| Summary: | Infection experiments are critical for understanding wildlife disease dynamics. Although infection experiments are typically designed to reduce complexity, disease outcomes still result from complex interactions between host, pathogen, and environmental factors. Cryptic variation across factors can lead to decreased repeatability of infection experiments within and between research groups and hinder research progress. Furthermore, studies with unexpected results are often relegated to the "file drawer" and potential insights gained from these experimental outcomes are lost. Here, we report unexpected results from an infection experiment studying the response of two differentially-susceptible but related frogs (American Bullfrog Rana catesbeiana and the Mountain yellow-legged frog Rana muscosa) to the amphibian-killing chytrid fungus (Batrachochytrium dendrobatidis, Bd). Despite well-documented differences in susceptibility between species, we found no evidence for antibody-mediated immune response and no Bd-related mortality in either species. Additionally, during the study, the sham-inoculated R. catesbeiana control group became unexpectedly Bd-positive. We used a custom genotyping assay to demonstrate that the aberrantly-infected R. catesbeiana carried a Bd genotype distinct from the inoculation genotype. Thus R. catesbeiana individuals were acquired with low-intensity infections that could not be detected with qPCR. In the Bd-inoculated R. catesbeiana treatment group, the inoculated genotype appeared to out-compete the cryptic infection. Thus, our results provide insight into Bd coinfection dynamics, a phenomenon that is increasingly relevant as different pathogen strains are moved around the globe. Our experiment highlights how unexpected experimental outcomes can serve as both cautionary tales and opportunities to explore unanswered research questions. We use our results as a case study to highlight common sources of anomalous results for infection experiments. We argue that understanding these factors will aid researchers in the design, execution, and interpretation of experiments to understand wildlife disease processes.
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