To capture the functional diversity of microbiota, one must identify metabolic functions and species of interest within hundreds or thousands of microorganisms. We present Metage2Metabo (M2M) a resource that meets the need for de novo functional screening of genome-scale metabolic networks (GSMNs) at the scale of a metagenome, and the identification of critical species with respect to metabolic cooperation. M2M comprises a flexible pipeline for the characterisation of individual metabolisms and collective metabolic complementarity. In addition, M2M identifies key species, that are meaningful members of the community for functions of interest. We demonstrate that M2M is applicable to collections of genomes as well as metagenome-assembled genomes, permits an efficient GSMN reconstruction with Pathway Tools, and assesses the cooperation potential between species. M2M identifies key organisms by reducing the complexity of a large-scale microbiota into minimal communities with equivalent properties, suitable for further analyses.
BackgroundBecause the cost of cereals is unstable and represents a large part of production charges for meat-type chicken, there is an urge to formulate alternative diets from more cost-effective feedstuff. We have recently shown that meat-type chicken source is prone to adapt to dietary starch substitution with fat and fiber. The aim of this study was to better understand the molecular mechanisms of this adaptation to changes in dietary energy sources through the fine characterization of transcriptomic changes occurring in three major metabolic tissues – liver, adipose tissue and muscle – as well as in circulating blood cells.ResultsWe revealed the fine-tuned regulation of many hepatic genes encoding key enzymes driving glycogenesis and de novo fatty acid synthesis pathways and of some genes participating in oxidation. Among the genes expressed upon consumption of a high-fat, high-fiber diet, we highlighted CPT1A, which encodes a key enzyme in the regulation of fatty acid oxidation. Conversely, the repression of lipogenic genes by the high-fat diet was clearly associated with the down-regulation of SREBF1 transcripts but was not associated with the transcript regulation of MLXIPL and NR1H3, which are both transcription factors. This result suggests a pivotal role for SREBF1 in lipogenesis regulation in response to a decrease in dietary starch and an increase in dietary PUFA. Other prospective regulators of de novo hepatic lipogenesis were suggested, such as PPARD, JUN, TADA2A and KAT2B, the last two genes belonging to the lysine acetyl transferase (KAT) complex family regulating histone and non-histone protein acetylation. Hepatic glycogenic genes were also down-regulated in chickens fed a high-fat, high-fiber diet compared to those in chickens fed a starch-based diet. No significant dietary-associated variations in gene expression profiles was observed in the other studied tissues, suggesting that the liver mainly contributed to the adaptation of birds to changes in energy source and nutrients in their diets, at least at the transcriptional level. Moreover, we showed that PUFA deposition observed in the different tissues may not rely on transcriptional changes.ConclusionWe showed the major role of the liver, at the gene expression level, in the adaptive response of chicken to dietary starch substitution with fat and fiber.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4520-5) contains supplementary material, which is available to authorized users.
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