Metagenomics Versus Metatranscriptomics of the Murine Gut Microbiome for Assessing Microbial Metabolism During Inflammation

Abstract

Shotgun metagenomics studies have improved our understanding of microbial population dynamics and have revealed significant contributions of microbes to gut homeostasis. They also allow in silico inference of the metagenome. While they link the microbiome with metabolic abnormalities associated with disease phenotypes, they do not capture microbial gene expression patterns that occur in response to the multitude of stimuli that constantly ambush the gut environment. Metatranscriptomics closes that gap, but its implementation is more expensive and tedious. We assessed the metabolic perturbations associated with gut inflammation using shotgun metagenomics and metatranscriptomics. Shotgun metagenomics detected changes in abundance of bacterial taxa known to be SCFA producers, which favors gut homeostasis. Bacteria in the phylum Firmicutes were found at decreased abundance, while those in phyla Bacteroidetes and Proteobacteria were found at increased abundance. Surprisingly, inferring the coding capacity of the microbiome from shotgun metagenomics data did not result in any statistically significant difference, suggesting functional redundancy in the microbiome or poor resolution of shotgun metagenomics data to profile bacterial pathways, especially when sequencing is not very deep. Obviously, the ability of metatranscriptomics libraries to detect transcripts expressed at basal (or simply low) levels is also dependent on sequencing depth. Nevertheless, metatranscriptomics informed about contrasting roles of bacteria during inflammation. Functions involved in nutrient transport, immune suppression and regulation of tissue damage were dramatically upregulated, perhaps contributed by homeostasis-promoting bacteria. Functions ostensibly increasing bacteria pathogenesis were also found upregulated, perhaps as a consequence of increased abundance of Proteobacteria. Bacterial protein synthesis appeared downregulated. In summary, shotgun metagenomics was useful to profile bacterial population composition and taxa relative abundance, but did not inform about differential gene content associated with inflammation. Metatranscriptomics was more robust for capturing bacterial metabolism in real time. Although both approaches are complementary, it is often not possible to apply them in parallel. We hope our data will help researchers to decide which approach is more appropriate for the study of different aspects of the microbiome.