A new analytical pipeline reveals metatranscriptomic changes upon high-fat diet in a Down syndrome mouse model.

Abstract

The existing methods designated for metatranscriptomic studies are still rare and being developed. In this paper we present a new analytical pipeline combining contig assembly, gene selection and functional annotation. This pipeline allowed us to reconstruct contigs with very high unique mappability (83%) and select sequences encoding putative bacterial genes reaching also a very high (66%), unique mappability of the NGS sequencing reads. Then, we have applied our pipeline to study faecal metatranscriptome of a Down syndrome (DS) mouse model, the Ts65Dn mice, in order to identify the differentially expressed transcripts. Recent studies have implicated dysbiosis of gut microbiota in several central nervous system (CNS) disorders, including DS. Given that DS individuals have an increased prevalence of obesity, we also studied the effects of a high-fat diet (HFD) on the transcriptomic changes of mice gut microbiomes, as the complex symbiotic relationship between the gut microbiome and its host is strongly influenced by diet and nutrition. Using our new pipeline we found that compared to wild type (WT), Ts65Dn mice showed an elevated expression levels of genes involved in hypoxanthine metabolism, which contributes to oxidative stress, and a down-regulated expression of genes involved in interactions with host epithelial cells and virulence. Microbiomes of mice fed HFD showed significantly higher expression levels of genes involved in membrane lipopolysaccharides / lipids biosynthesis, and decreased expression of osmoprotection and lysine fermentation genes, among others. We also found evidence that mice microbiota is capable of expressing genes encoding for neuromodulators, which may play a role in development of compulsive overeating and obesity. Our results show a DS-specific metatranscriptome profile and show that a high-fat diet affects the metabolism of mice gut microbiome by changing activity of genes involved in lipids, sugars, proteins and amino acids metabolism and cell membranes turnover. Our new analytical pipeline combining contig assembly, gene selection and functional annotation provides new insights into the metatranscriptomic studies.