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Gottschling, D. E.

Publications and source records attributed to Gottschling, D. E..

3 recordsLinked to original sources

Cell enlargement drives aging-associated proteome remodeling and shortens replicative lifespan

The molecular and cellular basis of aging and its associated functional decline remains poorly understood. Even free-living microorganisms age and, in yeast, replicative aging shares key hallmarks with human cellular senescence, including progressive cell enlargement. Recent work has shown that chemical and genetic manipulations that increase cell size promote the onset of senescence in both yeast and human cells, suggesting that cell enlargement can drive some of the physiological changes associated with aging. Here, we quantitatively determined how cell enlargement contributes to age-associated physiology in yeast by combining automated aging technologies with quantitative proteomics. We find that the majority of aging-associated proteome remodeling can be recapitulated by genetically enlarging young proliferating cells. These enlarged cells exhibit accelerated proteome aging and shortened replicative lifespans, while smaller cells are longer-lived. While cell enlargement is the predominant factor driving proteome remodeling during aging, we also identified a minority of aging-specific molecular markers whose expression influences lifespan. Together, our results demonstrate that cell enlargement is a major driver of aging-associated proteome remodeling and influences lifespan independently of established aging factors such as extrachromosomal rDNA circles.

cell biology↗

The Yeast Lifespan Machine: a microfluidic platform for automated replicative lifespan measurements

The budding yeast, Saccharomyces cerevisiae, has emerged as a model system for studying the aging processes in eukaryotic cells. However, the full complement of tools available in this organism has not been fully applied, in part because of limitations in throughput that restrict the ability to carry out detailed analyses. Recent advances in microfluidics have provided direct longitudinal observation of entire yeast lifespans, but have not yet achieved the normal scale of operation possible in this model system. Here we present a microfluidic platform, called the Yeast Lifespan Machine, where we combine improvements in microfluidics, image acquisition, and image analysis tools to increase robustness and throughput of lifespan measurements in aging yeast cells. We demonstrate the platforms ability to measure the lifespan of large populations of cells and distinguish long- and short-lived mutants, all with minimal involvement of the experimenter. We also show that environmental pH is capable of significantly modulating lifespan depending on the growth media, highlighting how microfluidic technologies reveal determinants of lifespan that are otherwise difficult to ascertain.

cell biology↗

Protein-Metabolite Interactomics Reveals Novel Regulation of Carbohydrate Metabolism

Metabolism is highly interconnected and also has profound effects on other cellular processes. However, the interactions between metabolites and proteins that mediate this connectivity are frequently low affinity and difficult to discover, hampering our understanding of this important area of cellular biochemistry. Therefore, we developed the MIDAS platform, which can identify protein-metabolite interactions with great sensitivity. We analyzed 33 enzymes from central carbon metabolism and identified 830 protein-metabolite interactions that were mostly novel, but also included known regulators, substrates, products and their analogs. We validated previously unknown interactions, including two atomic-resolution structures of novel protein-metabolite complexes. We also found that both ATP and long-chain fatty acyl-CoAs inhibit lactate dehydrogenase A (LDHA), but not LDHB, at physiological concentrations in vitro. Treating cells with long-chain fatty acids caused a loss of pyruvate/lactate interconversion, but only in cells reliant on LDHA. We propose that these regulatory mechanisms are part of the metabolic connectivity that enables survival in an ever-changing nutrient environment, and that MIDAS enables a broader and deeper understanding of that network.

biochemistry↗