Development of Metagenomic Methods for Health Monitoring of Endangered Species Using Fecal Samples

Metagenomic analysis of fecal samples is emerging as a powerful tool for monitoring endangered species, particularly in assessing the burden of pathogens and parasites that can threaten population viability. However, accurate identification in non-model species remains challenging due to the frequent absence of host-specific pathogen reference genomes. In this study, we developed a robust computational framework for detecting potentially pathogenic bacteria from metagenomic sequences by mapping them to available reference genomes in databases. Several key parameters affecting the analysis, including mapping algorithm, database configuration, and identification parameters, were analyzed to optimize detection sensitivity and specificity. Applying this approach to fresh fecal samples of the Iberian desman (Galemys pyrenaicus), a critically endangered semi-aquatic mammal, we identified 26 potentially pathogenic bacterial species, with prevalences ranging from isolated cases to nearly half of the individuals examined. Furthermore, our analysis revealed that some desmans had atypical compositions of potential pathogens, suggesting variations in environmental exposure or host genetic factors. This work demonstrates a novel application of fecal metagenomics for species-level detection of microorganisms implicated in disease, providing a powerful approach to gain essential insights into the health and epidemiology of endangered species and to support the development of more effective conservation strategies.