Home LiteratureArticle Details
PMID: 24763370 Published · ppublish English Journal Article Randomized Controlled Trial Research Support, Non-U.S. Gov't

Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men.

The ISME journal ·Vol. 8 ·No. 11 ·2014-11-00 ·Pages 2218-30

Salonen A, Lahti L, Salojärvi J, Holtrop G, Korpela K, Duncan SH, Date P, Farquharson F, Johnstone AM, Lobley GE, Louis P, Flint HJ, de Vos WM

Abstract

There is growing interest in understanding how diet affects the intestinal microbiota, including its possible associations with systemic diseases such as metabolic syndrome. Here we report a comprehensive and deep microbiota analysis of 14 obese males consuming fully controlled diets supplemented with resistant starch (RS) or non-starch polysaccharides (NSPs) and a weight-loss (WL) diet. We analyzed the composition, diversity and dynamics of the fecal microbiota on each dietary regime by phylogenetic microarray and quantitative PCR (qPCR) analysis. In addition, we analyzed fecal short chain fatty acids (SCFAs) as a proxy of colonic fermentation, and indices of insulin sensitivity from blood samples. The diet explained around 10% of the total variance in microbiota composition, which was substantially less than the inter-individual variance. Yet, each of the study diets induced clear and distinct changes in the microbiota. Multiple Ruminococcaceae phylotypes increased on the RS diet, whereas mostly Lachnospiraceae phylotypes increased on the NSP diet. Bifidobacteria decreased significantly on the WL diet. The RS diet decreased the diversity of the microbiota significantly. The total 16S ribosomal RNA gene signal estimated by qPCR correlated positively with the three major SCFAs, while the amount of propionate specifically correlated with the Bacteroidetes. The dietary responsiveness of the individual's microbiota varied substantially and associated inversely with its diversity, suggesting that individuals can be stratified into responders and non-responders based on the features of their intestinal microbiota.

MeSH Terms
Adult Aged Bacteria/classification,genetics,isolation & purification,metabolism Cross-Over Studies Diet, Reducing Fatty Acids, Volatile/analysis Feces/chemistry,microbiology Fermentation Humans Intestines/microbiology Male Metabolic Syndrome/diet therapy,microbiology Microbiota Middle Aged Obesity/diet therapy,microbiology Phylogeny
Chemicals
Fatty Acids, Volatile
Authors & Affiliations
13 authors, click to expand affiliations / ORCID
Salonen Anne
Immunobiology Research Program, Department of Bacteriology and Immunology, Haartman Institute, University of Helsinki, Helsinki, Finland.
Lahti Leo
1] Laboratory of Microbiology, Wageningen University, Wageningen, The Netherlands [2] Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland.
Salojärvi Jarkko
Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland.
Holtrop Grietje
Biomathematics and Statistics Scotland, Aberdeen, UK.
Korpela Katri
Immunobiology Research Program, Department of Bacteriology and Immunology, Haartman Institute, University of Helsinki, Helsinki, Finland.
Duncan Sylvia H
Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, UK.
Date Priya
Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, UK.
Farquharson Freda
Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, UK.
Johnstone Alexandra M
Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, UK.
Lobley Gerald E
Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, UK.
Louis Petra
Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, UK.
Flint Harry J
Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, UK.
de Vos Willem M
1] Immunobiology Research Program, Department of Bacteriology and Immunology, Haartman Institute, University of Helsinki, Helsinki, Finland [2] Laboratory of Microbiology, Wageningen University, Wageningen, The Netherlands [3] Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland.
References (41)
41 references, click to expand
  1. Structure, function and diversity of the healthy human microbiome.
    Nature. 2012 Jun 13;486(7402):207-14 PMID: 22699609
  2. Immuno-microbiota cross and talk: the new paradigm of metabolic diseases.
    Semin Immunol. 2012 Feb;24(1):67-74 PMID: 22265028
  3. Ruminococcus bromii is a keystone species for the degradation of resistant starch in the human colon.
    ISME J. 2012 Aug;6(8):1535-43 PMID: 22343308
  4. Fermentation in the human large intestine: its physiologic consequences and the potential contribution of prebiotics.
    J Clin Gastroenterol. 2011 Nov;45 Suppl:S120-7 PMID: 21992950
  5. Gut microbiota signatures predict host and microbiota responses to dietary interventions in obese individuals.
    PLoS One. 2014 Mar 06;9(6):e90702 PMID: 24603757
  6. Obesity and the gut microbiota.
    J Clin Gastroenterol. 2011 Nov;45 Suppl:S128-32 PMID: 21992951
  7. Diabetes, obesity and gut microbiota.
    Best Pract Res Clin Gastroenterol. 2013 Feb;27(1):73-83 PMID: 23768554
  8. High-protein, reduced-carbohydrate weight-loss diets promote metabolite profiles likely to be detrimental to colonic health.
    Am J Clin Nutr. 2011 May;93(5):1062-72 PMID: 21389180
  9. Linking long-term dietary patterns with gut microbial enterotypes.
    Science. 2011 Oct 7;334(6052):105-8 PMID: 21885731
  10. Microbial degradation of complex carbohydrates in the gut.
    Gut Microbes. 2012 Jul-Aug;3(4):289-306 PMID: 22572875
  11. Gut microbiota composition correlates with diet and health in the elderly.
    Nature. 2012 Aug 9;488(7410):178-84 PMID: 22797518
  12. The role of the gut microbiota in nutrition and health.
    Nat Rev Gastroenterol Hepatol. 2012 Sep 04;9(10):577-89 PMID: 22945443
  13. Comparative analysis of pyrosequencing and a phylogenetic microarray for exploring microbial community structures in the human distal intestine.
    PLoS One. 2009 Aug 20;4(8):e6669 PMID: 19693277
  14. Selective increases of bifidobacteria in gut microflora improve high-fat-diet-induced diabetes in mice through a mechanism associated with endotoxaemia.
    Diabetologia. 2007 Nov;50(11):2374-83 PMID: 17823788
  15. Faecal levels of Bifidobacterium and Clostridium coccoides but not plasma lipopolysaccharide are inversely related to insulin and HOMA index in women.
    Clin Nutr. 2013 Dec;32(6):1017-22 PMID: 23538004
  16. Integrative top-down system metabolic modeling in experimental disease states via data-driven Bayesian methods.
    J Proteome Res. 2008 Feb;7(2):497-503 PMID: 18179164
  17. Intake of whole-grain and fiber-rich rye bread versus refined wheat bread does not differentiate intestinal microbiota composition in Finnish adults with metabolic syndrome.
    J Nutr. 2013 May;143(5):648-55 PMID: 23514765
  18. Wheat bran affects the site of fermentation of resistant starch and luminal indexes related to colon cancer risk: a study in pigs.
    Gut. 1999 Dec;45(6):840-7 PMID: 10562582
  19. Insight into the prebiotic concept: lessons from an exploratory, double blind intervention study with inulin-type fructans in obese women.
    Gut. 2013 Aug;62(8):1112-21 PMID: 23135760
  20. In vitro characterization of the impact of selected dietary fibers on fecal microbiota composition and short chain fatty acid production.
    Anaerobe. 2013 Oct;23:74-81 PMID: 23831725
  21. A human gut microbial gene catalogue established by metagenomic sequencing.
    Nature. 2010 Mar 4;464(7285):59-65 PMID: 20203603
  22. Inter-individual differences in response to dietary intervention: integrating omics platforms towards personalised dietary recommendations.
    Proc Nutr Soc. 2013 May;72(2):207-18 PMID: 23388096
  23. Human gut microbiome viewed across age and geography.
    Nature. 2012 May 09;486(7402):222-7 PMID: 22699611
  24. Diet rapidly and reproducibly alters the human gut microbiome.
    Nature. 2014 Jan 23;505(7484):559-63 PMID: 24336217
  25. Gut microbiome composition is linked to whole grain-induced immunological improvements.
    ISME J. 2013 Feb;7(2):269-80 PMID: 23038174
  26. Development and application of the human intestinal tract chip, a phylogenetic microarray: analysis of universally conserved phylotypes in the abundant microbiota of young and elderly adults.
    Environ Microbiol. 2009 Jul;11(7):1736-51 PMID: 19508560
  27. Resistant starches types 2 and 4 have differential effects on the composition of the fecal microbiota in human subjects.
    PLoS One. 2010 Nov 29;5(11):e15046 PMID: 21151493
  28. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa.
    Proc Natl Acad Sci U S A. 2010 Aug 17;107(33):14691-6 PMID: 20679230
  29. Colonic bacterial metabolites and human health.
    Curr Opin Microbiol. 2013 Jun;16(3):246-54 PMID: 23880135
  30. Dominant and diet-responsive groups of bacteria within the human colonic microbiota.
    ISME J. 2011 Feb;5(2):220-30 PMID: 20686513
  31. Predicting a human gut microbiota's response to diet in gnotobiotic mice.
    Science. 2011 Jul 1;333(6038):101-4 PMID: 21596954
  32. Impact of short term consumption of diets high in either non-starch polysaccharides or resistant starch in comparison with moderate weight loss on indices of insulin sensitivity in subjects with metabolic syndrome.
    Nutrients. 2013 Jun 10;5(6):2144-72 PMID: 23752495
  33. Intestinal microbiota in healthy adults: temporal analysis reveals individual and common core and relation to intestinal symptoms.
    PLoS One. 2011;6(7):e23035 PMID: 21829582
  34. Reduced dietary intake of carbohydrates by obese subjects results in decreased concentrations of butyrate and butyrate-producing bacteria in feces.
    Appl Environ Microbiol. 2007 Feb;73(4):1073-8 PMID: 17189447
  35. Dietary intervention impact on gut microbial gene richness.
    Nature. 2013 Aug 29;500(7464):585-8 PMID: 23985875
  36. Interactions between gut microbiota, host genetics and diet relevant to development of metabolic syndromes in mice.
    ISME J. 2010 Feb;4(2):232-41 PMID: 19865183
  37. Polysaccharide utilization by gut bacteria: potential for new insights from genomic analysis.
    Nat Rev Microbiol. 2008 Feb;6(2):121-31 PMID: 18180751
  38. The capacity of short-chain fructo-oligosaccharides to stimulate faecal bifidobacteria: a dose-response relationship study in healthy humans.
    Nutr J. 2006 Mar 28;5:8 PMID: 16569219
  39. Effect of inulin on the human gut microbiota: stimulation of Bifidobacterium adolescentis and Faecalibacterium prausnitzii.
    Br J Nutr. 2009 Feb;101(4):541-50 PMID: 18590586
  40. Complete genome of a new Firmicutes species belonging to the dominant human colonic microbiota ('Ruminococcus bicirculans') reveals two chromosomes and a selective capacity to utilize plant glucans.
    Environ Microbiol. 2014 Sep;16(9):2879-90 PMID: 23919528
  41. Comparative analysis of fecal DNA extraction methods with phylogenetic microarray: effective recovery of bacterial and archaeal DNA using mechanical cell lysis.
    J Microbiol Methods. 2010 May;81(2):127-34 PMID: 20171997
Article Info
Journal
The ISME journal
Abbr.
ISME J
ISSN
1751-7370
Published
2014-11-00
Epub
2014-00-24
Pages
2218-30
Language
English
Region
England
NLM ID
101301086
PMCID
PMC4992075
Subset
IM
Analysis Services
Analysis Services

Contact

No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong

Qilu Normal University · Genelibs Bioinformatics Lab

750 Shunhua Rd, Jinan

2F, Bldg F, University Science Park

Tel: 0531-88819269

WeChat Official Account

Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.


Business Email

E-mail: product@genelibs.com