Compositions and methods related to the infant microbiome

Abstract

Provided herein are methods for diagnosing a metabolic disorder and methods for the early identification of infants at risk for developmental delays. Also provided are compositions comprising bacteria that increase an amino acid or metabolite or combination thereof in a biological sample, as well as methods of using the compositions for treating a metabolic disorder in infants.

Description

ATTORNEY DOCKET NO. 090464-1548125 (024WO1)COMPOSITIONS AND METHODS RELATED TO THE INFANT MICROBIOMECROSS REFERENCE TO RELATED APPLICATION

[0001] This application claims priority to and the benefit of United States Provisional Patent Application Serial No. 63 / 761,495, filed February 21, 2025. The entire contents of this application are incorporated herein by this reference as if fully set forth herein.BACKGROUND

[0002] Child development normally progresses through predictable phases for the development of certain cognitive, language, social / emotional, behavioral, and motor skills. However, some children may experience delays or may stop developing at all in one or more of these areas. Although numerous strategies have been identified to support children once diagnosed as having a developmental delay, less is known about the specific causes of developmental delays, creating great concern for parents. The infant gut microbiome has been linked to infant neurodevelopment; however, research relating to the effect of the constituents of the microbiome remains limited. The establishment of methods for the early identification of infants at risk of developmental delays, as well as compositions and methods for treating infants at risk, would be advantageous.SUMMARY

[0003] The Summary is provided to introduce a selection of concepts that are further described below in the Detailed Description. This Summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used as an aid in limiting the scope of the claimed subject matter.

[0004] In one aspect, compositions are provided that comprise bacteria that increase an amino acid or metabolite or combination thereof in a biological sample of a subject. In some embodiments, the amino acids or metabolites comprise tryptophan, tyrosine, glutamine, glutamate, kynurenine, gamma-aminobutyric acid (GABA), or a combination thereof. In some embodiments, the compositions comprise two or more bacteria that increase an amino acid or metabolite or combination thereof in a biological sample of a subject. In some embodiments, the compositions comprise a synergistic combination of two or more of Bacteroides thetaiotaomicron, Bacteroides cellulosilyticus, and Parabacteroides distasonis. In someATTORNEY DOCKET NO. 090464-1548125 (024WO1)embodiments, the bacteria are provided as a live culture. In some embodiments, the bacteria are lyophilized.

[0005] The compositions may further comprise a pharmaceutically acceptable carrier. In some embodiments, the composition is formulated for oral administration. In some embodiments, the pharmaceutically acceptable carrier is one or more selected from a group consisting of alginate, gum arabic, pectin, animal proteins, chitosan (CS), xanthan, k-carrageenan, cellulose, starch, glycogen, acrylic acid derivatives, cellulose acetate trimellitate (CAT), hydroxypropyl methylcellulose acetate succinate (HPMCAS), cellulose acetate phthalate (CAP), hydroxypropyl methyl-cellulose phthalate (HPMCP), whey protein, casein, gelatin, polyacrylamides, Poly (D, L-lactic-co-glycolic acid) (PLGA), polyvinyl alcohol (PVA), poly-l-lysine (PLL), polystyrene, dextran, chitosan, pectin, cyclodextrin, amylose, guar gum, chondroitin sulphate, inulin, locust bean gum, fructose, fructooligosaccharides, mineral metal salt, glutathione, carboxymethyl cellulose (CMC), carboxymethylpachymaran (CMP), and combinations thereof. In some embodiments, the composition is formulated in a food product. In some embodiments, the composition is an infant formula, a liquid drop, an acidified milk, a milk powder, or a milk concentrate.

[0006] In another aspect, methods are provided for detecting a microbiome component or biomarker associated with a metabolic disorder in a subject. The methods comprise, obtaining a biological sample from the subject; measuring a level of a microbiome component or biomarker in the biological sample, wherein the microbiome component comprises one or more bacterial strains; and determining if the level of the microbiome component or biomarker is increased or decreased as compared to a control. In some embodiments, the one or more bacterial strains decrease an amino acid or metabolite or combination thereof in the biological sample. In certain embodiments, the metabolic disorder negatively affects cognition or neurodevelopment in the subject, increases inflammation and neuroinflammation in the subject, or both. In some embodiments, the biological sample is a fecal sample. In some embodiments, the subject is an infant of 0 to 12 months in age.

[0007] In some embodiments, the method comprises measuring a level of one or more biomarkers, wherein the one or more biomarkers are selected from a group consisting of an amino acid, kynurenine, GABA, eotaxin, IL-10, and cortisol. In some embodiments, the method comprises measuring a level of one or more biomarkers, wherein the one or more biomarkers comprise an amino acid, a metabolite, or a cofactor of a metabolic pathway selectedATTORNEY DOCKET NO. 090464-1548125 (024WO1)from a group consisting of an amino acid, carbohydrate, vitamin, tricarboxylic acid (TCA) cycle, lipid, nucleotide, peptide, orxenobiotic metabolic pathway.

[0008] In certain embodiments of the methods, the one or more biomarkers are selected from a group consisting of alanine, S-l-apyrroline-5-carboxylate, glutamine, glutamate, N-butyryl-leucine, N6-carboxyethyllysine, N6-acetyllysine, glutarylcarnitine (C5-DC), 3-sulfo-alanine, N-butyryl-phenylalanine, phenyllactate (PLA), N-carbamoylputrescine, spermine, indoxyl glucuronide, kynurenine, N-alpha-acetylomithine, N6-carboxymethyllysine, glucuronate, ribose, oxalate (ethanedioate), flavin mononucleotide (FMN), 5-(2-hydroxyethyl)-4-methylthiazole, aconitate [cis or trans], N-stearoyl-sphingosine (dl8: 1 / 18:0)*, Undecenoylcarnitine (Cl 1:1), hexanoylglycine, 3-hydroxypalmitate, 1-palmitoyl-2-linoleoyl-diglaactosylglycerol (16:0 / 18:2)*, docosahexaenoate (DHA; 22:6n3), arachidonate (20:4n6), l-palmitoyl-2-linoleoyl-GPC (16:0 / 18:2), phytosphingosine, N-stearoyl-phytosphingosine (tl8:0 / 18:0)*, sphingosine, heptadecasphingosine (dl7:l), xanthine, hypoxanthine, adenine, N1 -methyladenosine, guanine, thymidine 5'-monophosphate, uridine 5'-monophosphate (UMP), phenylacetylglutamine, phenylacetylglycine, glutaminylleucine, leucylalanine, lyslleucine, alanylleucine, p-cresol sulfate, hippurate, benzoate, 3,5-dihydroxyphenylpropionate, and pyrraline.

[0009] In certain embodiments of the methods, the one or more biomarkers comprise a dipeptide, phosphatidylcholine, or combination thereof; and a decrease in the level of the biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject. In certain embodiments, the one or more biomarkers comprise one or more of a dicarboxylate fatty acid, S-l-pyrroline-5-carboxylate, N-butyryl-phenylalanine, N-butyryl-leucine, N-carbamoylputrescine, uridine 5 '-monophosphate (UMP), 3-hydroxypalmitate, flavin mononucleotide (FMN), hypoxanthine, N6-carboxyethyllysine, phenyllactate (PLA), kynurenine, and l-palmitoyl-2-linoleol-GPC (16:0 / 18:2), or a combination thereof; and a decrease in the level of the biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject.

[0010] In certain embodiments of the methods, the one or more biomarkers comprise a metabolite or cofactor of an acyl glycine, chemical, medium chain acyl carnitine, benzoate, lysophospholipid, ascorbate and aldarate, long chain polyunsaturated fatty acid, creatine, or TCA cycle metabolic pathway; and an increase in the level of the biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject. In certain embodiments, the one or more biomarkers comprise one or more of indoxylATTORNEY DOCKET NO. 090464-1548125 (024WO1)glucuronide, phenylacetylglutamine, phytosphingosine, sphingosine, undecenoylcamitine (Cl 1 : 1), and spermine; and wherein an increase in the level of the biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject.

[0011] In some embodiments of the methods, a level of two, three, four, five, or six biomarkers are measured. In some embodiments, the methods comprise measuring a level of phytosphingosine, arachidonate, docosahexaenoate, glutamine, pyrraline, and DGDG 16:0 / 18:2. In certain embodiments, an increase in the level of phytosphingosine, arachidonate, and docosahexaenoate as compared to a control, and a decrease in the level of glutamine, pyrraline, and DGDG 16:0 / 18:2 as compared to a control, are associated with the metabolic disorder in the subject. In some embodiments, the one or more biomarkers comprise tryptophan, tyrosine, glutamine, glutamate, arginine, kynurenine, gamma-aminobutyric acid (GABA), eotaxin, IL-10, and cortisol. In certain embodiments, an increase in the level of eotaxin and cortisol as compared to a control, and a decrease in the level of tryptophan, tyrosine, glutamine, glutamate, arginine, kynurenine, GABA, and / or IL- 10 as compared to a control, are associated with the metabolic disorder in the subject. In certain embodiments, the methods further comprising administering to the subject a therapeutically effective amount of a composition comprising a bacteria that increase an amino acid or metabolite in a biological sample of the subject. In some embodiments, the composition comprises two or more bacteria that increase an amino acid or metabolite in a biological sample of the subject.

[0012] In another aspect, methods are provided for diagnosing a metabolic disorder in a subject. The methods comprise obtaining a biological sample from the subject; administering a portion of the subject’s biological sample to a germ -free mouse; measuring a level of a microbiome component or biomarker in a biological sample from the mouse or measuring a behavior of the mouse; and diagnosing the subject with the metabolic disorder if the level of the microbiome component or biomarker is increased or decreased as compared to a control, or if the behavior of the mouse is negatively affected as compared to a control.

[0013] In some embodiments of the methods, the biological sample is a fecal sample. In some embodiments, the subject is 0 to 12 months of age. In some embodiments, the behavior of the mouse is measured by a novel object recognition test, a fear conditioning test, or a sociability or social novelty test. In some embodiments, the level of one or more biomarkers in the biological sample from the mouse are measured, wherein the one or more biomarkers comprise an amino acid, a metabolite, or a cofactor of a metabolic pathway selected from a group consisting of an amino acid, carbohydrate, vitamin, tricarboxylic acid (TCA) cycle, lipid,ATTORNEY DOCKET NO. 090464-1548125 (024WO1)nucleotide, peptide, or xenobiotic metabolic pathway. In some embodiments, the methods further comprise administering to the subject a therapeutically effective amount of a composition comprising at least two or more bacteria that increase an amino acids or metabolite in a biological sample of the subject.

[0014] In another aspect, kits are provided for use in any of the disclosed methods. The kits may comprise an agent for measuring the level or presence of the microbiome component or biomarker in the biological sample and instructions. In other embodiments, the kits may comprise a therapeutically effective amount of any of the disclosed bacterial compositions.

[0015] In another aspect, methods are provided for treating a subject having, suspected of having, or at risk for having a metabolic disorder or cognitive or neurodevelopmental condition or disorder. The methods comprise administering to the subject a therapeutically effective amount of any of the disclosed bacterial compositions. In some embodiments of the disclosed methods, administration of the composition improves neural development or function in the subject as compared to a control. In some embodiments, the improvement in neural development or function is measured by the Harris Infant Neuromotor Test (HINT), the Bayley Scales of Infant and Toddler Development (BSID), or the Cognitive Assessment of Young Children (CAYC). In some embodiments, the subject being treated is an infant of 0 to 12 months in age. In some embodiments, the improvement in neural development or function is measured, for example, when the subject is 0 to 36 months in age. In some embodiments, the subject has a metabolic disorder associated with lower levels of an amino acid or metabolite. The composition may be formulated, for example, for oral administration. In some embodiments, the composition is formulated in a food product. In some embodiments, the composition is an infant formula, a liquid drop, an acidified milk, a milk powder, or a milk concentrate. In some embodiments, the bacteria are provided as a live culture. In other embodiments, the bacteria are lyophilized.

[0016] In some embodiments of the disclosed methods, administration of the composition increases the level of an amino acid or a metabolite of an amino acid in the subject. In some embodiments, administration of the composition increases the level of gamma-aminobutyric acid (GABA) in the subject. In some embodiments, administration of the composition increases the level of IL-10 in the subject. In some embodiments, administration of the composition lowers the level of cortisol in the subject. In some embodiments, administration of the composition lowers the level of eotaxin in the subject.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)DESCRIPTION OF THE FIGURES

[0017] The present application includes the following figures. The figures are intended to illustrate certain embodiments and / or features of the compositions and methods, and to supplement any description(s) of the compositions and methods. The figures do not limit the scope of the compositions and methods, unless the written description expressly indicates that such is the case.

[0018] FIG. 1 is a graph showing the distribution of BSID cognitive scores in the COMBINE child cohort. See Hemmingway etal.„ 2020, Br. J. Nutrition 124(4):440-49. Twelve infants were in the low scoring category (<85) and 20 infants were in the high scoring category (>115). Three infants scoring in the normal range (95, 100, 105) were also selected.

[0019] FIG. 2 is a schematic of preclinical modeling of infant fecal microbiomes in mice and bioreactors.

[0020] FIG. 3 is a graph showing the summary of the mortality of mouse offspring. The percentage of offspring mortality is shown for controls (left three bars (Wild Type, Germ Free, Control Mouse FMT)); mouse lines from normal scoring infants (fourth and fifth bars from the left (NS at 1 month or 9 months)); mouse lines from low scoring infants (sixth-ninth bars from the left (LS at 1-4 months, 6 months, 9 months, or 12 months)); and mouse lines from high scoring infants (far right four bars (HS at 1-4 months, 6 months, 9 months, or 12 months)). Animals from low scoring infants 6 months of age and younger had significantly increased mortality compared to all other groups. 120 mouse lines are shown, inclusive of mouse FMT control lines. Each point is the mean value of all animals tested in a mouse line (n= 16 or 24, half male and half female).

[0021] FIGS. 4A-4B provides results of an open field test. FIG. 4 A shows the top-down view of the open field testing apparatus. Animals were allowed to explore for 10 minutes, and the time in the center four squares (dark blue) was monitored. FIG. 4B is a representative heat map and motion trace of LS mouse behavior. These data show that LE mouse lines (generated with low-scoring, early time point infant samples) avoid the center of the apparatus and hide in comers compared to LL lines (generated with low-scoring, late time point infant samples).

[0022] FIG. 5 is a graph showing the time in the center zone for a representative example for each group, demonstrating that LSI 1-60 has reduced time in the center. All data points are shown for representatives of each group. The results are shown for controls (left two bars (n=24)), normal scoring lines (next two bars from the left (n=16)), low scoring animals (next two bars from the left (n=24)), and high scoring animals (right two bars (n=24)). StatisticalATTORNEY DOCKET NO. 090464-1548125 (024WO1)analysis **** p < 0.0001, *** p < 0.001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons. All other groups were not significantly different.

[0023] FIG. 6 is a graph showing the time in the center zone for all animals, demonstrating that LE mice spend less time in the center. The results are shown for the control (left bar), mouse lines from normal scoring infants (next two bars), mouse lines from low scoring infants (next four bars), and mouse lines from high scoring infants are in blue (right four bars). Animals from low scoring infants 6 months of age and younger had significantly less time in the center zone compared to all other groups. 120 mouse lines are shown, inclusive of mouse control lines. Each point is the mean value of all animals tested in a mouse line (n= 16 or 24, half male and half female) Statistical analysis **** p < 0.0001, *** p < 0.001 ** p < 0.01 by Two Way ANOVA, with Tukey’s correction for multiple comparisons. All other groups were not significantly different.

[0024] FIG. 7A is an image of the testing apparatus in which animals were allowed to explore for 10 minutes while the time in each side of the box was measured. FIG. 7B provides representative heat maps and motion traces of LS mouse behavior (LE shown on the left, LL shown on the right). LE mouse lines avoid the center and hide in comers compared to LL lines.

[0025] FIG. 8 is a graph showing the time in the light side of the box for a representative example for each group, demonstrating that LSI 1-60 mice spend less time in the light side of the box. All data points are shown for representatives of each group. The results are shown for controls (left two bars (n=24)), normal scoring lines (next two bars (n=16)), low scoring animals (next two bars from the left (n=24)), and high scoring animals (right two bars (n=24)). Statistical analysis **** p < 0.0001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons. All other groups were not significantly different.

[0026] FIG. 9 is a graph showing the time in the light side of the box for all animals, demonstrating that LE mice spend less time in the light side of the box. The results are shown for the controls (left bar), mouse lines from normal scoring infants (next two bars from the left), mouse lines from low scoring infants (next four bars from the left), and mouse lines from high scoring infants (four bars on the right). Animals from low scoring infants 4 months of age and younger had significantly less time in the light compared to all other groups. 120 mouse lines are shown. Each point is the mean value of all animals tested in a mouse line (n= 16 or 24, half male and half female) Statistical analysis **** p < 0.0001, by Two Way ANOVA, with Tukey’s correction for multiple comparisons. All other groups were not significantly different.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)

[0027] FIG. 10 is a graph showing the recognition index for a representative example for each group, demonstrating that LSI 1-60 prefers a familiar object. All data points are shown for representatives of each group. The results are shown for the controls (left two bars (n=24)), normal scoring lines (next two bars from the left (n=l 6)), low scoring animals (next two bars from the left (n=24)), and high scoring animals (right tow bars (n=24)). Statistical analysis **** p < 0.0001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons. All other groups were not significantly different.

[0028] FIG. 11 is a graph showing the recognition index for all animals, demonstrating that LE mice prefer a familiar object. The results are shown for the controls (left bar), mouse lines from normal scoring infants (next two bars from the left), mouse lines from low scoring infants (next four bars from the left), and mouse lines from high scoring infants (right four bars). Animals from low scoring infants 4 months of age and younger had significantly less time with the novel object compared to all other groups. 120 mouse lines are shown, inclusive of mouse control lines. Each point is the mean value of all animals tested in a mouse line (n= 16 or 24, half male and half female) Statistical analysis **** p < 0.0001, Two Way ANOVA with Tukey’s correction for multiple comparisons. All other groups were not significantly different.

[0029] FIG. 12 is a graph showing the percentage of time spent immobile during contextual testing for a representative example for each group, demonstrating that LSI 1-60 did not associate an adverse experience with the environment after 24 hours. All data points are shown for representatives of each group. The results are shown for controls (left two bars (n=24)), normal scoring lines (next two bars from the left (n=l 6)), low scoring animals (next two bars from the left (n=24)), and high scoring animals (right two bars (n=24)). Statistical analysis **** p < 0.0001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons. All other groups were not significantly different.

[0030] FIG. 13 is a graph showing the percentage of time spent immobile during contextual testing for all animals, demonstrating that LE mice have deficits in contextual memory. The results are shown for controls (left bar), mouse lines from normal scoring infants (next two bars from left), mouse lines from low scoring infants (next four bars from left), and mouse lines from high scoring infants (right four bars). Animals colonized with fecal samples from low scoring infants 4 months of age and younger had significantly less time freezing compared to all other groups. 120 mouse lines are shown, inclusive of mouse FMT control lines. Each point is the mean value of all animals tested in a mouse line (n= 16 or 24, half male and half female)ATTORNEY DOCKET NO. 090464-1548125 (024WO1)Statistical analysis **** p < 0.0001, Two Way ANOVA with Tukey’s correction for multiple comparisons. All other groups were not significantly different.

[0031] FIG. 14 is a graph showing the percentage of time spent immobile during cued fear conditioning testing for all animals, demonstrating that LS3-60 mice did not associate an adverse experience with a repeated cue. The percent of time spent immobile in a new environment was measured before (precued) and after the tone cue was played (cued). All data points shown are for representatives of each group. For the precued and cued measurements, the results are shown for controls (left bar (n=24)), low scoring animals (next two bars from left (n=24 in each group)), and high scoring animals (right two bars (n=24 in each group)). Statistical analysis **** p < 0.0001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons. All other groups were not significantly different.

[0032] FIG. 15 provides a schematic of the three-chamber box used in a sociability test (right) and a graph (top panel) showing total interaction time which demonstrates that LS3-60 mice do not have a preference for interaction with a mouse as compared to an empty cup (left two bars) compared to all other groups (n=6 per group). Statistical analysis **** p < 0.0001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons. Motion traces (bottom panel) showing a representative movement trace of an LS3-60 and LS3-275 during the 10 minute test.

[0033] FIG. 16 provides a schematic of the three-chamber box used in a social novelty test (right) and a graph (top panel) showing total interaction time which demonstrates that LS3-60 mice do not have a preference for interaction with a novel mouse as compared to a familiar mouse (left two bars) compared to all other groups (n=6 per group). Statistical analysis **** p < 0.0001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons. Motion traces showing a representative movement trace of an LS3-60 and LS3-275 during the 10 minute test.

[0034] FIGS. 17A-17D are graphs showing the microbial diversity in infant fecal samples and humanized mice. FIG. 17A shows that within-sample microbial diversity increases with infant age but does not differ between low-scoring (right bar in each pair) and high-scoring donors (left bar in each pair. FIG. 17B shows that principal component analysis places samples into the ordination space based on their microbial similarity. Infant fecal samples from Early life (age of 1-4 months) do not cluster based on donor’s BSID scores. FIG. 17C shows that within-sample diversity increases with donor age in mice and differs based on the donor’s BSID score for mice humanized with fecal sample 30-day, 60-day, and 365-day-old infants.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)FIG. 17D shows that fecal samples from humanized mice do not cluster based on the BSID score of their infant microbiome donors. Asterisks correspond to P < 0.05 using Wilcoxon rank-sum tests.

[0035] FIGS. 18 is a graph providing the taxonomic trends between low-scoring and high-scoring humanized mice. Using univariate statistics and linear models, statistically significant taxonomic differences were not identified, but several statistical trends were identified. Almost all of these species are rare and detected in less than 25% of Early mice. Boxplots were created using only nonzero counts; 10'6corresponds to the limit of detection.

[0036] FIG. 19 provides graphs showing that mouse fecal metabolites were significantly different between LE and HE mice. The most discriminatory depleted (left panel) or enriched (right panel) metabolites that remained statistically significant after multiple comparison correction (P<0.05, linear mixed effects models with false discovery rate correction) are shown.

[0037] FIG. 20 is a heatmap illustrating that mouse fecal metabolites were significantly different between LE and HE mice. Discriminatory metabolites that were statistically significant without multiple comparison correction (P<0.05, linear mixed effects models) are shown. Heatmap displays Spearman’s rho correlation between pairs of metabolites. Metabolites have the same order in rows (top to bottom) and columns (left to right). Using hierarchical clustering, metabolites were grouped into seven clusters. Within clusters, metabolites were either all enriched (1, 2, 5, 6), all depleted (3, 4), or had mixed trends (7) in high-scoring mice.

[0038] FIGS. 21A-2B are plots showing that the metabolic groups were significantly different between LE and HE mice. Pathway enrichment analysis was performed to identify classes or groups of metabolites that were collectively enriched or depleted in either LE or HE mice (FIG. 21A). Groups with positive (right) scores are enriched in LE mice whereas groups negative (left) scores are depleted in contrast to HE mice. FIG. 2 IB shows metabolites enriched or depleted with p < 0.01 and 7 metabolites passed multiple comparison corrections. *p < 0.05.

[0039] FIG. 22A is a schematic diagram showing that free amino acids are depleted in LE mice (left panel) but normalized in LL mice (right panel). Out of 20 amino acids, 19 had lower median abundance in LE than HE mice. A similar pattern was detected for dipeptides where 28 out of 30 dipeptides had lower median abundance in LE than HE mice, while these differences normalized between LL and HL mice. FIG. 22B is a schematic diagram showing that dipeptides are depleted in LE mice as compared to HE mice. FIG. 22C is a schematic diagram showing significantly depleted and enriched metabolic groups.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)

[0040] FIGS. 23A-23B are graphs showing that microbial tryptophan synthesis genes and tryptophan metabolites are depleted in LE mice microbiomes. Microbial genes involved in tryptophan synthesis were enriched in HE mice feces (FIG. 23 A). Tryptophan and four of its metabolic derivatives were enriched in HE mice feces (FIG. 23B).

[0041] FIG. 24 is a schematic diagram showing predictive models based on the top 18 metabolites that discriminate LE and HE mice. After identifying the top 18 metabolites using linear models, the ability of these metabolites to predict whether mouse feces were collected from an LE or HE mouse line were evaluated. Prediction was performed using cross-validated random forest classifiers and evaluated using the accuracy metric.

[0042] FIG. 25 provides boxplots for six mouse fecal metabolites identified with a machine learning model that can accurately predict the B SID score of the microbiome donor. A machine learning pipeline that combines random forest classifiers and feature selection with Wilcoxon rank-sum tests identified six features that collectively have a predictive accuracy of 78% (crossvalidated accuracy of 68%). The boxplots display the scaled abundance of these metabolites in LE and HE mice. Each data point is the median fecal abundance across 4 mice from the same line.

[0043] FIG. 26 is a schematic diagram showing the species-metabolite correlations informed rational design of microbial consortia for rescuing behavior. The networks display the highest correlation between kynurenine (left) and N-carbamoylputrescine (right) with microbial species (green), metabolites (yellow), and microbial genes / proteins (blue and orange). Edge color indicates direction of positive (red) or negative (blue) correlations, whereas edge thickness indicates strength of correlation.

[0044] FIG. 27 is a graph showing the mortality in mouse offspring of rescue lines. In each set of bars, the results from left to right are from an original low scoring line, self-control, and mouse line rescued by FMT of a high scoring fecal slurry (one early, three late). The parent and self-control animals had significantly increased mortality compared to all other groups.

[0045] FIGS. 28A-28B are graphs demonstrating that behavior is improved with HS FMT. The results in FIG. 28A are for light dark box assessments, and the results in FIG. 28B are for contextual fear assessments. The results were scored as described (n=16 or 24, half male half female). Statistical analysis **** p < 0.0001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons.

[0046] FIG. 29 is a graph showing that FMT from HS feces reduces pro-inflammatory eotaxin. Mouse blood was collected by cardiac puncture immediately prior to sacrifice. PlasmaATTORNEY DOCKET NO. 090464-1548125 (024WO1)was recovered in K2-EDTA collection tubes. Immune markers were quantified by multiplexed ELISA. For each of three LS lines, the level of eotaxin is shown for the original low scoring line, the self-control, and mouse lines rescued by FMT of one of three high scoring lines fecal slurry (n=6 per group, 3M, 3F). The parent and self-control animals had significantly increased levels compared to the matched rescue lines. Statistical analysis **** p < 0.0001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons.

[0047] FIG. 30 is a graph showing that FMT from HS feces stimulates IL-10 release. Mouse blood was collected by cardiac puncture immediately prior to sacrifice. Plasma was recovered in K2-EDTA collection tubes. Immune markers were quantified by multiplexed ELISA. For each of three LS lines, the level of IL-10 is shown for the original low scoring line, the self-control, and mouse lines rescued by FMT of one of three high scoring lines fecal slurry (n=6 per group, 3M, 3F). IL- 10 was undetectable in the plasma of the parent and self-control animals and present in all rescue lines. There were no significant differences noted between males and female animals. (Values for the limit of detection were assigned where appropriate. Statistical analysis **** p < 0.0001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons.

[0048] FIGS. 31A-31D are graphs showing that amino acid concentrations are increased after FMT from HS feces. Amino acid concentrations were measured by quantitative targeted metabolomics. In each graph, from left to right, the results are shown for the original low scoring line, self-control, mouse lines rescued by FMT of one of three high scoring lines fecal slurry (n=6 per group, 3M, 3F). Tryptophan (FIG. 31 A), tyrosine (FIG. 3 IB), and glutamate (FIG. 31C) all showed significant increases after FMT with HS feces. Combining all 20 amino acid values in each sample resulted in a similar trend (FIG. 3 ID). Statistical analysis **** p < 0.0001, *** p < 0.001, ** p < 0.01, * p < 0.1 by Two Way ANOVA, with Tukey’s correction for multiple comparisons.

[0049] FIGS. 32A-32B are graphs showing that HS FMT increases Kynurenine and gamma-aminobutyric acid (GABA) concentrations in mouse plasma. In each figure, from left to right, the results are shown for the three low scoring lines, two self controls, and each of the three LS mouse lines rescued by FMT of one of two HS lines fecal slurry. Kynurenine (FIG.32A) and GABA (FIG. 32B) levels in mouse plasma were measured by targeted metabolomics. The fold change over the average value in the self-control or parent line was calculated. In all cases, successful rescues had a 2-4 fold change in these neuroactive molecules. StatisticalATTORNEY DOCKET NO. 090464-1548125 (024WO1)analysis **** p < 0.0001, by Two Way ANOVA, with Tukey’s correction for multiple comparisons.

[0050] FIG. 33 is a graph showing mortality in mouse offspring in the testing of microbial consortia intervention. From left to right, the mortality percentage is shown for Germ free control, NS mouse line control, parent LSI 1-60, a successful rescue consortia, and two unsuccessful rescue consortia. CS1 includes Bacteroides thetaiotaomicron, Bacteroides cellulosdyticus, and Parabacteroides distasonis. CS2 includes three Bifidobacteria strains, and CS3 includes Clostridioides difficde and Enterococcus faecalis. CS1 had significantly lower mortality, while CS2 and CS3 had significantly higher mortality.

[0051] FIG. 34 is a graph showing that LS 11 - CS 1 restored time in the light side to normal scoring levels. All data points are shown for representatives of each group. From left to right, the results are shown for controls (n=24), normal scoring lines, a low scoring animal (n=24), and low scoring animals given CS1 or CS2 bacterial strain cocktail (n=16). CS1 (purple) treatment rescued the behavioral deficit of the parent line (red) while CS2 (gray) did not. Statistical analysis **** p < 0.0001 by Two Way ANOVA, with Tukey’s correction for multiple comparisons. Each testing group of animals was 50% male and 50% female.

[0052] FIG. 35 is a graph showing that LSI 1 - CS1 reversed the LSI deficit in contextual memory. The percent of time spent immobile during contextual testing was calculated for all animals. From left to right, the results are shown for controls, mouse lines from normal scoring infants, a mouse line from low scoring infants (LSI 1-60), CS1, or CS2. LSI 1-60 did not associate environment with adverse outcomes, while treatment with CS1 but not CS2 reversed this phenotype. (n= 12-24, half male and half female) Statistical analysis **** p < 0.0001, Two Way ANOVA with Tukey’s correction for multiple comparisons. All other groups were not significantly different.

[0053] FIGS. 36A-36C are graphs showing the fold change of fecal Kynurenine (FIG.36 A), tryptophan (FIG. 36B), and glutamate (FIG. 36C) concentrations following treatment with a bacterial consortia CS 1. FIGS. 36A-36C show results for four low-scoring backgrounds (LSI 1, LSI, LS4, LS6), demonstrating that levels were restored by CS1 but not by FMT from the same LS infant or by FMT from a control LS infant (LS11). P < 0.01. FIG. 36D shows results for four high-scoring backgrounds (HS14, HS2, HS19, HS3), demonstrating that there was no significant increase in the levels observed after treatment with CS1 or with FMT from a control HS infant (HS14).ATTORNEY DOCKET NO. 090464-1548125 (024WO1)

[0054] FIGS. 37A-37B are graphs showing the fecal Kynurenine concentration in four low-scoring backgrounds (LSI 1, LSI, LS4, LS6) before and after treatment with bacterial consortia CS1 V2 (FIG. 37A) or CS1 V3 (FIG. 37B). Levels were restored by both CS1 V2 and CS1 V3, but not by FMT from the same LS infant or by FMT from a control LS infant (LSI 1).

[0055] FIGS. 38A-38B are graphs showing the fecal Kynurenine concentration in four low-scoring backgrounds (LS11, LSI, LS4, LS6) before and after treatment with Bacteroides thetaiotaomicron (CS6) (FIG. 38A) or Parabacteroides distasonis (CS8) (FIG. 38B). Neither species, when administered individually, produced a significant increase in fecal Kynurenine across any of the four LS-derived backgrounds.

[0056] FIG. 39 is a graph showing that increases in GABA levels in mouse feces associated with improved outcomes can be detected 3 weeks post FMT transfer. Fecal samples were collected from mice 3 weeks post whole FMT transfer and targeted metabolomics were performed. Two low-scoring backgrounds and two successful HS transfers were tested. In all combinations, the GABA levels increased over the self-control mice, indicating that the testing regimen may be significantly shortened to screen microbial candidates.

[0057] FIGS. 40A-40C are graphs showing that widespread astrocyte activation is present in the brains of mice from low early lines. Brain sections of adult mice from low (left bar in each group), normative (middle bar in each group), and high (right bar in each group) scoring early and late mouse lines were immunostained with antibodies against the activated astrocyte marker GFAP, and then imaged (lOx) and analyzed for GFAP staining intensity in the cortex (FIG. 40A), hippocampus (FIG. 40B), and hypothalamus (FIG. 40C). Individual mice are represented as squares (males, n=5-8) or circles (female, n=6-8). The data were normalized to values from normative early mice and represented as mean values ± SEM. Statistical significance was calculated by Two-way ANOVA followed by Tukey’s multiple comparisons test. **p<0.01, ****p<0.0001.

[0058] FIGS. 41A-41C are graphs showing that microglia activation is present in the cortex, hippocampus, and hypothalamus of mice from low scoring early and late lines. Brain sections of adult mice from low (left bar in each group), normative (middle bar in each group), and high (right bar in each group) scoring, early and late mouse lines were immunostained with antibodies against the microglia marker Ibal, and then imaged (lOx) and analyzed for Ibal intensity in the cortex (FIG. 41A), hippocampus (FIG. 41B), and hypothalamus (FIG. 41C). Individual mice are represented as squares (males, n=5-8) or circles (female, n=6-8). The data were normalized to the normative early mouse group and represented as mean values ± SEM.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)Statistical significance was calculated by Two-way ANOVA followed by Tukey’s multiple comparisons test. **p<0.01, ****p<0.0001.

[0059] FIGS. 42A-42C are graphs demonstrating that the key inhibitory synapse marker Gephyrin is elevated in the hippocampus and prefrontal cortex of low early (LE) mice relative to normative (NE) and / or high early (HE) mice. Inhibitory synapses in low (left bar in each group), normative (middle bar in each group), and high (right bar in each group) scoring early and late time point mice were visualized by immunostaining brain sections with antibodies against the inhibitory postsynaptic marker Gephyrin. Stained brain sections were imaged at 63x with a high-resolution confocal microscope and then analyzed for synaptic marker intensity. Quantification of gephyrin staining intensity is shown for the hippocampal brain regions DG (FIG. 42A) and CAI (FIG. 42B) and for the cortical region PFC (FIG. 42C). Individual mice are represented as squares (males, n=5- 8) or circles (female, n=4-8). The data were normalized to the normative early mice and represented as mean values ± SEM. Statistical significance was calculated by Two-way ANOVA followed by Tukey’s multiple comparisons test. *p<0.05, **p<0.01, ***p<0.001. DG, dentate gyrus; CAI, Cornu Ammonis 1; PFC, prefrontal cortex.

[0060] FIGS. 43A-43C are graphs showing that the key excitatory postsynaptic marker PSD95 is reduced in the hippocampus of mice generated from the microbiomes of high scoring infants relative to normative scoring infants. Excitatory synapses in low (left bar in each group), normative (middle bar in each group), and high (right bar in each group) early and late time point mice were visualized by immunostaining brain sections with antibodies against the excitatory postsynaptic marker PSD95. Stained brain sections were imaged at 63x with a high-resolution confocal microscope and then analyzed for postsynaptic marker staining intensity. Quantification of PSD95 intensity is shown for the hippocampal regions DG (FIG. 43 A) and CAI (FIG. 43B) and the prefrontal cortex (PFC) (FIG. 43C). Individual mice from the various groups are represented as squares (males, n=4-7) or circles (female, n=4-6). The data were normalized to NE mice and represented as mean values ± SEM. Statistical significance was calculated by Two-way ANOVA followed by Tukey’s multiple comparisons test. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0061] FIGS. 44A-44E provide the results of brain immunochemistry analyses showing the aberrant synaptic architecture and widespread neuroinflammation in LE mice. FIG. 44A provides graphs showing that the key neuromodulator Serotonin (5-HT) is reduced in the cortex and hippocampus of mice generated from low scoring early infant microbiomes. Fixed brainATTORNEY DOCKET NO. 090464-1548125 (024WO1)sections from low (LE) and high (HE) scoring early time point mice were immunostained with antibodies against 5-HT to visualize serotonergic inputs. Brain sections were then imaged at 40x with a confocal microscope and analyzed for 5-HT staining density. Quantification of 5-HT staining is shown for the cortex and hippocampal regions CAI and dentate gyrus (DG). Individual mice are represented as circles (N=l 1-13). The data were normalized to LE mice and represented as mean values ± SEM. *p<0.05, **p<0.01. FIGS. 44B-44E provide graphs showing the ratio of the staining intensity in LE to HE scoring mice for gephyrin (FIG. 44B), PSD-95 (FIG. 44C), Ibal (FIG. 44D), and GFAP (FIG. 44E).DETAILED DESCRIPTION

[0062] The following description recites various aspects and embodiments of the present compositions and methods. No particular embodiment is intended to define the scope of the compositions and methods. Rather, the embodiments merely provide non-limiting examples of various compositions and methods that are at least included within the scope of the disclosed compositions and methods. The description is to be read from the perspective of one of ordinary skill in the art; therefore, information well known to the skilled artisan is not necessarily included.I. Introduction

[0063] Although numerous strategies are available to support children once diagnosed as having a developmental delay, less is known about the specific causes of developmental delays. The infant gut microbiome has been linked to infant neurodevelopment, and an association of infant composite cognition with the composition of the microbiome may be established as soon as 6 months. See, e.g., Cerdo etal., 2023, Cell Host & Microbe 31:1974-88. Research regarding the effect on the infant microbiome and particular components of the microbiome on development remains of great interest. The present disclosure describes a new metabolic disorder associated with infants having lower scores on a neurodevelopmental screen. The metabolic disorder is caused, at least in part, by certain bacterial strains present in the subject’s microbiome, which decrease the concentration of amino acids and metabolites and / or increase inflammation and neuroinflammation in the subject. Based on the discovery of this new metabolic disorder, the present disclosure provides methods for diagnosing the metabolic disorder, methods for the early identification of infants at risk of developmental delays, and compositions and methods for treating the metabolic disorder in infants.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)II. Definitions

[0064] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. All patents, patent applications and publications referred to throughout the disclosure herein are incorporated by reference in their entirety.

[0065] Articles “a” and “an” are used herein to refer to one or to more than one (i.e. at least one) of the grammatical object of the article. By way of example, “an element” means at least one element and can include more than one element.

[0066] The use of any and all examples or exemplary language (e.g., “such as”) provided herein, is intended merely to better illustrate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed.

[0067] The terms “may,” “may be,” “can,” and “can be,” and related terms are intended to convey that the subject matter involved is optional (that is, the subject matter is present in some examples and is not present in other examples), not a reference to a capability of the subject matter or to a probability, unless the context clearly indicates otherwise.

[0068] “About” is used to provide flexibility to a numerical range endpoint by providing that a given value may be “slightly above” or “slightly below” the endpoint without affecting the desired result.

[0069] The terms “optional” and “optionally” mean that the subsequently described event, circumstance, or material may or may not occur or be present, and that the description includes instances where the event, circumstance, or material occurs or is present as well as instances where it does not occur or is not present.

[0070] The use herein of the terms “including,” “comprising,” or “having,” and variations thereof, is meant to encompass the elements listed thereafter and equivalents thereof as well as additional elements. Embodiments recited as “including,” “comprising,” or “having” certain elements are also contemplated as “consisting essentially of’ and “consisting of’ those certain elements. As used herein, “and / or” refers to and encompasses any and all possible combinations of one or more of the associated listed items, as well as the lack of combinations where interpreted in the alternative (“or”).

[0071] As used herein, the transitional phrase “consisting essentially of’ (and grammatical variants) is to be interpreted as encompassing the recited materials or steps “and those that do not materially affect the basic and novel characteristic(s)” of the claimed invention. See In re Herz, 537F.2d 549, 551-52 (CCPA 1976) (emphasis in the original); .scca / .w MPEP §2111.03.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)Thus, the term “consisting essentially of’ as used herein should not be interpreted as equivalent to “comprising.”

[0072] Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise-indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. For example, if a concentration range is stated as 1% to 50%, it is intended that values such as 2% to 40%, 10% to 30%, or 1% to 3%, etc., are expressly enumerated in this specification. These are only examples of what is specifically intended, and all possible combinations of numerical values between and including the lowest value and the highest value enumerated are to be considered to be expressly stated in this disclosure.III. Methods for Analysis of Microbiome

[0073] Provided herein are compositions and methods that may be used to study a subject that has, is suspected of having, or is at risk of having a metabolic disorder characterized by a reduction of amino acids or metabolites in a biological sample from the subject and / or an increase in inflammation and neuroinflammation in the subject. In some embodiments, the disclosed methods are for detecting a microbiome component or biomarker associated with the metabolic disorder. For example, the level of the microbiome component or biomarker may be measured by measuring expression of a bacterial gene or a level of a bacterial function, or by measuring expression of a host gene or function. In some embodiments, the disclosed methods are for diagnosing a subject as having the metabolic disorder.Methods for Detection

[0074] Methods are provided for detecting a microbiome component or biomarker associated with a metabolic disorder in a subject. In some embodiments, the methods include obtaining a biological sample from the subject; measuring a level of a microbiome component or biomarker in the biological sample, wherein the microbiome component comprises one or more bacterial strains; and determining if the level of the microbiome component or biomarker is increased or decreased as compared to a control. In some embodiments, the level of the microbiome component is measured directly. In some embodiments, the level of the microbiome component is measured indirectly, by detecting one or biomarkers.Detection of microbiome constituent

[0075] In some embodiments, the level of the microbiome component may be measured directly in a sample from the subject. As used throughout, the term “subject” refers to an individual. Typically, the subject in need of administration of a disclosed composition has, isATTORNEY DOCKET NO. 090464-1548125 (024WO1)suspected of having, or is at risk of having a metabolic, cognitive, or neurodevelopmental disorder or delay. The subject can be a pediatric subject ranging in age from birth to five years of age. Thus, pediatric subjects of less than five years of age, two years of age, one year of age, six months of age, five months of age, four months of age, three months of age, two months of age, one month of age, three weeks of age, two weeks of age, one week of age, six days of age, five days of age, four days of age, three days of age, two days of age, one day of age, or any age between these ages, are included as subjects. In some embodiments, the subject is 0 to 12 months of age. In certain embodiments, the subject is 0 to 6 months of age. Preferably, the subject is an animal, for example, a mammal such as a primate, and, more preferably, a human. Non-human primates are subjects as well. The term subject includes domesticated animals, such as cats, dogs, etc., livestock (for example, cattle, horses, pigs, sheep, goats, etc.) and laboratory animals (for example, ferret, chinchilla, mouse, rabbit, rat, gerbil, guinea pig, etc.). Thus, veterinary uses and medical formulations are contemplated herein.

[0076] A biological sample may be any sample from a subject that includes a microbiome of the subject. In some embodiments, the biological sample is a fecal sample. In some embodiments, the biological sample is selected from a group consisting of a colonic lavage fluid, luminal brush, blood, plasma, serum, cerebrospinal fluid, pinch biopsy, sub-mucosal biopsy, synovial fluid, urinary sample, dental plaque, saliva, and skin.

[0077] As used herein, the terms “microbiome,” “microbiota,” “gut microbiome,” and “gut microbiota” refer to the microorganisms (microbes), including bacteria, archaea, fungi, and viruses, that live in the digestive tract of a subject. Bacteria are the largest component of the microbiome. A newborn establishes its microbiome through interaction with, for example, its mother, maternal milk, maternal gut, delivery method, family, pet, and a host of environmental factors. See, e.g., Enav et al., 2022, Cell Host & Microbe 30:627-637; Ma et al., 2023, Front. Cell Infect. Microbiol. 13:1-12. The microbiome is dynamic and changes over time. See, e.g., Enav, 2022; Alessandri et al., 2022, npj Biofilms and Microbiomes, 8(88). The infant microbiome, therefore, has a lower number of total species of microorganisms than an adult gut microbiome, and the number of microorganisms increases and the composition changes over time. Intestinal dysbiosis, where there is an alteration or imbalance in the gut microbiome of the subject, may result in various conditions and diseases. The dysbiosis in an infant microbiome may be particularly important as it may affect the infant’s development and / or susceptibility to conditions and diseases throughout life. As used herein, the term “microbiome component” or “component of a microbiome” refers to one or more constituents of theATTORNEY DOCKET NO. 090464-1548125 (024WO1)microbiome (e.g., bacteria, archaea, fungi, viruses). For example, a microbiome component may include, but is not limited to, one or more bacteria present in the microbiome of the subj ect.

[0078] In some embodiments, the methods are used to measure the level of one or more bacteria of the phyla Actinobacteria, Actinomycetota, Bacillota, Bacterioidata (Bacteroidetes), Deferribacteraceae, Firmicutes, Fusobacteriota, Proteobacteria, Pseudomonadota, Mycoplasmatota (Teneri cutes), and Verrucomicrobia in a biological sample of the subject. In some embodiments, the level of one or more bacteria may be performed by analyzing (e.g., by sequencing) at least a portion of the bacterial genome of the bacteria present in the sample. In certain embodiments, the portion of the bacterial genome has at least 80% sequence identity (e.g., at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100% sequence identity) to the sequence of a bacterial species associated with depletion of an amino acid or metabolite as disclosed in this application. In some embodiments, the methods are used to measure the level of one or more bacteria that decrease or deplete the level of amino acids or metabolites in a subject as compared to a control. The decrease in the level of amino acids or metabolites may be a decrease in concentration of 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43%, 44%. 45%, 46%, 47%, 48%, 49%, 50%, or more of the amino acids or metabolites as compared to a control. In any of the methods disclosed, a control may be a value observed for a normal subject (e.g., a subject that does not have the metabolic disorder) or a value observed for the subject prior to treatment. A control can also be a reference value.

[0079] In some embodiments, the methods are used to measure the level of one or more bacteria that maintain or increase the level of amino acids or metabolites in a subject. For example, the one or more bacteria may include, but are not limited to, bacteria of the genus Turicibacler. Luxibacler. Parabacteroides, Bacteroides, Enterococcus, Bifidobacterium, Phocaeicola, and Eggerthella, and combinations thereof. In some embodiments, the compositions may include one or more of Turicibacter sp. 1E2, Luxibacter massiliensis, Parabacteroides distasonis, Bacteroides thetaiotamicron, Lachnospiraceae bacterium, Enterococcus avium, Bifidobacterium longum, Phocaeicola dorei, Bacteroides caccae, and Eggerthella lenta. The increase in the level of amino acids or metabolites may be an increase in concentration of 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43%, 44%. 45%, 46%, 47%, 48%, 49%,ATTORNEY DOCKET NO. 090464-1548125 (024WO1)50%, or more of the amino acids or metabolites as compared to a control. In certain embodiments, the one or more bacteria comprise a sequence that has at least 80% sequence identity (e.g., at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100% sequence identity) to one or more of the sequences provided by GenBank Accession Nos. GCA_014131755.1 (Bacteroides thetaiotaomicrori), GCA_018292125.1 (Bacteroides cellulosilyticus), and GC A O 18279895.1 (Parabacteroides distasonis).

[0080] An amino acid refers to any monomer unit that can be incorporated into a peptide, polypeptide, or protein. As used herein, the term “free amino acid” refers to an amino acid that is not incorporated in a polypeptide. The twenty natural or genetically encoded alpha-amino acids are as follows: alanine (Ala or A), arginine (Arg or R), asparagine (Asn or N), aspartic acid (Asp or D), cysteine (Cys or C), glutamine (Gin or Q), glutamic acid (Glu or E), glycine (Gly or G), histidine (His or H), isoleucine (He or I), leucine (Leu or L), lysine (Lys or K), methionine (Met orM), phenylalanine (Phe or F), proline (Pro or P), serine (Ser or S), threonine (Thr or T), tryptophan (Trp or W), tyrosine (Tyr or Y), and valine (Vai or V). The structures of these twenty natural amino acids are shown in, e.g., Stryer et al., 2002, BIOCHEMISTRY, 5thed., Freeman and Company. In certain embodiments, the term amino acid also includes unnatural amino acids, modified amino acids (e.g., having modified side chains and / or backbones), and amino acid analogs. An amino acid metabolite refers to a molecule produced in a metabolic pathway of an amino acid. Examples of metabolites include, but are not limited to, S-lpyrroline-5-carboxylate, N-butyryl-leucine, N6-carboxyethyllysine, N6-acetyllysine, Glutarylcarnitine (C5-DC), 3 -sulfo-alanine, N-butyryl-phenylalanine, Phenyllactate (PLA), N-carbamoylputrescine, spermine, indoxyl glucuronide, and kynurenine.

[0081] In some embodiments, the step of measuring the level of a microbiome component in the biological sample comprises measuring the presence or absence of the microbiome component in the sample. In some embodiments, the concentration of the microbiome component is measured. The level of the microbiome component may be measured by any methods known in the art for measuring the component. For example, a microbiome component may be measured by molecular assays (e.g., PCR, sequencing), culture tests, staining, and biochemical assays. In some embodiments, the components are measured by amplicon sequencing, whole genome shotgun sequencing, and / or PCR.Detection of biomarkers

[0082] In some disclosed methods, the level of the microbiome component is measured indirectly, by detecting a level of one or biomarkers that are indicative of the presence of theATTORNEY DOCKET NO. 090464-1548125 (024WO1)microbiome component in the subject’s microbiome or the subject’s response to the presence of the microbiome component. For example, the one or more biomarkers may include an amino acid, a metabolite, or a cofactor of a metabolic pathway or a molecule that is affected by such pathway. In some embodiments, the biomarker is selected from a group consisting of an amino acid, kynurenine, GABA, eotaxin, IL-10, and cortisol.

[0083] In some embodiments, the amino acid, metabolite, or cofactor is associated with a pathway selected from a group consisting of an amino acid, carbohydrate, vitamin, tricarboxylic acid (TCA) cycle, lipid, nucleotide, peptide, or xenobiotic metabolic pathway. Examples of other biomarkers that may be measured include, but are not limited to, the one or more biomarkers selected from a group consisting of alanine, S-l-pyrroline-5-carboxylate, glutamine, N-butyryl-leucine, N6-carboxyethyllysine, N6-acetyllysine, glutarylcamitine (C5-DC), 3 -sulfo-alanine, N-butyryl-phenylalanine, phenyllactate (PL A), N-carbamoylputrescine, spermine, indoxyl glucuronide, kynurenine, N-alpha-acetylornithine, N6-carboxymethyllysine, glucuronate, ribose, oxalate (ethanedi oate), flavin mononucleotide (FMN), 5-(2-hydroxyethyl)-4-methylthiazole, aconitate [cis or trans], N-stearoyl-sphingosine (d!8: 1 / 18:0)*, Undecenoylcarnitine (Cl 1:1), hexanoylglycine, 3-hydroxypalmitate, 1-palmitoyl-2-linoleoyl-diglaactosylglycerol (16:0 / 18:2)*, docosahexaenoate (DHA; 22:6n3), arachidonate (20:4n6), l-palmitoyl-2-linoleoyl-GPC (16:0 / 18:2), phytosphingosine, N-stearoyl-phytosphingosine (tl 8 :0 / l 8 :0)*, sphingosine, heptadecasphingosine (dl7:l), xanthine, hypoxanthine, adenine, N1 -methyladenosine, guanine, thymidine 5'-monophosphate, uridine 5'-monophosphate (UMP), phenylacetylglutamine, phenylacetylglycine, glutaminylleucine, leucylalanine, lyslleucine, alanylleucine, p-cresol sulfate, hippurate, benzoate, 3,5-dihydroxyphenylpropionate, and pyrraline. Biomarkers may be measured by any methods known to one of skill in the art for measuring the particular biomarker, for example, by measuring binding to a substrate or ligand, spectrometry, chromatography, bioactivity assay, and the like.

[0084] In some methods, the one or more biomarkers comprise a dipeptide, phosphatidylcholine, or both; and wherein a decrease in the level of the biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject. In some methods, the one or more biomarkers comprise one or more of a dicarboxylate fatty acid, S-l-pyrroline-5-carboxylate, N-butyryl-phenylalanine, N-butyryl-leucine, N-carbamoylputrescine, uridine 5'-monophosphate (UMP), 3-hydroxypalmitate, flavin mononucleotide (FMN), hypoxanthine, N6-carboxyethyllysine, phenyllactate (PLA),ATTORNEY DOCKET NO. 090464-1548125 (024WO1)kynurenine, and l-palmitoyl-2-linoleol-GPC (16:0 / 18:2); and a decrease in the level of the biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject. In some embodiments, the one or more biomarkers comprise a metabolite or cofactor of an acyl glycine, chemical, medium chain acyl carnitine, benzoate, lysophospholipid, ascorbate and aldarate, long chain polyunsaturated fatty acid, creatine, or TCA cycle metabolic pathway; and an increase in the level of the biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject.

[0085] The methods may include measuring the level of two, three, four, five, six, seven, eight, nine, ten, or more biomarkers. In some embodiments, the methods include measuring the level of six biomarkers. In some embodiments, the methods include measuring the level of an amino acid, kynurenine, GABA, eotaxin, IL-10, and cortisol. In certain embodiments, an increase in the level of eotaxin or cortisol as compared to a control, and a decrease in the level of an amino acid, kynurenine, GABA, or IL-10 as compared to a control, are associated with the metabolic disorder in the subject. In some embodiments, the methods include measuring a level of phytosphingosine, arachidonate, docosahexaenoate, glutamine, pyrraline, and DGDG 16:0 / 18:2. In certain embodiments, an increase in the level of phytosphingosine, arachidonate, and docosahexaenoate as compared to a control, and a decrease in the level of glutamine, pyrraline, and DGDG 16:0 / 18:2 as compared to a control, are associated with the metabolic disorder in the subject.Detection of Effect in Germ-Free Mouse Model

[0086] In some disclosed methods, the level of the microbiome component is measured indirectly, by determining the effect of the biological sample in a mouse model. These methods include administering or contacting a portion of the subject’s biological sample with a germ-free mouse and then measuring a level of a microbiome component in a mouse biological sample or measuring a behavior of the mouse. In some embodiments, the mouse biological sample is a mouse fecal sample. In some embodiments, the level of the microbiome component in the mouse sample is measured as discussed for the subject’s sample in the previous sections. In some methods, the level of the microbiome component in the mouse biological sample is measured indirectly, by detecting a level of one or biomarkers that are indicative of the presence of the microbiome component in the mouse’s biological sample. For example, the one or more biomarkers may include an amino acid, a metabolite, or a cofactor of a metabolic pathway or a molecule that is affected by such pathway. In some embodiments, the mouse behavior isATTORNEY DOCKET NO. 090464-1548125 (024WO1)measured in a behavioral test, such as, but not limited to, a novel object recognition test, a fear conditioning test, or a sociability or social novelty test.Methods of Diagnosis

[0087] Methods are provided for diagnosing a subject as having a metabolic disorder characterized by lower levels of an amino acid or metabolite in a biological sample from the subject. In some embodiments, the metabolic disorder negatively affects cognition or neurodevelopment in the subject, increases inflammation and neuroinflammation in the subject, or both. In certain embodiments, the metabolic disorder causes a developmental delay in the subject.

[0088] Infant and childhood development normally progresses through predictable phases. The development may be monitored by a number of physical, cognitive, social-emotional, linguistic, and behavioral milestones. Numerous assessments are known to those of ordinary skill in the art for monitoring development and diagnosing developmental delays. These assessments include, but are not limited to the Bayley Scales of Infant and Toddler Development (BSID (e.g., BSID-4)), the Harris Infant Neuromotor Test (HINT), Battelle Developmental Inventory (BDI), Developmental Assessment of Young Children (DAYC), the Cognitive Assessment of Young Children (CAYC), Assessment Evaluation & Programming System (AEPS), Early Learning Accomplishment Profile (ELAP), Infant Toddler Developmental Assessment (IDA), Brigance Inventory of Early Development, Parents’ Evaluation of Developmental Status (PEDS), The Survey of Well being of Young Children (SWYC), Ages and Stages Questionnaires (ASQ-3), Modified Checklist for Autism in Toddlers (M-CHAT), and Global Scale for Early Development (GSED). A developmental delay refers to a failure to meet one or more milestones by the predicted timeline of the particular developmental assessment.

[0089] In some embodiments, the diagnostic method includes a detection method as disclosed in any of the previous sections, further comprising diagnosing the subject as having the metabolic disorder or cognitive or neurodevelopmental condition if the level of the microbiome component or biomarker differs from the control. In some embodiments, the diagnostic method further includes diagnosing the subject as having the metabolic disorder or cognitive or neurodevelopmental condition if a mouse that has been administered the subject’s microbiome sample exhibits a behavior that is negatively affected as compared to a control.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)IV. Therapeutic Compositions

[0090] Compositions are provided that may be used for the treatment of a subject that has, is suspected of having, or is at risk of having a metabolic disorder characterized by a reduction of amino acids or other metabolites in a biological sample from the subject, decreased cognition or delayed neurodevelopment, or increased inflammation and neuroinflammation in the subject. In some embodiments, the metabolic disorder is characterized by a reduction of an amino acid, a metabolite, or a cofactor of a metabolic pathway or a molecule that is affected by such pathway. For example, in some embodiments, the metabolic disorder is characterized by a change in the level of an amino acid, kynurenine, GABA, eotaxin, IL- 10, cortisol, or combinations thereof. In some embodiments, the disclosed compositions comprise a bacterial strain that is effective to increase the level of an amino acid or other metabolite in a biological sample of the subject.Bacterial Species

[0091] The present compositions may be used to restore an infant microbiome to a healthier composition for development. The disclosed compositions comprise a bacterial species that, upon administration to a subject, under conditions wherein the bacteria colonize the gut, increases the level of amino acids or metabolites in a biological sample of the subject, improves cognition or neurodevelopment, decreases the level of inflammation and neuroinflammation in the subject, or a combination thereof. In some embodiments, the disclosed compositions comprise two or more bacterial species. In other embodiments, the compositions include 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, or more bacterial species. In some embodiments, the disclosed compositions include one or more bacteria of the phyla Actinobacteria, Actinomycetota, Bacilotta, Bacterioidata (Bacteroidetes), Deferribacteraceae, Firmicutes, Fusobacteriota, Proteobacteria, Pseudomonadota Mycoplasmatota (Tenericutes), and Verrucomicrobia. In some embodiments, the present compositions include one or more bacteria of the genus Turicibacter , Luxibacler. Parabacteroides, Bacteroides, Lachnospiraceae, Enterococcus, Bifidobacterium, Phocaeicola, and Eggerthella. In some embodiments, the compositions may include one or more of Turicibacter sp. 1E2, Luxibacter massiliensis, Parabacteroides distasonis, Bacteroides thetaiotamicron, Lachnospiraceae bacterium, Enterococcus avium, Bifidobacterium longum, Phocaeicola dorei, Bacteroides caccae, and Eggerthella lenta. In certain embodiments, the compositions include a synergistic combination of two or more of Bacteroides thetaiotaomicron, Bacteroides cellulosilyticus, and Parabacteroides distasonis. In some embodiments, the bacteria are obtained from a fecalATTORNEY DOCKET NO. 090464-1548125 (024WO1)sample from one or more infants that have been designated as a high early scoring sample as described herein.

[0092] The disclosed compositions may comprise a therapeutically effective amount (i.e., an effective amount to increase the level of free amino acids or metabolites in a biological sample of the subject, improve cognition or neurodevelopment, decrease the level of neuroinflammation in the subject, etc.) of any of the bacterial combination as described herein and a pharmaceutical carrier. The term carrier means a compound, composition, substance, or structure that, when in combination with a composition, aids or facilitates preparation, storage, administration, delivery, effectiveness, selectivity, or any other feature of the compound or composition for its intended use or purpose. For example, a carrier can be selected to minimize any degradation of the active ingredient and to minimize any adverse side effects in the subject.

[0093] The disclosed compositions may be provided, for example, in the form of a powder, food / drink product, drink, liquid drops, capsule, tablet, or suppository. In some embodiments, the composition is formulated in a food / drink product. The food product may be, for example, an infant formula, an acidified milk, a milk powder, or a milk concentrate. In some embodiments, the bacteria are provided as a live culture. In some embodiments, the bacteria are lyophilized. In some embodiments, the bacteria are provided at about 0.005 mg to about 1,000 mg, or any value therein. Alternatively, the bacteria may be present in the composition at about 102to about 1012colony forming units (CFU). In some embodiments, the bacteria are present in the composition, for example, at about 1 x 102CFU / g, 5 x 102CFU / g, 1 x 103CFU / g, 5 x 103CFU / g, 1 x 104CFU / g, 5 x 104CFU / g, 1 x 105CFU / g, 5 x 105CFU / g, 1 x 106CFU / g, 5 x 106CFU / g, 1 x 107CFU / g, 5 x 107CFU / g, 1 x 108CFU / g, 5 x 108CFU / g, 1 x 109CFU / g, 5 x 109CFU / g, 1 x 1010CFU / g, 5 x 1010CFU / g, 1 x 1011CFU / g, 5 x 1011CFU / g, 1 x 1012CFU / g.

[0094] The pharmaceutical compositions can also contain a pharmaceutically acceptable excipient. Such excipients include any pharmaceutical agent that does not itself induce an immune response harmful to the individual receiving the composition, and which may be administered without undue toxicity. Pharmaceutically acceptable excipients include, but are not limited to, liquids such as water, saline, glycerol, sugars and ethanol. Pharmaceutically acceptable salts can be included therein, for example, mineral acid salts such as hydrochlorides, hydrobromides, phosphates, sulfates, and the like; and the salts of organic acids such as acetates, propionates, malonates, benzoates, and the like. Additionally, auxiliary substances, such as wetting or emulsifying agents, pH buffering substances, and the like, may be presentATTORNEY DOCKET NO. 090464-1548125 (024WO1)in such vehicles. The preparation of pharmaceutically acceptable carriers, excipients and formulations containing these materials is described in, e.g., Remington: The Science and Practice of Pharmacy, 22nd edition, Loyd V. Allen et al., editors, Pharmaceutical Press (2012). The disclosed compositions may include various pharmaceutically acceptable excipients, such as microcrystalline cellulose, mannitol, glucose, defatted milk powder, polyvinylpyrrolidone, starch and combinations thereof.

[0095] In some embodiments, the composition is formulated as a food or drink product or as an additive to food or drink product. In some embodiments, the disclosed composition may be prepared as a liquid drop to be administered to the subject. The concentration of the bacteria in the composition may vary, for example, depending upon the desired result, the type of bacteria used, and the form and method of administration.

[0096] In some embodiments, the disclosed composition may be prepared in a capsule. The capsule may be a hollow, generally cylindrical capsule formed from various substances, such as gelatin, cellulose, carbohydrate or the like. In addition to the bacteria, the capsule may include coloring, flavoring, rice or other starch, glycerin, caramel color, and / or titanium dioxide. In some embodiments, the composition is prepared as a tablet. The tablet may include the bacteria and one or more tableting agents, such as dibasic calcium phosphate, stearic acid, croscarmellose, silica, cellulose and cellulose coating. In some embodiments, the composition may be prepared as a suppository. The suppository may include the bacteria and one or more carriers, such as polyethylene glycol, acacia, acetylated monoglycerides, carnuba wax, cellulose acetate phthalate, corn starch, dibutyl phthalate, docusate sodium, gelatin, glycerin, iron oxides, kaolin, lactose, magnesium stearate, methyl paraben, pharmaceutical glaze, povidone, propyl paraben, sodium benzoate, sorbitan monoleate, sucrose talc, titanium dioxide, white wax and coloring agents.V. Methods of Treatment

[0097] Also provided herein are methods to treat, inhibit, or delay progression of a disorder or condition. In some embodiments, the subject has, is suspected of having, or is at risk of having a metabolic disorder characterized by lower levels of an amino acid or other metabolite in a biological sample from the subject. In some embodiments, the metabolic disorder negatively affects cognition or neurodevelopment in the subject, increases inflammation and neuroinflammation in the subject, or a combination thereof. In certain embodiments, the metabolic disorder causes a developmental delay in the subject. In some embodiments, the methods of treatment according to the present disclosure can include administering to a subjectATTORNEY DOCKET NO. 090464-1548125 (024WO1)a composition comprising bacterial species that, upon administration to the subject under conditions wherein the bacteria colonize the gut, increase the level of amino acids or other metabolites in a biological sample of the subject, improve cognition or neurodevelopment, decrease the level of inflammation and neuroinflammation in the subject, or a combination thereof. The subject can be a pediatric subject ranging in age from birth to five years of age. Thus, pediatric subjects of less than five years of age, two years of age, one year of age, six months of age, five months of age, four months of age, three months of age, two months of age, one month of age, three weeks of age, two weeks of age, one week of age, six days of age, five days of age, four days of age, three days of age, two days of age, one day of age, or any age between these ages, are included as subjects. In some embodiments, the subject is 0 to 12 months of age. In some embodiments, the subject is an infant of 0 to 6 months in age.

[0098] “Treating,” “treatment,” and the like may refer to any indicia of success in the treatment or amelioration of the disorder or condition. Treating or treatment of the disorder or condition refers to ameliorating the disorder or condition in a subject or any one or more symptoms thereof. The term ameliorating refers to any therapeutically beneficial result in the treatment of the disorder or condition, or lessening in the severity or progression. Thus, treating or treatment includes ameliorating at least one physical parameter or symptom. For example, “treating” or “treatment” with respect to the metabolic disorder includes the administration of a disclosed composition to increase the amino acids or other metabolites as disclosed above. Thus, in the disclosed methods, treatment can refer to at least a 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100% , 200%, 300%, 400%, or 500% increase, or any value in between, in the level of the amino acid or other metabolite. In another example, a method for treating the disorder or condition in a subject by administering a composition as described in this disclosure is considered to be a treatment if there is a 10% reduction in one or more symptoms (e.g., neuroinflammation) of the disorder or condition in a subject as compared to a control. Thus the reduction can be a 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, or any percent reduction in between 10% and 100% as compared to level at the time of treatment. In some embodiments, the composition increases the level of GABA in the subject. In some embodiments, the composition increases the level of kynurenine in the subject. In some embodiments, administration of the composition increases the level of IL- 10 in the subject. In some embodiments, administration of the composition lowers the level of cortisol in the subject. In some embodiments, administration of the composition lowers the level of eotaxin in the subject. The effect of treatment can be compared to an individual or pool of individualsATTORNEY DOCKET NO. 090464-1548125 (024WO1)not receiving the treatment, or to the same subject prior to treatment or at a different time during treatment.

[0099] The term “administer,” as used herein, refers to a method of delivering the disclosed compositions to the subject. The pharmaceutical compositions (e.g., as described above) are prepared for administration in a number of ways, including but not limited to ingestion and absorption. In some embodiments, the composition is formulated for oral administration. In some embodiments, the composition is formulated in a food product. In some embodiments, the composition is an infant formula, a liquid drop, an acidified milk, a milk powder, or a milk concentrate.

[0100] As used herein, the term “therapeutically effective amount” or “effective amount” refers to an amount of a therapeutic composition that, when administered to a subject, is effective to treat a disorder or condition such that the symptoms of the disorder or condition are ameliorated. A therapeutically effective amount is not, however, a dosage so large as to cause adverse side effects. A suitable dose of a therapeutic composition as described herein, which dose is capable of treating a disorder or condition in a subject, can depend on a variety of factors including the particular therapeutic composition used and whether it is used concomitantly with other therapeutic agents. Other factors affecting the dose administered to the subject include, e.g., the type or extent of disorder or condition. Generally, a therapeutically effective amount may vary with the subject’s age, condition, and sex, as well as the extent of the disorder or condition in the subject and can be determined by one of skill in the art. Other factors can include, e.g., other medical disorders concurrently or previously affecting the subject, the age and general health of the subject, the genetic disposition of the subject, diet, time of administration, the route of administration, and the size (body weight, body surface, or organ size), the rate of excretion, drug combination, and any other additional therapeutics that are administered to the subject. It should also be understood that a specific dosage and treatment regimen for any particular subject also depends upon the judgment of the treating medical practitioner (e.g., doctor or nurse). A therapeutically effective amount is also one in which any toxic or detrimental effects of the composition are outweighed by the therapeutically beneficial effects. The dosage of the therapeutically effective amount may be adjusted by the individual physician or veterinarian in the event of any complication. In some instances, a therapeutically effective amount may vary from about 102to about 1012colony forming units (CFU). In some embodiments, the therapeutically effective amount may be, for example, about 1 x 102CFU / g, 5 x 102CFU / g, 1 x 103CFU / g, 5 x 103CFU / g, 1 x 104CFU / g, 5 x 104CFU / g, 1 x 105CFU / g,ATTORNEY DOCKET NO. 090464-1548125 (024WO1)5 x IO5CFU / g, 1 x 106CFU / g, 5 x 106CFU / g, 1 x 107CFU / g, 5 x 107CFU / g, 1 x IO8CFU / g, 5 x IO8CFU / g, 1 x 109CFU / g, 5 x 109CFU / g, 1 x IO10CFU / g, 5 x IO10CFU / g, 1 x IO11CFU / g, 5 x IO11CFU / g, 1 x 1012CFU / g., or any range or amount within that range. In some embodiments, the amount is administered for 1, 2, 3, 4, 5, or 6, days, or 1, 2, 3, or 4 weeks, or 1, 2, 3, 4, 5, or 6 months or more. In some embodiments, the administration of the therapeutic composition is discontinued after establishing, in the subject, a stable engraftment of the bacterial strains of the therapeutic composition. In some embodiments, the administration of the therapeutic composition is discontinued when the level of the biomarker(s) have returned to a normal level, as compared to a control for about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 months.VI. Kits

[0101] Also disclosed are kits for use in any of the methods disclosed herein. The kits of this disclosure may comprise a carrier container being compartmentalized to receive in close confinement one or more containers such as packets, vials, tubes, and the like, each of the containers comprising one of the separate elements to be used in the method. In some embodiments, the kits include instructions for performing the methods.

[0102] In some embodiments of the detection and diagnostic methods, one or more of the containers may comprise an agent that is, or can be, detectably labeled. The kit may also have containers containing buffer(s) and / or a container comprising other agents for performing the methods. For example, a kit for detecting constituents of a microbiome is provided herein.

[0103] Therapeutic bacterial compositions, as described in this disclosure for use in treating a metabolic disorder or cognitive or neurodevelopmental disorder or condition, may be delivered in a pharmaceutical package or kit to a subject’s family or to doctors, healthcare providers, or treatment facilities. Typically, the packaging comprises paper (cardboard) or plastic. In some embodiments, the kit or pharmaceutical package further comprises instructions for use (e.g., for administering according to a method as described herein).

[0104] In some embodiments, a pharmaceutical package or kit comprises unit dose forms of the bacterial composition. The dose and form can be any doses or forms as described herein. In one embodiment, the kit or pharmaceutical package includes doses suitable for multiple days of administration, such as one week, one month, or three months.

[0105] Disclosed are materials, compositions, and components that can be used for, can be used in conjunction with, can be used in preparation for, or are products of the disclosed methods and compositions. These and other materials are disclosed herein, and it is understood that when combinations, subsets, interactions, groups, etc. of these materials are disclosed thatATTORNEY DOCKET NO. 090464-1548125 (024WO1)while specific reference of each various individual and collective combinations and permutations of these compounds may not be explicitly disclosed, each is specifically contemplated and described herein. For example, if a method is disclosed and discussed and a number of modifications that can be made to a number of molecules including in the method are discussed, each and every combination and permutation of the method, and the modifications that are possible are specifically contemplated unless specifically indicated to the contrary. Likewise, any subset or combination of these is also specifically contemplated and disclosed. This concept applies to all aspects of this disclosure including, but not limited to, steps in methods using the disclosed compositions. Thus, if there are a variety of additional steps that can be performed, it is understood that each of these additional steps can be performed with any specific method steps or combination of method steps of the disclosed methods, and that each such combination or subset of combinations is specifically contemplated and should be considered disclosed.

[0106] Publications cited herein and the material for which they are cited are hereby specifically incorporated by reference in their entireties.EXAMPLES

[0107] The following examples are offered to illustrate, but not to limit, the claimed invention.EXAMPLE 1. Generation of infant humanized mouse lines.

[0108] The COMBINE child cohort study followed 456 Irish mother-infant pairs from the third trimester of pregnancy to three years of age. A large amount of clinical and environmental metadata was collected on the mothers and children, including neurodevelopmental screening and collection of infant fecal samples longitudinally in the first 12 months. At two years of age, infants were administered the Bayley’s Scale of Infant Development III test, which measures cognitive skills, language, and motor skills. Scores of the BSID test followed a normal distribution with an average of 104 and a standard deviation of 14. Infants that scored one standard deviation above and below the mean score were selected for study (Fig. 1). Additionally, three infants that scored in the normal range were also included. Each infant had multiple fecal samples collected between one month of age up to twelve months.

[0109] To colonize germ-free mice with infant fecal microbiomes, fecal slurries were prepared for each of the 117 fecal samples collected from the 35 infants (Figure 2). The fecalATTORNEY DOCKET NO. 090464-1548125 (024WO1)samples from each infant and the time points of collection are displayed in Table 1. Highlighted cells indicate the stool samples from each of the 35 infants that were included in this study. Infants (rows) are sorted by the Bayley Scales of Infant Development (BSID) composite cognitive score.Table 1Infant age (Days)

[0110] Slurries were administered to germ-free mating pairs in the germ-free facility and kept in the facility for approximately 3 weeks before being transferred to a mouse roomATTORNEY DOCKET NO. 090464-1548125 (024WO1)dedicated solely for this study. Multiple breeding pairs were generated from the initial founder pair and a dedicated mouse colony for each sample was established (with the exception of three microbiome samples from which colonization with their fecal samples did not yield any surviving pups). Subsequent behavioral, brain, metagenomic, and metabolomic analysis was performed on offspring of each of the established mouse lines.EXAMPLE 2. Low-scoring infant microbiomes collected at or before six months of age yield mice that are defective in multiple behaviors.[oni] To assess the impact of infant microbiomes on mouse behavior, four behavior tests were performed as described below. Overall, the findings were consistent and robust across the different assessments. The key finding from the entire data set is that germfree mice transplanted with microbial community samples from low-scoring infants between 1-4 months of age show distinct abnormal behavior in all tests compared to humanized mice with microbiome transfers from high-scoring and normal scoring infants (See FIGS. 3-16).

[0112] To generate enough animals for all analyses, additional breeding pairs were generated from the founder animals. A second key finding is these abnormal behaviors are transmitted vertically. All experiments were conducted on animals from generations F1-F5. To simplify the data description, low-scoring infants are referred to as L or LS, and high-scoring infants are referred to as H or HS. Fecal samples collected prior to six months of age are categorized as E for early, while samples from 6 months of life are in a transitional state and grouped separately, and samples from 9 or 12 months of age are categorized as L for late. For example, all of the major phenotypes described below occur in the LE infant samples (low-scoring, early time points) and are not present in the low-scoring late (LL), high-scoring early (HE), high-scoring late (HL), normal -scoring early (NE), or normal -scoring late (NL) infant samples.Rearing pups to weaning.

[0113] Upon establishment of the initial breeding pair for each infant microbiome, a pattern of defective rearing of pups to maturity emerged. Mice colonized with LE microbiomes had normal litter sizes but significantly more mortality before weaning than the LL, HE, HL, NE or NL groups. Wild-type C57B1 / 6 mice have approximately 92% survival of their pups to weaning, while germ-free C57B1 / 6 animals have reduced survival (approximately 78%). Providing germ-free animals with a mouse fecal transplant partially rescues this phenotype (approximately 84%). Mice colonized with infant microbiomes from the LL, HE, HL, NE, orATTORNEY DOCKET NO. 090464-1548125 (024WO1)NL groups show no defects in pup survival compared to control animals. However, mice colonized with samples from the LE group (n = 20) all showed that less than 50% of infant mice survived to weaning, despite having normal litter sizes (FIG. 3). Data for 120 mouse lines (117 humanized microbiota mouse lines, 2 mouse FMT control lines, and 1 conventional control mouse line) are shown in Figure 3. In general, LE mice also did not show normal nesting behavior and maternal instincts compared to the other groups. In addition, there is an indication that LE mice display more aggressive behavior than other animals. These data show that LE microbiomes have a dramatic effect on nurturing pups to weaning.Open Field Test.

[0114] The open field test was the first behavioral test done on the mice to determine if there is a deficit in locomotion in the groups. As expected, no overall movement deficit was observed (data not shown). However, the assay can also be used to measure exploratory behavior and anxiety-like behaviors. The test consists of a 40 cm x 40 cm box (FIG. 4A) where the animals can explore freely for ten minutes. Decreased time in the center of the box (or increased time in the comers) are indicators of increased anxiety. Figure 4B shows a representative heat map and movement trace of a low scoring early mouse test (top panels) as compared to a low scoring late mouse test (bottom panels). LE mice were observed to spend significantly less time in the center compared to controls and the LL, HE, HL, NE, and NL groups. Figure 5 shows all data points in a representative example of each group. Data for 71 mouse lines tested is shown in Figure 6. The mice in the LS - 6 month group were also slightly lower than the HS - 6 month group.Light / dark box.

[0115] The light / dark test is commonly used as a test of anxious behavior in mice. Mice that display increased anxiety spend less time in the light side of the box versus the enclosed and dark side of the box in the ten-minute test (FIG. 7A). Figure 7B shows a representative heat map and movement trace of a mouse from a low scoring early line (left panels) as compared to a mouse from a low scoring late mouse line (right panels). LE mice spent significantly less time in the light compared to controls while the LL, HE, HL, NE, and NL groups all spent the same amount or increased time in the light compared to controls. Figure 8 shows all data points in a representative example of each group. Data for 71 mouse lines tested is shown in Figure 9. These data show that mice colonized with LE microbiomes display an increased anxiety phenotype and reduced exploration compared to the other groups and control animals.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)Novel object recognition.

[0116] The novel object recognition test is a behavioral test that investigates aspects of learning and memory. Mice prefer novel objects and therefore will spend more time with a new object provided to them versus a familiar object. The recognition index ranges from a value of 0 to 100. A value of more than 50 indicates the preference for the novel object, while a value below 50 indicates a preference for the familiar object.

[0117] LE mice spent less time with a novel object than control mice and mice from the other 7 infant microbiome groups, which all preferred the novel object as expected. A representative of each group is presented in Figure 10. Figure 11 shows the results of 71 lines that were tested for novel object recognition. The data show that LE groups spent less than 50% of time interacting with the novel object. A score of at or near 50% indicates no preference between objects which demonstrates a memory defect. Scores significantly lower than 50% could also be interpreted as an anxiety phenotype where the animal is actively avoiding the novel object because of increased anxiety or other behavioral alteration. From this data, it can be concluded that all tested LE mouse lines have an abnormal response to the presence of a novel object, although this test alone is not sufficient to determine the cause of deviation from the expected response shown by all other groups of mice.Fear conditioning.

[0118] The fear conditioning test was used to test associative learning, including contextual and cued learning. LE mice were defective in both aspects of learning (FIGS. 12-14). Fear conditioning has two phases, training and testing. In the training phase, the animal is placed in a conditioning chamber and allowed to explore briefly, followed by a tone playing (conditioned stimulus) and a mild foot shock (unconditioned stimulus). Twenty-four hours later, the animals are put back into the same environment to test recent memories. Amount of freezing behavior, (immobility except for breathing) is measured to test the animal’s ability to associate the environment with aversive experience. Animals that do not remember something bad happened in that space will freeze less than an animal which remembers. A representative data set from each group is shown in Figure 12. The mean value of 71 lines that were tested is summarized in Figure 13. Taken together, this data shows that LE lines have a defect in remembering adverse environments after 24 hours.

[0119] Cued fear conditioning measures the ability to associate an auditory cue (a tone) with an adverse event (foot shock the prior day) in a new environment. Two hours after the contextual fear conditioning test (26 hours from the foot shock), animals are placed into aATTORNEY DOCKET NO. 090464-1548125 (024WO1)chamber that is completely different from the environment in which the foot shock happened. The time spent freezing is measured before and after the same tone that proceeded the foot shock is played. The expectation is that in a new environment mice will not freeze (pre-cued). As expected, there was no difference between any of the groups in this phase of the testing. However, when the tone is played, animals that associate the sound with an adverse event will freeze. Figure 14 shows representative data from control, low scoring, and high scoring mouse lines. Low scoring early mice froze less than all other groups following the tone, indicating a deficit in cued associative memory.Sociability and Social Novelty.

[0120] Deficits in social interaction are a common problem for individuals who have low scores on the Bayley’s scale of infant development. To determine if the mouse lines from low-scoring animals were impaired in social interactions, a two-stage test was performed to gauge sociability and social novelty (FIGS. 15-16). In the sociability test, animals are placed into an empty three-chamber box and allowed to become accustomed to the environment for 10 minutes. Then a mouse is placed in a cup in one of the chambers (FIG. 15, right panel). Because mice are social animals, it is expected that the mouse will spend more time interacting with the mouse than the empty cup in the opposite chamber. Interaction with either cup is scored. Figure 15 shows the results of male mice from LE, LL (2 months), HE, and HL (9 month) groups. A representative trace of animal movement comparing the LE to LL lines is also shown. LS3-60 shows no preference for the cup with the mouse as compared to the empty cup, while all other lines prefer the mouse.

[0121] During the social novelty phase of the test, the previously encountered animal (mouse 1) remains in the original position, and a new unfamiliar mouse (mouse 2) is placed in the opposite chamber and interactions are measured for 10 more minutes. It is expected that the mouse will spend more time interacting with the new mouse (mouse 2). Figure 16 shows the results of male mice from LE, LL (9 months), HE, and HL (9 month) groups. A representative trace of animal movement comparing the LE to LL lines is also shown. LS3-60 shows no preference for the new mouse (mouse 2), while all other lines prefer the new mouse. These results indicate that LE mice display a deficit in social behavior similar to that seen in animal models of autism spectrum disorder and other disorders that affect sociability.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)EXAMPLE 3. No taxonomic signature stratifies low versus high scoring infants.

[0122] Having established a consistent pattern of behavioral deficits in LE microbiome mice, the microbiome of each group was analyzed to determine if the community structure of the microbiome associated with these phenotypes. Two analyses were conducted - 1) metagenomic analysis of low scoring and high scoring infant microbiomes directly and 2) metagenomic analysis of the microbiomes that were established in the mice. Whole genome shotgun metagenomics was performed using Illumina short-read sequencing (average of 30.45 million reads per sample). The taxonomic composition of microbial communities was identified with a standard bioinformatic pipeline, by pre-processing the sequencing data with KneadData then analyzing the genomic sequences with MetaPhlAn.Infant microbiomes from low -scoring and high-scoring infants.

[0123] For this analysis, 108 infant microbiomes from fecal samples were analyzed and found to be consistent with what has been observed in previous infant microbiome studies: diversity increases over time, infant microbiomes are less diverse than adult microbiomes, and infant microbiomes were taxonomically similar (FIGS. 17 A-B). Analysis of microbial species across the cohort did not identify any strong correlations between individual microbes and BSID scores that would indicate which microbes are driving these phenotypes. Modest trends were detected for enrichment of Klebsiella oxytoca during early infancy (< 6 months) and Paracteroides distasonis during late infancy (>6 months) in low-scoring infants. Bacteria commonly associated with infant microbiomes, such as Bifidobacteria, were distributed across the cohort and did not trend towards either group. It was also found that no species were consistently identified across the entire cohort, with 89% of species found in <20% of infant microbiomes.Infant microbiomes in humanized mice.

[0124] Diversity analyses suggested that microbial diversity within each mouse sample was lower in LE than HE mice (FIG. 17C). However, as found with the infant microbiomes, there was no statistically significant taxonomic signature associated with the microbes that colonized mice and behavioral phenotypes. Only modest statistical trends were identified that certain species are more prevalent in HE mice (FIG. 18). Species like Bacteroides thetaiotaomicron and Parabacteroides distasonis were enriched in HE mice.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)EXAMPLE 4. Metabolomics of humanized infant mouse lines identifies candidate biomarkers.

[0125] To identify potential functional differences between LE, LL, HE, and HL mice, a large-scale metabolomics screen was performed, followed up by selected targeted metabolomics.Metabolon large-scale targeted metabolomics.

[0126] Metabolon is a company that has a metabolomics platform that provides relative levels of -4000 individual metabolites in various sample matrices. Fecal samples from 32 mouse lines (16 high scoring lines vs 16 low scoring lines, 3 mice per line) were analyzed and metabolites that differentiated the high scoring vs low scoring groups were identified. Two types of analyses were performed: linear models that identify individual metabolites that are differential between LE and HE mice, and pathway enrichment analysis that identifies metabolic classes that trend in either group.

[0127] Using linear models, 51 metabolites were identified that discriminated between LE and HE mice (P<0.05, linear mixed effects models). Out of these 51 metabolites, the top 18 were statistically significant after multiple comparison correction (FIG. 19, P<0.05, linear mixed effects models with false discovery rate correction). These broader set of 51 discriminatory metabolites were highly correlated and clustered into 7 groups based on their relative abundances in mouse feces (FIG. 20). Within clusters, metabolites were either all enriched (1, 2, 5, 6), all depleted (3, 4), or had mixed trends (7) in high-scoring mice (FIG. 20).

[0128] Pathway enrichment analysis was performed to identify metabolic classes or groups that collectively differ in abundance between LE and HE (FIGS. 21A-21B). Dipeptides and phosphatidylcholines were found to be depleted, while 9 different metabolic groups are enriched in LE mice. Of the metabolites discriminatory between the HE and LE mouse lines, many have clear links to metabolism and brain function. Amino acids and dipeptides were reduced in low functioning fecal samples (FIGS. 21A-21B, FIGS. 22A-22C). Tryptophan, an essential amino acid, is the precursor for several immune modulators and neuroactive compounds (such as kynurenine and serotonin). Tryptophan metabolites were more abundant in high scoring mouse lines feces with kynurenine being one of the top differential metabolites. This finding was also supported by increased amounts of tryptophan synthesis genes in the fecal metagenomes of HE animals (FIGS. 23A-23B).ATTORNEY DOCKET NO. 090464-1548125 (024WO1)Metabolomics-based models for predicting BSID score of mouse donor.

[0129] To demonstrate that fecal metabolites can be potentially used as biomarkers for mouse behavioral phenotypes, predictive models were trained based on the top 18 metabolites that separated HE from LE infants (FIG. 24A) and achieved a cross-validated accuracy of 89%. However, this model benefits from the prior knowledge of which metabolites discriminate between mouse cohorts. Next, a predictive model was trained on all metabolites detected in the untargeted assays. This model reached a training accuracy of 78% using only 6 metabolites: phytosphingosine, arachidonic acid, docosahexaenoate, arachidonate, glutamine, pyrraline, and DGDG 16:0 / 18:2 (FIG. 25). A more conservative estimate of accuracy was computed as 68% using cross-validation. These models were trained on relative abundance data from the Metabolon untargeted assay. Predictive models trained on absolute abundances using assays that target these metabolites of interests may perform better with higher accuracy.Correlations between metabolites and microbes associated with behavioral phenotypes.

[0130] For the top discriminatory metabolites in the analysis, correlations were computed between their relative abundances and the abundances of microbial species, genes, proteins, and pathways. For kynurenine and N-carbamoylputrescine, which are both depleted in LE mice, several correlations with microbial species and functions were identified (FIG. 26). Species correlated with these metabolites were also enriched in HE mice in contrast to LE mice, including Bacteroides lhelaiolaomicron. Bacteroides caccae, Parabacteroides dislasonis. Bifidobacterium longum. and Eggerthella lenta.EXAMPLE 5. Phenotypes associated with low-functioning humanized mouse lines can be rescued by a second FMT from a high-functioning infant.

[0131] Based on the robust and consistent impact of LE fecal samples to drive multiple deficits in mouse behavior, learning and memory, it was hypothesized that a second fecal microbiota transplant (FMT) from a high scoring infant would be able to rescue these behavioral abnormalities. To test this theory, three LE mouse lines (LSI, LS4, LS6) were selected that had unique microbiomes, and transplants were performed with three different high-scoring infants (HS2, HS14, HS19). Fecal slurry was transplanted from both an early (2-month, 60) and late (9-month, 275) fecal collection for each patient. As a control, each LE mouse line received its own infant LE fecal slurry that was used to create the line (noted as LS-self). Each FMT was a single dose of fecal slurry provided to pups at ~21 days of age (at weaning), and behaviors were monitored in their offspring as described above. Transplant ofATTORNEY DOCKET NO. 090464-1548125 (024WO1)fecal slurry from HS infants greatly decreased mortality in these mouse lines compared to the parent and control lines (FIG. 27). Each HE / HL FMT rescued the three behaviors that were tested— pup rearing, light / dark box, and fear conditioning (FIGS. 27, 28A-28B). The self LE FMT control did not show any improvements in the behavioral tests conducted and were similar or lower than the original LE line, demonstrating the simple act of FMT was not sufficient to rescue phenotypes. An example of the three different behaviors that were rescued is shown in Figures 28A-28B.EXAMPLE 6. Immune markers differentiated high versus low scoring infants.

[0132] Thirty-two serum immune markers were profiled in the same group of animals highlighted above in the FMT experiments in the previous Examples. The two most striking differences between LE animals versus LE animals rescued by HE or HL FMTs were in the chemokine eotaxin (CCL11) and the anti-inflammatory cytokine IL-10 (FIGS. 29-30). In LE animals and LE animals given the same FMT again (LS-self), eotaxin levels were about 4 times higher compared to LE animals that received a HE or HL FMT. In contrast, levels of IL-10 were below the limit of detection in LE animals and present in all HE or HL FMT animals (FIG. 30). IL-10 levels were significantly greater in LS6 mouse lines compared to LSI and LS4 lines.

[0133] Eotaxin functions as an eosinophil chemokine and high levels have been linked to neurodegeneration and abnormal brain development, therefore high levels in the LE animals (FIG. 29) may be playing a role in behavioral deficits observed in these lines. Eotaxin has also been associated with long COVID impacts on the brain, potentially through impacts on microglia. See, e.g., Fernandez-Castaneda etal., 2022, Cell 185(14):P2452-68.EXAMPLE 7. Targeted metabolomics identified amino acids and their derivatives as biomarkers of rescue.

[0134] To understand how these FMTs impacted key fecal and serum metabolites, targeted metabolomics of key metabolites that differentiated HE vs LE mouse lines in our untargeted metabolomics data were performed. These key metabolites included amino acids, polyamines, tryptophan and tryptophan derived metabolites (such as kynurenine), and lipids. Amino acid concentrations in both feces and serum were found to be reduced in LE mouse lines (as observed above), and FMT with HE or HL fecal slurries increased amino acid levels by 200-500%. As examples, the amino acids that are key neurotransmitter precursors, tryptophan,ATTORNEY DOCKET NO. 090464-1548125 (024WO1)tyrosine, and glutamate, were all significantly increased in mouse lines that received HE or HL FMTs (three right samples in FIGS. 31A-31C). In contrast, these amino acids did not change in concentration when animals received the FMT from LE fecal slurries (self). Further, summarizing the concentration of all 20 amino acids resulted in similar trends (FIG. 3 ID), suggesting an overall metabolic defect may result in loss of metabolites derived from amino acids. Similarly, metabolites derived from amino acids that are known to be neuroactive (kynurenine and GABA) were found to be similarly increased in the plasma of animals that had their behavior phenotypes rescued by HE or HL FMTs (FIGS. 32A-32B). These results support that altered amino acid metabolism in low-scoring infant microbiomes may be responsible for impaired brain function.EXAMPLE 8. A three-strain bacterial consortium isolated from high-scoring infants can rescue phenotypes associated with a low-scoring mouse line.

[0135] To address if a defined consortium of bacteria could resolve LE phenotypes as well as full FMTs described above, 160 strains (from 59 bacterial species) were isolated from fecal slurries of 7 high scoring infants to build a biobank of candidate therapeutic strains. A list of isolated bacterial species is shown in Table 2.Table 2ATTORNEY DOCKET NO. 090464-1548125 (024WO1)

[0136] Using metagenomic data from the FMT rescue experiments, a consortium of three strains was selected and designated CS1 (Bacteroides thetaiotaomicron, Bacteroides cellulosdyticus, and Parabacteroides distasonis) for testing in a LE mouse line for the ability to reverse behavioral phenotypes. An additional three strain consortium made up of three Bifidobacteria strains (designated CS2) was also tested. While Bifidobacterial species are commonly used as probiotics and is a reason that we tested this consortium, the data here did not suggest that Bifidobacteria were likely the cause of rescuing behavior phenotypes. A third consortium was designed to test the hypothesis that altered amino acid metabolism may be responsible for behavioral phenotypes. The third consortium comprised Clostridioides difficile and Enterococcus faecalis (noted here as CS3). The metabolic modeling predicted that these species significantly consume amino acids from their environment and also cross-feed amino acids with each other. Therefore, it was expected that CS3 would fail to rescue LS 11 behavioral phenotypes and may even exacerbate them. Indeed, this was the case. Figure 33 shows the mortality in the offspring of animals given CS1, CS2, and CS3 (LS11-CS1, LS11-CS2, and LS11-CS3, respectively). Compared to the parental LSI 1-60 control, CS1 significantly reduced mortality, while CS2 had little to no impact on pup survival, and CS3 increased mortality to 89% of all pups bom.

[0137] The Fl and F2 offspring of LSI 1-CS1 were tested in the light dark box task (FIG.34). CS1 restored the exploration time in the light side of the box to similar levels as controls, while CS2 was unable to do so. CS1 also was able to restore abnormal behaviors associated with anxiety and learning / memory in contextual fear conditioning (FIG. 35).ATTORNEY DOCKET NO. 090464-1548125 (024WO1)

[0138] To assess the impact of CS1 on biomarkers associated with high functioning animals, metabolites were measured as described in the previous examples in the serum and in feces. Similar to successful whole FMT rescues, CS1 resulted in a 2-5 fold increase in these metabolites compared to the concentrations found in the LE parental line (Table 3), supporting the data found in FMT rescue experiments. In Table 3, ND indicates that the biomarker can be measured but has not yet been measured, and XX indicates that the biomarker cannot be measured with targeted metabolomics of feces because the biomarkers were measured in Luminex based assays.Table 3

[0139] The restorative effect observed for CS1 was further evaluated in additional LS-derived microbiome backgrounds. For this experiment, CS1 was administered to humanized mice colonized with microbiota derived from three additional independent LS infant donors. The fold changes in fecal Kynurenine, tryptophan, and glutamate concentration were determined before and after CS 1 treatment or FMT from the same or a control LS infant (FIGS.36A-36C). Oral gavage was performed twice weekly. Each line underwent rapid screening of biomarkers at 6 weeks of age (3 weeks post- weaning). CS1 treatment drove statistically significant (p<0.01) increases in fecal kynurenine (>2.5-fold), tryptophan (>3-fold), and glutamine (>2.75-fold) in each LS mouse line. Similar results were observed when screening for fecal glutamine (data not shown). These data demonstrate that the restorative effect of CS1 is reproducible across multiple independent LS microbiome backgrounds, is not restricted to a single donor-derived microbiome, and has broad applicability within LS-associated metabolic contexts.

[0140] The effect of CS1 also was evaluated to determine if CS1 could enhance levels in HS-derived microbiome backgrounds. CS1 was administered to humanized mice colonized with microbiota derived from four independent HS infant donors. The fold change in fecalATTORNEY DOCKET NO. 090464-1548125 (024WO1)Kynurenine levels was determined before and after CS1 treatment or after FMT from a control HS infant (FIG. 36A). No significant increase in fecal Kynurenine was observed in HS-derived microbiome backgrounds following CS1 administration. These findings support the selective correction of LS-associated metabolic dysfunction and the absence of enhancement in microbiomes derived from high-scoring infants. Therefore, CS1 provides therapeutic normalization rather than augmentation of the baseline metabolic state.

[0141] CS1 includes three bacterial strains (Bacteroides thetaiotaomicron, Bacteroides cellulosdyticus, and Parabacteroides distasonis) that were isolated from a single high-scoring donor. Additional experiments were performed with bacterial strains that were isolated from different infant donors as shown in Table 4. CS1 VI in Table 4 is the same as CS1 in the previous experiments. In CS1 V2 and V3, the strains of B. thetaiotaomicron and P. distasonis were replaced with strains of the same species derived from alternative infant donors, while B. cellulosdyticus remained unchanged.Table 4

[0142] To assess the impact of CS1 V2 and CS1 V3 on biomarkers associated with high functioning animals, the fold change of Kynurenine in feces was measured as described in the previous examples before and after treatment. Similar to successful whole FMT and CS1 VI rescues, both CS1 V2 and CS1 V3 restored fecal Kynurenine levels in the LS-derived backgrounds, resulting in about a 3-fold increase in Kynurenine after treatment with CS1 V2 or CS1 V3 compared to the concentrations found in the mice before treatment, in all four LS-derived backgrounds (FIGS. 37A-37B). These data demonstrate the functional robustness across strain substitutions. The rescue phenotype is not limited to specific strain identifiers, and there is species-level functionality within the consortium.

[0143] In addition, two of the three species in CS1 (Bacteroides thetaiotaomicron and Parabacteroides distasonis) were assessed individually for their ability to restore the levels ofATTORNEY DOCKET NO. 090464-1548125 (024WO1)biomarkers associated with high functioning animals. Neither B. thetaiotaomicron nor P. distasonis, when administered individually, produced a significant increase in fecal Kynurenine across any of the four LS-derived backgrounds (FIGS. 38A-38B). These findings indicate that individual strains are insufficient to reproduce the rescue phenotype, the full multistrain consortium is required for metabolic restoration, and the therapeutic effect is consortiumdependent.EXAMPLE 9. Development of a rapid screen method to determine restoration of low-scoring phenotypes.

[0144] Because many of the experiments described are time and effort consuming to perform; it would be advantageous to streamline the process in order to more rapidly assess the impact of candidate microbial strains on the biomarkers associated with high- and low-scoring phenotypes. Leveraging the data described above from whole FMT rescues, tests were performed to determine alterations in biomarkers associated with rescue that could be detected within weeks of microbial transfer. In fact, for example, fecal amino acids and GABA levels were found to be restored to normal levels three weeks post FMT transfer (Rapid Screen column - Table 3 above, see also FIG. 39. XX indicates that the marker cannot be measured). Fecal samples were collected from mice 3 weeks post whole FMT transfer and targeted metabolomics were performed. Two low-scoring backgrounds and two successful HS transfers were tested. In all combinations, the GABA levels increased over the self-control mice, indicating that the testing regimen may be significantly shortened to screen microbial candidates (FIG. 39). Taken together, the results 1) demonstrated a causative role for the microbiome in behavior and cognition in pre-clinical humanized mice, 2) established biomarkers that distinguish the phenotypes of humanized mice from LS and HS infants, 3) determined at least three microbial strains that can reverse the metabolic dysfunction associated with poor behavioral outcomes, and 4) determined these changes can be monitored as soon as three weeks post microbial transfer.EXAMPLE 10. Impact of infant microbiome on brain development.

[0145] To determine how the developing human gut microbiome affects brain development and health, the brains of mice from the humanized mouse lines described above were analyzed. Following behavioral testing, adult mice were perfused, and their brains were extracted, sectioned, and subjected to immunohistochemistry (IHC), imaging, and image analysis. TheATTORNEY DOCKET NO. 090464-1548125 (024WO1)analyses focused on brain regions important for higher level cognition, learning and memory, and mood regulation (e.g., cortex, hippocampus, hypothalamus).

[0146] Low scoring infant microbiomes cause widespread neuroinflammation in mouse brains. Neuroinflammation, an inflammatory response that occurs in the brain, is considered a significant risk factor for various neuropsychiatric disorders, including depression, anxiety, and schizophrenia. To assess neuroinflammation in the humanized mouse lines, mouse brains were analyzed for markers of activated astrocytes and microglia, two glial cell types that play essential roles in maintaining brain health and function. Astrocytes are one of the most abundant cell types in the brain. Under normal conditions, astrocytes perform diverse functions including regulating synapse formation, function, and plasticity, maintaining blood-brain barrier integrity, and providing metabolic and trophic support to neurons. In response to pathological conditions, astrocytes transform their morphology and function (i.e., become reactive), which shifts the balance between their neuro-supportive and neuro-toxic properties. Utilizing GFAP as a marker for reactive astrocytes, we detected robust widespread astrocyte activation in the cortex, hippocampus, and hypothalamus of mice from low scoring early (LE) lines, which was significantly reduced in the brains of mice from low scoring late (LL) lines (FIGS. 40A-40C). Notably, astrocyte activation was also reduced in the brains of mice generated from normative and high scoring infants at both early and late time points (NE, NL, HE, HL) (FIGS. 40A-40C). Thus, widespread astrocyte activation is present specifically in the brains ofLE mice, which also show behavioral abnormalities.

[0147] Microglia, which account for approximately 10% of brain cells, function as resident macrophage-like immune cells that provide immune surveillance and facilitate homeostatic maintenance by clearing misfolded proteins, dead cells, and cellular debris and pruning synapses during neural circuit refinement. Like astrocytes, microglia become activated in response to disease, injury, or infection, resulting in shape change, enhanced phagocytic activity, and the release of inflammatory molecules that recruit other immune cells and initiate an inflammatory cascade. Using the microglial marker Ibal, we detected robust microglia activation in the cortex, hippocampus, and hypothalamus of low scoring early (LE) mice relative to normative and high scoring early (NE, HE) mice (FIGS. 41A-41C), akin to our activated astrocyte results. However, unlike astrocyte activation, microglia activation was also elevated in low scoring late time point (LL) mice relative to normative and high scoring late (NL, HL) mice (FIGS. 41A-41C). Thus, widespread microglial activation is present in the brains of mice generated from the microbiomes of low scoring infants collected at both earlyATTORNEY DOCKET NO. 090464-1548125 (024WO1)and late time points in contrast to mice generated from normative and high scoring infants. Taken together, the results indicate that low scoring infant microbiomes cause widespread neuroinflammation in mouse brains. This result has important implications since while acute neuroinflammation is a rapid, protective response to injury or infection, chronic neuroinflammation often results in neuronal damage and dysfunction and is associated with neurological and neuropsychiatric disorders.EXAMPLE 11. Microbiomes from low scoring infants alter synapse development in mice.

[0148] Synapses are specialized sites of cell-cell contact that mediate information flow and storage within neural networks. The development and function of synapses can be influenced by environmental factors such as the gut microbiome (through modulation of the gut-brain axis), which can impact behavior, cognition, and mood. Astrocytes and microglia also help regulate synapse structure and function, and their hyperactivation during brain development can dysregulate synapse formation, function, and / or pruning, resulting in deficits in cognitive function and mood regulation seen in neurodevelopmental disorders. To assess the effects of the developing human gut microbiome on synapse development, we examined the brains of mice from the humanized mouse lines for markers for the following synapse types: (1) inhibitory synapses that use the neurotransmitter GABA to suppress neural activity, (2) excitatory synapses that use the neurotransmitter glutamate to promote neural activity, and (3) modulatory synapses that use neuromodulators (e.g., serotonin, dopamine) to modify neuronal excitation and plasticity.

[0149] Inhibitory GABAergic synapses limit the information flow between neurons by decreasing the likelihood of postsynaptic neuron depolarization and the generation of an action potential. To assess inhibitory synapse development, high-resolution (63x) confocal imaging and analysis of key inhibitory synaptic markers including the postsynaptic inhibitory marker Gephyrin was performed (FIGS. 42A-42C). In the hippocampal regions DG (dentate gyrus) and CAI (Cornu Ammonis 1) as well as the prefrontal cortex (PFC), low scoring early time point (LE) mice had increased Gephyrin staining relative to normative and / or high scoring early time point (NE, HE) mice. No significant differences were seen for Gephyrin staining between LL, NL, or HL mice. These results suggest that LE mice, which display behavioral defects, have an upregulation of GABAergic inhibitory synapses in their hippocampus and prefrontal cortex relative to NE and / or HE mice.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)

[0150] Excitatory glutamatergic synapses transmit information between cells by increasing the likelihood of postsynaptic neuron depolarization and the generation of an action potential. To evaluate excitatory synapse development, a similar high-resolution analysis was performed on humanized mouse brains, imaging and analyzing key excitatory synaptic markers including the postsynaptic marker PSD95 in different brain regions (FIGS. 43A-43C). In the hippocampus (DG and CAI), for the early time point mice, both LE and HE mice had reduced PSD95 staining relative to NE mice, whereas for the late time point mice, only the HL mice had reduced PSD95 staining (FIGS. 43A-43B). In contrast, no significant difference in PSD95 staining was observed in the PFC for any mouse group (FIG. 43C). Thus, excitatory synapses appear to be reduced in the hippocampus of mice generated using the microbiomes of high scoring infants. Together, the results identified alterations in excitatory and inhibitory synaptic markers in the brains of mice from low versus normative and / or high humanized mouse lines. This finding is significant given that brain function requires a stringent balance of excitatory (E) and inhibitory (I) synapse formation during neural circuit assembly, and alterations in this E / I balance are frequently seen in neurodevelopmental disorders.

[0151] In addition to glutamate and GABA, neuromodulators such as serotonin (5-hydroxytryptamine, 5-HT) play important roles in the brain in regulating processes like learning and memory and mood regulation. Indeed, low levels of serotonin are frequently associated with depression and anxiety disorders, while many anti-depressant medications work by increasing serotonin levels in the brain. To assess serotonin levels in the brains of humanized mice, brain sections from LE and HE mice were immunostained with antibodies against 5-HT, imaged at 40x with a confocal microscope, and analyzed for 5-HT staining density (FIG. 44A). Notably, serotonin was found to be reduced in the cortex and hippocampus (CAI and DG) of humanized mice generated from low scoring early infant microbiomes (LE) compared to those generated from high scoring early infant microbiomes (HE) (FIG. 44A). This result could explain some of the behavioral deficits seen in the LE mouse line. Additional brain immunohistochemistry and imaging was consistent with aberrant synaptic architecture and widespread neuroinflammation in LE mice (FIGS. 44B-44E). Inhibitory synaptic development assessed in the dentate gyrus (DG) and CAI hippocampal regions using the postsynaptic marker Gephyrin showed increased Gephyrin staining in LE mice relative to HE mice (FIG. 44B). Excitatory synaptic development evaluated using the postsynaptic marker PSD95 in hippocampal regions DG and CAI showed no difference between LE and HE mice (FIG. 44C). Astrocytic activation assessed by GFAP staining intensity in the cortex,ATTORNEY DOCKET NO. 090464-1548125 (024WO1)hippocampus (Hippo) and hypothalamus (Hypo). GFAP levels were increased across all brain regions in LE compared to HE mice (FIG. 44E). Microglial activation based on Ibal staining intensity in the cortex, hippocampus, and hypothalamus. Ibal intensity was markedly elevated in all examined brain regions in LE mice relative to HE mice (FIG. 44D).

Claims

ATTORNEY DOCKET NO. 090464-1548125 (024WO1)What is claimed is:

1. A composition comprising at least two or more bacteria that increase an amino acid or metabolite or combination thereof in a biological sample of a subject.

2. The composition of claim 1, wherein the amino acids or metabolites comprise tryptophan, tyrosine, glutamine, glutamate, kynurenine, gamma-aminobutyric acid (GABA), or a combination thereof.

3. The composition of claim 1 or 2, comprising a synergistic combination of two or more of Bacteroides thetaiotaomicron, Bacteroides cellulosdyticus, and Parabacteroides distasonis.

4. The composition of any one of claims 1-3, further comprising a pharmaceutically acceptable carrier.

5. The composition of any one of claims 1-4, wherein the composition is formulated for oral administration.

6. The composition of claim 4 or 5, wherein the pharmaceutically acceptable carrier is one or more selected from a group consisting of alginate, gum arabic, pectin, animal proteins, chitosan (CS), xanthan, k-carrageenan, cellulose, starch, glycogen, acrylic acid derivatives, cellulose acetate trimellitate (CAT), hydroxypropyl methylcellulose acetate succinate (HPMCAS), cellulose acetate phthalate (CAP), hydroxypropyl methyl-cellulose phthalate (HPMCP), whey protein, casein, gelatin, polyacrylamides, Poly (D, L-lactic-co-glycolic acid) (PLGA), polyvinyl alcohol (PVA), poly-l-lysine (PLL), polystyrene, dextran, chitosan, pectin, cyclodextrin, amylose, guar gum, chondroitin sulphate, inulin, locust bean gum, fructose, fructooligosaccharides, mineral metal salt, glutathione, carboxymethyl cellulose (CMC), carboxymethylpachymaran (CMP), and combinations thereof.

7. The composition of any one of claims 1-6, wherein the composition is formulated in a food product.

8. The composition any one of claims 1-7, wherein the composition is an infant formula, a liquid drop, an acidified milk, a milk powder, or a milk concentrate.

9. The composition of any one of claims 1-8, wherein the bacteria are provided as a live culture.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)10. The composition of any one of claims 1-8, wherein the bacteria are lyophilized.

11. A method for detecting a microbiome component or biomarker associated with a metabolic disorder in a subject, comprising:a. obtaining a biological sample from the subject;b. measuring a level of a microbiome component or biomarker in the biological sample, wherein the microbiome component comprises one or more bacterial strains; andc. determining if the level of the microbiome component or biomarker is increased or decreased as compared to a control.

12. The method of claim 11, wherein the one or more bacterial strains decrease an amino acid or metabolite or combination thereof in the biological sample.

13. The method of claim 11 or 12, wherein the metabolic disorder negatively affects cognition or neurodevelopment in the subject, increases inflammation and neuroinflammation in the subject, or both.

14. The method of any one of claims 11-13, wherein the biological sample is a fecal sample.

15. The method of any one of claims 11-14, wherein the subject is an infant of 0 to 12 months in age.

16. The method of any one of claims 11-15, wherein step b) comprises measuring a level of one or more biomarkers, wherein the one or more biomarkers are selected from a group consisting of an amino acid, kynurenine, GABA, eotaxin, IL-10, and cortisol.

17. The method of any one of claims 11-15, wherein step b) comprises measuring a level of one or more biomarkers, wherein the one or more biomarkers comprise an amino acid, a metabolite, or a cofactor of a metabolic pathway selected from a group consisting of an amino acid, carbohydrate, vitamin, tricarboxylic acid (TCA) cycle, lipid, nucleotide, peptide, or xenobiotic metabolic pathway.

18. The method of claim 17, wherein the one or more biomarkers are selected from a group consisting of alanine, S-l-apyrroline-5 -carboxylate, glutamine, glutamate, N-butyryl-leucine, N6-carboxyethyllysine, N6-acetyllysine, glutarylcamitine (C5-DC), 3 -sulfo-alanine, N-butyryl-phenylalanine, phenyllactate (PLA), N-carbamoylputrescine, spermine, indoxylATTORNEY DOCKET NO. 090464-1548125 (024WO1)glucuronide, kynurenine, N-alpha-acetylomithine, N6-carboxymethyllysine, glucuronate, ribose, oxalate (ethanedioate), flavin mononucleotide (FMN), 5-(2-hydroxyethyl)-4-methylthiazole, aconitate [cis or trans], N-stearoyl-sphingosine (dl8: 1 / 18:0)*, Undecenoylcarnitine (Cl 1:1), hexanoylglycine, 3-hydroxypalmitate, l-palmitoyl-2-linoleoyl-diglaactosylglycerol (16:0 / 18:2)*, docosahexaenoate (DHA; 22:6n3), arachidonate (20:4n6), l-palmitoyl-2-linoleoyl-GPC (16:0 / 18:2), phytosphingosine, N-stearoyl-phytosphingosine (tl 8:0 / 18:0)*, sphingosine, heptadecasphingosine (dl7:l), xanthine, hypoxanthine, adenine, N1 -methyladenosine, guanine, thymidine 5 '-monophosphate, uridine 5'-monophosphate (UMP), phenylacetylglutamine, phenylacetylglycine, glutaminylleucine, leucylalanine, lyslleucine, alanylleucine, p-cresol sulfate, hippurate, benzoate, 3,5-dihydroxyphenylpropionate, dicarboxylate fatty acid, and pyrraline.

19. The method of claim 17 or 18, wherein the one or more biomarkers comprise a dipeptide, phosphatidylcholine, or both; and wherein a decrease in the level of the biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject.

20. The method of any one of claims 17-19, wherein the one or more biomarkers comprise one or more of a dicarboxylate fatty acid, S-l-pyrroline-5-carboxylate, N-butyryl-phenylalanine, N-butyryl-leucine, N-carbamoylputrescine, uridine 5'-monophosphate (UMP), 3-hydroxypalmitate, flavin mononucleotide (FMN), hypoxanthine, N6-carboxy ethyllysine, phenyllactate (PLA), kynurenine, and l-palmitoyl-2-linoleol-GPC (16:0 / 18:2); and wherein a decrease in the level of the biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject.

21. The method of any one of claims 17-20, wherein the one or more biomarkers comprise a metabolite or cofactor of an acyl glycine, chemical, medium chain acyl carnitine, benzoate, lysophospholipid, ascorbate and aldarate, long chain polyunsaturated fatty acid, creatine, or TCA cycle metabolic pathway; and wherein an increase in the level of the biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject.

22. The method of any one of claims 17-21, wherein the one or more biomarkers comprise one or more of indoxyl glucuronide, phenylacetylglutamine, phytosphingosine, sphingosine, undecenoylcarnitine (Cl 1:1), and spermine; and wherein an increase in the level of theATTORNEY DOCKET NO. 090464-1548125 (024WO1)biomarker in the biological sample as compared to a control is associated with the metabolic disorder in the subject.

23. The method of any one of claims 17-22, wherein step b) comprises measuring a level of two, three, four, five, or six biomarkers.

24. The method of any one of claims 17-23, wherein step b) comprises measuring a level of phytosphingosine, arachidonate, docosahexaenoate, glutamine, pyrraline, and DGDG 16:0 / 18:2.

25. The method of claim 24, wherein an increase in the level of phytosphingosine, arachidonate, and docosahexaenoate as compared to a control, and a decrease in the level of glutamine, pyrraline, and DGDG 16:0 / 18:2 as compared to a control, are associated with the metabolic disorder in the subject.

26. The method of any one of claims 17-23, wherein the one or more biomarkers comprise tryptophan, tyrosine, glutamine, arginine, kynurenine, gamma-aminobutyric acid (GABA), eotaxin, IL- 10, and cortisol.

27. The method of claim 26, wherein an increase in the level of eotaxin and cortisol as compared to a control, and a decrease in the level of tryptophan, tyrosine, glutamine, arginine, kynurenine, GABA, and IL- 10 as compared to a control, are associated with the metabolic disorder in the subject.

28. The method of any one of claims 11-25, further comprising administering to the subject a therapeutically effective amount of a composition comprising at least two or more bacteria that increase an amino acid or metabolite in a biological sample of the subject.

29. A method for diagnosing a metabolic disorder in a subject, comprising:a. obtaining a biological sample from the subject;b. administering a portion of the subject’s biological sample to a germ-free mouse; c. measuring a level of a microbiome component or biomarker in a biological sample from the mouse or measuring a behavior of the mouse; andd. diagnosing the subj ect with the metabolic disorder if the level of the microbiome component or biomarker is increased or decreased as compared to a control, or if the behavior of the mouse is negatively affected as compared to a control.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)30. The method of claim 29, wherein the biological sample is a fecal sample.

31. The method of claim 29 or 30, wherein the subject is 0 to 12 months of age.

32. The method of any one of claims 29-31, wherein step c) comprises measuring the behavior of the mouse in a novel object recognition test, a fear conditioning test, or a sociability or social novelty test.

33. The method of any one of claims 29-31, wherein step c) comprises measuring a level of one or more biomarkers in the biological sample from the mouse, wherein the one or more biomarkers comprise an amino acid, a metabolite, or a cofactor of a metabolic pathway selected from a group consisting of an amino acid, carbohydrate, vitamin, tricarboxylic acid (TCA) cycle, lipid, nucleotide, peptide, orxenobiotic metabolic pathway.

34. The method of any one of claims 29-33, further comprising administering to the subject a therapeutically effective amount of a composition comprising at least two or more bacteria that increase an amino acids or metabolite in a biological sample of the subject.

35. A kit for use in the method of any one of claims 11-34, comprising an agent for measuring the level or presence of the microbiome component or biomarker in the biological sample and instructions.

36. A method of treating a subject having, suspected of having, or at risk for having a metabolic disorder or cognitive or neurodevelopmental condition or disorder, comprising: administering to the subject a therapeutically effective amount of the composition of any one of claims 1-10.

37. The method of claim 28 or 36, wherein administration of the composition improves neural development or function in the subject as compared to a control.

38. The method of any one of claims 36-37, wherein the improvement in neural development or function is measured by the Harris Infant Neuromotor Test (HINT), the Bayley Scales of Infant and Toddler Development (BSID), or the Cognitive Assessment of Young Children (CAYC).

39. The method of any one of claims 36-38, wherein the subject being treated is an infant of 0 to 12 months in age.ATTORNEY DOCKET NO. 090464-1548125 (024WO1)40. The method of any one of claims 37-39, wherein the improvement in neural development or function is measured when the subject is 0 to 36 months in age.

41. The method of any one of claims 36-40, wherein the subject has a metabolic disorder associated with lower levels of an amino acid or metabolite.

42. The method of any one of claims 36-41, wherein the composition is formulated for oral administration.

43. The method of any one of claims 36-42, wherein the composition is formulated in a food product.

44. The method of any one of claims 36-42, wherein the composition is an infant formula, a liquid drop, an acidified milk, a milk powder, or a milk concentrate.

45. The method of any one of claims 36-44, wherein the bacteria are provided as a live culture.

46. The method of any one of claims 36-44, wherein the bacteria are lyophilized.

47. The method of any one of claims 36-46, wherein administration of the composition increases the level of an amino acid or a metabolite of an amino acid in the subject.

48. The method of any one of claims 36-47, wherein administration of the composition increases the level of gamma-aminobutyric acid (GABA) in the subject.

49. The method of any one of claims 36-48, wherein administration of the composition increases the level of IL- 10 in the subject.

50. The method of any one of claims 36-49, wherein administration of the composition lowers the level of cortisol in the subject.

51. The method of any one of claims 36-50, wherein administration of the composition lowers the level of eotaxin in the subject.

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