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.