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Title: Macromolecular Crowding Regulates the Gene Expression Profile by Limiting Diffusion

Journal Article · · PLoS Computational Biology (Online)
 [1];  [2];  [2];  [3]
  1. Univ. of California, Santa Barbara, CA (United States). Dept. of Mechanical Engineering
  2. Univ. of California, Santa Barbara, CA (United States). Dept. of Computer Science
  3. Univ. of California, Santa Barbara, CA (United States). Dept. of Mechanical Engineering and Dept. of Computer Science

We seek to elucidate the role of macromolecular crowding in transcription and translation. It is well known that stochasticity in gene expression can lead to differential gene expression and heterogeneity in a cell population. Recent experimental observations by Tan et al. have improved our understanding of the functional role of macromolecular crowding. It can be inferred from their observations that macromolecular crowding can lead to robustness in gene expression, resulting in a more homogeneous cell population. We introduce a spatial stochastic model to provide insight into this process. Our results show that macromolecular crowding reduces noise (as measured by the kurtosis of the mRNA distribution) in a cell population by limiting the diffusion of transcription factors (i.e. removing the unstable intermediate states), and that crowding by large molecules reduces noise more efficiently than crowding by small molecules. Finally, our simulation results provide evidence that the local variation in chromatin density as well as the total volume exclusion of the chromatin in the nucleus can induce a homogenous cell population

Research Organization:
Univ. of California, Santa Barbara, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division; National Science Foundation (NSF); US Army Research Office (ARO)
Grant/Contract Number:
SC0008975; DMS-1001012; W911NF-09-0001; R01-EB014877; R01-GM113241
OSTI ID:
1345287
Alternate ID(s):
OSTI ID: 1423941
Journal Information:
PLoS Computational Biology (Online), Journal Name: PLoS Computational Biology (Online) Vol. 12 Journal Issue: 11; ISSN 1553-7358
Publisher:
Public Library of ScienceCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 26 works
Citation information provided by
Web of Science

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