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J Proteome Res. 2016 Apr 1;15(4):1253-61. doi: 10.1021/acs.jproteome.5b01138. Epub 2016 Mar 3.

Proteogenomic Analysis of a Hibernating Mammal Indicates Contribution of Skeletal Muscle Physiology to the Hibernation Phenotype.

Author information

1
Department of Biology, University of Minnesota Duluth , 1035 Kirby Drive, Duluth, Minnesota 55812, United States.
2
Center for Mass Spectrometry and Proteomics, University of Minnesota , 1479 Gortner Avenue, St. Paul, Minnesota 55108, Unites States.
3
Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota , 321 Church Streey South East, Minneapolis, Minnesota 55455, United States.
4
Minnesota Supercomputing Institute , 512 Walter Library, 117 Pleasant Street South East, Minneapolis, Minnesota 55455, United States.

Abstract

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.

KEYWORDS:

AMP − deaminsase 1; Galaxy-P; fibromodulin; hibernation; iTRAQ; proteogenomics; quantitative proteomics; skeletal muscle

PMID:
26903422
DOI:
10.1021/acs.jproteome.5b01138
[Indexed for MEDLINE]

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