Characterization of metabolites and microbiota composition from human stool provides powerful insight into the molecular phenotypic difference between subjects with normal weight and those with overweight/obesity. The aim of this study was to identify potential metabolic and bacterial signatures from stool that distinguish the overweight/obesity state in children/adolescents. Using 1H NMR spectral analysis and 16S rRNA gene profiling, the fecal metabolic profile and bacterial composition from 52 children aged 7 to 16 was evaluated. The children were classified into three groups (16 with normal-weight, 17 with overweight, 19 with obesity). The metabolomic analysis identified four metabolites that were significantly different (p < 0.05) among the study groups based on one-way ANOVA testing: arabinose, butyrate, galactose, and trimethylamine. Significantly different (p < 0.01) genus-level taxa based on edgeR differential abundance tests were genus Escherichia and Tyzzerella subgroup 3. No significant difference in alpha-diversity was detected among the three study groups, and no significant correlations were found between the significant taxa and metabolites. The findings support the hypothesis of increased energy harvest in obesity by human gut bacteria through the growing observation of increased fecal butyrate in children with overweight/obesity, as well as an increase of certain monosaccharides in the stool. Also supported is the increase of trimethylamine as an indicator of an unhealthy state.

Department of Food Science Czech University of Life Sciences Prague Prague Czech Republic

Department of Medical Microbiology 2nd Faculty of Medicine Charles University Motol University Hospital Prague Czech Republic

Department of Paediatrics 2nd Faculty of Medicine Charles University Motol University Hospital Prague Czech Republic

Human Nutrition School of Medicine Dentistry and Nursing College of Medical Veterinary and Life Sciences University of Glasgow Glasgow Royal Infirmary Glasgow United Kingdom

Olivova Children's Medical Institution Říčany Czech Republic

Zobrazit více v PubMed

UNICEF. Children, food and nutrition: growing well in a changing world. 2019.

Zhao X, Gang X, Liu Y, Sun C, Han Q, Wang G. Using Metabolomic Profiles as Biomarkers for Insulin Resistance in Childhood Obesity: A Systematic Review. Journal of Diabetes Research. Hindawi Limited; 2016. 10.1155/2016/8160545 PubMed DOI PMC

Juonala M, Magnussen CG, Berenson GS, Venn A, Burns TL, Sabin MA, et al.. Childhood adiposity, adult adiposity, and cardiovascular risk factors. N Engl J Med. 2011;365: 1876–1885. 10.1056/NEJMoa1010112 PubMed DOI

Dietz WH. Health consequences of obesity in youth: Childhood predictors of adult disease. Pediatrics. 1998. pp. 518–525. PubMed

Vernocchi P, Del Chierico F, Putignani L. Gut microbiota profiling: Metabolomics based approach to unravel compounds affecting human health. Front Microbiol. 2016;7. 10.3389/fmicb.2016.01144 PubMed DOI PMC

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: 968–984. 10.1016/j.ebiom.2015.07.007 PubMed DOI PMC

Álvarez-Mercado AI, Navarro-Oliveros M, Robles-Sánchez C, Plaza-Díaz J, Sáez-Lara MJ, Muñoz-Quezada S, et al.. Microbial population changes and their relationship with human health and disease. Microorganisms. 2019;7. 10.3390/microorganisms7030068 PubMed DOI PMC

Riva A, Borgo F, Lassandro C, Verduci E, Morace G, Borghi E, et al.. Pediatric obesity is associated with an altered gut microbiota and discordant shifts in Firmicutes populations. Environ Microbiol. 2017;19: 95–105. 10.1111/1462-2920.13463 PubMed DOI PMC

Ley RE, Bäckhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc Natl Acad Sci U S A. 2005;102: 11070–11075. 10.1073/pnas.0504978102 PubMed DOI PMC

Le Chatelier E, Nielsen T, Qin J, Prifti E, Hildebrand F, Falony G, et al.. Richness of human gut microbiome correlates with metabolic markers. Nature. 2013;500: 541–546. 10.1038/nature12506 PubMed DOI

Radjabzadeh D, Boer CG, Beth SA, van der Wal P, Kiefte-De Jong JC, Jansen MAE, et al.. Diversity, compositional and functional differences between gut microbiota of children and adults. Sci Rep. 2020;10: 1–13. PubMed PMC

Zierer J, Jackson MA, Kastenmüller G, Mangino M, Long T, Telenti A, et al.. The fecal metabolome as a functional readout of the gut microbiome. Nat Genet. 2018;50: 790–795. 10.1038/s41588-018-0135-7 PubMed DOI PMC

Marcobal A, Kashyap PC, Nelson TA, Aronov PA, Donia MS, Spormann A, et al.. A metabolomic view of how the human gut microbiota impacts the host metabolome using humanized and gnotobiotic mice. ISME J. 2013;7: 1933–1943. 10.1038/ismej.2013.89 PubMed DOI PMC

Larive C, Barding G, Dinges M. NMR spectroscopy for metabolomics and metabolic profiling. Anal Chem. 2015;87: 133–146. 10.1021/ac504075g PubMed DOI

Markley J, Brüschweiler R, Edison A, Eghbalnia H, Powers R, Raftery D, et al.. The future of NMR-based metabolomics. Curr Opin Biotechnol. 2017;43: 34–40. 10.1016/j.copbio.2016.08.001 PubMed DOI PMC

Zhang A, Sun H, Wang P, Han Y, Wang X. Modern analytical techniques in metabolomics analysis. Analyst. 2012;137: 293–300. 10.1039/c1an15605e PubMed DOI

Rangel-Huerta OD, Pastor-Villaescusa B, Gil A. Are we close to defining a metabolomic signature of human obesity? A systematic review of metabolomics studies. Metabolomics. Springer US; 2019. 10.1007/s11306-019-1553-y PubMed DOI PMC

Newgard CB, An J, Bain JR, Muehlbauer MJ, Stevens RD, Lien LF, et al.. A Branched-Chain Amino Acid-Related Metabolic Signature that Differentiates Obese and Lean Humans and Contributes to Insulin Resistance. Cell Metab. 2009;9: 311–326. 10.1016/j.cmet.2009.02.002 PubMed DOI PMC

Santoru ML, Piras C, Murgia A, Palmas V, Camboni T, Liggi S, et al.. Cross sectional evaluation of the gut-microbiome metabolome axis in an Italian cohort of IBD patients. Sci Rep. 2017;7: 1–14. PubMed PMC

Státní zdravotní ústav (Czech National Institute of Public Health). Hodnocení růstu a vývoje dětí a mládeže, SZÚ (Evaluation of growth and development of children and youth, SZÚ). 2006. http://www.szu.cz/publikace/data/rustove-grafy

WHO | BMI-for-age (5–19 years). WHO. 2019.

Chong J, Yamamoto M, Xia J. MetaboAnalystR 2.0: From Raw Spectra to Biological Insights. Metabolites. 2019;9: 57. 10.3390/metabo9030057 PubMed DOI PMC

Chong J, Wishart DS, Xia J. Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis. Curr Protoc Bioinforma. 2019;68. 10.1002/cpbi.86 PubMed DOI

R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the miseq illumina sequencing platform. Appl Environ Microbiol. 2013;79: 5112–5120. 10.1128/AEM.01043-13 PubMed DOI PMC

Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13: 581–583. 10.1038/nmeth.3869 PubMed DOI PMC

Schliep KP. phangorn: phylogenetic analysis in R. Bioinforma Appl NOTE. 2011;27: 592–593. 10.1093/bioinformatics/btq706 PubMed DOI PMC

McMurdie PJ, Holmes S. Phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS One. 2013;8. 10.1371/journal.pone.0061217 PubMed DOI PMC

Dhariwal A, Chong J, Habib S, King IL, Agellon LB, Xia J. MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Res. 2017;45: W180–W188. 10.1093/nar/gkx295 PubMed DOI PMC

Chong J, Liu P, Zhou G, Xia J. Using MicrobiomeAnalyst for comprehensive statistical, functional, and meta-analysis of microbiome data. Nat Protoc. 2020;15: 799–821. 10.1038/s41596-019-0264-1 PubMed DOI

Morton JT, Marotz C, Washburne A, Silverman J, Zaramela LS, Edlund A, et al.. Establishing microbial composition measurement standards with reference frames. Nat Commun. 2019;10: 1–11. PubMed PMC

Mandal S, Van Treuren W, White RA, Eggesbø M, Knight R, Peddada SD. Analysis of composition of microbiomes: a novel method for studying microbial composition. Microb Ecol Heal Dis. 2015;26. PubMed PMC

Weiss S, Xu ZZ, Peddada S, Amir A, Bittinger K, Gonzalez A, et al.. Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome. 2017;5. 10.1186/s40168-017-0237-y PubMed DOI PMC

Thorsen J, Brejnrod A, Mortensen M, Rasmussen MA, Stokholm J, Al-Soud WA, et al.. Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies. Microbiome. 2016;4: 62. 10.1186/s40168-016-0208-8 PubMed DOI PMC

Jonsson V, Österlund T, Nerman O, Kristiansson E. Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics. BMC Genomics. 2016;17: 78. 10.1186/s12864-016-2386-y PubMed DOI PMC

ANCOM v2.1.

Friedman J, Alm EJ. Inferring Correlation Networks from Genomic Survey Data. PLoS Comput Biol. 2012;8: e1002687. 10.1371/journal.pcbi.1002687 PubMed DOI PMC

Li L. Infectious Microecology. Advanced Topics in Science and Technology in China. Springer; 2014. pp. 1–22. 10.1007/978-3-662-43883-1_1 DOI

Murugesan S, Nirmalkar K, Hoyo-Vadillo C, García-Espitia M, Ramírez-Sánchez D, García-Mena J. Gut microbiome production of short-chain fatty acids and obesity in children. European Journal of Clinical Microbiology and Infectious Diseases. Springer Verlag; 2018. pp. 621–625. 10.1007/s10096-017-3143-0 PubMed DOI

Lu Y, Fan C, Li P, Lu Y, Chang X, Qi K. Short chain fatty acids prevent high-fat-diet-induced obesity in mice by regulating g protein-coupled receptors and gut Microbiota. Sci Rep. 2016;6. 10.1038/srep37589 PubMed DOI PMC

Schwiertz A, Taras D, Schäfer K, Beijer S, Bos NA, Donus C, et al.. Microbiota and SCFA in Lean and Overweight Healthy Subjects. Obesity. 2010;18: 190–195. 10.1038/oby.2009.167 PubMed DOI

Turnbaugh P. J., Ley R. E., Mahowald M. A., Magrini V., Mardis E. R. Gordon J. I. et al.. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444: 1027–1031. 10.1038/nature05414 PubMed DOI

Payne AN, Chassard C, Zimmermann M, Müller P, Stinca S, Lacroix C. The metabolic activity of gut microbiota in obese children is increased compared with normal-weight children and exhibits more exhaustive substrate utilization. Nutr Diabetes. 2011;1: e12–e12. 10.1038/nutd.2011.8 PubMed DOI PMC

Kallus SJ, Brandt LJ. The intestinal microbiota and obesity. Journal of Clinical Gastroenterology. 2012. pp. 16–24. 10.1097/MCG.0b013e31823711fd PubMed DOI

Brahe LK, Astrup A, Larsen LH. Is butyrate the link between diet, intestinal microbiota and obesity-related metabolic diseases? 2013; 1–10. PubMed

Goffredo M, Mass K, Parks EJ, Wagner DA, McClure EA, Graf J, et al.. Role of gut microbiota and short chain fatty acids in modulating energy harvest and fat partitioning in youth. J Clin Endocrinol Metab. 2016;101: 4367–4376. 10.1210/jc.2016-1797 PubMed DOI PMC

Oliphant K, Allen-Vercoe E. Macronutrient metabolism by the human gut microbiome: Major fermentation by-products and their impact on host health. Microbiome. 2019;7: 1–15. PubMed PMC

Morrison DJ, Preston T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes. 2016;7: 189–200. 10.1080/19490976.2015.1134082 PubMed DOI PMC

Ríos-Covián D, Ruas-Madiedo P, Margolles A, Gueimonde M, De los Reyes-Gavilán CG, Salazar N. Intestinal short chain fatty acids and their link with diet and human health. Frontiers in Microbiology. Frontiers Media S.A.; 2016. 10.3389/fmicb.2016.00185 PubMed DOI PMC

Louis P, Hold GL, Flint HJ. The gut microbiota, bacterial metabolites and colorectal cancer. Nature Reviews Microbiology. Nature Publishing Group; 2014. pp. 661–672. 10.1038/nrmicro3344 PubMed DOI

Flint HJ, Duncan SH, Scott KP, Louis P. Links between diet, gut microbiota composition and gut metabolism. Proceedings of the Nutrition Society. Cambridge University Press; 2014. pp. 13–22. 10.1017/S0029665114001463 PubMed DOI

de la Cuesta-Zuluaga J, Mueller NT, Álvarez-Quintero R, Velásquez-Mejía EP, Sierra JA, Corrales-Agudelo V, et al.. Higher fecal short-chain fatty acid levels are associated with gut microbiome dysbiosis, obesity, hypertension and cardiometabolic disease risk factors. Nutrients. 2019;11. 10.3390/nu11010051 PubMed DOI PMC

Hjorth MF, Zohar Y, Hill JO, Astrup A. Personalized Dietary Management of Overweight and Obesity Based on Measures of Insulin and Glucose. Annu Rev Nutr. 2018;38: 245–272. 10.1146/annurev-nutr-082117-051606 PubMed DOI PMC

Vignoli A, Ghini V, Meoni G, Licari C, Takis PG, Tenori L, et al.. High-Throughput Metabolomics by 1D NMR. Angew Chemie—Int Ed. 2019;58: 968–994. 10.1002/anie.201804736 PubMed DOI PMC

Macfarlane GT, Macfarlane S. Bacteria, colonic fermentation, and gastrointestinal health. J AOAC Int. 2012;95: 50–60. 10.5740/jaoacint.sge_macfarlane PubMed DOI

Hansen NW, Sams A. The microbiotic highway to health—New perspective on food structure, gut microbiota, and host inflammation. Nutrients. MDPI AG; 2018. 10.3390/nu10111590 PubMed DOI PMC

Wang Z, Klipfell E, Bennett BJ, Koeth R, Levison BS, Dugar B, et al.. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature. 2011;472: 57–65. 10.1038/nature09922 PubMed DOI PMC

Zeisel SH, Mar M-H, Howe JC, Holden JM. Concentrations of Choline-Containing Compounds and Betaine in Common Foods. J Nutr. 2003;133: 1302–1307. 10.1093/jn/133.5.1302 PubMed DOI

Blaak EE, Canfora EE. Increased circulating choline, L-carnitine and TMAO levels are related to changes in adiposity during weight loss: role of the gut microbiota? Ann Transl Med. 2018;6: S92–S92. 10.21037/atm.2018.11.11 PubMed DOI PMC

Rath S, Heidrich B, Pieper DH, Vital M. Uncovering the trimethylamine-producing bacteria of the human gut microbiota. Microbiome. 2017;5: 1–14. PubMed PMC

Yan S, Huang J, Chen Z, Jiang Z, Li X, Chen Z. Metabolomics in gut microbiota: applications and challenges. Sci Bull. 2016;61: 1151–1153. 10.1007/s11434-016-1142-7 DOI

Gao X, Jia R, Xie L, Kuang L, Feng L, Wan C. Obesity in school-aged children and its correlation with Gut E.coli and Bifidobacteria: A case-control study. BMC Pediatr. 2015;15. 10.1186/s12887-015-0384-x PubMed DOI PMC

Liu Y, Ajami N, El-Serag H, Hair C, Graham D, White D. Dietary quality and the colonic mucosa-associated gut microbiome in humans. Am J Clin Nutr. 2019;110: 701–712. 10.1093/ajcn/nqz139 PubMed DOI PMC

Kelly TN, Bazzano LA, Ajami NJ, He H, Zhao J, Petrosino JF, et al.. Gut Microbiome Associates with Lifetime Cardiovascular Disease Risk Profile among Bogalusa Heart Study Participants. Circ Res. 2016;119: 956–964. 10.1161/CIRCRESAHA.116.309219 PubMed DOI PMC

Flegal KM, Troiano RP. Changes in the distribution of body mass index of adults and children in the US population. Int J Obes. 2000;24: 807–818. 10.1038/sj.ijo.0801232 PubMed DOI

Morales P, Fujio S, Navarrete P, Ugalde JA, Magne F, Carrasco-Pozo C, et al.. Impact of Dietary Lipids on Colonic Function and Microbiota: An Experimental Approach Involving Orlistat-Induced Fat Malabsorption in Human Volunteers. Clin Transl Gastroenterol. 2016;7: e161. 10.1038/ctg.2016.20 PubMed DOI PMC

Mutual Interactions of Silymarin and Colon Microbiota in Healthy Young and Healthy Elder Subjects

Gut metabolome and microbiota signatures predict response to treatment with exclusive enteral nutrition in a prospective study in children with active Crohn's disease

Faecal Bacteriome and Metabolome Profiles Associated with Decreased Mucosal Inflammatory Activity Upon Anti-TNF Therapy in Paediatric Crohn's Disease

Effects of Lactiplantibacillus plantarum and Lacticaseibacillus paracasei supplementation on the faecal metabolome in children with coeliac disease autoimmunity: a randomised, double-blinded placebo-controlled clinical trial