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Inclusion of Kinetic Proteomics in Multi-Omics Methods to Analyze Calorie Restriction Effects on Aging

One of the greatest risk factors for disease is advanced age. As the human lifespan has increased, so too have the burdens of caring for an increasingly older population suffering from rising rates of cardiovascular disease, kidney disease, diabetes, and dementia. The need for improving medical technology and developing new therapies for age-related diseases is manifest. Yet our understanding of the processes of aging and how to attenuate the effects of aging remains incomplete. Various studies have established calorie restriction as a robust method for extending lifespan in laboratory organisms; however the mechanism is a topic of much debate. Advancing our understanding of calorie restriction holds promise for illuminating biochemical processes involved in the aging process. One of the best explanations for the lifespan extension benefits of calorie restriction is that it improves cellular protein homeostasis (proteostasis), but because proteostasis is dynamic, it can be difficult to measure. We developed a novel combined omics methodology integrating kinetic proteomics, and applied it to a mouse model placed on calorie restriction. Our unbiased approach integrating just three measurements (kinetic proteomics, quantitative proteomics, and transcriptomics) enabled us to characterize the synthesis and degradation of thousands of proteins, and determine that calorie restriction largely alters proteostasis by slowing global protein synthesis post-transcriptionally. Validating our omics approach, we were able to replicate many previous results found in the literature, demonstrating the differential regulation of various protein ontologies in response to the nutrient stress of calorie restriction. Moreover, we were able to detect differential degradation of the large and small ribosomal subunits under calorie restriction, and proposed a model in which the rate of protein synthesis could be attenuated by the depletion of the large ribosomal subunit relative to the small subunit. The flexibility of our dynamic combined omics approach was demonstrated by the expansion of measurements to include nucleic acids and lipids. Flux measurements of DNA, ribosomal RNA, and lipids yielded cellular division rates, ribosome turnover, and lipid metabolism insights, respectively. We also adapted this approach to two-dimensional tissue imaging by DESI-MS in a proof-of-concept study to demonstrate its utility for studying regional differences in metabolism. The future integration of metabolomics and lipidomics into our combined omics approach would be facile, and add unprecedented depth to systems-wide studies involving cellular metabolism. Applied to the regulation of cellular homeostasis in humans, this has the potential to open new avenues for elucidating the etiology of aging, understanding the pathology of age-related diseases, and identifying novel targets for therapeutics.

Identiferoai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-10125
Date06 December 2019
CreatorsCarson, Richard Hajime
PublisherBYU ScholarsArchive
Source SetsBrigham Young University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations
Rightshttps://lib.byu.edu/about/copyright/

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