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The robust regulation of the cell cycle is critical for the survival and proliferation of bacteria. To gain a comprehensive understanding of the mechanisms regulating the bacterial cell cycle, it is essential to accurately quantify cell-cycle-related parameters and to uncover quantitative relationships. In this paper, we demonstrate that the quantification of cell size parameters using microscopic images can be influenced by software and by the parameter settings used. Remarkably, even if the consistent use of a particular software and specific parameter settings is maintained throughout a study, the type of software and the parameter settings can significantly impact the validation of quantitative relationships, such as the constant-initiation-mass hypothesis. Given these inherent characteristics of microscopic image-based quantification methods, it is recommended that conclusions be cross-validated using independent methods, especially when the conclusions are associated with cell size parameters that were obtained under different conditions. To this end, we presented a flexible workflow for simultaneously quantifying multiple bacterial cell-cycle-related parameters using microscope-independent methods. [ABSTRACT FROM AUTHOR]

The robust regulation of the cell cycle is critical for the survival and proliferation of bacteria. To gain a comprehensive understanding of the mechanisms regulating the bacterial cell cycle, it is essential to accurately quantify cell-cycle-related parameters and to uncover quantitative relationships. In this paper, we demonstrate that the quantification of cell size parameters using microscopic images can be influenced by software and by the parameter settings used. Remarkably, even if the consistent use of a particular software and specific parameter settings is maintained throughout a study, the type of software and the parameter settings can significantly impact the validation of quantitative relationships, such as the constant-initiation-mass hypothesis. Given these inherent characteristics of microscopic image-based quantification methods, it is recommended that conclusions be cross-validated using independent methods, especially when the conclusions are associated with cell size parameters that were obtained under different conditions. To this end, we presented a flexible workflow for simultaneously quantifying multiple bacterial cell-cycle-related parameters using microscope-independent methods.

Summary It is generally assumed that the allocation and synthesis of total cellular resources in microorganisms are uniquely determined by the growth conditions. Adaptation to a new physiological state leads to a change in cell size via reallocation of cellular resources. However, it has not been understood how cell size is coordinated with biosynthesis and robustly adapts to physiological states. We show that cell size in Escherichia coli can be predicted for any steady-state condition by projecting all biosynthesis into three measurable variables representing replication initiation, replication-division cycle, and the global biosynthesis rate. These variables can be decoupled by selectively controlling their respective core biosynthesis using CRISPR interference and antibiotics, verifying our predictions that different physiological states can result in the same cell size. We performed extensive growth inhibition experiments, and we discovered that cell size at replication initiation per origin, namely the initiation mass or unit cell, is remarkably invariant under perturbations targeting transcription, translation, ribosome content, replication kinetics, fatty acid and cell wall synthesis, cell division, and cell shape. Based on this invariance and balanced resource allocation, we explain why the total cell size is the sum of all unit cells. These results provide an overarching framework with quantitative predictive power over cell size in bacteria. [ABSTRACT FROM AUTHOR]

Abstract: One of the recognized prokaryotic cell cycle theories is Cooper–Helmstetter (CH) theory which relates start of DNA replication to particular (initiation) cell mass, cell growth and division. Different aspects of this theory have been extensively studied in the past. In the present study CH theory was applied at single cell level. Universal equations were derived for different cell parameters (cell mass and volume, surface area, DNA amount and content) depending on constructivist cell cycle parameters (unit mass, replication and division times, cell age, cell cycle duration) based on selected growth laws of cell mass (linear, exponential). The equations derived can be integrated into single-cell models for the analysis and design of bacterial cells. [Copyright &y& Elsevier]

The relationships between growth rate, cell-cycle parameters, and cell size were examined in two unicellular cyanobacteria representative of open-ocean environments: Prochlorococcus (strain MIT9312) and Synechococcus (strain WH8103). Chromosome replication time, C, was constrained to a fairly narrow range of values (∼4–6 h) in both species and did not appear to vary with growth rate. In contrast, the pre- and post-DNA replication periods, B and D, respectively, decreased with increasing growth rate from maxima of ∼30 and 10–20 h to minima of ∼4–6 and 2–3 h, respectively. The combined duration of the chromosome replication and postreplication periods ( C+ D), a quantity often used in the estimation of Prochlorococcus in situ growth rates, varied ∼2.4-fold over the range of growth rates examined. This finding suggests that assumptions of invariant C+ D may adversely influence Prochlorococcus growth rate estimates. In both strains, cell mass was the greatest in slowly growing cells and decreased 2- to 3-fold over the range of growth rates examined here. Estimated cell mass at the start of replication appeared to decrease with increasing growth rate, indicating that the initiation of chromosome replication in Prochlorococcus and Synechococcus is not a simple function of cell biomass, as suggested previously. Taken together, our results reflect a notable degree of similarity between oceanic Synechococcus and Prochlorococcus strains with respect to their growth-rate-specific cell-cycle characteristics. [ABSTRACT FROM AUTHOR]

Cell cycle behavior in the marine Synechococcus strain WH8101 was examined in detail over a wide range of light- and nitrogen-limited growth rates. The presence of bimodal DNA frequency distributions under all conditions confirms that the overlapping rounds of DNA replication that characterize E. coli and other fast-growing prokaryotes are not present in this organism. Although chromosome replication time, C, was constrained to a fairly narrow range of values overall, it nevertheless did vary with growth rate and limiting factor. Light-limited cells growing at moderate rates had higher C values than did N-limited cells growing at comparable rates (by as much as a factor of 2). As these cells became light saturated, however, C decreased sharply to the level observed under N limitation. The post-replication period, D, decreased monotonically with growth rate under both light and N limitation, approaching a constant value at moderate to high growth rates. Average cell volume at the time of initiation of DNA replication was calculated from the values of C and D, combined with directly measured mean cell volume, and was found to be constant at all growth rates above ∼0.7 d-1. This pattern was confirmed by estimates of initiation volume based on flow cytometric light scatter measurements, and suggests that as has been found in other prokaryotic systems, cell mass may play an important role in regulating the timing of chromosome replication in cyanobacteria. Furthermore, because the magnitude of C + D influences average cell mass (given a constant mass at initiation), changes in these parameters (particularly C) may be responsible for the previously reported nonlinear relationship between light-limited growth rate and both RNA cell-1 and average cell volume. [ABSTRACT FROM AUTHOR]