Mammalian hibernation is a strategy employed by many species to survive fluctuations in resource availability and environmental conditions. Hibernating mammals endure conditions of dramatically depressed heart rate, body temperature, and oxygen consumption yet do not show the typical pathological response. Because of the high abundance and metabolic cost of skeletal muscle, not only must it adjust to the constraints of hibernation, but also it is positioned to play a more active role in the initiation and maintenance of the hibernation phenotype. In this study, MS/MS proteomic data from thirteen-lined ground squirrel skeletal muscles were searched against a custom database of transcriptomic and genomic protein predictions built using the platform Galaxy-P. This proteogenomic approach allows for a thorough investigation of skeletal muscle protein abundance throughout their circannual cycle. Of the 1563 proteins identified by these methods, 232 were differentially expressed. These data support previously reported physiological transitions, while also offering new insight into specific mechanisms of how their muscles might be reducing nitrogenous waste, preserving mass and function, and signaling to other tissues. Additionally, the combination of proteomic and transcriptomic data provides unique opportunities for estimating post-transcriptional regulation in skeletal muscle throughout the year and improving genomic annotation for this nonmodel organism.
Bibliographical noteFunding Information:
This manuscript was improved by the helpful comments from Clair Hess. We thank LeeAnn Higgins and Todd Markowski for their role in proteomic data acquisition. This work was funded by NSF grant 1147079 for the Galaxy-P team, NIH Grant 1RC2HL101625-01 and USARMC contract W81XWH-11-0409 to M.T.A., and the University of Minnesota McKnight Presidential Endowment. We also acknowledge the Center for Mass Spectrometry and Proteomics and the Minnesota Supercomputing Institute for support.
© 2016 American Chemical Society.
- AMP -deaminsase 1
- quantitative proteomics
- skeletal muscle