Abstract
For a genetically identical microbial population, multi-gene expression in various environments requires effective allocation of limited resources and precise control of heterogeneity among individual cells. However, it is unclear how resource allocation and cell-to-cell variation jointly shape the overall performance. Here we demonstrate a Simpson's paradox during overexpression of multiple genes: two competing proteins in single cells correlated positively for every induction condition, but the overall correlation was negative. Yet this phenomenon was not observed between two competing mRNAs in single cells. Our analytical framework shows that the phenomenon arises from competition for translational resource, with the correlation modulated by both mRNA and ribosome variability. Thus, heterogeneity plays a key role in single-cell multi-gene expression and provides the population with an evolutionary advantage, as demonstrated in this study.
Highlights
Bacteria often simultaneously turn on the expression of multiple pathways or cellular machineries to perform multitasking in response to various conditions
Microbes perform multitasking for a wide range of purposes, including survival, adaptation, colonization, and evolution. Both modelling and experimental results at the ensemble level reveal trade-offs between different tasks due to resource competition, but it is unclear how single cells allocate limited intracellular resources to perform multitasking, and how does a population coordinate single cell performances during multitasking to maximize population efficiencies. We address this question by using bacterial multi-gene overexpression as the basic form of multitasking
We demonstrate that the phenomenon arises from competition for translational resources, with the correlation modulated by heterogeneity of both mRNA and ribosomes
Summary
Bacteria often simultaneously turn on the expression of multiple pathways or cellular machineries to perform multitasking in response to various conditions. Modules for different tasks often compete with each other for limited intracellular resources, which could affect the performance of the overall system [6,7,8,9]. The performance of a module varies from cell to cell due to biological stochasticity, leading to phenotypic heterogeneity. Distinctive phenotypes within a genetically identical population are sometimes harnessed as a mechanism for division of labor, where distinct subpopulations perform different tasks, reducing resource competition within each single cell. It remains elusive to what degree phenotypic heterogeneity affects simultaneous operation of multiple functional modules within every single cell. How do single cells deal with resource competition, and how does a population coordinate single cell performances during multitasking to maximize population efficiencies [2,13,14]?
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