Supplemental Figure 1: Realistic modeling of cell size noise and cell growth rate noise as a function of division rates from Division rate, cell size and proteome allocation: impact on gene expression noise and implications for the dynamics of genetic circuits

(A) Model description. The model is as described in Figure 2-A, with the following additional assumptions. The exponential cell growth rate is assumed to be normally distributed around the population average. Noise and memory in cell division and birth size are modeled with the recently proposed 'noisy linear map' (Tanouchi et al, 2015; Jun & Taheri-Araghi, 2015). The case a = 1 corresponds to the ‘adder’ principle (Taheri-Araghi et al, 2015) and a = 0 means that birth size is independent of previous birth size (‘sizer’). (B) Extraction of noisy linear map and cell growth rate noise parameters as a function of population division rate from recent mother machine data at different growth conditions (Taheri-Araghi et al, 2015). We fit simple linear trends to the extracted data to extrapolate to intermediate growth conditions. bµ is chosen such that average birth size matches Vbrith(µ) = b(µ)/2-a(µ) = 0.19 × 21.11×µ. This exponential dependency has been shown in (Taheri-Araghi et al, 2015) to describe the data very well (see their Figure S1). (C) Histograms of individual cell growth rates at different growth conditions show that using normal distributions is accurate.