Sckrabulis et al. - Using metabolic theory to describe temperature and thermal acclimation effects on parasitic infection
Jason P. Sckrabulis: jason.sckrabulis@gmail.com
Karie A. Altman: karie.altman@gmail.com
Thomas R. Raffel: raffel@oakland.edu
Conceptualization: JPS, KAA & TRR. Methodology: JPS, KAA, & TRR. Analysis: JPS & TRR. Writing - review & editing: JPS, KAA, & TRR. Funding: TRR. Literature searching: JPS.
Please email jason.sckrabulis@gmail.com with any issues or suggestions with the data or code supplement, or submit via the GitHub issues tab for this repository. For questions concerning the manuscript, please email the corresponding author at jason.sckrabulis@gmail.com.
- April 18, 2022: Update citation and Dryad DOI information
- November 17, 2021: Fixed references in .R files to other scripts and datasets; other improvements for parity with Dryad submission
- September 24, 2021: Replaced contents of
/code
with revised code - October 21, 2020: Replaced normal text files within
/code
with .R files - August 27, 2020: Repository complete for submission
- July 1, 2020: First full commit
Please cite work as:
Sckrabulis, JP, KA Altman, and TR Raffel. 2022. Using metabolic theory to describe temperature and thermal acclimation effects on parasitic infection. The American Naturalist DOI: https://doi.org/10.1086/719409.
Archived version of data and code can be found on Dryad + Zenodo:
Predicting temperature effects on species interactions can be challenging, especially for parasitism where it is difficult to experimentally separate host and parasite thermal performance curves. Prior authors proposed a possible solution based on the metabolic theory of ecology (MTE), using MTE-based equations to describe the thermal mismatch between host and parasite performance curves and account for thermal acclimation responses. Here we use published infection data, supplemented with experiments measuring metabolic responses to temperature in each species, to show that this modeling framework can successfully describe thermal acclimation effects on two different stages of infection in a tadpole-trematode system. All thermal acclimation effects on host performance manifested as changes in one key model parameter (activation energy), with measurements of host respiration generating similar MTE parameter estimates and acclimation effects compared to measurements of the host’s ability to clear encysted parasites. This result suggests that metabolic parameter estimates for whole-body metabolism can sometimes be used to estimate temperature effects on host and parasite performance curves. However, we found different thermal patterns for measurements of host prevention of initial parasite encystment emphasizing potential challenges when applying MTE-based models to complex parasite-host systems with multiple distinct stages of infection.
- README.md
- LICENSE.txt
- data
Folder of experimental data as .csv files used in data analysis for manuscript (Please note that metacercaria encystment and clearance data is from Altman et al. 2016 and can be found on Dryad here)Activation energy bootstrap Sckrabulis et al 2021 AmNat.csv
(final output fromActivation energy bootstrap.txt
used in Fig. 3)Cerc swimming speed Sckrabulis et al 2021 AmNat.csv
(dataset for cercaria swimming speed experiment)Uninfected tadpole respiration Sckrabulis et al 2021 AmNat.csv
(dataset for host respiration acclimation experiment)
- code
Folder of statistical R code used to analyze data as .R filesActivation energy bootstrap Sckrabulis et al 2021 AmNat.R
(Used to generate individual 95% confidence bands for respiration and metacercaria clearance)Cercaria swimming speed Sckrabulis et al 2021 AmNat.R
(Used to analyzeCerc swimming speed Sckrabulis et al 2021 AmNat.csv
data)Metacercaria persistence Sckrabulis et al 2021 AmNat.R
(Used to analyze metacercaria clearance rate from Altman et al. 2016 data on Dryad)Metacercaria encystment Sckrabulis et al 2021 AmNat.R
(Used to analyse metacercaria encystment from Altman et al. 2016 data on Dryad)Mismatches Sensitivity and To Sckrabulis et al 2021 AmNat.R
(Used to generate hypothetical thermal mismatches, sensitivity analysis and To optimization plots in Supplement)Uninfected tadpole respiration Sckrabulis et al 2021 AmNat.R
(Used to analyseUninfected tadpole respiration Sckrabulis et al 2021 AmNat.csv
data)
Activation energy bootstrap Sckrabulis et al 2021 AmNat.csv
Variable name | Description |
---|---|
AccTemp | Temperature at which the tadpole was acclimated in Celsius as a range of values from the minimum and maximum of our experimental range in 0.1 C increments |
resp | Activation energy calculated from the best fit model for tadpole respiration at that particular acclimation temperature |
rlow | Lower value of 95% confidence interval for the predicted activation energy for respiration at that acclimation temperature |
rhigh | Upper value of 95% confidence interval for the predicted activation energy for respiration at that acclimation temperature |
clear | Activation energy calculated from the best fit model for metacercaria clearance at that particular acclimation temperature |
clow | Lower value of 95% confidence interval for the predicted activation energy for clearance at that acclimation temperature |
chigh | Upper value of 95% confidence interval for the predicted activation energy for clearance at that acclimation temperature |
Cercaria swimming speed Sckrabulis et al 2021 AmNat.csv
Variable name | Description |
---|---|
Snail | Number signifying which snail the cercaria originated from |
Temperature | Temperature at which the cercariae were recorded |
avgSpeed | Average swimming speed for each cercaria, calculated in pixels per second within imageJ by the wrMTrck plugin (Nussbaum-Krammer, C.I., M.F. Neto, R.M. Brielmann, J.S. Pederson, and R.I. Morimoto. 2015. Investigating the spreading and toxicity of prion-like proteins using the metazoan model organism C. elegans. Journal of Visualized Experiments 95: e52321) |
avgSpeedMM | Average swimming speed for each cercaria in millimeters per second, calculated using the conversion factor 94.5 pixels per millimeter |
Uninfected tadpole respiration Sckrabulis et al 2021 AmNat.csv
Variable name | Description |
---|---|
Type | Label for respiration jars in the experiment where tad = tadpole for measurement & control = an empty control jar |
ID | Jar label for internal tracking of location |
Block | Number representing which block the jar was in |
AccInc | Number signifying which acclimation incubator the animal was maintained in during the acclimation period |
AccTemp | Temperature at which the tadpole was acclimated measured in Celsius |
Stage | Gosner stage of the tadpole (based on Gosner, K. 1960. A simplified table for staging anuran embryos and larvae with notes on identification. Herpetologica 16(3): 183-190) |
Mass | Tadpole mass measured in grams |
PerfRound | Number signifying which of the three sequential performance temperatures the measurement was taken |
PerfTemp | Temperature at which respiration measurements were taken in Celsius |
Time | Duration of the respiration period, calculated from start and stop times in minutes |
O2 | Change in dissolved oxygen, calculated by the difference between the initial concentration of oxygen in the control jars and the final measurement from each tadpole, in milligrams per liter |
O2/Time | Rate of oxygen consumed per minute, calculated by dividing O2 by Time |
O2/Time/Mass | Mass-corrected rate of oxygen consumed per minute per tadpole mass, calculated by dividing O2/Time by Mass (units: g/L oxygen per min per g tadpole) |
corO2/Time/Mass | Corrected O2/Time/Mass value to obtain mass-corrected rate of oxygen consumed per minute controlling for jar volume, calculated by multiplying O2/Time/Mass by volume of jar 0.57L (units: g oxygen per min per g tadpole) |