The intestinal microbiome is closely related to host health, and metatranscriptomic analysis can be used to assess the functional activity of microbiomes by quantifying microbial gene expression levels, helping elucidate the interactions between the microbiome and the environment. However, the functional changes in the microbiome along the host intestinal tract remain unknown, and previous analytical methods have limitations, such as potentially overlooking unknown genes due to dependence on existing databases. The objective of this study is to develop a computational pipeline combined with next-generation sequencing for spatial covariation analysis of the functional activity of microbiomes at multiple intestinal sites (biogeographic locations) within the same individual. This method reconstructs a reference metagenomic sequence across multiple intestinal sites and integrates the metagenome and metatranscriptome, allowing the gene expression levels of the microbiome, including unknown bacterial genes, to be compared among multiple sites. When this method was applied to metatranscriptomic analysis in the intestinal tract of common marmosets, a New World monkey, the reconstructed metagenome covered most of the expressed genes and revealed that the differences in microbial gene expression among the cecum, transverse colon, and feces were more dynamic and sensitive to environmental shifts than the abundances of the genes. In addition, metatranscriptomic profiling at three intestinal sites of the same individual enabled covariation analysis incorporating spatial relevance, accurately predicting the function of a total of 10,856 unknown genes. Our findings demonstrate that our proposed analytical method captures functional changes in microbiomes at the gene resolution level.
ASJC Scopus subject areas
- コンピュータ サイエンスの応用