Methods and compositions of palatable triacetin

Abstract

Orally administered compositions comprising triacetin are presented that increase the concentration of short chain fatty acids in the gut, namely acetic acid, wherein the compositions comprising triacetin are palatable at desirable concentrations. The triacetin formulations can also be orally administered to a dysbiotic subject to increase short chain fatty acid (SCFA) concentrations in the gut of the subject while substantially avoiding gas production in the subject. Advantageously, administration of contemplated compositions also increases gut barrier integrity and helps restore a balanced gut microbiome.

Description

METHODS AND COMPOSITIONS OF PALATABLE TRIACETIN

[0001] This application claims priority to U. S. Provisional Patent Application No. 63 / 716,056, filed November 4, 2024, and to U. S. Provisional Patent Application No. 63 / 781,595, filed April 1, 2025, and additionally to U. S. Provisional Patent Application No. 63 / 852,302, filed July 28, 2025. The entire disclosures of each of the foregoing applications are incorporated herein by reference in their entirety.Field of the Invention

[0002] The field of the invention is nutritional supplements, especially as it relates to oral compositions comprising triacetin (glycerol triacetate) and to methods of modulating gut short-chain fatty acids (SCFAs). Certain embodiments concern palatable consumer-acceptable formulations, and certain embodiments concern compositions and methods that increase colonic SCFA levels.Background of the Invention

[0003] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.

[0004] All publications and patent applications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.

[0005] Fatty acids with a carbon number between 2 and 6 are considered short chain fatty acids (SCFAs) and have the following names: acetic, propionic, butyric, valeric, and caproic acid. The main constitutive materials in animals are acetate, propionate, and butyrate. SCFAs are naturally produced by gut bacteria and are essential sources of nutrition to the cells in the colon. SCFAs also play several roles in preventing diseases, including inflammatory diseases, type 2 diabetes, obesity, heart disease, and other conditions.

[0006] To improve gut health and contribute to reducing the risk of such diseases, various nutritional supplements that release SCFAs in the gut upon administration have been developed. For example, tributyrin is a triglyceride that releases butyrate in the gut once it is digested. However, at various desirable quantities, and especially at higher concentrations, tributyrin and other related molecules are awful -tasting, and adding masking agents and / or flavorants fail to make tributyrin palatable. In some instances, flavoring and / or sweetening agents unexpectedly make the taste worse.

[0007] Additionally, most existing nutritional supplements have trouble reaching the colon intact to release SCFAs, and the low amounts that do reach the colon typically fail to deliver SCFAs in an amount sufficient to maintain healthy levels of SCFAs in the gut without excessive administration of the supplement. On the other hand, supplements such as sodium butyrate, lysine butyrate, and / or apple cider vinegar do not provide acetic acid or SCFAs to the colon, as most of them are absorbed in the stomach and small intestine.

[0008] To avoid at least some of the issues associated with administration of acetic acid, butyric acid, or tributyrin, insoluble fiber or probiotics can be administered to a subject, and certain bacteria in the microbiome of the subject will then ferment these insoluble fibers or metabolize the fiber, producing desirable quantities of SCFAs. For example, inulin (a linear beta 2-1 glucosidic fructan) has been shown to stimulate butyrate production in the gut of healthy subjects. Unfortunately, inulin and many other indigestible fibers are also known to cause significant gas production, which can lead to excessive bloating, discomfort or even pain. Such issues are further exacerbated in subjects suffering from inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), or other inflammatory or metabolic dysbiosis, and that can lead to discontinuation of oral fiber intake due to pain and bloating. While these conditions could greatly benefit from fiber-derived SCFAs in the gut, the same fiber will unfortunately also exacerbate many symptoms of these conditions.

[0009] For that reason, many subjects suffering from inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), or other inflammatory or metabolic dysbiosis will modify their diet to a low FODMAP diet, which is a type of elimination diet in which fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAP) are reduced or entirely avoided. In some cases, probiotics are also eliminated to avoid excessive bacterial load in the gut. Unfortunately, while reducing gas production and providing at least some symptomatic relief, a lack of fermentable fiber over extended periods will typically lead toreduced SCFA levels in the gut, which, in turn, delays or even prevents repair of the gut barrier, thereby leading to further gastrointestinal issues.

[0010] Thus, even though various compositions and methods of nutritional supplements for providing SCFAs to the colon are known in the art, all or almost all of them suffer from several drawbacks, particularly where they lack palatability, and where they struggle to provide effective quantities of SCFAs to the colon. Therefore, there remains a need for improved supplements which are palatable and effective in providing SCFAs to the lower gastrointestinal tract, colon, and small intestine.Summary of The Invention

[0011] The inventive subject matter is directed to various compositions and methods of increasing the concentration of short chain fatty acids in the gut of a subject by administering to the subject one or more compositions comprising triacetin.

[0012] For example, in one aspect of the inventive subject matter, the inventor contemplates a method of increasing the concentration of short-chain fatty acids (SCFAs) in the gut comprises administering to a subject a composition that includes triacetin at 100-1000 mg per 1-8 oz together with a flavorant, wherein the composition is palatable.

[0013] In some embodiments, the triacetin is introduced into the composition from a RTM composition.

[0014] In other embodiments, the triacetin is introduced into the composition from a RTD composition.

[0015] Additional embodiments are contemplated in which the administering is orally administering.

[0016] In some embodiments, the triacetin is introduced into the composition in combination with a pharmaceutically or nutritionally acceptable carrier.

[0017] In further embodiments, the triacetin is the sole active ingredient that increases the concentration of SCFAs of the subject.

[0018] In yet further embodiments, administering the composition to the subject (1) improves health of the subject’s gut and / or oral microbiome, (2) improves the integrity of the subject’sgastrointestinal barrier, and / or (3) causes approximately 70% or more of the triacetin in the composition to reach the subject’s lower GI tract.

[0019] It is also contemplated that, in some embodiments, the composition has a score of 6.0 or higher on a 9-point hedonic scale.

[0020] In additional embodiments, the subject has a low-fiber diet.

[0021] As will be readily appreciated, in certain embodiments, the flavorant may comprise citral, limonene, linalool, ethyl butyrate, isoamyl acetate, methyl anthranilate, hexyl acetate, ethyl 2-methylbutyrate, γ-decalactone, δ-decalactone, orange oil, lemon oil, lime oil, bergamot oil, vanillin, ethyl vanillin, maltol, ethyl maltol, acetoin, diacetyl, menthol, menthyl lactate, WS-3, WS-23, ginger oil, cinnamon oil, clove oil, nutmeg oil, cardamom extract, green tea extract, apple extract, strawberry extract, grape extract, pineapple extract, mango extract, peach extract, coconut extract, raspberry ketone, ethyl acetate, propyl butyrate, benzaldehyde, γ-nonalactone, δ-dodecalactone, ethyl maltol, linalyl acetate, citric acid, or a combination thereof.

[0022] The composition, in some embodiments, is formulated as a GLP-1 drink to provide nutritional support for a subject taking a GLP-1 agonist, a probiotic-containing drink, a prebiotic-containing drink, a fiber drink, a nutrition drink, a protein shake, or a sports drink.

[0023] Alternatively, or in addition, the composition may further comprise a pH modifier in other embodiments.

[0024] In some embodiments, the composition may further comprise tributyrin.

[0025] In further embodiments, the composition comprises between 100 mg and 1,000 mg triacetin per 1-8 oz of the composition.

[0026] It is additionally contemplated in some embodiments that the composition has a flavor intensity that increases proportionally with a quantity of flavoring.

[0027] In another aspect of the contemplated subject matter, a composition is contemplated for increasing the concentration of SCFAs in a gut of a subject, comprising triacetin at a concentration of 100-1000 mg triacetin per 1-8 oz of the composition; and a flavorant; wherein the composition is palatable.

[0028] As will be readily apparent, in some embodiments, the composition is part of a RTM composition.

[0029] In further embodiments, the composition is part of a RTD composition.

[0030] It is also contemplated that the triacetin is the sole active ingredient that increases the concentration of SCFAs in the gut of the subject in certain embodiments.

[0031] It should be appreciated that the composition may, in some embodiments, comprise 100 mg of triacetin per 1 oz.

[0032] The inventor additionally contemplates, in other embodiments, a method of increasing a concentration of short chain fatty acids (SCFAs) in a gut of a dysbiotic subject without substantially increasing gas production in the dysbiotic subject, comprising the step of orally administering to the subject a composition comprising triacetin in combination with a pharmaceutically or nutritionally acceptable carrier, wherein the composition is administered in an amount effective to increase the concentration of SCFAs in the gut by at least 10% and gas production does not increase by more than 10% in the subject as compared to the concentration of SCFAs and gas production in the gut without administration of the composition.

[0033] In some embodiments, the dysbiotic subject is diagnosed with or suspected to have inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), leaky gut syndrome, inflammatory dysbiosis, excessive bloating, or metabolic dysbiosis.

[0034] In further embodiments, the dysbiotic subject has dysbiosis due to old age, perimenopause, menopause, or post-menopause.

[0035] The inventor also contemplates in some embodiments that the subject has a low-fiber or low-FODMAP diet.

[0036] In further embodiments, butyrate and acetate account for a majority of the increased concentration of SCFAs in the gut.

[0037] Upon oral administration, in some embodiments, the concentration of SCFAs in the gut increases by at least 25% without substantial increase in gas production in the subject as compared to an SCFA concentration without oral administration.

[0038] However, it should be appreciated that in other embodiments, upon oral administration, the concentration of SCFAs in the gut increases by at least 50% without substantial increase in gas production in the subject as compared to an SCFA concentration without oral administration.

[0039] In some embodiments, the gas production does not increase by more than 10% as compared to gas production without oral administration when measured at 24 hours after oral administration.

[0040] In additional embodiments, the composition, upon oral administration, reduces pH in the gut by at least 0.2 pH units.

[0041] The increase in the concentration of SCFAs in certain embodiments may be observable at least 24 hours after oral administration.

[0042] It is also contemplated that the composition, upon oral administration, and in certain embodiments, enhances growth of SCFA-producing gut microbes in the subject as compared to baseline of the subject without oral administration.

[0043] The SCFA-producing gut microbes comprise, in some embodiments, Mediterraneibacter butyricigenes and / or Anaerobutyricum soehngenii.

[0044] In certain embodiments, the composition, upon oral administration, enhances gut barrier integrity in the subject as compared to baseline of the subject without oral administration.

[0045] And in different embodiments, the composition is formulated as a capsule, a powder, a ready -to-drink, a gummy, a gel, a chew, a buccal pouch, and / or a tablet.

[0046] The composition may further comprise tributyrin or other butyrate or acetate derivatives, in some embodiments.

[0047] In optional embodiments, the composition is formulated as or in a ready-to-mix formulation, or wherein the composition is formulated as or in a ready -to-drink formulation.

[0048] In other optional embodiments, the triacetin is the sole active ingredient that increases the concentration of SCFAs in the gut of the subject.

[0049] It is further contemplated that in some embodiments the composition further comprises a prebiotic fiber, optionally wherein the fiber is an insoluble fiber.

[0050] In some embodiments, the prebiotic fiber is a gum or is a mushroom fiber.

[0051] In certain embodiments, the composition further comprises a probiotic organism.

[0052] The inventor also contemplates in a different embodiment of the inventive subject matter a composition for increasing the concentration of short chain fatty acids (SCFAs) in a gut of a dysbiotic subject, comprising triacetin in combination with a pharmaceutically or nutritionally acceptable carrier and formulated for oral administration, wherein, upon oral administration, the concentration of SCFAs in the gut increases by at least 10% and gas production does not increase by more than 10% in the subject as compared to the concentration of SCFAs and gas production in the gut without administration of the composition.

[0053] In some embodiments, the composition comprises between 50 mg and 500 mg of triacetin.

[0054] In other embodiments, butyrate and acetate account for a majority of the increased concentration of SCFAs in the gut.

[0055] It should be appreciated that, in some embodiments, upon oral administration, the concentration of SCFAs in the gut increases by at least 25% without substantial increase in gas production in the subject as compared to an SCFA concentration without oral administration.

[0056] However, in further embodiments, upon oral administration, the concentration of SCFAs in the gut increases by at least 50% without substantial increase in gas production in the subject as compared to an SCFA concentration without oral administration.

[0057] The gas production may not increase by more than 10% as compared to gas production without oral administration when measured at 24 hours after oral administration, in certain embodiments.

[0058] In some embodiments, the composition, upon oral administration, reduces pH in the gut by at least 0.2 pH units.

[0059] In yet further embodiments, the increase in the concentration of SCFAs is observable at least 24 hours after oral administration.

[0060] According to the presently disclosed subject matter the composition, in some embodiments, upon oral administration, enhances growth of SCFA-producing gut microbes in the subject as compared to baseline of the subject without oral administration.

[0061] In further embodiments, the SCFA-producing gut microbes comprise Mediterraneibacter butyricigenes and Anaerobutyricum soehngenii.

[0062] It is also contemplated that the composition, upon oral administration, enhances gut barrier integrity in the subject as compared to baseline of the subject without oral administration.

[0063] The dysbiotic subject, in some contemplated embodiments, is diagnosed with or suspected to have inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), leaky gut syndrome, inflammatory dysbiosis, excessive bloating, or metabolic dysbiosis.

[0064] However, in further embodiments, the dysbiotic subject has dysbiosis due to old age, perimenopause, menopause, or post-menopause.

[0065] The composition is, in other embodiments, formulated as a capsule, a powder, a ready -to-drink, a gummy, a gel, a chew, a buccal pouch, and / or a tablet.

[0066] In addition, and in other embodiments, the composition further comprises tributyrin or other butyrate or acetate derivatives.

[0067] The composition may optionally be formulated as or in a ready -to-mix formulation, or wherein the composition is formulated as or in a ready-to-drink formulation in some embodiments.

[0068] In some embodiments, the triacetin is the sole active ingredient that increases the concentration of SCFAs in the gut of the subject.

[0069] In different embodiments, the composition further comprises a prebiotic fiber, optionally wherein the fiber is an insoluble fiber.

[0070] The prebiotic fiber, in some embodiments, is a gum or is a mushroom fiber.

[0071] Additionally, the composition may optionally further comprise a probiotic or a postbiotic (heat-treated probiotic) organism.

[0072] Viewed from another perspective, the inventive subject matter may be directed to a composition for increasing the concentration of short chain fatty acids (SCFAs) in a gut of a dysbiotic subject, comprising triacetin in combination with a pharmaceutically or nutritionally acceptable carrier and formulated for oral administration, wherein the triacetin is at a concentration of 100-1000 mg triacetin per 1-8 oz of the composition. This composition may further have a flavorant. It is contemplated that, upon oral administration of this composition, the concentration of SCFAs in the gut increases by at least 10% and gas production does not increase by more than 10% in the subject as compared to the concentration of SCFAs and gas production in the gut without administration of the composition, and the concentration of SCFAs in the gut exceed an amount of SCFAs esterified within the triacetin. It is further contemplated that this composition is palatable.

[0073] The triacetin may be at a concentration of 100 mg per 8 oz of the composition.

[0074] Further, upon oral administration, bloating in the subject may not increase by more than 10% as compared to bloating in the gut without administration of the composition.

[0075] This composition may be part of a RTM composition.

[0076] The composition may alternatively be part of a RTD composition.

[0077] The triacetin can be introduced into the composition from a soft chew or gummy composition for humans or animals, among other options.

[0078] In some cases, the composition further comprises tributyrin, lysine butyrate or any butyrate derivative.

[0079] In other instances, the composition may further comprise a mushroom blend, resistant starch or any fiber or prebiotic that boosts SCFAs, or a combination thereof.

[0080] Various objects, features, aspects, and advantages of the inventive subject matter will become more apparent from the following detailed description of preferred embodiments, along with the accompanying drawing figures in which like numerals represent like components.Brief Description of the Drawings

[0081] FIG. 1 depicts representative data showing that the fecal microbiota of IBS subjects displayed marked interpersonal differences and relevant differences compared to a healthy cohort. (A) Abundances (%) of the most abundant genera for each IBS subject (subjects 1-8) and healthy adult (subjects 9-16). (B) Linear discriminant analysis effect size (LEfSe) showing the taxa that explained differences between both cohorts (p < 0.05).

[0082] FIG. 2 depicts data showing TA and MB boosted SCFA levels in a product-specific manner with remarkably low gas production for TA. The impact on (A) pH, (B) gas production (mbar), (C) total SCFA (mM), (D) acetate (mM), (E) propionate (mM) and (F) butyrate (mM).

[0083] FIG. 3 depicts data showing that TA and MB each enhanced the growth of specific SCFA-producing gut microbes. The impact on (A) microbial diversity (community modulation score (CMS)), and (B) OTUs that were significantly affected (p adjusted < 0.05), expressed as log2 transformation of the ratio of abundance treatment / abundance NSC, averaged across all 8 IBS subjects. Hence, values > 0 reflect a stimulation by TA / MB, while values < 0 indicate an inhibition by TA / MB. Bars highlighted by a black outline indicate a statistically significant increase / decrease. (C) Individual correlations between butyrate (mM) and specific OTUs based on Spearman’s rank correlation coefficient.

[0084] FIG. 4 depicts data showing that TA and MB promoted epithelial gut barrier integrity, both under non-stressed and stressed conditions. The host-microbiome interaction assay assessed barrier integrity (TEER, normalized to 0 h) under (A) unstressed (24 h) and (B) stressed conditions (30 h = additional 6h LPS treatment). References included cell medium (blank), LPS treatment (between 24-30h; LPS) and its co-supplementation of dexamethasone (D) or hydrocortisone (H). The control to evaluate potential significance of treatment effects (= NSC) involved a study arm in which the IBS microbiota was cultured in the ex vivo SIFR® technology in absence of any treatment.

[0085] FIG. 5 depicts informational material regarding how the impact of TA and MB on the gut microbiota of IBS subjects was assessed using the ex vivo SIFR® (Systemic Intestinal Fermentation Research; Cryptobiotix, Belgium) technology (n = 8). (A) Experimental configuration, (B) timeline and analysis.

[0086] FIG. 6 depicts data showing that the strong increase in SCFA levels with TA was accompanied by only mild increases in gas production. (A) 2 Ratio of gas production per mole of SCFA being produced (mbar / mM). (B) Absolute gas production (mbar) in function of 3 total SCFA production (mM).

[0087] FIG. 7 depicts data showing that TA and MB tended to lower TNF-a, while exerting neutral effects on IL-6 and IL-10. The host-microbiome 7 interaction assay assessed (A) TNF-a, (B) IL-6, (C) IL- 10 at 3 Oh, i.e. upon 24h of interaction between test products and the 8 human cells, followed by LPS treatment for an additional 6h period. References included cell medium alone (blank), LPS 9 treatment alone (between 24-48h) and co-supplementation of dexamethasone (D) or hydrocortisone (H). The control to evaluate potential significance of treatment effects (= NSC) involved a study arm in which the IBS microbiota was cultured over 24h in the ex vivo SIFR® technology in absence of any treatment.

[0088] FIG. 8 depicts data showing that TA and MB did not impact traditional microbial diversity indices. The impact on (A) the Chaol diversity index, (B) Shannon diversity index and (C) reciprocal Simpson diversity index.

[0089] FIG. 9 depicts TB, TA, LB, and combinations of TB and TA plotted against key fermentative parameters over 24 hours.

[0090] FIG. 10 is a bar graph depicting gut barrier integrity improvements (TEER) across TA, TB, and MB test products under non-stressed and stressed conditions, illustrating a trend of MB > TA> TB.

[0091] FIG. 11 depicts predicted (SIFR® technology) and in vivo SCFA production (Boets et al., 2015) (mmol / g inulin / day).

[0092] FIG. 12 is a table of exemplary study arms, test products, respective test doses along with abbreviations that were used to refer to the study arms throughout the present disclosure.

[0093] FIG. 13 depicts an exemplary schematic overview of the reactor design, timeline and analysis of the project during which the SIFR® technology was used to assess the impact on metabolite production and composition by the gut microbiota of IBS donors (n = 8) upon treatment with the test products.

[0094] FIG. 14 depicts an overview of the statistical comparisons that were performed during the project.

[0095] FIG. 15 is a table of average values (± SD) of key fermentation parameters as averaged across all test subjects, at the end of the untreated NSC incubations, following inoculation with a faecal microbiota of IBS patients (n = 8).

[0096] FIG. 16 depicts graphs showing data from an exemplary principal component analysis (PCA) summarizing the impact on microbial metabolite production by the gut microbiota of IBS patients, based on key fermentation parameters. (A), (B) PCA calculated based on the average across the 8 different donors at (A) Oh and 24h and (B) 24h only. (C) PCA calculated based on individual values of the donors (at 24h).

[0097] FIG. 17 depicts several graphs showing the impact of the exemplary test products on (A) pH, (B) gas production, (C) total SCFA, (D) acetate, (E) propionate, (F) butyrate, (G) bCFA, (H) valerate for 8 IBS patients at 24h. Statistical differences between NSC and the individual treatments are visualized via * (0.1 < padjusted < 0.2), ** (0.05 < padjusted < 0.1) or *** (padjusted < 0.05). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicated a dark shade, and the highest value in a light shade.

[0098] FIG. 18 depicts several graphs showing a comparison of the exemplary effects of test products on gas production, total SCFA, acetate, propionate, butyrate, bCFA and valerate against the no-substrate control (NSC). The effects are presented as % of increase (positive values) or decrease (negative values) from NSC (dashed line), as averaged across 8 IBS donors. Standard deviation is indicated by vertical lines.

[0099] FIG. 19 is a table of a comparison between the empirical and theoretical SCFA released upon treatment with TA, TB and their mixtures. Ac: acetate, Pr: propionate, Bt: butyrate, Ac eq: acetate equivalents.

[0100] FIG. 20 depicts graphs showing the impact of the test products on the ratio between gas and SCFA production. (A) Ratio between the gas and SCFA production at 24h. Statistical differences between NSC and the individual treatments are visualized via * (0.1 < padjusted < 0.2), ** (0.05 < padjusted < 0.1) or *** (padjusted < 0.05). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicatedpurple, and the highest value in yellow. (B) Biplot illustrating the average relationship between gas and SCFA production at 24h for the different treatments. The vertical and horizontal lines indicate the standard deviation across the 8 donors. The grey dashed line indicates the expected ratio for the NSC.

[0101] FIG. 21 depicts (A) Principal component analysis (PCA) summarizing the microbial community composition of the 8 IBS patients that provided a faecal donation for the current SIFR® study, compared to a cohort of 8 healthy adults. The PCA was calculated based on the (centered) abundances (%) of the microbial genera, as quantified via 16S rRNA gene profiling. (B) Abundances (%) of the key genera of the different faecal microbiota.

[0102] FIG. 22 depicts bacterial OTUs that were found in significantly different relative abundances in the faecal microbiota of the IBS donors (n = 8) and the healthy adults (n = 8) (pnon-adjusted < 0.05).

[0103] FIG. 23 depicts (A / B / C / D) Microbial diversity, (E) bacterial cell density (cells / mL) and (F) average microbial composition at genus level (cells / mL) of the in vivo-derived inocula (INO) and upon 24h of incubation in the SIFR technology in absence of a treatment (NSC) (n = 8).

[0104] FIG. 24 depicts (A) a graph depicting the impact on total bacterial cell counts of the test products compared to an untreated control (NSC). Samples were collected after 24h of simulated colonic incubations. Statistical differences between NSC and the individual treatments are visualized via * (0.1 < padjusted < 0.2), ** (0.05 < padjusted < 0.1) or *** (padjusted < 0.05). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicated a dark shade, and the highest value in a light shade. (B / C) The impact of the test products on microbial composition at phylum level (based on 16S sequencing) as averaged over simulations for 8 IBS donors via the SIFR® technology platform, presented both as (B) proportional (%) and (C) absolute values (cells / mL).

[0105] FIG. 25 depicts several graphs showing the impact on A) the combined community modulation score (CMS), (B) the Chaol diversity index, (C) the reciprocal Simpson diversity index and the (D) Shannon diversity index, for the test products, compared to a no substrate control (NSC). Samples were collected after 24h of incubation. Statistical differences between NSC and the individual treatments are visualized via * (0.1 < padjusted < 0.2), ** (0.05 < padjusted < 0.1) or *** (padjusted < 0.05). The rank of the average values per treatment are indicated at thebottom of the figure, with the lowest average being indicated a dark shade, and the highest value in a light shade.

[0106] FIG. 26 depicts a principal component analysis (PCA) summarizing the impact of the test products on the gut microbial composition of IBS patients (n = 8), compared to a no substrate control (NSC), as tested via the SIFR® technology. The PCA was calculated based on the log2 -transformation of centered average levels of the top 150 most abundant OTUs, as quantified via 16S rRNA gene profiling combined with flow cytometry (cells / mL), at 24h of incubation. Top 15 OTUs (with top 5 highlighted in red) exhibited the largest variances in the PC As are indicated on the plot.

[0107] FIG. 27 depicts (A) The impact of the test products on bacterial families that were significantly (padjusted< 0.20, indicated by *) or consistently affected (indicated by $) by any of the treatments, expressed as log2 transformation of abundance treatment / abundance NSC ratios (log2FC), averaged across all 8 donors. Samples were collected at 24h after initiation of the colonic incubations. Log2FC was indicated in bold where statistical significance or consistent increase / decrease occurred. Top 5 families with the largest variations among the treatments in PCA analysis were also included in the heat map and indicated with #. (B) Regularized Canonical Correlation Analysis (rCCA) to highlight correlations between fundamental fermentation parameters and microbial composition upon fermentation in all study arms (threshold > 0.42). The white circles indicate values larger than the threshold and black dots indicate statistical significance (p < 0.05) in the individual correlations between the SCFA and the family based on Spearman’s rank correlation coefficient.

[0108] FIG. 28 depicts (A) The impact of the test products on OTUs that were significantly (padjusted < 0.20, indicated by *), or consistently affected by any of the treatments (indicated by $), expressed as log2 transformation of abundance treatment / abundance NSC ratios, averaged across all 8 donors. Samples were collected at 24h after initiation of the colonic incubations. Log2FC was indicated in bold where statistical significance or consistent increase / decrease occurred. Top 5 OTUs with the largest variations among the treatments in the PCA analysis were also included in the heat map and indicated with #. (B) Regularized Canonical Correlation Analysis (rCCA) to highlight correlations between fundamental fermentation parameters and microbial composition upon fermentation in all study arms (threshold > 0.33). The white circles indicate values larger than the threshold and black dots indicate statistical significance (p <0.05) in the individual correlations between the SCFA and the OTU based on Spearman’s rank correlation coefficient.

[0109] FIG. 29 depicts TA-associated stimulation of butyrogenic taxa (e.g., Faecalibacterium prausnitzii, Anaerobutyricum soehngenii, Mediterraneibacter A butyricigenes) and their correlations with butyrate.

[0110] FIG. 30 depicts additional Lachnospiraceae modulations with TA, including Bariatricus, Mediterraneibacter torques, and Hungatella hathewayi.

[0111] FIG. 31 depicts TB-associated changes, including increased levels of a butyrogenic Lachnospira pectinoschiza OTU.

[0112] FIG. 32 depicts MB’s bifidogenic effects (e.g., B. adolescentis, B. longum) and positive correlations between Bifidobacteriaceae and acetate.

[0113] FIG. 33 depicts MB-stimulated propionogenic taxa in Bacteroidaceae (e.g., Phocaeicola dorei, Bacteroides uniformis, B. caccae) and Parabacteroides distasonis with propionate correlations.

[0114] FIG. 34 depicts the propionogenic Coprococcus A catus response to MB, correlating positively with propionate and negatively with butyrate.

[0115] FIG. 35 depicts MB-stimulated butyrogenic OTUs (e.g., Anaerostipes hadrus, Lacrimispora, Roseburia inulinivorans, Butyribacter sp.) and other health-related taxa (e.g., Fusicatenibacter sacchari varans).

[0116] FIG. 36 is a table showing the identification level of compounds detected through metabolomics.

[0117] FIG. 37 depicts data from a principal component analysis (PC A) comparing the biological variances of the samples at Oh and 24h to the analytical variance of the quality control (QC) samples. PCA was calculated based on standardized values of metabolites annotated at level 1 / 2a as quantified via untargeted LC-MS for 8 different IBS patients.

[0118] FIG. 38 depicts amino acid consumption / production trends between 0 h and 24 h across donors, highlighting efficient conversion of select amino acids.

[0119] FIG. 39 depicts data from a principal component analysis (PC A) summarizing the impact on microbial metabolite production by the gut microbiota of IBS (n = 8) as tested via the SIFR® technology, upon simulated ingestion of the test products. The PCA was calculated based on the standardized average values across the eight donors tested for 77 ‘produced’ metabolites annotated at level 1 / 2a, quantified via untargeted LC-MS, at 24h upon initiation of the colonic incubations.

[0120] FIG. 40 depicts a heat map showing the impact of the test products compared to a no substrate control (NSC) on metabolites annotated at level 1 / 2 as quantified via untargeted LC-MS after 24h of incubation, tested via the SIFR® technology for IBS patients (n = 8). The metabolites were significantly affected by any of the treatments (FDR = 0.20). Significant differences are indicated by bold of the average log 2(abundance treatment / abundance NSC).

[0121] FIG. 41 depicts a heat map showing the results of a Regularized Canonical Correlation Analysis (rCCA) to highlight correlations between specific significantly affected metabolites (shown in FIG.40) and significantly / consistently affected families (shown in FIG.27) (threshold > 0.29). The white circles indicate values larger than the threshold and black dots indicate statistical significance (p < 0.05) in the pairwise correlations between the metabolites and the families based on Spearman’s rank correlation coefficient.

[0122] FIG. 42 depicts a heat map showing the results of a Regularized Canonical Correlation Analysis (rCCA) to highlight correlations between specific significantly affected metabolites (shown in FIG. 40) and significantly / consistently affected OTUs shown in Figure 15 A) (threshold > 0.25). The white circles indicate values larger than the threshold and black dots indicate statistical significance (p < 0.05) in the pairwise correlations between the metabolites and the OTUs based on Spearman’s rank correlation coefficient.

[0123] FIG. 43 depicts graphs showing increases in 3 -methylhistidine with TB, TA, and TA / TB mixtures relative to NSC.

[0124] FIG. 44 depicts graphs showing increases in 4-guanidinobutyric acid, muramic acid, and tetrahydro-2H-pyran-2-one associated with higher TA content.

[0125] FIG. 45 depicts graphs showing decreases in tryptophol and indole-3 -acetic acid with TA and / or TB relative to NSC.

[0126] FIG. 46 depicts graphs showing the impact of the test products compared to a no substrate control (NSC) on gut barrier integrity as measured by the TEER of the Caco-2 epithelial layer after (A) 24h treatment in absence of LPS and (B) 30h treatment (including 6h treatment with LPS) in the basal compartment containing differentiated THP-1 cells) using the SIFR® technology. Samples exposed to the cells were collected from the SIFR® model after 24h of colonic incubation. Statistical differences between NSC and the individual treatments are visualized via * (0.1 < padjusted < 0.2), ** (0.05 < padjusted < 0.1) or *** (padjusted < 0.05). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicated purple, and the highest value in yellow.

[0127] FIG. 47 depicts various graphs showing Pearson correlation analysis between SCFA production and gut barrier integrity as measured by the TEER of the Caco-2 epithelial layer after (A-D) 24h treatment in the absence of LPS and (E-H) 30h of treatment (= 24h in absence of LPS and 6h in presence of LPS in the basal compartment containing differentiated THP-1 cells).

[0128] FIG. 48 depicts graphs showing the impact of the test products compared to a no substrate control (NSC), on immune modulation as measured by the levels of immune markers (A)TNF-a, (B) IL-6, (C) IL-8, (D) CXCL-10, (E) IL-10, (F) ILl-p. Statistical differences between NSC and the individual treatments are visualized via * (0.1 < padjusted < 0.2), ** (0.05 < padjusted < 0.1) or *** (padjusted < 0.05). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicated in a dark shade, and the highest value in a light shade.

[0129] FIG. 49 depicts a heat map showing regularized Canonical Correlation Analysis (rCCA) to highlight correlations between gut barrier integrity (TEER) and immune markers with microbial composition at OTU level (threshold > 0.38). The white circles indicate values larger than the threshold and black dots indicate statistical significance (p < 0.05) in the individual correlations between the SCFA and the families based on Spearman’s rank correlation coefficient.

[0130] FIG. 50 depicts the impact of triacetin and the mushroom blend on (A) butyrate and (B) total SCFA production as normalized against the test dose, at 24h. The line indicates the average and standard deviation of inulin.

[0131] FIG. 51 depicts an illustration of the inaccuracy of diversity estimations for products that increase (e.g. prebiotic) or decrease (e.g. antibiotic) total cell density of the gut microbiome.

[0132] FIG. 52 depicts an data showing Dextran supported a high microbial diversity of the human adult gut microbiota ex vivo. The impact of dextran and IN on the novel community modulation scores (CMS), presented as a positive (increased OTUs), negative (decreased OTUs) and combined score.

[0133] FIG. 53 is a List of level 1 / 2a metabolites identified in the exemplary metabolomics analysis; Level 1: identification by retention times (compared against in-house authentic standards), accurate mass (accepted deviation of 3ppm), and MS / MS spectra, Level 2a: identification by retention times (compared against in-house authentic standards), accurate mass (accepted deviation of 3ppm).

[0134] FIG. 54 depicts additional panels of metabolomics outcomes (Level l / 2a).

[0135] FIG. 55 depicts further panels of metabolomics outcomes (Level l / 2a).

[0136] FIG. 56 depicts graphs showing the impact of the test products on the most abundant phyla in the microbiota of IBS patients (n = 8), compared to a no substrate control (NSC). Statistical differences between NSC and the individual treatments are visualized via * (0.1 < Padjusted < 0.2), ** (0.05 < Padjusted < 0.1) or * * * (padjusted < 0.05). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicated in a dark shade, and the highest value in a light shade.

[0137] FIG. 57 depicts additional graphs showing the impact of the test products on more of the most abundant phyla in the microbiota of IBS patients (n = 8), compared to a no substrate control (NSC). Statistical differences between NSC and the individual treatments are visualized via * (0.1 < Padjusted < 0.2), ** (0.05 < padjusted < 0.1) or * * * (padjusted < 0.05). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicated in a dark shade, and the highest value in light shade.

[0138] FIG. 58 depicts a schematic overview of the reactor design, timeline and analysis of the exemplary project in which the SIFR® technology was used to assess the impact on the gut microbiota of obese dogs (n = 8) upon treatment with triacetin.

[0139] FIG. 59 depicts a table of the average values (± SD) of key fermentative parameters as averaged across all test subjects, at the end of the untreated NSC incubations, following inoculation with a faecal microbiota of obese dogs (n = 8).

[0140] FIG. 60 depicts graphs showing results of a principal component analysis (PCA) summarizing the impact on microbial metabolite production by the obese dogs’ gut microbiota, based on key fermentative parameters. PCA calculated based on the average across the eight different animals (A) at Oh and 24h and (B) PCA calculated based on individual values of the animals (at 24h).

[0141] FIG. 61 depicts graphs showing the impact of triacetin on (A) pH, (B) gas production, (C) total SCFA, (D) acetate, (E) propionate, (F) butyrate, (G) bCFA for eight obese dogs at 24h. Statistical differences between NSC and triacetin are visualized via * (0.01 < Padjusted < 0.05), ** (0.001 < Padjusted < 0.01) or * * * (padjusted < 0.001). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicated as a dark shade, and the highest value as a light shade.

[0142] FIG. 62 depicts dot plots showing a comparison of the effects of triacetin on gas production, total SCFA, acetate, propionate, butyrate, bCFA against the no-substrate control (NSC). The effects are presented as % of increase (positive values) or decrease (negative values) from NSC (dashed line), as averaged across all eight animals. Standard deviation is indicated by vertical lines.

[0143] FIG. 63 is a table displaying a comparison between the empirical and theoretical SCFA released upon treatment with TA. Ac: acetate, Pr: propionate, Bt: butyrate, Ac eq: acetate equivalents.

[0144] FIG. 64 depicts graphs showing the impact of triacetin on the ratio between gas and SCFA production. (A) Ratio between the gas and SCFA production at 24h. Statistical differences between NSC and triacetin are visualized via * (0.01 < padjusted < 0.05), ** (0.001 < Padjusted < 0.01) or *** (padjusted < 0.001). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicated purple, and the highest value in yellow. (B) Biplot illustrating the average relationship between gas and SCFA production at 24h for the different treatments. The vertical and horizontal lines indicate the standard deviation across the 8 animals. The grey diagonal dashed line indicates the expected ratio based on the data of the NSC.

[0145] FIG. 65 depicts data for (A) Principal component analysis (PCA) summarizing the microbial community composition of the eight obese dogs that provided a faecal donation for the current SIFR® study. The PCA was calculated based on the (centred) abundances (%) of the microbial genera, as quantified via 16S rRNA gene profiling. (B) Abundances (%) of the key genera of the different faecal microbiota.

[0146] FIG. 66 depicts graphs of data regarding (A / B / C) Microbial diversity, (D) bacterial cell density (cells / mL) and (E) average microbial composition at genera level (cells / mL) of the in vivo-derived inocula (INO) and upon 24h of incubation in the SIFR® technology in absence of a treatment (NSC) (n = 8).

[0147] FIG. 67 depicts graphs showing (A) the impact on total bacterial cell counts of triacetin compared to an untreated control (NSC). Samples were collected after 24h of colonic incubations. Statistical differences of NSC vs. triacetin are visualized via * (0.01 < padjusted < 0.05), ** (0.001 < padjusted < 0.01) or *** (padjusted < 0.001). The rank of the average values per treatment are indicated at the bottom, with the lowest average being indicated in a dark shade, and the highest in a light shade. (B / C) The impact of triacetin on composition at phylum level as averaged over simulations for eight animals, presented as (B) proportional (%) and (C) absolute values (cells / mL).

[0148] FIG. 68 depicts violin plots showing the impact of triacetin on (A) the combined community modulation score (CMS), (B) the Chaol diversity index, (C) Shannon diversity index and (D) the reciprocal Simpson diversity index, compared to a no substrate control (NSC). Samples were collected after 24h of incubation. Statistical differences between NSC and triacetin are visualised via * (0.01 < padjusted < 0.05), ** (0.001 < padjusted < 0.01) or *** (padjusted < 0.001). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicated purple, and the highest value in yellow.

[0149] FIG. 69 depicts a graph showing the results of a principal component analysis (PCA) summarizing the impact of triacetin on the gut microbial composition of obese dogs (n = 8), compared to a no substrate control (NSC), as tested via the SIFR® technology. The PCA was calculated based on the log2 -transformation of centered average levels of the top 50 most abundant species, as quantified via shotgun sequencing combined with flow cytometry (cells / mL). Top 15 species that exhibited the largest variances in the PC As are highlighted (with top 5 highlighted in red).

[0150] FIG. 70 depicts (A), (B) heat graphs of the impact of triacetin on bacterial families (A) and species (B) that were consistently affected (indicated by $) by any of the treatments, expressed as log2 transformation of abundance treatment / abundance NSC ratios (log2FC), averaged across all eight animals. No taxa were significantly affected by triacetin (padjusted < 0.05). Samples were collected at 24h after initiation of the colonic incubations. Log2FC was indicated in bold where statistical significance or consistent increase / decrease occurred. Top 5 families with the largest variations among the treatments based on PCA analysis were also included in the heat map and indicated with #. (C), (D) Regularized Canonical Correlation Analysis (rCCA) to highlight correlations between fundamental fermentative parameters and microbial composition at family and species level, respectively, upon fermentation in all study arms. The white circles indicate values larger than the threshold and black dots indicate statistical significance (p < 0.05) in the individual correlations between the SCFA and the families or species based on Spearman’s rank correlation coefficient.

[0151] FIG. 71 is a table showing the identification level of compounds detected through metabolomics in the exemplary experiment in which the impact of triacetin on the gut microbiome of obese dogs was studied.

[0152] FIG. 72 depicts dot graphs showing principal component analysis (PCA) summarizing the impact on metabolite production by the gut microbiota of obese dogs (n = 8) upon treatment with test products compared to a parallel untreated no substrate control (NSC). The PCA was calculated based on 10 different quality control samples and standardized individual values of metabolites annotated at level 1 / 2a as quantified via untargeted LC-MS, at 0 / 24h of colonic incubations. Numbers indicate the dogs recruited as faecal donors for this study, while arrows indicate the effect of TA on the individual dogs.

[0153] FIG. 73 depicts a list of level 1 / 2a metabolites identified in the metabolomics analysis in the exemplary experiment in which the impact of triacetin on the gut microbiome of obese dogs was studied; Level 1: identification by retention times (compared against inhouse authentic standards), accurate mass (accepted deviation of 3ppm), and MS / MS spectra, Level 2a: identification by retention times (compared against in-house authentic standards), accurate mass (accepted deviation of 3ppm).

[0154] FIG. 74 is a list of additional l / 2a metabolites identified in the metabolomics analysis in the exemplary experiment in which the impact of triacetin on the gut microbiome of obese dogs was studied, continued from FIG. 73.

[0155] FIG. 75 is a list of yet additional l / 2a metabolites identified in the metabolomics analysis, continued from FIG. 73.

[0156] FIG. 76 is a list of still further l / 2a metabolites identified in the metabolomics analysis, continued from FIG. 73.

[0157] FIG. 77 depicts various violin plots for 11 metabolites that were significantly affected by at least one of the treatments in the exemplary experiment in which the impact of triacetin on the gut microbiome of obese dogs was studied.

[0158] FIG. 78 depicts a heat map for the 11 metabolites that were significantly affected by at least one of the treatments in the exemplary experiment in which the impact of triacetin on the gut microbiome of obese dogs was studied based on the log2ratios versus the NSC. The heat map shows the impact of triacetin compared to a no substrate control (NSC) on metabolites annotated at level 1 / 2 as quantified via untargeted LC-MS after 24h of incubation, tested via the SIFR® technology for obese dogs (n = 8). The metabolites were significantly affected by any of the treatments (FDR = 0.05). Significant differences are indicated by bold of the average log2(abundance treatment / abundance NSC).

[0159] FIG. 79 depicts the results from a Regularized Canonical Correlation Analysis (rCCA) to highlight correlations between specific significantly affected metabolites (shown in FIG. 78) and (A) top 5 families contributing the largest variations (shown in 70A) and (B) top 5 species contributing the largest variations and consistently affected species (shown in Figure 1 IB) upon simulated ingestion of triacetin (threshold > 0.35 and 0.43, respectively). The white circles indicate values larger than the threshold and black dots indicate statistical significance (p < 0.05) in the individual correlations between the metabolites and the families based on Spearman’s rank correlation coefficient. The white circles indicate values larger than the threshold and black dots indicate statistical significance (p < 0.05) in the individual correlations between the SCFA and the species based on Spearman’s rank correlation coefficient.

[0160] FIG. 80 depicts an infographic illustrating SIFR® screening and prism modes and the pipeline for predictive, translational gut-health R& D.1

[0161] FIG. 81 depicts an infographic showing the general process for determining SIFR® predictivity for in vivo changes in microbial composition and barrier-integrity benefits observed clinically.

[0162] FIG. 82 depicts a bar graph measuring the release of acetate along the simulated upper GIT passage (expressed as % of the animal equivalent dose (AED); for test arms where no acetate was dosed, identical AED as TA was assumed). Final % released at the end of the small intestinal phase are shown on the corresponding bars of the test products.

[0163] FIG. 83 depicts various violin plots showing the impact of the tri acetin on the most abundant phyla in the canine microbiota (n = 8), compared to a no-substrate control (NSC). Statistical differences between NSC and triacetin are visualized via * (0.01 < padjusted < 0.05), ** (0.001 < padjusted < 0.01) or *** (padjusted < 0.001). The rank of the average values per treatment are indicated at the bottom of the figure, with the lowest average being indicated in a dark shade, and the highest value in a light shade.Detailed Description

[0164] Short-chain fatty acids (SCFAs) such as acetate, propionate, and butyrate are end-products of microbial metabolism in the large intestine. Acetic acid, the acid form of acetate, is a SCFA produced naturally in the gut, primarily by bacterial fermentation of fibers in the colon. Acetic acid is the most abundant SCFA in the gut, exceeding propionic and butyric acid levels by two-fold and plays several essential roles in gut health. For example, acetic acid increases colonic blood flow and ileal motility and is anti-inflammatory. Additionally, studies have shown that acetic acid administration significantly increased energy expenditure and suppressed fat accumulation in animals, and these results have been extended to human subjects.

[0165] SCFAs contribute to overall gut health, maintenance of epithelial barrier function, support colonocyte energy requirements, influence luminal pH, and have been associated with immunomodulatory effects. In individuals with dysbiotic microbiota or functional bowel disorders, SCFA profiles can deviate from eubiotic reference patterns. A variety of dietary and supplemental strategies have been explored to modulate SCFAs, including fermentable fibers, resistant starches, direct SCFA salts, and triglyceride esters of SCFAs.

[0166] Many direct SCFA sources (e.g., butyrate and some salts) can present strong off-odors and aversive taste, leading to poor palatability and adherence. Fermentable substrates can elevate SCFAs, but they may also increase gas production and bloating in sensitive populations. Therefore, there remains a need for orally deliverable compositions that are acceptable to consumers at efficacious use levels, and that favorably modulate SCFA levels without undue gastrointestinal discomfort, particularly in subjects that are sensitive to bloating.

[0167] Triacetin (glycerol triacetate) is the triester of glycerol and acetic acid. Upon enzymatic hydrolysis, triacetin yields glycerol and acetate. Without being bound by theory, the acetate released from triacetin is contemplated to contribute to luminal acetate pools and, through microbial cross-feeding pathways, support production of other SCFAs such as butyrate in the colon.

[0168] From a stoichiometric perspective, one mole of triacetin can liberate up to three moles of acetate upon complete hydrolysis. This relationship provides a convenient “theoretical acetate” reference against which measured SCFA changes can be compared in experimental models. In some contexts, observed increases in total SCFAs may exceed the theoretical contribution of administered acetate alone, which may reflect microbially mediated amplification mechanisms (e.g., cross-feeding, pH-mediated growth advantages).

[0169] SCFA bioactivity is often most relevant in the distal small intestine and colon. Free SCFAs and certain salts may be absorbed or neutralized proximally, reducing distal delivery. Triacetin, by contrast, is an ester that can be formulated in ways that influence the site and rate of hydrolysis. For example, selection of dosage form (capsule, powder, ready-to-mix beverage, ready-to-drink beverage, gummy, or other food formats), matrix composition, and optional encapsulation strategies can modulate release kinetics. In certain embodiments, limiting small-intestinal liberation of acetate may enhance colonic availability and functional effects.

[0170] There remains a need for palatable oral compositions comprising triacetin that are acceptable to consumers at specified dosing concentrations; and compositions and methods that increase gut SCFAs by defined thresholds e.g., at least 10%) relative to baseline, optionally with constraints on gas production.

[0171] The present disclosure addresses these needs in separate Aspects, each supported by a common technical background. Unless expressly stated otherwise, “Aspect 1” and “Aspect 2” are provided for organizational convenience only. Any feature, element, limitation, range,parameter, component, or step described in connection with one Aspect may be used with, substituted for, combined with, or omitted from the other Aspect(s), in whole or in part, in any operable order and combination, to the extent not mutually exclusive. Accordingly, the disclosure contemplates embodiments implementing only Aspect 1, only Aspect 2, both Aspects together, and any permutation comprising selected features from one or both Aspects (including optional features, repetitions, re-ordering of steps, and scaling within stated ranges).Aspect 1: Palatable Triacetin Compositions

[0172] The inventor has unexpectedly discovered various methods and compositions for triacetin, typically at a concentration of about 100-1000 mg triacetin per 1-8 oz of the composition, that are palatable, stable, and effective at providing and / or increasing the concentration of short-chain fatty acids (SCFAs) in the lower gut. At the contemplated formulation concentrations, the compositions described herein may also be suitable as ready-to-mix (RTM) and / or ready-to-drink (RTD) formulations. Therefore, the inventor has discovered a good-tasting supplement that can effectively reach the colon and lower gastrointestinal (GI) to release SCFAs at desired concentrations, whereas supplements in the prior art fail to deliver SCFAs to the colon at the same quantities while being as palatable. Viewed from another perspective, the inventor herein contemplates various compositions and methods of increasing the concentration of SCFAs in the gut of a subject by administering to the subject a palatable composition comprising triacetin and a flavorant, wherein the triacetin is imperceivable or maskable by taste.

[0173] In some embodiments, an effective amount of triacetin is any amount that, in one dosage, improves the health of the microbiome of the lower intestine, improves the integrity of the gastrointestinal barrier, and / or is absorbable in the lower gastrointestinal tract such that at least 50%, at least 60%, at least 70% or at least 80% of administered triacetin reaches the lower gastrointestinal tract.

[0174] It is contemplated that, so long as relative concentrations of the active compound and final composition remain within the ranges described herein, the resulting compositions will maintain desirable palatability while delivering an ideal or effective amount of SCFAs to the intended target site, whether it be the lower GI, colon, or overall gut. Notably, preferred formulations will include free triacetin in the specified concentration ranges in which the triacetin is or can be sufficiently diluted in a liquid carrier to allow for masking the flavor witha flavorant such that the triacetin flavor is rendered imperceptible, but present at quantities that will an effective amount of triacetin to the distal small intestine and colon. For example, it is contemplated that the compositions described herein may comprise an active compound, such as triacetin or a triglyceride, at concentrations ranging from about 100 mg to about 1000 mg for every 1 to 8 fluid ounces (fl oz) of the composition when prepared for oral administration. In certain embodiments, the compositions provide about 100 mg, 200 mg, 300 mg, 400 mg, 500 mg, 600 mg, 700 mg, 800 mg, 900 mg, or 1000 mg of the active compound per approximately 1 fl oz, 8 fl oz, 12 fl oz, 16 oz, 18 oz, or 20 oz of the final beverage or formulation. In other embodiments, the compositions may provide about 100-1000 mg per 1-20 fl oz, or about 1-1000 mg per 8-12 fl oz. These formulation concentrations may be adjusted depending on desired palatability and dosage. The specific milligram amounts and fluid-ounce volumes recited herein may be freely adjusted, interchanged, or combined as would be understood by one of ordinary skill in the art to achieve the desired concentration, taste, and / or bioavailability. For example, one embodiment of the compositions disclosed herein is an 8-oz beverage having 100-1000 mg of triacetin.

[0175] However, in other embodiments, a dosage unit may contain between 1 mg and 50,000 mg triacetin or more. For example, contemplated dosage ranges include between 0.1 mg and lOOmg, between 50 mg and 500 mg, between 250 mg and 1,000 mg, between 800 mg and 2,000 mg, between 1,500 mg and 5,000 mg, between 4,000 mg and 8,000 mg, between 6,000 mg and 12,000 mg, between 10,000 mg and 25,000 mg, between 20,000 mg and 40,000 mg, or between 35,000 mg and 70,000 mg. In further example, there may be at least 0.5mg, at least 10 mg, at least 50 mg, at least 100 mg, at least 500 mg, at least 1,000 mg, at least 2,000 mg, at least 3,000, at least 4,000 mg, at least 5,000 mg, at least 10,000 mg, at least 25,000 mg, or at least 50,000 mg. In various embodiments, the dosage unit is contemplated to include no more than 60,000 mg, no more than 40,000 mg, no more than 20,000 mg, no more than 10,000 mg, no more than 8,000 mg, no more than 6,000 mg, no more than 4,000 mg, no more than 2,000 mg, no more than 800 mg, no more than 600 mg, no more than 400 mg, no more than 200 mg, or no more than 1 mg.

[0176] However, as described herein, the preferable range of triacetin concentration such that the composition delivers effective amounts of triacetin while being palatable and having a masked triacetin flavor remain in the range between 100-1000 mg triacetin per 1-20 oz of the composition. In this context, it should be especially appreciated that the quantities of triacetinnoted herein are immediately bioavailable and not encapsulated, complexed in an inclusion complex, or otherwise sequestered within a carrier. Thus, where a formulation is a liquid, triacetin forms a homogenously distributed part of the liquid formulation. Where a formulation is in a powder (or otherwise dried) for, the triacetin will be adsorbed to a soluble carrier (e.g., a gum) such that upon placement of the carrier with adsorbed triacetin, both the carrier and the triacetin will go readily (e.g., within less than 60 sec) into solution.

[0177] In further contemplated aspects of the disclosed subject matter, the triacetin is the sole or predominant (e.g., at least 60 wt%, or at least 70 wt%) active ingredient in the composition which increases concentration of SCFAs in the gut, or the composition may further comprise an additional active ingredient which increases the concentration of SCFAs in the gut (e.g., or one or more probiotic, prebiotic, and / or postbiotic).

[0178] Especially where the contemplated compositions are formulated as RTD products, and in some embodiments, a composition may comprise triacetin in the contemplated concentrations diluted or combined with a liquid carrier such as water, juice, protein shake, medical drink, nutritional drink, soda, sparkling water, sports drink, or another beverage base. In further embodiments, the composition comprises a fiber drink, such as a fiber-fortified juice, smoothie mix with added fiber, pre-mixed fiber drink, a Metamucil® product, a Fiber One® product, a Benefiber® product, an Olipop® product, or other fiber drinks. In yet additional embodiments, the composition comprises a nutrition drink, such as Ensure® by Abbott™, BOOST® by Nestle®, Glucerna®, a Kate Farms® product, an Orgain® product, a TopCare® product, or other nutrition drinks. In such embodiments, it is contemplated that adding triacetin, with or without a pharmaceutically or nutritionally acceptable carrier, at the disclosed concentrations per fluid ounce of beverage, results in a beverage that can deliver effective amounts of acetic acid to the lower GI or colon while having a triacetin-undetectable or triacetin-masked flavor.

[0179] It should be appreciated that triacetin may additionally be introduced into the composition from a soft chew composition or a gummy composition formulated for humans or animals. In some aspects, the contemplated compositions are specifically formulated as pet food compositions, such as base meals of raw, freeze-dried, or cooked meat, fish, eggs, vegetables, kibble, canned foods, pet medicines, catnip, and other good products for pets.

[0180] Especially where the contemplated compositions are formulated as RTM products, and in further embodiments, the inventor contemplates a triacetin-containing RTM composition optionally combined with a pharmaceutically or nutritionally acceptable carrier which can be added to a liquid carrier. In such embodiments, the RTM compositions may be provided as powders, granules, or other solid or semi-solid forms configured to be mixed or reconstituted with a liquid carrier prior to oral administration. Suitable carriers for RTM formulations include, without limitation, cellulose, microcrystalline cellulose, hydroxypropyl methylcellulose (HPMC), carboxymethylcellulose (CMC), maltodextrin, starch, sucrose, dextrose, mannitol, or combinations thereof. Such carriers may serve to stabilize the active compound, provide bulk and uniform distribution, improve flowability, prevent clumping, enhance dispersibility upon hydration, or impart desirable texture and mouthfeel.

[0181] Further, and in other embodiments, suitable compositions can be formulated as powders, granules, encapsulated particles, emulsified pre-mixes, concentrated syrups, chews, gummies, gel dissolvable tablets, buccal pouch, nasal spray or other solid or semi-solid preparations that are readily combinable with a liquid or ingestible medium prior to use. In certain embodiments, the compositions may be provided in single-serve packets, sachets, stickpacks, or scooped portions, facilitating easy preparation of drinkable beverages. However, in many embodiments, the contemplated compositions are final, packaged products such as liquids or beverages.

[0182] Accordingly, the RTD, RTM, and / or other formulations described herein enable convenient formulation, storage, and consumption while maintaining the stability and bioavailability of the active compound.

[0183] In preferred embodiments, the administering is orally administering. However, in other embodiments, the administering may be sublingual, buccal, enteral, parenteral, or even rectal administration. In contemplated formulations made using RTM and / or RTD formulations, a daily recommended dosage may be 100 mg per 1 oz, or less than 90 mg / oz, less than 80 mg / oz, less than 70 mg / oz, less than 60 mg / oz, less than 50 mg / oz, less than 40 mg / oz, less than 30 mg / oz, less than 20 mg / oz, or less than 10 mg / oz. In further embodiments of the disclosed invention, the daily recommended dosage may be at least 100 mg, 300 mg, at least 500 mg, at least 750 mg, at least 1 g, at least 3 g, or at least 5 g. Carriers of the formulations may be liquid (typically aqueous, which may be carbonated or not) or solid, or semi-solid (e.g., gels, pastes, gummies, etc.).

[0184] To evaluate palatability, a comparison can be drawn between a butyric acid (BA) dilution series, with concentrations ranging from 0.01 mg BA per 1 oz to 500 mg BA per 1 oz, to an RTD composition comprising 100 mg triacetin per 1 oz. In such a series, the inventor discovered that the triacetin composition is far more palatable than 500 mg BA / oz, 250 mg BA / oz, 100 mg BA / oz, 50 mg BA / oz, 25 mg BA / oz, 10 mg BA / oz, and / or 3 mg BA / oz. Compared to just 1 mg BA / oz, the composition comprising triacetin is contemplated to be slightly more palatable. At around 0.3 mg BA / oz, the composition comprising triacetin is contemplated to be most comparable in palatability. At 0.1 mg BA / oz and lower, the BA dilution is contemplated to be more palatable than the composition comprising triacetin. As will be readily appreciated, while now palatable, such low concentrations of BA will be substantially ineffective to deliver meaningful quantities to the distal small intestine and colon. The palatability and maskability of free triacetin at the contemplated concentrations (e.g., between 100-1,000 mg in 1-8 oz) is particularly unexpected as corresponding quantities of free acetate, butyrate, and tributyrin would be very unpleasant or completely repulsive.

[0185] Evaluations of palatability may be measured using hedonic scale testing, wherein participants taste each product and rate the products on a 9-point scale, from “dislike extremely (1) to “like extremely” (9). In some hedonic scale testing comparisons, a mean difference of 1 or more on the scale between products is considered a statistically significant difference, allowing one to conclude that a product is significantly more palatable than the other. However, in some embodiments of the present invention, even if the threshold of significance is raised to 2, 3, or even 4 points of difference on the scale, it is contemplated the composition comprising 100-1,000 mg triacetin per 1-8 oz is still significantly more palatable than nearly all formulations of BA. Additionally, or alternatively, hedonic scale testing may be used as described by Jones, L. V., Peryam, D. R., and Thurstone, L. L. 1955. Development of a scale for measuring soldiers’ food preferences. Food Research, 20, 512-520, and / or as described by Peryam, D. R. and Pilgrim, F. J. 1957. Hedonic scale method of measuring food preferences. Food Technology (September 1957), 9-14.

[0186] Using at least one hedonic scale, a composition is generally considered in some embodiments to be palatable or acceptable when it achieves a mean score about 6.0 or higher on the 9-point scale. However, in the food and beverage market, companies generally target a mean score of 6.5-7.0 to ensure market viability. Therefore, it is contemplated that the compositions herein may be palatable when exhibiting mean hedonic scores within orexceeding about 6.0, indicating consumer acceptability and suitability for commercial formulation. In further embodiments, the compositions herein are considered to be more palatable than a comparative sample of BA or when exhibiting a mean hedonic score difference of more than 1.0.

[0187] It is further contemplated that an advantage of the disclosed compositions is that the palatability may be influenced by the proportionality / linearity of the flavor intensity to the amount of flavoring added to the composition. For example, and in some embodiments, flavor intensity may be measured on a scale of 1 to 10 points, where 1 represents a barely noticeable flavor intensity and 10 represents maximum flavor intensity to the point of being overwhelming. Applying such a scale to the disclosed compositions, which are contemplated to have a linear / proportional flavor intensity, may mean that every 10 mg of flavorant added increases flavor intensity by about 0.5 point. Perhaps for a second flavorant with a much more noticeable flavor profile, 10 mg would increase the flavor intensity by 3 points. In other embodiments, a combination of a first and second flavorant may achieve an increase in flavor intensity. Notably, while triacetin formulations at a concentration range of 100-1,000 mg / 1-8 oz can be effectively masked with one or more flavorants, the chemically very similar acetic acid / butyric acid formulations or tributyrin formulations were not able to be effectively masked to produce an acceptable flavor.

[0188] In further embodiments, in addition to being palatable, or as an alternative, the contemplated compositions may be triacetin-maskable. A “triacetin-maskable” composition refers to a composition comprising triacetin in a state such that the characteristic triacetin flavor can be substantially masked or rendered organoleptically undetectable by the inclusion of only a low concentration of flavorant or masking agent. Such composition can be considered triacetin-maskable if, when combined with a flavorant or masking agent at or below a minimal masking threshold, the triacetin flavor is no longer perceptible to an ordinary human taster. In one embodiment, the composition is triacetin-maskable when the triacetin flavor recognition rate decreases by at least 75% upon the addition of the flavorant or masking agent present at no more than between 0.1-1.0 wt% of the total composition, as determined using triangle testing or ASTM El 885 sensory protocols. In another embodiment, the triacetin flavor intensity score, measured on a 9-point sensory scale, decreases by at least 3 units on average when a masking flavorant is added at or below X ppm, wherein X is less than or equal to 25% of the concentration typically required to mask triacetin flavor in aqueous control solutions.

[0189] Therefore, and in one embodiment of the inventive subject matter, a composition is contemplated comprising triacetin at 100-1,000 mg per 1-8 fl oz and a flavorant, formulated to be palatable and / or triacetin-maskable, wherein flavor intensity increases substantially linearly with the amount of added flavoring.

[0190] Examples of suitable flavorants and / or flavoring may include MCT oil, vanillin, stevia, lemon oil, caffeine, citric acid, or other substances which tend to affect flavor intensity. Additionally, bitter masking agents, such as sodium gluconate, may be incorporated into the composition to affect the flavor intensity. In some embodiments, flavorants may include those flavors known to the skilled artisan, such as natural and artificial flavors. These flavorings may be chosen from synthetic flavor oils and flavoring aromatics and / or oils, oleoresins and extracts derived from plants, leaves, flowers, fruits, and so forth, and combinations thereof. The flavorant may be a hydrophobic flavorant, in some embodiments.

[0191] Nonlimiting representative flavor oils include spearmint oil, cinnamon oil, oil of wintergreen (methyl salicylate), peppermint oil, Japanese mint oil, clove oil, bay oil, anise oil, eucalyptus oil, thyme oil, cedar leaf oil, oil of nutmeg, allspice, oil of sage, mace, oil of bitter almonds, and cassia oil. Also useful flavorings are artificial, natural and synthetic fruit flavors such as vanilla, and citrus oils including lemon, orange, lime, grapefruit, yazu, sudachi, and fruit essences including apple, pear, peach, grape, berry, blueberry, strawberry, raspberry, cherry, plum, pineapple, apricot, banana, melon, apricot, ume, cherry, raspberry, blackberry, black currant, tropical fruit, mango, mangosteen, pomegranate, papaya and so forth. Other potential flavors whose release profiles can be managed include a milk flavor, a butter flavor, a cheese flavor, a cream flavor, and a yogurt flavor; a vanilla flavor; a creamy vanilla flavor; tea or coffee flavors, such as a green tea flavor, a oolong tea flavor, a tea flavor, a cocoa flavor, a chocolate flavor, and a coffee flavor; mint flavors, such as a peppermint flavor, a spearmint flavor, and a Japanese mint flavor; spicy flavors, such as an asafetida flavor, an ajowan flavor, an anise flavor, an angelica flavor, a fennel flavor, an allspice flavor, a cinnamon flavor, a camomile flavor, a mustard flavor, a cardamom flavor, a caraway flavor, a cumin flavor, a clove flavor, a pepper flavor, a coriander flavor, a sassafras flavor, a savory flavor, a Zanthoxyli Fructus flavor, a perilla flavor, a juniper berry flavor, a ginger flavor, a star anise flavor, a horseradish flavor, a thyme flavor, a tarragon flavor, a dill flavor, a capsicum flavor, a nutmeg flavor, a basil flavor, a maijoram flavor, a rosemary flavor, a bayleaf flavor, and a wasabi (Japanese horseradish) flavor; alcoholic flavors, such as a wine flavor, a whisky flavor, abrandy flavor, a rum flavor, a gin flavor, and a liqueur flavor; floral flavors; and vegetable flavors, such as an onion flavor, a garlic flavor, a cabbage flavor, a carrot flavor, a celery flavor, mushroom flavor, and a tomato flavor. These flavoring agents may be used in liquid or solid form and may be used individually or in admixture. Commonly used flavors include mints such as peppermint, menthol, spearmint, artificial vanilla, cinnamon derivatives, and various fruit flavors, whether employed individually or in admixture. Flavors may also provide breath freshening properties, particularly the mint flavors when used in combination with cooling agents, as discussed in US20080299249A1.

[0192] Additional additives, such as warming agents, cooling agents, tingling agents, flavors, sweeteners, sour tastes, bitter tastes, salty tastes, surfactants, breath-freshening agents, anti-microbial agents, anti-bacterial agents, anti-calculus agents, antiplaque agents, fluoride compounds, remineralization agents, pharmaceuticals, micronutrients, throat care actives, tooth whitening agents, energy boosting agents, concentration boosting agents, appetite suppressants, colors and others may also be included in any or all portions of the contemplated compositions, including but not limited to those mentioned in US20080299249A1. Such additives may be used in amounts sufficient to achieve their intended effects. In further embodiments, these additional additives may further contribute to the palatability of the composition, either by further adding noticeable flavors or qualities, or by further masking the taste of triacetin.

[0193] It is additionally contemplated that administering the composition to a subject may cause a significant amount of triacetin to reach the lower GI and colon more effectively than a second composition comprising a short chain fatty acid. For example, tributyrin, a supplement which releases butyric acid— another SCFA— in the gut upon ingestion, is one example of a second composition comprising a SCFA. The inventor contemplates that the disclosed composition effectively reaches the colon and releases SCFAs in the colon far more effectively than tributyrin or any other second composition. For example, it is contemplated that for every dosage of the composition administered to the subject, at least 50%, or at least 60%, or at least 70%, or at least 80% of the triacetin in the administered dose will reach the lower GI tract. The inventor also contemplates that the disclosed compositions uniquely achieve this release in the lower GI and colon while also being palatable.

[0194] The inventor also contemplates that the compositions disclosed may further comprise a pH modifier. For example, citric acid, sodium bicarbonate, hydrochloric acid,sodium hydroxide, lactic acid, potassium hydroxide, phosphoric acid, calcium carbonate, ammonium hydroxide, and / or any other pH modifiers may be incorporated into the compositions to adjust acidity or alkalinity levels in the gut or elsewhere in the body.

[0195] It is further contemplated that the introduction of acetic acid through triacetin into the gut induces further production of acetic acid and / or other short-chain fatty acids, creating a positive feedback loop.

[0196] As discussed throughout this application, although SCFA-containing supplements and nutrients are commercially available, they come with challenges. For example, US5919822A discloses clinical nutrition compositions comprising short chain fatty acid (SCFA)-containing lipids, including triglycerides (triacylglycerols) in which the fatty acid moieties may be short chain carboxylic acids such as acetate, propionate, or butyrate. US5919822A discusses compounds where glycerol is esterified with three acetate groups, as well as other triglycerides that, upon hydrolysis, yield SCFAs. However, the description of compositions in US5919822A do not specify dilution levels for triacetin or address palatability or taste-masking strategies. As such, these compositions are likely to taste offensive, potentially resulting in the need for administration methods other than ingestion.

[0197] Remarkably, the present invention overcomes these challenges as it is directed to formulations wherein triacetin is administered at a specific dilution, ideally within the range of 100-1000 mg / oz to 100-1000 mg / 8 oz, optimized to both deliver SCFAs effectively to the lower gastrointestinal tract and to enhance palatability by facilitating taste masking. Unlike US5919822A, which does not address taste or dilution for flavor masking, the present disclosure provides a unique approach to SCFA delivery that is particularly suitable for oral, RTM, and RTD administration where patient / subject compliance and sensory acceptability are critical.

[0198] Additionally, the disclosure of WO2019217907A1 discusses the treatment and prevention of metabolic diseases by modulating metabolic pathways through the administration of various metabolism-enhancing agents, including short-chain fatty acids (SCFAs) such as butyrate, propionate, and valerate, as well as agents that promote endogenous SCFA production in the gut (e.g., prebiotics, probiotics, or SCFA prodrugs like tributyrin). While WO2019217907A1 recognizes the therapeutic benefit of increasing SCFA levels in the gut, it does not disclose or suggest the use of triacetin as a direct, palatable, and precisely dosed SCFAprecursor for human consumption, nor does it address the formulation challenges associated with palatability and consumer acceptance.

[0199] In contrast, the present invention provides a method of increasing gut SCFA concentrations by administering a composition comprising triacetin at a defined concentration (such as 100-1000 mg per 1-8 oz of the composition), wherein the composition is specifically formulated to be palatable by inclusion of a flavorant. This approach directly overcomes the limitations of prior art, such as WO2019217907A1, which does not teach or enable the use of triacetin in a consumer-friendly, palatable beverage or food matrix. The present invention thus provides significant advantages in terms of dosing precision, consumer compliance, and product acceptability, which are not addressed or achieved by the approaches disclosed in WO2019217907A1. Furthermore, the instant invention enables convenient, scalable, and pleasant administration of SCFA precursors, thereby facilitating broader adoption and improved outcomes in the management of metabolic health.

[0200] Various other compositions known in the art use tri acetin as a plasticizer rather than as an active ingredient. For example, see EP2560660A1, AU2010239311B2, and EP3179983 Al, all of which use triacetin merely as a plasticizer. It is noted that while tributyrin has long been used as a supplement for supporting gut health, triacetin is primarily used as a mere plasticizer or humectant in the art. For example, the Wikipedia site for triacetin describes the uses of triacetin, explaining that “[i]t is used as an excipient in pharmaceutical products, where it is used as a humectant, a plasticizer, and as a solvent.” It is noted that the use of triacetin as the sole active ingredient to both increase SCFA levels in the gut and to solve the problem of palatability is unexpected in view of the known uses of triacetin in the art.Aspect 2: Unexpected SCFA Increase (>10%) With Low Gas Production

[0201] In addition to the compositions and methods noted above, the inventor has unexpectedly discovered that, upon orally administering a contemplated composition comprising triacetin to a dysbiotic subject, the total SCFA production in the gut of the subject exceeded the theoretical SCFA production that would be expected based on the amount of acetate released from the administered triacetin. This unexpectedly high SCFA stimulation by triacetin even significantly surpassed stimulation by inulin on a normalized mass basis. Thus, and in one embodiment of the contemplated subject matter, the inventor contemplates various compositions and methods of increasing the concentration of SCFAs, and particularly aceticacid and butyric acid, in the gut of a subject by administering to the subject a composition comprising triacetin. In at least some embodiments, the individual is a dysbiotic subject. And in a further embodiment, the inventor contemplates compositions and methods of increasing the concentration of SCFAs beyond a theoretical amount of SCFAs, wherein the theoretical amount is the number SCFAs esterified within the triacetin.

[0202] In other embodiments of the presently disclosed invention, the inventor contemplates a method of increasing a concentration of short chain fatty acids (SCFAs) in a gut of a dysbiotic subject without substantially increasing gas production in the dysbiotic subject, comprising the steps of orally administering to the subject a composition comprising triacetin in combination with a pharmaceutically or nutritionally acceptable carrier, wherein the composition is administered in an amount effective to increase the concentration of SCFAs in the gut by at least 10% as compared to the concentration of SCFAs in the gut without administration of the composition.

[0203] For example, in some embodiments, the triacetin amount effective to increase SCFAs by at least 10% may be a beverage concentration of about 100-1000 mg per 1-8 fl oz (e.g., an 8-oz serving containing about 100-1000 mg triacetin). In another embodiment, the amount effective to increase SCFAs by at least 10% is 50-500 mg triacetin per dosage, wherein a dosage is 1-20 oz. In further embodiments, the amount effective to increase SCFAs by at least 10% is 50-500 mg, 250-1000 mg, 800-2000 mg, 1500-5000 mg, 4000-8000 mg, 6000-12,000 mg, 10,000-25,000 mg, 20,000-40,000 mg, or even 35,000-70,000 mg per dosage. The particular amount in some embodiments may be selected based on palatability. In certain embodiments, the amount effective to increase SCFAs by 10% is 400 mg oral ingestion (supported by ex vivo IBS-microbiome data discussed in Experimental Data showing robust acetate and butyrate increases with low gas). However, it should be appreciated that any other formulation containing amounts of triacetin effective to increase SCFA concentration in the gut by at least 10% as compared to the concentration of SCFAs in the gut without administration of the composition. Triacetin may be the sole active ingredient, or triacetin may be used in combination with optional actives (e.g., tributyrin), provided the administered amount is sufficient to achieve at least a 10% increase.

[0204] In further embodiments, administration of the compositions disclosed herein may increase the concentration of SCFAs by at least 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or 50% as compared to the concentration of SCFAs in the gut without administration of thecomposition. The particular percentage of increase may depend on the concentration of triacetin administered, and / or the frequency of administration.

[0205] In additional embodiments, administration of the compositions disclosed herein may cause gas production and / or bloating to not increase by more than 10%, 20%, 30%, 40% or 50% relative to gas production and / or bloating in a dysbiotic gut without administration, or a healthy gut without administration. In further embodiments, administration of the compositions disclosed herein may cause gas production and / or bloating to not increase by more than 10%, 20%, 30%, 40% or 50% relative to a dysbiotic gut or a healthy gut with administration of tributyrin, mushroom blend, and / or inulin. It is noted that gas production may be measured using a method according to the experiments described herein. For example, and in some embodiments, gas production may be measured by connecting a pressure meter to an inserted needle and measuring headspace pressure in millibar, optionally at 24h of anaerobic incubation of a sample. In further aspects, gas production may be measured as gas production per mole of total SCFA generated (mbar / mM). Gas production can also be measured as absolute gas (mbar) as a function of SCFA (mM) for tolerability profiling as shown in FIG.6B, FIG.20B, or FIG. 64B. However, it should be appreciated that other methods can be used as alternatives or supplementary measurements, such as gas composition analysis from reactor headspace using gas chromatography or mass spectrometry, breath tests for H2 and CH4, ingestible gas-sensing capsules that measure intraluminal gas concentrations, imaging-based measurement such as abdominal MRI or CT, patient-reported outcomes, measuring related biomarkers, or any other suitable method. Bloating, in some aspects, is considered to be a function of gas production.

[0206] As will be readily appreciated, such benefits are particularly desirable for individuals with inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), or other inflammatory or metabolic dysbiosis as butyrate and acetate levels can be significantly boosted without excessive gas production and bloating.

[0207] For example, and as detailed and evidenced through data in FIG. 2 and FIG. 6 and discussed throughout the Experimental Data section below, the administration of a composition comprising triacetin to a subject significantly increased the levels of both acetic acid and butyric acid in the gut while only minimally producing gas in the microbiome of subjects with inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), or other inflammatory or metabolic dysbiosis. Indeed, when SCFA production was plotted against gas production, gasproduction was comparable to the untreated control while total SCFA production was significantly and substantially increased as is shown in more detail in the data in FIG. 6-7.Moreover, contemplated compositions also exhibited a significant decrease in TNF-a in a hostmicrobiome interaction assay as is also shown in more detail in FIG. 7.

[0208] In another embodiment, the inventor contemplates a method of increasing a concentration of short chain fatty acids (SCFAs) in a gut of a dysbiotic subject without substantially increasing gas production in the dysbiotic subject, comprising the steps of orally administering to the subject a composition comprising triacetin in combination with a pharmaceutically or nutritionally acceptable carrier, wherein the composition acts as a prebiotic, probiotic, and a postbiotic after administration. For example, the composition may comprise, in addition to triacetin, bacteria such as Lactobacillus, Bifidobacterium, and / or any other bacteria described herein. In additional embodiments, the composition may further comprise tributyrin. The composition in other embodiments may further comprise akkermansia muciniphila, a probiotic that supports the gut barrier, encourages healthy weight management, and has been shown to increase natural GLP-1 production. In yet further embodiments, the composition may further comprise Inavea™ prebiotic fiber (organic baobab pulp, organic acacia seyal gum).EXPERIMENTAL DATA

[0209] Exemplary experiments were conducted with the aim of deciphering the microbiome-modulating potential of triacetin (TA, TriBiome™) and a mushroom blend (MB, Hblistiq™) when dosed the microbiome of Irritable Bowel Syndrome (IBS) subjects, using the ex vivo SIFR® technology. IBS is a common gastrointestinal disorder, characterized by abdominal pain, altered bowel habits (diarrhea and / or constipation) and a dysbiosis of the gut microbiome. This dysbiosis is difficult to restore via fiber supplementation, which typically promotes gas production, potentially worsening IBS symptoms. It is contemplated that two novel products, triacetin (including but not limited to the composition of TriBiome™) and a mushroom blend (Hblistiq™), modulate the microbiome of IBS subjects (n = 8), confirmed by the ex vivo SIFR® (Systemic Intestinal Fermentation Research) technology combined with a co-culture of epithelial / immune (Caco-2 / THP-l) cells.

[0210] As will be discussed in further detail, first, the IBS microbiomes revealed large interpersonal variability and an IBS-associated dysbiosis. TA increased the beneficialmetabolites acetate and butyrate (~ Anaerobutyricum soehngenii, Mediterraneibacter _A butyricigenes, Faecalibacterium prausnitzii). Besides, MB stimulated a larger number of gut microbes and additionally promoted propionate.

[0211] Despite more strongly increasing total SCFA levels, TA induced significantly less gas production than MB. Mechanistically, acetate with TA was derived from hydrolysis, a process that indeed does not induce gas production. Notably, both TA and MB enhanced gut barrier integrity (TEER), which is related to lower symptom severity in IBS patients. Overall, the exemplary experiments described herein highlight the product-specific microbiome modulation and potential of MB, TA or combinations thereof as dietary interventions for managing IBS symptom severity.

[0212] To study the microbiome-modulating effect of TA and MB for IBS subjects ex vivo, fresh fecal samples eight IBS subjects were collected. Subjects with both IBS-M (mixed type) and IBS-D (diarrhea type) were included. They additionally complied with following criteria: age 30-65, no antibiotic / probiotic intake in 3 months prior to study, no other gastro-intestinal disorders (cancer, ulcers, IBD) and 20 < body mass index < 25. This resulted in the enrolment of 8 specific IBS subjects with an average age of 42.8 (± 6.8) years. To understand whether the microbiomes of these IBS subjects displayed an IBS -associated dysbiosis, fecal microbiota of healthy human adults were sourced. These healthy adults complied with the same criteria as the IBS subjects (except that they did not suffer from IBS-M or IBS-D). The healthy subjects had an average age of 38.0 (± 4.3) years. The gut microbiome plays a crucial role in human health, amongst others, by producing short-chain fatty acids (SCFAs) from glycans.

[0213] The main SCFAs are acetate, propionate and butyrate, which each have specific benefits. Disruptions in the microbiome are associated with diseases like IBS, one of the most common gastrointestinal disorders. Key symptoms of IBS are abdominal pain or discomfort and altered bowel habits, i.e. diarrhea (IBS-D), constipation (IBS-C) or a mix thereof (IBS-M). It is contemplated that fecal microbiome transplantation from a healthy donor to IBS subjects improves symptom scores. As IBS -associated microbial dysbiosis (especially IBS-D) is linked to a depletion of butyrate-producing microbes, restoring butyrate production seems a promising strategy. Mechanistically, butyrate could restore gut barrier integrity, which is relevant in IBS given that IBS patients suffer from an impaired barrier integrity that is linked to symptom severity.

[0214] The simulated upper gastrointestinal tract passage of TA was performed as described before. Briefly, TA, both as such and upon encapsulation, was exposed to an oral, gastric and small intestinal phase, during which digestive secretions were sequentially added. Samples were collected at the end of each phase and analyzed for SCFA content to assess the potential release of the SCFA acetate from TA. As acetate released along the upper gastrointestinal tract would get absorbed in vivo, it was important to accurately estimate colonic delivery of TA (= intact TA fraction at the end of the upper gastrointestinal tract = 100% -measured free acetate level at end of upper gastrointestinal tract / theoretically dosed acetate as part of TA). Doing so, a biorelevant (non-digestible) fraction of the oral TA dose could be administered at the colonic incubations.

[0215] Colonic fermentations were performed as described before. Briefly, bioreactors containing 5mL of a blend of nutritional medium (M0028, Cryptobiotix, Ghent, Belgium), fecal IBS microbiota and a specific test product (TA or MB) were rendered anaerobic using a bioreactor management device (Cryptobiotix, Ghent, Belgium) and incubated under constant agitation (140 rpm) at 37°C (MaxQ 6000, Thermo Scientific, Merelbeke, Belgium).

[0216] The study consisted of three arms that were each assessed for eight individual IBS subjects (n = 8). This included the unsupplemented control (no substrate control; NSC), triacetin (TA; TriBiome™, Compound Solutions, Carlsbad, USA) and a mushroom blend (MB; Hblistiq™, Compound Solutions, Carlsbad, US) (FIG. 1A). In contrast to the products that were tested in n = 1 for each IBS subject, the NSC arm was run in n = 3 for each subject to confirm the high technical reproducibility of the SIFR® technology. TA was tested at a dose simulating the oral ingestion of 400 mg TA as part of a capsule. MB was tested at a daily dose of 1000 mg and consisted of 50% Cordyceps militaris, 30% Ganoderma lucidum (Reishi), 5% Hericium erinaceus (Lion’s mane), 5% Lentinula edodes (Shiitake), 5% Pleurotus eryngii (King trumpet) and 5% Tramates versicolor (Turkey tail).

[0217] After 24h of incubation, gas pressure was measured in the headspace of reactors and liquid samples were collected for assessment of key fermentative parameters (pH, gas and SCFA production), microbial composition and host microbiome interactions (FIG. IB).Treatment effects of TA and MB were established by comparing the study arms treated with TA / MB to the NSC study arm. Indeed, the latter (NSC) involved growing the IBS microbiomes under identical conditions, except without TA / MB supplementation.

[0218] SCFA (acetate, propionate and butyrate) were determined via gas chromatography with flame ionization detection, as previously described. Briefly, samples were diluted, acidified, supplemented with sodium chloride and internal standard and extracted with diethyl ether. Extracts were analyzed using a Trace 1300 chromatograph equipped with a Stabilwax-DA capillary GC column, a flame ionization detector, and a split injector using nitrogen gas as the carrier and makeup gas. Finally, pH was measured using an electrode.

[0219] Microbial composition was analyzed via quantitative 16S rRNA gene profiling targeting the V3-V4 region. Briefly, cell densities per individual operational taxonomic unit (OTU) were estimated by multiplying relative abundances (%) obtained via 16S rRNA gene sequencing with total cell numbers of each sample (cells / mL; flow cytometry). First, DNA was extracted via the SPINeasy DNA Kit for Soil (MP Biomedicals, Eschwege, Germany). Subsequently, library preparation and sequencing were performed on an Illumina MiSeq platform with v3 chemistry (2x300bp). Amplicons were generated via the primers 341F and 785Rmod. Pre-processing and OTU picking was performed with Mothur v1.35.1, including annotation of representative sequences with NCBI blast v2.10.0. Total cell numbers were quantified by diluting samples in PBS, stain-ing cells with SYTO 16 and counting them via a Novocyte flow cytometer (Agilent, Santa Clara, US).

[0220] To study the impact of colonic samples (upon TA / MB treatment) on host cells, a coculture experiment with epithelial cells (human adenocarcinoma Caco-2 cell line) and immune cells (human acute monocytic leukemia THP1 cell line, differentiated to activated macrophages by a PMA treatment) was performed, as previously described. Briefly, the gut wall was created by covering immune cells with an epithelial layer. The host-microbiome interaction assay had two phases: (i) 24 h treatment with colonic samples to evaluate gut barrier integrity under unstressed conditions, and (ii) 6h additional incubation with lipopolysaccharide (LPS) to evaluate effects under stressed conditions. Colonic samples were centrifuged and filter sterilized before use in the assay. Transepithelial electrical resistance (TEER) measured gut barrier integrity at 0 h, 24 h, and 30 h. Immune effects at 3 Oh were studied via cytokine / chemokine production using a Multiplex Luminex® Assay kit on the MAGPix® analyzer (IL-6, IL-10, TNF-a).

[0221] Data analysis was performed using R (version 4.4.0). Statistical analysis was conducted using a linear mixed-effects model, which accounted for both fixed effects (treatment) and random effects (interpersonal variation). The Benjamini -Hochberg correctionwas applied to control the false discovery rate across parameters. Effects of TA or MB compared to the reference (NSC) were assessed via a post hoc pairwise comparison, again with Benjamini -Hochberg correction of - values. Effects were significant at padjusted < 0.05. In the violin plots, statistical differences between TA or MB and the NSC are indicated with * (0.01 < Padjusted < 0.05), ** (0.001 < Padjusted < 0.01) or *** (padjusted < 0.001), while differences between TA and MB are indicated with $ / $$ / $$$. Finally, pairwise correlation analysis using Spearman’s rank correlation coefficient was performed between SCFA and absolute levels of different OTUs.

[0222] The stimulation of SCFA such as butyrate is usually achieved by consumption of dietary fibers. Pathways involved in the production of SCFA, particularly butyrate, typically involve the production of gases such as H2 and CO2. This is problematic for IBS patients that are often on low FODMAP diet, i.e. a diet low in fermentable oligosaccharides, disaccharides, monosaccharides and polyols, in an attempt to minimize colonic gas production and associated discomfort. An additional issue is that the outcome of colonic fermentation of fibers can be prone to large interpersonal differences, which cause unpredictable treatment outcomes. There is thus a need to develop products that promote SCFA production, in particular butyrate, without causing intestinal discomfort.

[0223] While clinical studies are essential to demonstrate health benefits, they are ill-suited to gain mechanistic insights into microbiome modulation. First, metabolites such as SCFA are readily absorbed, rendering fecal samples non-informative on metabolite production in the colon. In addition, fecal microbiome composition is confounded by multiple factors that altogether cause great heterogeneity in microbiota profiles, thus obscuring insights in true associations with interventions or diseases. The ex vivo SIFR® technology (Systemic Intestinal Fermentation Research) that employs high-throughput, reactor-based simulations of the gut microbiome, was recently introduced to overcome such limitations. The technology was validated to provide predictive insights for clinical studies, not only in terms of microbiome modulation but also for effects on barrier integrity and immune modulation. Such clinical predictivity stems from the ability of the technology to cultivate microbiomes in a way that they still highly resemble the original in vivo microbiome, a distinctive feature compared to legacy in vitro gut models. In doing the experiments described herein, the aim was to evaluate whether two novel products with unknown microbiome-modulating potential, triacetin (TA; triacyl glyceride of acetate; including but not limited to the composition of TriBiome™) and amushroom blend (MB; a new fibre source (Holistiq™)), impact the IBS microbiome, using the ex vivo SIFR® technology.

[0224] Notably, and as discussed further below, TA and MB restored butyrate production, each via different pathways. A unique effect of TA was that it induced low gas production, while MB uniquely promoted propionate production and microbial diversity. A key finding was that both TA and MB enhanced gut barrier integrity, suggesting that both products are promising therapeutic agents to improve IBS-related disease symptoms.

[0225] The following results especially substantiate the embodiments of Aspect 2; however, the formulations and examples evaluated herein also inform and support the palatable triacetin compositions of Aspect 1 and are incorporated by reference into Aspect 1 embodiments. The Experimental Data and examples described herein are presented to illustrate particular embodiments of the invention and are not intended to define or limit the scope of the claimed invention. Variations and equivalents of the examples provided will be apparent to those skilled in the art and are within the scope of the invention.1.1: The IBS microbiome displayed large interpersonal differences and an IBS- associated dysbiosis.

[0226] The fecal microbiomes of the IBS subjects, used to assess the microbiomemodulating potential of TA and MB, displayed large interpersonal differences (FIG. 1A). First, Bifidobacteriaceae ranged from virtually absent (subjects 2 / 6 / 7), over 2-3% (subjects 3 / 5) and 5-10% (subjects 1 / 4) up to 30% of the microbiota for subject 8, whose microbiota was in contrast depleted from Ruminococcaceae (e.g., Faecalibacterium, Gem-65 miger). Besides, Bacteroidaceae genera (Phocaeicola and / or Bacler aides) were highly abundant for subjects 3 / 4 / 7Z8. Covering such large interpersonal differences is essential to obtain representative insights into the microbiome-modulating potential of interventions.

[0227] The relevance of the IBS cohort was further confirmed by the observation of an IBS-specific phenotype compared to healthy adults (FIG. IB). Indeed, the IBS microbiota was enriched with OTUs related to Blautia K wexlerae. Blautia faecis and Mediterraneibacter gnavus (formerly Ruminococcus gnavus), at the expense of Bacillota (formerly Firmicutes) OTUs including Bariatricus comes (formerly Coprococcus comes). Notably, Bifidobacterium species colonized the microbiota of healthy subjects more consistently compared to IBS subjects, with abundances ranging from 1.6 - 5.6% (FIG. 1A).

[0228] FIG. 1 depicts results showing that the fecal microbiota of IBS subjects displayed marked interpersonal differences and relevant differences compared to a healthy cohort. (A) Abundances (%) of the most abundant genera for each IBS subject (subjects 1-8) and healthy adult (subjects 9-16). (B) Linear discriminant analysis effect size (LEfSe) showing the taxa that explained dif-78 ferences between both cohorts (p < 0.05).1.2: Encapsulation enhances colonic delivery of TA.

[0229] To apply a relevant TA dose in the colon, the stability of TA along the upper gastrointestinal tract was first assessed. When dosed as such, a cumulative acetate release of 33.8% (± 0.3%) was noted along the upper gastrointestinal tract, implying that 66.2% of TA escaped digestion. Upon encapsulation, the cumulative acetate release at the end of the small intestinal phase was 10.8% (± 0.9%). This demonstrates that encapsulation improves colonic delivery of TA to 89.2%. The subsequent study focusing on how TA impacts the colonic microbiome simulated this scenario in which TA is encapsulated (= 89.2% of the oral TA dose was administered at the start of the colonic phase).1.3. 7 1 and MB boosted SCFA, which was accompanied by only low gas production for TA.

[0230] TA and MB significantly lowered colonic pH, increasing gas production and total SCFA levels (FIG. 2A, B, C). Notable product-specific effects were that while TA more specifically increased acetate and butyrate, MB significantly increased all three main SCFA (also propionate) (FIG. 2D, E, F). Moreover, while TA increased acetate and total SCFA significantly stronger than MB, gas production was significantly lower with TA. This remarkably low gas production with TA was further stressed when calculating the ratio of gas production per mole of SCFA being generated: unlike MB, TA markedly and significantly decreased this ratio (FIG. 6).

[0231] FIG. 2 depicts data showing TA and MB boosted SCFA levels in a product-specific manner with remarkably low gas production for TA. The impact on (A) pH, (B) gas production (mbar), (C) total SCFA (mM), (D) acetate (mM), (E) propionate (mM) 98 and (F) butyrate (mM).1.4: 7'1 and MB each enhanced the growth of specific SCFA-producing gut microbes

[0232] The product-specific effects on SCFA levels were confirmed by product-specific effects on microbial composition, further corroborating how TA and MB each trigger specific microbial pathways in the colon. TA specifically increased a consortium of Lachnospiraceae members, with particularly strong effects on OTUs related to Anaerobutyricum soehngenii and Mediterraneibacter A butyricigenes (FIG. 3B). MB stimulated a broader range of OTUs related to species not only belonging to the Lachnospiraceae (e.g. Bariatricus, Coprococcus and Butyribacter species) but also to the Bifidobacteriaceae (e.g. Bifidobacterium adolescentis) and Bacteroidaceae families (e.g. Phocaeicola dorei and Bacteroides uniformis). The involvement of a larger number of taxa in the fermentation of MB was in line with the finding that MB specifically increased microbia diversity as quantified by the community modulation score (CMS) (FIG. 3A).

[0233] Finally, strong correlations between butyrate levels and two specific species were noted, suggesting the involvement of these species, Mediterraneibacter A butyricigenes (upon TA treatment) and Faecal ibacterium prausnitzii (upon TA and MB treatment), in the production of butyrate (FIG. 3C). For F. prausnitzii, this was not captured by the statistical analysis of treatment effects due to the large interpersonal differences in baseline levels of F. prausnitzii among IBS subjects. Nevertheless, its strong correlation with butyrate confirmed that F. prausnitzii is a key driver of butyrate production during microbial fermentation of TA and MB in the colon.

[0234] FIG. 3 depicts data showing that TA and MB each enhanced the growth of specific SCFA-producing gut microbes. The impact on (A) microbial diversity (community modulation score (CMS)), and (B) OTUs that were significantly affected (padjusted < 0.05), expressed as log2 transformation of the ratio of abundance treatment / abundance NSC, averaged across all 8 IBS subjects. Hence, values > 0 reflect a stimulation by TA / MB, while values < 0 indicate an inhibition by TA / MB. Bars highlighted by a black outline indicate a statistically significant increase / decrease. (C) Individual correlations between butyrate (mM) and specific OTUs based on Spearman’s rank correlation coefficient.1.5: 7'1 and MB promoted gut barrier integrity under non-stressed and stressed conditions.

[0235] The stimulation of beneficial SCFA by specific gut microbes translated into strong and significant increases of gut barrier integrity (TEER) upon treatment with TA and MB, bothunder non-stressed and stressed conditions (FIG. 5A, B) MB tended to increase barrier integrity more strongly, especially under non-stressed conditions. Further, both TA and MB tended to lower the production of the pro-inflammatory cytokine TNF-a, while exerting rather neutral effects on IL-6 and IL- 10 (FIG. 7).

[0236] Additionally, FIG. 4 depicts data showing that TA and MB promoted epithelial gut barrier integrity, both under non-stressed and stressed conditions. The host-microbiome interaction assay assessed barrier integrity (TEER, normalized to 0 h) under (A) unstressed (24 h) and (B) stressed conditions (30 h = additional 6h LPS treatment). References included cell medium (blank), LPS treatment (between 24-30h; LPS) and its co-supplementation of dexamethasone (D) or hydrocortisone (H). The control to evaluate potential significance of treatment effects (= NSC) involved a study arm in which the IBS microbiota was cultured in the ex vivo SIFR® technology in absence of any treatment.1.6: Additional Findings

[0237] It is further noted that FIG. 5 depicts informational material regarding how the impact of TA and MB on the gut microbiota of IBS subjects was assessed using the ex vivo SIFR® 255 technology (n = 8). (A) Experimental configuration, (B) timeline and analysis.

[0238] FIG. 6 depicts data showing that the strong increase in SCFA levels with TA was accompanied by only mild increases in gas production. (A) 2 Ratio of gas production per mole of SCFA being produced (mbar / mM). (B) Absolute gas production (mbar) in function of 3 total SCFA production (mM).

[0239] FIG. 7 depicts data showing that TA and MB tended to lower TNF-a, while exerting neutral effects on IL-6 and IL-10. The host-microbiome 7 interaction assay assessed (A) TNF-a, (B) IL-6, (C) IL-10 at 30h, i.e. upon 24h of interaction between test products and the 8 human cells, followed by LPS treatment for an additional 6h period. References included cell medium alone (blank), LPS 9 treatment alone (between 24-48h) and co-supplementation of dexamethasone (D) or hydrocortisone (H). The control to evaluate potential significance of treatment effects (= NSC) involved a study arm in which the IBS microbiota was cultured over 24h in the ex vivo SIFR® technology in absence of any treatment.

[0240] FIG. 8 depicts data showing that TA and MB did not impact traditional microbial diversity indices. The impact on (A) the Chaol diversity index, (B) Shannon diversity index and (C) reciprocal Simpson diversity index.

[0241] The results described above in Results 1.1 to 1.5 revealed important information related to the microbiome-modulating potential of triacetin (TA) and a mushroom blend (MB) when dosed the microbiome of IBS subjects, using the ex vivo SIFR® technology.1.7: Discussion of Experimental Data

[0242] In these exemplary experiments, the use of representative IBS microbiota ensured representative findings on the microbiome-modulating potential of both products (TA and MB): the relevance of the IBS cohort followed from the large interpersonal differences that were covered along with the observation of an IBS-specific phenotype. IBS microbiota was particularly enriched with OTUs related to Blautia species and Mediterraneibacter gnavus, a species that was shown to have a pathogenic role in diarrhea-predominant IBS.

[0243] In addition, a subject-specific depletion of Ruminococcaceae was noted. A key finding of the current study is that TA and MB strongly promoted gut barrier integrity, the hallmark of gut health in general, yet particularly relevant in IBS, where enhanced barrier integrity has been linked to lower symptom severity. Notably, TA and MB exerted this beneficial effect through product-specific modulation of the gut microbiome.

[0244] Both TA and MB enhanced the SCFA butyrate, which has been shown to promote gut barrier integrity. While the impact on butyrate and barrier integrity was similar for TA and MB, the underlying processes differed. TA specifically increased the butyrate producers Mediterraneibacter A butyricigenes and Anaerobutyricum soehngenii, while MB rather increased Bariatricus, Coprococcus, and Butyribacter species.

[0245] Additionally, both MB and TA stimulated Faecalibacterium prausnitzii. a species shown to exert beneficial effects via butyrate and the production of anti-inflammatory peptides. Another example of how these buty rate-producing gut microbes could contribute to health benefits is that Anaerobutyricum soehngenii is linked with metabolic health, particularly in obese and insulin-resistant individuals. This aligns with observations that TA decreased de novo lipogenesis and, in doing so, lowered weight gain in an animal model of diet-induced obesity.

[0246] These findings altogether suggest that TA and MB can promote butyrogenic members of the gut microbiome, thus restoring the IBS-associated dysbiosis characterized by a depletion in such microbes. Moreover, the stimulation of butyrate upon TA and MB is likely a key mechanism by which MB and TA promote barrier integrity that contributes to lower symptom severity in IBS.

[0247] A notable observation for TA was that its strong increase in SCFA levels was accompanied by only low gas production. This is of interest as previous research in the field has focused on identifying treatments that attenuate gas production upon fiber consumption, aiming at providing benefits via SCFA while minimizing discomfort for IBS patients. Mechanistically, the low gas production with TA is explained by the hydrolysis of TA, which directly releases glycerol and up to three molecules of acetate without yielding gases that are typically produced when gut microbes ferment fibers into SCFA.

[0248] While subsequent acetate-into-butyrate cross-feeding interactions noted for TA did yield gases likely including CO2 and H2, overall gas production with TA was thus attenuated. Another remarkable finding was that the experimentally observed increases of acetate and butyrate exceeded the theoretically dosed amounts of acetate (as part of TA), i.e., 123.2% of carbon was recovered (91.5% as acetate, 31.7% as butyrate). This suggests that additional synergistic interactions take place, potentially including that TA lowers colonic pH, thus favoring growth of butyrate producers over other gut microbes. In addition, part of the carbon atoms could be derived from fermentation of the glycerol backbone. Overall, this suggests that TA is an effective product for delivering SCFA to the body without causing gas-related discomfort.

[0249] A notable product-specific effect of MB was that it also increased propionate production, mediated via B. uniformis and P. dorei. Bacteroides and Phocaeicola species commonly utilize the succinate pathway to convert succinate into propionate. Beneficial effects of propionate include promoting satiety, lowering blood cholesterol, and improving insulin sensitivity. Further, MB uniquely promoted Bifidobacteriaceae, another family containing distinct health-related members of the gut microbiome. The involvement of these taxa in the fermentation of MB aligns with earlier studies with mushrooms and likely relates to fiber constituents of mushrooms such as chitin, P-glucan, and hemicellulose. Compared to TA, the fermentation of MB involved a larger spectrum of gut microbes, causing MB to increase microbial diversity, as assessed with the community modulation score.1.8: Triacetin Compared to Additional Test Products

[0250] In other embodiments, the inventor has discovered a variety of unexpected results when testing and comparing a series of test products including triacetin (TA), tributyrin (TB), TA / TB mixes, lysine-butyrate (LB), fulvic acid (FA), spermidine (SP) and a mushroom blend (MB) on the gut microbiota of IBS patients.

[0251] For example, and in one embodiment, it is contemplated that in IBS patients, more than 70%, more than 75%, more than 85%, more than 88%, more than 89%, or more than 90% TA escapes small intestinal digestion and thus reaches the colon, while a mere 28.5% TB and 3.3% LB reach the colon. Therefore, it is contemplated that triacetin reaches the colon at least 38%, at least 40%, at least 45%, or at least 50% more effectively than TB and LB.

[0252] It is further contemplated that, in some embodiments, after 24h of colonic incubation, several product-specific effects will be observed. See FIG. 9. For example, for subjects administered TA, at least 70-90% of the theoretical value of acetate administered to the subject will be absorbed to the colon, but even more surprisingly, a vast increase in butyrate producers will be observed, including but not limited to Faecalibacterium prausnitzii. Anaerobutyricum soehngenii as well as Mediterraneibacter A butyricigenes. As a result, the concentration of butyrate in the colon is significantly increased in addition to acetate, despite triacetin being the sole active ingredient administered to the subject. This unexpected result may be a result of the glycerol backbone of triacetin being fermented by SCFA-producing gut microbiota in addition to acetate.

[0253] In contrast, for subjects administered TB, only approximately 52.6% of the theoretical value of butyrate is absorbed to the colon. In addition, TB administration will not cause a significant increase in acetate, propionate, or other SCFAs.

[0254] The inventor additionally contemplates that, in certain embodiments, a TA+TB mixture may be administered to a subject. The TA+TB mixture is contemplated to exert effect in line with the presence of TA and TB, such that the higher TA content is, the stronger the TA-related effects will be. Metabolomics analysis may be used to observe impact of TA and TB on a small number of metabolites, i.e., decreasing the levels of tryptophol and increasing the production of 3 -methylhistidine. Further, in some embodiments, TA also specifically increases the levels of 8-valerolactone in a dose-dependent manner.

[0255] MB is contemplated to increase microbial diversity significantly, such as by increasing or stimulating SCFA products like Bifidobacterium adolescentis and B. longum (which increase acetate), Bacteroidota OTUs related to Phocaeicola dorei. Bacteroides uniformis. Bacleroidescaccae. Parabacteroides distasonis, and Lachnospiraceae OTUs related to Coprococcus A catus (which increase propionate), and F. prausnilzii. Anaerostipes hadrus, Anaerobutyricum soehngenii. Butyricibacter sp., and Lacrimispora sp. (which increase butyrate). However, as shown in the Experimental Data and FIG. 2 and FIG. 6, MB results in a significantly high gas production.

[0256] LB is contemplated to mildly increase butyrate and have a minor impact on acetate. SP and FA are contemplated to contribute the least to SCFA production in the colon, even decreasing acetate, butyrate, and especially propionate concentrations in the colon.

[0257] In some embodiments, it is further contemplated that host-microbiota interaction assays will reveal that the production of health-related metabolites by specific microbes translated in beneficial effects on host cells for the test products. For example, gut barrier integrity is contemplated to be increased by MB, TA, and TB (MB> TA> TB), both under nonstressed (no LPS) and stressed (+ LPS) conditions, positively correlated with acetate and butyrate production. See FIG. 10. Further, all test products are contemplated to decrease pro-inflammatory TNF-a, except TB. Further, pro-inflammatory CXCL-10 is contemplated to decrease from treatment by any of the test products, except TB / MB.

[0258] While tributyrin’s primary mode of action solely involves hydrolysis and release of butyrate, triacetin and mushroom blend are contemplated to also undergo fermentation by the IBS gut microbiome, thus particularly profoundly impacting microbial composition and promoting cross-feeding to induce SCFA production.

[0259] As will become readily apparent from the following description, the underlying experimental procedures and methodologies provide further context for the exemplary results summarized above. The following sections detail exemplary materials, methods, and data that demonstrate certain aspects of the invention. It should be understood that these examples are provided for illustrative purposes only and are not intended to limit the scope of the present disclosure. Variations, modifications, and equivalents may be employed without departing from the spirit and broader inventive concepts described herein.

[0260] SIFR® (Systemic Intestinal Fermentation Research) is a technology used herein which addresses operational and analytical bottlenecks to increase experimental throughput, while continuously ameliorating biorelevance, making it a useful tool for both the early (screening) and late (in-depth) preclinical R& D during product characterization and development. The SIFR® can be implemented to simulate a wide range of host organisms (human and animal) and conditions (age groups, well vs unwell, IBD, pathogen infections...) according to published state-of-the-art protocols and is compatible with virtually all kind of actives, from naked actives, API and food components like antibodies, pre- / pro- or synbiotics, to formulated products and whole food.

[0261] As discussed throughout this disclosure, a key function of the gut microbiome consists in the fermentation of carbohydrates in the colon, resulting in the production of SCFAs, mainly including acetate, propionate and butyrate, each related with particular health benefits. As a result, the predictivity of the SIFR® technology in terms of SCFA production was assessed by the inventor against high-quality in vivo data of SCFA production upon intake of the reference prebiotic inulin. It followed that the predicted SCFA production by the SIFR® technology corresponds well to the actual in vivo SCFA production, particularly in terms of the total SCFA. See FIG. 11.

[0262] The SIFR® technology is preferably validated by studying the impact of three structurally different carbohydrates (inulin, 2’fucosyl-lactose and resistant dextrin) for which clinical data is available. Interestingly, in do so, it follows that changes observed in the SIFR® technology within 24-48h corresponded with in vivo observations upon repeated daily intake of the aforementioned carbohydrates over weeks (2-6 weeks), down to species level (shallow- shotgun sequencing), i.e. resistant dextrin specifically increased Parabacteroides dislasonis. 2’FL specifically increased Bifidobacterium adolescentis and Anaerobutyricum hallii. while inulin increased Bifidobacteriaceae. These validation studies also demonstrated that, unlike working with a single or pooled inoculum (n = 6), including 6 different donors (n = 1 ) provided representative insights that support mode-of-action, via the strong correlations between metabolic and compositional datasets.

[0263] Besides being validated to provide predictive insights for clinical findings upon long-term prebiotic intake, other applications of the SIFR® technology are related to, amongst others, (i) the development of synbiotics to boost butyrate production, (ii) scoping of prebiotic potential of serum-derived immunoglobulins, (iii) development ofage- specific functional ingredients, (iv) investigation of the specificity by which prebiotics impact the gut microbiota, or (v) effects of probiotics when supplied to a small intestinal microbiota.

[0264] As mentioned above, a key focus of using this technology has been to minimize the bias in microbiota composition between in vzvo-derived microbiota and the one colonizing the bioreactors during SIFR® studies. While this is already important when investigating the impact on microbial composition, this is even of greater importance when performing metabolomics studies given that altered ratios among species greatly impact the metabolic output. As an example, during a recent study, upon its introduction in a traditional in vitro gut model for breast-fed infants, a major increase of Veillonellaceae was observed upon cultivation over several weeks (> 80%). This contrasts with the in vivo microbiota of breast-fed infants that contains <1% Veillonellaceae and >98% Bifidobacteriaceae. As a result, metabolite production in such models was not mainly acetate / lactate (produced by Bifidobacteriaceae') but rather acetate / propionate (metabolites of Veillonellaceae26. By avoiding bias in microbial composition, the SIFR® technology allows for more representative observations.

[0265] A final strength of the SIFR® technology comes from standardization and automation. Whereas traditional preclinical models rely on complex and intensive manual work that contribute to variations in the output, the SIFR® technology relies on automation and identical processing of bioreactors to minimize the error rate and maximize the technical reproducibility across replicates. The variability observed on key fermentation parameters (pH, gas production, SCFA levels) is typically around 1 -3%, demonstrating that the entire pipeline from SIFR® implementation to sample to result is highly robust. Consequently, the SIFR® technology is a very sensitive platform to scope for potential treatment effects on the gut microbiota, even if minimal.

[0266] Using this technology, and in some embodiments, an exemplary study can be conducted of the impact on the gut microbiota of IBS patients for a series of test products, as described herein. With the ex vivo SIFR® technology, the impact on metabolite production (key fermentation parameters (pH, gas, SCFA, bCFA) and metabolomics), microbial composition (quantitative 16S rRNA gene profiling) and host-microbiota interactions can be assessed for the gut microbiota of 8 different IBS patients. The test products may be compared against a no-substrate control (NSC).

[0267] In certain embodiments, two triglycerides, i.e. triacetin (TA), tributyrin (TB) and three combinations thereof in different ratios, lysine-butyrate (LB), spermidine HC1 (SP), a mushroom blend (MB), fulvic acid (FA) and its combination with tributyrin can be tested against a no-substrate control. Exemplary test doses of the test products are indicated in the table depicted in FIG. 12. The exemplary test doses of TA, TB and LB may be determined based on a pre-test where the three products were subjected to simulated upper gastrointestinal (GIT) passage. As discussed above, more than 70-90% TA reach the colon upon upper GIT passage, while just approximately 3.3% of LB, and 28.5% of TB reached the colon upon upper GIT passage. The dose in this embodiment can be calculated based on a human equivalent dose (HED) of 1 g / day for LB, and 400 mg / day for TB and TA, with adjustments for dry weight (90% for TB and 100% for the other products).

[0268] An ex vivo SIFR® study can be implemented, simulating the colonic fermentation of test products by the gut microbiota derived from IBS patients (n = 8). The simulation parameters, in some embodiments of the study, are those shown in FIG. 13. In this exemplary study, there are 11 study arms (including the NSC). The time points are 0 hours (only NSC) and 24 hours. The NSC at 24 hours can be run in technical triplicate per donor to demonstrate the high reproducibility of the SIFR® technology. In this exemplary study, the selection criteria for IBS patients can be: age 30-65, no antibiotic use in the past 3 months, no other gastrointestinal disorders (cancer, ulcers, IBD), no use of probiotic, non-smoking, alcohol consumption < 3 units / d and BMI < 30.

[0269] In certain embodiments, analyses are performed at defined time points to assess fermentation outcomes, microbiota composition, metabolite profiles, and host-microbiome interactions. Measurements of key fermentation parameters are conducted at about 0 hours for a non-substrate control (NSC) condition and at about 24 hours for all test arms. Microbial composition analysis (quantitative 16S rRNA gene profiling) is likewise conducted at about 0 hours for NSC and at about 24 hours for all test arms. Additionally, in some embodiments, the composition of faecal microbiota from eight healthy donors can be characterized at about 0 hours for comparative purposes. Untargeted metabolomics focusing on semi-polar compounds can be performed at about 0 hours for NSC and at about 24 hours for the following study arms: NSC, TB, TA, TB3TA1, TB1TA3, and TB1TA1. Host-microbiome interaction assays using a Caco-2 / THP-l co-culture model can be carried out at about 24 hours for all study arms. Infurther embodiments, additional samples collected at about 24 hours may be reserved for optional assessment of GLP-1 and PYY production using an NCI-H716 cell model.

[0270] In some embodiments, fermentation performance is monitored by quantifying (i) pH, (ii) gas production, and (iii) short-chain fatty acids (SCFAs) together with branched-chain fatty acids (bCFAs) as markers of microbial metabolic activity. The SCFA panel explicitly includes acetate, propionate, butyrate, and valerate. The bCFA measurement comprises the sum of isobutyrate, isovalerate, and isocaproate. SCFAs and bCFAs are determined via a gas chromatography-flame ionization detection (GC-FID) approach. In these embodiments, pH is recorded using a suitable pH measurement device, and gas production is measured to index total gaseous output over the incubation period. These key fermentation parameters are assessed at about 0 hours for NSC and at about 24 hours for all test arms.

[0271] In further embodiments, microbial community composition can be evaluated by quantitative 16S rRNA gene profiling. Following DNA extraction, library preparation and sequencing can be performed on an Illumina MiSeq platform with v3 chemistry. The V3-V4 hypervariable regions of the 16S rRNA gene may be amplified using primers 34 IF and 785Rmod. Results can be analyzed at multiple taxonomic levels, including phylum, family, and operational taxonomic unit (OTU) levels. To obtain representative insights into the impact of the interventions on the gut microbiota, proportional sequencing data (percentage values) can be corrected for the total amount of cells present in each sample, with total cell counts determined via flow cytometry. This quantitative normalization enables interpretation of absolute or quasi-absolute changes rather than relative changes alone. In some embodiments, the faecal microbiota composition from eight healthy donors is also analyzed at about 0 hours for comparison alongside the NSC and test arm datasets.

[0272] In certain embodiments, metabolite profiling is performed using an untargeted LC-MS / MS approach optimized for semi polar metabolites. The LC-MS platform comprises a Thermo Scientific Vanquish liquid chromatograph coupled to a Thermo Q Exactive HF mass spectrometer. An electrospray ionization (ESI) interface is employed as the ionization source, and data are acquired in both negative and positive ionization modes. Ultra performance liquid chromatography (UPLC) is performed using a slightly modified version of an established protocol adapted for the analyte class and matrix under investigation. Peak areas are extracted using Compound Discoverer 3.1 (Thermo Scientific). In addition to the automated compoundextraction, a manual extraction of compounds included in an in house library is performed using Skyline 21.1 (MacCoss Lab Software).

[0273] Compound identification confidence may be assigned, in some embodiments, using multi-level criteria. For example: Level 1: identification by matching retention times to in house authentic standards, accurate mass with an accepted deviation of 3 ppm, and MS / MS spectral concordance. Level 2a: identification by matching retention times to in house authentic standards and accurate mass within a 3 ppm deviation. Level 2b: identification by accurate mass (within a 3 ppm deviation) together with MS / MS spectral evidence. Level 3: identification by accurate mass alone (within a 3 ppm deviation). This untargeted metabolomics analysis can be conducted at about 0 hours for NSC and at about 24 hours for NSC, TB, TA, TB3TA1, TB1TA3, and TB1TA1.

[0274] The timeline of this exemplary experiment, in some embodiments, may be as presented in FIG. 13. Briefly, this may involve appropriate differentiation periods for both Caco-2 (= epithelial cells) and THP1 -cells (immune cells) after which the co-culture experiment may be performed during which the in vivo gut wall is recreated by covering the THP-1 cells with the epithelial layer in a transwell system. The actual experiment may comprise (i) a 24h treatment period during which test products are applied on the apical side of the epithelial cells allowing to evaluate the impact on gut barrier integrity and (ii) a subsequent 6h LPS challenge of THP- 1 cells at the basal side to evaluate the impact of the test products on immune functioning.

[0275] At the start of the main experiment, culture media in the apical chamber can be replaced with samples derived from the SIFR® incubations, diluted in cell medium. Upon measuring TEER, plates can be incubated for 24h after which the TEER is again measured and 500 ng / ml of LPS is added to the basal chamber of the transwells containing the THP-1 cells. Upon a 6h LPS challenge to boost cytokine / chemokine production, TEER can be measured and samples from both apical and basal compartments can be collected and subjected to cytokine / chemokine analysis using Multiplex. Luminex® Assay kit on the MAGPix® analyser (IL-6, CXCL10, IL-10, IL-ip, TNF-a) or ELISA (IL-8).

[0276] For exploratory evaluation of the obtained results, a series of principle component analysis (PCA) may be performed. The two principal components with the largest eigenvalues can then be plotted. For the statistical evaluation of the treatment effects on key fermentationparameters, cell counts, microbial diversity (4 indices) and microbial composition (phylum level) across 8 different donors, a repeated measures ANOVA analysis was performed (~ based on paired t-testing, thus accounting for fact that values are compared between samples of a given donor). The statistical significance of the potential treatment effects was determined via Benjamini -Hochberg post hoc testing. The latter involves that a correction for multiple comparisons was implemented where p-values were adjusted by multiplying them with the total number of comparisons divided by the rank of each original p-value (across all p-values). In this specific case, 10 comparisons were considered (= NSC vs. 10 treatments). See FIG. 14.In practice, this means that while the largest obtained p-value remains uncorrected (i.e., multiplied 1), the lowest p-value can be multiplied with 10, thus strongly decreasing the chance of type 1 errors (i.e. false positives). In addition, the resulting series of adjusted p-values can be rendered non-decreasing (i.e., when an adjusted p-value is higher than any of the subsequent adjusted p-values, its value should be equaled to this lowest value). This generates a false discovery rate threshold allowing to estimate and control the chance of type 1 errors i.e., false positives). Statistical differences can be visualized via * (0.1 < padjusted < 0.2), ** (0.05 < padjusted < 0.1) or *** (padjusted < 0.05) for treatment v NSC. See FIG. 14.

[0277] For the statistical evaluation of the treatment effects on microbial composition (family and OTU level) and metabolite production (metabolomics), the Benjamini -Hochberg correction may be applied within each comparison (NSC vs. 10 test products), given the large number of features analyzed. In some embodiments, for statistical analysis of the quantitative 16S rRNA gene profiling, a value below the limit of quantification (LOQ) can be equaled to the LOQ. Then, statistics can be performed based on log-transformation of the absolute values (to render the data normally distributed). To establish an overall LOQ, first, 1 read can be divided by the total amount of reads in each sample, followed by multiplication with the bacterial cell count detected via flow cytometry. This may allow to obtain a LOQ for each sample individually. Then, the highest LOQ was used as overall LOQ of the entire dataset.

[0278] To illustrate the most representative change for each taxon or metabolite, fold changes against the NSC can be calculated for individual donors. Subsequently, log2-transformation can be performed on the geometric mean of these fold changes. Geometric mean may be advantageously used since it is more accurate and representative than the often-used arithmetic mean, especially for positively skewed data which is often the case for microbial composition and metabolomic data (due to interpersonal variances). Further, regularizedCanonical Correlation Analysis (rCCA) can be performed to highlight correlations between metabolites and compositional data (at family and OTU level). Regarding compositional data, log-transformed, absolute phylogenetic data was used as input. rCCA may be executed using the mixOmics package with the shrinkage method for estimation of penalization parameters in R.

[0279] Regarding the key fermentation parameters, the key function of the gut microbiota is to ferment carbohydrates (and to lesser extent proteins), resulting in the formation of shortchain fatty acids (SCFA). Acetate, propionate and butyrate are SCFAs that have each been related with particular health benefits. Besides exerting anti-inflammatory effects, SCFAs also decrease the pH of the colonic lumen which for instance increases mineral absorption and inhibits growth of pathogens. Acetate is a minor energy source for epithelial cells but reaches the portal vein after which it is metabolized in various tissues. Like acetate, propionate reaches the portal vein after which it is taken up by the liver. Health effects related to propionate include that it promotes satiety, lowers blood cholesterol, decreases liver lipogenesis and improves insulin sensitivity. Butyrate on the other hand is the preferred energy source of epithelial cells and plays a protective role against colon cancer and colitis. As a result, treatments preferable stimulate acetate, propionate and butyrate production. Further, while valerate is much less studied than the other SCFA, it has also been demonstrated to decrease growth of cancer cells or to exert antipathogenic effects against C. difficile.

[0280] In contrast to aforementioned SCFA, bCFA are indicative for proteolytic fermentation, which is associated with formation of metabolites such as phenol and indole that exert detrimental health effects. On the other hand, there is also evidence that bCFA can be oxidized when butyrate is not available, thereby contributing to health benefits. In addition, it is contemplated that a mix of bCFA (isobutyrate and isovalerate) is able to prevent gut permeability induced by pro- inflammatory cytokines in the Caco-2 cell line model.

[0281] Further, while fermenting colonic substrates, the main gases that are produced are H2 and CO2. They can be further converted to other gases (CH4, H2S) but also to acetate. While fermentation by gut microbes (except Bifidobacteria) inevitably results in gas production, excessive gas production should be avoided as this can lead to abdominal pain or bloating.

[0282] On top of the core experimental design, additional incubations can be run for the sole purpose of quality control. This considered that NSC incubations at 24h were run intechnical triplicate. Based on the analysis of pH and levels of three main SCFA (acetate, propionate and butyrate) for these replicates, it followed that the coefficient of variation (= standard deviation / average) was as low as 0.75%. This variation is very low since it includes all variation the preparation of the media / reactors up to final sample analysis via GC-FID / pH probes. The high reproducibility of the SIFR® platform makes it a very sensitive tool to unravel the impact of test ingredients on the gut microbiome. In addition, upon analyzing key fermentation parameters (pH, gas production, SCFA and bCFA) at the end of the untreated NSC incubations (24h), it follows that microbial communities derived from each of the 8 donors resulted in diverse metabolic profiles. For average values (± SD) of key fermentation parameters as averaged across all test subjects at the end of the untreated NSC incubations, following inoculation with a faecal microbiota of IBS patient (n = 8), see FIG. 15. The production of butyrate, produced by strictly anaerobic gut microbes, further confirms that the SIFR® experiment is performed under optimal conditions. While technical reproducibility is contemplated to be 0.75%, biological variation across the IBS patients was 12.6%, reflecting interpersonal differences.

[0283] In some embodiments, a PCA based on key fermentation parameters, as averaged across the 8 test subjects, can provide comprehensive insight in overall treatment effects since the first two components explained 96.5% of variation (FIG. 16A). All parameters (except pH) correlated negatively with PCI, indicating that samples with enhanced microbial activity positioned to the left side. First, when focusing on the impact of time, it followed that there was a marked differential clustering of Oh and 24h samples. As the incubation progressed, samples moved from the right to the left side of the PCA, suggesting enhanced production of acetate, propionate, butyrate, bCFA and gases. In further embodiments, additional PCA analysis may be performed to visualize product-specific effects at 24h, as averaged across the 6 donors, thus removing the time effects observed in FIG. 16A. Marked product-specific effects were observed (FIG. 16B) (i) LB, SP, FA positioned close to NSC caused milder impact on microbial metabolite production compared to the other test products; (ii) TB, TA, and their combinations shifted to the right or upper right side of the NSC, primarily relating to increased acetate and butyrate production. Interestingly, the higher the TA content in the treatments, the more pronounced the effects were; (iii) MB: shifted to the right / lower right of NSC and specifically relating to stimulation of propionate and gas production.

[0284] Finally, a PCA based on the individual values of each of the 8 donors at 24h (Figure 4C) is contemplated to demonstrate that there are some interindividual differences in the NSC, along both PCI and PC2. Interestingly, despite the interpersonal differences, the treatment effects were largely consistent across the different donors.

[0285] To fully grasp the treatment effects at 24h, dedicated figures were made per fermentation parameter. See FIG. 17. To understand which treatment most strongly impacts a specific parameter, average values across donors were ranked, with 1 corresponding to the highest value (highlighted with a lighter colored dot), and 11 corresponding to the lowest value (highlighted with a darker colored dot). ‘ * / ** / ***’ indicate the extent of the significance of a potential treatment effect versus the NSC. Finally, additional dot plots were generated to visualize the effects of each test product on the key fermentation parameter as % of change compared to NSC, as averaged across all donors. See FIG. 18.

[0286] In certain embodiments, the administration of TA to the gut microbiota results in significantly decreased pH, increased production of acetate and butyrate, and to a lesser extent valerate (with minor propionate decrease). Further, TB is contemplated to exhibit decreased pH due to the stimulation of butyrate and to lesser extent valerate (with minor propriate decrease). Unlike TA, TB is contemplated to mildly, but significantly decrease acetate levels, while increasing bCFA production.

[0287] In further embodiments, the combinations of TA + TB are contemplated to significantly increase acetate / butyrate, but more pronounced effects are observed with higher TA content. Based on PCA analysis, LB, FA, and SP are contemplated to exert milder impacts on microbial metabolite production. First, similar to TB, the combination of TB+FA is contemplated to significantly increase butyrate production and decrease propionate production. The effects are contemplated however to be milder compared to TB. Further in-depth analysis is contemplated to reveal that LB significantly increases butyrate (yet, decreases acetate), FA significantly decreases pH (yet, decreases acetate / butyrate), and SP significantly decreases the levels of all three main SCFAs (acetate, propionate, and butyrate). Overall, FA / SP are contemplated to not increase metabolic activity of the gut microbiota.

[0288] Unlike the other test products, fermentation of MB is contemplated to significantly increase the production of all three main SCFAs, most notably propionate (FIG. 17). Further,the stimulation of acetate / butyrate by MB is contemplated to be milder compared to TA. Besides, MB also significantly decreased pH and increased gas production.

[0289] In further embodiments, the observed SCFA production induced by adding TA, TB, and their mixtures can be compared to a theoretical amount of acetate and butyrate that could be released from TA and TB, assuming that fermentation of the glycerol backbone would not contribute to SCFA production. See FIG. 19. To account for the differing alkyl chain lengths in acetate, propionate, and butyrate, their production may be normalized for the number of carbon atoms in each SCFA and expressed as acetate equivalents. It is contemplated in some embodiments that this comparison will demonstrate that, in treatments containing TA, observed acetate production may range from 81.6% (TB3TA1) to 93.1% (TB1TA3) of the theoretical values. This indicates that the increased acetate production in these study arms was primarily due to hydrolyzation of TA. Additionally, the fact that acetate release was less than 100% suggests that a portion of the released acetate was utilized and converted into other metabolites, such as butyrate.

[0290] In further embodiments, the comparison between these treatments is contemplated to reveal that, at higher concentrations of TA in the treatments (TA and TB1TA3), SCFA production (expressed as acetate equivalents) exceeded 100% of the theoretical values (123.2% and 112.1%, respectively). This suggests that at higher doses of TA, fermentation of the glycerol backbone may substantially contribute to the increased SCFA production.

[0291] In yet further embodiments, the comparison is contemplated to reveal that the empirical release of TB from TB and TB3TA1 was notably lower than the theoretical values (52.6% and 62.7%, respectively). This discrepancy may be attributed to an overestimation of TB purity or the low abundance of gut bacteria in the IBS patients' microbiota capable of hydrolyzing TB into butyrate.

[0292] It is contemplated that excessive gas production during fermentation could lead to abdominal pain or bloating. As such, the relationship between gas production and total SCFA production is relevant to assess the tolerability of a compound. Crucially, and based on experimental results, it is contemplated that all treatments containing TB or TA, but especially TA on its own, resulted in a significantly lower gas / SCFA-ratio as compared to the NSC. See FIG. 20. This unexpected result suggests higher tolerability for human consumption. This is likely due to the fact that the release of acetate and butyrate from the triglycerides involvedfewer metabolic steps than their production by certain bacteria through the fermentation of more complex substrates (e.g., fibers or proteins), which often involves multiple gas-producing steps. Further, the fermentation of MB is contemplated to increase the production of gases and all three main SCFAs but not gas / SCFA-ratio compared to NSC, thus also suggesting high tolerability of MB for consumption.

[0293] The Actinomycetota phylum (formerly Actinobacteriota) mainly consists of Bifidobacteriaceae and Coriobacteriaceae. The Bifidobacteriaceae family contains many known health-related species, able to produce acetate and lactate. Collinsella species are on the other hand the most abundant Coriobacteriaceae members and produce H2 gas, formate, acetate and lactate. The Bacteroidota phylum (formerly Bacteroidetes) contains versatile glycan-fermenting members. Key taxa are Bacteroides and Prevotella, two genera considered to be main differentiators between the so-called enterotypes. Bacteroides species produce acetate and propionate and doing so also succinate (as intermediate of propionate production). Other families are Rikenellaceae (e.g. Alistipes) and Tannerellaceae (e.g. Parabacteroides). Further, the Bacillota phyla (formerly Firmicutes) contains a diverse series of phyla including, amongst others: Acidaminococcaceae'. a key species of this family is Phascolarctobacterium aecium, an abundant colonizer that is able to convert succinate into propionate; Coprobacillaceae (e.g. Thomasclavelia ramosa) and Christensenellaceae (e.g. C. minuta); Lachnospiraceae: contains several important butyrate-producing species such as Anaerobutyricum hallii, Anaeroslipes. Bulyrivibrio. Coprococcus, Roseburia. Further, Lachnospiraceae are among the first to be established in the gastrointestinal tract, with Mediterraneibacter gnavus being the exclusive representative of this family in 2-months old breast-fed infants. Further, this family also contains Dorea spp., which is a major gas producer (H2 / CO2) related to IBS; Ruminococcaceae: several important butyrate-producing species such as Butyricicoccus pullicaecorum, Gemmiger formicilis, Faecalibacterium prausnitzii and Subdoligranulum variable, Selenomonadaceae: Megamonas species; Veillonellaceae'. lactate-converting, acetate / propionate / H2-producing species such as Veilonella, Enter ococcaceae, Lactobacillaceae and Streptococcaceae are Bacillota families containing lactic acid producing member that typically colonize the upper GIT but to much lower extent the colon.

[0294] While Pseudomonadota (formerly Proteobacteria) mainly contain opportunistic pathogens (e.g. Escherichia coll), Verrucomicrobiota (formerly Verrucomicrobia) has the health-related, mucin- degrading, acetate / propionate-producing Akkermansia muciniphila asits main representative. Finally, besides bacteria, there are also Archaea such as Methanobrevibacter smithii colonize the human gut. M. smithii converts H2 / CO2 to CH4. Other H2 and / or CO2 consumers are acetogens (Blautia hydrogenolrophica Lachnospiraceae member) and sulfate reducers (Desufovibrio piger. Pseudomonadota member that converts H2 / SO4 to H2S).

[0295] A PCA at genus level may be conducted based on microbial composition of the microbiota derived from faecal samples of the 8 IBS patients as well as a reference cohort of 8 healthy adults. See FIG. 21. When focusing on variations among the IBS patients, the largest variation could be observed for donors exhibiting very high (donor 8), high (donors 1 / 4), low (donors 3 / 5) and very low Bifidobacterium levels (donors 2 / 6 / 7). Besides, Phocaeicola and Bacteroides. markers of the Bacteroides enterotype were highly abundant for donor 8 and donors 3 / 4 / 7, respectively. Particularly, in this exemplary experiment, donor 8 had very low levels of Ruminococcaceae (i.e., Faecalibacterium, Gemmiger) which are markers of the Ruminococcus enterotype. Further, donor 1 / 6 / 7 also displayed higher levels of the methane-producing archaeon Methanobrevibacter. Overall, these first findings stress that the eight IBS donors recruited as faecal donors for the current study covered the wide range of microbiota composition that occurs in vivo across different enterotypes, thus ensuring representative findings.

[0296] To further unravel potential differences in fecal microbial composition between the two cohorts, an additional statistical analysis can be performed to pinpoint the significant differences between the two cohorts (p < 0.05, unpaired t-test). Following OTUs is contemplated to display significantly higher levels (%) in specific cohorts’ microbiota. See FIG. 22. The IBS donors include: Blautia A wexlerae and Blautia faecis, in alignment with previous studies demonstrating significantly higher Blautia abundances in the microbiota of IBS patients’ Mediterraneibacter gnavus'. A previous study have demonstrate the role of M. gnavus pathogenic role in diarrhoea-predominant irritable bowel syndrome’ and Parasutterella, Bacteroides thetaiotaomicron. The HE donors include: Several Bacillota OTUs related to Bariatricus comes as well as the relatively low- abundance Hominicoprocola fusiformis, Turicibacter bilis, Enterococcus B Other low-abundance OTUs related to Odoribacler. Pandoraeae sp., Sutterella. While not significantly different, Bifidobacterium could be observed more consistently and evenly in the microbiota of the healthy donors compared to theIBS donors. Overall, the comparison between the IBS and the healthy donors verifies the biorelevance of the IBS cohort recruited for this study.

[0297] The preservation of the in vzvo-derived microbiota and thus the minimal bias in microbiota composition during SIFR® studies is in contrast to consistent in vitro biases that have been observed for traditional long-term in vitro models and in recently developed shortterm in vitro models, given that SIFR® studies adhere to ex vivo rather than in vitro simulation principles. This can also be confirmed during the exemplary studies described herein upon comparing the original sample and the same sample incubated for 24h using the SIFR® technology. For example, and in some embodiments, first, a diverse range of in vzvo-derived gut microbes endured the procedure over the 24h incubation period, maintaining the microbial diversity, both in terms of species richness (FIG. 23A) and evenness (FIG. 23B / C). Under control conditions (NSC), the total cell numbers increased from Oh (INO) to 24h with a factor of 4.07 (± 0.92) (Figure 10D). Importantly, at the end of the 24h NSC incubation, microbial composition reflected the original inoculum (INO) (FIG. 23E).

[0298] This accurate preservation of in vzvo-derived microbiota for the entire duration of the exemplary experiment classifies the application of SIFR® technology as an ex vivo study, which is a study that uses an artificial environment outside the host with minimum alteration of natural conditions. Such sustained similarity is fundamentally different from consistent biases observed for the current generation of in vitro gut models.

[0299] In further embodiments, it is contemplated that an analysis of the total cell numbers across the different samples demonstrates that TA and MB significantly increase total bacterial cell density. See FIG. 24A. As shown in FIG. 24, there are differences in cell numbers across study arms, and therefore it is important to correct the proportional data obtained via sequencing (%) with the total cell counts in order to obtain insights into the true changes in microbial composition. The conversion of sequencing data using flow cytometry data is visualized at phylum level. See FIG. 24B / C. Subsequent data processing at OTU and family level can thus be performed based on the quantitative results. This exploratory, exemplary data visualization of microbial composition at phylum level shows that Actinomycetota, Bacteroidota, Bacillota A and Pseudomonadota were the main phyla. It also demonstrated that MB markedly increased the levels of Actinomycetota (containing acetate / lactate-producing Bifidobacterium) and Bacillota A (containing the main butyrate producers of the gut microbiota), while TA mainly increased the abundance of Bacillota A. See FIG. 56-57. Formore details of these findings at phylum level, violin plots were generated based on quantitative data of the phyla for the individual animals as depicted in FIG. 83.

[0300] Four diversity indices may be calculated, in certain embodiments, to obtain optimal insights into microbial diversity. See FIG. 25. First, a new diversity score, i.e. the community modulation score (CMS), was recently developed by Cryptobiotix (FIG. 25A). This index removes great part of the noise that is introduced when assessing diversity using traditional indices. On average, most of the test products did not affect the combined CMS, except MB which significantly increased the CMS, indicating a positive impact of MB on microbial diversity. Next, traditional diversity indices were also calculated: while the Chaol diversity index is a measure of species richness (FIG. 25B), the reciprocal Simpson diversity index / Shannon diversity index reflect also species evenness (FIG. 25C / D). In contrast to the CMS, these indices show that the test products did not significantly impact the microbial diversity in term of species richness and evenness.

[0301] Regarding the treatment effects, PCA may be conducted based on the average results across the 6 donors at 24h. Further, for optimal insights, the PCA can be made at high phylogenic resolution, i.e. based on the centered average levels of the 150 most abundant OTUs. See FIG. 26A / B. It is contemplated that the resulting PCA reveals various treatment effects of the products, compared to the NSC. For example, in an exemplary experiment, TA shifted upwards along pC2 relative to NSC and in a dose-dependent manner with increasing TA content in the treatments, relating to butyrate-producing OTUs. MB shifted to the upper right side relative to NSC and is distinctively separated from the other treatments and related to increased levels of OTUs related to acetogenic Bifidobacerium spp., acetate / propionate-producing, Bacteroidota taxa, propionate / butyrate-producing Coprococcus A catus, as well as butyrate producers in the phylum Bacillota A. As for TB, LB, SP, FA, TB+FA, these were positioned close to NSC and thus exhibited relatively mild impact on microbial composition. Overall, the exploratory analysis reveals product-specific impact on microbial composition. To statistically support these findings, the data was further processed family and OTU level.

[0302] In additional embodiments, to gain insight in treatment effects at family and OTU level, all taxa that were significantly (padjusted < 0.20) and non-significantly but consistently affected were displayed in a heat map based on the average ratios versus the NSC (Figure 14A and Figure 15 A). Top 5 families and OTUs with the largest variations among the treatments in a PCA analysis were also included in the heat maps. A selection of relevant taxa will behighlighted along the text below via dedicated figures based on log2(fold change of treatment vs. NSC). Further, at both taxonomic levels, a rCCA was performed to highlight correlations between key fermentation parameters and specific taxa (FIG. 27B, FIG. 28B). In addition, pairwise correlation analysis using Spearman’s rank correlation coefficient were also performed in some embodiments with significant correlations also being highlighted in the figures. Owing to interpersonal differences and treatment effects, correlations could be established between specific metabolites and certain taxa, in line with known metabolic capabilities of these taxa. Several correlations could be observed as a result. For example, Propionate ~ the propionogenic family Acidaminococcaceae Q as well as propionate-producing Coprococcus A catus, and Butyrate ~ Butyrogenic Ruminococcaceae (including Faecalibacterium prausnitzii) Mediterraneibacter butyr icigenes59 and Lacrimispora.

[0303] When focusing on the impact of TA and TB in the treatments, profound stimulatory effects of TA on several taxa in the phylum Bacillota A were noted. For example butyrate OTUs related to Facealibacterium prausnitzii, Anaerobutyricum soehngenii (high abundances) and Midterraneibacter A butyricigenes (low abudnances). Esepcially OTUs related to F. prausnitzii and M. butyricigenes strongly correlated with butyrate. Importantly, these taxa can convert acetate into butyrate via butyryl-CoA: acetate CoA-transferase pathway, confirming that acetate-to-butyrate conversion markedly contributes to TA-induced butyrate production. See FIG. 29. Further, other OTUs belonging to Lachnospiraceae related to Bariatricus, Mediterranebacter torques, Hungatella hatewayi. See FIG.30. In contrast, TB only mildly but consistently increased the levels of a butyrogenic OTU related to butyrogenic Lachnospira pectinoschiza. See FIG. 31.

[0304] As discussed herein, TA+TB combinations exerted effects in line with the presence of TA and TB in combinations, i.e. the higher the TA content is, the stronger the effects were.

[0305] Of all test products, MB is contemplated to exhibit the most pronounced impact on microbial composition, promoting the largest numbers of OTUs, including several SCFA-producing, health-related OTUs. First, MB tended to exhibit bifidogenic effect (= increased Bifidobaceriaceae), except in donor 4’s microbiota, as evidenced by increased abundances of acetate-producing OTU related to B. adolescentis and B. longum. Importantly, significant positive correlation between Bifidobacteriaceae and acetate suggest a role of Bifidobacterium spp. In promoting acetate production upon MB treatment. See FIG. 32. The drawback of MB, as opposed to triacetin, is high gas production.

[0306] Further, MB is contemplated to stimulate propionogenic OTUs in the family Bacteroidaceae relating to Phocaeicola dorei, Bacteroides uniformis, B. caccae. Significant positive correlation between Bacteroidaceae and propionate levels confirmed the role of these taxa in promoting propionate production. Further, MB also markedly stimulated the less abundant propionogenic OTU related to Parabacteroides distasonis, also belonging to the phylum Bacteroidota. See FIG. 33.

[0307] In addition to the aforementioned propionate-producing OTUs within the phylum Bacteroidota, MB is also contemplated to stimulate an OTU related to the propionogenic Coprococcus A catus (family Lachnospiraceae). Although Coprococcus A catus (OTU82) is capable of producing both propionate and butyrate, it exhibited a significant positive correlation with propionate and a significant negative correlation with butyrate. This suggests that the butyrate-producing pathway in this OTU was deactivated, resulting in its primary contribution to propionate production. See FIG. 34.

[0308] Further, MB is contemplated to stimulate a number of butyrogenic OTUs in the family Lachnospiraceae, including those related to Anaerostipes hadrus. Lacrimispora, Roseburia inulinivorans and Butyribacter sp. Similar to TA, MB also tended to increase OTUs related to F. prausnitzii and A. soehngenii. All of these taxa could play an important role in promoting butyrate production. MB is also contemplated to promote several other Lachnospiraceae OTUs, including an OTU related to Fusicatenibacter saccharivorans, known for its IL-10-mediated anti-inflammatory effects. Similar to TA, MB is additionally contemplated to stimulate OTUs related to Bariatricus and torques. See FIG. 35.

[0309] According to an exemplary experiment described herein, a total of 588 compounds were detected upon the LC-MS metabolomics analysis. As detailed in materials and methods, compounds were annotated with three levels of identification. The number of compounds detected per level is listed in FIG.36. Given the higher degree of certainty of correct annotation at level 1 and 2a, the analysis and interpretation mostly focus on level 1 / 2a metabolites. In another embodiment of an exemplary experiment, a quality control (QC) was performed by analyzing QC samples, created by taking a small aliquot from each sample, with regular intervals throughout the analysis. As followed from the PCA based on the level 1 / 2a-annotated metabolites, these 17 QC samples grouped tightly together indicating that the biological variance (either due to the effects of the incubation time, the test products or interpersonal differences) largely exceeded the analytical variance (represented by the spread of QCsamples). See FIG. 37. Indeed, the coefficient of variation (= standard deviation / average) was on average 8.68% amongst level 1 / 2a metabolites. The high reproducibility of both the SIFR® incubations as well as the metabolomics analysis warrants that observed differences are truly due to a treatment and not due to technical variation.

[0310] Additional embodiments of an exemplary experiment according to the present disclosure, focused on 155 level 1 / 2a metabolites (ensuring correct annotation) especially given that these metabolites have been linked with the gut microbiome (as nutrient or metabolite) often in the context of health or disease. See FIG. 53-55. Therefore, in some embodiments of an exemplary experiment, a series of amino acids (arginine, aspartic acid, glutamine, histidine, lysine, methionine, tyrosine) was efficiently consumed when comparing the 24h samples with those collected at Oh (INO). On the other hand, the levels of several other amino acids (alanine, isoleucine, leucine, phenylalanine, valine) exhibited marked interpersonal differences at 24h, potentially due to varying rate of consumption / production in the different donors. An efficient conversion of amino acids is of interest given the potential resulting production of health-related metabolites. See FIG. 38. Then, out of 155 metabolites examined, the levels of 77 metabolites increased in at least 4 donors along 24h incubations. It is contemplated that this result may be attributed to the 4 donors production by human-derived microbes or their presence in one of the test products.

[0311] To better grasp treatment effects at 24h, an additional PCA was made in yet another exemplary experiment. See FIG. 39. Based on the average values across donors at 24h (thus omitting differences between 0-24h which were represented in FIG. 38. of the aforementioned 77 level 1 / 2a metabolites. Based on this exemplary experiment, higher TA content in the treatment was observed to result in a more pronounced shift to the right along PC1, indicating, in some embodiments, a stronger impact on metabolite production. TB alone caused a downward shift along PC2, suggesting that in some embodiments distinct treatment effect compared to TA-containing treatments.

[0312] Of the 77 metabolites, only 7 metabolites were significantly affected (padjusted < 0.2) by at least one treatment. These significantly affected metabolites are presented in a heat map (based on the log2ratios versus the NSC; FIG. 40. Further, in order to link the production of specific metabolites to specific microbial taxa, a correlation analysis was again performed between these significantly affected metabolites and compositional data (at family level (FIG.41) and OTU level (FIG. 42). This revealed, in certain embodiments, that correlations could be established between the presence of specific taxa and the production of specific metabolites.

[0313] In further exemplary experiments, TB, TA and all of their mixtures in different ratios significantly increased the levels of 3 -methylhistidine (3-MH). See FIG. 43. In humans, 3-MH is a constituent of actin and myosin. Increased urinary excretion of 3-MH is a biomarker of muscle breakdown or protein-rich diet. Further, TA specifically increased the levels of a few metabolites in a dose-dependent manner with increasing TA content in the treatments. For example, 4-guanidinobutyric acid slightly but significantly increased for TA and TB1TA3. 4-guanidinobutyric acid was previously shown to have inhibitory effects against gastric lesions. Hydrolysis of 4-guanidinobutyric acid produces y-aminobutyric acid (GABA) - a major inhibitory neurotransmitter with relaxing, anti-anxiety, and anti -convulsive effects64. GABA increases the cell surface mucin MUC1 that prevents the adhesion of microorganisms. Muramic acid, a component of many typical bacterial cell walls, was also increased. Additionally, terahydro-2H-pyran-2-one (8-valerolactone, oxan-2-one) was strongly induced by high content of TA in the treatments. To see the log2 (fold change vs NSC) for 4-guanidinobutyric acid, muramic acid, and terahydro-2H-pyran-2-one in response to various treatments, see FIG. 44.

[0314] Finally, TA, TB and their mixtures decreased the production of 3-(2-hydroxyethyl)indole (tryptophol), while TA specifically and significantly decreased the levels of indole-3 -acetic acid (IAA). Both tryptophol and indole-3 -acetic acid are tryptophan derivatives. Tryptophol has been suggested as a functional analogue of the neurotransmitters melatonin and serotonin. Indole-3 -acetic acid, exhibits both anti -oxi dative and antiinflammatory effects. See FIG. 45. However, high IAA levels positively correlated with markers of oxidative stress and inflammation and with high mortality in chronic kidney disease.

[0315] It is contemplated that the epithelial cell layer of the gut wall performs a pivotal role as the first physical barrier against external factors. The tight junction proteins are crucial for the maintenance of epithelial barrier integrity. A. compromised barrier integrity (‘leaky gut’) is considered to contribute to many pathological conditions including, amongst others, inflammatory bowel disease, obesity, and metabolic disorders. Measuring the trans-epithelial electrical resistance (TEER) is a widely accepted quantitative technique to measure the integrity of tight junction dynamics in cell culture models. The following cytokines / chemokines were measured during an exemplary experiment conducted according to the presently disclosed subject matter: IL-6, IL-10, IL-ip, CXCL10, IL-8 and TNF-a. First,IL- 10 is an anti-inflammatory cytokine that inhibits both antigen presentation and subsequent release of pro-inflammatory cytokines, thereby attenuating mucosal inflammation. Further, while IL-6 can exert pro-inflammatory effects owing to its ability to prevent T cell apoptosis, it is also known to promote barrier function, survival of intestinal epithelial cells and antimicrobial defense. In contrast, TNF-a is a driver of intestinal inflammation and weakens the epithelial barrier integrity by inducing apoptosis in intestinal epithelial cells. Additionally, IL-ip exerts pro-inflammatory effects by e.g. promoting pathogenic T cell responses such as Thl7 cell differentiation and IFN-y production. Further, CXCL10, an ‘inflammatory' chemokine, is also known to mediate immune responses through the activation and recruitment of leukocytes such as cells, eosinophils, monocytes and NK cells. IL-8 is mainly a neutrophil chemoattractant that induces the migration of neutrophils from peripheral blood into inflamed tissue. It is well known that IL-8 production is increased in the tissue of IBD patients compared with that of normal controls.

[0316] It is further contemplated that in comparing the impact of test products on the epithelial barrier integrity and cytokines / chemokines ex vivo using the SIFR® technology, and in vivo, relying on clinical data, the SIFR® data would mirror the clinical findings, predicting the increase in gut barrier integrity and a reduction in pro-inflammatory cytokines. The ability to accurately measure such health-related outcomes is a powerful extension of SIFR® technology towards a better understanding of the clinical outcomes.

[0317] As will be readily apparent, the impact of the test products on gut barrier integrity upon 24h of interaction between colonic samples and the co-culture of epithelial and immune cells (Caco-2 and THP-1 differentiated macrophages) was studied and observed in yet another exemplary experiment. See FIG. 46. In this exemplary experiment, treatments containing TA. TB, and MB (MB > TA > TB) significantly improved gut barrier integrity. In contrast, SP tended to decrease gur barrier integrity. After stimulation of THP-1 differentiated macrophages with LPS (= stressed conditions) over an additional 6h period (thus total of 30h) (FIG. 45B) the impact of the test products on the gut barrier integrity were similar to the observations at 24h. After exposure to LPS for 6h, MB / TA / TB -containing treatments further enhanced gut barrier integrity, while SP reduced gut barrier integrity.

[0318] To further establish potential correlations between gut barrier integrity and SCFA production, a correlation analysis was performed between the individual SCFA and TEER. This revealed that acetate and butyrate (thus, total SCFA) positively correlated with an increasein TEER at both 24h in the absence of LPS as well as after 6h of treatment with LPS (FIG.47). The data partially suggested a potential role of SCFA in maintaining a healthy gut barrier. Additionally, other microbial metabolites (including those reported in section 6) might also play a role in the modulation of gut barrier integrity. Finally, a correlation between microbial composition (OTU level (FIG.49) revealed the marked positive correlation between improved gut barrier integrity at 24 / 30h and presence of, amongst others, OTUs related to Parabacteroides distasonis, and to a lesser extent, OTUs related to Faecalibacterium prausnitzii. Lacrimispora, Mediterraneibacter A butyr icigenes, suggesting that these specific taxa might be involved in the beneficial effect of the treatments on barrier integrity. For the impact of the test products compared to a no substrate control (NSC), on immune modulation as measured by the levels of immune markers, see FIG. 48.

[0319] In another exemplary experiment, upon 24h of interaction between the colonic samples and the co-culture of epithelial and immune cells, macrophages were triggered with LPS to boost their cytokine / chemokine response. It is important to note that LPS was not administered apically of the epithelial cells but basolaterally (so in the compartment where immune cells are present). Doing so, immune cells are equally stimulated. The response of immune cells thus reflects a potential differential priming of immune cells in presence of the treatments, prior to the LPS trigger. The following observations were made: Pro-inflammatory TNF-a significantly decreased for all test products, except TB as such. In addition, pro-inflammatory CXCL-10 tended to decrease for all treatments, except TB / MB. TB tended to stimulate all the pro-inflammatory markers but also the anti-inflammatory marker IL-10 which was also stimulated by MB. SP exerted the strongest inhibitory effects on pro-inflammatory TNF-a / ILl-P along with IL-6 and the anti-inflammatory marker IL-10. Finally, correlation between cytokine / chemokine responses with microbial composition were established (OTU level (FIG. 49)). Fusicatenibacter saccharivorans (OTU18) and Mediterraneibacter torques (OTU39) negatively correlated with both IL-6 and the pro-inflammatory ILl-p. In contrast, OTUs related to Faecalibacterium prausnitzii. Mediterraneibacter butyricigenes. Lacrimispora. Phocaeicola dorei. Parabacteroides distasonis displayed the opposite trend. Besides, Lacrimispora (OTU76) positively correlated with IL-6 and both the antiinflammatory marker IL- 10 as well as the pro-inflammatory marker ILl-p.

[0320] The various exemplary experiments discussed above aimed to characterize the impact on the gut microbiota of IBS patients for a series of test products, i.e., triacetin (TA),tributyrin (TB) and three combinations thereof in different ratios, lysine-butyrate (LB), spermidine HC1 (SP), a mushroom blend (MB), fulvic acid (FA) and its combination with tributyrin. The impact on metabolite production (key fermentation parameters (pH, gas, SCFA, bCFA), metabolomics) and microbial composition (quantitative 16S rRNA gene profiling) was assessed, in some embodiments, at 24h after introduction of the test products in the colonic environment of IBS patients, as simulated with the ex vivo SIFR® technology.

[0321] In many embodiments of these experiments, eight different IBS patients were included in the study design as faecal donors, which is important since it has been established that there are marked interpersonal differences among the human population. Importantly, clinically relevant differences in faecal microbiome composition compared to a cohort of healthy adults were also observed, including significantly higher levels of Blautia spp. as well as Mediterraneibacter gnavus. This further confirmed that SIFR® technology can preserve clinically relevant dysbiosis of the gut microbiota. The high technical reproducibility of the SIFR® technology was demonstrated by the minor variation observed across technical replicates, i.e., the coefficient of variation (= SD / AVG) was on average 0.75% in various embodiments for analysis of key fermentation parameters. This very high technical reproducibility renders the SIFR® technology very sensitive to decipher changes in the human gut microbiome. An upper GIT passage was simulated in a pre-test for LB and encapsulated TA, TB and showed that 89.2% of TA but only 28.5% of TB and 3.3% LB could reach the colon.

[0322] Based on this, the doses using for SIFR® experiment of these three test products were calculated. After 24h of simulated colonic fermentation, TA significantly increased the levels of acetate, mainly due to hydrolysis of triacetin, as well as butyrate. The latter involved conversion of acetate to butyrate by butyrogenic taxa as well as fermentation of the glycerol backbone, resulting in increased abundance of butyrate-producing OTUs related to Faecalibacterium prausnitzii. Anaerobutyricum soehngenii as well as Mediterraneibacter A butyricigenes. On the other hand, TB only increased butyrate, mainly due to hydrolysis of tributyrin, and thus did not profoundly impact microbial composition. The effects on butyrate production were remarkably lower for TB, likely due to lower amount of TB delivered to the colon compared to TA. Thus, as expected, the higher the content of TA in TA: TB mixes, the stronger the stimulation of butyrate was. Interestingly, the increased butyrate production observed for TA / TB occurred at the expense of significantly lower propionate production. Aprevious clinical study demonstrated that microencapsulated sodium butyrate in a triglyceride matrix was effective in relieving the symptoms of IBS by modifying intestinal microbiota78. The results of the current study suggested that TA, due to its higher deliverability to the colon and stronger stimulation of butyrate compared to TB, could potentially even more effective in the treatment of IBS symptoms.

[0323] Particularly given that the SCFA stimulation was only accompanied by a minor gas production, thus, exhibited high tolerability for human consumption. Further, metabolomics analysis revealed that TA and TB had relatively mild effects on the production of metabolites other than SCFAs. This suggests that TA and TB can be used therapeutically to specifically target SCFA production without significantly altering the broader gut metabolic profile.

[0324] Among the other test products, LB also mildly (~ lower dose) increased butyrate production. On the other hand, both SP and FA mildly decreased acetate and butyrate as well as propionate (for SP). In addition, MB was well-fermented by the gut microbiota and exerted a positive impact on microbial diversity, as evidenced by its stimulatory effects on various taxa, including SCFA producers. In particular, MB displayed pronounced bifidogenic effects which correlated with a strong increase in acetate production. In addition, MB also stimulated various propionate-producing taxa in the phylum Bacteroidota as well as another propionogenic OTU from the phylum Bacillota A (Coprococcus A catus, leading to increased propionate production. Further, MB was also fermented by various butyrate producers in the families Lachnospiraceae and Ruminococcaceae, resulting in an elevated butyrate production. While increasing the production of and all three main SCFA, MB did not disproportionally increase gas production and thus, could also be well tolerated for consumption.

[0325] It is contemplated that a similar experimental setup may be used to study the effects of inulin (IN) on adults. When comparing the effects per gram of supplemented product to IN, TA is contemplated to produce higher levels of butyrate (+1.27 mM / g; 64% more), and total SCFA (+5.27 mM / g; 65% more) (FIG.50). MB produced comparable levels of butyrate (-0.05 mM / g; 6% less), but lower levels of total SCFA (-4.60 mM / g; 57% less). The lower total SCFA levels for MB might be due to the presence of other substrates beyond carbohydrates in MB (in contrast to inulin that is 100% carbohydrate). Nevertheless, despite its likely lower carbohydrate content, butyrate production is highly similar for MB compared to inulin. Finally, analysis of host-microbiota interaction demonstrated enhancing effects of TA, TB and MB on intestinal epithelial barrier before and after exposing to the potent inflammation inducer LPS.Importantly, this effect positively correlated with all the increased production of acetate and butyrate. In particular, butyrate is the primary energy source for colonocytes and thus in crucial for maintaining the health of the gut barrier. Besides its anti-inflammatory effects, gut-derived butyrate also interferes with oncogenic pathways and thus has been proposed as a promising therapeutic target for cancer treatments.

[0326] Altogether, triacetin, tributyrin and mushroom blend in various embodiments exhibited product-specific stimulation of the three main SCFA in the colonic environment, suggesting potential health benefits, e.g., by enhancing the gut epithelial barrier integrity. While tributyrin’s primary mode of action solely involved hydrolysis and release of butyrate, triacetin and mushroom blend also underwent thorough fermentation by the gut microbiota, thus profoundly impacting the microbial composition and promoting cross-feeding to induce SCFA production.

[0327] When assessing the impact of interventions on the gut microbiota, a-diversity indices are often used to obtain insights into community structure. Results of diversity indices should however be interpreted with caution. First, a-diversity indices can be based on species richness (e.g., observed number of species / OTUs and the Chaol diversity index) and / or evenness (e.g., reciprocal Simpson diversity and Shannon diversity index), two fundamentally different concepts. First, species richness is higher as more taxa are present. Second, evenness is higher as the dominant microbes are more evently distributed (e.g. when dominant microbes are present at similar levels = high index value <-> when specific microbes are highly abundant = low index value). As such, results obtained with one index cannot necessarily be compared with another index.

[0328] Further, while differences in cell density among microbial samples is key to obtain accurate insights into the gut microbiota (both in vivo and ex vivo), current diversity indices largely ignore such differences. The resulting inaccuracy is illustrated for two main scenarios. See FIG. 51. First, prebiotics that increase cell density (larger circle area in FIG. 51), and second, antibiotics that lower cell density (smaller circle area in FIG. 51). Given the similar sequencing depth among samples (illustrated by similar area of analyzed community fractions in FIG. 51, ), when products modulate cell density, they alter proportional sampling depth impact, and cause inaccurate insights into microbial diversity: Prebiotic lowers proportional sequencing depth, which can result in underestimation of diversity. Antibiotic increases proportional sequencing depth, which can result in overestimation of diversity. As such,moving away from relative composition analysis towards quantitative taxonomic analysis exposes limitations of traditional a-diversity indices. Variations in cell density are often overlooked, leading to an underestimated diversity in high-biomass samples.

[0329] More recently a new diversity index was introduced, the Community Modulation Score (CMS), which better captures the impact on diversity of test products that impact cell density. The CMS, rooted in quantitative sequencing, reflects the number of gut microbes that is supported (positive CMS (CMS+)) or suppressed (negative CMS (CMS-)) upon treatment. The sum of both values (overall CMS) reflects the net number of species that increasingly grew upon treatment: CMS > 0 results in product increased overall diversity. CMS < 0 results in product lowered overall diversity. Upon its introduction, the potential of this new approach allows one to discriminate between prebiotics. First, both the positive CMS and negative CMS were higher for dextran compared to inulin (IN), suggesting that more species are stimulated / less species are inhibited for dextran compared to inulin. As a result, the combined CMS was positive for dextran (average = 13.8) and negative for inulin (average = -12.7). In other words, inulin specifically increased a limited number of species that outcompeted a larger number of other gut microbes. Dextran increased microbial diversity, while inulin decreased it. See FIG. 52.

[0330] It is noted that those with low-fiber diets or various diseases characterized by gut dysbiosis such as irritable bowel syndrome, “leaky gut syndrome”, menopause, (age-related) dysbiosis, and / or other diseases may be deficient in naturally produced SCFAs. Therefore, the compositions disclosed herein may be particularly advantageous and / or beneficial to subjects with low-fiber diets or diseases that affect gut health. It is noted that, with regard to dysbiosis, the compositions described herein are contemplated to beneficial for patients having dysbiosis due to age, poor diet, stress, infections, chronic diseases, medications, genetics, environmental factors such as exposure to toxins, heavy metals, and pesticides, and other lifestyle habits such as lack of physical activity, smoking, alcohol consumption, etc., and / or any other cause of dysbiosis. Other conditions in which dysbiosis of the gut is prevalent include inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), leaky gut syndrome, inflammatory dysbiosis, or metabolic dysbiosis.

[0331] Common to most, if not all of these conditions, is the poor tolerance to insoluble fiber and / or probiotics. Insoluble fiber in the microbiome in such subjects ferments and causes significant gas production, leading to bloating, discomfort, and pain. Viewed from a differentperspective, it is contemplated that the compositions presented herein may advantageously provide not only SCFAs to the gut in individuals with low levels of SCFAs and high levels of gas, discomfort, and pain, but may also increase microbial diversity (especially bacteria that produce SCFAs). Triacetin and / or its combinations also stimulate microorganisms present in the gut to increase production of SCFAs (especially Mediterraneibacter butyricigenes and / or Anaerobutyricum soehngenii).

[0332] In further embodiments, it should be particularly appreciated that triacetin was able to significantly increase butyrate in the gut of dysbiotic subjects without substantial gas production. Such benefit is particularly desirable as many dysbiotic subjects tend to avoid fermentable fiber due to their propensity to produce substantial quantities of gas (as is, for example, well known for inulin).

[0333] It is further noted that individuals who suffer from conditions affecting the gut such as IBS are often advised to follow a low-FODMAP diet, which deliberately restricts fermentable carbohydrates, i.e. a diet low in fermentable oligosaccharides, disaccharides, monosaccharides and polyols, in an attempt to minimize colonic gas production and associated discomfort. As a result, their gut microbiome may produce reduced levels of short-chain fatty acids (SCFAs) due to the lower availability of fermentable fibers. This can also result in other side effects such as constipation and vitamin-deficiency. Therefore, there is a strong need for such individuals to have a composition that both boosts SCFA levels while not causing bloating or excessive gas production. Even more advantageous would be a composition that has these qualities and is also palatable, which is lacking in the prior art. Remarkably, the present invention addresses the long felt need in the art for such a composition.

[0334] Further, and as shown in FIG. 4, compositions comprising triacetin promote epithelial gut barrier integrity, both under non-stressed and stressed conditions.

[0335] Despite the advantages of orally administering triacetin over fermentable fibers or butyrate derivatives as a supplement for dysbiotic subjects, it is further contemplated that the orally administered supplement may further comprise additional nutritionally relevant compounds. For example, contemplated compositions may further comprise all butyrate derivatives (sodium butyrate, lysine-butyrate,...), fermentable fibers (resistant starches, polyphenols, fulvic acid, and / or prebiotic mushrooms or extracts or powders thereof. While no particular combination is preferred, it is generally preferred across all embodiments thattriacetin is the most important active ingredient with respect to increasing SCFA concentration and / or production. Still further, it is noted that the compositions presented herein may also include one or more probiotic or postbiotic (heat-treated probiotic) organisms that produce SCFAs and / or that use SCFAs as a nutrient. Moreover, contemplated compositions also modulated gut pH towards a less alkaline level, which is also favorable for a healthy gut microbiome.

[0336] In addition to the triacetin, it is further contemplated that nutritionally acceptable functional ingredients may be co-administered with the supplement. Most typically, this includes a probiotic strain. For example, the supplement may utilize a probiotic derived from the groups Lactobacillus, Bifidobacterium bacillus, Verrucomicrobia, Saccharomyces boulardii, Streptococcus, Enterococcus, and / or Escherichia. The inventor further contemplates that, in various embodiments, at least two nutritionally acceptable probiotic strains may be selected from the groups Lactobacillus, Bifidobacterium, Verrucomicrobia, tributyrincillus, Saccharomyces boulardii, Streptococcus, Enterococcus, and / or Escherichia. Alternatively, or additionally, other nutritionally acceptable functional ingredients may also be administered with the triacetin for further health benefits. For example, vitamin C, vitamin D, psyllium husk, apple cider vinegar, berberine, polyphenols, inulin, FOS, GOS, glutamine, prebiotics, B vitamins, zinc, magnesium, selenium, vitamin A, collagen, cinnamon, and / or turmeric. Depending on the accessibility of a given nutritionally acceptable functional ingredient, the additional ingredient may be contained within the same supplement, or it may be eaten contemporaneously with the supplement. However, not wishing to be bound by examples provided herein, different ingredients may also be used to stimulate growth and / or diversity of various intestinal commensal species.

[0337] The compositions and methods for administration of triacetin disclosed herein allow for a concentration of triacetin that weighs more than 30%, more than 40%, more than 50%, more than 60%, more than 70%, more than 80%, or more than 90% of the total composition. In further embodiments of the invention, inventor contemplates administering a composition containing triacetin wherein triacetin makes up less than 30% of the weight of the composition being administered, and in further embodiments wherein the remaining weight of the composition does not contain other active ingredients that affect gut microbiome health. Applicant additionally contemplates administering a composition containing triacetin wherein triacetin makes up at least roughly 25%, 20%, 15%, 10%, or even less of the total weight ofthe composition. As such, suitable percentages of the total weight of the composition consisting of triacetin therefore include 0.1-10%, 10-20%, 20-30%, 30-40%, and 40-50%.

[0338] It is further contemplated by the inventor that quantities of SCFAs available in the gut appeared to be most effectively improved at dosage on a mg per kg of body weight basis. However, it is also contemplated that some select indices of affect may be observed at 60 min post-ingestion. The inventor further contemplates that improvements in SCFA levels as well as various other select indices of affect in subjects treated with triacetin would be observed at 120 min, 180 min, 200 min, 220 min, 240 min, 260 min, 280 min, 300 min, 320 min, 330 min, 360 min, or in some cases even larger periods of time post-ingestion. As such, suitable periods of time before observing such improvements post-ingestion include 30-60 min, 60-90 min, 90-120 min, 120-150min, 150-180, min, 180-200 min, 200-220 min, 220-240 min, 240-260 min, 260-280 min, 280-300 min, 300-320 min, 320-340 min, 340-360 min, 360-380 min, 380-400 min, 400-500 min, 500-600 min, and even longer. However, in further embodiments, typical periods of time before observing aforementioned improvements will be less than 600 min, or less than 400 min, or less than 300 min, or less than 200 min, or less than 100 min, or less than 60 min post-ingestion.

[0339] While subjects in certain embodiments of the inventive subject matters experience improvements in SCFA levels as well as certain indices of affect at 180 min post-ingestion, the applicant contemplates that such improvements could be observed in less than 180 min postingestion. Applicant further contemplates that such improvements can be observed at 60 min, 70 min, 80 min, 90 min, 100 min, 110 min, 120 min, 130 min, 140 min, 150 min, 160 min, or 170 min post-ingestion. As such, suitable periods of time before observing such improvements post-ingestion include 60-80 min, 80-100 min, 100-120 min, 120-140 min, 140-160 min, 160-180 min, and even longer. However, in further embodiments, typical periods of time before observing aforementioned improvements will be more than 60 min, or more than 80 min, or more than 100 min, or more than 120 min, or more than 140 min, or more than 160 min, or more than 180 min post-ingestion.

[0340] It is further contemplated that the possible periods of time it will take after ingestion for triacetin to cause improvements in SCFA levels or gut microbiome health may be dependent on a subject’s metabolism and other factors, including age, muscle-to-fat ratio, amount of physical activity, hormone function, or other factors (such as CYP450 variants) that could affect metabolism.

[0341] It is further contemplated that triacetin administration may improve gut SCFA levels and / or gut microbiome health directly and / or indirectly. For example, triacetin may directly nurture the growth of beneficial bacteria in the gut, such as lactobacillus, bifidobacterium, akkermansia muciniphila, faecalibacterium prausnitzii, eubacterium rectale, and / or other helpful bacteria. Further, triacetin administration may directly inhibit the proliferation and / or activity of harmful bacteria such as Clostridium difficile, escherichia coli (pathogenic strains, salmonella enterica, staphylococcus aureus, helicobacter pylori, and any other harmful microorganisms. Triacetin may also indirectly improve gut microbiome health by increasing microbial diversity in the gut microbiome over time.

[0342] The inventor further contemplates that the subject receiving administration of the composition or compositions disclosed herein may be a human, pet, insect, or animal used in research or experimentation. Further, it should be appreciated that humans include people of all ages, including children, adults, and the elderly.1.9: Triacetin Effect on Gut Micriobiota of Obese Dogs

[0343] In an additional exemplary experiment, the inventor aimed to characterize the impact of triacetin on the gut of microbiota of obese dogs, microbiota of obese dogs. Using the ex vivo SIFR® technology, the impact on metabolite production (key fermentative parameters (pH, gas, SCFA, bCFA) and metabolomics) and microbial composition (shallow-shotgun sequencing) of the gut microbiota of 8 different animals was assessed (See FIG. 58) and compared against a no-substrate control (NSC).

[0344] A key function of the gut microbiota is to ferment carbohydrates (and to lesser extent proteins), resulting in the formation of short-chain fatty acids (SCFA). Acetate, propionate and butyrate are SCFA that have each been related with particular health benefits. Besides exerting anti-inflammatory effects, SCFA also decrease the pH of the colonic lumen which for instance increases mineral absorption and inhibits growth of pathogens. Acetate is a minor energy source for epithelial cells but reaches the portal vein after which it is metabolized in various tissues. Like acetate, propionate reaches the portal vein after which it is taken up by the liver. Health effects related to propionate include that it promotes satiety, lowers blood cholesterol, decreases liver lipogenesis and improves insulin sensitivity. Butyrate is the preferred energy source of epithelial cells and plays a protective role against colon cancer and colitis. As a result, preferable treatments stimulate acetate, propionate and butyrate production.Further, while valerate is much less studied than the other SCFA, it has also been demonstrated to decrease growth of cancer cells5 or to exert antipathogenic effects against C. difficile.

[0345] In contrast to aforementioned SCFA, bCFA are indicative of proteolytic fermentation, which is itself associated with formation of metabolites such as phenol and indole that exert detrimental health effects. On the other hand, there is also evidence that bCFA can be oxidized when butyrate is not available, thereby contributing to health benefits. In addition, a mix of bCFA (isobutyrate and isovalerate) is able to prevent gut permeability induced by pro-inflammatory cytokines in the Caco-2 cell line model.

[0346] Finally, while fermenting colonic substrates, the main gases that are produced are H2 and CO2. They can be further converted to other gases (CH4, H2S) but also to acetate. While fermentation by gut microbes (except Bifidobacteria) inevitably results in gas production, excessive gas production should be avoided as this can lead to abdominal pain or bloating.

[0347] On top of the core exemplary experimental design involving obese dogs, additional incubations were run for the sole purpose of quality control. This considered that NSC incubations at 24h were run in technical triplicate. Based on the analysis of pH and levels of three main SCFA (acetate, propionate and butyrate) for these replicates, it followed that the coefficient of variation (= standard deviation / average) was as low as 1.60%. This includes all variation related to the preparation of media / reactors up to final sample analysis via GC-FID / pH probes. The high reproducibility of the SIFR® platform makes it a sensitive tool to unravel the impact of test ingredients on the gut microbiome.

[0348] Upon analyzing key fermentative parameters (pH, gas production, SCFA and bCFA) at the end of the untreated NSC incubations (24h), it followed that microbial communities derived from each of the 8 animals resulted in diverse metabolic profiles (Table 1). The production of butyrate, produced by strictly anaerobic gut microbes further confirmed that the SIFR® experiment was performed under optimal conditions. Biological variation across the 8 animals was 16.38%, reflecting interindividual differences among different animals in vivo.

[0349] Regarding the high level observations, a PCA based on key fermentative parameters, as averaged across the 8 test subjects, provided comprehensive insight in overall effects since the first two components explained 100% of variation of the dataset (Figure 2A).The largest variations along PC1 (99.9%) were explained mainly by the impact of time. As the fermentation progressed, the 24h samples moved to the right side of the PCA and related to increased production of gases, bCFA, acetate, propionate and butyrate.

[0350] In addition, treatment effects of TA are mainly explained along PC2 (0.7% variation). TA shifted downwards along PC2 and specifically related to higher acetate and butyrate levels compared to NSC.

[0351] Finally, a PCA based on the individual values of each of the 8 animals at 24h (See FIG. 60) demonstrated that there were some interindividual differences between the animals. TA supplementation did not form a distinct cluster from NSC and could imply that the effects of TA were relatively mild compared to NSC. The PCA also displayed animal-specific effects, with samples of dogs 4 and 8 respectively positioning strongly upward and downward, relating to particularly high acetate and butyrate production for these specific animals.

[0352] In order to fully grasp the treatment effects at 24h, dedicated figures were made per fermentative parameter (See FIG. 61). Average values across 8 animals were ranked, with 1 corresponding to the highest value (highlighted with yellow dot), and 2 corresponding to the lowest value (highlighted with purple dot). ‘ * / ** / ***’ indicate the extent of the significance of a potential treatment effect versus the NSC.

[0353] Further, additional dot plots were generated to visualize effects of each test product on the key fermentative parameter as % of change compared to NSC, as averaged across all animals (See FIG. 62).

[0354] The treatment effects of triacetin were observed. Among all the key fermentative parameters that were measured during the current studies, triacetin significantly: decreased pH, increased acetate, and increased butyrate, which increased total SCFA. In contrast, no significant effects were observed for gas production, propionate and bCFA production.

[0355] Next, the observed SCFA production induced by adding TA was compared to theoretical amount of acetate that could be released from TA, assuming that fermentation of the glycerol backbone would not contribute to SCFA production (See FIG. 63). To account for the differing alkyl chain lengths in acetate, propionate, and butyrate, their production was normalized for the number of carbon atoms in each SCFA and expressed as acetate equivalents (Ac eq). The comparison demonstrated that observed acetate increases covered 76.6% of thetheoretical amount of acetate present in TA. When the impact on propionate and butyrate was taken into account, the total observed acetate equivalents corresponded to 105.0%, thus slightly exceeding the theoretical values. These values were similar, yet slightly lower compared to the one observed for humans in the previous project (91.5% and 123.2%, respectively).

[0356] Further, gas production was evaluated. Gases are typically produced in the pathways in which bacteria produce health-related SCFA. Excessive gas production is however to be avoided as this could lead to abdominal pain or bloating.

[0357] Hence, the relationship between gas production and total SCFA production is an interesting balance to assess the tolerability of a product (See FIG. 64). Since TA significantly increased total SCFA but not gas production, TA tended to reduce gas / SCFA ratio (-4.4% on average vs NSC, not significant). This observation aligns with the fact that most of acetate released from TA via hydrolysis of TA, a process that did not produce gas, unlike the fermentation of colonic substrates by gut microbes. It is noted that no other pre-biotic, probiotic, or post-biotic is known the cause such a dramatic increase in SCFAs while resulting in such low gas production.

[0358] To discuss the results of the exemplary experiment, the key taxonomic groups of the canine gut microbiome must be understood. The canine gut microbiota is characterized by relatively low diversity and a distinct composition compared to that of humans. One of the core components of the healthy canine microbiome is Fusobacterium, an acetate and butyrate producing genus belonging to the Fusobacteriota phylum. Fusobacterium species are highly efficient at degrading proteins into amino acids and peptides, aligning with the carnivorous diet of dogs. Fusobacterium abundance is influenced by age, with higher Fusobacterium levels for older dogs.

[0359] Another dominant phylum in the canine gut microbiota is Bacteroidota, which includes key producers of acetate and propionate. Among its members, Prevotella species, particularly Prevotella copri, are considered core gut bacteria of dogs. Higher abundances of P. copri have been associated with fiber- and carbohydrate-rich diets, such as commercial kibble, while reduced levels have been reported in atopic dogs. In addition to Prevotella, Phocaeicola species, also members of the family Bacteroidaceae, are notable contributors to acetate and propionate production in the canine gut.

[0360] Other major taxa in the core canine gut microbiota belong to the Bacillota phyla. Megamonas (family Selenomonadaceae), is another dominant acetate and propionate producing taxon of canine gut microbiota. Other important genera include Blautia, Streptococcus, Ruminococcus, and Faecalimonas, all of which support gut health through various metabolic activities, including short-chain fatty acid (SCFA) production.

[0361] While present in the canine gut microbiota, the phylum Actinomycetota comprises only a small proportion and is predominantly represented by acetate producing Collinsella spp., in contrast to humans where Bifidobacterium spp. are more prominent. A PCA at genus level (explaining a large portion of the variation (94.4%)) demonstrated that there were marked differences in microbial composition between the eight animals at baseline (See FIG. 65).

[0362] Most of the variation was explained along PCI (82.5%) and differentiated between dogs with high Prevotella (right: dogs 2, 4, 5 and 8) and low Prevotella (dogs 6 / 7). Dog 6’s microbiota was characterised by elevated levels of Phocaeicola and Faecalibacterium. On the other hand, dogs 1 and 7 exhibited a more even distribution of genera in the microbiota, with dog 7’s microbiota showing higher abundances of Megamonas, Enter ocloster, Ruminococcus B and Faecalimonas and dog 1 containing particularly high levels of Holdemanella and Faecalibacterium.

[0363] Overall, these first findings stress that the 8 animals included in this exemplary study as faecal donors covered the broad range of microbiota composition that occurs in vivo, thus ensuring representative findings.

[0364] For quality control, SIFR® accuracy and ex vivo nature were confirmed. The preservation of the in vzvo-derived microbiota and thus the minimal bias in microbiota composition during SIFR® studies is in contrast to consistent in vitro biases that have been observed for traditional long-term in vitro models and in recently developed short-term in vitro models, given that SIFR® studies adhere to ex vivo rather than in vitro simulation principles.

[0365] This was also confirmed during the current study upon comparing the original sample and the same sample incubated for 24h using the SIFR® technology. First, a diverse range of in vzvo-derived gut microbes endured the procedure over the 24h incubation period, maintaining the microbial diversity, both in terms of species richness (See FIG. 66A) and evenness (See FIG. 66B / C). Under control conditions (NSC), the total cell numbers increased from Oh (INO) to 24h with a factor of 3.51 (± 1.15) (See FIG. 66D). Importantly, at the end ofthe 24h NSC incubation, microbial composition reflected the original inoculum (INO) (See FIG. 66E)

[0366] In conclusion, this accurate preservation of in vzvo-derived microbiota for the entire duration of the experiment classifies the application of SIFR® technology as an ex vivo study, which is a study that uses an artificial environment outside the host with minimum alteration of natural conditions.

[0367] In addition, cell density and a-diversity were analyzed. Analysis of the total cell numbers across the different samples demonstrated that TA exhibited higher average total bacterial cell density (See FIG. 67A). However, the difference was not statistically significant due to interindividual differences in the response to TA.

[0368] Given these differences in cell numbers across study arms, it was of important to correct the proportional data obtained via sequencing (%) with the total cell counts in order to obtain insights into the true changes in microbial composition. The proportional abundances and the conversion of sequencing data using flow cytometry data is visualized at phylum level (See FIG. 67B / C). Subsequent data processing at higher taxonomic levels was thus performed based on the quantitative results.

[0369] This exploratory data visualization of microbial composition at phylum level showed that Bacteroidota, three Bacillota phyla, Pseudomonadota and Actinomycetota were the main phyla. On average, TA tended to increase Bacteroidota and Bacillota A, however, these effects were not statistically significant due to interindividual differences.

[0370] Four diversity indices were calculated to obtain optimal insights into microbial diversity (See FIG. 68). First, a new diversity score, i.e. the community modulation score (CMS), was recently developed by Cryptobiotix (See FIG. 68A). This index removes great part of the noise that is introduced when assessing diversity using traditional indices. In addition, traditional diversity indices were also calculated: while the Chaol diversity index is a measure of species richness (See FIG. 68B), the reciprocal Simpson diversity index / Shannon diversity index reflect also species evenness (See FIG. 68C / D). TA only significantly decreased Simpson diversity index and Shannon diversity index, indicating decreased diversity in term of species richness, but did not affect the CMS and Chaol index.

[0371] In an exploratory analysis of the treatment effects, PCA analysis was conducted based on the average results across the eight animals at Oh and 24h. Further, for optimal insights, the PCA was made at high phylogenetic resolution, i.e. based on the centered average levels of the most abundant species (See FIG. 69A / B).

[0372] The resulting PCA revealed strongest time-dependent effects between 0-24h observed along PCI (98.4% variations of the dataset), while the treatment effects of TA were mainly observed along PC2 which explained only 1.6% variations of the dataset. Overall, this indicates that the impact of TA on the composition of the canine gut microbiota was rather mild, in contrast to the previous observations in human microbiota (project P0173).

[0373] In a more in-depth analysis of the treatment effects, to gain insight in treatment effects at family and OTU level, all taxa that were significantly (padjusted < 0.05) and non- significantly but consistently affected were displayed in a heat map based on the average ratios versus the NSC (See FIG. 70A / B). Top 5 families and species with the largest variations based on the PCA analysis (section 3.5, Figure 10) were also included in the heat maps. A selection of relevant taxa will be highlighted along the text below via dedicated figures based on log2(fold change of treatment vs. NSC) and / or absolute abundances (in cells / mL). Further, log2(fold change of treatment vs. NSC) and absolute abundances (cells / mL) of all the most abundant families and OTUs are presented herein.

[0374] Further, at both taxonomic levels, a rCCA was performed to highlight correlations between key fermentative parameters and specific taxa (Figure 11C / D). In addition, pairwise correlation analysis using Spearman’s rank correlation coefficient were also performed with significant correlations also being highlighted in the figures. Owing to interpersonal differences and treatment effects, correlations could be established between specific metabolites and certain taxa, in line with known metabolic capabilities of these taxa.

[0375] Overall, no bacterial families and species were significantly affected by TA (padjusted < 0.05). At species level, only two species were consistently affected by TA (Slackia A piriformis and Thomasclavelia ramosd). Slackia piriformis increased specifically for donors 5 and 6. S. piriformis has been previously detected in canine microbiota, however, its role in canine health and SCFA production has not been investigated.

[0376] In addition to evaluating the taxa that were significantly and consistently impacted, the effects on other taxa were also examined. Especially, the small but significantly increasedbutyrate production with TA could be associated with various taxa, increasing in the microbiota of different dogs: Dorea B: increased for most dogs (except dog 8). Dorea has been reported to produce butyrate.

[0377] For dog 7, which exhibited the highest butyrate production in both NSC and TA study arm, a strong increase was noted for Blautia and Blautia A which contains several butyrogenic species. Blautia species are part of the Clostridium cluster XlVa that contains several butyrate-producing bacteria. Highest abundance of potent butyrate producer Faecalibacterium was also observed for these dogs compared to the other dogs. Dog 6 which exhibited the strongest induction of butyrate with TA (compared to NSC) exhibited high increases in butyrate-producing Fusobacterium A.

[0378] A total of 623 compounds was detected upon the LC-MS metabolomics analysis. As detailed herein, compounds in this exemplary experiment were annotated with three levels of identification. The number of compounds detected per level is listed in FIG.71. The absolute levels (in peak area, AUC) of all level 1 / 2a, level 2b and level 3 metabolites at 24h are discussed herein. Given the higher degree of certainty of correct annotation at level 1 and 2a, the analysis and interpretation focus on level 1 / 2a metabolites.

[0379] A quality control (QC) was performed by analysing QC samples, created by taking a small aliquot from each sample, with regular intervals throughout the analysis. As followed from the PC A based on the level 1 / 2a-annotated metabolites, these 10 QC samples grouped tightly together indicating that the biological variance (represented by the spread of the samples) largely exceeded the analytical variance (represented by the spread of QC samples) (See FIG. 72). The high reproducibility of both the SIFR® incubations as well as the metabolomics analysis warrants that observed differences are not due to technical variation.

[0380] The PCA provided comprehensive insight given that the first two components explained 49.6% of the variation of this reduced dataset (See FIG. 72). Based on the PCA, the following factors were the main factors driving changes in metabolite production. Regarding time, there was a marked differential clustering of Oh and 24h samples. As the incubation progressed, samples moved from the right to the left of the PCA, suggesting consumption of nutrients / production of specific metabolites between Oh and 24h. Regarding interindividual differences, these are mainly observed along PC2 (See FIG. 72B). The effects of TA onindividual dogs were illustrated by arrows. The PC A showed an overlap between NSC and TA clusters, suggesting that TA had minimal impact on metabolite production compared to NSC.

[0381] While the data was statistically processed at each annotation level, the current report focuses on 175 level 1 / 2a metabolites (ensuring correct annotation) and given that these metabolites have previously been linked with the gut microbiome (as nutrient or metabolite) often in the context of health or disease (See FIG. 73-76). A series of amino acids was efficiently consumed when comparing the 24h samples with those collected at Oh (INO). An efficient conversion of amino acids is of interest given the potential resulting production of health-related metabolites by the gut microbiota between 0-24h.

[0382] A series of amino acids was efficiently consumed when comparing the 24h samples with those collected at Oh (INO). An efficient conversion of amino acids is of interest given the potential resulting production of health-related metabolites by the gut microbiota between 0-24h.

[0383] Out of the 175 level 1 / 2a metabolites, the levels of 89 metabolites increased in at least 4 animals along 24h incubations. This suggest them to be of particular interest as they are (i) produced by canine-derived gut microbes or (ii) present in one of the test products.

[0384] Out of the aforementioned 89 metabolites, 11 metabolites were significantly affected (padjusted < 0.05) by at least one of the treatments. See FIG. 77. These significantly affected metabolites are presented in a heat map (based on the log2ratios versus the NSC; See FIG. 78). Further, in order to link the production of specific metabolites to specific microbial taxa, a correlation analysis was again performed between these significantly affected metabolites and compositional data (at family level and species level (See FIG. 79)). This revealed that correlations could be established between the presence of specific taxa and the production of specific metabolites. Statistical analysis was also performed for level 2b, and level 3 metabolites and the results are described herein.

[0385] Among the metabolites that were significantly affected, 4,6-dioxoheptanoic acid (or succinylacetone, SA) stood out for the very strong and specific increase upon treatment with triacetin. The increase was most pronounced for dog 4 > dog 1 / 3 / 5 / 7 > dog 2 / 6 / 8. The microbial production of SA and its impact on canine health has not been thoroughly investigated. However, research in humans has revealed that elevated levels of SA are associated with tyrosinemia type I. In this condition, the final step of tyrosine catabolism, which involves ahydrolase (FAH) converting fumarylacetoacetate to fumarate, is disrupted, resulting in the production of SA instead. Accumulation of SA levels can lead to liver and kidney dysfunctions and damages and trigger porphyria-like signs such as peripheral neuropathies.

[0386] Other significantly stimulated metabolites increased with very low fold changes (< 1.17-fold). On the other hand, three metabolites significantly decreased upon TA treatment, including kynurenic acid - a metabolite of tryptophan metabolism via the kynurenine pathway - and 3- oxo-7-hydroxychol-4-enoic which is produced through endogenous bile acid biosynthesis.

[0387] Similar to the previous study (P0173) in which the impact of triacetin was assessed in human microbiota, triacetin also significantly elevated acetate levels and stimulated butyrate production in the microbiota of obese dogs. In contrast to the previous study, triacetin did not significantly affect propionate production in the current study.

[0388] When comparing the % released acetate and total SCFA (compared to the theoretical value), respectively 76.6% and 105.0% was released, thus exceeding the theoretical values by 5.0%. The findings on the impact of TA on acetate and butyrate production were thus similar, yet milder in canine microbiota compared to the human microbiota (previous study P0173). For comparison, % released acetate was 91.5% and % released total SCFA (in acetate equivalents) was 123.2% for the human microbiota.

[0389] While direct evidence in canines is limited, increased acetate and butyrate production has been shown to benefit metabolic health in humans and several animal models. Acetate supplementation in rodents reduces body weight gain by up to 72% on high-fat diets, primarily by enhancing fat oxidation and suppressing lipid accumulation. Additionally, butyrate promotes "browning" of white adipose tissue and insulin sensitivity, thus increasing energy expenditure and metabolic rate. The preliminary findings suggest that triacetin supplementation is a promising strategy for weight management in obese dogs, thus improving their health and well-being.

[0390] The study found relatively low diversity in the eight canine microbiota samples. For comparison, the top 50 species covered 97.7% of the canine microbiota, compared to the previous human study (P0173) where the top 150 OTUs accounted for 96.8%. The present study also showed that the canine microbiota does not contain butyrate producers belonging to the Lachnospiraceae like Anaerobutyricum and Mediterraneibacter and had less prominentand consistent presence of Faecalibacterium. These taxa are an integral part of the human microbiota and increase butyrate production mainly through cross-feeding on metabolites such as acetate and lactate, which are produced by taxa like Bifidobacterium. Importantly, the P0173 study demonstrated that these taxa were promoted by TA and likely consumed acetate directly hydrolysed from TA to boost butyrate production without affecting Bifidobacterium species.

[0391] Major butyrate producers in canine microbiota such as Fusobacterium species are not as efficient or versatile in fibre fermentation as some other gut bacteria. Instead, they produce butyrate via alternative pathway, such as the lysine, the 2-hydroxyglutarate and the 4-aminobutyrate pathway where amino acids serve as major substrates, reflecting the rather carnivorous diet of dogs. The absence of butyrate producers commonly found in humans gut microbiota explains TA's minimal impact of on canine microbial composition, with the effects observed mostly for individual dogs and not significantly across the cohort.

[0392] As a remark, SA was identified at level 2a. Therefore, it is possible that an isomer with identical molecular weight and similar functional groups may be present in the samples instead of SA. Triacetin supplementation promoted acetate, largely due to hydrolysis of triacetin, without significantly / consistently affecting the microbial composition of obese dogs. Nevertheless, TA exerted stimulatory effects on certain taxa for individual dogs, likely contributing to the overall significant increase in butyrate levels. This increase in SCFA levels could potentially assist weight management, canine health and well-being.

[0393] Regarding the materials and methods, triacetin were tested at and animal equivalence dose (AED) of 150 mg / d against a no substrate control (before upper GIT simulation). This dose corresponds to 133.5 mg / d triacetin tested in the SIFR® colonic simulation.

[0394] A simulation of the oral phase and upper gastrointestinal tract (GIT) was performed to remove the digestible and absorbable fractions of triacetin. The upper GIT simulation was adapted from on procedure described by Van den Abbeele et al, 202342, with modifications for canine physiology. Based on the results of the upper GIT simulation, a corresponding dose of triacetin was chosen for the SIFR®.

[0395] An ex vivo SIFR® study was implemented, simulating the colonic fermentation of test products by the gut microbiota derived from medium-sized obese dogs (n = 8)7. The simulation parameters were as follows (FIG. 58): Study arms = 2, and time points = Oh (onlyNSC), 24h. As a remark, the NSC at 24h was run in technical triplicate per animal to demonstrate the high reproducibility of the SIFR® technology.

[0396] Colonic simulation was performed as described recently. Briefly, individual bioreactors were processed in parallel in a bioreactor management device. Each bioreactor contained 5 mL of nutritional medium-fecal inoculum blend supplemented with digested test products derived from the simulated small intestinal digestion protocol, then sealed individually, before being rendered anaerobic. Blend MOO 17 was used for preparation of the nutritional medium (Cryptobiotix, Ghent, Belgium). After preparation, bioreactors were incubated under continuous agitation (140 rpm) at 37 °C (MaxQ 6000, Thermo Scientific, Thermo Fisher Scientific, Merelbeke, Belgium). Upon gas pressure measurement in the headspace, liquid samples were collected for subsequent analysis.

[0397] Regarding timeline and analyses, the key fermentative parameters were pH, gas production, SCFA (acetate, propionate, butyrate), bCFA (isobutyrate, isovalerate and isocaproate), at Oh (only NSC), 6h and 24h (all test arms). The SCFA levels were also measured before the upper GIT simulation and after the gastric simulation and small intestinal simulation (FIG. 58). Microbial composition analysis (shallow shotgun sequencing) at Oh (NSC) and 24h (all test arms). The Metabolomics looked at (untargeted LC-MS / MS semi-polar analysis) at Oh (only NSC) and 24h (all test arms). Additional samples were collected for optional hostmicrobiota interaction analysis and other additional analysis at 24h (all test arms)

[0398] Concentrations of SCFAs and bCFAs were determined via gas chromatography with flame ionization detection (Trace 1300, Thermo Fisher Scientific) upon diethyl ether extraction as previously described43. pH was measured using a calibrated pH electrode (Hanna Instruments Edge HI2002, Temse, Belgium) and the accumulation of gases in the headspace was determined by a needle connected to a pressure meter as previously described.

[0399] To determine total counts, samples were diluted in anaerobic phosphate-buffered saline (PBS), followed by cell staining with SYTO 16 at a final concentration of 1 µM, and counted via a BD Novocyte Quanteon (Agilent). Data may be optionally analyzed using NovoExpress, version 1.6.2.

[0400] DNA extraction and sequencing analysis were performed as previously described. Briefly, DNA was extracted via the SPINeasy DNA Kit for Soil (MP Biomedicals, Eschwege, Germany), according to manufacturer’s instructions. A library was prepared using the NexteraXT DNA Library Preparation Kit (Illumina, San Diego, CA, USA) and IDT Unique Dual Indexes (total DNA input, 1 ng). A proportional amount of Illumina Nextera XT fragmentation enzyme was added to fragment genomic DNA. Libraries were constructed, purified, and quantified as previously described, then sequenced on an Illumina Nextseq 2000 platform 2 x 150 base pairs. The CosmosID-HUB Microbiome Platform (CosmosID Inc., Germantown, MD, USA) was used to convert unassembled sequencing reads to relative abundances (%) of taxa. Quantitative insights were obtained by correcting proportions (%) with total counts (cells / ml; flow cytometry), resulting in estimated cells / ml of different taxa.

[0401] Metabolomics analysis was performed as previously described. In brief, the analysis was carried out using a Vanquish UHPLC (Thermo Scientific, Germering, Germany) coupled to Orbitrap Exploris 240 MS (Thermo Scientific, Bremen, Germany) using an electrospray ionization source, applied both in negative and positive ionization mode. The UPLC was performed using a adapted version of the protocol described by Doneanu et al.. Peak areas were extracted using Compound Discoverer 3.3 (Thermo Scientific), along with a manual extraction based on an in-house library using Skyline 24.1 (MacCoss Lab Software).

[0402] Annotation of compounds was communicated at different confidence levels, i.e. level 1 (retention times (compared against in-house authentic standards), accurate mass (with an accepted deviation of 3 ppm) and MS / MS spectra), level 2a (retention times and accurate mass), level 2b (accurate mass and MS / MS spectra) and level 3 (accurate mass alone). Technical variability was confirmed by running a quality control sample (pooled aliquots of all samples) every six samples.

[0403] All multivariate and univariate analysis was performed using R, including violin plots, bar charts, heat maps, principal component analysis, statistical analysis and correlation analysis. Data are scaled to unit variance before running a principal component analysis (PC A). The two principal components with the largest eigenvalues are used for data visualization. For the statistical evaluation of the treatment effects on key fermentative parameters, cell counts, microbial diversity (4 indices) and microbial composition (phylum level), a linear mixed-effects model was implemented for each parameter, across 8 different animals. This approach accounts for both fixed effects (treatment) and random effects (individual variability). Statistical differences for selected pairwise comparisons from the statistical tests were visualized on the violin plots via * (0.01 < padjusted < 0.05), ** (0.001 < padjusted < 0.01) or *** (padjusted < 0.001) for TA vs NSC.

[0404] For the analysis of microbial composition, three measures were taken. First, a value of a given taxonomic group below the limit of quantification (LOQ) was considered equal to the overall LOQ. Second, a threshold was set to retain the most abundant species in the analysis. Third, the statistical analysis was performed on log2 -transformed values.

[0405] For the statistical evaluation of the treatment effects on microbial composition (family and species level) and metabolite production (metabolomics), a linear mixed-effects model was also applied. The Benjamini -Hochberg correction was applied to correct the p-value of overall treatment effect on one taxon / metabolite across all taxa / metabolites in the dataset. In addition, Regularized Canonical Correlation Analysis (rCCA) was performed for taxonomic changes and metabolite production.

[0406] As discussed throughout the present disclosure, SIFR® technology - Systemic Intestinal Fermentation Research -accommodates research questions at different preclinical stages of product development. This ex vivo simulation can be implemented either in screening mode or prism mode. The SIFR® in screening mode has been developed to evaluate a large number of test conditions (>100) and narrow down the number of product candidates for further in-depth evaluation. Meanwhile, the SIFR® in prism mode provides in-depth mechanistic characterization, including interindividual variation and analysis across omics to anticipate clinical variation and de-risk further product development. See FIG. 80 which provides an infographic about how gut health product development requires predictive data.

[0407] As shown in FIG. 81, SIFR® is predictive for in vivo changes in microbial composition. The translation of preclinical results to valid clinical outcomes remains an issue to this day. This “Valley of Death” is very present in gut microbiome research due to the intractability of gut microbiome interactions in vivo. The ex vivo SIFR® technology successfully predicted shifts in the gut microbiota composition observed in vivo across different interventions (inulin, resistant dextrin, 2’FL). This predictivity for clinical outcomes enables the quick generation of mechanistic hypotheses, while the high throughput of the technology embraces the inter-individual variation at the preclinical stage to de-risk clinical trials on the responder / non-responder question. Next to predictivity for changes in microbiota composition, the SIFR® technology has also shown to predict health benefits observed in clinical studies, such as gut barrier integrity. See FIG. 81. Moreover, SIFR® studies have also provided mechanistic insights into metabolite production that aligned with observations from in vivo studies (i.e. IP A; Carrot RG-I consistently stimulates IPA production).

[0408] The SIFR® technology has been applied herein for the investigation of a variety of products (i.e. complex food matrices (wholefoods), pre / pro / post- and synbiotics, sweeteners,...) in a wide range of populations (adults, children, infants, elderly; diseased or healthy), and hosts (human, cats, dogs, swine and poultry), in both small and large intestine.

[0409] In order to select the dose of TA used for the SIFR® colonic simulation, acetate release (expressed as % of the animal equivalent dose (AED)) were assessed along the simulated upper GIT. Overall, only a small portion of acetate was released along the upper GIT. See FIG. 82.

[0410] In some embodiments, the numbers expressing quantities of ingredients, properties such as concentration, reaction conditions, and so forth, used to describe and claim certain embodiments of the invention are to be understood as being modified in some instances by the term “about.” As used herein, the terms "about" and "approximately", when referring to a specified, measurable value (such as a parameter, an amount, a temporal duration, and the like), is meant to encompass the specified value and variations of and from the specified value, such as variations of + / -10% or less, alternatively + / -5% or less, alternatively + / -1% or less, alternatively + / -0.1% or less of and from the specified value, insofar as such variations are appropriate to perform in the disclosed embodiments. Thus, the value to which the modifier "about" or "approximately" refers is itself also specifically disclosed. The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein.

[0411] As used herein, the term “administering” a pharmaceutical composition or drug refers to both direct and indirect administration of the pharmaceutical composition or drug, wherein direct administration of the pharmaceutical composition or drug is typically performed by a health care professional (e.g., physician, nurse, etc.), and wherein indirect administration includes a step of providing or making available the pharmaceutical composition or drug to the health care professional for direct administration (e.g., via injection, infusion, oral delivery, topical delivery, etc.). It should further be noted that the terms “prognosing” or “predicting” a condition, a susceptibility for development of a disease, or a response to an intended treatment is meant to cover the act of predicting or the prediction (but not treatment or diagnosis of) the condition, susceptibility and / or response, including the rate of progression, improvement, and / or duration of the condition in a subject. Still further, it should be noted that where acomposition is “administered” to a subject and that subject is diagnosed with a disease or condition, such administration need not be done (or even be effective) for the treatment of the disease or condition, but that administration may support metabolism or physiology in the subject where such support may or may not alleviate a sign or symptom of the disease or condition.

[0412] All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g. “such as”) provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.

[0413] As used in the description herein and throughout the claims that follow, the meaning of “a,” “an,” and “the” includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of “in” includes “in” and “on” unless the context clearly dictates otherwise. As also used herein, and unless the context dictates otherwise, the term "coupled to" is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms "coupled to" and "coupled with" are used synonymously.

[0414] It should be apparent to those skilled in the art that many more modifications besides those already described are possible without departing from the inventive concepts herein. The inventive subject matter, therefore, is not to be restricted except in the scope of the appended claims. Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms “comprises” and “comprising” should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refers to at least one of something selected from the group consisting of A, B, C.... and N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.

Claims

AMENDED CLAIMSreceived by the International Bureau on 13 May 2026 (13.05.2026) What is claimed is:

1. A method of increasing the concentration of SCFAs in a gut of a subject, the method comprising:administering to the subject a composition comprising triacetin at a concentration of 100-1000 mg triacetin per 1-8 oz of the composition;wherein the composition further comprises a flavorant; andwherein the composition is palatable.

2. The method of claim 1, wherein the triacetin is introduced into the composition from a RTM composition.

3. The method of claim 1, wherein the triacetin is introduced into the composition from a RTD composition.

4. The method of any one of claims 1-3, wherein the administering is orally administering.

5. The method of any one of claims 1-4, wherein the triacetin is introduced into the composition in combination with a pharmaceutically or nutritionally acceptable carrier.

6. The method of any one of claims 1-5, wherein the triacetin is the sole active ingredient that increases the concentration of SCFAs of the subject.

7. The method of any one of claims 1-6, wherein administering the composition to the subject (1) improves health of the subject’s gut and / or oral microbiome, (2) improves the integrity of the subject’s gastrointestinal barrier, and / or (3) causes approximately 70% or more of the triacetin in the composition to reach the subject’s lower GI tract.

8. The method of any one of claims 1-7, wherein the composition has a score of 6.0 or higher on a 9-point hedonic scale.

9. The method of any one of claims 1-8, wherein the subject has a low-fiber diet.

10. The method of any one of claims 1-9, wherein the flavorant comprises citral, limonene, linalool, ethyl butyrate, isoamyl acetate, methyl anthranilate, hexyl acetate, ethyl 2- methylbutyrate, y-decalactone, 5-decalactone, orange oil, lemon oil, lime oil, bergamot oil, vanillin, ethyl vanillin, maltol, ethyl maltol, acetoin, diacetyl, menthol, menthyl lactate,WS-3, WS-23, ginger oil, cinnamon oil, clove oil, nutmeg oil, cardamom extract, green tea extract, apple extract, strawberry extract, grape extract, pineapple extract, mango extract, peach extract, coconut extract, raspberry ketone, ethyl acetate, propyl butyrate, benzaldehyde, y-nonalactone, 5-dodecalactone, ethyl maltol, linalyl acetate, citric acid, or a combination thereof.

11. The method of any one of claims 1-10, wherein the composition comprises a GLP-1 drink, a probiotic-containing drink, a prebiotic-containing drink, a fiber drink, a protein shake, a nutrition drink or a sports drink.

12. The method of any one of claims 1-11, wherein the composition further comprises a pH modifier.

13. The method of any one of claims 1-12, wherein the composition further comprises tributyrin.

14. The method of any one of claims 1-13, wherein the composition comprises 100 mg triacetin per 1-8 oz of the composition.

15. The method of any one of claims 1-14, wherein the triacetin is introduced into the composition from a soft chew or gummy composition for humans or animals.

16. A composition for increasing the concentration of SCFAs in a gut of a subject, comprising:triacetin at a concentration of 100-1000 mg triacetin per 1-8 oz of the composition; and a flavorant; andwherein the composition is palatable and wherein the increase in SCFA concentration occurs without an increase in gas production of more than 10%.

17. The composition of claim 16, wherein the composition is part of a RTM composition.

18. The composition of claim 16, wherein the composition is part of a RTD composition.

19. The composition of any one of claims 16-18, wherein the triacetin is the sole active ingredient that increases the concentration of SCFAs in the gut of the subject.

20. The composition of any one of claims 16-19, wherein the composition comprises 100 mg of triacetin per 1 oz.

21. A method of increasing a concentration of short chain fatty acids (SCFAs) in a gut of a dysbiotic subject without substantially increasing gas production in the dysbiotic subject, comprising:orally administering to the subject a composition comprising triacetin in combination with a pharmaceutically or nutritionally acceptable carrier;wherein the composition is administered in an amount effective to increase the concentration of SCFAs in the gut by at least 10% and gas production does not increase by more than 10% in the subject as compared to the concentration of SCFAs and gas production in the gut without administration of the composition.

22. The method of claim 21, wherein the dysbiotic subject is diagnosed with or suspected to have inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), leaky gut syndrome, inflammatory dysbiosis, excessive bloating, or metabolic dysbiosis.

23. The method of claim 21 or 22, wherein the dysbiotic subject has dysbiosis due to old age, perimenopause, menopause, or post-menopause.

24. The method of any one of claims 21-23, wherein the subject has a low-fiber or low- FODMAP diet.

25. The method of any one of claims 21-24, wherein butyrate and acetate account for a majority of the increased concentration of SCFAs in the gut.

26. The method of any one of claims 21-25, wherein upon oral administration, the concentration of SCFAs in the gut increases by at least 25% without substantial increase in gas production in the subject as compared to an SCFA concentration without oral administration.

27. The method of any one of claims 26, wherein upon oral administration, the concentration of SCFAs in the gut increases by at least 50% without substantial increase in gas production in the subject as compared to an SCFA concentration without oral administration.

28. The method of any one of claims 27, wherein the gas production does not increase by more than 10% as compared to gas production without oral administration when measured at 24 hours after oral administration.

29. The method of any one of claims 21-28, wherein the composition, upon oral administration, reduces pH in the gut by at least 0.2 pH units.

30. The method of any one of claims 21-29, wherein the increase in the concentration of SCFAs is observable at least 24 hours after oral administration.

31. The method of any one of claims 21-30, wherein the composition, upon oral administration, enhances growth of SCFA-producing gut microbes in the subject as compared to baseline of the subject without oral administration.

32. The method of any one of claims 21-31, wherein the SCFA-producing gut microbes comprise Mediterraneibacter butyricigenes and / or Anaerobutyricum soehngenii.

33. The method of any one of claims 21-32, wherein the composition, upon oral administration, enhances gut barrier integrity in the subject as compared to baseline of the subject without oral administration.

34. The method of any one of claims 21-33, wherein the composition is formulated as a capsule, a powder, a ready-to-drink, a gummy, a gel, a chew, a buccal pouch, and / or a tablet.

35. The method of any one of claims 21-34, wherein the composition further comprises tributyrin or other butyrate or acetate derivatives.

36. The method of any one of claims 21-35, wherein the composition is formulated as or in a ready-to-mix formulation, or wherein the composition is formulated as or in a ready-to- drink formulation.

37. The method of any one of claims 21-36, wherein the triacetin is the sole active ingredient that increases the concentration of SCFAs in the gut of the subject.

38. The method of any one of claims 21-37, wherein the composition further comprises a prebiotic fiber, optionally wherein the fiber is an insoluble fiber.

39. The method of claim 38, wherein the prebiotic fiber is a gum or is a mushroom fiber.

40. The method of claim 21, wherein the composition further comprises a probiotic or postbiotic (heat-treated probiotic) organism.

41. A composition for increasing the concentration of short chain fatty acids (SCFAs) in a gut of a dysbiotic subject, comprising:triacetin in combination with a pharmaceutically or nutritionally acceptable carrier and formulated for oral administration;wherein, upon oral administration, the concentration of SCFAs in the gut increases by at least 10% and gas production does not increase by more than 10% in the subject as compared to the concentration of SCFAs and gas production in the gut without administration of the composition.

42. The composition of claim 41, wherein the composition comprises between 50 mg and 500 mg of triacetin.

43. The composition of claim 41 or 42, wherein butyrate and acetate account for a majority of the increased concentration of SCFAs in the gut.

44. The composition of any one of claims 41-43, wherein upon oral administration, the concentration of SCFAs in the gut increases by at least 25% without substantial increase in gas production in the subject as compared to an SCFA concentration without oral administration.

45. The composition of any one of claims 41-44, wherein upon oral administration, the concentration of SCFAs in the gut increases by at least 50% without substantial increase in gas production in the subject as compared to an SCFA concentration without oral administration.

46. The composition of any one of claims 41-45, wherein the gas production does not increase by more than 10% as compared to gas production without oral administration when measured at 24 hours after oral administration.

47. The composition of any one of claims 41-46, wherein the composition, upon oral administration, reduces pH in the gut by at least 0.2 pH units.

48. The composition of any one of claims 41-47, wherein the increase in the concentration of SCFAs is observable at least 24 hours after oral administration.

49. The composition of any one of claims 41-48, wherein the composition, upon oral administration, enhances growth of SCFA-producing gut microbes in the subject as compared to baseline of the subject without oral administration.

50. The composition of claim 49, wherein the SCFA-producing gut microbes comprise Mediterraneibacter butyricigenes and Anaerobutyricum soehngenii.

51. The composition of any one of claims 41-50, wherein the composition, upon oral administration, enhances gut barrier integrity in the subject as compared to baseline of the subject without oral administration.

52. The composition of any one of claims 41-51, wherein the dysbiotic subject is diagnosed with or suspected to have inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), leaky gut syndrome, inflammatory dysbiosis, excessive bloating, or metabolic dysbiosis.

53. The composition of any one of claims 41-52, wherein the dysbiotic subject has dysbiosis due to old age, perimenopause, menopause, or post-menopause.

54. The composition of any one of claims 41-53, wherein the composition is formulated as a capsule, a powder, a ready-to-drink, a gummy, a gel, a chew, a buccal pouch, and / or a tablet.

55. The composition of any one of claims 41-54, wherein the composition further comprises tributyrin or other butyrate or acetate derivatives.

56. The composition of any one of claims 41-55, wherein the composition is formulated as or in a ready -to-mix formulation, or wherein the composition is formulated as or in a ready- to-drink formulation.

57. The composition of any one of claims 41-56, wherein the triacetin is the sole active ingredient that increases the concentration of SCFAs in the gut of the subject.

58. The composition of any one of claims 41-57, wherein the composition further comprises a prebiotic fiber, optionally wherein the fiber is an insoluble fiber.

59. The composition of claim 58, wherein the prebiotic fiber is a gum or is a mushroom fiber.

60. The composition of any one of claims 41-59, further comprising a probiotic or a postbiotic (heat-treated probiotic) organism.

61. A composition for increasing the concentration of short chain fatty acids (SCFAs) in a gut of a dysbiotic subject, comprising:triacetin in combination with a pharmaceutically or nutritionally acceptable carrier and formulated for oral administration;wherein the triacetin is at a concentration of 100-1000 mg triacetin per 1-8 oz of the composition;a flavorant;wherein, upon oral administration, the concentration of SCFAs in the gut increases by at least 10% and gas production does not increase by more than 10% in the subject as compared to the concentration of SCFAs and gas production in the gut without administration of the composition;wherein, upon oral administration, the concentration of SCFAs in the gut exceed an amount of SCFAs esterified within the triacetin; andwherein the composition is palatable.

62. The composition of claim 61, wherein the triacetin is at a concentration of 100 mg per 8 oz of the composition.

63. The composition of claim 61 or 62, wherein, upon oral administration, bloating in the subject will not increase by more than 10% as compared to bloating in the gut without administration of the composition.

64. The composition of any one of claims 61-63, wherein the composition is part of a RTM composition.

65. The composition of any one of claims 61-64, wherein the composition is part of a RTD composition.

66. The composition of any one of claims 61-65, wherein the triacetin is introduced into the composition from a soft chew or gummy composition for humans or animals.

67. The composition of any one of claims 61-66, further comprising tributyrin, lysine butyrate or any butyrate derivative.

68. The composition of any one of claims 61-67, further comprising a mushroom blend, resistant starch or any fiber or prebiotic that boosts SCFAs, or a combination thereof.

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