Simulations were initialized by calculating the combined minimal media components of both GENREs and setting flux ranges accordingly. FIG. 3B is a plot showing C. difficile str. R20291 GENRE (iCdR703) biomass flux (computational analog for bacterial growth) following each step of iterative growth and metabolic interaction simulations with interacting species. FIG. 3C is a plot illustrating cooperative indices for predicted axes of cooperation between the C. difficile GENRE and the MAG-enabled GENRE of Bifidobacterium longum. C. difficile cooperative indices are represented as negative. FIG. 3D is a plot showing competitive indices for predicted axes of metabolite competition between the C. difficile GENRE and the MAG-enabled GENRE of Blautia producta. C. difficile cooperative indices are represented as negative. FIG. 3E is a schematic for an embodiment of in vitro validation of growth inhibition and metabolic crosstalk between candidate species and C. difficile str. R20291 through conditioned media experiments. Conditioned media was generated for each potential interactor species as well as C. difficile str. R20291 itself as a positive control of competition for growth substrates.

[0025] FIGs. 4A-4B: Metabolomics validation for ecological interactions with C. difficile. Untargeted LC-MS analysis from conditioned medium experiments at each labeled stage from Figure 3E for both validation species with C. difficile str. R20291 (n = 6 each); predicted cooperator (FIG. A) Bifidobacterium longum str. ATCC 55813 and predicted competitor (FIG. B) Blautia producta str. DSM 2950. Log10 Intensity refers to the transformed difference in relative intensity for metabolites between the medium before and after bacterial growth. For a change in relative scaled intensity of a given metabolite to be included in the analysis, it must be significantly decreased in both C. difficile and the other species' individual cultures, or the intensities or the intensities must be significantly increased in other species' individual cultures and then significantly decreased following C. difficile growth in the conditioned medium. Statistically significant differences determined by Wilcoxon rank-sum test and green stars denote possible Stickland fermentation substrates.

[0026] FIGs. 5A-5I: in vivo testing of targeted consortia in an animal model of acute CDI. FIG. 5A is an embodiment of an experimental timeline of animal model used to test probiotic efficacy (n=14 per group). FIG. 5B is a post-infection survival curve for each experimental groups used. Significant difference determined by Kaplan-Meier test. FIG. 5C is a graph showing quantification of total C. difficile str. R20291 CFU per gram of cecal content in mice (Day 5). Significant differences determined by Wilcoxon rank sum test with Benjamini- Hochberg correction. FIG. 5D is a plot of relative concentration of C. difficile toxin per gram of cecal content in mice (Day 5). Significant differences again determined by Wilcoxon rank-sum test with Benjamini- Hochberg correction. FIG. 5E are microscopy images and plots depicting C. difficile colony morphologies from overnight growth on BHIS plated from cecal content of infected animals receiving the indicated probiotic consortia. Significant differences determined by Wilcoxon rank-sum test with Benjamini-Hochberg correction. FIG. 5F is a plot illustrating NMDS ordination of Bray-Curtis dissimilarities of cecal communities from each experimental group at the time of representative takedown (Day 5). Significant difference determined by PERMANOVA. FIG. 5G is a plot of inverse Simpson diversity of cecal communities from each experimental group (Day 5). Significant difference determined by Wilcoxon rank-sum test with Benjamini-Hochberg correction. Selected cell-type to live cell ratio from flow cytometric analysis; (FIG. 5H) Eosinophils or (FIG. 5I) ILC3 cells. Significant differences determined by Wilcoxon rank-sum test with Benjamini-Hochberg correction.

[0027] FIG. 6 is a is a block diagram illustrating an example of a machine upon which one or more aspects of embodiments of the present disclosure can be implemented.

[0028] FIGs. 7A-7D: Taxonomic composition and predicted functional capacity of microbiota in successful FMT donor samples. Results from analysis of 16S rRNA gene sequencing collected from capsule donor samples with 79.8% (71 / 89) efficacy used in the previous study from Staley et. al.22. To avoid skewing results toward individuals with larger numbers of utilized capsules, a maximum of 5 samples were randomly selected (when possible) from each donor for analysis across 10 unique donor pools, resulting in 76 donor samples for downstream analysis. FIG. 7A is a plot of relative abundances of Family-level taxonomic representation from ASVs associated with successful resolution of rCDI. FIG. 7B is a genus-level breakdown of the dominant Family (Lachnospirales) from FIG. 7A. FIG. 7C illustrates median and IQR for gene abundances from top 25 most abundant pathways in imputed metagenomic content using PICRUSt. Median points are colored based on the pathway’s relationship to metabolism. FIG. 7D is a breakdown of most abundant individual gene inferred abundances.

[0029] FIGs. 8A-8D: Supplementary metagenomic analysis of FMT donor samples. Comparisons of Inv. Simpson diversity from community structures inferred by MetaPhlAn2 analysis in (FIG. 8A) high success-associated versus low success-associated samples or (FIG. 8B) successful rCDI resolution versus failure. Differences calculated by Wilcoxon ranked-sum test. FIGs. 8C and 8D depict a similar analysis to FIGs. 1C and 1D, instead limiting the predictive model to only non-metabolic pathway abundances at Superorganismlevel.

[0030] FIGs. 9A-9B: MAG quality filtering results. Raw MAGs generated from unsupervised Metabat2 contig clustering were pruned first by a minimum size of >1.3 Mb and >1345 putative genes (based on Pelagibacter ubique, smallest genome of a free-living bacterium). CheckM analysis was then performed on both size-filtered MAG groups, and another filter was applied of >50% completeness and <33% contamination (defined within CheckM). CheckM quality metrics for the pre-filter and resultant post-filter MAGs are shown in (FIG. 9A) completeness and (FIG. 9B) contamination. Statistically significant differences determined by Wilcoxon rank-sum test.

[0031] FIGs. 10A-10C: Computational and in vitro validation of consortia interactions with C. difficile. FIG. 10A is a plot showing quantification of directionality for shared metabolites across all cooperative simulations performed with iCdR703. FIG. 10B is a plot of in silico consortia impact on iCdR703 biomass flux. Interaction metabolites for each group were determined using the union of edges of interaction returned by individual simulations for component species. Lower bounds of exchange reactions for edges of potential competition were set to 0, and those for edges of potential cooperation were set to -1000. FIG. 10C is a plot of the combined in vitro consortia effects on 18 hr growth of C. difficile str. R20291 at 37°C in the indicated pre-conditioned media compared to fresh BHI + 10% FBS (n=5). Significant differences determined by Dynamic Time Warping and PERMANOVA.

[0032] FIGs. 11A-11D: Additional immunological characterization of murine infection models with consortium gavage. For data regarding spectral flow cytometry gating strategy, see FIG. S5A in U.S. Provisional Application 63 / 517,567, incorporated by reference herein. Resultant densities of cell types of interest are as follows FIG. 11A shows plots depicting select innate immunity cell lineages with previous links the GDI response, FIG. 11B shows plots depicting select adaptive immunity cell lineages with previous links the GDI response, and (FIG. 11C) additional cell lineages with large-scale changes between groups. All values reflect percentages of total live cells detected, and significant differences determined by Wilcoxon rank-sum test. FIG. 11D is a plot showing clinical scores of mice following infection and bacteriotherapy (n = 9). Groups with no remaining animals are denoted by NA. Scores were based on weight loss, coat conditions, activity level, diarrhea, posture and eye condition for a cumulative clinical score between 1 and 20. Weight loss and activity levels were scored between 0 and 4 with four being greater than or equal to 25% loss in weight. Coat condition, diarrhea, posture, and eye condition were scored between 0 and 3. Diarrhea scores were 1 for soft or yellow stool, 2 for wet tail, and 3 for liquid or no stool. Mice were euthanized if severe illness developed based on a clinical score > 14.

[0033] FIGs. 12A-12C: Additional testing for consortia detectability and growth suppression from conditioned media. FIG. 12A depicts detectability of 16S rRNA gene sequencing reads of the respective consortium members. FIG. 12B is a plot of growth inhibition diameter measurements from disk diffusion assay for C. difficile str. R20291 with the indicated treatments (n = 6). FIG. 12C is a plot of area under the curve results from 18-hr C. difficile str. R20291 growth in supplemented (50:50) liquid BHIS previously depleted by str. R20291 over 24 hours with the indicated growth medium variation. Significant differences were determined by Wilcoxon rank-sum test with Benjamini-Hochberg correction (n = 4).

[0034] DETAILED DESCRIPTION

[0035] Before the present disclosure is described in greater detail, it is to be understood that this disclosure is not limited to particular embodiments described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present disclosure will be limited only by the appended claims.

[0036] Although example embodiments of the present disclosure are explained in some instances in detail herein, it is to be understood that other embodiments are contemplated. Accordingly, it is not intended that the present disclosure be limited in its scope to the details of construction and arrangement of components set forth in the following description or illustrated in the drawings. The present disclosure is capable of other embodiments and of being practiced or carried out in various ways.

[0037] Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit (unless the context clearly dictates otherwise), between the upper and lower limit of that range, and any other stated or intervening value in that stated range, is encompassed within the disclosure. The upper and lower limits of these smaller ranges may independently be included in the smaller ranges and are also encompassed within the disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure.

[0038] As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present disclosure. Any recited method can be carried out in the order of events recited or in any other order that is logically possible.

[0039] Regarding machine hardware, it should be appreciated that any of the components or modules referred to with regards to any of the present invention embodiments discussed herein, may be integrally or separately formed with one another. Further, redundant functions or structures of the components or modules may be implemented. Moreover, the various components may be communicated locally and / or remotely with any user / operator / customer / client or machine / system / computer / processor. Moreover, the various components may be in communication via wireless and / or hardwire or other desirable and available communication means, systems and hardware. Moreover, various components and modules may be substituted with other modules or components that provide similar functions.

[0040] Embodiments of the present disclosure will employ, unless otherwise indicated, techniques of genetics, microbiology, biochemistry, molecular biology, cellular biology, tissue culture, therapeutic administrations and the like.

[0041] Before the embodiments of the present disclosure are described in detail, it is to be understood that, unless otherwise indicated, the present disclosure is not limited to particular materials, reagents, reaction materials, manufacturing processes, or the like, as such can vary. It is also to be understood that the terminology used herein is for purposes of describing particular embodiments only and is not intended to be limiting. It is also possible in the present disclosure that steps can be executed in different sequence where this is logically possible.

[0042] Definitions

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present disclosure, suitable methods and materials are described herein.

[0044] As used in the specification and the appended claims, the singular forms “a,” “an,” and “the” may include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a support” includes a plurality of supports. In this specification and in the claims that follow, reference will be made to a number of terms that shall be defined to have the following meanings unless a contrary intention is apparent.

[0045] Unless otherwise indicated, all numbers expressing quantities of ingredients, properties such as reaction conditions, and so forth used in the specification and claims are to be understood as being modified in all instances by the term “about.” Accordingly, unless indicated to the contrary, the numerical parameters set forth in this specification and claims are approximations that can vary depending upon the desired properties sought to be obtained by the presently disclosed subject-matter.

[0046] The term “about”, when used herein in reference to a value, refers to a value that is similar, in context to the referenced value. In general, those skilled in the art, familiar with the context, will appreciate the relevant degree of variance encompassed by “about” in that context, for example, ±5%, ±4%, ±3%, ±2%, etc.

[0047] Two events or entities are “associated” with one another, as that term is used herein, if the presence, level and / or form of one is correlated with that of the other. For example, a particular entity (e.g., polypeptide, genetic signature, metabolite, microbe, etc.) is considered to be associated with a particular disease, disorder, or condition, if its presence, level and / or form correlates with incidence of and / or susceptibility to the disease, disorder, or condition (e.g., across a relevant population). In some embodiments, two or more entities are physically “associated” with one another if they interact, directly or indirectly, so that they are and / or remain in physical proximity with one another. In some embodiments, two or more entities that are physically associated with one another are covalently linked to one another; in some embodiments, two or more entities that are physically associated with one another are not covalently linked to one another but are non-covalently associated, for example by means of hydrogen bonds, van der Waals interaction, hydrophobic interactions, magnetism, and combinations thereof.

[0048] As used herein, the term “comparable” refers to two or more agents, entities, situations, sets of conditions, etc., that may not be identical to one another but that are sufficiently similar to permit comparison there between so that one skilled in the art will appreciate that conclusions can reasonably be drawn based on differences or similarities observed. In some embodiments, comparable sets of conditions, circumstances, individuals, or populations are characterized by a plurality of substantially identical features and one or a small number of varied features. Those of ordinary skill in the art will understand, in context, what degree of identity is required in any given circumstance for two or more such agents, entities, situations, sets of conditions, etc. to be considered comparable. For example, those of ordinary skill in the art will appreciate that sets of circumstances, individuals, or populations are comparable to one another when characterized by a sufficient number and type of substantially identical features to warrant a reasonable conclusion that differences in results obtained or phenomena observed under or with different sets of circumstances, individuals, or populations are caused by or indicative of the variation in those features that are varied.

[0049] Those skilled in the art will appreciate that the term “composition”, as used herein, can be used to refer to a discrete physical entity that comprises one or more specified components. In general, unless otherwise specified, a composition can be of any suitable form - e.g., gel, liquid, solid, etc. A composition or method described herein as "comprising" one or more named elements or steps is open-ended, meaning that the named elements or steps are essential to a particular aspect or embodiment, but other elements or steps can be added within the scope of the composition or method. To avoid prolixity, it is also understood that any composition or method described as "comprising" (or which "comprises") one or more named elements or steps also describes the corresponding, more limited composition or method "consisting essentially of' (or which "consists essentially of") the same named elements or steps, meaning that the composition or method includes the named essential elements or steps and can also include additional elements or steps that do not materially affect the basic and novel characteristic(s) of the composition or method. It is also understood that any composition or method described herein as "comprising" or "consisting essentially of" one or more named elements or steps also describes the corresponding, more limited, and closed-ended composition or method "consisting of" (or "consists of') the named elements or steps to the exclusion of any other unnamed element or step. In any composition or method disclosed herein, known or disclosed equivalents of any named essential element or step can be substituted for that element or step.

[0050] In this disclosure, "consisting essentially of" or "consists essentially" or the like, when applied to methods and compositions encompassed by the present disclosure refers to compositions like those disclosed herein, but which may contain additional structural groups, composition components or method steps (or analogs or derivatives thereof as discussed above). Such additional structural groups, composition components or method steps, etc., however, do not materially affect the basic and novel characteristic(s) of the compositions or methods, compared to those of the corresponding compositions or methods disclosed herein. "Consisting essentially of" or "consists essentially" or the like, when applied to methods and compositions encompassed by the present disclosure have the meaning ascribed in U.S. Patent law and the term is open-ended, allowing for the presence of more than that which is recited so long as basic or novel characteristics of that which is recited is not changed by the presence of more than that which is recited, but excludes prior art embodiments.

[0051] As used herein, “Improved,” “increased” or “reduced,” or grammatically comparable comparative terms, indicate values that are relative to a baseline value or reference measurement. For example, in some embodiments, an assessed value achieved with an agent of interest may be “improved” relative to that obtained or expected in the absence of treatment or with a comparable reference agent or control. Alternatively, or additionally, in some embodiments, an assessed value achieved with an agent of interest may be “improved” relative to that obtained in the same subject or system under different conditions (e.g., prior to or after an event such as administration of an agent of interest), or in a different, comparable subject (e.g., in a comparable subject or system that differs from the subject or system of interest). In some embodiments, comparative terms refer to statistically relevant differences (e.g., that are of a prevalence and / or magnitude sufficient to achieve statistical relevance). Those skilled in the art will be aware, or will readily be able to determine, in a given context, a degree and / or prevalence of difference that is required or sufficient to achieve such statistical significance.

[0052] As used herein, “isolated” means separated from constituents that otherwise may be present, for example, separated from bacterial stains or species that are not desired, or separating from other constituents that may be present with the micro-organisms in nature.

[0053] As used herein, the term “encode” refers to principle that DNA can be transcribed into RNA, which can then be translated into amino acid sequences that can form proteins

[0054] As used herein, the terms “optional” or “optionally” means that the subsequently described event or circumstance can or cannot occur, and that the description includes instances where said event or circumstance occurs and instances where it does not.

[0055] As used herein, “individual”, "organism", "host", "subject", and “patient” refers to any living entity comprised of at least one cell. A living organism can be as simple as, for example, a single isolated eukaryotic cell or cultured cell or cell line, or as complex as a mammal, including a human being, and animals (e.g., vertebrates, amphibians, fish, mammals, e.g., cats, dogs, horses, pigs, cows, sheep, rodents, rabbits, squirrels, bears, primates (e.g., chimpanzees, gorillas, and humans). These terms (“individual,” “subject,” “host,” and “patient,” used interchangeably herein also refer to any mammalian subject for whom diagnosis, treatment, or therapy is desired, particularly humans. In embodiments, subject may relate to particular components of the subject, for instance specific tissues or fluids of a subject (e.g., human tissue in a particular area of the body of a living subject), which may be in a particular location of the subject, referred to herein as an "area of interest" or a "region of interest."

[0056] As used herein, “kit” means a collection of at least two components constituting the kit. Together, the components constitute a functional unit for a given purpose. Individual member components may be physically packaged together or separately. For example, a kit comprising an instruction for using the kit may or may not physically include the instruction with other individual member components. Instead, the instruction can be supplied as a separate member component, either in a paper form or an electronic form which may be supplied on computer readable memory device or downloaded from an internet website, or as recorded presentation.

[0057] As used herein, “instruction(s)” means documents describing relevant materials or methodologies pertaining to a kit. These materials may include any combination of the following: background information, list of components and their availability information (purchase information, etc.), brief or detailed protocols for using the kit, trouble-shooting, references, technical support, and any other related documents. Instructions can be supplied with the kit or as a separate member component, either as a paper form or an electronic form which may be supplied on computer readable memory device or downloaded from an internet website, or as recorded presentation. Instructions can comprise one or multiple documents and are meant to include future updates.

[0058] Reference throughout this specification to “one embodiment”, “an embodiment”, “another embodiment”, “some embodiment,” means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases “in one embodiment,” “in an embodiment,” “in another embodiment”, or “in some embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment, but they may. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner, as would be apparent to a person skilled in the art from this disclosure, in one or more embodiments. Furthermore, while some embodiments described herein include some, but not other, features included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention. For example, in the appended claims, any of the claimed embodiments can be used in any combination.

[0059] A “control” sample or value refers to a sample that serves as a reference, usually a known reference, for comparison to a test sample or condition. For example, a test sample can include cells exposed to a test condition or a test agent, while the control is not exposed to the test condition or agent (e.g., negative control). The control can also be a positive control, e.g., a known primary cell or a cell exposed to known conditions or agents, for the sake of comparison to the test condition. A control can also represent an average value gathered from a plurality of samples, e.g., to obtain an average value. For therapeutic applications, a sample obtained from a patient suspected of having a given disorder or deficiency can be compared to samples from a known normal (non-deficient) individual. A control can also represent an average value gathered from a population of similar individuals, e.g., patient having a given deficiency or healthy individuals with a similar medical background, same age, weight, etc. A control value can also be obtained from the same individual, e.g., from an earlier-obtained sample, prior to the disorder or deficiency, or prior to treatment. One of skill will recognize that controls can be designed for assessment of any number of parameters.

[0060] The term “biological sample” encompasses a variety of sample types obtained from an organism or a cell line. The term encompasses blood and other liquid samples of biological origin, solid tissue samples, such as a biopsy specimen or tissue cultures or cells derived therefrom and the progeny thereof. The term includes samples that have been manipulated in any way after their procurement, such as by treatment with reagents, solubilization, or enrichment for certain components. The term includes a clinical sample, and includes cells in cell culture, cell supernatants, cell lysates, serum, plasma, biological fluids, and tissue samples.

[0061] The term “clinical well-being” as used herein, refers to a state or degree of clinical or physiological wellness or health of a patient. A clinician can evaluate a patient’s clinical wellbeing by physical examination or performing one or more tests or assays.

[0062] “Inhibitors,” “activators,” and “modulators” of expression or of activity are used to refer to inhibitory, activating, or modulating molecules, respectively, identified using in vitro and in vivo assays for expression or activity of a described target protein (or encoding polynucleotide), e.g., ligands, agonists, antagonists, and their homologs and mimetics. The term “modulator” includes inhibitors and activators. Inhibitors are agents that, e.g., inhibit expression or bind to, partially or totally block stimulation or protease inhibitor activity, decrease, prevent, delay activation, inactivate, desensitize, or down regulate the activity of the described target protein, e.g., antagonists. Activators are agents that, e.g., induce or activate the expression of a described target protein or bind to, stimulate, increase, open, activate, facilitate, enhance activation or protease inhibitor activity, sensitize or up regulate the activity of described target protein (or encoding polynucleotide), e.g., agonists. Modulators include naturally occurring and synthetic ligands, antagonists and agonists (e.g., small chemical molecules, antibodies and the like that function as either agonists or antagonists). Such assays for inhibitors and activators include, e.g., applying putative modulator compounds to cells expressing the described target protein and then determining the functional effects on the described target protein activity, as described above. Samples or assays comprising described target protein that are treated with a potential activator, inhibitor, or modulator are compared to control samples without the inhibitor, activator, or modulator to examine the extent of effect. Control samples (untreated with modulators) are assigned a relative activity value of 100%. Inhibition of a described target protein is achieved when the activity value relative to the control is about 80%, optionally 50% or 25, 10%, 5% or 1%. Activation of the described target protein is achieved when the activity value relative to the control is 110%, optionally 150%, optionally 200, 300%, 400%, 500%, or 1000-3000% or more higher.

[0063] The terms “administering,” “delivering,” and “introducing,” can be used interchangeably to indicate the introduction of a therapeutic composition or agent (e.g., compositions comprising one or more bacterial species as described herein) into the body of a subject. The therapeutic composition or agent can be administered through any appropriate means that results in the delivery of at least a portion of the composition or agent to a desired location in the subject such that the composition or agent retains its therapeutic capability. Useful methods of delivering the therapeutic include, but are not limited to, intravenous delivery, subcutaneous delivery, intradermal delivery, intracoronary delivery, intracardiac delivery, oral delivery, or any combination thereof. The term “administered continuously” refers to the continuous delivery of a therapeutic agent, e.g., compound, molecule, peptide, biologic, chemical, etc. over a 24-hour period.

[0064] The term “therapeutically effective amount” refers to an amount of therapeutic agent effective to treat at least one symptom of a disease or disorder in a subject. In other words, such an amount is sufficient to bring about a beneficial or desired clinical effect. The “therapeutically effective amount” of the agent for administration may vary based upon the desired activity, the diseased state of the subject being treated, the dosage form, method of administration, subject factors such as the subject's sex, genotype, weight and age, the underlying causes of the condition or disease to be treated, the route of administration and bioavailability, the persistence of the administered agent in the body, evidence of natriuresis and / or diuresis, the type of formulation, and the potency of the agent.

[0065] As used herein, the terms “pharmaceutically acceptable” or “pharmacologically acceptable” refer to compositions that do not substantially produce adverse reactions, e.g., toxic, allergic, or immunological reactions, when administered to a subject.

[0066] The terms “therapy,” “treatment,” and “amelioration” refer to any reduction in the severity of symptoms, e.g., of a neurodegenerative disorder or neuronal injury. As used herein, the terms “treat” and “prevent” are not intended to be absolute terms. Treatment can refer to any delay in onset, amelioration of symptoms, improvement in patient survival, improved cognitive function or coordination, increase in survival time or rate, etc. The effect of treatment can be compared to an individual or pool of individuals not receiving the treatment, or to the same patient prior to treatment or at a different time during treatment. In some aspects, the severity of disease is reduced by at least 10%, as compared, e.g., to the individual before administration or to a control individual not undergoing treatment. In some aspects the severity of disease is reduced by at least 25%, 50%, 75%, 80%, or 90%, or in some cases, no longer detectable using standard diagnostic techniques.

[0067] As used throughout, the terms “nucleic acid,” “nucleic acid sequence,” “oligonucleotide,” “nucleotides,” or other grammatical equivalents as used herein mean at least two nucleotides, either deoxyribonucleotides or ribonucleotides, or analogs thereof, covalently linked together. Polynucleotides are polymers of any length, including, e.g., 20, 50, 100, 200, 300, 500, 1000, 2000, 3000, 5000, 7000, 10,000, etc. A polynucleotide described herein generally contains phosphodiester bonds, although in some cases, nucleic acid analogs are included that may have at least one different linkage, e.g., phosphoramidate, phosphorothioate, phosphorodithioate, or O-methylphophoroamidite linkages, and peptide nucleic acid backbones and linkages. Mixtures of naturally occurring polynucleotides and analogs can be made; alternatively, mixtures of different polynucleotide analogs, and mixtures of naturally occurring polynucleotides and analogs may be made. The following are non- limiting examples of polynucleotides: a gene or gene fragment, exons, introns, messenger RNA (mRNA), transfer RNA, ribosomal RNA, ribozymes, cDNA, cRNA, recombinant polynucleotides, branched polynucleotides, plasmids, vectors, isolated DNA of any sequence, isolated RNA of any sequence, nucleic acid probes, and primers. A polynucleotide may comprise modified nucleotides, such as methylated nucleotides and nucleotide analogs. If present, modifications to the nucleotide structure may be imparted before or after assembly of the polymer. The sequence of nucleotides may be interrupted by non-nucleotide components. A polynucleotide may be further modified after polymerization, such as by conjugation with a labeling component. The term also includes both double- and single-stranded molecules. Unless otherwise specified or required, the term polynucleotide encompasses both the double-stranded form and each of two complementary single-stranded forms known or predicted to make up the double-stranded form. A polynucleotide is composed of a specific sequence of four nucleotide bases: adenine (A), cytosine (C), guanine (G), thymine (T), and uracil (U) for thymine when the polynucleotide is RNA. Thus, the term “polynucleotide sequence” is the alphabetical representation of a polynucleotide molecule. Unless otherwise indicated, a particular polynucleotide sequence also implicitly encompasses conservatively modified variants thereof (e.g., degenerate codon substitutions) and complementary sequences as well as the sequence explicitly indicated. Specifically, degenerate codon substitutions may be achieved by generating sequences in which the third position of one or more selected (or all) codons is substituted with mixed-base and / or deoxyinosine residues.

[0068] Unless otherwise indicated, a particular nucleic acid sequence also implicitly encompasses conservatively modified variants thereof, alleles, orthologs, SNPs, and complementary sequences as well as the sequence explicitly indicated.

[0069] As used herein, “cDNA” refers to a DNA sequence that is complementary to an RNA transcript in a cell. It is a man-made molecule. Typically, cDNA is made in vitro by an enzyme called reverse-transcriptase using RNA transcripts as templates.

[0070] As used herein with reference to the relationship between DNA, cDNA, cRNA, RNA, protein / peptides, and the like “corresponding to” or “encoding” (used interchangeably herein) refers to the underlying biological relationship between these different molecules. As such, one of skill in the art would understand that operatively “corresponding to” can direct them to determine the possible underlying and / or resulting sequences of other molecules given the sequence of any other molecule which has a similar biological relationship with these molecules. For example, from a DNA sequence an RNA sequence can be determined and from an RNA sequence a cDNA sequence can be determined.

[0071] As used herein, “gene” can refer to a hereditary unit corresponding to a sequence of DNA that occupies a specific location on a chromosome and that contains the genetic instruction for a characteristic(s) or trait(s) in an organism. The term gene can refer to translated and / or untranslated regions of a genome. “Gene” can refer to the specific sequence of DNA that is transcribed into an RNA transcript that can be translated into a polypeptide or be a catalytic RNA molecule, including but not limited to, tRNA, siRNA, piRNA, miRNA, long- non-coding RNA and shRNA.

[0072] The word "expression" or "expressed" as used herein in reference to a gene means the transcriptional and / or translational product of that gene. The level of expression of a DNA molecule in a cell may be determined on the basis of either the amount of corresponding mRNA that is present within the cell or the amount of protein encoded by that DNA produced by the cell (Sambrook et al., 1989 Molecular Cloning: A Laboratory Manual, 18.1-18.88).

[0073] The terms “polypeptide” and “peptide” are used interchangeably herein to refer to a polymer of amino acid residues in a single chain. The terms apply to amino acid polymers in which one or more amino acid residue is an artificial chemical mimetic of a corresponding naturally occurring amino acid, as well as to naturally occurring amino acid polymers and non- naturally occurring amino acid polymers. Amino acid polymers may comprise entirely L-amino acids, entirely D-amino acids, or a mixture of L- and D-amino acids. The term “protein” as used herein refers to either a polypeptide or a dimer ( / .e., two) or multimer ( / .e., three or more) of single chain polypeptides. The single chain polypeptides of a protein may be joined by a covalent bond, e.g., a disulfide bond, or non-covalent interactions. The terms “portion” and “fragment” are used interchangeably herein to refer to parts of a polypeptide, nucleic acid, or other molecular construct.

[0074] The term “amino acid” refers to naturally occurring and synthetic amino acids, as well as amino acid analogs and amino acid mimetics that function in a manner similar to the naturally occurring amino acids. Naturally occurring amino acids are those encoded by the genetic code, as well as those amino acids that are later modified, e.g., hydroxyproline, y- carboxyglutamate, and O-phosphoserine. Amino acid analogs refer to compounds that have the same basic chemical structure as a naturally occurring amino acid, i.e., an a carbon that is bound to a hydrogen, a carboxyl group, an amino group, and an R group, e.g., homoserine, norleucine, methionine sulfoxide, methionine methyl sulfonium. Such analogs have modified R groups (e.g., norleucine) or modified peptide backbones, but retain the same basic chemical structure as a naturally occurring amino acid. Amino acid mimetics refers to chemical compounds that have a structure that is different from the general chemical structure of an amino acid, but that functions in a manner similar to a naturally occurring amino acid.

[0075] Amino acids may be referred to herein by either their commonly known three letter symbols or by the one-letter symbols recommended by the IUPAC-IUB Biochemical Nomenclature Commission. Nucleotides, likewise, may be referred to by their commonly accepted single-letter codes. The amino acids in the polypeptides described herein can be any of the 20 naturally occurring amino acids, D-stereoisomers of the naturally occurring amino acids, unnatural amino acids and chemically modified amino acids. Unnatural amino acids (that is, those that are not naturally found in proteins) are also known in the art, as set forth in, for example, Zhang et al. “Protein engineering with unnatural amino acids,” Curr. Opin. Struct. Biol. 23(4): 581-87 (2013); Xie et al. “Adding amino acids to the genetic repertoire, "Curr. Opin. Chem. Biol. 9(6): 548-54 (2005); and all references cited therein. Beta and gamma amino acids are known in the art and are also contemplated herein as unnatural amino acids.

[0076] In accordance with standard nomenclature, amino acid residue sequences are denominated by either a three letter or a single letter code as indicated as follows, for example: Alanine (Ala, A), Arginine (Arg, R), Asparagine (Asn, N), Aspartic Acid (Asp, D), Cysteine (Cys, C), Glutamine (Gin, Q), Glutamic Acid (Glu, E), Glycine (Gly, G), Histidine (His, H), Isoleucine (lie, I), Leucine (Leu, L), Lysine (Lys, K), Methionine (Met, M), Phenylalanine (Phe, F), Proline (Pro, P), Serine (Ser, S), Threonine (Thr, T), Tryptophan (Trp, W), Tyrosine (Tyr, Y), and Valine (Vai, V). “Protein” and “Polypeptide” can refer to a molecule composed of one or more chains of amino acids in a specific order. The term protein is used interchangeable with “polypeptide.” The order is determined by the base sequence of nucleotides in the gene coding for the protein. Proteins can be involved in the structure, function, and regulation of various functions.

[0077] The term “identity” or “substantial identity,” as used in the context of a polynucleotide or polypeptide sequence described herein, refers to a sequence that has at least 60% sequence identity to a reference sequence. Alternatively, percent identity can be any integer from 60% to 100%. Exemplary embodiments include at least: 60%, 65%, 70%, 75%, 80%, 85%, 88%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%, as compared to a reference sequence using the programs described herein; preferably BLAST using standard parameters, as described below. One of skill will recognize that these values can be appropriately adjusted to determine corresponding identity of proteins encoded by two nucleotide sequences by taking into account codon degeneracy, amino acid similarity, reading frame positioning and the like.

[0078] For sequence comparison, typically one sequence acts as a reference sequence to which test sequences are compared. When using a sequence comparison algorithm, test and reference sequences are entered into a computer, subsequence coordinates are designated, if necessary, and sequence algorithm program parameters are designated. Default program parameters can be used, or alternative parameters can be designated. The sequence comparison algorithm then calculates the percent sequence identities for the test sequences relative to the reference sequence, based on the program parameters. A “comparison window,” as used herein, includes reference to a segment of any one of the number of contiguous positions selected from the group consisting of from 20 to 600, usually about 50 to about 200, more usually about 100 to about 150 in which a sequence may be compared to a reference sequence of the same number of contiguous positions after the two sequences are optimally aligned. Methods of alignment of sequences for comparison are well-known in the art. Optimal alignment of sequences for comparison may be conducted by the local homology algorithm of Smith & Waterman Add. APL. Math. 2:482 (1981), by the homology alignment algorithm of Needleman & Wunsch J. Mol. Biol. 48:443 (1970), by the search for similarity method of Pearson & Lipman Proc. Natl. Acad. Sci. (U.S.A.) 85: 2444 (1988), by computerized implementations of these algorithms (e.g., BLAST), or by manual alignment and visual inspection.

[0079] Algorithms that are suitable for determining percent sequence identity and sequence similarity are the BLAST and BLAST 2.0 algorithms, which are described in Altschul et al. (1990) J. Mol. Biol. 215: 403-10 and Altschul et al. (1977) Nucleic Acids Res. 25: 3389-402, respectively. Software for performing BLAST analyses is publicly available through the National Center for Biotechnology Information (NCBI) web site. The algorithm involves first identifying high scoring sequence pairs (HSPs) by identifying short words of length W in the query sequence, which either match or satisfy some positive-valued threshold score T when aligned with a word of the same length in a database sequence. T is referred to as the neighborhood word score threshold (Altschul et al. (1977)). These initial neighborhood word hits act as seeds for initiating searches to find longer HSPs containing them. The word hits are then extended in both directions along each sequence for as far as the cumulative alignment score can be increased. Cumulative scores are calculated using, for nucleotide sequences, the parameters M (reward score for a pair of matching residues; always >0) and N (penalty score for mismatching residues; always <0). For amino acid sequences, a scoring matrix is used to calculate the cumulative score. Extension of the word hits in each direction are halted when: the cumulative alignment score falls off by the quantity X from its maximum achieved value; the cumulative score goes to zero or below, due to the accumulation of one or more negative-scoring residue alignments; or the end of either sequence is reached. The BLAST algorithm parameters W, T, and X determine the sensitivity and speed of the alignment. The BLASTN program (for nucleotide sequences) uses as defaults a word size (W) of 28, an expectation (E) of 10, M=1 , N=-2, and a comparison of both strands. For amino acid sequences, the BLASTP program uses as defaults a word size (W) of 3, an expectation (E) of 10, and the BLOSUM62 scoring matrix (see Henikoff & Henikoff, Proc. Natl. Acad. Sci. USA 89:10915 (1989)).

[0080] The BLAST algorithm also performs a statistical analysis of the similarity between two sequences (see, e.g., Karlin & Altschul, Proc. Nat'l. Acad. Sci. USA 90:5873-5787 (1993)). One measure of similarity provided by the BLAST algorithm is the smallest sum probability (P(N)), which provides an indication of the probability by which a match between two nucleotide or amino acid sequences would occur by chance. For example, a nucleic acid is considered similar to a reference sequence if the smallest sum probability in a comparison of the test nucleic acid to the reference nucleic acid is less than about 0.01 , more preferably less than about 10'5, and most preferably less than about 1O'20.

[0081] The terms “bacterial population” or “bacterial consortium” as used herein refers to a homogeneous population of bacteria consisting of a single strain of a bacterial species or a heterogeneous population of bacteria consisting of at least two distinguishable strains of a single bacterial species or of a plurality of species.

[0082] The terms "co-administration" or "co-administered" as used herein refer to the administration of at least two compounds or agent(s) or therapies to a subject. In some embodiments, the co-administration of two or more agents / therapies is concurrent. In other embodiments, a first agent / therapy is administered prior to a second agent / therapy in this aspect, each component may be administered separately, but sufficiently close in time to provide the desired effect, in particular a beneficial, additive, or synergistic effect. Those of skill in the art understand that the formulations and / or routes of administration of the various agents / therapies used may vary. The appropriate dosage for co-administration can be readily determined by one skilled in the art. In some embodiments, when agents / therapies are coadministered, the respective agents / therapies are administered at lower dosages than appropriate for their administration alone. Thus, co-administration is especially desirable in embodiments where the co-administration of the agents / therapies lowers the requisite dosage of a known potentially harmful (e.g., toxic) agent(s).

[0083] The term "composition" as used herein refers to a product comprising the specified ingredients in the specified amounts, as well as any product which results, directly or indirectly, from combination of the specified ingredients in the specified amounts. Such a term in relation to a pharmaceutical composition is intended to encompass a product comprising the active ingredient(s), and the inert ingredient(s) that make up the carrier, as well as any product which results, directly or indirectly, from combination, complexation, or aggregation of any two or more of the ingredients, or from dissociation of one or more of the ingredients, or from other types of reactions or interactions of one or more of the ingredients. Accordingly, the pharmaceutical compositions of the present disclosure encompass any composition made by admixing a compound of the present disclosure and a pharmaceutically acceptable carrier.

[0084] When a compound of the present disclosure is used contemporaneously with one or more other drugs, a pharmaceutical composition containing such other drugs in addition to the compound of the present disclosure is contemplated. Accordingly, the pharmaceutical compositions of the present disclosure include those that also contain one or more other active ingredients, in addition to a compound of the present disclosure. The weight ratio of the compound of the present disclosure to the second active ingredient may be varied and will depend upon the effective dose of each ingredient. Generally, an effective dose of each will be used. Thus, for example, but not intended to be limiting, when a compound of the present disclosure is combined with another agent, the weight ratio of the compound of the present disclosure to the other agent will generally range from about 1000:1 to about 1 :1000, preferably about 200: 1 to about 1 :200. Combinations of a compound of the present disclosure and other active ingredients will generally also be within the aforementioned range, but in each case, an effective dose of each active ingredient should be used. In such combinations the compound of the present disclosure and other active agents may be administered separately or in conjunction. In addition, the administration of one element may be prior to, concurrent to, or subsequent to the administration of other agent(s).

[0085] A composition of the disclosure can be a liquid solution, suspension, emulsion or a powder. Various delivery systems are known and can be used to administer a composition of the disclosure, e.g. encapsulation in liposomes, microparticles, microcapsules, and the like, and then delivered to a patient by means of such as a nebulizer.

[0086] Compositions for administration may include sterile aqueous or non-aqueous solvents, such as water, isotonic saline, isotonic glucose solution, buffer solution, or other solvents conveniently used for parenteral administration of therapeutically active agents, stabilizers, buffers, or preservatives, e.g. antioxidants such as methylhydroxybenzoate or similar additives.

[0087] A composition of the disclosure may be sterilized by, for example, addition of sterilizing agents to the composition, irradiation of the composition, or heating the composition. Alternatively, the compounds or compositions of the present disclosure may be provided as sterile solid preparations e.g. lyophilized powder, which are readily dissolved in sterile solvent immediately prior to use.

[0088] After pharmaceutical compositions have been prepared, they can be placed in an appropriate container and labeled for treatment of an indicated condition. For administration of a composition of the disclosure, such labeling would include amount, frequency, and method of administration.

[0089] The term “freeze-dried (lyophilized) as used herein refers to a preparation of bacterial cells that have been initially frozen and the water content removed by vacuum.

[0090] The terms "inactivated probiotic" or "inactivated micro-organism" as used herein mean that the metabolic activity or reproductive ability of the organism has been reduced or destroyed. The inactivated organisms do, however, still retain, at the cellular level, at least a portion their biological glycol-protein and DNA / RNA structure. As used herein, the term "inactivated" is synonymous with "non-viable". The term "pharmaceutically acceptable carrier" as used herein refers to a diluent, adjuvant, excipient, or vehicle with which a probe of the disclosure is administered and which is approved by a regulatory agency of the Federal or a state government or listed in the U.S. Pharmacopeia or other generally recognized pharmacopeia for use in animals, and more particularly in humans. Such pharmaceutical carriers can be liquids, such as water and oils, including those of petroleum, animal, vegetable or synthetic origin, such as peanut oil, soybean oil, mineral oil, sesame oil and the like. The pharmaceutical carriers can be saline, gum acacia, gelatin, starch paste, talc, keratin, colloidal silica, urea, and the like. When administered to a patient, the probe and pharmaceutically acceptable carriers can be sterile. Water is a useful carrier when the probe is administered intravenously. Saline solutions and aqueous dextrose and glycerol solutions can also be employed as liquid carriers, particularly for injectable solutions. Suitable pharmaceutical carriers also include excipients such as glucose, lactose, sucrose, glycerol monostearate, sodium chloride, glycerol, propylene, glycol, water, ethanol and the like. The present compositions, if desired, can also contain minor amounts of wetting or emulsifying agents, or pH buffering agents. The present compositions advantageously may take the form of solutions, emulsion, sustained-release formulations, or any other form suitable for use.

[0091] The term "preventing" means to stop or hinder a disease, disorder, or symptom of a disease or condition through some action.

[0092] The term "probiotic" is recognized in the state of the art as a microorganism which, when administered in adequate amounts, confers a health benefit to the host. A probiotic microorganism must fulfil several requirements related to lack of toxicity, viability, adhesion and beneficial effects. These probiotic features are strain-dependent, even among bacteria of the same species. Therefore, it is important to find those strains that have a better performance in all probiotic requirements.

[0093] The term "reducing" means to diminish in extent, amount, or degree.

[0094] The term “therapeutic agent” as used herein refers to a therapeutic substance selected from a group consisting of, but not limited to, analgesics, anesthetics, anti-inflammatory agents, antiasthma agents, antibiotics (including penicillins), anticoagulants, antihistamines, antitussives, antihypertensive agents, antimuscarinic agents, antimycobacterial agents, antioxidant agents, antipyretics, immunosuppressants, immunostimulants, antiviral agents, bacteriostatic agents, bronchodilators, buffering agents, contrast media, corticosteroids, cough suppressants (expectorants and mucolytics), diagnostic agents, diagnostic imaging agents, free radical scavenging agents, growth factors, haemostatics, immunological agents, lipid regulating agents, muscle relaxants, proteins, peptides and polypeptides, prostaglandins, radio-pharmaceuticals, time release binders, anti-allergic agents, stimulants and anoretics, steroids, sympathomimetics, vasodilators, and xanthines. The terms "treating" or "treatment" as used herein refers to an alleviation of symptoms associated with a disorder or disease, or inhibition of further progression or worsening of those symptoms, or prevention or prophylaxis of the disease or disorder, or curing the disease or disorder. Similarly, as used herein, an "effective amount" or a "therapeutically effective amount" of a compound of the invention refers to an amount of the compound that alleviates, in whole or in part, symptoms associated with the disorder or condition, or halts or slows further progression or worsening of those symptoms or prevents or provides prophylaxis for the disorder or condition.

[0095] Discussion

[0096] Fecal Microbial Transplant (FMT) refers to the transfer of healthy donor fecal material to the intestine of a recipient to alter their gut microbiome, conferring a health benefit. The microbial ecosystem of the intestines is involved in several aspects of our physiology including educating the immune system, directly protecting from infection, regulating epithelial homeostasis, and augmenting host metabolism! FMT has been effective to varying degrees across numerous inflammatory, neurological, and metabolic disorders with connections to the gut microbiota. However, manipulation of the gut microbiome through FMT has proven most effective in treating recurrent Clostridioides difficile infection (rCDI). Unfortunately, in addition to positive effects, there have also been adverse health events including transfer of pathogens and inflammatory agents.

[0097] Described herein are systems, methods, and computer readable medium for, among other things, predictive platforms for novel microbial therapeutics. Such systems, methods, and computer readable medium can be utilized for identifying candidate microbiota for administration against a candidate bacterial infection in particular. In embodiments, described herein are systems, methods and computer readable media for, among other things, systems- ecology designed platforms that provide bacterial consortium candidates for treatment of severe bacterial infections. In embodiment, the bacterial infection is a severe Clostridioides difficile (C. diff) infection. In embodiments, described herein are systems, methods and computer readable medium for, among other things, potential bacterial therapeutics for treating C. diff infection. An aspect of the present disclosure also provides a system, method and computer readable medium for, among other things, algorithms / models that enabled the predictions of the specific combinations of bacteria to enable the therapeutic intervention.

[0098] Also described herein are compositions, pharmaceutical compositions, kits, and methods of administration relating to novel therapeutics for bacterial infections. Novel therapeutics can comprise one or more species of bacteria that can be administered to a subject. The subject can be one having or suspected of having a bacterial infection, for example, an antibiotic-resistant infection such as C. diff infection or recurring C. diff infection. The therapeutics described herein can comprise at least one bacterial strain. In embodiments, the at least one bacterial can be a strain of one or more of Bifidobacterium (for example, Bifidobacterium longum (B. long urn)), Escherichia (for example, Escherichia coli (E. coli), Roseburia (for example, Roseburia intestinalis (R. intestinalis)), or Streptococcus (for example, Streptococcus thermophilus (S. thermophilus)). The one or more bacterial strains (and bacteria of such strains) may be either a live organism capable of proliferation in the subject patient, a non-living strain such as, but not limited to, a heat-killed non-proliferative strain, or a combination of proliferative and non-proliferative populations of a strain. It is further contemplated that the compositions of the disclosure may comprise a plurality of strains of the same Lactobacillus species or a plurality of species, each of which may be proliferative or nonproliferative. In some embodiments of the compositions of the disclosure, additional bacterial species or strains thereof may be included with the one or more of Bifidobacterium (for example, Bifidobacterium longum (B. longum)), Escherichia (for example, Escherichia coli (E. coli), Roseburia (for example, Roseburia intestinalis (R. intestinalis)), or Streptococcus (for example, Streptococcus thermophilus (S. thermophilus)).

[0099] I. PREDICTIVE PLATFORMS

[0100] Described herein are methods, systems, platforms, and machine-readable media relating to platforms to identify novel bacterial populations for the treatment of various disorders, for example, a bacterial infection that is recurring or otherwise resistant to treatment {e.g., resistant to treatment with conventional small molecules (less than 2500 daltons) therapies). In embodiments, the methodologies and platforms are related to novel therapeutics for C. diff infection.

[0101] A. Methodologies

[0102] Described herein are methods of identifying candidate microbiota for administration against a candidate bacterial infection.

[0103] Methods as described herein can comprise determining, from provided successful bacterial administration metagenomic sequencing data and failed bacterial administration metagenomic sequencing data, taxonomic bacterial composition of one or more samples of a successful bacterial administration against the candidate bacterial infection and taxonomic composition one or more samples of a successful bacterial administration against a candidate bacterial infection.

[0104] In embodiments, the candidate bacterial infection is a Clostridioides difficile (C. diff) infection.

[0105] In embodiments, the microbiota administration is a fecal microbiota transplant.

[0106] In embodiments, the one or more successful administration samples and one or more failed administration samples are each fecal samples. In embodiments, successful administration is determined by a reduction in C. diff toxin level compared to before administration, increased survival, or both.

[0107] In embodiments, failed administration is determined by no change or increased C. diff toxin levels compared to before administration, reduced survival, or both.

[0108] In embodiments, methods as described herein can further comprise providing one or more samples of a successful bacterial administration against the candidate bacterial infection from one or more donors and providing one or more samples of a failed bacterial administration against the candidate bacterial infection from one or more donors. The samples can be fecal samples or fecal transplant samples.

[0109] In embodiments, methods as described herein can further comprise sequencing the metagenome of the one or more successful bacterial administration samples and the metagenome of the one or more failed bacterial administration samples. In embodiments, the metagenomic sequencing comprises next-gen sequencing.

[0110] Methods as described herein can comprise determining superorganism-level functional metabolic capacity from the successful bacterial administration metagenomic sequencing data and failed bacterial administration metagenomic sequencing data. In embodiments, the superorganism-level functional capacity can be determined by assembling contiguous genomic sequences from the metagenomic sequencing data; annotating gene content by assigning functional pathways to the assembled genomic sequences; mapping metagenomic reads to annotated genes; and differentiating functionalities of the mapped metagenomic reads.

[0111] Methods as described herein can comprise identifying metabolic pathways with differential metabolic capacities between the successful and failed administrations from the determined capacities.

[0112] Methods as described herein can comprise clustering the successful bacterial administration samples and failed bacterial administration samples based on the identified determined functional metabolic capacities.

[0113] Methods as described herein can comprise annotating the gene content of each cluster.

[0114] Methods as described herein can comprise quantifying the annotated gene content.

[0115] Methods as described herein can comprise segregating the quantified gene content based on administration success or failure.

[0116] Methods as described herein can comprise identifying genes enriched in one or more metabolic pathways from the segregated quantified gene content of the successful administration. Methods as described herein can comprise reconstructing the metabolism of the one or more metabolic pathways mapped onto one or more species from the determined taxonomic composition.

[0117] Methods as described herein can comprise segregating the reconstructed metabolism of the determined taxonomic composition into cooperative or competitive with the candidate bacterial infection. In embodiments, segregating the quantified gene content is using machine learning. Machine learning can be utilized and / or implemented according to methods known in the art. In embodiments, the machine learning is supervised, semi-supervised, unsupervised or reinforcement. In embodiments, the machine learning utilizes random forests, support vector machines. In embodiments, the machine learning utilizes classification, regression, and / or clustering.

[0118] In embodiments, reconstructing the metabolism and segregating the reconstructed metabolism is with genome-scale metabolic network reconstructions (GENREs). GENREs are comprehensive mathematical representations of metabolic reactions in a cell. GENREs include the mapping of gene annotation to reaction stoichiometry and capture the stoichiometry as a mathematical matrix. Additional information relating to GENREs can be found, for example, in Bauer, E. & Thiele, I. From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota. mSystems 3, e00209-17 (2018); Bauer, E. & Thiele, I. From metagenomic data to personalized in silico microbiotas: predicting dietary supplements for Crohn’s disease. NPJ Syst Biol Appl 4, 27 (2018); and Jenior, M. L. et al. Novel Drivers of Virulence in Clostridioides difficile Identified via Context-Specific Metabolic Network Analysis. mSystems 6, e0091921 (2021), the entire contents of all of three of which are incorporated by reference as if fully set forth herein.

[0119] Methods as described herein can comprise identifying one or more bacterial species for administration from the determined taxonomic composition having cooperative or competitive metabolism with the candidate bacterial infection.

[0120] In embodiments of methods as described herein, the one or more metabolic pathways are one or more of amino acid biosynthesis, combined galactose metabolism, amino sugar metabolism, nucleotide sugar metabolism, starch metabolism, or sucrose metabolism, individually or in any combination thereof.

[0121] In an embodiment, a method of identifying candidate microbiota for administration against a candidate bacterial infection, is described, comprising: determining, from provided successful bacterial administration metagenomic sequencing data and failed bacterial administration metagenomic sequencing data, taxonomic bacterial composition of one or more samples of a successful bacterial administration against the candidate bacterial infection and taxonomic composition one or more samples of a successful bacterial administration against a candidate bacterial infection; determining superorganism-level functional metabolic capacity from the successful bacterial administration metagenomic sequencing data and failed bacterial administration metagenomic sequencing data; identifying metabolic pathways with differential metabolic capacities between the successful and failed administrations from the determined capacities; clustering the successful bacterial administration samples and failed bacterial administration samples based on the identified determined functional metabolic capacities; annotating the gene content of each cluster; quantifying the annotated gene content; segregating the quantified gene content based on administration success or failure; identifying genes enriched in one or more metabolic pathways from the segregated quantified gene content of the successful administration; reconstructing the metabolism of the one or more metabolic pathways mapped onto one or more species from the determined taxonomic composition; segregating the reconstructed metabolism of the determined taxonomic composition into cooperative or competitive with the candidate bacterial infection; and identifying one or more bacterial species for administration from the determined taxonomic composition having cooperative or competitive metabolism with the candidate bacterial infection.

[0122] In an embodiment, a method of identifying candidate microbiota for administration against a candidate bacterial infection, is described, comprising: providing one or more samples of a successful bacterial administration against the candidate bacterial infection from one or more donors and providing one or more samples of a failed bacterial administration against the candidate bacterial infection from one or more donors; sequencing the metagenome of the one or more successful bacterial administration samples and the metagenome of the one or more failed bacterial administration samples; determining, from provided successful bacterial administration metagenomic sequencing data and failed bacterial administration metagenomic sequencing data, taxonomic bacterial composition of one or more samples of a successful bacterial administration against the candidate bacterial infection and taxonomic composition one or more samples of a successful bacterial administration against a candidate bacterial infection; determining superorganism-level functional metabolic capacity from the successful bacterial administration metagenomic sequencing data and failed bacterial administration metagenomic sequencing data; identifying metabolic pathways with differential metabolic capacities between the successful and failed administrations from the determined capacities; clustering the successful bacterial administration samples and failed bacterial administration samples based on the identified determined functional metabolic capacities; annotating the gene content of each cluster; quantifying the annotated gene content; segregating the quantified gene content based on administration success or failure; identifying genes enriched in one or more metabolic pathways from the segregated quantified gene content of the successful administration; reconstructing the metabolism of the one or more metabolic pathways mapped onto one or more species from the determined taxonomic composition; segregating the reconstructed metabolism of the determined taxonomic composition into cooperative or competitive with the candidate bacterial infection; and identifying one or more bacterial species for administration from the determined taxonomic composition having cooperative or competitive metabolism with the candidate bacterial infection.

[0123] B. Systems for Predictive Platforms

[0124] FIG. 6 is a block diagram illustrating an example of a machine upon which one or more aspects of embodiments of the present invention can be implemented (in particular, systems and machine-readable media that can perform the methods in (A) above).

[0125] Referring to FIG. 6, an aspect of an embodiment of the present invention includes, but not limited thereto, a system, method, and computer readable medium that provides: a) a systems-ecology designed bacterial consortium protects from severe Clostridioides difficile infection; b) bacterial therapeutics for treating C. diff infection; and / or c) algorithms / models that enabled the predictions of combinations of bacteria to enable the therapeutic intervention for bacterial infections generally ( / .e., bacterial infections other than C. diff , which illustrates a block diagram of an example machine 400 upon which one or more embodiments (e.g., discussed methodologies) can be implemented (e.g., run).

[0126] Examples of a machine 400 can include logic, one or more components, circuits (e.g., modules), or mechanisms. Circuits are tangible entities configured to perform certain operations. In an example, circuits can be arranged (e.g., internally or with respect to external entities such as other circuits) in a specified manner. In an example, one or more computer systems (e.g., a standalone, client or server computer system) or one or more hardware processors (processors) can be configured by software (e.g., instructions, an application portion, or an application) as a circuit that operates to perform certain operations as described herein. In an example, the software can reside (1) on a non-transitory machine readable medium or (2) in a transmission signal. In an example, the software, when executed by the underlying hardware of the circuit, causes the circuit to perform the certain operations.

[0127] In an example, a circuit can be implemented mechanically or electronically. For example, a circuit can comprise dedicated circuitry or logic that is specifically configured to perform one or more techniques such as discussed above, such as including a special-purpose processor, a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC). In an example, a circuit can comprise programmable logic (e.g., circuitry, as encompassed within a general-purpose processor or other programmable processor) that can be temporarily configured (e.g., by software) to perform the certain operations. It will be appreciated that the decision to implement a circuit mechanically (e.g., in dedicated and permanently configured circuitry), or in temporarily configured circuitry (e.g., configured by software) can be driven by cost and time considerations.

[0128] Accordingly, the term "circuit" is understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily (e.g., transitorily) configured (e.g., programmed) to operate in a specified manner or to perform specified operations. In an example, given a plurality of temporarily configured circuits, each of the circuits need not be configured or instantiated at any one instance in time. For example, where the circuits comprise a general-purpose processor configured via software, the general- purpose processor can be configured as respective different circuits at different times. Software can accordingly configure a processor, for example, to constitute a particular circuit at one instance of time and to constitute a different circuit at a different instance of time.

[0129] In an example, circuits can provide information to, and receive information from, other circuits. In this example, the circuits can be regarded as being communicatively coupled to one or more other circuits. Where multiple of such circuits exist contemporaneously, communications can be achieved through signal transmission (e.g., over appropriate circuits and buses) that connect the circuits. In embodiments in which multiple circuits are configured or instantiated at different times, communications between suet, circuits can be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple circuits have access. For example, one circuit can perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further circuit can then, at a later time, access the memory device to retrieve and process the stored output. In an example, circuits can be configured to initiate or receive communications with input or output devices and can operate on a resource (e.g., a collection of information).

[0130] The various operations of method examples described herein can be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors can constitute processor-implemented circuits that operate to perform one or more operations or functions. In an example, the circuits referred to herein can comprise processor-implemented circuits.

[0131] Similarly, the methods described herein can be at least partially processor-implemented. For example, at least some of the operations of a method can be performed by one or processors or processor-implemented circuits. The performance of certain of the operations can be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In an example, the processor or processors can be located in a single location (e.g., wittl in a tlome environment, an office environment or as a server farm), while in other examples the processors can be distributed across a number of locations. The one or more processors can also operate to support performance of the relevant operations in a "cloud computing" environment or as a "software as a service" (SaaS). For example, at least some of the operations can be performed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., Application Program Interfaces (APIs).)

[0132] Example embodiments (e.g., apparatus, systems, or methods) can be implemented in digital electronic circuitry, in computer hardware, in firmware, in software, or in any combination thereof. Example embodiments can be implemented using a computer program product (e.g., a computer program, tangibly embodied in an information carrier or in a machine readable medium, for execution by, or to control the operation of, data processing apparatus such as a programmable processor, a computer, or multiple computers).

[0133] A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a standalone program or as a software module, subroutine, or other unit suitable for use in a computing environment. A computer program can be deployed to be executed on one computer or on multiple computers at one site or distributed across multiple sites and interconnected by a communication network.

[0134] In an example, operations can be performed by one or more programmable processors executing a computer program to perform functions by operating on input data and generating output. Examples of method operations can also be performed by, and example apparatus can be implemented as, special purpose logic circuitry (e.g., a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC)).

[0135] The computing system can include clients and servers. A client and server are generally remote from each other and generally interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. In embodiments deploying a programmable computing system, it will be appreciated that both hardware and software architectures require consideration. Specifically, it will be appreciated that tt1e choice of whether to implement certain functionality in permanently configured tlardware (e.g., an ASIC), in temporarily configured hardware (e.g., a combination of software and a programmable processor), or a combination of permanently and temporarily configured hardware can be a design choice. Below are set out hardware (e.g., machine 400) and software architectures that can be deployed in example embodiments.

[0136] In an example, the machine 400 can operate as a standalone device or the machine 400 can be connected (e.g., networked) to other machines. In a networked deployment, the machine 400 can operate in the capacity of either a server or a client machine in server-client network environments. In an example, machine 400 can act as a peer mactline in peer-to-peer (or other distributed) network environments. The machine 400 can be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a mobile telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) specifying actions to be taken (e.g., performed) by the machine 400. Further, while only a single machine 400 is illustrated, the term "machine" shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

[0137] Example machine (e.g., computer system) 400 can include a processor 402 (e.g., a central processing unit (CPU), a graphics processing unit (GPU) or both), a main memory 404 and a static memory 406, some or all of which can communicate with each other via a bus 408. The machine 400 can furttler include a display unit 410, an alphanumeric input device 412 (e.g., a keyboard), and a user interface (Ul) navigation device 411 (e.g., a mouse). In an example, the display unit 810, input device 417 and Ul navigation device 414 can be a touch screen display. The mactl ine 400 can additionally include a storage device (e.g., drive unit) 416, a signal generation device 418 (e.g., a speaker), a network interface device 420, and one or more sensors 421, such as a global positioning system (GPS) sensor, compass, accelerometer, or other sensor.

[0138] The storage device 416 can include a machine readable medium 422 on which is stored one or more sets of data structures or instructions 424 (e.g., software) embodying or utilized by any one or more of the methodologies or functions described herein. The instructions 424 can also reside, completely or at least partially, within the main memory 404, within static memory 406, or within the processor 402 during execution thereof by the machine 400. In an example, one or any combination of the processor 402, the main memory 404, the static memory 406, or the storage device 416 can constitute machine readable media.

[0139] While the machine readable medium 422 is illustrated as a single medium, the term "machine readable medium" can include a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) that configured to store the one or more instructions 424. The term "machine readable medium" can also be taken to include any tangible medium that is capable of storing, encoding, or carrying instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present disclosure or ttlat is capable of storing, encoding or carrying data structures utilized by or associated with such instructions. The term "machine readable medium" can accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic media. Specific examples of mactline readable media can include non- volatile memory, including, by way of example, semiconductor memory devices (e.g., Electrically Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM)) and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

[0140] Tt1e instructions 424 can further be transmitted or received over a communications network 426 using a transmission medium via the network interface device 420 utilizing any one of a number of transfer protocols (e.g., frame relay, IP, TCP, UDP, HTTP, etc.). Example communication networks can include a local area network (LAN), a wide area network (WAN), a packet data network (e.g., the Internet), mobile telephone networks (e.g., cellular networks), Plain Old Telephone (POTS) networks, and wireless data networks (e.g.,

[0141] IEEE 802.11 standards family known as Wi-Fi®, IEEE 802.16 standards family known as WiMax®), peer-to-peer (P2P) networks, among ottlers. The term "transmission medium" shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible medium to facilitate communication of such software.

[0142] II. MICROBIAL COMPOSITIONS

[0143] Described herein are microbial compositions (also referred to herein as “populations” or “consortium / consortia”) comprising one or more bacterial strains (also referred to as “microbiota”). In embodiments, the one or more bacterial strains can comprise bacteria (also referred to herein as “micro-organism” or “micro-organisms”) that can be grampositive, nonmotile, branched anaerobic bacteria. In embodiments, the one or more bacterial strains can comprise bacteria that can be gram-negative, facultative anaerobic, rod-shaped, coliform bacteria. In embodiments, the one or more bacterial strains can comprise bacteria that can be gram-positive anaerobic bacteria. In embodiments, the one or more bacterial strains can comprise bacteria that can be gram-positive and facultatively anaerobic. Bacteria consortia as described herein comprise viable and metabolically active micro-organisms, which can be proliferative or non-proliferaive.

[0144] In embodiments, described herein are one or more bacteria that cooperatively share amino acids and carbohydrates with C. difficile. In embodiments, the shared amino acids comprise one or more of leucine, phenylalanine, glucose-1-phosphase, L-proline, ornithine, fumarate, or glucose-6-phosphate, individually or in any combination of any thereof.

[0145] In embodiments, microbial compositions as described herein can comprise one or more of Bifidobacterium (for example, Bifidobacterium longum (B. longum)), Escherichia (for example, Escherichia coli (E. coli), Roseburia (for example, Roseburia intestinalis (R. intestinalis)), or Streptococcus (for example, Streptococcus thermophilus (S. thermophilus)), individually or in any combination of any thereof.

[0146] In embodiments, compositions as described herein can comprise one or more of Bifidobacterium longum (B. longum), Escherichia coli (E. coli), Roseburia intestinalis (R. intestinalis), or Streptococcus thermophilus (S. thermophilus), individually or in any combination of any thereof.

[0147] In embodiments, compositions as described herein can comprise Bifidobacterium longum (B. longum), Escherichia coli (E. coli), Roseburia intestinalis (R. intestinalis), and Streptococcus thermophilus (S. thermophilus).

[0148] In embodiments, microbial compositions as described herein can consist essentially of one or more of Bifidobacterium (for example, Bifidobacterium longum (B. longum)), Escherichia (for example, Escherichia coli (E. coli), Roseburia (for example, Roseburia intestinalis (R. intestinalis)), or Streptococcus (for example, Streptococcus thermophilus (S. thermophilus)), individually or in any combination of any thereof.

[0149] In embodiments, compositions as described herein can consist essentially of one or more of Bifidobacterium longum (B. longum), Escherichia coli (E. coli), Roseburia intestinalis (R. intestinalis), or Streptococcus thermophilus (S. thermophilus), individually or in any combination of any thereof.

[0150] In embodiments, compositions as described herein can consist essentially of Bifidobacterium longum (B. longum), Escherichia coli (E. coli), Roseburia intestinalis (R. intestinalis), and Streptococcus thermophilus (S. thermophilus).

[0151] In embodiments, microbial compositions as described herein can consist of one or more of Bifidobacterium (for example, Bifidobacterium longum (B. longum)), Escherichia (for example, Escherichia coli (E. coli), Roseburia (for example, Roseburia intestinalis (R. intestinalis)), or Streptococcus (for example, Streptococcus thermophilus (S. thermophilus)), individually or in any combination of any thereof.

[0152] In embodiments, compositions as described herein can consist of one or more of Bifidobacterium longum (B. longum), Escherichia coli (E. coli), Roseburia intestinalis (R. intestinalis), or Streptococcus thermophilus (S. thermophilus), individually or in any combination of any thereof.

[0153] In embodiments, compositions as described herein can consist of Bifidobacterium longum (B. longum), Escherichia coli (E. coli), Roseburia intestinalis (R. intestinalis), and Streptococcus thermophilus (S. thermophilus).

[0154] In embodiments, the B. longum strain is ATCC 55813 B. longum. In embodiments, the E. coli strain is K12 E. coli. In embodiments, the R. intestinalis strain is DSM 14610 R. intestinalis. In embodiments, the S. thermophilus strain is LMD-9 S. thermophilus. Microbial compositions as described herein be compositions in which the abovereferenced bacterial strains are isolated. In embodiments, microbial compositions as described herein be compositions in which the above-referenced bacterial strains are enriched compared to any one or more other strains (i.e., other bacteria from other strains may be present in trace amounts or other amounts that do not affect the function of the bacteria intended to be administered to a subject).

[0155] In general, the compositions of the present disclosure can contain replicating or nonreplicating probiotic microorganisms in a therapeutically effective dose and / or in a prophylactic effective dose. In embodiments, such doses can include dosage ranges of: about 106to about 1011CFUs; about 106to about 107CFUs; about 106to about 108CFUs; about 106to about 109CFUs; about 106to about 1O10CFUs; about 1O10to about 1011CFUs; about 109to about 1011CFUs; about 108to about 1011CFUs; about 107to about 1011CFUs; about 107to about 108CFUs; about 107to about 109CFUs; about 107to about 1O10CFUs; about 108to about 109CFUs.

[0156] In prophylactic applications, compositions according to the present disclosure can be administered to a person susceptible to or otherwise at risk of a bacterial infection or other disorder in an amount that is sufficient to at least partially reduce the risk of that infection or disorder persisting or otherwise developing. Such an amount is defined to be "a prophylactic effective dose". Again, the precise amounts depend on a number of factors such as the subject’s state of health and weight. Those skilled in the art will be able to adjust the therapeutically effective dose and / or the prophylactic effective dose appropriately.

[0157] In terms of numerical amounts, the "short-time high temperature" treated nonreplicating micro-organisms may be present in the composition in an amount corresponding to between 104and 1012equivalent cfu / g of the dry composition. Obviously, non-replicating micro-organisms do not form colonies, consequently, this term is to be understood as the amount of non-replicating micro-organisms that is obtained from 104and 1012cfu / g replicating bacteria. This includes micro-organisms that are inactivated, non-viable or dead or present as fragments such as or cell wall or cytoplasmic compounds. In other words, the quantity of micro-organisms which the composition contains is expressed in terms of the colony forming ability (cfu) of that quantity of micro-organisms as if all the micro-organisms were alive irrespective of whether they are, in fact, non-replicating, such as inactivated or dead, fragmented or a mixture of any or all of these states.

[0158] The bacteria may be rendered non-replicating by any method that is known in the art. The technologies available today to render probiotic strains non-replicating are usually heattreatment, gamma-irradiation, UV light, or the use of chemical agents (formalin, paraformaldehyde). It may be convenient, to be able to heat treat the bacterial micro- organisms of the disclosure either together so that the micro-organisms retain or improve their beneficial properties.

[0159] Heat treatment may be carried out at least at 71.5 °C for at least 1 second. Long-term heat treatments or short-term heat treatments may also be used. Hence, for example, the heat treatment may be a high temperature treatment at about 71.5-150 °C for about 1-120 seconds. More preferred the micro-organisms may be subjected to a high temperature treatment at about 90-140 °C, for example 90-120 °C, for a short term of about 1-30 secs. This high temperature treatment renders the micro-organisms at least in part non-replicating. The high temperature treatment may be carried out at normal atmospheric pressure but may be also carried out under high pressure. Typical pressure ranges are from 1 to 50 bar, preferably from 1-10 bar, even more preferred from 2 to 5 bar. Obviously, it is preferred if the probiotics are heat treated in a medium that is either liquid or solid, when the heat is applied. An ideal pressure to be applied will therefore depend on the nature of the composition which the micro-organisms are provided in and on the temperature used. Depending on the nature and amount of the composition the micro-organisms are provided in and depending on the architecture of the heating apparatus used, the time of heat application may differ.

[0160] As set forth in Patent Cooperation Treaty Rule 13bis.3 (and U.S. Patent and Trademark Office Manual of Patent Examining Procedure § 1823.01), a deposit was made with the American Type Culture Collection (ATCC®) located at 10801 University Boulevard, Manassas, VA 20110 on [[this date]] and having an accession number [[this number]].

[0161] III. KITS AND PACKAGING

[0162] Described herein are kits comprising microbial compositions and pharmaceutical microbial compositions, in addition to containers for storage and / or use, and instructions for use. The kit can be a package which houses a container which contains compounds of the disclosure or formulations of the disclosure and also houses instructions for administering the compounds or formulations to a subject. The disclosure further relates to a commercial package comprising compounds of the disclosure or formulations of the disclosure together with instructions for simultaneous, separate or sequential use. In particular a label may include amount, frequency, and method of administration.

[0163] The disclosure also provides a pharmaceutical pack or kit comprising one or more containers filled with one or more of the ingredients of a composition of the disclosure to provide a therapeutic effect. Associated with such container(s) can be various written materials such as instructions for use, or a notice in the form prescribed by a governmental agency regulating the labeling, manufacture, use or sale of pharmaceuticals or biological products, which notice reflects approval by the agency of manufacture, use, or sale for human administration. The disclosure also relates to articles of manufacture and kits containing materials useful for treating a disease disclosed herein. An article of manufacture may comprise a container with a label. Examples of suitable containers include bottles, vials, and test tubes, or a delivery device such as a nebulizer, which may be formed from a variety of materials including glass and plastic. A container holds compounds of the disclosure or formulations of the disclosure which are effective for treating a disease disclosed herein. The label on the container indicates that the compounds of the disclosure or formulations of the disclosure are used for treating a disease disclosed herein and may also indicate directions for use. In aspects of the disclosure, a medicament or formulation in a container may comprise any of the medicaments or formulations disclosed herein.

[0164] The disclosure also contemplates kits comprising one or more of compounds of the disclosure. In aspects of the disclosure, a kit of the disclosure comprises a container described herein. In particular aspects, a kit of the disclosure comprises a container described herein and a second container comprising a buffer. A kit may additionally include other materials desirable from a commercial and user standpoint, including, without limitation, buffers, diluents, filters, needles, syringes, and package inserts with instructions for performing any methods disclosed herein (e.g., methods for treating a disease disclosed herein). A medicament or formulation in a kit of the disclosure may comprise any of the formulations or compositions disclosed herein.

[0165] The compositions ( / .e., those comprising, consisting essentially of, or consisting of miRNA and / or miRNA mimics described herein) can be utilized in the preparation of a kit. In some embodiments, kits are provided for carrying out any of the methods described herein. The kits of this disclosure may comprise a carrier container being compartmentalized to receive in close confinement one or more containers such as vials, tubes, and the like, each of the containers comprising one of the separate elements to be used in the methods.

[0166] In some instances, one of the containers may comprise a composition as described in this disclosure that is, or can be, detectably labeled. The kit may also have containers containing buffer(s) and / or a container comprising a reporter-means, such as a biotin-binding protein, such as avidin or streptavidin, bound to a reporter molecule, such as an enzymatic or fluorescent label. In some embodiments, the kit comprises separate containers containing compositions described herein and a detectable label.

[0167] A composition as described in this disclosure for use in treating a bacterial infection in subjects may be delivered in a pharmaceutical package or kit to doctors and cancer patients. Such packaging is intended to improve patient convenience and compliance with the treatment plan. Typically, the packaging comprises paper (cardboard) or plastic. In some embodiments, the kit or pharmaceutical package further comprises instructions for use (e.g., for administering according to a method as described herein). In some embodiments, a pharmaceutical package or kit comprises unit dose forms of a composition or components of compositions described herein. In some embodiments, the pharmaceutical package or kit further comprises unit dose forms of one or more of an additional therapeutic, for example, another medicament used for treatment of a disorder in a patient.

[0168] In one embodiment, the kit or pharmaceutical package comprises a composition as described herein in a defined, therapeutically effective dose in a single unit dosage form or as separate unit doses. The dose and form of the unit dose (e.g., tablet, capsule, immediate release, delayed release, etc.) can be any doses or forms as described herein.

[0169] In one embodiment, the kit or pharmaceutical package includes doses suitable for multiple days of administration, such as one week, one month, or three months.

[0170] In certain embodiments, kits are provided for producing a single-dose administration unit. In certain embodiments, kits containing single or multi-chambered pre-filled syringes are included. In certain embodiments, kits containing one or more containers of a formulation described in this disclosure are included.

[0171] IV. PHARMACEUTICAL COMPOSITIONS AND FORMULATIONS

[0172] Compositions comprising one or more bacterial strains and micro-organisms of the present disclosure and a pharmaceutically acceptable carrier are also provided. The compositions may further comprise a diluent, solubilizer, emulsifier, preservative, and / or adjuvant to be used with the methods disclosed herein.

[0173] In certain embodiments, acceptable formulation materials preferably are nontoxic to recipients at the dosages and concentrations employed. In certain embodiments, the formulation material(s) are for s.c. and / or I.V. administration. In certain embodiments, the pharmaceutical composition can contain formulation materials for modifying, maintaining or preserving, for example, the pH, osmolality, viscosity, clarity, color, isotonicity, odor, sterility, stability, rate of dissolution or release, adsorption or penetration of the composition. In certain embodiments, suitable formulation materials include, but are not limited to, amino acids (such as glycine, glutamine, asparagine, arginine or lysine); antimicrobials; antioxidants (such as ascorbic acid, sodium sulfite or sodium hydrogen- sulfite); buffers (such as borate, bicarbonate, Tris-HCI, citrates, phosphates or other organic acids); bulking agents (such as mannitol or glycine); chelating agents (such as ethylenediamine tetraacetic acid (EDTA)); complexing agents (such as caffeine, polyvinylpyrrolidone, beta-cyclodextrin or hydroxypropyl-beta- cyclodextrin); fillers; monosaccharides, disaccharides, and other carbohydrates (such as glucose, mannose or dextrins); proteins (such as serum albumin, gelatin or immunoglobulins); coloring, flavoring and diluting agents; emulsifying agents; hydrophilic polymers (such as polyvinylpyrrolidone); low molecular weight polypeptides; salt- forming counterions (such as sodium); preservatives (such as benzalkonium chloride, benzoic acid, salicylic acid, thimerosal, phenethyl alcohol, methylparaben, propylparaben, chlorhexidine, sorbic acid or hydrogen peroxide); solvents (such as glycerin, propylene glycol or polyethylene glycol); sugar alcohols (such as mannitol or sorbitol); suspending agents; surfactants or wetting agents (such as pluronics, PEG, sorbitan esters, polysorbates such as polysorbate 20, polysorbate 80, triton, tromethamine, lecithin, cholesterol, tyloxapal); stability enhancing agents (such as sucrose or sorbitol); tonicity enhancing agents (such as alkali metal halides, preferably sodium or potassium chloride, mannitol sorbitol); delivery vehicles; diluents; excipients and / or pharmaceutical adjuvants. (Allen (2012) Remington - The Science and Practice of Pharmacy, 22d Edition, Lloyd V, Allen, ed., The Pharmaceutical Press). In certain embodiments, the optimal pharmaceutical composition is determined by one skilled in the art depending upon, for example, the intended route of administration, delivery format and desired dosage. See, for example, Allen (2012) Remington - The Science and Practice of Pharmacy, 22d Edition, Lloyd V, Allen, ed., The Pharmaceutical Press.

[0174] In certain embodiments, the primary vehicle or carrier in a pharmaceutical composition can be either aqueous or non-aqueous in nature. For example, in certain embodiments, a suitable vehicle or carrier can be water for injection, physiological saline solution, possibly supplemented with other materials common in compositions for parenteral administration. In certain embodiments, the saline comprises isotonic phosphate-buffered saline. In certain embodiments, neutral buffered saline or saline mixed with serum albumin are further exemplary vehicles. In certain embodiments, pharmaceutical compositions comprise a pH controlling buffer such phosphate-buffered saline or acetate-buffered saline. In certain embodiments, a composition comprising micro-organisms described herein can be prepared for storage by mixing the selected composition having the desired degree of purity with optional formulation agents (see Allen (2012) Remington - The Science and Practice of Pharmacy, 22d Edition, Lloyd V, Allen, ed., The Pharmaceutical Press) in the form of a lyophilized cake or an aqueous solution. Further, in certain embodiments, a composition comprising micro-organisms described herein can be formulated as a lyophilizate using appropriate excipients. In some instances, appropriate excipients may include a cryopreservative, a bulking agent, a surfactant, or a combination of any thereof. Exemplary excipients include one or more of a polyol, a disaccharide, or a polysaccharide, such as, for example, mannitol, sorbitol, sucrose, trehalose, and dextran 40. In some instances, the cryopreservative may be sucrose or trehalose. In some instances, the bulking agent may be glycine or mannitol. In one example, the surfactant may be a polysorbate such as, for example, polysorbate-20 or polysorbate-80.

[0175] In certain embodiments, the pharmaceutical composition can be selected for parenteral delivery. In certain embodiments, the compositions can be selected for inhalation or for delivery through the digestive tract, such as orally. The preparation of such pharmaceutically acceptable compositions is within the ability of one skilled in the art.

[0176] In certain embodiments, the formulation components are present in concentrations that are acceptable to the site of administration. In certain embodiments, buffers are used to maintain the composition at physiological pH or at a slightly lower pH, typically within a pH range of from about 5 to about 8. For example, the pH may be 5.0, 5.1 , 5.2, 5.3, 5.4, 5.5, 5.6,

[0177] 5.7, 5.8, 5.9, 6.0, 6.1 , 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8. 6.9, 6.9, 7.0, 7.1 , 7.2, 7.3, 7.4, 7.5, 7.6,

[0178] 7.7, 7.8, 7.9, 8.0, 8.1 , 8.2, 8.3, 8.4, or 8.5. In some instances, the pH of the pharmaceutical composition may be in the range of 6.6-8.5 such as, for example, 7.0-8.5, 6.6-7.2, 6.8-7.2, 6.8-7.4, 7.2-7.8, 7.0-7.5, 7.5-8.0, 7.2-8.2, 7.6-8.5, or 7.8-8.3. In some instances, the pH of the pharmaceutical composition may be in the range of 5.5-7.5 such as, for example, 5.5-5.8, 5.5- 6.0, 5.7-6.2, 5.8-6.5, 6.0-6.5, 6.2-6.8, 6.5-7.0, 6.8-7.2, or 6.8-7.5. In some instances, the pH of the pharmaceutical composition may be in the range of 4.0-5.5 such as, for example, 4.0- 4.3, 4.0-4.5, 4.2-4.8, 4.5-4.8, 4.5-5.0, 4.8-5.2, or 5.0-5.5. In an embodiment, the pH is 7.2.

[0179] In certain embodiments when parenteral administration is contemplated, a therapeutic composition can be in the form of a pyrogen-free, parenterally acceptable aqueous solution comprising micro-organisms described herein in a pharmaceutically acceptable vehicle. In certain embodiments, a vehicle for parenteral injection is sterile distilled water in which micro-organisms compositions described herein are formulated as a sterile, isotonic solution and properly preserved. In certain embodiments, the preparation can involve the formulation of the desired molecule with an agent, such as injectable microspheres, bio- erodible particles, polymeric compounds (such as polylactic acid or polyglycolic acid), beads or liposomes, that can provide for the controlled or sustained release of the product which can then be delivered via a depot injection. In certain embodiments, hyaluronic acid can also be used, and can have the effect of promoting sustained duration in the circulation. In certain embodiments, implantable drug delivery devices can be used to introduce the desired molecule.

[0180] In certain embodiments, it is contemplated that formulations can be administered orally. In certain embodiments, micro-organisms described herein that are administered in this fashion can be formulated with or without carriers customarily used in compounding solid dosage forms, such as tablets and capsules. In certain embodiments, a capsule can be designed to release the active portion of the formulation at the point in the gastrointestinal tract when bioavailability is maximized, and pre-systemic degradation is minimized. In certain embodiments, diluents, flavorings, low melting point waxes, vegetable oils, lubricants, suspending agents, tablet disintegrating agents, and binders can also be employed.

[0181] The pharmaceutical composition to be used for in vivo administration typically is sterile. In certain embodiments, sterilization is accomplished by filtration through sterile filtration membranes. In certain embodiments, where the composition is lyophilized, sterilization using this method can be conducted either prior to or following lyophilization and reconstitution. In certain embodiments, the composition for parenteral administration can be stored in lyophilized form or in a solution. In certain embodiments, parenteral compositions generally are placed into a container having a sterile access port, for example, an intravenous solution bag or vial having a stopper pierceable by a hypodermic injection needle.

[0182] In certain embodiments, once the pharmaceutical composition has been formulated, it can be stored in sterile vials as a solution, suspension, gel, emulsion, solid, or as a dehydrated or lyophilized powder. In certain embodiments, such formulations can be stored either in a ready-to-use form or in a form (e.g., lyophilized) that is reconstituted prior to administration.

[0183] In certain embodiments, kits are provided for producing a single-dose administration unit. In certain embodiments, the kit can contain both a first container having a dried protein and a second container having an aqueous formulation. In certain embodiments, kits containing single and multi-chambered pre-filled syringes are included.

[0184] In certain embodiments, the effective amount of a pharmaceutical composition comprising micro-organisms described herein to be employed therapeutically depends, for example, upon the therapeutic context and objectives. One skilled in the art will appreciate that the appropriate dosage levels for treatment, according to certain embodiments, vary depending, in part, upon the molecule delivered, the indication for which a one or more miRNAs, miRNA mimics, or both is being used, the route of administration, and the size (body weight, body surface or organ size) and / or condition (the age and general health) of the patient. The clinician can titer the dosage and modify the route of administration to obtain the optimal therapeutic effect.

[0185] The clinician also selects the frequency of dosing, taking into account the pharmacokinetic parameters of the micro-organisms described herein in the formulation used. In certain embodiments, a clinician administers the composition until a dosage is reached that achieves the desired effect. In certain embodiments, the composition can therefore be administered as a single dose or as two or more doses (which may or may not contain the same amount of the desired molecule) over time, or as a continuous infusion via, for example, an implantation device or catheter. Further refinement of the appropriate dosage is routinely made by those of ordinary skill in the art and is within the ambit of tasks routinely performed by them. In certain embodiments, appropriate dosages can be ascertained through use of appropriate dose-response data.

[0186] In certain embodiments, the route of administration of the pharmaceutical composition is in accord with known methods, e.g., orally, through injection by intravenous, intraperitoneal, intracerebral (intra-parenchymal), intracerebral, intraventricular, intramuscular, subcutaneously, intra-ocular, intraarterial, intraportal, or intralesional routes; by sustained release systems or by implantation devices. In certain embodiments, the compositions can be administered by bolus injection or continuously by infusion, or by implantation device. In certain embodiments, individual elements of a combination therapy may be administered by different routes.

[0187] In certain embodiments, the composition can be administered locally, e.g., during surgery or topically. Optionally local administration is via implantation of a membrane, sponge, or another appropriate material onto which the desired molecule has been absorbed or encapsulated. In certain embodiments, where an implantation device is used, the device can be implanted into any suitable tissue or organ, and delivery of the desired molecule can be via diffusion, timed-release bolus, or continuous administration.

[0188] V. M ETHODS OF USE AND TREATM ENT

[0189] As described herein, the present disclosure provides a method of treating a subject with a disorder characterized by a bacterial infection, particularly a recurring or treatmentresistant infection, ( / .e., a subject “in need thereof’), comprising administering to the subject a therapeutically effective amount of compositions ( / .e., those comprising, consisting essentially of, or consisting of micro-organisms described herein) according to the present disclosure. In some embodiments, the subject has or is determined to have a C. diff infection (or otherwise suspected of having a C. diff infection).

[0190] The compositions described herein are useful in, inter alia, methods for treating a bacterial infection in a subject. In some embodiments, the subject has or is suspected to have a bacterial infection. In some embodiments, the subject is diagnosed with a bacterial infection. In some embodiments, the subject is a human that is suspected of having a bacterial infection.

[0191] In embodiments, a disorder or bacterial infection as described herein is a C. diff or recurring C. diff infection.

[0192] The compositions can be administered to a subject, e.g., a human subject, using a variety of methods that depend, in part, on the route of administration. The route can be, e.g., intravenous injection or infusion (IV), subcutaneous injection (SC), intraperitoneal (IP) injection, intramuscular injection (IM), intradermal injection (ID), subcutaneous, transdermal, intracavity, oral, or intrathecal injection (IT). The injection can be in a bolus or a continuous infusion. Techniques for preparing injectate or infusate delivery systems containing antibodies are well known to those of skill in the art. Generally, such systems should utilize components which will not significantly impair the biological properties of the antibodies, such as the paratope binding capacity (see, for example, Remington's Pharmaceutical Sciences, 18th edition, 1990, Mack Publishing). Those of skill in the art can readily determine the various parameters and conditions for producing antibody injectates or infusates without resort to undue experimentation. In some embodiments, compositions as described herein can be therapeutically delivered to a subject by way of colonic or oral administration.

[0193] Treating or treatment of any disease or disorder refers to ameliorating a disease or disorder that exists in a subject or a symptom thereof, in particular, ameliorating symptoms of bacterial infection or bacterial toxin levels. The term ameliorating refers to any therapeutically beneficial result in the treatment of a disease state, e.g., a reduction in bacterial toxin levels or improved survival.

[0194] Thus, treating or treatment includes ameliorating at least one parameter or symptom. Treating or treatment includes modulating the disease or disorder, either physically (e.g., stabilization of a discernible symptom) or physiologically (e.g., stabilization of a physical parameter) or both. Thus, in the disclosed methods, treatment can refer to a 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% reduction in the severity of an established disease or condition or symptom of the disease or condition. For example, a method for treating a bacterial infection in a subject by administering a composition as described in this disclosure is considered to be a treatment or therapeutic, for example, if there is a 10% improvement according to the measured or observed parameter in a subject as compared to a control. Thus, the reduction can be a 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, or more (or any percent improvement in between 10% and 100%) as compared to native or control levels. It is understood that treatment does not necessarily refer to a cure or complete ablation of the disease, condition, or symptoms of the disease or condition.

[0195] Described herein are therapeutically effective amounts as defined previously. A therapeutically effective amount is not, however, a dosage so large as to cause adverse side effects. A suitable dose capable of ameliorating a bacterial infection in a subject, can depend on a variety of factors including the particular construct used and whether it is used concomitantly with other therapeutic agents. Generally, a therapeutically effective amount may vary with the subject’s age, condition, and sex, as well as the extent of the disease in the subject and can be determined by one of skill in the art. Other factors can include, e.g., other medical disorders concurrently or previously affecting the subject, the general health of the subject, the genetic disposition of the subject, diet, time of administration, rate of excretion, drug combination, and any other additional therapeutics that are administered to the subject. It should also be understood that a specific dosage and treatment regimen for any particular subject also depends upon the judgment of the treating medical practitioner (e.g., doctor or nurse). A therapeutically effective amount is also one in which any toxic or detrimental effects of the composition are outweighed by the therapeutically beneficial effects. The dosage of the therapeutically effective amount may be adjusted by the individual physician or veterinarian in the event of any complication. A pharmaceutical composition can include a therapeutically effective amount of micro-organisms described herein. Such effective amounts can be readily determined by one of ordinary skill in the art as described above, embodiments are given throughout the present disclosure (in particular relating to colony-forming units or CFUs).

[0196] Suitable human doses of any of the micro-organisms described herein can further be evaluated in, e.g., Phase I dose escalation studies. See, e.g., van Gurp et al. (2008) Am J Transplantation 8(8):1711-1718; Hanouska et al. (2007) Clin Cancer Res 13(2, part 1):523- 531 ; and Hetherington et al. (2006) Antimicrobial Agents and Chemotherapy 50(10): 3499- 3500.

[0197] Toxicity and therapeutic efficacy of such micro-organisms can be determined by known pharmaceutical procedures in cell cultures or experimental animals (e.g., animal models of any of the cancers described herein). These procedures can be used, e.g., for determining the LD5o (the dose lethal to 50% of the population) and the ED50 (the dose therapeutically effective in 50% of the population). The dose ratio between toxic and therapeutic effects is the therapeutic index, and it can be expressed as the ratio LD50 / ED50. A compositions comprising micro-organisms that exhibits a high therapeutic index is preferred. While constructs that exhibit toxic side effects may be used, care should be taken to design a delivery system that targets such constructs to the site of affected tissue and to minimize potential damage to normal cells and, thereby, reduce side effects.

[0198] The data obtained from the cell culture assays and animal studies can be used in formulating a range of dosage for use in humans. The dosage of a micro-organism lies generally within a range of circulating concentrations of the miRNAs or miRNA mimics that include the ED50 with little or no toxicity. The dosage may vary within this range depending upon the dosage form employed and the route of administration utilized. For micro-organisms herein, the therapeutically effective dose can be estimated initially from cell culture assays. A dose can be formulated in animal models to achieve a circulating plasma concentration range that includes the EC50 ( / .©., the concentration of the construct - e.g., antibody - which achieves a half-maximal inhibition of symptoms) as determined in cell culture. Such information can be used to more accurately determine useful doses in humans. Levels in plasma may be measured, for example, by high performance liquid chromatography. In some embodiments, e.g., where local administration is desired, cell culture or animal models can be used to determine a dose required to achieve a therapeutically effective concentration within the local site.

[0199] In some embodiments, a composition or component of a composition described herein (i.e., one or more bacterial strains comprising micro-organisms) can be administered to a subject as a monotherapy. Alternatively, the composition or component of a composition described herein can be administered in conjunction with other therapies for the bacterial infection (combination therapy). For example, the composition can be administered to a subject at the same time, prior to, or after, a second therapy. In some embodiments, the composition or component of a composition described herein, and the one or more additional active agents are administered at the same time. Optionally, the composition or component of a composition described herein is administered first in time and the one or more additional active agents are administered second in time. In some embodiments, the one or more additional active agents are administered first in time and the micro-organism composition or component of a composition described herein is administered second in time. Optionally, the composition or component of a composition described herein, and the one or more additional agents are administered simultaneously in the same or different routes.

[0200] A composition as described herein can replace or augment a previously or currently administered therapy, such as previously prescribed antibiotic.

[0201] Monitoring a subject (e.g., a human patient) for an improvement of symptoms of bacterial infection, as defined herein, means evaluating the subject for a change in a given parameter or symptom exhibited by the subject by a clinician in a social setting or self-reporting by the patient. In some embodiments, the evaluation is performed at least one (1) hour, e.g., at least 2, 4, 6, 8, 12, 24, or 48 hours, or at least 1 day, 2 days, 4 days, 10 days, 13 days, 20 days or more, or at least 1 week, 2 weeks, 4 weeks, 10 weeks, 13 weeks, 20 weeks or more, after an administration. The subject can be evaluated in one or more of the following periods: prior to beginning of treatment; during the treatment; or after one or more elements of the treatment have been administered. Evaluation can include evaluating the need for further treatment, e.g., evaluating whether a dosage, frequency of administration, or duration of treatment should be altered. It can also include evaluating the need to add or drop a selected therapeutic modality.

[0202] In certain embodiments, the effective amount of a pharmaceutical composition comprising one or more micro-organisms of the present disclosure to be employed therapeutically depends, for example, upon the therapeutic context and objectives. One skilled in the art will appreciate that the appropriate dosage levels for treatment, according to certain embodiments, vary depending, in part, upon the molecule delivered, the indication for which a micro-organism is being used, the route of administration, and the size (body weight, body surface or organ size) and / or condition (the age and general health) of the patient. The clinician can titer the dosage and modify the route of administration to obtain the optimal therapeutic effect.

[0203] The clinician also selects the frequency of dosing, taking into account the pharmacokinetic parameters of the active components in the formulation used. Such pharmacokinetic parameters are well known in the art, i.e., the rate of absorption, bioavailability, metabolism, clearance, and the like (see, e.g., Hidalgo-Aragones (1996) J. Steroid Biochem. Mol. Biol. 58:611-617; Groning (1996) Pharmazie 51 :337-341 ; Fotherby (1996) Contraception 54:59-69; Johnson (1995) J. Pharm. Sci. 84:1144-1146; Rohatagi (1995) Pharmazie 50:610-613; Brophy (1983) Eur. J. Clin. Pharmacol. 24:103-108; the latest Remington's, supra). In certain embodiments, a clinician administers the composition until a dosage is reached that achieves the desired effect. In certain embodiments, the composition can therefore be administered as a single dose or as two or more doses (which may or may not contain the same amount of the desired molecule) over time, or as a continuous infusion via, for example, an implantation device or catheter. Further refinement of the appropriate dosage is routinely made by those of ordinary skill in the art and is within the ambit of tasks routinely performed by them. In certain embodiments, appropriate dosages can be ascertained through use of appropriate dose-response data.

[0204] In some cases, the dosage (of the active components] or compositions as described herein) ranges from a therapeutically-effective amount (or prophylactically-effecitve amount) of about 106to about 1011CFUs; about 106to about 107CFUs; about 106to about 108CFUs; about 106to about 109CFUs; about 106to about 1010CFUs; about 1010to about 1011CFUs; about 109to about 1011CFUs; about 108to about 1011CFUs; about 107to about 1011CFUs; about 107to about 108CFUs; about 107to about 109CFUs; about 107to about 1010CFUs; about 108to about 109CFUs. In certain examples, the compositions thereof can be administered once every other day at least four times. An exemplary treatment regime may include administration once per day, once per week, twice a week, once every two weeks, once every three weeks, once every four weeks, once a month, once every 3 months, or once every three to 6 months. In some cases, the treatment comprises administering a composition according to one of the aforementioned dosing regimens for a first period and another of the aforementioned dosing regimens for a second period. In some cases, the treatment discontinues for a period of time before the same or a different dosing regimen resumes. For example, a patient may be on a dosing regimen for two weeks, off for a week, on for another two weeks, and so on.

[0205] While embodiments of the present disclosure are described in connection with the Examples and the corresponding text and figures, there is no intent to limit the disclosure to the embodiments in these descriptions. On the contrary, the intent is to cover all alternatives, modifications, and equivalents included within the spirit and scope of embodiments of the present disclosure.

[0206] Other features, objects, and advantages of the present invention are apparent in the description that follows. It should be understood, however, that the description, while exemplifying certain embodiments of the present invention, is given by way of illustration only, not limitation. Various changes and modifications within the scope of the invention will become apparent to those skilled in the art from the detailed description. VI. EXAMPLES

[0207] Now having described the embodiments of the disclosure, in general, the examples describe some additional embodiments. While embodiments of the present disclosure are described in connection with the example and the corresponding text and figures, there is no intent to limit embodiments of the disclosure to these descriptions. On the contrary, the intent is to cover all alternatives, modifications, and equivalents included within the spirit and scope of embodiments of the present disclosure.

[0208] The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to perform the methods and use the compositions and compounds disclosed and claimed herein. Efforts have been made to ensure accuracy with respect to numbers (e.g., amounts, temperature, etc.), but some errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, temperature is in °C, and pressure is in atmosphere. Standard temperature and pressure are defined as 25 °C and 1 atmosphere.

[0209] EXAMPLE 1 :

[0210] A. Introduction

[0211] GDI is the most frequent hospital-acquired infection in the United States and Europe4- 6. Antibiotics are a major risk factor for contracting GDI, and many groups have shown that antibiotic treatment disrupts the gastrointestinal microbiota, altering host immunity, enabling colonization by C. difficile, and also increase the likelihood of recurrence7-9. FMT has been extremely effective for quickly resolving >90% of rCDI cases after a single infusion underscoring the importance of the gut microbial community in this infectionlO. Metabolomic analyses of samples taken from FMT recipients revealed significant shifts in concentration of C. difficile growth substrates as well as germination signals including bile acidsl 1. Additionally, it has also been shown that access to simple carbohydrates and fermentable amino acids downregulates C. difficile virulence expression12-14. Together, these findings support the hypothesis that bacterial co-metabolism is important to the mechanism of successful FMT and that microbial community members may possess cross-feeding metabolic interactions with C. difficile that lead to symptom resolution. This hypothesis is largely contrary to efforts where the prevailing theory has been that competition for nutrients is the primary mechanism behind microbe-mediated GDI resolution15.

[0212] Systems biology approaches have been effective for predicting specific mechanisms in complex biological phenotypes. Culture-based approaches have identified resident bacterial members of the murine microbiota that directly impact survival during GDI in gnotobiotic mice16. One set of computational tools for understanding metabolism within systems biology are genome-scale metabolic network reconstructions (GENREs). GENREs have recently been utilized with metagenomic sequencing from Crohn’s disease patients to uncover metabolic interactions between microbes that may influence diseasei 7, 18. Recently, new GENREs for C. difficile were generated by the inventors to identify previously unappreciated metabolic links to virulence19. Since rCDI is caused by a single organism, and susceptibility is strongly associated with the gut microbiome, rCDI presents a unique opportunity for development of defined consortia based on metabolic pathways as replacement for FMT.

[0213] In embodiments as described herein are combined pipelines of in silico, in vitro, and in vivo methods to design and test a targeted consortia of bacterial species that metabolically interact with bacteria (for example, C. diff) during infection. By performing deep metagenomic sequencing on human FMT donor samples associated with both successful and failed resolution of rCDI, amino acid metabolism pathways found that were more predictive than species abundances in successful FMT. Isolating those metagenome-assembled genomes (MAGs) enriched for this functionality, 26 MAGs were identified for candidate probiotics which were used to generate GENREs to simulate both competitive and cooperative metabolic interactions with C. difficile. This analysis revealed that potential probiotic species with the greatest impact on C. difficile GENRE growth most frequently shared or competed for amino acids, which we subsequently validated in vitro. These results led to the creation of two four- member bacterial consortia that favored either high levels of metabolic cooperation or competition with C. difficile. The effect of each consortium was tested in an animal model of GDI. Administration of the cooperative consortium led to survival of all animals, while animals in both the competitive consortium and control groups succumbed to the infection. It was found that rather than diminishing pathogen burden, treatment with the cooperative consortia significantly decreased C. difficile toxin levels, increased community diversity, and increased eosinophil abundance. These findings represent a paradigm shift in the thinking behind mechanisms of FMT efficacy; namely, that metabolic cooperation with C. difficile to downregulate virulence during healthy community recovery may outweigh the importance of outcompeting the pathogen for nutrients. This is the first instance that a computationally selected and designed live biotherapeutic, leveraging sequencing data from patient samples, has been created and shown efficacy in a pre-clinical animal model of disease.

[0214] B. Results

[0215] Metagenomics from Successful FMT Supports the Importance of Metabolic Interactions with C. diff

[0216] To profile the bacterial taxa and metabolic pathways that we predicted would be overrepresented in successful FMT, we deeply sequenced metagenomes from a unique FMT donor cohort from a recent clinical study at the University of Virginia20. A total of 119 patients with confirmed rCDI were treated with FMT and followed to determine efficacy of the therapy. A failed FMT was defined as recurrence of diarrhea with a positive stool ELISA for C. difficile toxin or positive tcdB PCR within three months of FMT. Among the donor samples, we selected three individuals based on dissimilar rates of successful rCDI resolution across recipients (FIG. 1A). Donor A had a donation pool of 33 samples which were associated with a 90.9% success rate across patient recipients (30 / 33), while donors B and C had success rates of 53.3% (16 / 30) and 57.1 % (8 / 14) respectively. From each donor, four samples were chosen which were reflective of that donor’s overall success rate, were separate donations, and went to a distinct recipient. From the 12 samples, shotgun metagenomic sequencing resulted in 158 million curated reads per sample (Table S1 of U.S. Provisional Patent Application Serial No. 63 / 517,567 filed on August 3, 2023, the contents of which incorporated by reference as if fully set forth herein). This study design allowed for partial control for within individual variation among the donors as well as recipient-specific effects that may have impacted FMT efficacy. By focusing downstream analyses on donor A versus donors B & C combined, we sought to identify those microbial features that most associated with consistent successful FMT.

[0217] To assess differences in microbial taxonomic composition among the donor metagenomes, we employed MetaPhlAn221 using the default settings. Through this analysis we found a dominance of Bacillota (formerly Firmicutes) across all the donors, with Clostridiaceae being enriched relative to Ruminococcaceae in donor A samples (high-success FMT) compared to those from donors B & C (low-success FMT) (FIG. 1B). There also was relatively little difference in alpha-diversity between the grouping (FIG. 8A & 8B). Next, we sought to determine superorganism-level functional capacity. To accomplish this goal, we first performed a de novo assembly of contiguous genomic sequences (contigs) and then annotated gene content according to KEGG pathways. To measure the differential abundances of each pathway across donor groups we mapped metagenomic reads to annotated genes from each sample. Supervised machine learning was applied to these data to identify the functionalities that best differentiated the microbiomes. Comparing the donor A samples against donors B & C samples, it was revealed that glycosaminoglycan, fructose, mannose, arginine, and proline metabolism discriminated between donors and were significantly overrepresented in donor A (high-success FMT) samples (error rate: 8.33%) (FIG. 1C). Similarly, while achieving a lower overall accuracy, comparison of all successful outcome- associated samples against the FMT failure highlighted arginine & proline metabolism as well as glycosaminoglycan degradation as more abundant in communities associated with successful FMT (FIG. 1D). Since our a priori prediction was that metabolic interaction(s) with C. difficile are important for successful FMT, as a control, we performed the same analysis for non-metabolic pathway gene abundances but found substantially reduced ability to discriminate groups in either comparison (FIGs. 8C & 8D). Ultimately the metabolic pathway abundances were more informative than analyses at the taxonomic level in defining traits of successful FMT thus supporting our hypothesis that FMT functions via metabolism rather than by the presence of specific species. However, the metabolic pathways identified in this analysis do not denote directionality for flow of metabolites leaving us unable to determine if identified pathways represent competition or cross-feeding with C. difficile.

[0218] To validate the observations from our single-site clinical study, we examined two 147 publicly available datasets of 16S rRNA gene sequencing of samples across multiple donors in well-controlled, single-site studies of FMT efficacy22,23. Across both studies, successful clinical outcome was achieved in 79.8% of patients (71 / 89). Lachnospirales were largely the dominant taxa across donor samples (FIG. 7A) and was primarily composed of the genus Blautia (FIG. 7B), which has been associated with increased consumption of amino acids with additional probiotic properties24 and reduced abundance in GDI patient cohorts25. To explore possible differences in representation of metabolic pathways we assessed the imputed metagenomic content from ASV abundances using PICRUSt26. Results show a high abundance of genes involved in amino acid biosynthesis in successful FMT samples, supporting nutrient cross-feeding as a critical factor in rCDI resolution by FMT (FIG. 70). FIG. 7D is a breakdown of most abundant individual gene inferred abundances.

[0219] EXAMPLE 2: MAG-directed Analysis Identifies Specific Metabolic Pathways Across Diverse Bacterial Groups That Associate Successful FMT

[0220] Next, we sought to move past a superorganism view of metabolism by leveraging our metagenomic data to make a more discrete analysis of metabolic contributions of individual species to FMT efficacy. Contigs were clustered to yield putative Metagenome-assembled genomes (or MAGs) and curated for quality and potentially contaminating regions (FIGs. 9A- 9B). Gene content within each MAG was annotated with a protein-level 60% minimum identity and 1e-3 E-value to the KEGG GENES database, and putative species-level classifications were assigned to those MAGs with >50% single taxonomic origin for annotated genes. MAGs with the identical classification within single samples were collapsed and unique gene annotations were conserved to make the final collection of MAGs. Remaining MAGs were then validated for both contamination and completeness, which resulted in an overall reduction from 2411 draft MAGs to 463 high-quality validated MAGs with a median of 1876 annotated genes each for downstream analysis.

[0221] To focus specifically on association of MAG-encoded metabolism with FMT outcome, we then quantified metabolic pathway abundances within each MAG by mapping metagenomic reads from their associated samples and tabulating gene abundances for those KEGG pathways. Next, we employed supervised machine learning for these gene abundances to uncover pathways that best segregate MAGs associated with the highest success rate (Donor A). The resulting predictive model had a high overall accuracy of 74.1%, and those pathways with the highest predictive value associated with successful rCDI resolution involved multiple C. difficile carbon sources including genes associated with amino acid biosynthesis, as well as the metabolism of N176 acetylglucosamine, sucrose, and galactose (FIG. 2A).

[0222] Focusing on those pathways highlighted by the previous analysis, we sought to identify MAGs enriched for genes in amino acid biosynthesis, combined galactose metabolism, amino sugar & nucleotide sugar metabolism, and starch & sucrose metabolism pathways. We then calculated the fraction of genes within each MAG dedicated to each pathway and examined these ratios together to identify those MAGS with the highest capacities for either form of metabolism (FIG. 2B). To isolate the MAGs most associated with FMT success, we applied a strict abundance cutoff (>90th percentile) in either pathway category. This filter resulted in 85 MAGs of interest from across all three donors which contained the highest levels of either amino acid or carbohydrate metabolism, of which 63.53% were derived from successful FMT- associated samples (Table S4 of U.S. Provisional Patent Application Serial No. 63 / 517,567 filed on August 3, 2023, the contents of which incorporated by reference as if fully set forth herein). Consolidation of MAGs with identical species annotations across samples then reduced this value to 44 MAGs (Table S2 of U.S. Provisional Patent Application Serial No. 63 / 517,567 filed on August 3, 2023, the contents of which incorporated by reference as if fully set forth herein). Further integration of our metabolic analysis of MAGs with literature-based manual curation resulted in a limited collection of 26 MAGs that contained members across dominant phyla of the gut microbiome, possessed maximum metabolic association with successful FMT (Donor A), and had culturable isolates available (FIG. 2C).

[0223] EXAMPLE 3: Simulated Metabolic Interactions with C. diff Revealed Candidate Probiotic Bacterial Species

[0224] To measure the directionality of each metabolic relationship with C. difficile, we sought to reconstruct the metabolism encoded in each of the 26 MAGs. While the gene and enzyme annotation level does not show directionality, flux balance analysis (FBA) based simulations allow for a clearer prediction of net consumption in B. producta and net production in B. longum. To do this, we developed a novel model building platform based on two slightly varied implementations of parsimonious flux analysis (FIG. 2D). Briefly, after mapping annotated genes to metabolic reactions, those gene-associated reactions were excluded from an overall flux minimization objective formulation to add the fewest reactions necessary to achieve growth (i.e., positive biomass reaction flux)27. Then, a minimum uptake rate for a common subset of minimal media components was applied during gapfilling, and the same process as the previous step was repeated, improving the ability of GENREs to grow in a greater variety of environmental conditions. We assessed the quality of the resultant GENREs using multiple quality metrics widely accepted within the field including stoichiometric consistency, overall mass balance of reactions, and MEMOTE28 score (a recently published tool for evaluating GENRE quality). This evaluation indicated that the GENREs produced here were high quality with a median M EMOTE score of 78% and flux / mass consistency in line with previous automated reconstructions.

[0225] To infer directionality of ecological interactions between the candidate probiotic strain GENREs and the C. difficile GENRE, we created a novel algorithm that characterizes potential edges of interaction as well as their degree of impact on growth during either cooperation or competition through separate iterative growth simulations. In each iteration, GENREs progressively increase levels of cooperation or competition for metabolites until no new interactions are found. The approach isolates the distinct metabolic impacts each microbe may have to reduce risk for false-negatives and maximize the ability to detect all possible edges of metabolic interaction(s). We performed simulations for all 26 MAGs generated in combination with the GENRE of the hypervirulent isolate C. difficile str. R20291 (iCdR703) and we found during cooperation simulations that both amino acids and carbohydrates were shared with C. difficile, with leucine, phenylalanine, and glucose- 1 -phosphate being the most frequent. Interestingly, there were relatively very few instances where C. difficile supplied metabolites to a partner species and mostly participated in largely one directional relationships (FIG. 10C). Competitive simulations identified almost exclusively amino acids, namely leucine and serine, as the edges of competition with other GENREs. Surprisingly, many of the bacteria identified in the analysis were more able to cross-feed rather than compete with C. difficile. While our initial hypothesis was that competition for nutrients was the most important interaction for FMT, these results support that metabolic cross-feeding may be a driving force behind successful FMT.

[0226] To validate our ecological interaction predictions, we selected two species with some of the highest predicted impacts on C. difficile growth in silico through either cooperation or competition for further testing. FIG. 3A is a schematic and constraints for an embodiment of an in silico simulation of metabolic interactions between probiotic and C. difficile GENREs. Bifidobacterium longum was a top cooperator and Blautia producta was one of the strongest competitors tested (FIG. 3B). This analysis revealed that the B. longum GENRE shared multiple preferred carbon sources with C. difficile including L-proline, ornithine, fumarate, and glucose-6-phosphate (FIG. 3C). Alternatively, B. producta was predicted to compete with C. difficile for exclusively amino acids, most strongly for asparagine, alanine, and threonine (FIG. 3D). To support these predictions in vitro, we employed a method of successive bacterial growth in conditioned rich culture medium that our group has previously utilized29,30 for measuring specific axes of metabolic interaction between species (FIG. 3E). Utilizing type strains B. longum ATCC 55813 and B. producta DSM 2950, we generated conditioned BHI + 10% FBS from either species through 24-hour incubation, followed by sterilization; 24-hour incubation ensures that species were grown to saturation, controlling for differences in kinetics and bacterial load. C. difficile str. R20291 was then grown for 18 hours in each conditioned medium to assess growth. As predicted by the in silico analysis, C. difficile grew poorly in B. producta conditioned medium which indicated a greater degree of nutrient depletion than in B. longum conditioned medium, which supported relatively high C. difficile growth (data not shown).

[0227] To further validate ecological predictions, we next performed untargeted LC-MS profiling on aliquots of conditioned media from each step of the experimental procedure with

[0228] B. longum and B. producta (FIG. 3E). Metabolites included in downstream analysis met one of the following criteria: scaled intensity for the given metabolite significantly decreased in both

[0229] C. difficile and the other species’ individual cultures, implying competition for that metabolite, or the intensities were significantly increased in other species’ individual cultures and then significantly decreased following C. difficile growth in the conditioned medium suggesting cooperation. This multi-layered analysis showed that the B. longum added a substantial number of metabolites to the medium that were subsequently consumed by C. difficile versus metabolites that were competed for (FIG. 4A). Concordantly, B. producta had an opposite phenotype, competing for many more metabolites than it shared with C. difficile (FIG. 4B). Among the metabolites identified via this analysis were numerous Stickland fermentation substrates (indicated by green stars), with no carbohydrate concentration changes meeting the same strict criteria.

[0230] EXAMPLE 4: Cooperative Consortium Protects Mice From CDI

[0231] Next, we assembled two distinct consortia that maximized either competition or cooperation with C. difficile. Membership of each consortium was chosen based on two criteria: first, species with the largest sum of competitive or cooperative indices, respectively, and second a unique range of individual metabolite interactions with C. difficile (Table S3 of U.S. Provisional Patent Application Serial No. 63 / 517,567 filed on August 3, 2023, the contents of which incorporated by reference as if fully set forth herein). We limited each consortium to the top four species in each category to streamline laboratory cultivation of strains and promote reproducibility (Table 1); importantly, combined in silico and in vitro validation supported collective effects on C. difficile growth with no detectable direct deleterious effects (FIG. 10B, 10C, 12B, & 12C). To test the effect of our systems-assembled consortia on the course of CDI in vivo, we utilized a murine model of CDI (FIG. 5A). Mice were sensitized to infection with antibiotic pretreatment, then challenged with C. difficile str. R20291. On days one and two, following pathogen challenge, animals were orally gavaged with freshly mixed overnight (24 hr) cultures of the cooperative consortium, competitive consortium, or sterile growth medium as a control and then monitored for disease progression. In parallel, another set of identical groups of animals were utilized to also monitor changes in survival, and strikingly all animals that were treated with the cooperative consortium survived the infection, while all mice that received either the competitive consortium or control succumbed to the infection (FIG. 5B).

[0232] Table 1 : Bacterial strains in each consortia predicted metabolic interactions with C. difficile. Strain designations along with the top specific metabolite axes of interaction with C. difficile, the total number of metabolites that the GENRE shares / com petes for with iCdR703, as well as the sum of each interaction index for all metabolites in each category.

[0233] To assess protective factors directly or indirectly provided by the cooperative consortium, the experiment was repeated and animals were instead sacrificed on day five post infection to characterize pathogen burden, virulence expression and host-response. Based on in vitro data, we predicted that the consortia would impact C. difficile colonization, so we performed quantitative culture for total C. difficile colony forming units (CFU) from cecal content (FIG. 5C) as well as relative quantity of toxins A & B (FIG. 5D). This comparison revealed that there was no difference in the load of C. difficile across all groups; however, only the cooperative consortium was associated with significant decrease in detectable toxin (p = 0.012). As toxin expression has been previously linked to metabolism, we also measured individual colony (n = 6) area via microscopy image processing to assess possible distinct patterns of phase variation (FIG. 5E). This measurement revealed that colony morphology of C. difficile exposed to the cooperative consortium became significantly rougher than the other groups. Colony morphology is indicative of phase-variation in C. difficile3'\ ,32 that occurs through invertible elements upstream of the colony morphology regulator genes (cmrRST) and flagellar flgB operon which impact toxin regulation. We have previously demonstrated that this phenotypic heterogeneity is a metabolically sensitive phenotype19, and supports that the added consortia are interacting with the pathogen metabolically.

[0234] Based on the degree of change in GDI disease severity, we became interested in also measuring the collateral impacts of each consortium on the gut microbiota as well as host response to the infection33. To accomplish these goals, we performed 16S rRNA gene sequencing from cecal content, which revealed a significant shift in community structure in only those animals receiving the cooperative consortia (FIG. 5F). We also found that alphadiversity of the cooperative-associated communities significantly increased relative to either of the other groups (FIG. 5G). Importantly, only sequences for a fraction of each assembled consortia were detectable in any of the samples from the competitive (3 / 4) or cooperativereceiving (2 / 4) groups (FIG. 12A). To then measure indirect effects on FMT efficacy through the host34, we also characterized consortia-associated changes in immune response. Using spectra flow cytometry to characterize cells in the colonic lamina propria (data not shown), we found that cooperative consortia promoted increased eosinophil levels (FIG. 5H) which has been associated with protection against CDI-associated mortality9,35. Additionally, significant decreases in ILC3 cells36 were observed in the same animals (FIG. 5I). These changes were also associated with no quantifiable differences in clinical scores between animals receiving the competitive consortia or control gavage (FIG. 11D). FIG. 11A shows plots depicting select innate immunity cell lineages with previous links the GDI response, FIG. 11B shows plots depicting select adaptive immunity cell lineages with previous links the GDI response, and (FIG. 11C) additional cell lineages with large-scale changes between groups. All values reflect percentages of total live cells detected, and significant differences determined by Wilcoxon rank-sum test.

[0235] EXAMPLE 5: Further Discussion of Examples 1-4

[0236] FMT has had extraordinary success in treatment of rCDI, with growing interest in leveraging this treatment for other diseases. In the current study, we developed a combined computational and experimental platform to identify potential probiotic bacterial species directly from human FMT metagenomic data. Leveraging rCDI as a proof of concept, we simulated ecological interactions for individual strains with C. difficile and identified a small collection of species with specific metabolic functions that reduced CDI-associated disease in vivo. This systems level approach was demonstrably robust to a small metagenome sample size, and may have similar accuracy for other investigations of potential metabolic interactions between microbes in the future.

[0237] Our findings underscore the complex ecology inherent to FMTs and highlight the utility of targeting metabolism within the microbiota. While some amount of competition may be critical for ultimately eliminating C. difficile colonization, the success of FMT in reducing disease may be more contingent on metabolic cooperation. One line of evidence that may support this reasoning is that both B. longum and E. coli are prominent constituents of the infant microbiome where C. difficile is most often associated with asymptomatic colonizations?. Our results support that amino acid cross-feeding of C. difficile by microbes present in FMT is likely a driving mechanism of reduced disease following infusion. While further mechanistic characterization of this pathway is needed, this interpretation agrees with previously appreciated negative genetic regulators of C. difficile toxin expression sensitive to intracellular levels of specific amino acids including L-proline38. Importantly, our results also suggest that FMT protects from GDI likely via a combination of effects on the pathogen, the microbiome, and the host response.

[0238] The methods and experimental designs of this pipeline were carefully considered to account for various challenges, such as sample size and prediction validations. Large and geographically diverse cohorts are often required to validate structural and functional features in microbiome data when the goal is to identify robust and consistent features. However, the goal of our pipeline was not to predict features that always occur in FMTs, but rather to select features that can successfully resolve GDI; this pipeline demonstrates the ability 373 to use a small pool of FMT donations as a starting point for subsequent modeling, analyses, and experiments of potential therapeutic communities. We validated model predictions with an in vitro setting first which allows for tighter control of variables; importantly, the in vitro data agreed well with the model predictions (FIGs. 10A-10C). It is important to emphasize that the models did not predict which of the communities would resolve disease, but rather which communities had cooperative or competitive relationships with C. difficile in a highly controlled setting (as validated in vitro). We then tested the communities in vivo since such an environment is inherently less controlled. While engraftment of these introduced microbes into the host microbiome is not verified here, there is evidence that the therapeutic benefit of such communities does not require complete engraftment 22,39. Additionally, the therapeutic benefit of the cooperative consortium could arise from a subset of the four species in the consortium. Furthermore, as observed clinically, different strains of C. difficile can result in differences in disease; future work will need to explore how this pipeline can be applied to different C. difficile strains and to investigate what the minimal therapeutic consortium might be. Systems biology approaches have been successfully applied to a variety of questions in C. difficile research. For example, a paired analysis of Environmental and Gene Regulatory Influence Networks (EGRIN) and metabolic models of C. difficile was used to identify the metabolic interactions between C. difficile and commensals at the microbial pathway and metabolite Ievel16. Additionally, systems analysis of the intestinal microbiome is being leveraged to identify biomarkers that can successfully predict recurrence of CDI40.41. Furthermore, industry-based efforts have been made to create targeted bacterial consortia. Seres Therapeutics has designed an encapsulated version of a human FMT which can be delivered orally15 and Vedanta Biosciences is testing a bacterial consortia therapy that focuses on prevention of recurrence in high-risk patients (Clinical Trial ID: NCT03788434). However, to our knowledge, our approach is the first instance of a computationally selected consortium using sequencing data from human FMT that has shown efficacy in an animal model of active infection and disease. Complete resolution of active CDI through non-invasive therapies will be a significant advancement within the field. Additionally, the systems biology pipeline created here can be used to identify additional tailored consortia against rCDI, as well as other collections of species that interface with host metabolism and related disease processes.

[0239] EXAMPLE 6: Materials and Methods for Examples 1-4

[0240] Clinical Sample Section

[0241] The FMT donor preparations (OpenBiome; Boston, MA) used in this study were all part of the FMT cohort described previously (UVA IRB-HSR #18229)20. Two aliquots (1 mL each) were removed from each donor preparation used on the day of the patient's FMT and stored at -80°C. Three donors were selected based on the number of donations and on patient outcome (i.e., FMT success / failure). A total of 119 patients with confirmed rCDI were treated with FMT and followed to determine treatment efficacy. A failed FMT was defined as recurrence of diarrhea with a positive stool ELISA for C. difficile toxin or positive tcdB PCR within three months of receiving FMT. From over the course of the study, four samples from each donor were chosen for DNA isolation and sequencing, controlling as much as possible for temporal effects within the donors as well as recipient-specific effects.

[0242] DNA processing and high-throughput sequencing: Aliquots were thawed on ice, fecal material was centrifuged (14,000 rpm for 1 min), then resuspended in solution CD1 (800 pL) and processed according to the manufacturer’s instructions (QIAamp PowerFecal Pro DNA Kit). Total DNA was measured using the DeNovix Broad Range dsDNA kit on a DeNovix fluorometer and sent for paired-end 150bp shotgun sequencing using the Nextera XT kit standard protocol. Sequencing was performed on an Illumina HiSeq 2500. Libraries for V4 16S rRNA gene sequencing were generated using the established paired-end 250bp amplicon sequencing protocol from Kozich et. al. and sequenced on Illumina NextSeq 550. All sequencing was performed with GENEWIZ, Inc.

[0243] Sequence Read Processing and Analysis

[0244] Paired-end 16S rRNA gene sequencing reads from previously published clinical studies were obtained from the NCBI SRA (SRP064361 and SRP070464), and processed using the standard DADA242 (v1.16) workflow (https: / / benjjneb.github.io / dada2 / bigdata.html). Family and genus-level ASV assignment was performed using the SILVA SSU NR99 r138.1 database. Abundance analysis of ASVs was performed as described in the Statistical methods section below.

[0245] Raw metagenomic read quality trimming was performed using Sickle (>Q25), and contigs were assembled using Megahit43 with the following settings: minimum kmer size of 87, maximum kmer size of 127, and a kmer step size of 10. A minimum assembled contig size of 1500 bp was used for all downstream analysis. Full community putative gene content was identified with Prodigal44 and annotated with DIAMOND blastp45 against the KEGG46 protein database. Curated reads were mapped to genes with Bowtie247, then PCR and sequencing errors were removed with PICARD MarkDuplicates to obtain final 427 read abundances for “superorganism” level analyses within FMT subcommunities.

[0246] In the next phase, read abundances and computed tetranucleotide frequencies for each contig were used with Metabat248 to cluster raw Metagenome-Assembled Genomes (MAGs). MAGs were decontaminated of possible erroneous contigs and pruned using CheckM49 (annotation kingdom or better, completeness >50% and contamination <33.3%) and excessively small MAGs were removed from downstream analysis (<1.3 Mb and <1354 putative genes; based on Pelagibacter ubique smallest free-living bacterium) to yield final high-quality MAGs. Gene content of each MAG was then called and annotated as in the previous section. Metagenomic reads were aligned to annotated genes of each MAG to assess relative abundance of gene / metabolic pathways and overall abundance of MAGs associated with positive outcome. Genus-level identification was performed by assessing for >40% annotated amino acid sequences in each MAG annotated as belonging to the same bacterial genus. Species identity of MAGs was determined with full length 16S rRNA gene BLAST and consensus gene annotation when possible. Full core functional content of final MAGs for downstream analysis was collectively validated through CheckM completeness- included annotations (FIG. 9A).

[0247] MAG-based de novo GENRE Construction

[0248] KEGG + ModelSEED universal reaction database was adapted from a previous GENRE-building effort from our group50. Additional curation was performed to add new annotations (KEGG46 r88.1) ModelSEED Biochem DB (https: / / github.com / ModelSEED / ModelSEEDDatabase). For each MAG, gene annotations were then mapped to corresponding metabolic reactions to create initial scaffolds for subsequent gapfilling. Gram + / - specific biomass formulations (Table S2 of U.S. Provisional Patent Application Serial No. 63 / 517,567 filed on August 3, 2023, the contents of which are incorporated by reference) were then added to each GENRE scaffold based on taxonomic annotations from the previous analysis. Gapfilling was then achieved using the universal reaction database through a two-phase optimization approach:

[0249] Flux balance analysis (FBA) is a mathematical method for analyzing metabolic flux through an in silico metabolic network51. As in parsimonious-FBA, in the first phase each reversible reaction is separated into individual forward and reverse reactions virrev. Linear coefficients g for each vector are now integrated (0 for reactions associated with a gene, and 1 for those that are not) and an objective function is then defined to minimize that total of flux across the entire model. These steps are all performed subject to a lower bound on the biomass flux (vobj) set to a fraction (f, set to >1%) of the previously identified maximum biomass flux (max vobj) and mass-balance constraints. Optimization (standard FBA) is performed and reactions found in the solution to have >1x105 flux that are not in the initial scaffold GENRE are then added to the model.

[0250] In the second phase, additional constraints are added to the optimization where the input flux for select core growth substrate exchange reactions ve (Table S2 of U.S. Provisional Patent Application Serial No. 63 / 517,567 filed on August 3, 2023, the contents of which are incorporated by reference) are required by setting a negative maximum flux (k, set to -0.01). As in the previous step, FBA is performed and new reactions found in the solution to have >1x105 flux are added to the scaffold GENRE to yield the gapfilled model. Final GENREs in downstream analyses met size and quality minimum inclusion criteria of >180 genes and >400 reactions (sizes based on E. coli core model / AF126045), with <20% of metabolites participating in possible mass-generating Ioops52. MEMOTE28 was then run on each MAG- enabled GENRE resulting in a median quality score of 78% (Fig. 2F)27.

[0251] Metabolic Interaction Predictions

[0252] First, each GENRE was constrained to achieve the minimum allowable optimal biomass of fraction f (>25%) in complete media, at which point the minimal media components necessary for this growth rate were then calculated subject to standard mass balance and reaction flux constraints. Then for each model in the simulation (iCdR703 and interaction partner) the union of results from these calculations is then found and the extracellular exchange reactions of both models are set to mirror this combined list. Initial exchange flux ranges for the available metabolites in competition simulations were an emin of -1000 (lower bound) and an emax of +1000 (upper bound). In cooperative simulations initial emin was - 1000. Flux variability analysis (FVA) was then performed for both GENREs focusing only on extracellular exchange reaction ranges. For those active exchange reactions for metabolites present in both GENREs, the lower or upper bound was modified by the given coefficient c (0.5) if calculating competition or s (100) if calculating cooperation.

[0253] During either type of interaction simulation, the opposite directions’ coefficient was set to 1 or 0 (c or s). Joint FVA was then repeated for the newly constrained GENREs until biomass flux either ceased to change or no new edges of interaction were found. Cooperative index for each metabolite was calculated as the exported metabolite exchange flux divided by the recipient GENRE’S maximum biomass flux. Alternatively, the competitive index for metabolites was calculated as the given metabolite’s absolute exchange flux divided by the importing GENRE’S maximum biomass flux, multiplied by the number of iterations that metabolite was contested.

[0254] Strain Acquisition, Cultivation, and Identification

[0255] Lyophilized type strain isolates for taxa identified through commercial vendors ATCC (https: / / www.atcc.org) or DSMZ (https: / / www.dsmz.de / ) as noted in the individual species identifiers. All strains were reconstituted and grown anaerobically (6% H, 20% CO2, 74% N2) at 37°C in liquid Brain Heart Infusion medium (BHI; BD Bacto Ref:237500 Lot:1194923) supplemented with 10% Fetal Bovine Serum (FBS; Gibco Ref:A38403-02 Lot:2240781 RP), and streaked on solid agar of the same medium (1.5% agar). Sanger sequencing of full 16S rRNA gene (Genewiz Inc., 27F - 1492R primers) was performed from all cultivated isolates prior to storage and experimentation to ensure correct isolates.

[0256] Conditioned Medium Experiments

[0257] Successive conditioned media experiments were performed as described previously29,30. Single colonies from each potential consortium member growing on BHI + 10% FBS solid medium were inoculated to fresh liquid BHI + 10% FBS and conditioned media from each strain was prepared by growing each species for 24 hr anaerobically at 37 °C. The resulting culture was centrifuged at 3500 rpm for 10 min and the supernatant was returned to pH 7.0 using 1M NaOH then filter sterilized (PVDF membranes with 0.22 pm pore size). Aliquots of spent medium were stored at -80 °C, and individual aliquots were thawed and equilibrated in the anaerobic chamber overnight prior to C. difficile inoculation. Similarly, C. difficile single colonies were picked from overnight growth on BHI + 10% FBS solid agar and then incubated in liquid BHI + 10% FBS for an additional 24 hr. Prior to growth measurements, liquid overnights were back-diluted 1 :3 into fresh liquid BHI + 10% FBS and incubated for 2 hr to initiate active growth. Conditioned media (250 pl each) was then inoculated with back- dilutions at a ratio of 1 :100 in a 96 well plate (Corning Ref:3596), and GD600 was measured every 5 min for 18 hr (Tecan Infinite M200 Pro). For conditioned medium supplementation experiments, sterile 24 hr growth conditioned medium from C. difficile str. R20291 was diluted 1 :1 with sterile aliquots of either cooperative or competitive consortia-depleted media (24 hr growth). Positive and negative controls of fresh BHI + 10% FBS or additional C. d / Tf / c / Ze-depleted media were performed simultaneously. Growth (OD600) was then measured as in the previous conditioned media experiments and ALICs were calculated from the resultant curves.

[0258] Disk Diffusion Assay

[0259] The entire surface of standard anaerobic BHIS agar plates was inoculated and spread with 100 pL of overnight C. difficile str. R20291 growth. Plates were air-dried for 10 minutes, at which point diffusion disks (Sigma #741146) saturated with 25 pL of liquid were added to the surface with replicates for each group. Plates were incubated at 37C for 24 hr and inhibition zone diameter was measured. Vancomycin concentration and area measurements were performed according to the guidelines established by the National Committee for Clinical Laboratory Standards. Growth inhibition diameter measurements from disk diffusion assay for C. difficile str. R20291 with the indicated treatments (n=6).

[0260] Untarqeted Mass Spectrometry

[0261] Liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis from conditioned media was performed in the UVA Metabolomics Core as previously described53. In summary, randomized sample injection was performed via a Thermo Vanquish UHPLC, and separation of the metabolites was achieved using Thermo Accucore C18 column (Thermo Scientific; 2.1 by 100 mm, 1.5 pm). For the 15-minute gradient, the mobile phase consists of solvent A (0.1% formic acid in water) and solvent B (0.1% formic acid in methanol). The gradient was as follows: 0 to 8.0 min 50% solvent B, 8.0 to 13.0 min held at 98% solvent B, and 13.1 to 15.0 min revert to 0% solvent B to re-equilibrate for next injection. Spectra were acquired on Thermo ID-X Tribrid MS, using both positive and negative mode. Data was acquired in full MS mode (1 pscan) at a resolution of 120,000 with a scan range of 67 to 1 ,000 m / z at a normalized automatic gain control target of 25%, and 50 ms of maximum injection time was allowed. Fragment masses were detected by Orbitrap at a resolution of 30,000. Raw spectra were analyzed in Compound Discoverer 3.1 with standard settings. Compound annotations were performed by searching the ddMS2 masses in mzCloud, ChemSpider, KEGG database, and an in-house database of I ROA Mass Spectrometry Metabolite Library of Standards (https: / / iroatech.com / ).

[0262] Animal Infection Model

[0263] Murine C. difficile infections were carried out as previously described9. Five-week-old C57BL6 male mice were purchased from Jackson Laboratories. All mice were housed under specific pathogen-free conditions at the AALAC accredited University of Virginia animal facility. Experiments were performed according to the provisions of the Animal Welfare Act and were approved by the University of Virginia Institutional Animal Care and Use Committee. Mice were maintained on the Envigo control diet (TD.05230) for three weeks before treatment with antibiotics and throughout the infection model. Prior to beginning the experimental model, mice from across litters were randomly assigned to respective groups. To make mice susceptible to infection, mice received an oral antibiotic cocktail containing 45 mg / L vancomycin (Mylan), 35 mg / L colistin (Sigma), 35 mg / L gentamicin (Sigma) and 215 mg / L metronidazole (Hospira) ad libitum for 3 days. The animals were switched back to plain drinking water two days before the infection. The day before infection, mice were injected intraperitoneally with 0.016 mg / g of clindamycin. The next day, mice were orally challenged with 103 C. difficile str. R20291 spores in 100 pl of sterile water via oral gavage. During the infection, mice were monitored daily for weight loss, as well as clinical signs of disease. Clinical score criteria included weight loss, coat condition, activity level, diarrhea, posture and eye condition for a cumulative clinical score between 1 and 20. Weight loss and activity levels were scored between 0 and 4 with four being greater than or equal to 25% loss in weight. Coat condition, diarrhea, posture, and eye condition were scored between 0 and 3. Diarrhea scores were 1 for soft or yellow stool, 2 for wet tail, and 3 for liquid or no stool. Mice were euthanized if severe illness developed based on a clinical score > 14. On days two and three post C. difficile challenge, 100 pl of each consortium, prepared from 24-hour cultures, was administered to mice via oral gavage. A third group received vehicle control.

[0264] In vivo C. difficile CFU Quantification

[0265] Cecal content samples were weighed and serially diluted under anaerobic conditions (6% H, 20% CO2, 74% N2) with anaerobic PBS. Plating for total C. difficile str. R20291 CFU was performed by plating diluted samples on BHI plates plus taurocholate (10%), cycloserine (0.5%), and cefoxitin (0.5%) at 37°C for 24 hr under anaerobic conditions after which, the resultant colonies were counted across all experimental replicates.

[0266] Relative Toxin Quantification

[0267] Supernatants were tested for the combined presence of Toxin A / B using the ToxA / B II kit (TechLab) according to manufacturer’s directions with the following modifications. Briefly, supernatants from dilutions of cecal contents used for C. difficile R20291 CFU quantification were directly added to assay wells. The goal was to measure the relative amount of toxins present in the sample compared to the positive control provided in the kit. To do this, increasing volumes of the positive control were used to construct a standard curve with the OD450 readout of samples calculated as relative toxin equivalents per gram of cecal content and normalized by the absolute quantity of C. difficile per gram of cecal content. We note that PCR can result in overcalls of toxin positivity54 and so our results are normalized to absolute quantity of C. difficile per gram of cecal content.

[0268] Colony Microscopy

[0269] At least one colony from each animal was included in each comparison for C. difficile grown on BHIS from cecal content of infected mice. Microscopy images were taken on an EVOS XL Core cell imaging system at x4 magnification. Colony dimensions were determined using Imaged (https: / / imagej.nih.gov / ij / ).

[0270] Immune Profiling

[0271] To isolate the lamina propria, colons were removed, longitudinally cut, and rinsed in cold Hank’s Balanced salt solution (HBSS) supplemented with 5% FBS and 25mM HEPES. Epithelial cells were removed by incubating each colon in pre-warmed HBSS supplemented with 15 mM HEPES, 5 mM EDTA, 10% FBS and 1mM dithiothreitol at 37C for 40 minutes in a shaking incubator at 220 rpm. The colon was then cut into smaller sections and digested in RPMI containing 0.17 mg / mL liberase TL (Sigma) and 30 mg / mL DNase (Sigma) at 37C in a shaking incubator. Following digestion, the tissue was passed through 40 and 100 uM cell strainers respectively, the cells were counted and re-suspended in FACS buffer (PBS with 2% FBS). Approximately 1 x 106 cells were plated in a 96-well plate and stained for flow cytometry. First, cells were Fc blocked (anti-mouse CD16 / 32 TruStain, BioLegend Cat #101320) and then stained with a fixable viability dye (Zombie NIR, BioLegend Cat #423105). The following antibodies were used for staining, CD19-PerCP-Cy5.5 ( BioLegend, Cat #115534), CD3- PerCP-Cy5.5 (BioLegend, Cat #100218), CD5-PerCP-Cy5.5 (BioLegend, Cat #100624), FcERIa- PerCP-Cy5.5 (BioLegend, Cat #1343420), Ly6C-AlexaFluor488 (BioLegend, Cat #128022), CXCR2-BV750 (BD, Cat #747816), Ly6G-BV650 (BioLegend, Cat #127641), SiglecF-AlexaFluor700 (ThermoFisher, Cat #56-1702-82), CD45-SparkViolet538 (BioLegend, Cat# 103179), CD8a-NovaFluorBlue610-70S (ThermoFisher, Cat#M003T02B06), CD4-APC Fire750(BioLegend, Cat# 100460), CX3CR1 -Alexa Fluor 647(BioLegend, Cat# 149004), CD90.2- BV785 (BioLegend, Cat# 105331), CD11c-PE-Cy7 (BioLegend, Cat# 117318), CD11 b-BV480 (BD, 566117), TCR Beta- BV570 (BioLegend, Cat# 109231), CD64- BV421 (BioLegend, Cat# 1393090), MHCII-BV605 (BioLegend, Cat# 107620), CD127- PE-Cy5 (BioLegend, Cat# 1350160), CD86- PE-Dazzle 594 (BioLegend, Cat# 105042), CD206-PE (BioLegend, Cat# 141706), GATA-3- BV711(BD, Cat# 565449), ROR gammaT-APC (ThermoFisher, Cat# 17-6981-82), FoxP3-PerCP-eFluor710 (ThermoFisher, Cat# 46-5773- 82). For intracellular transcription staining, the Foxp3 / Transcription Factor Staining Buffer Set (eBioscience, Cat #00-5523-00) was used according to the manufacturer’s instructions. Flow cytometry data was acquired using the Cytek Aurora Borealis outfitted with 5 lasers including blue, violet, yellow-green, red and UV. Data analysis was performed using OMIQ. Statistical Methods

[0272] All statistical analysis was performed in R v4.1.3. Rarefaction 587 (11 ,000 reads per sample), nonmetric multidimensional scaling of Bray-Curtis dissimilarity, and permutational multivariate analysis of variance (PERMANOVA) analyses were accomplished using the vegan R package55. Significant differences for growth curve AUC, metabolite concentrations, C. difficile CFU, community diversity, relative toxin equivalents, colony morphology, and immune cell population counts were determined by Wilcoxon signed-rank test and Benjamini- Hochberg correction when necessary. Supervised machine learning was accomplished with the base implementation of Random Forest also in R56. Dissimilarity between C. difficile str. R20291 growth curves in consortium-conditioned media were determined using Dynamic Time Warping57. Data and code availability: The GitHub repository for this study, with all programmatic code and GENREs described here, can be found at https: / / github.com / csbl / Jenior_FMT_2022. 16S rRNA gene sequencing reads were downloaded in raw FASTQ format from the NCBI Sequence Read Archive (SRP064361 and SRP070464). Screened metagenomic sequencing reads generated for this study have been uploaded to the NCBI SRA (PRJNA844211).

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Claims

CLAIMSAt least the following is claimed:1) A method of identifying candidate microbiota for administration against a candidate bacterial infection, comprising: determining, from provided successful bacterial administration metagenomic sequencing data and failed bacterial administration metagenomic sequencing data, taxonomic bacterial composition of one or more samples of a successful bacterial administration against the candidate bacterial infection and taxonomic composition one or more samples of a successful bacterial administration against a candidate bacterial infection; determining superorganism-level functional metabolic capacity from the successful bacterial administration metagenomic sequencing data and failed bacterial administration metagenomic sequencing data; identifying metabolic pathways with differential metabolic capacities between the successful and failed administrations from the determined capacities; clustering the successful bacterial administration samples and failed bacterial administration samples based on the identified determined functional metabolic capacities; annotating the gene content of each cluster; quantifying the annotated gene content; segregating the quantified gene content based on administration success or failure; identifying genes enriched in one or more metabolic pathways from the segregated quantified gene content of the successful administration; reconstructing the metabolism of the one or more metabolic pathways mapped onto one or more species from the determined taxonomic composition; segregating the reconstructed metabolism of the determined taxonomic composition into cooperative or competitive with the candidate bacterial infection; and identifying one or more bacterial species for administration from the determined taxonomic composition having cooperative or competitive metabolism with the candidate bacterial infection.2) The method of claim 1, wherein the candidate bacterial infection is a Clostridioides difficile (C. diff) infection.3) The method of claim 1, wherein the microbiota administration is a fecal microbiota transplant.4) The method of any one of claims 1 to 3, further comprising, before determining the taxonomic composition: providing one or more samples of a successful bacterial administration against the candidate bacterial infection from one or more donors and providing one or more samples of a failed bacterial administration against the candidate bacterial infection from one or more donors; and sequencing the metagenome of the one or more successful bacterial administration samples and the metagenome of the one or more failed bacterial administration samples.5) The method of any one of claims 1 to 4, wherein the one or more successful administration samples and one or more failed administration samples are each fecal samples.6) The method of any one of claims 1 to 5, wherein successful administration is determined by a reduction in C. diff toxin level compared to before administration, increased survival, or both.7) The method of any one of claims 1 to 6, wherein failed administration is determined by no change or increased C. diff toxin levels compared to before administration, reduced survival, or both.8) The method of any one of claims 1 to 7, wherein the metagenomic sequencing comprises shotgun sequencing, 16S rRNA sequencing, inferred from metatranscriptome, next-gen sequencing methods, using the 16S rRNA gene as a phylogenetic marker, or shotgun sequencing.9) The method of any one of claims 1 to 8, wherein the superorganism-level functional capacity is determined by: assembling contiguous genomic sequences from the metagenomic sequencing data; annotating gene content by assigning functional pathways to the assembled genomic sequences; mapping metagenomic reads to annotated genes; differentiating functionalities of the mapped metagenomic reads .10) The method of any one of claims 1 to 9, wherein the segregating the quantified gene content is using machine learning.11) The method of claim 10, wherein the machine learning is a random forest or support vector machine.12) The method of any one of claims 1 to 11, wherein reconstructing the metabolism and segregating the reconstructed metabolism is with genome-scale metabolic network reconstructions.13) The method of any one of claims 1 to 12, wherein the one or more metabolic pathways are one or more of amino acid biosynthesis, combined galactose metabolism, amino sugar metabolism, nucleotide sugar metabolism, starch metabolism, or sucrose metabolism, individually or in any combination thereof.14) A bacterial consortium, comprising one or more bacteria that cooperatively share amino acids and carbohydrates with C. difficile.15) The bacterial consortium of claim 14, wherein the shared amino acids comprise one or more of leucine, phenylalanine, glucose-1-phosphase, L-proline, ornithine, fumarate, or glucose-6-phosphate, individually or in any combination of any thereof.16) The bacterial consortium of claim 14 or 15, wherein the bacterial consortium comprises one or more of Bifidobacterium longum (B. longum), Escherichia coli (E. coli), Roseburia intestinalis (R. intestinalis), or Streptococcus thermophilus (S. thermophilus), individually or in any combination of any thereof.17) The bacterial consortium of any one of claims 14 to 16, wherein the bacterial consortium comprises Bifidobacterium longum (B. longum), Escherichia coli (E. coli), Roseburia intestinalis (R. intestinalis), and Streptococcus thermophilus (S. thermophilus).18) The bacterial consortium of any one of claims 14 to 17, wherein the bacterial consortium consists essentially of B. longum, E. coli, R. intestinalis, and S. thermophilus.19) The bacterial consortium of any one of claims 14 to 18, wherein the bacterial consortium consists of B. longum, E. coli, R. intestinalis, and S. thermophilus.20) The bacterial consortium of any one of claims 14 to 19, wherein each of the B. longum, E. coli, R. intestinalis, and S. thermophilus are at enriched levels compared to any other bacteria present in the consortium.21) The bacterial consortium of claim 16 to 20, wherein the B. longum is ATCC 55813 B. longum.22) The bacterial consortium of any one of claims 16 to 21, wherein the E. coli is K12 E. coli.23) The bacterial consortium of any one of claims 16 to 22, wherein the R. intestinalis is DSM 14610 R. intestinalis.24) The bacterial consortium of any one of claims 16 to 23, wherein the S. thermophilus is LMD-9 S. thermophilus.25) A method of treating a C. diff infection in a subject in need thereof, comprising: administering a pharmaceutical composition comprising the bacterial consortium of any one of claims 14 to 24 to a subject having or suspected of having a C. diff infection.26) The method of claim 25, wherein the C. diff infection is not responsive to antibiotic treatment.27) The method of claim 25 or 26, wherein the administering is oral administration or one or more fecal transplants.28) The method of any one of claims 25 to 27, wherein the bacterial consortium is administered in an effective amount to reduce one or more symptoms of C. diff infection.29) The method of claim 28, wherein the effective amount is about 106to about 1011.30) The method of any one of claims 25 to 29, further comprising a pharmaceutically acceptable carrier.31) The method of any one of claims 25 to 30, wherein the composition is sterilized prior to administration. 32) A kit, comprising: the bacterial consortium of any one of claims 14 to 25; and instructions for use.33) The kit of claim 32, further comprising a container containing the bacterial consortium.34) The kit of claim 32 or 33, wherein the bacterial consortium is provided in a dosage unit form.35) The kit of any one of claims 32 to 34, further comprising a pharmaceutically acceptable carrier.

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