Townsend, StJohn; (2023) Exploring long-term determinants of chronological lifespan using system-wide approaches. Doctoral thesis (Ph.D), UCL (University College London).

Preview

Text StJohnTownswend_Thesis_REVISED.pdf - Accepted Version Download (15MB) | Preview

Abstract

Ageing is a great research challenge. Age is the primary risk factor for many complex diseases, including cardiovascular disease, neurodegeneration and cancer. Anti-ageing interventions aim to delay the onset of these diseases and extend health span. Ageing remains enigmatic, however, and its proximal cause and mechanisms are not understood. This partly reflects the laborious nature of ageing experiments, typically requiring large timeframes and numerous individuals, which creates a bottleneck for systematic ageing studies. Yeast can be grown under highly parallelised experimental platforms and are well suited to systematic studies. However, ageing research is a notable exception, with the traditional colony-forming unit (CFU) assay for chronological lifespan being notoriously time- and resource-consuming. I present two alternative assays which circumnavigate this bottleneck. One is a high throughput CFU assay that is automated by robotics and supported by an R package to estimate culture viability by constructing a statistical model based on colony patterns. The second assay employs barcode sequencing to monitor strain viability in competitively ageing pools of deletion libraries, providing genome-scale functional insights into the genetics of lifespan. I employ this assay to dissect the genetic basis of rapamycin-mediated longevity, providing insights into the condition-specific nature of lifespan-extending mutations and the anti-ageing action of rapamycin. Experimental reproducibility is essential for research. Ageing studies, including those in yeast, are notably sensitive to batch effects: genetically identical cells grown under identical conditions can exhibit substantial phenotypic differences. I systematically test typically neglected factors, and demonstrate that chronological lifespan is strongly affected by pre-culture protocol such as the amount of colony picked for the pre-culture – suggesting a ‘memory’ which is passed across cell divisions from pre-culture to non-dividing, ageing cells. Hence, this work addresses key issues in yeast ageing research, both technological and biological, establishing a platform to robustly perform future studies at large scales.

Download activity - last month

Export as JSONCSVXML

Download activity - last 12 months

Export as CSVXMLJSON

Downloads by country - last 12 months

Export as JSONCSVXML

Archive Staff Only

View Item