Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1116795 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR29220800_1.fastq.gz | Fastqsanger.gz | |||
| SRR29220800_2.fastq.gz | Fastqsanger.gz | |||
| SRR29220900_1.fastq.gz | Fastqsanger.gz | |||
| SRR29220900_2.fastq.gz | Fastqsanger.gz | |||
| SRR29220801_1.fastq.gz | Fastqsanger.gz |
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Project description:Genome scale metabolic model of Drosophila gut microbe Acetobacter fabarum
Abstract -
An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and their impact on host physiology. This research can be confounded by poorly understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multiway interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition, and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that, in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle, including 2-oxoglutarate and succinate, are produced at high flux and cross-fed between bacterial taxa, suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host.IMPORTANCE Drosophila is an important model for microbiome research partly because of the low complexity of its mostly culturable gut microbiota. Our current understanding of how Drosophila interacts with its gut microbes and how these interactions influence host traits derives almost entirely from empirical studies that focus on individual microbial taxa or classes of metabolites. These studies have failed to capture fully the complexity of metabolic interactions that occur between host and microbe. To overcome this limitation, we reconstructed and analyzed 31 metabolic models for every combination of the five principal bacterial taxa in the gut microbiome of Drosophila This revealed that metabolic interactions between Drosophila gut bacterial taxa are highly dynamic and influenced by cooccurring bacteria and nutrient availability. Our results generate testable hypotheses about among-microbe ecological interactions in the Drosophila gut and the diversity of metabolites available to influence host traits.
2021-07-01 | MODEL2002040002 | BioModels
Project description:Recent RNA-sequencing studies have shown remarkable complexity in the mammalian transcriptome. The ultimate impact of this complexity on the predicted proteomic output is less well defined. We have undertaken a strand-specific RNA sequencing of multiple cellular RNA fractions (>18Gb) to uncover the transcriptional complexity of human ES cells. We have shown that human ES cells display a high degree of transcriptional diversity, with more than half? of active genes generating RNAs that differ from conventional gene models. We found evidence that more than >1000 genes express long 5’ and/or extended 3’ UTRs, which was confirmed by “virtual northern” analysis. Exhaustive sequencing the membrane-polysome and cytosolic/untranslated fractions of hESC was used to identify RNAs encoding peptides destined for secretion and the extracellular space and to demonstrate preferential selection of transcription complexity for translation in vitro. Finally, the impact of this newly defined transcriptional complexity on known gene-centric network models such as the Plurinet and the cell surface signalling machinery in human ES cells revealed a significant expansion of protein coding components at play, many of which alternative actions based on altered domain content. Human ES cells fractionated for mRNA, cytosolic polysome, membrane polysome
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