White-Nose Syndrome Disease Severity and a Comparison of Diagnostic Methods
Files
Download Full Text
Publication Date
March 2016
Abstract
White-nose syndrome is caused by the fungus Pseudogymnoascus destructans and has killed millions of hibernating bats in North America but the pathophysiology of the disease remains poorly understood. Our objectives were to (1) assess non-destructive diagnostic methods for P. destructans infection compared to histopathology, the current gold-standard, and (2) to evaluate potential metrics of disease severity. We used data from three captive inoculation experiments involving 181 little brown bats (Myotis lucifugus) to compare histopathology, quantitative PCR (qPCR), and ultraviolet fluorescence as diagnostic methods of P. destructans infection. To assess disease severity, we considered two histology metrics (wing area with fungal hyphae, area of dermal necrosis), P. destructans fungal load (qPCR), ultraviolet fluorescence, and blood chemistry (hematocrit, sodium, glucose, pCO2, and bicarbonate). Quantitative PCR was most effective for early detection of P. destructans, while all three methods were comparable in severe infections. Correlations among hyphae and necrosis scores, qPCR, ultraviolet fluorescence, blood chemistry, and hibernation duration indicate a multi-stage pattern of disease. Disruptions of homeostasis occurred rapidly in late hibernation. Our results provide valuable information about the use of non-destructive techniques for monitoring, and provide novel insight into the pathophysiology of white-nose syndrome, with implications for developing and implementing potential mitigation strategies.
Keywords
Blood Chemistry, Histopathology, Myotis Lucifugus, Non-Destructive Methods, Pcr, Pseudogymnoascus Destructans, Ultraviolet Fluorescence
Document Type
Article
Notes
EcoHealth, Vol. 13, no. 1 (2016-03-08).
Identifier
SFS0063032_00001
Recommended Citation
McGuire, Liam P.; Turner, James M.; and Warnecke, Lisa, "White-Nose Syndrome Disease Severity and a Comparison of Diagnostic Methods" (2016). KIP Articles. 5696.
https://digitalcommons.usf.edu/kip_articles/5696