Growth, Cell and Nuclear Divisions in some Bacteria

Schaechter, Moselio; Williamson, Joan P.; Jiang, Jun; Koch, Arthur L.

doi:10.1099/00221287-29-3-421

Cited by 285 publications

(174 citation statements)

References 25 publications

(14 reference statements)

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“…Hence, a single growth (elongation) rate α, obtained by fitting the plot of length vs. time with an exponential (9) for each cell cycle, is a satisfactory approximation of the single-cell elongation process. In agreement with previous observations (2,9,16,17), histograms of doubling time, growth rate, and size show a substantial degree of cell-to-cell variability even in tightly controlled environmental conditions, with roughly Gaussian growth rate distributions, and right-skewed initial and final size distributions ( Fig. 1 C−…”

Section: Resultssupporting

confidence: 77%

“…1B) from an initial size x 0 to a final size x f during a doubling time τ. Because, in steadystate growth, E. coli grows essentially through elongation, we used cell length to quantify growth (2,9,12). Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Attempts to address this long-standing question have been limited by restricted experimental access to single-cell attributes (2)(3)(4)(5). Even in the simple model organism E. coli, a fully quantitative characterization of how cell division time and size are determined is lacking (6), with most attempts dating back to the 1960s (2,7,8). Current high-throughput microfluidic techniques enable experiments measuring the attributes of many cells (9) opening up the possibility of testing quantitative models of cell division control.…”

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confidence: 99%

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Concerted control of Escherichia coli cell division

Osella

Nugent

Lagomarsino

2014

Proc. Natl. Acad. Sci. U.S.A.

178

260

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The coordination of cell growth and division is a long-standing problem in biology. Focusing on Escherichia coli in steady growth, we quantify cell division control using a stochastic model, by inferring the division rate as a function of the observable parameters from large empirical datasets of dividing cells. We find that (i) cells have mechanisms to control their size, (ii) size control is effected by changes in the doubling time, rather than in the single-cell elongation rate, (iii) the division rate increases steeply with cell size for small cells, and saturates for larger cells. Importantly, (iv) the current size is not the only variable controlling cell division, but the time spent in the cell cycle appears to play a role, and (v) common tests of cell size control may fail when such concerted control is in place. Our analysis illustrates the mechanisms of cell division control in E. coli. The phenomenological framework presented is sufficiently general to be widely applicable and opens the way for rigorous tests of molecular cell-cycle models.

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Section: Resultssupporting

confidence: 77%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

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Concerted control of Escherichia coli cell division

Osella

Nugent

Lagomarsino

2014

Proc. Natl. Acad. Sci. U.S.A.

178

260

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“…However, at the single-cell level, growth-related parameters such as the division time interval and division cell size are heterogeneous even in a clonal population growing at a constant rate (4)(5)(6)(7)(8)(9). Such "growth noise" causes concurrently living cells to compete within the population for representation among its future descendants.…”

mentioning

confidence: 99%

Noise-driven growth rate gain in clonal cellular populations

Hashimoto

Nozoe

Nakaoka

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

163

205

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Cellular populations in both nature and the laboratory are composed of phenotypically heterogeneous individuals that compete with each other resulting in complex population dynamics. Predicting population growth characteristics based on knowledge of heterogeneous single-cell dynamics remains challenging. By observing groups of cells for hundreds of generations at single-cell resolution, we reveal that growth noise causes clonal populations of Escherichia coli to double faster than the mean doubling time of their constituent single cells across a broad set of balanced-growth conditions. We show that the population-level growth rate gain as well as age structures of populations and of cell lineages in competition are predictable. Furthermore, we theoretically reveal that the growth rate gain can be linked with the relative entropy of lineage generation time distributions. Unexpectedly, we find an empirical linear relation between the means and the variances of generation times across conditions, which provides a general constraint on maximal growth rates. Together, these results demonstrate a fundamental benefit of noise for population growth, and identify a growth law that sets a "speed limit" for proliferation.growth noise | age-structured population model | cell lineage analysis | growth law | microfluidics C ell growth is an important physiological process that underlies the fitness of organisms. In exponentially growing cell populations, proliferation is usually quantified using the bulk population growth rate, which is assumed to represent the average growth rate of single cells within a population. In addition, basic growth laws exist that relate ribosome function and metabolic efficiency, macromolecular composition, and cell size of the culture as a whole to the bulk population growth rate (1-3). Population growth rate is therefore a quantity of primary importance that reports cellular physiological states and fitness.However, at the single-cell level, growth-related parameters such as the division time interval and division cell size are heterogeneous even in a clonal population growing at a constant rate (4-9). Such "growth noise" causes concurrently living cells to compete within the population for representation among its future descendants. For example, if two sibling cells born from the same mother cell had different division intervals, the faster dividing sibling is likely to have more descendants in the future population compared with its slower dividing sister, despite the fact that progenies of both siblings may proliferate equally well (Fig. 1). Intrapopulation competition complicates single-cell analysis because any growth-correlated quantities measured over the population deviate from intrinsic single-cell properties (10-12). In the case of the toy model described in Fig. 1, cells are assumed to determine their generation times (division interval) randomly by roll of a dice. The mean of intrinsic cellular generation time is thus ð1 + 2 + ⋯ + 6Þ=6 = 3.5 h, but population doubling time, which is...

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“…enzymes (C, W, V, V'), must be present as one produces new bacterial mass only from pre-existing living bacterial mass. The reaction k. 7 in equation (4) may be construed to provide for feed-back control cn rate of energy availability.…”

Section: Consider Equation (3)mentioning

confidence: 99%

The Living Cell as an Open Thermodynamic System: Bacteria and Irreversible Thermodynamics

Mercer¹

1971

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Growth, Cell and Nuclear Divisions in some Bacteria

Cited by 285 publications

References 25 publications

Concerted control of Escherichia coli cell division

Concerted control of Escherichia coli cell division

Noise-driven growth rate gain in clonal cellular populations

The Living Cell as an Open Thermodynamic System: Bacteria and Irreversible Thermodynamics

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