Dataset Information

HOME-BIO (sHOtgun MEtagenomic analysis of BIOlogical entities): a specific and comprehensive pipeline for metagenomic shotgun sequencing data analysis.

ABSTRACT:

Background

Next-Generation-Sequencing (NGS) enables detection of microorganisms present in biological and other matrices of various origin and nature, allowing not only the identification of known phyla and strains but also the discovery of novel ones. The large amount of metagenomic shotgun data produced by NGS require comprehensive and user-friendly pipelines for data analysis, that speed up the bioinformatics steps, relieving the users from the need to manually perform complex and time-consuming tasks.

Results

We describe here HOME-BIO (sHOtgun MEtagenomic analysis of BIOlogical entities), an exhaustive pipeline for metagenomics data analysis, comprising three independent analytical modules designed for an inclusive analysis of large NGS datasets.

Conclusions

HOME-BIO is a powerful and easy-to-use tool that can be run also by users with limited computational expertise. It allows in-depth analyses by removing low-complexity/ problematic reads, integrating the analytical steps that lead to a comprehensive taxonomy profile of each sample by querying different source databases, and it is customizable according to specific users' needs.

SUBMITTER: Ferravante C

PROVIDER: S-EPMC8256542 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundHealth surveillance of murine colonies employed for scientific purposes aim at detecting unwanted infection that can affect the well-being of animals and personnel, and potentially undermine scientific results. In this study, we investigated the use of a next-generation sequencing (NGS) metagenomic approach for monitoring the microbiota composition and uncovering the possible presence of pathogens in mice housed in specific pathogen-free (SPF) or conventional (non-SPF) facilities.ResultsAnalysis of metagenomic NGS assay through public and free algorithms and databases allowed to precisely assess the composition of mouse gut microbiome and quantify the contribution of the different microorganisms at the species level. Sequence analysis allowed the uncovering of pathogens or the presence of imbalances in the microbiota composition. In several cases, fecal pellets taken from conventional facilities were found to carry gene sequences from bacterial pathogens (Helicobacter hepaticus, Helicobacter typhlonius, Chlamydia muridarum, Streptococcus pyogenes, Rodentibacter pneumotropicus, Citrobacter rodentium, Staphylococcus aureus), intestinal protozoa (Entamoeba muris, Tritrichomonas muris, Spironucleus muris) nematoda (Aspiculuris tetraptera, Syphacia obvelata), eukaryotic parasites (Myocoptes musculinus) and RNA virus (Norwalk virus). Thus, the use of NGS metagenomics can reduce the number of tests required for the detection of pathogens and avoid the use of sentinel mice.ConclusionsIn summary, in comparison with standard approaches, which require multiple types of test, NGS assay can detect bacteria, fungi, DNA and RNA viruses, and eukaryotic parasites from fecal pellets in a single test. Considering the need to protect animal well-being and to improve the success and reproducibility of preclinical studies, this work provides the proof-of-concept that the use of NGS metagenomics for health monitoring of laboratory mice is a feasible and dependable approach, that is able to broaden the current concept of health monitoring of laboratory mice from "pathogen surveillance" to a more inclusive "microbiota surveillance".