Dataset Information

Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome.

ABSTRACT: BACKGROUND:Grazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal's diet, we inferred a microbiome-level metabolic network from shotgun metagenomic data. RESULTS:Using comparative genomics, we then linked this microbial network to that of the host animal using a set of interface metabolites likely to be transferred to the host. When the host sheep were fed a grain-based diet, the induced microbial metabolic network showed several critical differences from those seen on the evolved forage-based diet. Grain-based (e.g., concentrate) diets tend to be dominated by a smaller set of reactions that employ metabolites that are nearer in network space to the host's metabolism. In addition, these reactions are more central in the network and employ substrates with shorter carbon backbones. Despite this apparent lower complexity, the concentrate-associated metabolic networks are actually more dissimilar from each other than are those of forage-fed animals. Because both groups of animals were initially fed on a forage diet, we propose that the diet switch drove the appearance of a number of different microbial networks, including a degenerate network characterized by an inefficient use of dietary nutrients. We used network simulations to show that such disparate networks are not an unexpected result of a diet shift. CONCLUSION:We argue that network approaches, particularly those that link the microbial network with that of the host, illuminate aspects of the structure of the microbiome not seen from a strictly taxonomic perspective. In particular, different diets induce predictable and significant differences in the enzymes used by the microbiome. Nonetheless, there are clearly a number of microbiomes of differing structure that show similar functional properties. Changes such as a diet shift uncover more of this type of diversity.

SUBMITTER: Wolff SM

PROVIDER: S-EPMC5465553 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome.

Wolff Sara M SM Ellison Melinda J MJ Hao Yue Y Cockrum Rebecca R RR Austin Kathy J KJ Baraboo Michael M Burch Katherine K Lee Hyuk Jin HJ Maurer Taylor T Patil Rocky R Ravelo Andrea A Taxis Tasia M TM Truong Huan H Lamberson William R WR Cammack Kristi M KM Conant Gavin C GC

Microbiome 20170608 1

<h4>Background</h4>Grazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal's diet, we inferred a microbiome-level metabolic network from shotgun metagenomic data.<h4>Results</h4>Using comparative genomics, we then linked this microbial network to that of the host animal using a set of interface metabolites likely to be transferred to the host. When th ...[more]

PMID: 28595639

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Project description:Subacute ruminal acidosis (SARA) negatively impacts the dairy industry by decreasing dry matter intake, milk production, profitability, and increasing culling rate and death loss. Six ruminally cannulated, lactating Holstein cows were used in a replicated incomplete Latin square design to determine the effects of SARA induction on the ruminal microbiome and epithelium. Experimental periods were 10 days with days 1-3 for ad libitum intake of control diet, followed by 50% feed restriction on day 4, and ad libitum access on day 5 to the basal diet or the basal diet with an additional 10% of a 50:50 wheat/barley pellet. Based on subsequent ruminal pH, cows were grouped (SARA grouping; SG) as Non-SARA or SARA based on time <5.6 pH (0 and 3.4 h, respectively). Ruminal samples were collected on days 1 and 6 of each period prior to feeding and separated into liquid and solid fractions. Microbial DNA was extracted for bacterial analysis using 16S rRNA gene paired-end sequencing on the MiSeq Illumina platform and quantitative PCR (qPCR). Ruminal epithelium biopsies were taken on days 1 and 6 before feeding. Quantitative RT-PCR was used to determine gene expression in rumen epithelium. Bray-Curtis similarity indicated samples within the liquid fraction separated by day and coincided with an increased relative abundance of genera Prevotella, Ruminococcus, Streptococcus, and Lactobacillus on day 6 (P < 0.06). Although Firmicutes was the predominant phyla in the solid fraction, a SG × day interaction (P < 0.01) indicated a decrease on day 6 for SARA cows. In contrast, phylum Bacteroidetes increased on day 6 (P < 0.01) for SARA cows driven by greater genera Prevotella and YRC22 (P < 0.01). Streptococcus bovis and Succinivibrio dextrinosolvens populations tended to increase on day 6 but were not affected by SG. In ruminal epithelium, CLDN1 and CLDN4 expression increased on day 6 (P < 0.03) 24 h after SARA induction and a tendency for a SG × day interaction (P < 0.10) was observed for CLDN4. Overall, results indicate more rapid adaptation to an induced bout of SARA in the solid fraction ruminal microbiome compared with ruminal epithelium.

Project description:BackgroundAdaptive shifts in gut microbiome composition are one route by which animals adapt to seasonal changes in food availability and diet. However, outside of dietary shifts, other potential environmental drivers of gut microbial composition have rarely been investigated, particularly in organisms living in their natural environments.ResultsHere, we generated the largest wild nonhuman primate gut microbiome dataset to date to identify the environmental drivers of gut microbial diversity and function in 758 samples collected from wild Ethiopian geladas (Theropithecus gelada). Because geladas live in a cold, high-altitude environment and have a low-quality grass-based diet, they face extreme thermoregulatory and energetic constraints. We tested how proxies of food availability (rainfall) and thermoregulatory stress (temperature) predicted gut microbiome composition of geladas. The gelada gut microbiome composition covaried with rainfall and temperature in a pattern that suggests distinct responses to dietary and thermoregulatory challenges. Microbial changes were driven by differences in the main components of the diet across seasons: in rainier periods, the gut was dominated by cellulolytic/fermentative bacteria that specialized in digesting grass, while during dry periods the gut was dominated by bacteria that break down starches found in underground plant parts. Temperature had a comparatively smaller, but detectable, effect on the gut microbiome. During cold and dry periods, bacterial genes involved in energy, amino acid, and lipid metabolism increased, suggesting a stimulation of fermentation activity in the gut when thermoregulatory and nutritional stress co-occurred, and potentially helping geladas to maintain energy balance during challenging periods.ConclusionTogether, these results shed light on the extent to which gut microbiota plasticity provides dietary and metabolic flexibility to the host, and might be a key factor to thriving in changing environments. On a longer evolutionary timescale, such metabolic flexibility provided by the gut microbiome may have also allowed members of Theropithecus to adopt a specialized diet, and colonize new high-altitude grassland habitats in East Africa. Video abstract.

Project description:ObjectiveThe gut microbiota is an important influencing factor of metabolic health. Although dietary interventions with probiotics, prebiotics, and synbiotics can be effective means to regulate obesity and associated comorbidities, the underlying shifts in gut microbial communities, especially at the functional level, have not been characterized in great details. In this study, we sought to investigate the effects of synbiotics on the regulation of gut microbiota and the alleviation of high-fat diet (HFD)-induced metabolic disorders in mice.MethodsSpecific pathogen-free (SPF) male C57BL/6J mice were fed diets with either 10% (normal diet, ND) or 60% (high-fat diet, HFD) of total calories from fat (lard). Dietary interventions in the HFD-fed mice included (i) probiotic (Bifidobacterium animalis subsp. lactis and Lactobacillus paracasei subsp. paracasei DSM 46331), (ii) prebiotic (oat β-glucan), and (iii) synbiotic (a mixture of i and ii) treatments for 12 weeks. Besides detailed characterization of host metabolic parameters, a multi-omics approach was used to systematically profile the microbial signatures at both the phylogenetic and functional levels using 16S rRNA gene sequencing, metaproteomics and targeted metabolomics analysis.ResultsThe synbiotic intervention significantly reduced body weight gain and alleviated features of metabolic complications. At the phylogenetic level, the synbiotic treatment significantly reversed HFD-induced changes in microbial populations, both in terms of richness and the relative abundance of specific taxa. Potentially important species such as Faecalibaculum rodentium and Alistipes putredinis that might mediate the beneficial effects of the synbiotic were identified. At the functional level, short-chain fatty acid and bile acid profiles revealed that all dietary interventions significantly restored cecal levels of acetate, propionate, and butyrate, while the synbiotic treatment reduced the bile acid pools most efficiently. Metaproteomics revealed that the effects of the synbiotic intervention might be mediated through metabolic pathways involved in carbohydrate, amino acid, and energy metabolisms.ConclusionsOur results suggested that dietary intervention using the novel synbiotic can alleviate HFD-induced weight gain and restore gut microbial ecosystem homeostasis phylogenetically and functionally.

Dataset Information

Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome.

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Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome.

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