HolomiRA: a reproducible pipeline for miRNA binding site prediction in microbial genomes.

Abstract

Background: Small RNAs, such as microRNAs (miRNAs), are candidates for mediating communication between the host and its microbiota, regulating bacterial gene expression and influencing microbiome functions and dynamics. Here, we introduce HolomiRA (Holobiome miRNA Affinity Predictor), a computational pipeline developed to predict target sites for host miRNAs in microbiome genomes. HolomiRA operates within a Snakemake workflow, processes microbial genomic sequences in FASTA format using freely available bioinformatics software and incorporates built-in data processing methods. The pipeline begins by annotating protein-coding sequences from microbial genomes using Prokka. It then identifies candidate regions, evaluates them for potential host miRNA binding sites and the accessibility of these target sites using RNAHybrid and RNAup software. The predicted results that meet the quality filter parameters are further summarized and used to perform a functional analysis of the affected genes using SUPER-FOCUS software.

Results: In this paper, we demonstrate the use of the HolomiRA pipeline by applying it to publicly available metagenome-assembled genomes obtained from human feces, as well as from bovine feces and ruminal content. This approach enables the prediction of bacterial genes and biological pathways within microbiomes that could be influenced by host miRNAs. It also allows for the identification of shared or unique miRNAs, target genes, and taxonomies across phenotypes, environments, or host species.

Conclusions: HolomiRA is a practical and user-friendly pipeline designed as a hypothesis-generating tool to support the prediction of host miRNA binding sites in prokaryotic genomes, providing insights into host-microbiota communication mediated by miRNA regulation. HolomiRA is publicly available on GitHub: https://github.com/JBruscadin/HolomiRA .