期刊
MOLECULAR BIOLOGY AND EVOLUTION
卷 30, 期 12, 页码 2568-2578出版社
OXFORD UNIV PRESS
DOI: 10.1093/molbev/mst138
关键词
growth rate; lag duration; single cell; glucose deprivation; natural variation; Saccharomyces cerevisiae; clonal heterogeneity; respiro-fermentative growth
资金
- National Institutes of Health [GM097415]
- National Science Foundation [MCB-1244219]
- Dupont Young Professor award
- Direct For Biological Sciences
- Div Of Molecular and Cellular Bioscience [1244219] Funding Source: National Science Foundation
In microbial populations, growth initiation and proliferation rates are major components of fitness and therefore likely targets of selection. We used a high-throughput microscopy assay, which enables simultaneous analysis of tens of thousands of microcolonies, to determine the sources and extent of growth rate variation in the budding yeast (Saccharomyces cerevisiae) in different glucose environments. We find that cell growth rates are regulated by the extracellular concentration of glucose as proposed by Monod (1949), but that significant heterogeneity in growth rates is observed among genetically identical individuals within an environment. Yeast strains isolated from different geographic locations and habitats differ in their growth rate responses to different glucose concentrations. Inheritance patterns suggest that the genetic determinants of growth rates in different glucose concentrations are distinct. In addition, we identified genotypes that differ in the extent of variation in growth rate within an environment despite nearly identical mean growth rates, providing evidence that alleles controlling phenotypic variability segregate in yeast populations. We find that the time to reinitiation of growth (lag) is negatively correlated with growth rate, yet this relationship is strain-dependent. Between environments, the respirative activity of individual cells negatively correlates with glucose abundance and growth rate, but within an environment respirative activity and growth rate show a positive correlation, which we propose reflects differences in protein expression capacity. Our study quantifies the sources of genetic and nongenetic variation in cell growth rates in different glucose environments with unprecedented precision, facilitating their molecular genetic dissection.
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