Noise-driven growth rate gain in clonal cellular populations

Abstract

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...

Invariance of Initiation Mass and Predictability of Cell Size in Escherichia coli

“…We planned to perturb translation, transcription, DNA replication, cell division, cell wall synthesis for a wide range of growth inhibition and nutrient limitation, and quantitatively predict how cell size changes. We realized that a high-throughput single-cell approach [15,16] that led to the discovery of the “adder” principle [3,17,18] and its critical analysis [6] or the effects of growth rate fluctuations [16] was not feasible because of the large number of different experimental conditions involved. To this end, we took a population-level approach and built a multiplex turbidostat, which ensures long-term steady-state cell cultures in multiple independent growth conditions in a single experiment [19,20] (Figure 1C; see Supplemental Information).…”

Image analysis driven single-cell analytics for systems microbiology

“…We chose the Gamma distribution because the histograms of the aforementioned attributes have similar shape (skewness) to it (in Additional file 1: Figure S2 and Figure S3). Moreover, the gamma distribution is a flexible two-parameter distribution that belongs to exponential family and is used to model physical quantities that take positive values in microbiology, such as the cell division time (as in [14, 73]), the cell elongation rate (as in [73] and cell division length (as in [71]). The estimated parameters are provided in (see Additional file 1: Table S3).…”

The effects of individual nonheritable variation on fitness estimation and coexistence

“…As noted by Hashimoto et al (2016), nonheritable variation in longevity can also reduce the doubling time of a population in relation to the mean longevity of its constitutive cells. Simple arguments, which attend to the normalization M = 1, show that this finding is compatible with our results (not shown).…”

“…The notion that individual bacterial cells of the same genotype vary in their rates of cell division is supported by independent studies that used microfluidic techniques to track thousands of bacterial cells to determine their individual lifespan and map division events(Hashimoto et al, 2016;Jouvet et al, 2018). The notion that individual bacterial cells of the same genotype vary in their rates of cell division is supported by independent studies that used microfluidic techniques to track thousands of bacterial cells to determine their individual lifespan and map division events(Hashimoto et al, 2016;Jouvet et al, 2018).…”