Bacterial Growth Control Mechanisms Inferred from Multivariate Statistical Analysis of Single-Cell Measurements

Non-genetic inheritance restraint of cell-to-cell variation

“…The growth rate difference between the small and large sisters, decreases to almost zero by the end of the first cell cycle after separation (Figure 5B inset). This result reveals that the exponential growth rate of a cell immediately after division inversely scales with the size-fraction the cell receives from its mother (see also Kohram et al (2020)). It also demonstrates that the difference in the growth rates between SCs changes during the cell cycle indicating that they are not constant throughout the whole cycle as has been accepted so far (Godin et We have also examined how the protein concentration varies over time between the two cells by measuring the concentration of GFP (green fluorescent protein), via its fluorescence intensity, expressed from a constitutive promoter in a medium copy-number plasmid.…”

Multiple timescales in bacterial growth homeostasis

“…This result is somewhat surprising, as f exhibits the smallest CV among phenotypic variables, and is often considered irrelevant to growth homeostasis. A recent study however, showed that on short timescales f does correlate with the growth rate in the following cell cycle: the smaller-fraction daughter cell was found to grow faster than its larger sister (Kohram et al 2021).…”

“…Despite our best efforts to control the environment in microfluidic devices, some measurements do not exhibit similar statistics in repeated experiments that are nominally identical in external conditions. For example, distributions of cell size and highly expressed proteins collapse onto a universal shape after scaling, over a broad range and with very high precision, but when measured in physical units these variables exhibit a persistent individuality among lineages measured in different traps (Salman et al 2012;Brenner et al 2015a;Susman et al 2018;Kohram et al 2021). This individuality is apparent well beyond experimental error, but its origins remain unclear.…”

“…Such variables have been extensively used to infer statistical properties of bacterial physiology and variability (Amir 2014;Sauls, Li, and Jun 2016;Grilli et al 2017); they are illustrated in Fig 2A . One may identify the two fundamental time/rate variables in each cycle, the inter-division (or generation) time τ and the single-cycle exponential growth-rate α. Although growth deviates from an exact exponential when measured carefully (Kohram et al 2021;Nordholt, Heerden, and Bruggeman 2020;Vashistha, Kohram, and Salman 2021), the best fit exponential rate is still a useful approximation for growth over the cell cycle and will be used in what follows. Cell size is characterized by its length x 0 at the start and x τ at the end of each cycle, as well as their difference ∆ = x τ − x 0 .…”

“…An unbiased approach to test this question is required. Recent progress in this direction, using multivariate linear regression, revealed that multiple coordinated mechanisms could be involved in cell size regulation (Kohram et al 2021). Still, a holistic data-driven approach is not well developed.…”