Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links Between Ecological and Metabolic Variation

Overview

Journal mSystems

Publisher American Society for Microbiology

Specialty Microbiology

Date 2016 May 31

PMID 27239563

Citations 106

Authors

Cecilia Noecker

Alexander Eng

Sujatha Srinivasan

Casey M Theriot

Vincent B Young

Janet K Jansson

David N Fredricks

Elhanan Borenstein

Affiliations

Soon will be listed here.

Abstract

Importance: Studies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.

Citing Articles

16S rRNA sequencing-based evaluation of the protective effects of key gut microbiota on inhaled allergen-induced allergic rhinitis.

Tang Y, She Y, Chen D, Zhou Y, Xie D, Liu Z Front Microbiol. 2025; 15():1497262.

PMID: 39850128 PMC: 11756352. DOI: 10.3389/fmicb.2024.1497262.

Advances in multi-omics integrated analysis methods based on the gut microbiome and their applications.

Duan D, Wang M, Han J, Li M, Wang Z, Zhou S Front Microbiol. 2025; 15():1509117.

PMID: 39831120 PMC: 11739165. DOI: 10.3389/fmicb.2024.1509117.

Glutamine Attenuates Inflammation and Stimulates Amniotic Cell Proliferation in Premature Rupture of Membranes-related in vitro Models.

Xiang X, Zhang L, Li S, Ren Y, Chen D, Liu L Reprod Sci. 2024; 32(3):854-866.

PMID: 39367233 PMC: 11870963. DOI: 10.1007/s43032-024-01691-9.

The role of selenium intervention in gut microbiota homeostasis and gene function in mice with breast cancer on a high-fat diet.

Li Y, Liu M, Kong B, Zhang G, Zhang Q Front Microbiol. 2024; 15:1439652.

PMID: 39144222 PMC: 11322145. DOI: 10.3389/fmicb.2024.1439652.

The impact of aquaculture system on the microbiome and gut metabolome of juvenile Chinese softshell turtle ().

Ding X, Jin F, Xu J, Zhang S, Chen D, Hu B Imeta. 2024; 1(2):e17.

PMID: 38868566 PMC: 10989827. DOI: 10.1002/imt2.17.

References

Greenblum S, Turnbaugh P, Borenstein E . Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease. Proc Natl Acad Sci U S A. 2011; 109(2):594-9. PMC: 3258644. DOI: 10.1073/pnas.1116053109. View

Smith C, OMaille G, Want E, Qin C, Trauger S, Brandon T . METLIN: a metabolite mass spectral database. Ther Drug Monit. 2006; 27(6):747-51. DOI: 10.1097/01.ftd.0000179845.53213.39. View

DeSantis T, Hugenholtz P, Larsen N, Rojas M, Brodie E, Keller K . Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006; 72(7):5069-72. PMC: 1489311. DOI: 10.1128/AEM.03006-05. View

Marcobal A, Kashyap P, Nelson T, Aronov P, Donia M, Spormann A . A metabolomic view of how the human gut microbiota impacts the host metabolome using humanized and gnotobiotic mice. ISME J. 2013; 7(10):1933-43. PMC: 3965317. DOI: 10.1038/ismej.2013.89. View

He B, Nohara K, Ajami N, Michalek R, Tian X, Wong M . Transmissible microbial and metabolomic remodeling by soluble dietary fiber improves metabolic homeostasis. Sci Rep. 2015; 5:10604. PMC: 4455235. DOI: 10.1038/srep10604. View

Kim Y, Nowack S, Olsen M, Becraft E, Wood J, Thiel V . Diel metabolomics analysis of a hot spring chlorophototrophic microbial mat leads to new hypotheses of community member metabolisms. Front Microbiol. 2015; 6:209. PMC: 4400912. DOI: 10.3389/fmicb.2015.00209. View

Langille M, Zaneveld J, Caporaso J, McDonald D, Knights D, Reyes J . Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol. 2013; 31(9):814-21. PMC: 3819121. DOI: 10.1038/nbt.2676. View

Daniel H, Gholami A, Berry D, Desmarchelier C, Hahne H, Loh G . High-fat diet alters gut microbiota physiology in mice. ISME J. 2013; 8(2):295-308. PMC: 3906816. DOI: 10.1038/ismej.2013.155. View

Taxis T, Wolff S, Gregg S, Minton N, Zhang C, Dai J . The players may change but the game remains: network analyses of ruminal microbiomes suggest taxonomic differences mask functional similarity. Nucleic Acids Res. 2015; 43(20):9600-12. PMC: 4787786. DOI: 10.1093/nar/gkv973. View

10.

Heinken A, Thiele I . Systematic prediction of health-relevant human-microbial co-metabolism through a computational framework. Gut Microbes. 2015; 6(2):120-30. PMC: 4615372. DOI: 10.1080/19490976.2015.1023494. View

11.

. Structure, function and diversity of the healthy human microbiome. Nature. 2012; 486(7402):207-14. PMC: 3564958. DOI: 10.1038/nature11234. View

12.

Cowan T, Palmnas M, Yang J, Bomhof M, Ardell K, Reimer R . Chronic coffee consumption in the diet-induced obese rat: impact on gut microbiota and serum metabolomics. J Nutr Biochem. 2014; 25(4):489-95. DOI: 10.1016/j.jnutbio.2013.12.009. View

13.

Waldor M, Tyson G, Borenstein E, Ochman H, Moeller A, Finlay B . Where next for microbiome research?. PLoS Biol. 2015; 13(1):e1002050. PMC: 4300079. DOI: 10.1371/journal.pbio.1002050. View

14.

Stefka A, Feehley T, Tripathi P, Qiu J, McCoy K, Mazmanian S . Commensal bacteria protect against food allergen sensitization. Proc Natl Acad Sci U S A. 2014; 111(36):13145-50. PMC: 4246970. DOI: 10.1073/pnas.1412008111. View

15.

Turnbaugh P, Ley R, Mahowald M, Magrini V, Mardis E, Gordon J . An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006; 444(7122):1027-31. DOI: 10.1038/nature05414. View

16.

Walker A, Pfitzner B, Neschen S, Kahle M, Harir M, Lucio M . Distinct signatures of host-microbial meta-metabolome and gut microbiome in two C57BL/6 strains under high-fat diet. ISME J. 2014; 8(12):2380-96. PMC: 4260703. DOI: 10.1038/ismej.2014.79. View

17.

Ishii N, Nakahigashi K, Baba T, Robert M, Soga T, Kanai A . Multiple high-throughput analyses monitor the response of E. coli to perturbations. Science. 2007; 316(5824):593-7. DOI: 10.1126/science.1132067. View

18.

Carr R, Borenstein E . Comparative analysis of functional metagenomic annotation and the mappability of short reads. PLoS One. 2014; 9(8):e105776. PMC: 4141809. DOI: 10.1371/journal.pone.0105776. View

19.

Lu K, Abo R, Schlieper K, Graffam M, Levine S, Wishnok J . Arsenic exposure perturbs the gut microbiome and its metabolic profile in mice: an integrated metagenomics and metabolomics analysis. Environ Health Perspect. 2014; 122(3):284-91. PMC: 3948040. DOI: 10.1289/ehp.1307429. View

20.

Holmes K, Chen K, Lipinski C, Eschenbach D . Vaginal redox potential in bacterial vaginosis (nonspecific vaginitis). J Infect Dis. 1985; 152(2):379-82. DOI: 10.1093/infdis/152.2.379. View