Tools to understand seasonality in health quantification of microbe loads and analyses of compositional ecoimmunological data reveal complex patterns in tortoise populations


Meeting Abstract

133-3  Monday, Jan. 7 08:30 – 08:45  Tools to understand seasonality in health: quantification of microbe loads and analyses of compositional ecoimmunological data reveal complex patterns in tortoise populations SANDMEIER, FC*; LEONARD, KL; TRACY, CR; DRAKE, KK; ESQUE, T; NUSSEAR, K; GERMANO , J; Colorado State University-Pueblo; Colorado State University-Pueblo; University of Nevada, Reno; US Geological Survey; US Geological Survey; University of Nevada, Reno; Department of Conservation, New Zealand fcsandmeier@gmail.com

Using data from six wild tortoise (Gopherus agassizii) populations, we quantified seasonal differences in basic immune system measurements and microbial load in the respiratory tract, pertinent to this species’ susceptibility to disease. We used multivariate analyses of immune measures to detect trends in temporal and spatial variation in immune function. We stress the importance of using centered log-ratio (clr) transformations of leukocyte counts as necessary for the correct analysis of compositional data. Lymphocytes numbers increased and decreased temporally in opposition to cells involved in innate inflammatory processes (heterophils and eosinophils). We created a quantitative PCR assay for the potential pathogen, Pasteurella testudinis, and tested animals for P. testudinis, as well as for the known respiratory pathogens Mycoplasma agassizii and M. testudineum. We found very little disease and suggest that P. testudinis is a prevalent, commensal microbe in these tortoise populations. We determined that analysis of P. testudinis loads is a tool to study natural fluctuations in microbe levels in tortoise respiratory tracts. Our analyses showed that both the potential for inflammatory responses and microbe levels are highest in the spring for healthy tortoises. The genetic and statistical tools we used are easily applicable to other wildlife systems and provide the necessary data to quantify species-wide trends in health and test hypotheses pertinent to host-microbe dynamics.

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