Multi-Omic Analyses Reveal Bifidogenic Effect and Metabolomic Shifts in Healthy Human Cohort Supplemented With a Prebiotic Dietary Fiber Blend

Jea Woo Kang, Xinyu Tang, Charles J Walton, Mark J Brown, Rachel A Brewer, Rolando L Maddela, Jack Jingyuan Zheng, Joanne K Agus, Angela M Zivkovic, Jea Woo Kang, Xinyu Tang, Charles J Walton, Mark J Brown, Rachel A Brewer, Rolando L Maddela, Jack Jingyuan Zheng, Joanne K Agus, Angela M Zivkovic

Abstract

Dietary fiber, a nutrient derived mainly from whole grains, vegetables, fruits, and legumes, is known to confer a number of health benefits, yet most Americans consume less than half of the daily recommended amount. Convenience and affordability are key factors determining the ability of individuals to incorporate fiber-rich foods into their diet, and many Americans struggle to access, afford, and prepare foods rich in fiber. The objective of this clinical study was to test the changes in microbial community composition, human metabolomics, and general health markers of a convenient, easy to use prebiotic supplement in generally healthy young participants consuming a diet low in fiber. Twenty healthy adults participated in this randomized, placebo-controlled, double-blind, crossover study which was registered at clinicaltrials.gov as NCT03785860. During the study participants consumed 12 g of a prebiotic fiber supplement and 12 g of placebo daily as a powder mixed with water as part of their habitual diet in randomized order for 4 weeks, with a 4-week washout between treatment arms. Fecal microbial DNA was extracted and sequenced by shallow shotgun sequencing on an Illumina NovaSeq. Plasma metabolites were detected using liquid chromatography-mass spectrometry with untargeted analysis. The phylum Actinobacteria, genus Bifidobacterium, and several Bifidobacterium species (B. bifidum, B. adolescentis, B. breve, B. catenulatum, and B. longum) significantly increased after prebiotic supplementation when compared to the placebo. The abundance of genes associated with the utilization of the prebiotic fiber ingredients (sacA, xfp, xpk) and the production of acetate (poxB, ackA) significantly changed with prebiotic supplementation. Additionally, the abundance of genes associated with the prebiotic utilization (xfp, xpk), acetate production (ackA), and choline to betaine oxidation (gbsB) were significantly correlated with changes in the abundance of the genus Bifidobacterium in the prebiotic group. Plasma concentrations of the bacterially produced metabolite indolepropionate significantly increased. The results of this study demonstrate that an easy to consume, low dose (12 g) of a prebiotic powder taken daily increases the abundance of beneficial bifidobacteria and the production of health-promoting bacteria-derived metabolites in healthy individuals with a habitual low-fiber diet.

Clinical trial registration: www.clinicaltrials.gov/, identifier: NCT03785860.

Keywords: bifidobacteria; cholines; gut microbiome; indolepropionate; prebiotic.

Conflict of interest statement

JK and AZ have received research support from USANA Health Sciences, Inc. CW, MB, RB, and RM are employees of USANA Health Sciences, Inc. These interests have been reviewed and managed by the University of California, Davis in accordance with its Conflict-of-Interest policies. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declare that this study received funding from USANA Health Sciences, Inc. The funder had the following involvement in the study: study conceptualization and manuscript review.

Copyright © 2022 Kang, Tang, Walton, Brown, Brewer, Maddela, Zheng, Agus and Zivkovic.

Figures

Figure 1
Figure 1
Study CONSORT diagram. Participants were recruited with screening, consent, and enrollment process. The treatment order was randomized into two groups, one group (red) supplemented with the placebo and the other group (green) supplemented with the prebiotic followed by a washout period and crossover to the other treatment for each group.
Figure 2
Figure 2
(A) Relative abundance of the gut microbiome at the phylum level and (B) the family level within the phylum Actinobacteria pre- and post-treatment with placebo or prebiotic. (C) Box plots of the genus Bifidobacterium counts pre- and post-treatment with placebo or prebiotic. (D–H) Box plots of Bifidobacterium species counts pre- and post-treatment with placebo or prebiotic (*P <0.05, **P < 0.01).
Figure 3
Figure 3
(A) Volcano plot of all detected genes. Genes with a logFC (post–pre treatment) > 0 and a –log(P-value) > 0.05 are colored blue and genes with a logFC <0 and a –log(P-value) > 0.05 are colored red. All the other genes are colored gray. (B–E) Box plot of gene counts pre- and post-treatment with placebo or prebiotic (P ≤ 0.05, unadjusted). (F–H) Correlation plot of changes (post–pre) in Bifidobacterium abundance against changes (post–pre) in gene counts for both placebo and prebiotic in 20 subjects (prebiotic: P ≤ 0.05, adjusted, Kendall T).
Figure 4
Figure 4
(A) Volcano plot of all metabolites in human plasma samples. Metabolites with a logFC > 0 and a –log(P-value) > 0.05 are colored blue and metabolites with a logFC <0 and a –log(P-value) > 0.05 are colored red. All the other metabolites are colored gray. (B–J) Box plots of IPA, TMAO, choline, and acylcholines concentrations pre- and post-treatment with placebo or prebiotic (unadjusted P-value).

References

    1. Kovatcheva-Datchary P, Nilsson A, Akrami R, Lee YS, De Vadder F, Arora T, et al. . Dietary fiber-induced improvement in glucose metabolism is associated with increased abundance of prevotella. Cell Metab. (2015) 22:971–82. 10.1016/j.cmet.2015.10.001
    1. Surampudi P, Enkhmaa B, Anuurad E, Berglund L. Lipid lowering with soluble dietary fiber. Curr Atheroscler Rep. (2016) 18:75. 10.1007/s11883-016-0624-z
    1. Jenkins DJA, Kendall CWC, Vuksan V, Vidgen E, Parker T, Faulkner D, et al. . Soluble fiber intake at a dose approved by the US Food and Drug Administration for a claim of health benefits: serum lipid risk factors for cardiovascular disease assessed in a randomized controlled crossover trial. Am J Clin Nutr. (2002) 75:834–9. 10.1093/ajcn/75.5.834
    1. Sonnenburg JL, Bäckhed F. Diet–microbiota interactions as moderators of human metabolism. Nature. (2016) 535:56–64. 10.1038/nature18846
    1. So D, Whelan K, Rossi M, Morrison M, Holtmann G, Kelly JT, et al. . Dietary fiber intervention on gut microbiota composition in healthy adults: a systematic review and meta-analysis. Am J Clin Nutr. (2018) 107:965–83. 10.1093/ajcn/nqy041
    1. Markowiak-Kopeć P, Slizewska K. The effect of probiotics on the production of short-chain fatty acids by human intestinal microbiome. Nutrients. (2020) 12:1107. 10.3390/nu12041107
    1. Desai MS, Seekatz AM, Koropatkin NM, Kamada N, Hickey CA, Wolter M, et al. . A dietary fiber-deprived gut microbiota degrades the colonic mucus barrier and enhances pathogen susceptibility. Cell. (2016) 167:1339–53.e21. 10.1016/j.cell.2016.10.043
    1. Ruiz L, Delgado S, Ruas-Madiedo P, Sánchez B, Margolles A. Bifidobacteria and their molecular communication with the immune system. Front Microbiol. (2017) 8:2345. 10.3389/fmicb.2017.02345
    1. Cani PD, Neyrinck AM, Fava F, Knauf C, Burcelin RG, Tuohy KM, et al. . Selective increases of bifidobacteria in gut microflora improve high-fat-diet-induced diabetes in mice through a mechanism associated with endotoxaemia. Diabetologia. (2007) 50:2374–83. 10.1007/s00125-007-0791-0
    1. Khokhlova EV, Smeianov VV, Efimov BA, Kafarskaia LI, Pavlova SI, Shkoporov AN. Anti-inflammatory properties of intestinal Bifidobacterium strains isolated from healthy infants. Microbiol Immunol. (2012) 56:27–39. 10.1111/j.1348-0421.2011.00398.x
    1. Lee WJ, Hase K. Gut microbiota–generated metabolites in animal health and disease. Nat Chem Biol. (2014) 10:416–24. 10.1038/nchembio.1535
    1. Tojo R, Suárez A, Clemente MG., de los Reyes-Gavilán CG, Margolles A, Gueimonde M, et al. . Intestinal microbiota in health and disease: role of bifidobacteria in gut homeostasis.s World J Gastroenterol. (2014) 20:15163–76. 10.3748/wjg.v20.i41.15163
    1. Rosalie Bliss,. Online Nutrition Resources at Your Fingertips. (2017). Available from: (accessed December 01, 2021).
    1. Clemens R, Kranz S, Mobley AR, Nicklas TA, Raimondi MP, Rodriguez JC, et al. . Filling America's fiber intake gap: summary of a roundtable to probe realistic solutions with a focus on grain-based foods. J Nutr. (2012) 142:1390S−401S. 10.3945/jn.112.160176
    1. Deehan EC, Walter J. The fiber gap and the disappearing gut microbiome: implications for human nutrition. Trends Endocrinol Metab. (2016) 27:239–42. 10.1016/j.tem.2016.03.001
    1. Storey M, Anderson P. Income and race/ethnicity influence dietary fiber intake and vegetable consumption. Nutr Res. (2014) 34:844–50. 10.1016/j.nutres.2014.08.016
    1. Hsiao B sek, Sibeko L, Troy LM. A systematic review of mobile produce markets: facilitators and barriers to use, and associations with reported fruit and vegetable intake. J Acad Nutr Diet. (2019) 119:76–97.e1. 10.1016/j.jand.2018.02.022
    1. Gibson GR, Hutkins R, Sanders ME, Prescott SL, Reimer RA, Salminen SJ, et al. . Expert consensus document: The International Scientific Association for Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of prebiotics. Nat Rev Gastroenterol Hepatol. (2017) 14:491–502. 10.1038/nrgastro.2017.75
    1. Liu F, Li P, Chen M, Luo Y, Prabhakar M, Zheng H, et al. . Fructooligosaccharide (FOS) and Galactooligosaccharide (GOS) increase bifidobacterium but reduce butyrate producing bacteria with adverse glycemic metabolism in healthy young population. Sci Rep. (2017) 7:11789. 10.1038/s41598-017-10722-2
    1. Ze X, Duncan SH, Louis P, Flint HJ. Ruminococcus bromii is a keystone species for the degradation of resistant starch in the human colon. ISME J. (2012) 6:1535–43. 10.1038/ismej.2012.4
    1. Salazar N, Dewulf EM, Neyrinck AM, Bindels LB, Cani PD, Mahillon J, et al. . Inulin-type fructans modulate intestinal Bifidobacterium species populations and decrease fecal short-chain fatty acids in obese women. Clin Nutr. (2015) 34:501–7. 10.1016/j.clnu.2014.06.001
    1. Cardelle-Cobas A, Corzo N, Olano A, Peláez C, Requena T, Ávila M. Galactooligosaccharides derived from lactose and lactulose: influence of structure on Lactobacillus, Streptococcus and Bifidobacterium growth. Int J Food Microbiol. (2011) 149:81–7. 10.1016/j.ijfoodmicro.2011.05.026
    1. Kang JW, Zivkovic AM. The potential utility of prebiotics to modulate Alzheimer's Disease: a review of the evidence. Microorganisms. (2021) 9:2310. 10.3390/microorganisms9112310
    1. Thangaraju M, Cresci GA, Liu K, Ananth S, Gnanaprakasam JP, Browning DD, et al. . GPR109A is a G-protein–coupled receptor for the bacterial fermentation product butyrate and functions as a tumor suppressor in colon. Cancer Res. (2009) 69:2826–32. 10.1158/0008-5472.CAN-08-4466
    1. Docampo MD, Stein-Thoeringer CK, Lazrak A, Burgos da Silva MD, Cross J, van den Brink MRM. Expression of the butyrate/niacin receptor, GPR109a on T cells plays an important role in a mouse model of graft versus host disease. Blood. (2018) 132(Suppl. 1):61. 10.1182/blood-2018-99-118783
    1. Singh N, Gurav A, Sivaprakasam S, Brady E, Padia R, Shi H, et al. . Activation of Gpr109a, receptor for niacin and the commensal metabolite butyrate, suppresses colonic inflammation and carcinogenesis. Immunity. (2014) 40:128–39. 10.1016/j.immuni.2013.12.007
    1. Kasubuchi M, Hasegawa S, Hiramatsu T, Ichimura A, Kimura I. Dietary gut microbial metabolites, short-chain fatty acids, and host metabolic regulation. Nutrients. (2015) 7:2839–49. 10.3390/nu7042839
    1. Ganapathy V, Thangaraju M, Prasad PD, Martin PM, Singh N. Transporters and receptors for short-chain fatty acids as the molecular link between colonic bacteria and the host. Curr Opin Pharmacol. (2013) 13:869–74. 10.1016/j.coph.2013.08.006
    1. Campos-Perez W, Martinez-Lopez E. Effects of short chain fatty acids on metabolic and inflammatory processes in human health. Biochim Biophys Acta BBA Mol Cell Biol Lipids. (2021) 1866:158900. 10.1016/j.bbalip.2021.158900
    1. Tan J, McKenzie C, Potamitis M, Thorburn AN, Mackay CR, Macia L. Chapter three - the role of short-chain fatty acids in health and disease. In: Alt FW. editor. Advances in Immunology. Academic Press (2014). p. 91–119.
    1. Sakurai T, Odamaki T, Xiao J. Production of indole-3-lactic acid by Bifidobacterium strains isolated fromhuman infants. Microorganisms. (2019) 7:340. 10.3390/microorganisms7090340
    1. Qi Q, Li J, Yu B, Moon JY, Chai JC, Merino J, et al. . Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies. Gut. (2021) 71:1095–105. 10.1136/gutjnl-2021-324053
    1. Zambrana LE, McKeen S, Ibrahim H, Zarei I, Borresen EC, Doumbia L, et al. . Rice bran supplementation modulates growth, microbiota and metabolome in weaning infants: a clinical trial in Nicaragua and Mali. Sci Rep. (2019) 9:13919. 10.1038/s41598-019-50344-4
    1. Simó C, García-Cañas V. Dietary bioactive ingredients to modulate the gut microbiota-derived metabolite TMAO. New opportunities for functional food development. Food Funct. (2020) 11:6745–76. 10.1039/D0FO01237H
    1. Baugh ME, Steele CN, Angiletta CJ, Mitchell CM, Neilson AP, Davy BM, et al. . Inulin supplementation does not reduce plasma trimethylamine N-oxide concentrations in individuals at risk for type 2 diabetes. Nutrients. (2018) 10:793. 10.3390/nu10060793
    1. Hiel S, Bindels LB, Pachikian BD, Kalala G, Broers V, Zamariola G, et al. . Effects of a diet based on inulin-rich vegetables on gut health and nutritional behavior in healthy humans. Am J Clin Nutr. (2019) 109:1683–95. 10.1093/ajcn/nqz001
    1. David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE, Wolfe BE, et al. . Diet rapidly and reproducibly alters the human gut microbiome. Nature. (2014) 505:559–63. 10.1038/nature12820
    1. Zhu C, Sawrey-Kubicek L, Beals E, Rhodes CH, Houts HE, Sacchi R, et al. . Human gut microbiome composition and tryptophan metabolites were changed differently by fast food and Mediterranean diet in 4 days: a pilot study. Nutr Res. (2020) 77:62–72. 10.1016/j.nutres.2020.03.005
    1. Lewis SJ, Heaton KW. Stool form scale as a useful guide to intestinal transit time. Scand J Gastroenterol. (1997) 32:920–4. 10.3109/00365529709011203
    1. Everhart JE, Go VL, Johannes RS, Fitzsimmons SC, Roth HP, White LR, et al. . longitudinal survey of self-reported bowel habits in the United States. Dig Dis Sci. (1989) 34:1153–62. 10.1007/BF01537261
    1. Tao Z, Raffel RA, Souid AK, Goodisman J. Kinetic studies on enzyme-catalyzed reactions: oxidation of glucose, decomposition of hydrogen peroxide and their combination. Biophys J. (2009) 96:2977–88. 10.1016/j.bpj.2008.11.071
    1. Yao P, Liu Z, Tung S, Dong Z, Liu L. Fully automated quantification of insulin concentration using a microfluidic-based chemiluminescence immunoassay. J Lab Autom. (2016) 21:387–93. 10.1177/2211068215578822
    1. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. (1972) 18:499–502. 10.1093/clinchem/18.6.499
    1. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnetjournal. (2011) 17:10–2. 10.14806/ej.17.1.200
    1. Prjibelski A, Antipov D, Meleshko D, Lapidus A, Korobeynikov A. Using SPAdes de novo assembler. Curr Protoc Bioinforma. (2020) 70:e102. 10.1002/cpbi.102
    1. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST quality assessment tool for genome assemblies. Bioinforma Oxf Engl. (2013) 29:1072–5. 10.1093/bioinformatics/btt086
    1. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinforma Oxf Engl. (2014) 30:2068–9. 10.1093/bioinformatics/btu153
    1. Al-Ghalith G, Knights D. BURST enables mathematically optimal short-read alignment for big data. Bioinformatics. (2020). 10.1101/2020.09.08.287128 Available online at:
    1. McMurdie PJ, Holmes S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. (2013) 8:e61217. 10.1371/journal.pone.0061217
    1. Zhao G, Nyman M, Jönsson JÅ. Rapid determination of short-chain fatty acids in colonic contents and faeces of humans and rats by acidified water-extraction and direct-injection gas chromatography. Biomed Chromatogr. (2006) 20:674–82. 10.1002/bmc.580
    1. Hatano T, Saiki S, Okuzumi A, Mohney RP, Hattori N. Identification of novel biomarkers for Parkinson's disease by metabolomic technologies. J Neurol Neurosurg Psychiatry. (2016) 87:295–301. 10.1136/jnnp-2014-309676
    1. Evans AM, Bridgewater BR, Liu Q, Mitchell MW, Robinson RJ, Dai H. High resolution mass spectrometry improves data quantity and Quality as Compared to Unit Mass Resolution Mass Spectrometry in High-Throughput Profiling Metabolomics. Metabolomics. (2014) 04(02):2153–0769. 10.4172/2153-0769.1000132
    1. DeHaven CD, Evans AM Dai H, Lawton KA. Organization of GC/MS and LC/MS metabolomics data into chemical libraries. J Cheminformatics. (2010) 2:9. 10.1186/1758-2946-2-9
    1. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. (2014) 15:550. 10.1186/s13059-014-0550-8
    1. Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. . Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. (2015) 43:e47. 10.1093/nar/gkv007
    1. Wu T, Hu E, Xu S, Chen M, Guo P, Dai Z, et al. . clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation. (2021) 2:100141. 10.1016/j.xinn.2021.100141
    1. Mevik BH, Wehrens R. The pls package: Principal component and partial least squares regression in R. J Stat Soft. (2007) 18:1–23. 10.18637/jss.v018.i02
    1. Kuhn M. The Caret Package. Available from: (accessed March 3, 2022).
    1. Nadeem H, Rashid MH, Siddique MH, Azeem F, Muzammil S, Javed MR, et al. . Microbial invertases: a review on kinetics, thermodynamics, physiochemical properties. Process Biochem. (2015) 50:1202–10. 10.1016/j.procbio.2015.04.015
    1. Roopashri AN, Varadaraj MC. Molecular characterization of native isolates of lactic acid bacteria, bifidobacteria and yeasts for beneficial attributes. Appl Microbiol Biotechnol. (2009) 83:1115–26. 10.1007/s00253-009-1991-y
    1. O'Callaghan A, van Sinderen D. Bifidobacteria and their role as members of the human gut microbiota. Front Microbiol. (2016) 7:925. 10.3389/fmicb.2016.00925
    1. Meile L, Rohr LM, Geissmann TA, Herensperger M, Teuber M. Characterization of the d-Xylulose 5-Phosphate/d-Fructose 6-Phosphate Phosphoketolase Gene (xfp) from Bifidobacterium lactis. J Bacteriol. (2001) 183:2929–36. 10.1128/JB.183.9.2929-2936.2001
    1. Devika NT, Raman K. Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models. Sci Rep. (2019) 9:18222. 10.1038/s41598-019-54696-9
    1. Dittrich CR, Bennett GN, San KY. Characterization of the acetate-producing pathways in Escherichia coli. Biotechnol Prog. (2005) 21:1062–7. 10.1021/bp050073s
    1. Vital M, Howe AC, Tiedje JM. Revealing the bacterial butyrate synthesis pathways by analyzing (meta)genomic data. mBio. 5:e00889–14. 10.1128/mBio.00889-14
    1. Pinhal S, Ropers D, Geiselmann J, de Jong H. Acetate metabolism and the inhibition of bacterial growth by acetate. J Bacteriol. 201:e00147–19. 10.1128/JB.00147-19
    1. Liu S, Buring JE, Sesso HD, Rimm EB, Willett WC, Manson JE, et al. . prospective study of dietary fiber intake and risk of cardiovascular disease among women. J Am Coll Cardiol. (2002) 39:49–56. 10.1016/S0735-1097(01)01695-3
    1. Anderson JW, Deakins DA, Floore TL, Smith BM, Whitis SE. Dietary fiber and coronary heart disease. Crit Rev Food Sci Nutr. (1990) 29:95–147. 10.1080/10408399009527518
    1. Lattimer JM, Haub MD. Effects of dietary fiber and its components on metabolic health. Nutrients. (2010) 2:1266–89. 10.3390/nu2121266
    1. Grooms KN, Ommerborn MJ, Pham DQ, Djoussé L, Clark CR. Dietary fiber intake and cardiometabolic risks among US adults, NHANES 1999-2010. Am J Med. (2013) 126:1059–67.e4. 10.1016/j.amjmed.2013.07.023
    1. Zhang C, Liu S, Solomon CG, Hu FB. Dietary fiber intake, dietary glycemic load, and the risk for gestational diabetes mellitus. Diabetes Care. (2006) 29:2223–30. 10.2337/dc06-0266
    1. Wei B, Liu Y, Lin X, Fang Y, Cui J, Wan J. Dietary fiber intake and risk of metabolic syndrome: A meta-analysis of observational studies. Clin Nutr. (2018) 37(6, Part A):1935–42. 10.1016/j.clnu.2017.10.019
    1. U.S. Department of Agriculture and U.S. Department of Health and Human Services . Dietary Guidelines for Americans, 2020–2025. 9th ed. Washington, DC: U.S Department of Agriculture. Available online at:
    1. Healey GR, Murphy R, Brough L, Butts CA, Coad J. Interindividual variability in gut microbiota and host response to dietary interventions. Nutr Rev. (2017) 75:1059–80. 10.1093/nutrit/nux062
    1. Salonen A, Lahti L, Salojärvi J, Holtrop G, Korpela K, Duncan SH, et al. . Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men. ISME J. (2014) 8:2218–30. 10.1038/ismej.2014.63
    1. Zhang C, Derrien M, Levenez F, Brazeilles R, Ballal SA, Kim J, et al. . Ecological robustness of the gut microbiota in response to ingestion of transient food-borne microbes. ISME J. (2016) 10:2235–45. 10.1038/ismej.2016.13
    1. Magne F, Abély M, Boyer F, Morville P, Pochart P, Suau A. Low species diversity and high interindividual variability in faeces of preterm infants as revealed by sequences of 16S rRNA genes and PCR-temporal temperature gradient gel electrophoresis profiles. FEMS Microbiol Ecol. (2006) 57:128–38. 10.1111/j.1574-6941.2006.00097.x
    1. Martínez I, Kim J, Duffy PR, Schlegel VL, Walter J. Resistant starches types 2 and 4 have differential effects on the composition of the fecal microbiota in human subjects. PLoS ONE. (2010) 5:e15046. 10.1371/journal.pone.0015046
    1. Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A, et al. . Personalized nutrition by prediction of glycemic responses. Cell. (2015) 163:1079–94. 10.1016/j.cell.2015.11.001
    1. Franco-Robles E, López MG. Implication of fructans in health: immunomodulatory and antioxidant mechanisms. Sci World J. (2015) 2015:289267. 10.1155/2015/289267
    1. Ramirez-Farias C, Slezak K, Fuller Z, Duncan A, Holtrop G, Louis P. Effect of inulin on the human gut microbiota: stimulation of Bifidobacterium adolescentis and Faecalibacterium prausnitzii. Br J Nutr. (2008) 101:541–50. 10.1017/S0007114508019880
    1. Healey G, Murphy R, Butts C, Brough L, Whelan K, Coad J. Habitual dietary fibre intake influences gut microbiota response to an inulin-type fructan prebiotic: a randomised, double-blind, placebo-controlled, cross-over, human intervention study. Br J Nutr. (2018) 119:176–89. 10.1017/S0007114517003440
    1. Gu J, Mao B, Cui S, Tang X, Liu Z, Zhao J, et al. . Bifidobacteria exhibited stronger ability to utilize fructooligosaccharides, compared with other bacteria in the mouse intestine. J Sci Food Agri. (2022) 102:2413–23. 10.1002/jsfa.11580
    1. Lincoln L, More SS. Bacterial invertases: occurrence, production, biochemical characterization, and significance of transfructosylation. J Basic Microbiol. (2017) 57:803–13. 10.1002/jobm.201700269
    1. Ryan SM, Fitzgerald GF, van Sinderen D. Transcriptional regulation and characterization of a novel β-fructofuranosidase-encoding gene from Bifidobacterium breve UCC2003. Appl Environ Microbiol. (2005) 71:3475–82. 10.1128/AEM.71.7.3475-3482.2005
    1. Ehrmann MA, Korakli M, Vogel RF. Identification of the gene for β-Fructofuranosidase of Bifidobacterium lactis DSM10140T and characterization of the enzyme expressed in Escherichia coli. Curr Microbiol. (2003) 46:0391–7. 10.1007/s00284-002-3908-1
    1. Goh YJ, Zhang C, Benson AK, Schlegel V, Lee JH, Hutkins RW. Identification of a putative operon involved in fructooligosaccharide utilization by Lactobacillus paracasei. Appl Environ Microbiol. (2006) 72:7518–30. 10.1128/AEM.00877-06
    1. Scott KP, Martin JC, Chassard C, Clerget M, Potrykus J, Campbell G, et al. . Substrate-driven gene expression in Roseburia inulinivorans: Importance of inducible enzymes in the utilization of inulin and starch. Proc Natl Acad Sci USA. (2011) 108(Suppl. 1):4672–9. 10.1073/pnas.1000091107
    1. Reid SJ, Abratt VR. Sucrose utilisation in bacteria: genetic organisation and regulation. Appl Microbiol Biotechnol. (2005) 67:312–21. 10.1007/s00253-004-1885-y
    1. Palframan RJ, Gibson GR, Rastall RA, Vriers D. Carbohydrate preferences of Bifidobacterium species isolated from the human gut. Curr Issues Intest Microbiol. (2003) 4:71–5.
    1. Rossi M, Corradini C, Amaretti A, Nicolini M, Pompei A, Zanoni S, et al. . Fermentation of Fructooligosaccharides and Inulin by Bifidobacteria: a comparative study of pure and fecal cultures. Appl Environ Microbiol. (2005) 71:6150–8. 10.1128/AEM.71.10.6150-6158.2005
    1. Margolles A, Sánchez B. Selection of a Bifidobacterium animalis subsp. lactis Strain with a Decreased Ability To Produce Acetic Acid. Appl Environ Microbiol. (2012) 78:3338–42. 10.1128/AEM.00129-12
    1. Wolfe AJ. The acetate switch. Microbiol Mol Biol Rev. (2005) 69:12–50. 10.1128/MMBR.69.1.12-50.2005
    1. Belenguer A, Duncan SH, Calder AG, Holtrop G, Louis P, Lobley GE, et al. . Two routes of metabolic cross-feeding between Bifidobacterium adolescentis and butyrate-producing anaerobes from the human gut. Appl Environ Microbiol. (2006) 72:3593–9. 10.1128/AEM.72.5.3593-3599.2006
    1. Bernal V, Castaño-Cerezo S, Cánovas M. Acetate metabolism regulation in Escherichia coli: carbon overflow, pathogenicity, and beyond. Appl Microbiol Biotechnol. (2016) 100:8985–9001. 10.1007/s00253-016-7832-x
    1. Morrison DJ, Mackay WG, Edwards CA, Preston T, Dodson B, Weaver LT. Butyrate production from oligofructose fermentation by the human faecal flora: what is the contribution of extracellular acetate and lactate? Br J Nutr. (2006) 96:570–7.
    1. Rey FE, Faith JJ, Bain J, Muehlbauer MJ, Stevens RD, Newgard CB, et al. . Dissecting the in vivo metabolic potential of two human gut acetogens *. J Biol Chem. (2010) 285:22082–90. 10.1074/jbc.M110.117713
    1. Nogal A, Louca P, Zhang X, Wells PM, Steves CJ, Spector TD, et al. . Circulating levels of the short-chain fatty acid acetate mediate the effect of the gut microbiome on visceral fat. Front Microbiol. (2021) 12:711359. 10.3389/fmicb.2021.711359
    1. Meyer D, Stasse-Wolthuis M. The bifidogenic effect of inulin and oligofructose and its consequences for gut health. Eur J Clin Nutr. (2009) 63:1277–89. 10.1038/ejcn.2009.64
    1. Belenguer A, Duncan SH, Holtrop G, Flint HJ, Lobley GE. Quantitative analysis of microbial metabolism in the human large intestine. Curr Nutr Food Sci. (2008) 4:109–26. 10.2174/157340108784245957
    1. Hsu YL, Chen CC, Lin YT, Wu WK, Chang LC, Lai CH, et al. . Evaluation and optimization of sample handling methods for quantification of short-chain fatty acids in human fecal samples by GC–MS. J Proteome Res. (2019) 18:1948–57. 10.1021/acs.jproteome.8b00536
    1. Gupta RS, Nanda A, Khadka B. Novel molecular, structural and evolutionary characteristics of the phosphoketolases from bifidobacteria and Coriobacteriales. PLoS ONE. (2017) 12:e0172176. 10.1371/journal.pone.0172176
    1. Mets FD, Melderen LV, Gottesman S. Regulation of acetate metabolism and coordination with the TCA cycle via a processed small RNA. Proc Natl Acad Sci U. S. A. (2019) 116:1043–52. 10.1073/pnas.1815288116
    1. Arzamasov AA, van Sinderen D, Rodionov DA. Comparative genomics reveals the regulatory complexity of bifidobacterial arabinose and arabino-oligosaccharide utilization. Front Microbiol. (2018) 9:776. 10.3389/fmicb.2018.00776
    1. Pokusaeva K, Fitzgerald GF, van Sinderen D. Carbohydrate metabolism in bifidobacteria. Genes Nutr. (2011) 6:285–306. 10.1007/s12263-010-0206-6
    1. Wang M, Chen Y, Wang Y, Li Y, Zhang X, Zheng H, et al. . Beneficial changes of gut microbiota and metabolism in weaned rats with Lactobacillus acidophilus NCFM and Bifidobacterium lactis Bi-07 supplementation. J Funct Foods. (2018) 48:252–65. 10.1016/j.jff.2018.07.008
    1. Wortmann SB, Mayr JA. Choline-related-inherited metabolic diseases—A mini review. J Inherit Metab Dis. (2019) 42:237–42. 10.1002/jimd.12011
    1. Zeisel SH, Warrier M. Trimethylamine N-oxide, the microbiome, and heart and kidney disease. Annu Rev Nutr. (2017) 37:157–81. 10.1146/annurev-nutr-071816-064732
    1. Day-Walsh P, Shehata E, Saha S, Savva GM, Nemeckova B, Speranza J, et al. . The use of an in-vitro batch fermentation (human colon) model for investigating mechanisms of TMA production from choline, l-carnitine and related precursors by the human gut microbiota. Eur J Nutr. (2021) 60:3987–99. 10.1007/s00394-021-02572-6
    1. Rath S, Heidrich B, Pieper DH, Vital M. Uncovering the trimethylamine-producing bacteria of the human gut microbiota. Microbiome. (2017) 5:54. 10.1186/s40168-017-0271-9
    1. Zhang C, Yin A, Li H, Wang R, Wu G, Shen J, et al. . Dietary modulation of gut microbiota contributes to alleviation of both genetic and simple obesity in children. EBioMedicine. (2015) 2:968–84. 10.1016/j.ebiom.2015.07.007
    1. Li Q, Wu T, Liu R, Zhang M, Wang R. Soluble dietary fiber reduces trimethylamine metabolism via gut microbiota and co-regulates host AMPK pathways. Mol Nutr Food Res. (2017) 61:1700473. 10.1002/mnfr.201700473
    1. Zarei I, C Oppel R, C Borresen E, J Brown R, P Ryan E. Modulation of plasma and urine metabolome in colorectal cancer survivors consuming rice bran. Integr Food Nutr Metab. (2019) 6:1–14. 10.15761/IFNM.1000252
    1. Zambrana LE, Weber AM, Borresen EC, Zarei I, Perez J, Perez C, et al. . Daily rice bran consumption for 6 months influences serum glucagon-like peptide 2 and metabolite profiles without differences in trace elements and heavy metals in weaning nicaraguan infants at 12 months of age. Curr Dev Nutr. (2021) 5:nzab101. 10.1093/cdn/nzab101
    1. Kinchen JM, Mohney RP, Pappan KL. Long-chain acylcholines link butyrylcholinesterase to regulation of non-neuronal cholinergic signaling. J Proteome Res. (2022) 21:599–611. 10.1021/acs.jproteome.1c00538
    1. Audet-Delage Y, Villeneuve L, Grégoire J, Plante M, Guillemette C. Identification of metabolomic biomarkers for endometrial cancer and its recurrence after surgery in postmenopausal women. Front Endocrinol. (2018) 9:87. 10.3389/fendo.2018.00087
    1. Zeleznik OA, Poole EM, Lindstrom S, Kraft P, Van Hylckama Vlieg A, Lasky-Su JA, et al. . Metabolomic analysis of 92 pulmonary embolism patients from a nested case–control study identifies metabolites associated with adverse clinical outcomes. J Thromb Haemost. (2018) 16:500–7. 10.1111/jth.13937
    1. Germain A, Barupal DK, Levine SM, Hanson MR. Comprehensive circulatory metabolomics in ME/CFS reveals disrupted metabolism of acyl lipids and steroids. Metabolites. (2020) 10:34. 10.3390/metabo10010034
    1. Heresi GA, Mey JT, Bartholomew JR, Haddadin IS, Tonelli AR, Dweik RA, et al. . Plasma metabolomic profile in chronic thromboembolic pulmonary hypertension. Pulm Circ. (2020) 10:2045894019890553. 10.1177/2045894019890553
    1. Akimov MG, Kudryavtsev DS, Kryukova EV, Fomina-Ageeva EV, Zakharov SS, Gretskaya NM, et al. . Arachidonoylcholine and other unsaturated long-chain acylcholines are endogenous modulators of the acetylcholine signaling system. Biomolecules. (2020) 10:283. 10.3390/biom10020283
    1. Tuomainen M, Lindström J, Lehtonen M, Auriola S, Pihlajamäki J, Peltonen M, et al. . Associations of serum indolepropionic acid, a gut microbiota metabolite, with type 2 diabetes and low-grade inflammation in high-risk individuals. Nutr Diabetes. (2018) 8:1–5. 10.1038/s41387-018-0046-9
    1. Zelante T, Iannitti RG, Cunha C, De Luca A, Giovannini G, Pieraccini G, et al. . Tryptophan catabolites from microbiota engage aryl hydrocarbon receptor and balance mucosal reactivity via interleukin-22. Immunity. (2013) 39:372–85. 10.1016/j.immuni.2013.08.003
    1. Shimada Y, Kinoshita M, Harada K, Mizutani M, Masahata K, Kayama H, et al. . Commensal bacteria-dependent indole production enhances epithelial barrier function in the colon. PLoS ONE. (2013) 8:e80604. 10.1371/journal.pone.0080604
    1. Hwang IK, Yoo KY Li H, Park OK, Lee CH, Choi JH, et al. . Indole-3-propionic acid attenuates neuronal damage and oxidative stress in the ischemic hippocampus. J Neurosci Res. (2009) 87:2126–37. 10.1002/jnr.22030
    1. Zhao ZH, Xin FZ, Xue Y, Hu Z, Han Y, Ma F, et al. . Indole-3-propionic acid inhibits gut dysbiosis and endotoxin leakage to attenuate steatohepatitis in rats. Exp Mol Med. (2019) 51:1–14. 10.1038/s12276-019-0304-5
    1. Negatu DA, Gengenbacher M, Dartois V, Dick T. Indole propionic acid, an unusual antibiotic produced by the gut microbiota, with anti-inflammatory and antioxidant properties. Front Microbiol. (2020) 11:2654. 10.3389/fmicb.2020.575586
    1. Cicero AFG, Derosa G, Bove M, Imola F, Borghi C, Gaddi AV. Psyllium improves dyslipidaemia, hyperglycaemia and hypertension, while guar gum reduces body weight more rapidly in patients affected by metabolic syndrome following an AHA Step 2 diet. Mediterr J Nutr Metab. (2010) 3:47–54. 10.1007/s12349-009-0056-1
    1. Gibb RD, McRorie JW Jr, Russell DA, Hasselblad V, D'Alessio DA. Psyllium fiber improves glycemic control proportional to loss of glycemic control: a meta-analysis of data in euglycemic subjects, patients at risk of type 2 diabetes mellitus, and patients being treated for type 2 diabetes mellitus. Am J Clin Nutr. (2015) 102:1604–14. 10.3945/ajcn.115.106989
    1. Chandalia M, Garg A, Lutjohann D, von Bergmann K, Grundy SM, Brinkley LJ. Beneficial effects of high dietary fiber intake in patients with type 2 diabetes mellitus. N Engl J Med. (2000) 342:1392–8. 10.1056/NEJM200005113421903
    1. Aller R, de Luis DA, Izaola O, La Calle F., del Olmo L, Fernandez L, et al. . Effect of soluble fiber intake in lipid and glucose leves in healthy subjects: a randomized clinical trial. Diabetes Res Clin Pract. (2004) 65:7–11. 10.1016/j.diabres.2003.11.005
    1. Kristensen M, Jensen MG, Aarestrup J, Petersen KE, Søndergaard L, Mikkelsen MS, et al. . Flaxseed dietary fibers lower cholesterol and increase fecal fat excretion, but magnitude of effect depend on food type. Nutr Metab. (2012) 9:8. 10.1186/1743-7075-9-8
    1. Crimarco A, Springfield S, Petlura C, Streaty T, Cunanan K, Lee J, et al. . A randomized crossover trial on the effect of plant-based compared with animal-based meat on trimethylamine-N-oxide and cardiovascular disease risk factors in generally healthy adults: Study With Appetizing Plantfood—Meat Eating Alternative Trial (SWAP-MEAT). Am J Clin Nutr. (2020) 112:1188–99. 10.1093/ajcn/nqaa203
    1. Brown L, Rosner B, Willett WW, Sacks FM. Cholesterol-lowering effects of dietary fiber: a meta-analysis. Am J Clin Nutr. (1999) 69:30–42. 10.1093/ajcn/69.1.30
    1. She J, Wong CC, Yu J. Targeted prebiotics alter the obese gut microbiome in humans. Signal Transduct Target Ther. (2021) 6:1–2. 10.1038/s41392-021-00758-2
    1. Delannoy-Bruno O, Desai C, Raman AS, Chen RY, Hibberd MC, Cheng J, et al. . Evaluating microbiome-directed fibre snacks in gnotobiotic mice and humans. Nature. (2021) 595:91–5. 10.1038/s41586-021-03671-4
    1. Costabile A, Deaville ER, Morales AM, Gibson GR. Prebiotic potential of a maize-based soluble fibre and impact of dose on the human gut microbiota. PLoS ONE. (2016) 11:e0144457. 10.1371/journal.pone.0144457
    1. Chung WSF, Walker AW, Bosscher D, Garcia-Campayo V, Wagner J, Parkhill J, et al. . Relative abundance of the Prevotella genus within the human gut microbiota of elderly volunteers determines the inter-individual responses to dietary supplementation with wheat bran arabinoxylan-oligosaccharides. BMC Microbiol. (2020) 20:283. 10.1186/s12866-020-01968-4

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