The gastrointestinal microbiome: a malleable, third genome of mammals

Carroll, Ian M.; Threadgill, David W.; Threadgill, Deborah S.

doi:10.1007/s00335-009-9204-7

Cited by 56 publications

(39 citation statements)

References 95 publications

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“…These findings are important for two reasons. First, they suggest that the methodology used in this study (TRFLP) was robust, since it produced values that approximated those that were previously determined by pyrosequencing (11,44,45). Second, they suggest that the microbiota of 8604-fed mice were likely eubiotic, as their microbiota composition was similar to other healthy mice that consumed complex rodent chows (45,46).…”

Section: Discussionmentioning

confidence: 54%

“…Second, they suggest that the microbiota of 8604-fed mice were likely eubiotic, as their microbiota composition was similar to other healthy mice that consumed complex rodent chows (45,46). It is important to note, however, that the proportion of Proteobacteria in 8604-fed ER␤ Ϫ/Ϫ mice (21.0%) was slightly higher than both their ER␤ ϩ/ϩ littermates (13.8%) and the upper limit (15%) that is typically reported in eubiotic microbiota derived from other healthy mice (44).…”

Section: Discussionmentioning

confidence: 65%

“…The relative abundance of fecal Bacteroidetes, Firmicutes, and Proteobacteria from 8604-fed mice agreed with findings from similar studies performed previously, as expected. Indeed, Proteobacteria usually comprise a very small proportion of the eubiotic microbiota in healthy mice (1 to 15%), whereas the Firmicutes (30 to 70%) and Bacteroidetes (10 to 40%) are typically more abundant by comparison (11,44). These findings are important for two reasons.…”

Section: Discussionmentioning

confidence: 99%

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Diet Complexity and Estrogen Receptor β Status Affect the Composition of the Murine Intestinal Microbiota

Menon

Watson

Thomas

et al. 2013

Appl Environ Microbiol

122

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Intestinal microbial dysbiosis contributes to the dysmetabolism of luminal factors, including steroid hormones (sterones) that affect the development of chronic gastrointestinal inflammation and the incidence of sterone-responsive cancers of the breast, prostate, and colon. Little is known, however, about the role of specific host sterone nucleoreceptors, including estrogen receptor ␤ (ER␤), in microbiota maintenance. Herein, we test the hypothesis that ER␤ status affects microbiota composition and determine if such compositionally distinct microbiota respond differently to changes in diet complexity that favor Proteobacteria enrichment. To this end, conventionally raised female ER␤ ؉/؉ and ER␤ ؊/؊ C57BL/6J mice (mean age of 27 weeks) were initially reared on 8604, a complex diet containing estrogenic isoflavones, and then fed AIN-76, an isoflavone-free semisynthetic diet, for 2 weeks. 16S rRNA gene surveys revealed that the fecal microbiota of 8604-fed mice and AIN-76-fed mice differed, as expected. The relative diversity of Proteobacteria, especially the Alphaproteobacteria and Gammaproteobacteria, increased significantly following the transition to AIN-76. Distinct patterns for beneficial Lactobacillales were exclusive to and highly abundant among 8604-fed mice, whereas several Proteobacteria were exclusive to AIN-76-fed mice. Interestingly, representative orders of the phyla Proteobacteria, Bacteroidetes, and Firmicutes, including the Lactobacillales, also differed as a function of murine ER␤ status. Overall, these interactions suggest that sterone nucleoreceptor status and diet complexity may play important roles in microbiota maintenance. Furthermore, we envision that this model for gastrointestinal dysbiosis may be used to identify novel probiotics, prebiotics, nutritional strategies, and pharmaceuticals for the prevention and resolution of Proteobacteria-rich dysbiosis.

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Section: Discussionmentioning

confidence: 54%

Section: Discussionmentioning

confidence: 65%

Section: Discussionmentioning

confidence: 99%

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Diet Complexity and Estrogen Receptor β Status Affect the Composition of the Murine Intestinal Microbiota

Menon

Watson

Thomas

et al. 2013

Appl Environ Microbiol

122

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“…In this process, microbiota have been positioned as a key point due to their relation with some diseases such as obesity 4 and metabolic syndrome 5 or in host defense. 6 The connection between the diet and microbiota is described in two ways: (i) food may have a prebiotic effect modulating the bacterial composition; 7,8 (ii) and behaving as a metabolic entity, producing metabolites derived from food consumption. 9 One of the diet components that have been associated with health benets through microbiota interaction is polyphenols.…”

Section: Introductionmentioning

confidence: 99%

High levels of Bifidobacteria are associated with increased levels of anthocyanin microbial metabolites: a randomized clinical trial

et al. 2014

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The health benefits associated with the consumption of polyphenol-rich foods have been studied in depth, however, the full mechanism of action remains unknown. One of the proposed mechanisms is through microbiota interaction. In the present study, we aimed to explore the relationship between changes in fecal microbiota and changes in urinary phenolic metabolites after wine interventions. Nine participants followed a randomized, crossover, controlled interventional trial. After the washout period, they received red wine, dealcoholized red wine or gin for 20 days each. Polyphenol metabolites (n > 60) in urine were identified and quantified by UPLC-MS/MS and the microbial content of fecal samples was quantified by real-time quantitative PCR. Interventions with both red wine and dealcoholized red wine increased the fecal concentration of Bifidobacterium, Enterococcus and Eggerthella lenta, compared to gin intervention and baseline. When participants were categorized in tertiles of changes in fecal bacteria, those in the highest tertile of Bifidobacteria had higher urinary concentration changes in syringic acid, pcoumaric acid, 4-hydroxybenzoic acid and homovanillic acid (all anthocyanin metabolites) than those in tertile 1 (P < 0.05, all). In addition, changes of Bifidobacteria correlated positively with changes of these metabolites (r ¼ 0.5-0.7, P < 0.05, all). Finally, the 68.5% changes in Bifidobacteria can be predicted by syringic acid and 4-hydroxybenzoic acid changes. This study confirms the important role of polyphenols as bacterial substrates and their modulatory capacity as an important field in the research of new products with prebiotic and probiotic characteristics for the food industry.

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“…A mechanistic insight into the assembly of the gut microbiota is immediately relevant to our understanding of complex human diseases (6). Obesity (7), coronary heart disease (8), diabetes (9), and inflammatory bowel disease (10) have all been associated with composition of gut microbiota.…”

mentioning

confidence: 99%

Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors

Benson

Kelly

Legge

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

1,102

986

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In vertebrates, including humans, individuals harbor gut microbial communities whose species composition and relative proportions of dominant microbial groups are tremendously varied. Although external and stochastic factors clearly contribute to the individuality of the microbiota, the fundamental principles dictating how environmental factors and host genetic factors combine to shape this complex ecosystem are largely unknown and require systematic study. Here we examined factors that affect microbiota composition in a large (n = 645) mouse advanced intercross line originating from a cross between C57BL/6J and an ICR-derived outbred line (HR). Quantitative pyrosequencing of the microbiota defined a core measurable microbiota (CMM) of 64 conserved taxonomic groups that varied quantitatively across most animals in the population. Although some of this variation can be explained by litter and cohort effects, individual host genotype had a measurable contribution. Testing of the CMM abundances for cosegregation with 530 fully informative SNP markers identified 18 host quantitative trait loci (QTL) that show significant or suggestive genomewide linkage with relative abundances of specific microbial taxa. These QTL affect microbiota composition in three ways; some loci control individual microbial species, some control groups of related taxa, and some have putative pleiotropic effects on groups of distantly related organisms. These data provide clear evidence for the importance of host genetic control in shaping individual microbiome diversity in mammals, a key step toward understanding the factors that govern the assemblages of gut microbiota associated with complex diseases.16S rDNA | pyrosequencing | quantitative trait loci mapping | microbiome phenotyping | population

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The gastrointestinal microbiome: a malleable, third genome of mammals

Cited by 56 publications

References 95 publications

Diet Complexity and Estrogen Receptor β Status Affect the Composition of the Murine Intestinal Microbiota

Diet Complexity and Estrogen Receptor β Status Affect the Composition of the Murine Intestinal Microbiota

High levels of Bifidobacteria are associated with increased levels of anthocyanin microbial metabolites: a randomized clinical trial

Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors

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