Compositions and methods related to fecal persistent microbiome transplant

Abstract

The present disclosure provides compositions and methods related to fecal microbiome transplant. In particular, the present disclosure provides compositions and methods for generating a composition suitable for fecal microbiome transplant from a taxonomically defined bacterial culture composition based on various metabolic indicators.

Description

COMPOSITIONS AND METHODS RELATED TO FECAL PERSISTENT MICROBIOME TRANSPLANTGOVERNMENT SUPPORT

[0001] This invention was made with government support under grant numbers DK.034987 and DK056350 awarded by the National Institutes of Health. The government has certain rights in the invention.CROSS REFERENCE TO RELATED APPLICATIONS|0002] This application claims priority to and the benefit of U.S. Provisional Patent Application No. 63 / 647,667 filed July 23, 2024, and U.S. Provisional Patent Application No. 63 / 771,399 filed March 13, 2025, both of which are incorporated herein by reference in their entireties and for all purposes.FIELD

[0003] The present disclosure provides compositions and methods related to fecal microbiome transplant. In particular, the present disclosure provides compositions and methods for generating a composition suitable for fecal microbiome transplant from a taxonomically defined bacterial culture composition based on various metabolic indicators.BACKGROUND

[0004] The assembly and maintenance of the gut microbiome is a complex process. For example, breast milk, a foundation for symbiotic keystone species in newborns, not only primes infants for the introduction of solid foods after weaning but also imparts a lasting impact, potentially explaining the high levels of memory’ T cells observed in breastfed infants through adolescence. This immunological resilience translates into greater resistance against infections. Conversely, disruptions during early gut colonization can induce imbalances with repercussions for immune function, predisposing individuals to allergies and inflammatory conditions. Moreover, once an infant gut microbiome undergoes its critical assembly phase at approximately 3 years of age, making effective and stable modifications to it becomes difficult.

[0005] Microbial consortia in the human gut play a pivotal role in health and disease, influencing nutrient absorption, immune function, and resistance to pathogens. Recent advances in microbial ecology and genomics have paved the way for innovative approaches to manipulate these consortia to promote health. However, few in vitro studies have concurrently evaluated the microbial taxonomic responses and the associated metabolic outputs resultingfrom dietary changes, highlighting a significant gap in understanding. In the host, as most soluble monosaccharides are absorbed in the small intestine, the colonic microbiota predominantly engages in fermentative activity due to reduced oxygen availability. There, colonic microbiota's ability to extract energy from highly reduced carbohydrates is restricted under those conditions. As dietary7carbohydrate structures increase in complexity, reaching the lower intestine, they undergo selective fermentation into short-chain fatty acids (SCFAs). SCFAs are shared among consortium members through cross-feeding, a phenomenon that may play a critical role in determining the overall stability and resilience of the consortium. Linking taxonomic responses and metabolic outputs provides a nuanced understanding of the intricate dynamics within microbial consortia, thereby contributing to a more holistic comprehension of microbial ecology in the context of disruptive events. Thus, in vitro systems offer the ability to conduct multiple experimental replicates under highly controlled and standardized conditions. By simulating key natural environmental conditions in the gut, bioreactors can facilitate consortium-level research on dynamic microbe-microbe interactions.SUMMARY

[0006] Embodiments of the present disclosure include a method of generating a composition for fecal persistent microbiome transplant (FPMT) (also referred to as fecal microbiota transplantation or FMT). In accordance with these embodiments, the method includes inoculating a bioreactor with a defined culture composition, wherein the defined culture composition comprises a bacterial population, and a carbon source comprising a plurality7of carbohydrates; culturing the defined culture composition according to a set of culture conditions comprising defined taxonomic proportions of bacteria in the bacterial population, an adjusted feeding rate, and adjusted retention time; and assessing at least one metabolic indicator at least one timepoint during the culturing of the defined culture composition. In some embodiments, the at least one indicator indicates that the defined culture composition is suitable for FPMT.

[0007] In some embodiments, the bacterial population is obtained from one or more donors prior to culturing. In some embodiments, the bacterial population is obtained from a synthetic bacterial culture prior to culturing.

[0008] In some embodiments, bacterial population comprises one or more of the following: Bacteroidota, Clostridia, Negativicutes, Lactobacillales, Erysipelotrichia, Actinomycetota, and / or Pseudomonadota. In some embodiments, the defined taxonomic proportions of the bacteria comprise: from about 5% to about 15% Bacteroidota,' from about 10% to about 30%Clostridia, from about 1% to about 10% Negativicutes,' from about 10% to about 35% I.aciobacillales from about 1% to about 10% Erysipelotrichia: from about 5% to about 25% Actinomycetota, and / or from about 5% to about 15% Pseudomonadota.

[0009] In some embodiments, the plurality of carbohydrates comprises galactooligosaccharides (GOS) and / or lactose. In some embodiments, the GOS is humanized GOS (hGOS). In some embodiments, the plurality of carbohydrates further comprises N- Acet llactosamine (LacNAc) and / or a bile salt.

[0010] In some embodiments, the adjusted feeding rate ranges from about 0.04 h'1to about 0.12 h'1. In some embodiments, the adjusted feeding rate ranges from about 0.06 h'1to about 0.10 h’1.

[0011] In some embodiments, the adjusted retention time ranges from about 5 hours to about 30 hours. In some embodiments, the adjusted retention time ranges from about 10 hours to about 15 hours.

[0012] In some embodiments, the at least one metabolic indicator comprises carbon dioxide and / or hydrogen concentration. In some embodiments, the carbon dioxide concentration ranges from about 25 mg L’1h’1to about 300 mg L'1h’1. In some embodiments, the hydrogen concentration ranges from about 0.1 mg L'1h'1to about 1.5 mg L'1h'1.

[0013] In some embodiments, the at least one metabolic indicator comprises a short-chain fatty acid (SCFA). In some embodiments, the SCFA is acetate, propionate, and butyrate. In some embodiments, acetate ranges from about 5% to about 15%, propionate ranges from about 0.5% to about 5.0%, and butyrate ranges from about 0.1% to about 1.0%.

[0014] In some embodiments, the at least one metabolic indicator comprises lactate at a range of about 0.1% to about 5.0%.

[0015] In some embodiments, culturing comprises adding a carbohydrate feed composition according to the adjusted feeding rate.|0016] In some embodiments, the carbohydrate feed composition comprises lactose, sucrose, GOS, hGOS, and / or a bile salt.

[0017] In some embodiments, the method further comprises transplanting the defined culture composition into a human subject after assessing at least one metabolic indicator. In some embodiments, transplantation of the defined culture composition into the human subject produces a metabolically stable and persistent microbial consortia.

[0018] In some embodiments, transplantation of the defined culture composition into the human subject treats and / or prevents an immune disorder or condition. In some embodiments, the immune disorder or condition comprises at least one of Addison disease, celiac disease.dermatomyositis. Graves' disease, Hashimoto thyroiditis, inflammatory bowel disease, Crohn’s disease, ulcerative colitis, multiple sclerosis, Myasthenia gravis, pernicious anemia, reactive arthritis, rheumatoid arthritis, Sjogren syndrome, Systemic lupus erythematosus (lupus), and / or Type I diabetes.10019] In some embodiments, transplantation of the defined culture composition into the human subject treats and / or prevents an infection. In some embodiments, the infection is a bactenal infection, a fungal infection, or a viral infection. In some embodiments, the bacterial infection is caused by Clostridioides difficile, Salmonella, E. coli, Campylobacter, Shigella, Staphylococcus, and / or Clostridium.

[0020] Embodiments of the present disclosure also include a method of treating or preventing an immune disorder and / or infection in a subject. In accordance with these embodiments, the method includes generating a composition for fecal persistent microbiome transplant (FPMT) by inoculating a bioreactor with a defined culture composition, wherein the defined culture composition comprises a bacterial population, and a carbon source comprising a plurality of carbohydrates: culturing the defined culture composition according to a set of culture conditions comprising defined taxonomic proportions of bacteria in the bacterial population, an adjusted feeding rate, and adjusted retention time; assessing at least one metabolic indicator at at least one timepoint during the culturing of the defined culture composition; wherein the at least one indicator indicates that the defined culture composition is suitable for FPMT; and transplantation of the defined culture composition into the human subject, thereby treating or preventing the immune disorder and / or infection.

[0021] In some embodiments, the immune disorder comprises at least one of Addison disease, celiac disease, dermatomyositis, Graves’ disease, Hashimoto thyroiditis, inflammatory bowel disease. Crohn’s disease, ulcerative colitis, multiple sclerosis, Myasthenia gravis, pernicious anemia, reactive arthntis, rheumatoid arthritis, Sjogren syndrome, Systemic lupus erythematosus (lupus), and / or Type I diabetes.

[0022] In some embodiments, the infection is a bacterial infection, a fungal infection, or a viral infection. In some embodiments, the bacterial infection is caused by Clostridioides difficile, Salmonella, E. coli. Campylobacter, Shigella, Staphylococcus, and / or Clostridium.

[0023] Other aspects and embodiments of the disclosure will be apparent in light of the following detailed description.BRIEF DESCRIPTION OF THE DRAWINGS

[0024] FIGS. 1A-1B: Core microbiome analysis reveals stable taxonomic signatures across dietary and flow conditions. Venn diagram illustrating the shared OTUs across all carbon source experiments using the infant feces as a naturally derived inoculum, highlighting the consistently detected taxa under varying dietary conditions (FIG. 1 A). Venn diagram illustrating the persistent OTUs detected across increasing dilution rates for the hGOS + BS condition, enriched with human milk oligosaccharides (HMOs) (FIG. IB).

[0025] FIG. 2: Phylogenetic comparison between ex vivo infant fecal microbiota and the rationally designed minimal microbial consortium. Phylogenetic trees depicting the overall diversity present in the ex vivo culturing of feces from three healthy one-year-old infants (left) and species included in the minimal consortium inoculum (right). Species bolded in the ex vivo tree represent the strains chosen to be included in the minimal consortium. Bolded nodes on the ex vivo phylogenetic tree represent nodes that are also found on the minimal consortium phylogenetic tree. Bolded red nodes on the ex vivo phylogenetic tree represent similar strains found in the minimal consortium phylogenetic tree but were replaced with strains within the same genus or species that are fully sequenced and comply with BSL-1 restrictions. Taxonomic proportions for each tree provide a general overview of the diversity found within the majority of classified nodes.

[0026] FIG. 3: Genetic specialization observed in a minimal 16-species microbial consortium. This figure illustrates the genomic landscape of a 16 species curated inoculum. Clustering of genomes is based on the presence / absence patterns of 34.151 gene clusters. The outermost circles portray information regarding gene clusters present only in a single genome (dark blue), the number of genomes contributing to a gene cluster (yellow), and the number of genes present in a gene cluster (purple). The green line segments represent known Cluster of Orthologous Groups (COG) 20 categories. The innermost circles represent a single genome with the black line segments representing gene clusters. The histograms provide information on the number of gene clusters per genome, the number of singleton gene clusters per genome, and the redundancy (number of redundant genes) of each genome. The donut charts display the functional categorization of genes within the pan-genome based on the COG category 20 for the gene clusters present from a singular genome (top) and those that are found in all 16 species (bottom).

[0027] FIGS. 4A-4B: Minimal consortium taxonomic profiles and bacterial abundance variability across different carbon sources and feeding rates. Panel A represents the overalltaxonomic proportions present in each dynamically cultured consortium compared to the proposed and sequenced inoculum. Panel B shows the relative abundance scatter plots of each species in response to different carbon source conditions (GOS+BS, hGOS+BS, and lactose) at varying feeding rates (D = 0.04, 0.08, 0.12 h '). with colors representing each carbon source condition. Bifidobacterium longum subsp. infantis reads are collectively presented under the genus Bifidobacterium.

[0028] FIGS. 5A-5D: Beta diversity and dispersal patterns in minimal consortium assemblies. FIG. 5A represents weighted PCoA ordinations of OTU abundance data representing duplicate experiments of three carbon sources fed at three incremental rates to a standard minimal consortium inoculum. Feeding rates (D = 0.04, 0.08, 0.12 h ') and carbohydrate composition (experiments) are represented by unique shapes and colors, respectively. Colored ellipses represent 95% confidence intervals for all data in each dietary carbon composition experiment. FIGS. 5B-5D displays the results of the PERMDISP function for each independent carbon source grouped by feeding rate.

[0029] FIGS. 6A-6D: Metabolic Response to Carbon Source and Feeding Rate in a Minimal Microbial Consortium. FIG. 6A portrays the overall metabolic profiles showing concentrations of short-chain fatty acids (SCFA) and lactate across various carbon sources (GOS+BS, hGOS+BS, Lactose) and feeding rates (D = 0.04, 0.08, 0. 12 h'1). FIGS. 6B-6D show Procrustes analysis (PA)2results, illustrating the pairwise comparisons between microbiome and metabolome data collectively. Each data point represents a sample, with different shapes indicating metabolome (dot) and microbiome (square). Lines represent distance or similarity between the two datasets, with longer lines indicating greater dissimilarity. Correlation coefficient (R) and p values were calculated using Spearman Correlation Analysis, with R values indicating similarity, ranging from 0 to 1.

[0030] FIGS. 7A-7B: Representative expenmental design and timeline for evaluating the impact of GOS plus microbial intervention (either as a synthetic consortium or whole stool compositions) on a C. difficile infection model.

[0031] FIG. 8: Growth curves of C. difficile R20291 supplemented with various prebiotics: CDMM-C. difficile minimal media. CDMM-Glu- C. difficile minimal media supplemented with glucose, CDMM-GOS- C. difficile minimal media supplemented with GOS, CDMM-Lac- C. difficile minimal media supplemented with lactose.

[0032] FIG. 9: Changes in alpha diversity in response to diet, FMT / consortium, antibiotics, and C. difficile infection over time.

[0033] FIG. 10: Principal Component Analysis (PC A) and loading plots showing the ordination of samples collected from day 0 to day 7 according to their microbiome profiles. The ellipses represent a 95% confidence interval of samples of the same origin. Loading scores show taxa prevalent in at least 20% of the samples on the first and second principal components.

[0034] FIG. 11: Representative effects of GOS diet on relative abundance at genus level from day 0 to day 7.

[0035] FIG. 12: Principal Component Analysis (PCA) and loading plots showing the ordination of samples collected from day 7 to day 14 according to their microbiome profiles. The ellipses represent a 95% confidence interval of samples of the same origin. Loading scores show taxa prevalent in at least 20% of the samples on the first and second principal components.|0036] FIG. 13: Relative abundance at genus level of mice on control or GOS diet given either no intervention, microbial consortium, or FMT from days 8 to 14 before antibiotic treatment.

[0037] FIG. 14: Principal Component Analysis (PCA) and loading plots showing the ordination of samples collected at day 21 according to their microbiome profiles. The ellipses represent a 95% confidence interval of samples of the same origin. Loading scores show taxa prevalent in at least 10% of the samples on the first and second principal components.

[0038] FIG. 15: Principal Component Analysis (PCA) and loading plots showing the ordination of samples collected at day 23 according to their microbiome profiles. The ellipses represent a 95% confidence interval of samples of the same origin. Loading scores show taxa prevalent in at least 10% of the samples on the first and second principal components.

[0039] FIG. 16: Relative abundance at genus level of mice on GOS diet after antibiotic treatment and C. difficile infection and clearance.|0040] FIG. 17: Relative abundance at genus level of mice on control diet after antibiotic treatment and C. difficile infection and clearance.

[0041] FIG. 18: Relative abundance of C. difficile over time analyzed using 16S rRNA sequencing data.

[0042] FIG. 19: C. difficile clearance documented over time comparing diet. Relative abundance was calculated by taking absolute quantification of C. difficile over total bacterial load using qPCR. Analysis was completed with 2-way, repeated measures, ANOVA model with p-value < 0.05.

[0043] FIG. 20: C. difficile clearance documented over time comparing intervention within each diet. (A) Relative abundance was calculated by taking absolute quantification of C. difficile over total bacterial load using qPCR. Analysis was completed with 2-way, repeated measures, ANOVA model with p-value < 0.05.10044] FIG. 21 : Experimental rationale for using GOS+RDC as prevention method of infection.

[0045] FIGS. 22A-22D: Core species shared among five carbohydrate conditions in infant fecal sample cultures, as well as core species associated with lactose across four different feeding rates (FIG. 22A). In silico exploratory genomics reveals high genetic specialization among the RDC strains (FIG. 22B). The metabolic profile of rationally designed consortia (RDC) closely resembles that of infant fecal cultures with prebiotics in a bioreactor (FIG. 22C). Phylum-level taxonomy of the 16 strains selected for the rationally designed consortia (RDC) (FIG. 22D).

[0046] FIG. 23: Representative experimental design and timeline for evaluating the impact of GOS plus microbial interv ention on a C. difficile infection model.

[0047] FIGS. 24A-24B: Prebiotics + RDC reduced (FIG. 24A) alpha div ersity and (FIG. 24B) the final C. difficile bacterial load.

[0048] FIGS. 25A-25B: Persistence of RDC strains is increased by the GOS diet (FIG. 25 A). High persistence of Bifidobacterium is positively associated with the inhibition of C. difficile colonization, and low C. difficile colonization correlates with a better clearance outcome (FIG. 25B).DETAILED DESCRIPTION

[0049] The present disclosure provides compositions and methods related to fecal persistent microbiome transplant (FPMT). In particular, the present disclosure provides compositions and methods for generating a composition suitable for FMPT from a taxonomically defined bacterial culture composition based on various metabolic indicators.

[0050] As described further herein, embodiments of the present disclosure demonstrate distinct microbial dynamics within natural, complex consortia when cultured with varying carbon sources, which underscores the influence of dietary components on microbial consortium structure and function. Particularly, complex dietary fibers such as galactooligosaccharides (GOS) and human milk oligosaccharides (HMO) have been shown to select for beneficial bacteria able to degrade these compounds with various glycosidic bonds.Such insights are crucial for developing targeted dietary interv entions that could potentially modulate gut microbiota towards health-promoting states.

[0051] Microbial communities underpin essential functions in both natural ecosystems and engineered systems, yet the principles that govern their assembly, stability, and metabolic cross feeding dynamics remain incompletely understood. This is particularly salient in the context of the human gut microbiome, where the dynamic interactions among microbes, host factors, and dietary inputs shape health outcomes from infancy through adulthood. While dietary substrates such as galactooligosaccharides (GOS) and human milk oligosaccharides (HMOs) are recognized as key modulators of microbial consortia, there remains a critical need for controlled, mechanistic studies that dissect how resource type, availability, and system dynamics influence microbial community behavior and function.

[0052] Understanding the assembly and metabolic output of defined microbial consortia is essential for the development of precise strategies to modulate the gut microbiome. In previous work, it was demonstrated that complex, naturally sourced, microbial communities exhibit distinct yet reproducible responses to diverse dietary inputs, highlighting the importance of coupling taxonomic profiling with metabolic output to fully characterize ecosystem behavior. Notably, oligosaccharides such as GOS and HMOs, which contain a variety of glycosidic linkages, selectively enrich for bacteria capable of degrading these substrates, thereby shaping community composition and cross-feeding dynamics.

[0053] Dynamic culturing systems, such as continuous-flow packed-bed bioreactors, enable the establishment of steady-state conditions, allowing for fine-tuned sampling and analysis of microbial interactions under homeostatic growth thus eliminating temporal variability. This approach provides valuable insights into the contributions of metabolically active species and how carbon source identity and dilution rate, an often-overlooked variable, may profoundly impact cross-feeding dynamics and resource competition. Furthermore, steady-state sampling enables robust comparisons of taxonomic and metabolite profiles across environmental conditions, shedding light on mechanisms of ecosystem resilience and reproducibility.

[0054] Embodiments of the present disclosure address a fundamental question in microbial ecology: how do defined microbial consortia assemble, stabilize, and function under varying nutritional and environmental conditions? The concept of Metabolically Cohesive Consortia (MeCoCos) — microbial groups that engage in tightly integrated metabolic interactions — were leveraged to explore how- metabolic complementarity and resource sharing contribute to community resilience and structure.

[0055] Embodiments of the present disclosure include the design and cultivation of a rationally designed 16-member minimal microbial consortium (RDC) derived from assembled communities. Using a packed-bed continuous-flow bioreactor system, this consortium was cultured under multiple dietary regimes — including lactose, GOS, and the HMO disaccharide N-acetyllactosamine (LacNAc) — and at varying dilution rates to simulate shifts in resource abundance and turnover. By integrating real-time monitoring of gas production (e.g., H2, CO2) with steady-state sampling of both metabolite concentrations (lactate, butyrate, acetate, and propionate) and community composition, data demonstrated that community assembly is not only deterministic and reproducible but also conditionally stable, with LacNAc uniquely supporting consistent metabolic output and resilience to increased flow rates. These findings have broad implications for designing robust microbial therapeutics, understanding gut microbiome development in early life, and optimizing synthetic ecosystems for health and biotechnology applications.

[0056] Section headings as used in this section and the entire disclosure herein are merely for organizational purposes and are not intended to be limiting.1. Definitions

[0057] Throughout the specification and claims, the following terms take the meanings explicitly associated herein, unless the context clearly dictates otherwise. The phrase An one embodiment” as used herein does not necessarily refer to the same embodiment, though it may. Furthermore, the phrase '‘in another embodiment” as used herein does not necessarily refer to a different embodiment, although it may. Thus, as described below, various embodiments of the invention may be readily combined, without departing from the scope or spirit of the invention.

[0058] In addition, as used herein, the term “or” is an inclusive “or” operator and is equivalent to the term “and / or” unless the context clearly dictates otherwise. The term “based on” is not exclusive and allows for being based on additional factors not described, unless the context clearly dictates otherwise. In addition, throughout the specification, the meaning of “a,” “an,” and “the” include plural references. The meaning of “in” includes “in” and “on.”

[0059] The transitional phrase “consisting essentially of’ as used in claims in the present application limits the scope of a claim to the specified materials or steps “and those that do not materially affect the basic and novel characteristic(s)” of the claimed invention, as discussed in In re Herz, 537 F.2d 549. 551-52, 190 USPQ 461, 463 (CCPA 1976). For example, a composition “consisting essentially of’ recited elements may contain an unrecited contaminantat a level such that, though present, the contaminant does not alter the function of the recited composition as compared to a pure composition, i.e., a composition “consisting of’ the recited components.

[0060] The term “one or more,” as used herein, refers to a number higher than one. For example, the term “one or more” encompasses any of the following: two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, eleven or more, twelve or more, thirteen or more, fourteen or more, fifteen or more, twenty or more, fifty or more, 100 or more, or an even greater number.

[0061] The term “one or more but less than a higher number,” “two or more but less than a higher number,” “three or more but less than a higher number,” “four or more but less than a higher number,” “five or more but less than a higher number.” “six or more but less than a higher number,” “seven or more but less than a higher number,” “eight or more but less than a higher number,” “nine or more but less than a higher number,” “ten or more but less than a higher number,” “eleven or more but less than a higher number,” “twelve or more but less than a higher number,” “thirteen or more but less than a higher number,” “fourteen or more but less than a higher number,” or “fifteen or more but less than a higher number” is not limited to a higher number. For example, the higher number can be 10,000, 1,000, 100, 50, etc. For example, the higher number can be approximately 50 (e.g., 50, 49, 48, 47, 46, 45, 44, 43, 42, 41, 40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 32, 30, 29, 28, 27, 26. 25. 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8. 7, 6, 5, 4. 3 or 2).

[0062] As used herein, a “diagnostic” test application includes the detection or identification of a disease state or condition of a subject, determining the likelihood that a subject will contract a given disease or condition, determining the likelihood that a subject with a disease or condition will respond to therapy, determining the prognosis of a subject with a disease or condition (or its likely progression or regression), and / or determining the effect of a treatment on a subject with a disease or condition. For example, a diagnostic test can be used for detecting the presence or likelihood of a subject contracting a neoplasm or the likelihood that such a subject will respond favorably to a compound (e.g., a pharmaceutical, e.g., a drug) or other treatment.

[0063] The term “isolated” when used in relation to a nucleic acid, as in “an isolated oligonucleotide” refers to a nucleic acid sequence that is identified and separated from at least one contaminant nucleic acid with which it is ordinarily associated in its natural source. Isolated nucleic acid is present in a form or setting that is different from that in which it is found in nature. In contrast, non-isolated nucleic acids, such as DNA and RNA, are found in the statethey exist in nature. Examples of non-isolated nucleic acids include a given DNA sequence (e.g., a gene) found on the host cell chromosome in proximity to neighboring genes; RNA sequences, such as a specific mRNA sequence encoding a specific protein, found in the cell as a mixture with numerous other mRNAs which encode a multitude of proteins. However, isolated nucleic acid encoding a particular protein includes, by way of example, such nucleic acid in cells ordinarily expressing the protein, where the nucleic acid is in a chromosomal location different from that of natural cells, or is otherwise flanked by a different nucleic acid sequence than that found in nature. The isolated nucleic acid or oligonucleotide may be present in single-stranded or double-stranded form. When an isolated nucleic acid or oligonucleotide is to be utilized to express a protein, the oligonucleotide will contain at a minimum the sense or coding strand (i.e., the oligonucleotide may be single-stranded), but may contain both the sense and anti-sense strands (i.e., the oligonucleotide may be double-stranded). An isolated nucleic acid may, after isolation from its natural or typical environment, be combined with other nucleic acids or molecules. For example, an isolated nucleic acid may be present in a host cell into which it has been placed, e.g., for heterologous expression.

[0064] The term “purified” refers to molecules, either nucleic acid or amino acid sequences that are removed from their natural environment, isolated, or separated. An “isolated nucleic acid sequence” may therefore be a purified nucleic acid sequence. “Substantially purified” molecules are at least 60% free, preferably at least 75% free, and more preferably at least 90% free from other components with which they are naturally associated. As used herein, the terms “purified” or “to purify” also refer to the removal of contaminants from a sample. The removal of contaminating proteins results in an increase in the percent of polypeptide or nucleic acid of interest in the sample. In another example, recombinant polypeptides are expressed in plant, bacterial, yeast, or mammalian host cells and the polypeptides are purified by the removal of host cell proteins; the percent of recombinant polypeptides is thereby increased in the sample. |0065] As used herein, the terms “patient” or “subject” refer to organisms to be subject to various tests described herein. The term “subject” includes animals, preferably mammals, including humans. In a preferred embodiment, the subject is a primate. In an even more preferred embodiment, the subject is a human. Further with respect to diagnostic methods, a preferred subject is a vertebrate subject. A preferred vertebrate is warm-blooded; a preferred warm-blooded vertebrate is a mammal. A preferred mammal is most preferably a human. As used herein, the term “subject” includes both human and animal subjects. Thus, veterinary therapeutic uses are provided herein. As such, the present disclosure provides for the diagnosis of mammals such as humans, as well as those mammals of importance due to being endangered.such as Siberian tigers; of economic importance, such as animals raised on farms for consumption by humans; and / or animals of social importance to humans, such as animals kept as pets or in zoos. Examples of such animals include but are not limited to carnivores such as cats and dogs; swine, including pigs, hogs, and wild boars; ruminants and / or ungulates such as cattle, oxen, sheep, giraffes, deer, goats, bison, and camels; pinnipeds; and horses. Thus, also provided is the diagnosis and treatment of livestock, including, but not limited to, domesticated swine, ruminants, ungulates, horses (including racehorses), and the like. As described further herein, the terms “subject-specific” and “patient-specific” generally refer to a determination made, or an assay performed in a manner that is unique to an individual subject or patient. The terms “subject-specific” and “patient-specific” contrast with a determination made or an assay performed in a manner that is not unique to an individual subject or patient.

[0066] As used herein, the term “information” refers to any collection of facts or data. In reference to information stored or processed using a computer system(s), including but not limited to internets, the term refers to any data stored in any format (e.g. , analog, digital, optical, etc.). As used herein, the term “information related to a subject” refers to facts or data pertaining to a subject (e.g., a human, plant, or animal).

[0067] As used herein, the terms “sample,” “test sample,” and “biological sample” refer to a sample containing or suspected of containing a biomarker of the present disclosure. The sample may be derived from any suitable source. In some cases, the sample may comprise a liquid, fluent particulate solid, or fluid suspension of solid particles. In some cases, the sample may be processed prior to the analysis described herein. For example, the sample may be separated or purified from its source prior to analysis. In a particular example, the source is a mammalian (e.g., human) bodily substance (e.g., bodily fluid, blood such as whole blood, buffy coat, serum, plasma, urine, saliva, sweat, sputum, semen, mucus, lacrimal fluid, lymph fluid, amniotic fluid, interstitial fluid, cerebrospinal fluid, feces, tissue, organ, one or more dried blood spots, or the like). The sample may be a liquid sample or a liquid extract of a solid sample. In some embodiments, the source of the sample may be an organ or tissue, such as a biopsy sample and / or an endoscopic brushing sample (e.g., endoscopic esophageal brushing sample), which may be solubilized by tissue disintegration / cell lysis. Samples can be obtained by any number of methodologies. Cell free or substantially cell free samples can be obtained by subjecting the sample to various techniques including, but are not limited to, centrifugation and filtration.|0068]£Treat,” “treating” or “treatment” are each used interchangeably herein to describe reversing, alleviating, or inhibiting the progress of a disease and / or injury, or one or moresymptoms of such disease, to which such term applies. Depending on the condition of the subject, the term also refers to preventing a disease, and includes preventing the onset of a disease, or preventing the symptoms associated with a disease. A treatment may be either performed in an acute or chronic way. The term also refers to reducing the severity of a disease or symptoms associated with such disease prior to affliction with the disease. Such prevention or reduction of the severity of a disease prior to affliction refers to administration of a pharmaceutical composition to a subject that is not at the time of administration afflicted with the disease. “Preventing’’ also refers to preventing the recurrence of a disease or of one or more symptoms associated with such disease. “Treatment” and “therapeutically,” refer to the act of treating, as “treating” is defined above.

[0069] Preferred methods and materials are described below, although methods and materials similar or equivalent to those described herein can be used in practice or testing of the present disclosure. All publications, patent applications, patents and other references mentioned herein are incorporated by reference in their entirety. The materials, methods, and examples disclosed herein are illustrative only and not intended to be limiting.2. Compositions and Methods

[0070] Embodiments of the present disclosure provide compositions and methods related to fecal persistent microbiome transplant (FPMT). In particular, the present disclosure provides compositions and methods for generating a composition suitable for FMPT from a taxonomically defined bacterial culture composition based on various metabolic indicators.|0071] In accordance with these embodiments, experiments were conducted to understand how dietary' carbon inputs shape microbial community assembly and function is essential for designing targeted microbiome interventions. Embodiments of the present disclosure leveraged a defined 16-strain minimal microbial consortium, cultured in a continuous packed-bed bioreactor system, to investigate how dietary fiber complexity and nutrient flux shape microbial community assembly and function. By systematically varying carbon source structure and dilution rate, early-life gut ecological dynamics were emulated and species-specific and community-level responses to human milk oligosaccharides (HMOs) and galactooligosaccharides (GOS) were elucidated. These fibers have been extensively shown to enhance the proliferation of Bifidobacteria and other beneficial microbes, substantiating their application in diet-based modulation of gut health to mitigate symptoms concomitant with inflammatory’ bowel disease. Crohn's disease, and colorectal cancer.

[0072] Results of the present disclosure demonstrated that both the biochemical complexity of dietary carbohydrates and the rate of nutrient deliver}’ are critical determinants of microbial community structure. Notably, consortia fed human milk oligosaccharides containing N- acetyllactosamine (LacNAc) (hGOS+BS) exhibited greater structural variability across dilution rates than those fed GOS+BS or lactose. Principal coordinate analyses (PCoA) confirmed clustering of community structures according to carbon source, and PERMANOVA testing revealed statistically significant differences in community composition across feeding rates. These findings suggest that LacNAc induces selective pressures that reshape microbial communit ' dynamics, potentially through competition for complex substrates and altered metabolic cross-feeding.

[0073] Indeed, microbial communities assembled under hGOS+BS conditions bore compositional resemblance to breastfed infant gut microbiomes, which are typically dominated by Bifidobacteria and other HMO-utilizing taxa prior to the introduction of solid foods where Bacteroidota and Clostridia flourish due to a more complex diet. However, the consortia within the hGOS+BS conditions exhibited variable species coexistence patterns across each dilution rate increase compared to those receiving simpler substrates demonstrating the species-specific impact of LacNAc on consortium structure assembly (FIG. 4).

[0074] As described further herein, dilution rate was found to modulate the degree of divergence between consortia, with the greatest structural differences observed at the highest (D = 0.12 h’1) and lowest (D = 0.04 h-1) dilution rates. The intermediate rate (D = 0.08 h-1), corresponding to a 12.5-hour retention time, yielded the least significant differences, suggesting it may represent a metabolic intermediate where nutrient flux supports both growth and functional coexistence. These findings resonate with ecological principles of resource limitation and competition where both starvation and overabundance can destabilize microbial systems. Beta dispersion analyses further revealed that consortia fed hGOS + BS showed increased variability across dilution rates, while those fed GOS + BS and lactose remained more consistent. This suggests LacNAc not only promotes selective enrichment of specialized taxa but also disrupts metabolic interdependencies that otherwise stabilize the community under simpler carbon regimes.

[0075] Despite compositional differences, short chain fatty acids (SCFA) profiles across all conditions revealed a conserved functional signature dominated by acetate, with relatively stable butyrate levels. This suggests a degree of functional redundancy within the consortium, wherein distinct microbial configurations can reproduce similar metabolic outputs. However, significant shifts in lactate and propionate production under higher dilution rates in lactose andhGOS + BS conditions highlight metabolic sensitivity to both carbon complexity and turnover rate, with potential implications for host health given the role of these metabolites in gut physiology. Particularly the presence of bile salts, intended to mimic the small intestinal conditions, likely altered key-cross-feeding networks by selectively inhibiting sensitive species or promoting competitive exclusions. This may have cascading effects on downstream metabolite production and overall community resilience. However, Procrustes analysis revealed only moderate alignment between community structure and metabolite profiles, indicating taxonomic shifts alone are insufficient to predict functional outcomes. This further supports the need for integrated omics approaches to fully understand the emergent behavior of microbial consortia.

[0076] The discrete climax communities observed in hGOS+BS conditions further illustrate how substrate complexity can narrow the pool of successful colonizers, reducing network -wide metabolic exchange. These dynamics echo findings from broader ecological studies, where high substrate specialization can either enhance or fragment community stability depending on interaction strength and niche overlap.

[0077] The data described herein align with the concept of metabolically cohesive consortia (MeCoCos), which are thought to achieve stability' through tightly interlinked metabolic interactions rather than shared environmental pressures alone. Cross-feeding, critical for sustaining diversity and stability in complex microbiomes, was particularly sensitive to substrate type and availability in the culturing system. For instance, while B. breve declined under LacNAc-rich conditions (consistent with its limited HMO-utilization capacity), Bifidobacterium bifidum increased at higher dilution rates, likely reflecting asymmetric resource competition. The pangenome analysis supports these dynamics, showing that B. bifidum harbors 0-galactosidases suited for HMO breakdown, whereas B. breve possesses 0- glucosidases better suited for simpler oligosaccharides. These functional distinctions not only explain relative abundance patterns but also echo prior findings where B. breve benefits from degradation products generated by other species like B. bifidum or B. longum subsp. infantis — highlighting the importance of metabolic interdependence in consortium stability. These findings underscore the non-stochastic nature of community assembly, especially in early -life contexts where priority effects and interspecies facilitation can have long-lasting impacts on microbiome development.

[0078] Minimal consortia have been utilized in gut microbiome studies as both models for studying microbe-microbe interactions and host-microbe interactions making them a valuable, robust tool for exploring the intricacies within a complex system for broader human healthapplications. Minimal consortia can serve several applications to model several gut-associated interactions depending on the strategy employed for strain selection prior to pooling strains together. Strategies for strain selection in designing a minimal consortium can adopt either a top-down approach based on the most abundant bacterial taxa identified in the native microbiota or a bottom-up function-oriented selection which focuses on assessing individual strain functionality to achieve a compound, specific emergent consortium function. These strategies can model global consortium interactions or global consortium functionality.

[0079] In accordance with the above, results of the present disclosure emphasize the importance of selecting appropriate carbon sources and adjusting feeding rates to tailor the in vitro cultivation of gut microbiota for specific research or therapeutic outcomes. Furthermore, the use of a packed bed bioreactor (PBR) system in the experiments facilitated the emulation of gut conditions, enhancing the ability to maintain and study microbial consortia that are typically challenging to culture. This system proved essential for observing the dynamic interactions and stability of the consortium under vary ing nutritional and operational conditions.

[0080] In accordance with these embodiments, the present disclosure provides a method of generating a composition for fecal persistent microbiome transplant (FPMT) (also referred to as fecal microbiota transplantation or FMT). In some with these embodiments, the method includes inoculating a bioreactor with a defined culture composition, wherein the defined culture composition comprises a bacterial population, and a carbon source comprising a plurality of carbohydrates; culturing the defined culture composition according to a set of culture conditions comprising defined taxonomic proportions of bacteria in the bacterial population, an adjusted feeding rate, and adjusted retention time; and assessing at least one metabolic indicator at at least one timepoint during the culturing of the defined culture composition. In some embodiments, the at least one indicator indicates that the defined culture composition is suitable for FPMT.

[0081] In some embodiments, the bacterial population is obtained from one or more donors prior to culturing. In some embodiments, the bacterial population is obtained from a synthetic bacterial culture prior to culturing.

[0082] In some embodiments, bacterial population comprises one or more of the following: Bacteroidotci, Clostridia, Negativicutes, Lactobacillales, Erysipelotrichia, Actinomycetota, and / or Pseiidomonadota.|0083] In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 5% to about 15% Bacteroidota. In some embodiments, the defined taxonomicproportions of the bacteria comprise from about 5% to about 10% Bacteroidota. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 10% to about 15% Bacteroidota. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 7% to about 12% Bacteroidota.10084] In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 10% to about 30% Clostridia. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 10% to about 20% Clostridia. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 10% to about 15% Clostridia. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 15% to about 30% Clostridia. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 20% to about 30% Clostridia. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 15% to about 20% Clostridia.

[0085] In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 1% to about 10% Negativicutes . In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 1% to about 5% Negativicutes . In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 5% to about 10% Negativicutes. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 3% to about 7% Negativicutes.

[0086] In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 10% to about 35% Lactobacillales. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 10% to about 25% Lactobacillales. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 10% to about 15% Lactobacillales. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 15% to about 35% Lactobacillales. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 25% to about 35% Lactobacillales. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 15% to about 30% Lactobacillales . In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 20% to about 25% Lactobacillales .

[0087] In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 1% to about 10% Erysipelotrichia. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 1% to about 5% Erysipelotrichia. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 5% toabout 10% Erysipelotrichia. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 3% to about 7% Erysipelotrichia.

[0088] In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 5% to about 25% Actinomycetota. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 5% to about 15% Actinomycetota. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 15% to about 25% Actinomycetota. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 10% to about 20% Actinomycetota.

[0089] In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 5% to about 15% Pseudomonadota. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 5% to about 10% Pseudomonadota. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 10% to about 15% Pseudomonadota. In some embodiments, the defined taxonomic proportions of the bacteria comprise from about 7% to about 12% Pseudomonadota.

[0090] In some embodiments, the plurality of carbohydrates comprises galactooligosaccharides (GOS) and / or lactose. In some embodiments, the plurality of carbohydrates comprises galactooligosaccharides (GOS). In some embodiments, the plurality of carbohydrates comprises lactose. In some embodiments, the GOS is humanized GOS (hGOS). In some embodiments, the plurality of carbohydrates further comprises N- Acetyllactosamine (LacNAc) and / or a bile salt. In some embodiments, the bile salt comprises one or more of cholic, deoxy cholic, chenodeoxy cholic, and / or lithocholic acids.

[0091] In some embodiments, the adjusted feeding rate ranges from about 0.04 h'1to about 0.12 h’1. In some embodiments, the adjusted feeding rate ranges from about 0.04 h'1to about0.08 h'1. In some embodiments, the adjusted feeding rate ranges from about 0.08 h’1to about0.12 h’1. In some embodiments, the adjusted feeding rate ranges from about 0.06 h-1to about0.10 h’1. In some embodiments, the adjusted feeding rate ranges from about 0.08 h"1to about0.08 h’1.

[0092] In some embodiments, the adjusted retention time ranges from about 5 hours to about 30 hours. In some embodiments, the adjusted retention time ranges from about 5 hours to about 25 hours. In some embodiments, the adjusted retention time ranges from about 5 hours to about 20 hours. In some embodiments, the adjusted retention time ranges from about 5 hours to about 15 hours. In some embodiments, the adjusted retention time ranges from about 5 hours to about 10 hours. In some embodiments, the adjusted retention time ranges from about 10 hours to about 30 hours. In some embodiments, the adjusted retention time ranges from about 15 hoursto about 30 hours. In some embodiments, the adjusted retention time ranges from about 20 hours to about 30 hours. In some embodiments, the adjusted retention time ranges from about 25 hours to about 30 hours. In some embodiments, the adjusted retention time ranges from about 10 hours to about 15 hours. In some embodiments, the adjusted retention time ranges from about 15 hours to about 25 hours. In some embodiments, the adjusted retention time ranges from about 10 hours to about 20 hours.

[0093] In some embodiments, the at least one metabolic indicator comprises carbon dioxide and / or hydrogen concentration. In some embodiments, the at least one metabolic indicator comprises carbon dioxide concentration. In some embodiments, the at least one metabolic indicator comprises hydrogen concentration. In some embodiments, the adjusted feeding rate ranges from about 0.04 h1to about 0.12 h1. In some embodiments, the adjusted feeding rate ranges from about 0.04 h'1to about 0.08 h’1. In some embodiments, the adjusted feeding rate ranges from about 0.08 h'1to about 0.12 h'1. In some embodiments, the adjusted feeding rate ranges from about 0.06 h'1to about 0.10 h’1. In some embodiments, the adjusted feeding rate ranges from about 0.08 h'1to about 0.08 h’1.]0094] In some embodiments, the at least one metabolic indicator comprises a short-chain fatty acid (SCFA). In some embodiments, the SCFA is acetate, propionate, and / or butyrate. In some embodiments, acetate ranges from about 5% to about 15%. In some embodiments, acetate ranges from about 5% to about 10%. In some embodiments, acetate ranges from about 10% to about 15%. In some embodiments, propionate ranges from about 0.5% to about 5.0%. In some embodiments, propionate ranges from about 1.5% to about 5.0%. In some embodiments, propionate ranges from about 2.5% to about 5.0%. In some embodiments, propionate ranges from about 0.5% to about 4.0%. In some embodiments, propionate ranges from about 0.5% to about 2.5%. In some embodiments, propionate ranges from about 0.5% to about 1.5%. In some embodiments, propionate ranges from about 1.0% to about 3.0%. In some embodiments, butyrate ranges from about 0.1% to about 1.0%. In some embodiments, butyrate ranges from about 0.5% to about 1.0%. In some embodiments, butyrate ranges from about 0.1% to about 0.5%. In some embodiments, butyrate ranges from about 0.3% to about 0.7%.

[0095] In some embodiments, the at least one metabolic indicator comprises lactate at a range of about 0. 1% to about 5.0%. In some embodiments, the at least one metabolic indicator comprises lactate at a range of about 1.0% to about 5.0%. In some embodiments, the at least one metabolic indicator comprises lactate at a range of about 2.5% to about 5.0%. In some embodiments, the at least one metabolic indicator comprises lactate at a range of about 0.1% to about 4.0%. In some embodiments, the at least one metabolic indicator comprises lactate ata range of about 0. 1 % to about 2.5%. In some embodiments, the at least one metabolic indicator comprises lactate at a range of about 1.0% to about 3.0%.

[0096] In some embodiments, culturing comprises adding a carbohydrate feed composition according to the adjusted feeding rate. In some embodiments, the carbohydrate feed composition comprises lactose, sucrose, GOS, hGOS, and / or a bile salt (e.g., one or more of cholic, deoxy cholic, chenodeoxy cholic, and / or lithocholic acids). In some embodiments, the carbohydrate feed composition comprises lactose. In some embodiments, the carbohydrate feed composition comprises sucrose. In some embodiments, the carbohydrate feed composition comprises GOS. In some embodiments, the carbohydrate feed composition comprises hGOS. In some embodiments, the carbohydrate feed composition comprises a bile salt (e.g., one or more of cholic, deoxy cholic, chenodeoxy cholic, and / or lithocholic acids).

[0097] In some embodiments, the method further comprises transplanting the defined culture composition into a human subject after assessing at least one metabolic indicator. In some embodiments, transplantation of the defined culture composition into the human subject produces a metabolically stable and persistent microbial consortia.

[0098] In some embodiments, transplantation of the defined culture composition into the human subject treats and / or prevents an immune disorder or condition. In some embodiments, the immune disorder or condition comprises at least one of Addison disease, celiac disease, dermatomyositis, Graves' disease, Hashimoto thyroiditis, inflammatory bowel disease, Crohn’s disease, ulcerative colitis, multiple sclerosis, Myasthenia gravis, pernicious anemia, reactive arthritis, rheumatoid arthritis, Sjogren syndrome, Systemic lupus erythematosus (lupus), and / or Type I diabetes. As would be recognized by one of ordinary' skill in the art, the methods and compositions of the present disclosure can be adjusted to treat and / or prevent other immune disorders or conditions.

[0099] In some embodiments, transplantation of the defined culture composition into the human subject treats and / or prevents an infection. In some embodiments, the infection is a bacterial infection, a fungal infection, or a viral infection. In some embodiments, the bacterial infection is caused by Clostridioides difficile. Salmonella, E. coli, Campylobacter, Shigella, Staphylococcus, and / or Clostridium. As would be recognized by one of ordinary skill in the art, the methods and compositions of the present disclosure can be adjusted to treat and / or prevent other types of infections caused by various other pathogenic organisms.

[0100] Embodiments of the present disclosure also include a method of treating or preventing an immune disorder and / or infection in a subject. In accordance with these embodiments, the method includes generating a composition for fecal persistent microbiometransplant (FPMT) by inoculating a bioreactor with a defined culture composition, wherein the defined culture composition comprises a bacterial population, and a carbon source comprising a plurality of carbohydrates; culturing the defined culture composition according to a set of culture conditions comprising defined taxonomic proportions of bacteria in the bacterial population, an adjusted feeding rate, and adjusted retention time; assessing at least one metabolic indicator at at least one timepoint during the culturing of the defined culture composition; wherein the at least one indicator indicates that the defined culture composition is suitable for FPMT; and transplantation of the defined culture composition into the human subject, thereby treating or preventing the immune disorder and / or infection.

[0101] In some embodiments, the immune disorder comprises at least one of Addison disease, celiac disease, dermatomyositis. Graves' disease, Hashimoto thyroiditis, inflammatory bowel disease, Crohn’s disease, ulcerative colitis, multiple sclerosis, Myasthenia gravis, pernicious anemia, reactive arthritis, rheumatoid arthritis, Sjogren syndrome, Systemic lupus erythematosus (lupus), and / or Type I diabetes. As would be recognized by one of ordinary skill in the art. the methods and compositions of the present disclosure can be adjusted to treat and / or prevent other immune disorders or conditions.

[0102] In some embodiments, the infection is a bacterial infection, a fungal infection, or a viral infection. In some embodiments, the bacterial infection is caused by Clostridioides difficile, Salmonella, E. coli, Campylobacter, Shigella, Staphylococcus, and / or Clostridium. As would be recognized by one of ordinary skill in the art. the methods and compositions of the present disclosure can be adjusted to treat and / or prevent other types of infections caused by various other pathogenic organisms.3. Materials and Methods

[0103] Experimental Design. The assembly process of the rationally designed consortium was assessed by taking a similar experimental approach that replicates the conditions of the ex vivo conditions reported previously. The curated consortium was cultured independently in three minimally defined growth mediums enriched with various carbon sources including lactose and a combination of galacto-oligosaccharides (GOS) and bile salts (GOS+BS). further enriched with LacNAc (hGOS+BS). After a 24-hour batch period following inoculation, medium feeding was initiated. Dynamic operation was maintained with incremental feeding rates set at 0.04, 0.08, and 0.12 h’1, chosen to mirror infant colonic transit times and ensure physiological relevance. These rates correspond to retention times of 25. 12.5. and 8.3 hours, respectively, crucial for species adaptation and consortium stability', as longer doubling timesmay lead to washout phenomena. To mitigate washout phenomena, porous glass beads were used as the PBR packing material to emulate the gastrointestinal tract's high surface area to promote species retention and nutrient transformation. Triplicate sampling at each steady state achieved in each feeding rate condition yielded 54 samples, analyzed via 16S rRNA amplicon sequencing and targeted SCFA metabolic analysis. Steady state was confirmed by implementing inline gas measurement detectors and gas chromatography to monitor real-time generation and stabilization of hydrogen (H2) and carbon dioxide (CO2) production.

[0104] Inoculum preparation. FIG. 2 displays the strains included in the pooled inoculum. Strains were either purchased from American Type Culture Collection (ATCC; Manassas, Virginia, USA) or BEI Resources (Manassas, Virginia, USA). Additionally, the Microbiome Core at University of North Carolina at Chapel Hill generously provided strains from the Azcarate-Peril Microbiome Culture Collection (AMC) that were fully classified and sequenced. Pure cultures were cultivated anaerobically in MRS (BD Difco™ Lactobacilli MRS Broth Catalog # 288130) or M17 (BD Difco™ M17 Broth Catalog # 218561) media supplemented with 1% glucose except for Akkermansia muciniphila which was cultured in the presence of 2 g L1porcine mucin (CAS 84082-64-4; Sigma-Aldrich Catalog # M2378), and Lactobacillaceae strains and Escherichia coli that were cultured aerobically at 37 °C. Anaerobic cultures were maintained in a Coy anaerobic chamber (Coy Laboratory Products, Inc, Michigan, USA) under an anaerobic gas mix (5% CO2, 10% H2, 85% N2). Cell banks were generated by centrifuging 50 mL of mid-log cultures at 10.000 rpm for 10 min prior to resuspending cells in 10 mL of respective media supplemented with 0.5% glycerol. Resuspended cells were aliquoted into three 1 mL master cell stocks and ten 0.5 mL working stocks for storage at -80 °C. The remaining concentrated culture was used to perform plate counting to determine viability prior to freezing. The final sixteen species inoculum was generated by pooling a 0.5 mL working stock of each strain under strictly anaerobic conditions and aliquoted to eight 1 mL stocks for use of a standardized inoculum in each experiment.

[0105] Packed-Bed Reactor Setup. The bioreactors consisted of custom-made water- jacketed glass reactor vessels (6.5 cm internal diameter x 23.5 cm height, 600 mL volume; manufactured by Quark Glass, New Jersey, USA) connected to Biostat B-Plus control units (Sartorius Stedim Biotech S. A., Germany). The reactor vessels were packed with porous glassfoam beads 4-8 mm diameter (Dennert Poraver GmbH, Schlusselfeld, Germany) to provide the system with a high surface area and low metabolic gas retention. A recirculation loop was added to the system to facilitate homogeneous mixing, which increased the total volume to 620 mL. This recirculation loop contained a sampling port, a connector through which fresh mediawas fed, and a connector through which a 10% NaOH solution was provided to control pH. The porosity of the packed bed was 40%, and the active volume of the entire system was 350 mL. The ascending velocity of the recirculation loop in the reactor was 281.7 cm h’1, indicating a very well-mixed system. Before inoculation into bioreactors, the medium was depleted of oxygen to allow for the proliferation of anaerobic and slow-growing organisms by stripping the reactor headspace and recirculating sterile media with nitrogen gas. When sampling from the bioreactor, fifteen mL of liquid were sampled from a port in the recirculation loop of the reactor. Samples were mixed thoroughly, and 1.5 mL aliquots were placed into 2 mL microcentrifuge tubes and centrifuged at 10,000 x g for 2 min. The supernatants were transferred to a 2 mL vial for HPLC analysis, and pellets were stored at -80 °C for subsequent microbiome analysis.

[0106] PBR Culture Medium. The basal medium used in this study contained 10 g L'1yeast extract (BD Bacto, Lot # 6088514; Becton, Dickenson & Co.), 0.05 g L'1MgSO47H2O, 2.5 g L'1(NH4)2HPO4, and 0.005 g L'1MnSO4H2O. The carbohydrate compositions were always added at a final concentration of 20 g L'1. The evaluated carbohydrate sources were lactose, glucose, and galacto-oligosaccharides (GOS) (Oligomate. Yakult Pharmaceutical Industry Co., Ltd.). Two additional experiments were performed with GOS (Oligomate) and hGOS (Oligomate containing 1.2 g L'1LacNAc) where 0.4 g L'1of bile salts #3 (45-55% sodium cholate, 45-55% sodium deoxycholate, Hardy Diagnostics) were added to the culture medium (bile salt composition confirmed viaNMR analysis. METRIC at NC State University, data not shown).

[0107] Targeted Metabolite and Gas Analysis. Molecular gases, namely CO2and H2 generated by the consortium were continuously monitored in line with an ABB (EL3020; Zurich. Switzerland) gas analyzer and a Pfeiffer Omnistar (Pfeiffer Vacuum. USA) mass spectrometer connected in series. Nitrogen was supplied into the system at a rate of 0.208 L min'1and used to maintain anaerobiosis and as a stripping carrier gas. The system was determined to be at a steady state when the values of the in-line gas measurements remained stable for at least three retention times. Steady-state was corroborated by the compositional stability of short-chain fatty acids (SCFAs: acetate, propionate, and butyrate) and lactate. Measurements of targeted metabolites were performed by HPLC (Agilent 1100 chromatograph) with a refractive index detector under isocratic conditions. Metabolite separation was performed using 5mM H2SO4 at 0.5 mL min'1with a Phenomenex Rezex ROA column at 65 °C.

[0108] DNA Isolation and 16S rRNA Gene Amplicon Sequencing. DNA Isolation was performed as described previously. A total of 12.5 ng of DNA was used for 16S rRNA gene amplicon sequencing. Total DNA was amplified using universal primers targeting the V4 region of the bacterial 16S rRNA gene as described. Primer sequences contained overhang adapters appended to the 5’ end of each primer for compatibility' with the Illumina sequencing platform. The primers used were F515 / R806. Each 16S rRNA gene amplicon was purified using the AMPure XP reagent (Beckman Coulter. Indianapolis. IN). In the next step, each sample was amplified using a limited cycle PCR program, adding Illumina sequencing adapters and dual-index barcodes (index l(i7) and index 2(i5)) (Illumina, San Diego, CA) to the amplicon target. The final libraries were again purified using the AMPure XP reagent (Beckman Coulter), quantified, and normalized before pooling. The DNA library pool was then denatured with NaOH, diluted with hybridization buffer, and heat-denatured before loading on the MiSeq reagent cartridge (Illumina) and the MiSeq instrument (Illumina). Automated cluster generation and paired-end sequencing with dual reads were performed according to the manufacturer’s instructions.

[0109] Sequence Analysis. Sequence analysis including Chimera removal. Operational Taxonomic Unit (OTU) clustering, taxonomy assignments, and phylogenetic tree construction was performed in QIIME2 (v2019.10; qiime2.org). Sequence reads were analyzed without using the DADA2 algorithm to filter sequences. Instead, sequences were demultiplexed, j oined, and dereplicated using the q2 vsearch plugin and subsequently filtered with the q2 quality -filter q-score algorithm using default parameters. OTU clustering using an open-reference approach at 97% identity and subsequently was used for taxonomic classification. Taxonomy was assigned using a custom feature classifier that was trained using the q2-feature-classifier function in QIIME2 using the full 16S rRNA sequence data extracted from whole genome datasets for each strain included in the inoculum. Briefly, a Naive Bayes classifier was trained on reference sequences that were extracted at the appropriate primer sites and matching taxonomic classification based on the defined number of species included in the inoculum. Taxonomy was assigned using the classify-skleam algorithm. Phylogenetic trees were generated from representative sequences aligned using the Multiple Alignment using Fast Fourier Transform (MAFFT) program, and a tree was generated from this alignment using the FastTree algorithm. Finally, the final tree was visualized and annotated using the Interactive Tree of Life browser tool.|0110] Pan-genomics Analyses. Core microbiome analysis was performed using the Microbiome R package. Functional genomic analysis was performed using Anvio to create apan-genome analysis using the whole genomes of each of the included strains of the RDC. Anvio utilizes the Clusters of Orthologous Genes (COG) database to functionally assign genes.

[0111] Statistical Analysis. All statistics and graphing were performed in R (R Version 2023.12.1) unless otherwise noted. Taxonomy and OTU tables generated from QIIME2 were used as inputs for the phyloseq object in R. Statistical analyses involved ANOVA tests followed by Tukey’s HSD for means comparisons. Beta diversity statistics were performed using the PERMANOVA and PERMDISP functions of the vegan package in R. Unless otherwise noted, the alpha for all statistical tests was fixed at 0.05. Relative abundance data was transformed, and taxa agglomerated to the species level using the phyloseq package in RStudio prior to extracting the table and graphing in Origin Pro 2015 (OriginLab Corporation, Northampton, MA). Procrustes analysis (PA)2evaluating dissimilarities between microbiome and matching metabolome was conducted using Microbiome and Metabolome data integration analysis (M2IA) which measures the congruence of 2D data by superimposing and scaling two separate PCA models.

[0112] Animal housing, treatment, and sample collection. The Institutional Animal Care and Use Committee (1ACUC) of the University of North Carolina at Chapel Hill approved all animal experiments (Approved protocol number 22-038.0). The experiment included 48 female C57BL / 6J SPF mice aged 4-6 weeks from Jackson Labs. The experimental design is shown in FIGS. 7A-7B. During the standardization period, all mice were fed a control diet (D17121301; Research Diets INC) for two weeks. After the standardization period, mice were divided into two diet groups: one half continued the control diet, while the other half were fed a diet supplemented with GOS (D17121302; Research Diets INC.), which replaced 71.8 g of cellulose with 71.8 g of highly pure GOS per kilogram. The highly pure GOS (90% GOS, 10% lactose) used in this study was generated by standard transgalactosylation reactions as described previously. Animals remained on their respective diets until euthanized at the end of the experiment. A bacterial consortium or FMT interventions were administered to animals on days 7, 19, and 23 during the study. Antibiotics were administered through drinking water on day 14 through day 17, followed by an intraperitoneal injection of clindamycin on day 19 before C. difficile infection. Each mice group (N=48) was divided into four subgroups, which either received FMT-control (feces pooled from mice in the control diet), FMT-GOS (feces pooled from mice in the GOS diet) or no treatment (control). All mice were infected with 5 x 104spores of C. difficile R20291 on day 22. Fecal samples were collected at various time points and stored at -80°C. Blood samples were collected on day 31 after administration of the FITC- Dextran assay for intestinal permeability assessment and stored at -80°C.

[0113] C. difficile infection mouse model. Infection with C. difficile was carried out as described previously. Mice were treated with an oral antibiotic cocktail that included kanamycin (400 mg / L), gentamycin (35 mg / mL), colistin (44.74 mg / L), vancomycin (45 mg / L), and metronidazole (215 mg / L) (Central Compounding Center South). The antibiotics were dissolved in water, filtered sterilized, and administered through drinking water for three days (day 14-17). Mice received an intraperitoneal injection of clindamycin (10 mg / kg of mouse weight) before administration of 5 x 104CFU of C. difficile R20291.

[0114] Intestinal permeability assay. The permeability assay w as performed as described previously. Mice received 100 mg of 4kDa FITC-dextran / lOOg of body weight 4 h before sacrifice by gavage. After sacrifice, blood samples w ere collected via cardiac puncture, and serum was separated by centrifugation. The serum was assessed for fluorescence with a TEC AN Infinite M200 plate reader using an excitation wavelength of 485nm and an emission wavelength of 528nm. Analysis was completed by comparing it to a standard curve of FITC dextran. Statistical analysis of the FITC-dextran assay w as performed with tw o-w ay ANOVA uncorrected Fisher’s LSD test. Bar plots and line plots were generated in Prism GraphPad 10.

[0115] C. difficile growth curves. C. difficile R20291 was routinely cultured in brain heart infusion (BHI) medium, supplemented with yeast extract (5 g / L) and cysteine (2.5 g / L), in a 37°C anaerobic chamber with an atmosphere of 85% N2, 10% CO2, 5% H2. To assess growth in GOS as a carbohydrate source, C. difficile was grown in minimal media CDMM (Cartman6 Minton, 2010), supplemented with glucose, lactose, or GOS at a 1% concentration. Optical density (OD) values were measured at 600 nm on a plate reader, and growth rates were calculated with a simple linear regression model.

[0116] Bacterial consortium. Collaborators at NC State University designed and generated a synthetic bacterial consortium based on previous proportions identified from infant feces pooled from four healthy infants under the age of one (unpublished data), which was used in this study.

[0117] Fecal microbiota transplantation. Fresh fecal pellets w ere collected between 0 and7 days on either the control or GOS diets and stored at -80 °C. On the day of the challenge, frozen fecal pellets from each diet were thawed, pooled, resuspended in PBS (10 mg / mL of PBS), and homogenized. Mice received 100 of the pooled feces by orogastric gavage at each intervention day.

[0118] DNA isolation. DNA isolation from stool samples was performed as previously described. Fecal samples were transferred to 2 ml tubes containing 200 mg of 106 / 500pm glass beads (Sigma, MO, USA) and 0.5 ml of Qiagen PM1 buffer (Valencia, CA, USA). Mechanicallysis was performed on a Digital Vortex Mixer. After a 5-minute centrifugation, 0.45 mL of supernatants were aspirated, transferred to a new tube containing 0.15 ml of Qiagen IRS solution, and incubated at 4°C overnight. After a 5-minute centrifugation, the supernatant was aspirated and transferred to deep well plates containing 0.45 ml of Qiagen binding buffer supplemented with Qiagen ClearMag Beads. DNA was purified using the automated Kingfisher™ Flex Purification System, eluted in DNase-free water, and subsequently used for 16S rRNA amplicon sequencing and qPCR for C. difficile quantification.

[0119] 16S rRNA amplicon sequencing. Amplicon sequencing was performed as described previously. Total DNA was subject to amplification of the V4 region of the 16S rRNA gene using primers (515F-806R) with Illumina adaptors. Amplicons were barcoded using Illumina dual-index barcodes (Index 1 (i7) and Index 2(i5)), purified using Agencourt® AMPure® XP Reagent (Beckman Coulter, Brea, CA, USA) and quantified with Quant-iT™ PicoGreen® dsDNA Reagent (Molecular Probes, Thermo Fisher Scientific, MA, USA). Libraries were pooled in equimolar amounts and sequenced on NovaSeq (Illumina, San Diego, CA, USA).

[0120] Bioinformatic analysis of 16S rRNA amplicon sequencing data. Sequencing output from the Illumina platform was converted to fastq format and demultiplexed using Illumina BCL Convert 4.2.4 (BCL Convert v. 4.2.4. (2023) Illumina, Inc. San Diego, CA, USA). Quality control of the demultiplexed sequencing reads was verified by FastQC (FastQC 0.11.8. (2018) Babraham Institute. Cambridge, UK). Adapters were trimmed using Trim Galore (Trim Galore (2017) Babraham Institute. Cambridge, UK) The resulting paired-end reads were submitted to Kraken2 for taxonomic classification. An estimate of taxonomic composition, including host, was produced from these results using Bracken 2.5. The resulting non-host paired-end reads were processed with the QIIME 2 2022-2 wrapper for DADA2, including merging paired ends, quality filtering, error correction, and chimera detection. Amplicon sequencing units from DADA2 were assigned taxonomic identifiers with respect to the Silva 138 database. Alpha diversity (Evenness and Faith PD) was estimated using QIIME 2 at a rarefaction depth of 5,000 sequences per subsample. Beta diversity' estimates were calculated within QIIME 2 at a subsampling depth of 5,000. Aggregate differential abundance was estimated with ALDEx2 ANCOM-BC and MaAsLin2 on genera with a minimum abundance of 5.000 reads and minimum prevalence of 20%. 16S rRNA sequencing data visualization was performed using Qiime 2.0.

[0121] Quantitative Polymerase Chain Reaction (qPCR). Two standard curves were used to calculate the absolute abundance of C. difficile and total bacterial DNA. and the relative abundance of C. difficile was calculated by taking pathogen by total bacterial load. lOng / pl ofC. difficile genomic DNA and the ZymoBIOMICS Microbial Community DNA Standard (Zymo Research, NC, USA) as control, and target-specific primers were used for standard curve amplification reactions. The 50 pl reaction mix consisted of 25 pl KAPA HotStart High Fidelity Master Mix, 20 pl of the primer mix (1 nmol), and 5 pl DNA template. The thermal cycler was set for initial denaturation at 95°C for 3 min, 30 cycles of (95°C for 20 sec, 60°C for 20 sec, 72°C for 30 sec), and a final extension at 72°C for 3 min. Amplicons were run on a 1% agarose gel, and single bands were purified using the QiaQuick gel extraction kit (Qiagen, Santa Clarita, CA, USA). Concentrations were quantified using the QuantIT PicoGreen dsDNA reagent kit. Copy numbers were calculated, and each sample was diluted based on copy numbers for standards in qPCR reactions, starting at 100 copies and increasing by 10-fold to 100,000,000 copies. Standard curves were freshly prepared for each qPCR reaction and run in triplicates.|0122] DNA extracted from fecal samples was normalized to 1.7 ng / pl. qPCR was conducted using a QuantStudio Q6 instrument (Applied Biosystems, MA, USA). Each 10 pl reaction contained: 1 pl of normalized sample DNA, 0.4 pM of final primer concentration of tcdAqF and tcdAqR. and 5 pl of PowerSybr qPCR master mix (Thermo Fisher Scientific. MA, USA) for absolute quantification of C. difficile. The same procedure was implemented with 16S Universal V4F and 16S Universal V4R primers. Absolute quantification was determined by comparing against a generated standard curve, for both sets of primers, under the following cycling conditions: 50°C for 2 min, followed by 95°C for 10 min, and 40 cycles of (95°C for 15 sec, 60°C for 30 sec, and 72°C for 45 sec. Data analysis, including copy number calculation for each sample in copies / ng of total DNA, was performed using the Quantstudio 6 Flex Realtime PCR System Software (Applied Biosystems, MA, USA). Relative quantification of C. difficile was calculated by determining absolute quantification of the pathogen by total bacterial load. The qPCR data was analyzed using a two-way ANOVA repeated measures model.4. Examples

[0123] As described further herein, experiments were conducted to explore the in vitro assembly and stability of a minimal 16-species microbial consortium reflective of the human infant gut microbiota, through controlled experimentation with various carbohydrate sources and dilution rates. The results of the present disclosure clearly indicate that the consortium dynamics and metabolic responses are profoundly influenced by the structural complexity of the carbohydrates and the carbon supply rate. The observed differences in consortiumcomposition and metabolic output across different carbon sources underscore the critical role of dietary substrates in shaping microbial interactions and stability.

[0124] Species-specific metabolic capacities, particularly among Bifidobacterium strains, played a central role in determining coexistence and metabolic output, while competitive and facilitative interactions modulated by substrate availability7shaped community trajectories. These findings reinforce the importance of metabolic interdependencies in microbial ecology and highlight the utility of minimal consortia as tractable models for understanding microbiome resilience and informing therapeutic design.

[0125] It will be readily apparent to those skilled in the art that other suitable modifications and adaptations of the methods of the present disclosure described herein are readily applicable and appreciable, and may7be made using suitable equivalents without departing from the scope of the present disclosure or the aspects and embodiments disclosed herein. Having now described the present disclosure in detail, the same will be more clearly understood by reference to the following examples, which are merely intended only to illustrate some aspects and embodiments of the disclosure, and should not be viewed as limiting to the scope of the disclosure. The disclosures of all journal references, U.S. patents, and publications referred to herein are hereby incorporated by reference in their entireties.

[0126] The present disclosure has multiple aspects, illustrated by the follow ing non-limiting examples.Example 1

[0127] Core Microbiome Analysis Informs Rational Consortium Design. To identify stable and functionally relevant microbial members for rational community7design, a core microbiome analysis was performed across previous ex vivo culturing conditions using infant fecal inoculant. Particular emphasis was places on communities cultured with the human milk oligosaccharide, LacNAc (hGOS + BS), given their relevance to early-life microbiota development and reproducible behavior in prior experiments. A total of 24 operational taxonomic units (OTUs) were consistently detected across dietary7conditions (FIG. 1A), including keystone taxa such as Faecalibacterium prausnitzii and Thomasclavelia ramosa. identified with 99% confidence.

[0128] The shared core community was dominated by Firmicutes — particularly from the Clostridiales and Lactobacilliales orders — with recurrent detection of Veillonella, Streptococcus, and other lactic acid bacteria. Functional diversity was further supported by thepresence of Bacteroides fragilis, B. oval us. B. uniformis, and two Actinomycetota members including Eggerthella lenta and genus-level Bifidobacterium.

[0129] The persistence of taxa under varying dilution rates was next assessed in the HMO- enriched condition (hGOS + BS), which mimics shifts in resource abundance typical of gut environments. The 22 shared OTUs across dilution rates (FIG. IB) demonstrated compositional stability , again dominated by Firmicutes but with greater representation of Actinomycetota, Bacteroidota. and Proteobacteria. Notably. Bifidobacterium adolescentis consistently emerged as a stable core member, highlighting its persistence under HMO-enriched conditions.

[0130] Guided by core microbiome insights, a rationally designed 16-member minimal microbial consortium (RDC) was constructed that captured both the phylogenetic and metabolic diversity observed in the natural inoculum. Selected strains were chosen to represent dominant and metabolically active taxa involved in short-chain fatty' acid (SCFA) synthesis, including buty rate, acetate, propionate, and the organic acid lactate. These metabolic intermediates are essential for host energy metabolism and immune modulation.

[0131] FIG. 2 illustrates the phylogenetic mapping of taxa in the natural ex vivo community compared to those selected for the minimal consortium. From the original 219 classified tree nodes, strains were prioritized that preserved key' metabolic functions while reducing overall complexity7. Selection criteria included genome availability7, functional annotations, and compliance with BSL-1 safety standards. This resulted in a reduced representation of Clostridia and Proteobacteria members (due to limited availability of safe, culturable strains) and a deliberate increase in lactic acid bacteria to facilitate early carbon energy metabolism crucial for energizing the microbial consortium.Example 210132] In-silico Genomics Reveals Functional Specialization. Having complete genome sequences for each strain enabled pan-genomic analysis of the RDC to assess shared and unique putative functional capacities. Whole genome comparisons revealed substantial genetic specialization, with strain-specific accessory genes enriched for distinct carbohydrate utilization pathways. SCFA production, and potential cross-feeding capabilities.

[0133] The total genomic composition of the curated consortium was explored through Anvio pan-genome analysis, revealing a complex landscape of 34,151 total gene clusters (FIG. 3). A major portion of these gene clusters (29,529 / 34,151; 86.5%) were unique to individual genomes indicative of a high degree of genetic specialization. Of these gene clusters, only 19.856 (19,856 / 29.529; 67.2%) were functionally annotated and assigned a COG20 category.The Clusters of Orthologous Genes (COG) database was utilized to functionally assign gene clusters for which the majority were assigned as carbohydrate transport and metabolism, transcription, and cell wall / membrane / envelope biogenesis clusters at 10.8%, 9.24%, and 8.6%, respectively.10134] Beta-glucosidases (EC 3.2.1.21) are essential for carbohydrate metabolism in catalyzing the breakdown of complex carbohydrates such as GOS into simpler sugars. In total, 20 unique [3-glucosidases are present in the consortium contributed by 11 species. Notably, Bacteroides finegoldii exhibits a diverse array of eight unique P-glucosidases, while the remaining species display up to three distinct genes for this enzyme, reflecting a tailored adaptation to carbohydrate-rich niches within the gut ecosystem. Further illustrating this diversity. 41 unique p-galactosidase genes, which are crucial for the metabolism of lactose and other galactosides, were identified across seven species. Akkermansia muciniphila. Parabcicteroides john onii. and Bacteroides finegoldii are prominent contributors, possessing 7, 9, and 12 unique P-galactosidase genes, respectively. Interestingly, Bifidobacterium breve was the only Bifidobacterium to harbor two distinct putative P-glucosidases in contrast to Bifidobacterium bifidum being the only to harbor two distinct P-galactosidases.

[0135] In contrast, a core set of 33 gene clusters (0.1%) shared across all species points to a foundational suite of genes essential for basic communal operations. These core clusters, predominantly associated with essential cellular processes such as translation, ribosomal structure, and biogenesis (19 / 33, 58%), as well as post-translational modification, protein turnover, chaperones (10 / 33, 30%), replication, recombination and repair (3 / 33, 9%), and nucleotide transport and metabolism (1 / 33, 3%), suggest a sophisticated level of communal resilience and adaptability.

[0136] The remaining 13.5% (4,589 / 34,151) of gene clusters are common to multiple genomes and reveal significant redundancy in functions vital for survival and adaptability, with a pronounced focus on translation, ribosomal structure, and biogenesis (488 / 4,589; 10.6%). The consortium's genomic architecture, with considerable redundancy in carbohydrate metabolism (444 / 4,589; 9.7%) and energy production (242 / 4,589; 5.3%), underlines a preparedness to harness various carbon sources efficiently.Example 3

[0137] Species-Specific Responses to Carbon Source Dynamics and Consortium Shifts. To evaluate the stability and adaptability of the RDC, species-level community compositions were analyzed in response to different dietary carbon sources and increasing dilution rates.Taxonomic profiles (presence / absence) were compared to the original 16-strain inoculum to assess the extent of compositional retention under varying environmental pressures.

[0138] Across all conditions, the lactose and GOS+BS treatments closely mirrored the initial inoculum in terms of taxonomic proportions, indicating compositional robustness under these dietary inputs. In contrast, communities cultured with hGOS+BS — enriched with the HMO LacNAc — exhibited marked shifts in communit}’ structure (FIG. 4A). Notably, hGOS+BS conditions showed a reduction in Bacteroidota and Clostridia, accompanied by an increased relative abundance of Actinomycetota. Several classes, including Erysipelotrichia and Verrucomicrobiales , were undetectable under hGOS+BS. The hGOS+BS condition supported the lowest species richness, with a maximum of 11 detected species, compared to 14 in other conditions.

[0139] To further dissect community dynamics, relative abundances of each strain was tracked across a gradient of dilution rates (carbon availability). Species-level profiles (FIG. 4B) revealed distinct coexistence patterns modulated by both the complexity and availability' of the carbon source. A custom classifier identified 15 of the original 16 strains; Bifidobacterium longum subsp. infantis was not detected in any condition, including the initial inoculum. Reads aligning only at the genus level for Bifidobacterium suggest insufficient resolution or absence of the targeted subspecies.

[0140] In GOS+BS conditions, most species were retained, with two exceptions: B. bifidum and Leuconostoc mes enter oides . The latter emerged only at the highest dilution rate (0. 12 h '). while Weissella paramesenter oides was absent at an intermediate feeding rate (0.08 hThe addition of LacNAc (hGOS+BS) further narrowed community diversity. Bacteroides fmegoldii was entirely absent across dilution rates, while Parabacteroides johnsonii increased in abundance with elevated dilution rates — suggesting competitive fitness under high carbon flux. Conversely, Lactococcus lactis and L. mesenteroides were undetectable at higher feeding rates, indicative of washout dynamics.

[0141] Notably, Akkermansia muciniphila, Coprobacillus cateniformis, mdAnaerotruncus colihominis were absent across all hGOS+BS conditions, highlighting potential incompatibility with HMO-enriched substrates or remaining consistently under the limit of detection. In contrast, Roseburia hominis and Veillonella atypica persisted in all conditions, though R. hominis was consistently present at extremely low abundance (<105) under hGOS+BS, suggesting functional but low-prevalence niche occupancy.Example 4

[0142] Impact of Carbon Source on Microbial Consortium Structure Assembly and Stability. To examine how dietan’ carbon inputs shape community assembly, beta diversity metrics were analyzed to assess structural differences in microbial consortia formed under different carbohydrate sources and feeding rates. As previously observed, bile salts (BS) significantly influenced clustering patterns in community composition. This analysis was expanded to determine whether each carbon source and dilution rate assembled into distinct climax community structures.

[0143] Weighted PCoA of 54 samples (triplicates of biological duplicates) revealed distinct clustering of consortia by carbon source (FIG. 5A). Specifically, consortia cultured with GOS+BS and hGOS+BS formed clearly separated clusters, whereas lactose-fed communities displayed greater compositional variability across dilution rates. Some overlap in the lactose communities was observed between hGOS+BS and GOS+BS communities under lower dilution rates, suggesting shared community trajectories under prolonged retention times.

[0144] PERMANOVA analysis confirmed significant differences in community' structures between carbon sources (p = 0.001), supporting the observed clustering. Within each carbon source, PERMANOVA tests across dilution rates also yielded statistically significant results, though with varying degrees of significance. The intermediate feeding rate (D = 0.08 h1) exhibited the lowest significance (p = 0.05, F = 4. 17), while the highest feeding rate (D = 0. 12 h-1) showed the most pronounced divergence (p < 0.001, F = 15.80), suggesting increased perturbation with higher nutrient flux.

[0145] To assess structural stability, PERMDISP tests were conducted on each carbon source community'. As shown in FIGS. 5B-5D, lactose and GOS+BS consortia exhibited nonsignificant dispersion across dilution rates, indicating structural stability. In contrast, the hGOS+BS communities showed moderate dispersion (p = 0. 1. F = 2.35). These results indicate that the hGOS+BS consortium structure, whose ordination was accounted for phylogenetic and relative abundance data, changes across dilution rates as opposed to the lactose and GOS+BS consortia which display overlap among dilution rates.Example 5|0146] Metabolic Responses of Minimal Consortium to Carbon Source Variability. To complement the structural analysis, targeted metabolomics was performed to examine the functional output of the minimal consortium under different carbon sources and dilution rates. The focus was on SCFA and lactate production, key metabolites indicative of fermentativeactivity and microbial function. FIG. 6A displays metabolic profiles across conditions, highlighting how dilution rate and carbon complexity modulate metabolite concentrations. As expected, increasing the dilution rate reduced microbial doubling times and shortened metabolic turnover. Across all conditions, acetate was the most abundant metabolite, followed by propionate, lactate, and buty rate. Butyrate concentrations remained stable and statistically unchanged across all carbon source and carbon availability conditions, suggesting the persistence of butyrate-producing taxa. In contrast, propionate and lactate concentrations varied notably by condition. The lactose-fed consortia at the highest dilution rate exhibited significant increases in both metabolites, reflecting a shift in community7metabolism under rapid substrate influx. Acetate concentrations significantly increased (p < 0.01) between the lowest and highest feeding rates in both lactose and hGOS+BS conditions. Similarly, lactate concentrations in lactose-fed cultures showed significant increases at the highest dilution rate compared to lower rates (p < 0.01), except between D = 0.04 and D = 0.08 h '.

[0147] To assess the correspondence between microbial composition and functional output, Procrustes analysis (PA) based on Spearman Correlation Analysis was performed between community structure and metabolite profiles. The results, shown in FIGS. 5B-5D. indicate that GOS+BS and lactose displayed a moderate yet non-significant level of similarity (FIG. 5B; R=0.3, p=0.08). Comparing GOS+BS to hGOS+BS yielded a Procrustes correlation coefficient (R) of 0.28 with a p-value of 0.1. signifying a moderate similarity7without statistical significance (FIG. 6C). Notably, the Procrustes analysis between hGOS+BS and lactose consortia showed a higher correlation coefficient (R=0.57) with a p-value of le-4, indicating significant similarity7in minimal consortium dynamics (FIG. 6D).Example 610148] Galacto-oligosaccharides (GOS) are prebiotics metabolized by intestinal microorganisms that confer beneficial effects to the host. One of the potential beneficial effects of GOS is the protection against pathogen colonization by structurally mimicking intestinal binding sites and preventing epithelial barrier dysfunction. Experiments in this example were conducted to determine the effects of a GOS diet in combination with a microbial intervention (bacterial consortium or fecal microbiota transplantation [FMT]) in a mouse model of Clostridioides difficile (C. difficile) infection. C57BL / 6 mice (4-6 weeks old) were fed a defined diet (control) or GOS diet, received either the bacterial consortium or FMT and were administered one dose of 5X104CFU / ml of C. difficile R20291. The GOS diet alone increased the resistance to C. difficile colonization but did not impact clearance rates. Mice that receivedthe bacterial consortium and FMT had increased permeability but a lower abundance of C. difficile at the end of the study. Mice that received the bacterial consortium had a distinctly different gut microbiome composition compared to FMT-control or FMT-GOS groups. GOS diet facilitated the stable colonization of the consortium bacterial members, which persisted through the antibiotics and C. difficile infection challenges. The results described herein demonstrate that GOS supplementation, along with the bacterial consortium, may create an environment that aids in preventing pathogen colonization and effective clearance, leading to future clinical interventions to explore prebiotic supplementation as a preventative treatment for infection.

[0149] Experimental design. To evaluate the impact of GOS plus microbial intervention (either as a synthetic consortium or whole stool compositions) on a C. difficile infection model, 48 young adult (4-6 weeks old) mice were fed either a defined diet or the same diet where cellulose was replaced by pure GOS. After 7 days on the experimental diets, mice received either the bacterial consortium or FMT before and after antibiotic treatment and C. difficile infection (FIG. 7A-7B). Prior to conducting the mouse experiment, experiments were conducted to test whether C. difficile R20291 could metabolize GOS as its sole carbon source. The strain was grown in a minimal medium containing either GOS or glucose, lactose, or no carbohydrates as controls. The strain grew at a similar rate in CDMM without carbohydrates or with glucose or lactose (0.1, 0.09, and 0.09 h'1, respectively). C. difficile R20291 was also capable of utilizing GOS as a carbon source, showing a diauxic growth that corresponded to 0.2 h'1from 0.5 to 2 h, 0.15 h'1from 3 to 7.5 h, and 0.05 h'1from 10 to 18 h (FIG. 8).Example 7

[0150] The effect of diet on the gut microbiome. After the normalization period, mice were assigned either to the control or the GOS diet groups. Stool samples were collected on day 7, before the first bacterial intervention, for microbiome analysis (FIGS. 7A-7B). Significant differences were observed between the groups on day 7. As previously reported, diversity decreased in the GOS diet group (FIG. 9). FIGS. 10-11 show the effect of the GOS diet on day 7, directed by differences in the relative abundance of Akkermansia, Bifidobacterium, Lactobacillus, Lachnospiraceae, Bacteroides, and others (60 species in total; data not shown but can be made available upon request). In contrast, the composition of the gut microbiome in the control diet group w as directed by two clusters, which included Prevotella, Fusobacterium, and Veillonella (Cluster 1, 55 species), and Clostridia, Lachnospiraceae, and Roseburia in Cluster 2 (69 species). Analysis at the genus level at a prevalence of 20% showed that mice inthe GOS diet had a significantly higher abundance (Kruskal-Wallis with Dunn’s correction p<0.05) of species of the genera Lachnoclostridum, Erysipelatoclostridium, Lactobacillus, Enterococcus and Monoglobus, and the families Lachnospiraceae, Egger thellaceae, and Muribaculaceae compared to the control diet (data not shown but can be made available upon request), while 12 species of the genus Clostridium, and species of the genera Turicibater, Tuzzerella, Romboutsia, Roseburia. Lactococcus, Colidextribacter, Enter or habdus, and Dorea were more abundant in the control diet.Example 8

[0151] The gut microbiome responded differently to FMT and microbial consortium depending on the diet. Amore comprehensive analysis of the samples obtained on days 8, 9, 12, 13, and 14 was then conducted to specifically delineate the impacts of the first of three microbial interventions (FMT or microbial consortium), administered on day 7, within the dietary context before initiating antibiotic administration. No significant differences (ANOVA with Tukey pairwise comparisons. / ;>0.05) in alpha diversity w ere detected within any of the diet groups following the first intervention and before the first antibiotic administration (samples collected on days 8, 9, 12, 13, and 14) (FIG. 9). Principal Component Analysis (PC A) of samples according to their microbiome profile showed defined clusters based on diet and intervention. Positive loadings corresponding to the control diet group included Lachnospiraceae, Clostridium, and Roseburia (98 species). In contrast, the GOS diet group was associated hAkkermansia, Lachnospiraceae, and Lactobacillus (28 species) (FIGS. 12 and 13; data not shown but can be made available upon request). 72 species in Cluster 3, including Escherichia-Shigella, Aggregatibacter , and Fretibacterium, were distinctly separated from either diet; therefore, potentially associated with the microbial consortium or FMT.

[0152] Kruskal -Wallis analysis with pairwise comparisons showed that on day 8, the gut microbiome of mice on the control diet that received the defined consortium had an increased abundance of Bifidobacterium, compared to FMT. In contrast, mice that received FMT had a significantly increased abundance of Acetatifactor muris. The GOS group that received the defined consortium also had an increased abundance of Bifidobacterium compared to FMT. Similar observations were made on day 9, where mice on the control diet that received the defined consortium had an increased abundance of Lntestinimonas compared to FMT. The GOS group that received the defined consortium had an increased abundance of Bifidobacterium, compared to FMT. while mice that received FMT had an increased abundance of Prevotella.On day 12, mice on the control diet that received the defined consortium had an increased abundance of Parabacteroides johnsonii, compared to FMT, while mice that received FMT had an increased abundance of Erysipelatochlostridium, Peptococcus, and Lactobacillus ingluviei. The GOS group that received the defined consortium had an increased abundance of Parabacteroides johnsonii compared to FMT, while mice that received FMT had an increased abundance of Akkermansia. On day 13, mice on the control diet that received the defined consortium had a decreased abundance of Treponema medium and Bergeyella compared to FMT. The GOS group that received the defined consortium had an increased abundance of Parabacteroides johnsonii and Bifidobacterium and a decreased abundance oi Muribaculaceae and Akkermansia, compared to FMT. Finally, on day 14, before the administration of antibiotics, mice on the control diet that received the defined consortium had an increased abundance of Parabacteroides johnsonii (p=0.055) compared to FMT. The GOS group that received the consortium had an increased abundance of Parabacteroides johnsonii, compared to FMT, while mice that received the FMT and no intervention had an increased abundance of Muribaculaceae. The relative abundance of Parabacteroides johnsonii was increased (p<0.0001) in mice on either control or GOS diet given microbial consortium. In contrast, the relative abundance of Muribaculaceae was increased (p<0.0001) in mice given FMT, compared to the defined consortium (data not shown but can be made available upon request).Example 9

[0153] The effects of antibiotics and C. difficile infection on the gut microbiome in relation to diet and microbial interventions. Antibiotics were administered through drinking water between days 14 and 17, with an intraperitoneal clindamycin injection on day 19 as part of the C. difficile infection protocol. Mice were infected with C. difficile R20291 on day 22, and stool was collected at various time points until day 31 to assess pathogen clearance. The effects of antibiotics were observed on day 21 before C. difficile infection. Analysis of samples collected on day 21 showed an overall reduction in alpha diversity in both control and GOS diets (FIG. 9); however, no significant differences were detected within diets between interventions (ANOVA with Tukey pairwise comparisons. / •»().05) after antibiotic treatment. Within the control diet, the group that did not receive a microbial intervention had the lowest diversity. In contrast, mice that received either the consortium or FMT-GOS showed the low est reduction in diversity in response to antibiotics. Within the GOS diet, mice receiving the consortium had the lowest diversity’, while those receiving FMT-GOS showed the lowest reduction in diversity in response to antibiotics.

[0154] A Principal Component Analysis (PCA) plot of samples collected on day 21 showed that despite the effect of antibiotics, samples still clustered according to their respective diets and less according to the interventions (FIG. 14; data not shown but can be made available upon request). Samples from the mice fed the GOS diet that received no intervention showed overlapping ellipses with clusters corresponding to consortium and FMT-C group samples, while FMT-G samples clustered separately. FMT-G was correlated with two clusters, which included Akkermansia. Oscillibacter. and Roseburia (88 species), Enter obacteriaceae, Bacteroides, and Lactobacillus (84 species). At the same time, consortium and FMT-C were associated with Fretibacterium, Aggregatibacter, and Haemophilus (118 species). Likewise, samples from mice fed the control diet and no treatment overlapped in a cluster with controlconsortium and control-FMT-C samples, while control-FMT-G clustered separately. The control diet was correlated with three clusters. The no-treatment, consortium, and FMT-C were correlated with Cluster 1, comprised of 71 species, including Fretibacterium, Actinobacillus, and Neisseria. The FMT-G samples were associated with Cluster 2, which consisted of 91 species, including Akkermansia, Colidextribacter . and Oscillibacter .

[0155] Kruskall-Walhs pairwise comparisons with Dunn correction analysis of samples collected on day 21 showed that mice on the control diet that received the defined consortium had an increased abundance of Bifidobacterium and Escherichia-Shigella, compared to FMT. The GOS group that received the defined consortium had an increased abundance of Bifidobacterium and Parabacteroides johnsonii compared to FMT. Mice on the control diet given no intervention had an increased abundance of Lactococcus lactis compared to mice on the GOS diet, while mice on the GOS diet given the defined consortium had an increased abundance of Akkermansia compared to mice on the control diet (data not shown but can be made available upon request). There was an increased abundance of Lactobacillus in mice on the control diet given FMT-G compared to no intervention.|0156] Since C. difficile was administered on day 22, its effects on day 23 and beyond were analyzed. On day 23, mice on the control diet that received FMT-GOS had a significantly higher diversity' than mice that did not receive any treatment at day 23 ( / ?-().006). and mice on the control diet that received either intervention or no intervention on day 22 (FIG. 9). The decrease in diversity observed in mice in the control diet that received no treatment was reversed by day 26, and no significant differences between interventions were observed between or within diets on any of the subsequent days.|0157] A Principal Component Analysis (PCA) plot of samples collected on day 23 showed differences between groups primarily associated with the intervention within diets (FIG. 15;data not shown but can be made available upon request). Within the GOS group, samples from mice that received the consortium were more dissimilar in the ordination plane. In contrast, samples from animals receiving FMT-G were more dissimilar within the control diet. The control diet PC A plot identified three taxa clusters contributing to PCI and PC2, while these were reduced to two clusters in the GOS diet contributing mainly to PCI. Cluster 1 consisted of 230 species, including various species of Prevotella and Treponema. Cluster 2 contained 66 species, with several Clostridium species, including C. difficile. Within the control diet. Cluster 1 (209 species) contributed mostly to PCI and included most of the Clostridium and Lachnospiraceae species. Cluster 2 (40 species) contributed mostly to PC2, including Lactobacillus passer i. Lactobacillus salivarius, and Lactobacillus vaginalis. Finally, Cluster 3 comprised 46 species, including C. difficile. Kruskall-Wallis pairwise comparisons with Dunn correction analysis identified seven taxa with increased relative abundance in control nointervention mice compared to the GOS no-intervention mice (Cellulosilyticum lentocellum, Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, Lactobacillus, Yoonia-Loktanella, Lactococcus lactis, Leptotrichia goodfellowii, anAPaenibacillus macerans,p<0. 1). Within the GOS diet, mice that received the consortium had an increased abundance of Bifidobacterium and Parabacteroides johnsonii. while the animals that received FMT-GOS had increased Akkermansia. Within the control diet, mice in the FMT-GOS group had a higher representation of Akkermansia and species of the family Lachnospiraceae (p<0. 1) and a lower representation of C. difficile p=0. 12). Likewise, animals in the consortium intervention group had increased Parabacteroides johnsonii, Escherichia-Shigella, and Bifidobacterium but reduced Lactobacillus aviarius, C. difficile, and Enterococcus.

[0158] Kruskal -Wallis analysis with pairwise comparisons showed that on day 26 (data not shown but can be made available upon request), mice on the control diet that received microbial consortium had an increased abundance of Parabacteroides johnsonii, compared to FMT-C and FMT-G. Compared to FMT-C, there was an increased abundance of C. difficile in FMT- G, consortium, and no intervention. There was also ahigher abundance of Akkermansia in FMT compared to no-intervention and consortium. Mice on the GOS diet had an increased abundance of Parabacteroides johnsonii. Erysipelatochlostridium, and Escherichia-Shigella in consortium and FMT, compared to no intervention. In contrast, Bifidobacterium was in greater abundance in mice given consortium than FMT-C or FMT-G. On day 27, mice on the control diet that received the defined consortium had an increased abundance of Parabacteroides johnsonii compared to FMT. There was also an increased abundance of C. difficile in mice that received FMT-G, consortium, or no intervention, compared to FMT-C.Mice on the GOS diet had an increased abundance of Parabacteroides johnsonii and Erysipelatoclostridium in FMT and consortium, compared to the no-intervention group. There was also an increased abundance of Bifidobacterium in the consortium group compared to FMT, and no intervention. On days 28 and 29, mice on the control diet that received the defined consortium had an increased abundance of Parabacteroides johnsonii, compared to FMT and no intervention. There was a higher abundance of Clostridium species in mice given FMT-C, compared to FMT-G and consortium, whereas C. difficile was in higher abundance in mice given FMT-G and consortium, compared to FMT-C. Mice on the GOS diet had a higher abundance of Parabacteroides johnsonii, Erysipelatoclostridium, and Escherichia-Shigella in FMT and consortium, compared to no intervention. Bifidobacterium was once again in higher abundance in mice given consortium, compared to the FMT and no-intervention groups. On day 30, mice on the control diet given consortium had an increased abundance of Parabacteroides johnsonii and C. difficile compared to FMT-C. Mice on the GOS diet given consortium had an increased abundance of Bifidobacterium, compared to the FMT and nointervention groups. There was also an increased abundance of C. difficile in mice given no intervention, compared to FMT and consortium.

[0159] At the end of the experiment on day 31, intestinal contents were collected and analyzed. Mice on the control diet that received the defined consortium had a higher abundance of C. difficile compared to FMT-C , and mice that received FMT had an increased abundance of Lactobacillus. Mice fed the GOS diet that received the consortium had a higher abundance of Bifidobacterium and Parabacteroides johnsonii, compared to FMT and no intervention. C. difficile had an increased abundance in the no-intervention group compared to the defined consortium and FMT. In contrast, Escherichia-Shigella was in increased abundance in the defined consortium and FMT groups, compared to no intervention.Example 10

[0160] GOS inhibited C. difficile colonization while consortium and FMT improved clearance. Analysis at the species level identified 453 taxa of the class Clostridia in the dataset, which contained 13 orders. Clostridiales. Lachnospirales, Oscillospirales, and Peptostreptococcales-Tissierellales were the most represented orders, and all contained genera designated as "Clostridium or Clostridioides j The relative abundance of C. difficile over time from the 16S rRNA sequencing data showed relative abundances below 0.1% until the administration of C. difficile spores. On day 23, after the administration of C. difficile, mice on the control diet with no treatment had the highest relative abundance of C. difficile at 25.04%.In comparison, mice that received FMT-control had a relative abundance of 5.36%, and those that received FMT-GOS had 5.98%. Mice given the microbial consortium had a 2.91% relative abundance. In the GOS diet group, untreated mice had a C. difficile relative abundance of 2.91%. Mice given FMT-control had 5.29%, while those given FMT-GOS had 2.52% C. difficile relative abundance. Finally, mice given the microbial consortium had an overall relative abundance of 2. 12%.

[0161] To confirm the results from 16S rRNA amplicon sequencing data (FIG. 18), stool samples from the C. difficile infection period (from day 21 to day 31 [day 31 samples corresponded to intestinal contents collected at termination]) were collected, and the C. difficile bacterial load was quantified by quantitative (q)PCR. Clearance was calculated by determining the absolute quantity of C. difficile over the total bacterial load. As shown in FIG. 18, the clearance rates over time denoted a general downward trend. All interventions resulted in a lower presence of C. difficile compared to no treatment controls at the end of the study. When comparing diets within mice given either consortium or FMT interventions, the GOS diet showed lower C. difficile abundance compared to the control diet on day 22 (one day postinfection), confirming observations from 16S rRNA sequencing data and indicating that dietary GOS increased colonization resistance to the pathogen. Upon administration of the consortium, mice following the GOS diet exhibited a 10-fold reduction in pathogen content on day 22 (p=0.0035) compared to mice on the control diet.

[0162] Furthermore, on day 31 (p=0.0126), it was observed that the GOS diet contributed to accelerated clearance of C. difficile (FIG. 19). Mice receiving the bacterial consortium exhibited the highest initial inhibition of C. difficile compared to those in the no-treatment control and FMT groups. Both consortium and FMT-GOS interventions showed close to a 10- fold reduction in C. difficile with the GOS diet compared to the control diet at the endpoint. However, FMT-control intervention with the GOS diet did not efficiently promote C. difficile clearance (FIG. 20), though it still reduced C. difficile abundance to the same level as other interventions.

[0163] FMT-control was most effective within the control diet in clearing C. difficile compared to all interventions (FIG. 20). Similarly, when comparing clearance with different interventions within the GOS diet, FMT-GOS showed the highest clearance effectiveness (FIG. 20). These results highlight how the source of FMT, especially when the FMT is derived from the same diet mice group, significantly influenced clearance efficacy. Furthermore, the GOS diet combined with either consortium or FMT was more effective in clearing C. difficile compared to the control diet, suggesting symbiotic effects of prebiotic and bacteriaadministration. These findings emphasize the need to modulate the gut microbiota community with a prebiotic diet to enhance the effectiveness of FMT. Moreover, administering the predefined FMT derived from the same diet could optimize clearance effectiveness.Example 11

[0164] The GOS diet reduced intestinal permeability, but FMT-GOS increased permeability in mice. The GOS diet groups generally showed a lower, but not statistically significant, decrease in intestinal permeability compared to the control diet. Among the mice receiving FMT-control, the GOS diet group exhibited the lowest permeability (data not shown but can be provided upon request). However, FMT-GOS significantly increased permeability in both GOS and control diets (pO.OOOl).|0165] As provided herein, mice in the GOS diet group showed increased persistence of the taxa in the microbial consortium compared to the control diet group, specifically resulting in increased abundance of Parabacteroides johnsonii and Bifidobacterium. The results provided herein endorse the advantage of the combination of prebiotic and probiotic / commensal bacteria on the persistence of the components of the microbial intervention. Experiments were conducted to determine the effects of diet and microbial intervention on inhibiting C. difficile colonization and promoting clearance. The GOS diet inhibited C. difficile colonization more than the control diet. Although the specific mechanism underlying this inhibition remains indistinct, prior research indicates that prebiotics can exert anti-pathogenic effects. These effects encompass inhibiting pathogen adhesion, disrupting cell membrane and biofilm integrity, enhancing host immune response, and inhibiting pathogen proliferation.Example 12|0166] The gut microbiota plays a crucial role in maintaining host homeostasis and preventing pathogen invasion. Antibiotic use can disrupt this balance by creating open niches that increase susceptibility to pathogens like Clostridioides difficile. Strategies such as prebiotics, probiotics, and synbiotics help restore gut health by promoting the growth of beneficial bacteria and decreasing diversity to occupy the niche, preventing potential pathogen colonization. Galacto-oligosaccharides (GOS) and LacN Ac-enriched GOS (hGOS) promote beneficial bacteria like Bifidobacterium and Akkermansia. By selectively fermenting prebiotics, the beneficial bacteria gain a competitive advantage. Introducing a consortium can further occupy these niches, reducing C. difficile colonization and improving gut resilience.

[0167] Experiments were conducted to develop a rationally designed bacterial consortium (RDC) to synergize with prebiotics and used a bioreactor to examine the stability of microbialassembly and metabolic output (FIGS. 21-25). Using a mouse model of C. difficile infection (CDI), the effects of GOS diet on RDC microbial persistence and pathogen resistance were assessed. 16S rRNA sequencing and qPCR were used to track microbial dynamics. A stable 16-species microbial consortium was designed to optimize metabolic interactions in carbohydrate-rich environments. In the CDI mouse model, GOS promoted the growth of primary’ degraders like Bifidobacterium and Akkermansia, enhancing RDC persistence of Bifidobacterium. Lactobacillus. Parabacteroides. and Lactococcus, and enhancing host pathogen resistance. Linear regression showed a positive correlation between Bifidobacterium abundance and resistance to C. difficile infection.

[0168] As provided in FIGS. 21-25, the results described herein highlight the potential of synbiotics — specifically GOS with RDC — to modulate gut microbiota and reduce CDI risk. The use of a packed bed bioreactor (PBR) system in our experiments facilitated the emulation of gut conditions. This system proved essential for observing the dynamic interactions and stability' of the consortium under vary ing nutritional and operational conditions. These data underscore the promise of targeted microbiome-based interventions for gut health and infection prevention.

[0169] It is understood that the foregoing detailed description and accompanying examples are merely illustrative and are not to be taken as limitations upon the scope of the disclosure, which is defined solely by the appended claims and their equivalents.

[0170] All publications and patents mentioned in the above specification are herein incorporated by reference as if expressly set forth herein. Various changes and modifications to the disclosed embodiments will be apparent to those skilled in the art and may be made without departing from the spirit and scope thereof.

Claims

CLAIMSWhat is claimed is:

1. A method of generating a composition for fecal persistent microbiome transplant (FPMT), the method comprising: inoculating a bioreactor with a defined culture composition, wherein the defined culture composition comprises a bacterial population, and a carbon source comprising a plurality of carbohydrates; culturing the defined culture composition according to a set of culture conditions comprising defined taxonomic proportions of bacteria in the bacterial population, an adjusted feeding rate, and adjusted retention time; and assessing at least one metabolic indicator at at least one timepoint during the culturing of the defined culture composition; wherein the at least one indicator indicates that the defined culture composition is suitable for FPMT.

2. The method of claim 1 , wherein the bacterial population is obtained from one or more donors prior to culturing.

3. The method of claim 1, wherein the bacterial population is obtained from a synthetic bacterial culture prior to culturing.

4. The method of any one of claims 1 to 3, wherein bacterial population comprises one or more of the following: Bacteroldola, Clostridia, Negativicutes, Lactobacillales, Erysipelotrichia, Actinomycetota, and / or Pseudomonadota.

5. The method of any one of claims 1 to 4, wherein the defined taxonomic proportions of the bacteria comprise: from about 5% to about 15% Bacteroidota,' from about 10% to about 30% Clostridia,' from about 1% to about 10% Negativicutes,' from about 10% to about 35% Lactobacillales,' from about 1% to about 10% Erysipelotrichia.'from about 5% to about 25% Actinomycetotcr, and / or from about 5% to about 15% Pseudomonadota.

6. The method of any one of claims 1 to 5, wherein the plurality of carbohydrates comprises galactooligosaccharides (GOS) and / or lactose.

7. The method of claim 6, wherein the GOS is humanized GOS (hGOS).

8. The method of claim 6, wherein the plurality of carbohydrates further comprises N- Acetyllactosamine (LacNAc) and / or a bile salt.

9. The method of any one of claims 1 to 8, wherein the adjusted feeding rate ranges from about 0.04 h'1to about 0.12 h'1.

10. The method of any one of claims 1 to 8, wherein the adjusted feeding rate ranges from about 0.06 h’1to about 0. 10 h’1.

11. The method of any one of claims 1 to 10, wherein the adjusted retention time ranges from about 5 hours to about 30 hours.

12. The method of any one of claims 1 to 10, wherein the adjusted retention time ranges from about 10 hours to about 15 hours.

13. The method of any one of claims 1 to 12, wherein the at least one metabolic indicator comprises carbon dioxide and / or hydrogen concentration.

14. The method of claim 13, wherein the carbon dioxide concentration ranges from about 25 mg L’1h'1to about 300 mg L1h’1.

15. The method of claim 13, wherein the hydrogen concentration ranges from about 0. 1 mg L1h'1to about 1.5 mg L1h’1.

16. The method of any one of claims 1 to 15, wherein the at least one metabolic indicator comprises a short-chain fatty acid (SCFA).

17. The method of claim 16, wherein the SCFA is acetate, propionate, and butyrate.

18. The method of claim 17, wherein acetate ranges from about 5% to about 15%, propionate ranges from about 0.5% to about 5.0%, and buty rate ranges from about 0.1% to about 1.0%.

19. The method of any one of claims 1 to 18, wherein the at least one metabolic indicator comprises lactate at a range of about 0. 1% to about 5.0%.

20. The method of any one of claims 1 to 19, wherein the culturing comprises adding a carbohydrate feed composition according to the adjusted feeding rate.

21. The method of claim 20, wherein the carbohydrate feed composition comprises lactose, sucrose, GOS, hGOS, and / or a bile salt.

22. The method of any one of claims 1 to 21, wherein the method further comprises transplanting the defined culture composition into a human subject after assessing at least one metabolic indicator.

23. The method of claim 22, wherein transplantation of the defined culture composition into the human subject produces a metabolically stable and persistent microbial consortia.

24. The method of claim 22, wherein transplantation of the defined culture composition into the human subject treats and / or prevents an immune disorder or condition.

25. The method of claim 24, wherein the immune disorder or condition comprises at least one of Addison disease, celiac disease, dermatomyositis, Graves’ disease, Hashimoto thyroiditis, inflammatory bowel disease. Crohn’s disease, ulcerative colitis, multiple sclerosis, Myasthenia gravis, pernicious anemia, reactive arthritis, rheumatoid arthritis, Sjogren syndrome, Systemic lupus ery thematosus (lupus), and / or Type I diabetes.

26. The method of claim 22, wherein transplantation of the defined culture composition into the human subject treats and / or prevents an infection.

27. The method of claim 26, wherein the infection is a bacterial infection, a fungal infection, or a viral infection.

28. The method of claim 27, wherein the bacterial infection is caused by Clostridioides difficile, Salmonella, E. coli, Campylobacter, Shigella, Staphylococcus, and / or Clostridium.

29. A method of treating or preventing an immune disorder and / or infection in a subject, the method comprising: generating a composition for fecal persistent microbiome transplant (FPMT) by inoculating a bioreactor with a defined culture composition, wherein the defined culture composition comprises a bacterial population, and a carbon source comprising a plurality of carbohydrates; culturing the defined culture composition according to a set of culture conditions comprising defined taxonomic proportions of bacteria in the bacterial population, an adjusted feeding rate, and adjusted retention time; assessing at least one metabolic indicator at at least one timepoint during the culturing of the defined culture composition; wherein the at least one indicator indicates that the defined culture composition is suitable for FPMT; and transplantation of the defined culture composition into the human subject, thereby treating or preventing the immune disorder and / or infection.

30. The method of claim 29, wherein the immune disorder comprises at least one of Addison disease, celiac disease, dermatomyositis, Graves’ disease, Hashimoto thyroiditis, inflammatory bowel disease, Crohn's disease, ulcerative colitis, multiple sclerosis, Myasthenia gravis, pernicious anemia, reactive arthritis, rheumatoid arthritis. Sjogren syndrome, Systemic lupus erythematosus (lupus), and / or Type I diabetes.

31. The method of claim 29, wherein the infection is a bacterial infection, a fungal infection, or a viral infection.

32. The method of claim 31, wherein the bacterial infection is caused by Clostridioides difficile, Salmonella, E. coli, Campylobacter, Shigella, Staphylococcus, and / or Clostridium.

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