Effects of cell-cycle-dependent expression on random fluctuations in protein levels. Issue 12 (December 2016)

• Record Type: Journal Article
• Authors: Soltani, Mohammad; Singh, Abhyudai
• Is Part Of: Royal Society open science. Volume 3:Issue 12(2016)
• Publication Date: 2016-12
• Subjects: cell-to-cell variability -- moment dynamics -- noise decomposition -- stochastic cell-cycle times -- cell division; Science -- Periodicals; 500
• DOI: 10.1098/rsos.160578
• Languages: English
• ISSNs: 2054-5703

Abstract

Abstract : Expression of many genes varies as a cell transitions through different cell-cycle stages. How coupling between stochastic expression and cell cycle impacts cell-to-cell variability (noise) in the level of protein is not well understood. We analyse a model where a stable protein is synthesized in random bursts, and the frequency with which bursts occur varies within the cell cycle. Formulae quantifying the extent of fluctuations in the protein copy number are derived and decomposed into components arising from the cell cycle and stochastic processes. The latter stochastic component represents contributions from bursty expression and errors incurred during partitioning of molecules between daughter cells. These formulae reveal an interesting trade-off: cell-cycle dependencies that amplify the noise contribution from bursty expression also attenuate the contribution from partitioning errors. We investigate the existence of optimum strategies for coupling expression to the cell cycle that minimize the stochastic component. Intriguingly, results show that a zero production rate throughout the cell cycle, with expression only occurring just before cell division, minimizes noise from bursty expression for a fixed mean protein level. By contrast, the optimal strategy in the case of partitioning errors is to make the protein just after cell division. We provide examples of regulatory proteins that are expressed only towards the end of the cell cycle, and argue that such strategies enhance robustness of cell-cycle decisions to the intrinsic stochasticity of gene expression.