Non-invasive monitoring of multiple wildlife health factors by fecal microbiome analysis.

ABSTRACT: Fecal microbial biomarkers represent a less invasive alternative for acquiring information on wildlife populations than many traditional sampling methodologies. Our goal was to evaluate linkages between fecal microbiome communities in Rocky Mountain elk (Cervus canadensis) and four host factors including sex, age, population, and physical condition (body-fat). We paired a feature-selection algorithm with an LDA-classifier trained on elk differential bacterial abundance (16S-rRNA amplicon survey) to predict host health factors from 104 elk microbiomes across four elk populations. We validated the accuracy of the various classifier predictions with leave-one-out cross-validation using known measurements. We demonstrate that the elk fecal microbiome can predict the four host factors te

SUBMITTER: Pannoni SB 

PROVIDER: S-EPMC8826075 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature