Temperature shifts associated with bat arousals during hibernation inhibit the growth of Pseudogymnoascus destructans
Voyles, Jamie et al. (2022), Temperature shifts associated with bat arousals during hibernation inhibit the growth of Pseudogymnoascus destructans, Dryad, Dataset, https://doi.org/10.5061/dryad.sxksn036k
Temperature is a critically important factor in many infectious disease systems because it can regulate responses in both the host and the pathogen. White-nose syndrome (WNS) in bats is a severe infectious disease caused by the temperature-sensitive fungus, Pseudogymnoascus destructans (Pd). One feature of WNS is an increase in the frequency of arousal bouts (i.e., when bat body temperatures are elevated) in Pd-infected bats during hibernation. While several studies have proposed that increased frequency of arousals may play a role in the pathophysiology of WNS, it is unknown if the temperature fluctuations might mediate Pd growth. We hypothesized that exposure to a high frequency of elevated temperatures would reduce Pd growth due to thermal constraints on the pathogen. We simulated the thermal conditions for arousal bouts of uninfected and infected bats during hibernation (fluctuating from 8 - 25 °C at two different rates) and quantified Pd growth in vitro. We found that increased exposure to high temperatures significantly reduced Pd growth. Because temperature is one of the most critical abiotic factors mediating host-pathogen interactions, resolving how Pd responds to fluctuating temperatures will provide insights for understanding WNS in bats and other fungal diseases.
Culturing and experimental set up
We obtained a Pd culture from American Type Culture Collection number (Geomyces destructans ATCC), which was originally isolated from the wing of a little brown bat (Myotis lucifugus) in Williams Hotel Mine, Ulster County, New York, USA, in 2008 [7,8]. We revived the isolate by slowly warming the culture to room temperature (~21-22 °C) in a water bath (per ATCC manufacturer’s instructions). We transferred the Pd to two Sabourand’s Dextrose agar (SDA) plates and incubated it at 15 °C under 24 h darkness until we initiated the temperature experiment.
Temperature experimental set up
To harvest conidia for our experiment, we grew the cultures for 6-8 weeks on SDA agar plates or to when mycelia covered ~75% of the plates. We collected conidia by flooding the plates with 5 mL 0.5% 1x Phosphate Buffered Saline with Tween 20 (PBST) and allowed it to sit for 5 min. We then drew off 5 mL from the agar plate, counted conidia concentrations using a haemocytometer (Hausser Scientific, Horsham, PA, USA). We diluted the solution to a concentration of 2 x 104 conidia per 1 mL. We then inoculated 50 μL of the solution containing conidia into 30 wells in N = 8 Falcon 96-well, non-treated, flat-bottom microplates (Fisher Scientific, Waltham MA, USA). We also added 100 μL of Sabourand’s Dextrose Solution media (for which we used the same methods as for SDA but we omitted agar) to each well for all plates. To provide a negative control, we transferred the PBST solution containing Pd conidia to a 50 ml conical and submerged it in 100 °C water for 10 minutes. We then added 50 μL of PBST solution that contained heat killed Pd conidia and 100 μL of media to 30 negative control wells. We placed parafilm around the plates to maintain a tight seal on the lid and then incubated the plates in one of four temperature conditions and 80% humidity within incubators (Isotemp refrigerated incubators, Thermo Fisher, Waltham MA, USA) for 36 d.
The temperature treatments included: (1) constant 8 °C, a constant temperature within the thermal breath for Pd growth, (2) constant 25 °C, comparable to the skin temperature of hibernating bats during arousals , (3) fluctuating between 8- 25 °C every 16 days, simulating the Tb for “low frequency arousal” (uninfected, control) bats, and (4) fluctuating between 8- 25 °C every 7 days, simulating the Tb for “high frequency arousal” (i.e., infected bats with advanced WNS). For the fluctuating temperature treatments, the experimental plates were exposed to higher temperature conditions for 1 hour, which is the approximate duration of arousal for multiple bat species. Over the course of the experiment, we inspected the wells for contamination using a light microscope, seated the plates in a microplate reader (BioTek ELx800 spectrophotometer using the 540 nm filter), and recorded optical density (OD) every 3 days up to 36 days.
We assessed the difference in Pd growth over time among different temperature treatments using nonlinear mixed effects models with the ‘nlme’ package v22.214.171.124 in R v3.4.3 (R Core Team 2017). We selected a three-parameter logistic function because logistic growth curves are classically used to model the exponential and stationary phases of microbial growth in vitro. A nonlinear modeling approach allows for meaningful parameter estimates of culture stationary phase (i.e., asymptote), the time at which cultures are in exponential growth phase halfway to stationary phase (i.e., inflection point), and a scale parameter that determines the steepness of the growth curved. We corrected for initial conidia inoculation and media color by subtracting OD values of heat-killed controls from OD values of wells containing Pd. Due to an error in pipetting, we omitted two wells in one of the plates from our analyses. We then built models using the adjusted mean OD per plate per day (N = 8 plates per temperature treatment).
We compared model fits with analysis of variance (ANOVA) and likelihood ratio tests for nested models, and we selected models using AIC and principles of parsimony following Pinheiro and Bates (2000). Pd incubated at a constant temperature of 25 °C did not follow a logistic growth pattern (i.e., there was no Pd growth at this temperature) and we therefore excluded this temperature treatment from the final analysis. Our final model included fixed effects of temperature treatment on all three logistic growth parameters and the random effect of plate on the inflection point and scale parameters. We added an identity variance structure and an autoregressive moving average correlation structure to the model to address heteroscedasticity. We used an F-test to determine the significance of the temperature treatment fixed effect.
R v3.4.3 (R Core Team 2017)
National Science Foundation, Award: 1846403
University of Nevada, Reno, Award: Research and Innovation