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      A mechanistic stochastic framework for regulating bacterial cell division

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          Nature, nurture, or chance: stochastic gene expression and its consequences.

          Gene expression is a fundamentally stochastic process, with randomness in transcription and translation leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans, and its characteristics depend both on the biophysical parameters governing gene expression and on gene network structure. Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others. These situations include the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.
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            Stochasticity in gene expression: from theories to phenotypes.

            Genetically identical cells exposed to the same environmental conditions can show significant variation in molecular content and marked differences in phenotypic characteristics. This variability is linked to stochasticity in gene expression, which is generally viewed as having detrimental effects on cellular function with potential implications for disease. However, stochasticity in gene expression can also be advantageous. It can provide the flexibility needed by cells to adapt to fluctuating environments or respond to sudden stresses, and a mechanism by which population heterogeneity can be established during cellular differentiation and development.
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              Robust growth of Escherichia coli.

              The quantitative study of the cell growth has led to many fundamental insights in our understanding of a wide range of subjects, from the cell cycle to senescence. Of particular importance is the growth rate, whose constancy represents a physiological steady state of an organism. Recent studies, however, suggest that the rate of elongation during exponential growth of bacterial cells decreases cumulatively with replicative age for both asymmetrically and symmetrically dividing organisms, implying that a "steady-state" population consists of individual cells that are never in a steady state of growth. To resolve this seeming paradoxical observation, we studied the long-term growth and division patterns of Escherichia coli cells by employing a microfluidic device designed to follow steady-state growth and division of a large number of cells at a defined reproductive age. Our analysis of approximately 10(5) individual cells reveals a remarkable stability of growth whereby the mother cell inherits the same pole for hundreds of generations. We further show that death of E. coli is not purely stochastic but is the result of accumulating damages. We conclude that E. coli, unlike all other aging model systems studied to date, has a robust mechanism of growth that is decoupled from cell death. Copyright 2010 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Scientific Reports
                Sci Rep
                Springer Science and Business Media LLC
                2045-2322
                September 2016
                July 26 2016
                September 2016
                : 6
                : 1
                Article
                10.1038/srep30229
                27456660
                f8e0b74e-3874-49f7-ad9f-d789cbd1f08f
                © 2016

                https://creativecommons.org/licenses/by/4.0

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