Non-invasive monitoring of multiple wildlife health factors by fecal microbiome analysis
Pannoni, Samuel; Holben, William; Proffitt, Kelly (2023), Non-invasive monitoring of multiple wildlife health factors by fecal microbiome analysis, Dryad, Dataset, https://doi.org/10.5061/dryad.4j0zpc880
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 tested. Our results show that elk microbiomes respond to both the strong extrinsic factor of biogeography and simultaneously occurring, but more subtle, intrinsic forces of individual body-fat, sex, and age class. Thus, we have developed and described herein a generalizable approach to disentangle microbiome responses attributed to multiple host factors of varying strength from the same bacterial sequence data set. Wildlife conservation and management presents many challenges, but we demonstrate that non-invasive microbiome surveys from scat samples can provide alternative options for wildlife population monitoring. We believe that, with further validation, this method could be broadly applicable in other species and potentially predict other measurements. Our study can help guide the future development of microbiome-based monitoring of wildlife populations and supports hypothetical expectations found in host-microbiome theory.
Fecal sampling of Rocky Mountain elk from Montana, USA. Elk were sampled in winter 2014.
Sequence data: This data includes 16S rRNA raw sequences produced on a MiSeq with 300bp paired-end chemistry. Samples (elk) were demultiplexed and samples are provided as separate files. Files are paired with forward files ending in “R1” and reverse reads with “R3”. There are 4 populations of elk in this 16S survey, and the first letter of the filename denotes this: T = Tobacco Root, S = Sapphire, B = Bitterroot, F = Black’s Ford.
Metadata for each elk: For a complete description of associated data collected for each animal please review the csv file named “elk_meta_data.csv”. All metadata that was collected by MT Fish Wildlife and Parks is included and any data that was not collected (not sampled) is denoted with “n/a”. Variables include: Elk (ID), Population, Sex, Age, Pregnant, IFBF (body fat), TT4, FT4, TT3, color.