Using systems biology to predict lifespan in the yeast Saccharomyces cerevisiae

Date
2016
Authors
Hilsabeck, Tyler A.
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Abstract

Aging is a complex process that affects almost every species, albeit at different rates. Even within a species, individuals age at different rates and this variability is particularly intriguing at the single cell level where genetically identical organisms still exhibit large differences in lifespan even when environmental conditions are held constant. This disparity in aging rate both across and within species, suggests multiple factors likely act to control lifespan. For the most part, the nature of such factors are not fully known. In this study, I test the hypothesis that variance in lifespan of the single-celled yeast Saccharomyces cerevisiae is caused by alteration in nutrient metabolism; that is, when cells are constrained to operate in a distinct configuration of all their potential metabolic reactions, this, in and of itself, is sufficient to dictate lifespan outcome. To identify critical reactions for lifespan determination in S. cerevisiae, I modeled the metabolic configuration space of over 900 yeast single-gene knockout strains and then determined how usage of different metabolic configurations affected lifespan. Two separate, predictive models were created containing 7 and 18 terms, respectively, and with these models I identified flux changes in 439 key reactions responsible for variation in lifespan outcome. My results are consistent with the suggestion that metabolic configuration indeed plays a significant role in lifespan determination in S. cerevisiae, and that changes in mitochondrial lipid modifications mediated by the mitochondrial-associated membrane (MAM) subcellular compartment, are important longevity determinants.

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Keywords
Generalized Additive Modeling, in silico modeling, Replicative Lifespan, Saccharomyces Cerevisiae, yeast
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Department
Integrative Biology