ME ditome : Computational Detection of RNA Edit Sites Using de Novo Assembly in Microbiomes

Abstract

RNA editing is a post-transcriptional modification that alters single-nucleotide sites within RNA strands, thus diversifying transcriptomes and proteomes and modulating gene expression. While better characterized in eukaryotes and in a few microbes, the study of RNA editing in entire microbiomes remains unexplored. Recent studies have demonstrated that A-to-I RNA editing contributes to bacterial adaptation and pathogenicity. Previously, we developed MetaEdit, a reference-based computational pipeline to detect RNA edit sites in microbiomes. While MetaEdit successfully identified RNA edit sites in Escherichia coli within the context of the human gut microbiome, including previously reported loci, it relied primarily on aligning reads to reference genomes of target bacteria. This dependence on reference genomes introduced potential biases, as editing can only be identified in reference genomes, while editing in novel microbial strains missing from the reference databases could be overlooked. Even for reference genomes, the search for edit sites is inefficient since it would have to be conducted one reference genome at a time.

Here, we introduce MEditome, employing de novo assembly to overcome these limitations. This crucial change enables the detection of RNA edit sites across all microbial organisms in the microbiome, including novel bacterial strains for which comprehensive reference genomes are unavailable. Using sequencing data from the Integrative Human Microbiome Project, MEditome identified 2,295 unique RNA editing sites across diverse bacterial taxa. Several of these overlaps with previously identified edits in E. coli detected by MetaEdit in hok/gef gene family and arginine-associated genes, providing in silico validation of accuracy. We observed taxon-specific editing patterns and gene-level differential editing associated with inflammatory bowel disease, highlighting RNA editing as a potential regulatory mechanism influencing microbial adaptation and host–microbe interactions.