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Abstract Background Hibernation allows animals to survive periods of resource scarcity by reducing their energy expenditure through decreased metabolism. However, hibernators become susceptible to psychrophilic pathogens if they cannot mount an efficient immune response to infection. While Nearctic bats infected with white-nose syndrome (WNS) suffer high mortality, related Palearctic taxa are better able to survive the disease than their Nearctic counterparts. We hypothesised that WNS exerted historical selective pressure in Palearctic bats, resulting in genomic changes that promote infection tolerance. Results We investigated partial sequences of 23 genes related to water metabolism and skin structure function in nine Palearctic and Nearctic hibernating bat species and one non-hibernating species for phylogenetic signals of natural selection. Using maximum likelihood analysis, we found that eight genes were under positive selection and we successfully identified amino acid sites under selection in five encoded proteins. Branch site models revealed positive selection in three genes. Hibernating bats exhibit signals for positive selection in genes ensuring tissue regeneration, wound healing and modulation of the immune response. Conclusion Our results highlight the importance of skin barrier integrity and healing capacity in hibernating bats. The protective role of skin integrity against both pathophysiology and WNS progression, in synergy with down-regulation of the immune reaction in response to the Pseudogymnoascus destructans infection, improves host survival. Our data also suggest that hibernating bat species have evolved into tolerant hosts by reducing the negative impact of skin infection through a set of adaptations, including those at the genomic level.

We present a DNA-based implementation of reaction system with molecules encoding elements of the propositional logic, that is, propositions and formulas. The protocol can perform inference steps using, for example, modus ponens and modus tollens rules and de Morgan’s laws. The set of the implemented operations allows for inference of formulas using the laws of natural deduction. The system can also detect whether a certain proposition a can be deduced from the basic facts and given rules. The whole protocol is fully autonomous; that is, after introducing the initial set of molecules, no human assistance is needed. Only one restriction enzyme is used throughout the inference process. Unlike some other similar implementations, our improved design allows representing simultaneously a fact a and its negation ~a, including special reactions to detect the inconsistency, that is, a simultaneous occurrence of a fact and its negation. An analysis of correctness, completeness, and complexity is included.