LAUSR

We developed an analysis method that integrates metagenomes and metatranscriptomes from multiple intestinal sites to elucidate how microbial function varies along the intestinal tract. This method enables spatial covariation analysis of the functional activity of microbiomes and accurate identification of gene expression changes among intestinal sites, including changes in the expression of unknown bacterial genes. ABSTRACT 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. IMPORTANCE We developed an analysis method that integrates metagenomes and metatranscriptomes from multiple intestinal sites to elucidate how microbial function varies along the intestinal tract. This method enables spatial covariation analysis of the functional activity of microbiomes and accurate identification of gene expression changes among intestinal sites, including changes in the expression of unknown bacterial genes. Moreover, we applied this method to the investigation of the common marmoset intestine, which is anatomically and pharmacologically similar to that of humans. Our findings indicate the expression pattern of the microbiome varies in response to changes in the internal environment along the intestinal tract, and this microbial change may affect the intestinal environment.