Figure 2. Plots that could potentially lead to misinterpreting exponential growth.

(A, B) Data is obtained from experiments in M9 alanine medium ($⟨T_d⟩$ = 214 min, N = 816 cells). (A) $\ln (\frac{L_d}{L_b})$ vs $⟨\lambda ⟩T_d$ plot is shown. The blue dots are the raw data, the red correspond to the binned data trend, the yellow line is the best linear fit obtained by performing linear regression on the raw data and the black dashed line is the y = x line. A priori, non-linear trend in binned data might point to growth being non-exponential. (B) $⟨\lambda ⟩T_d$ vs $\ln (\frac{L_d}{L_b})$ plot is shown for the same experiments. (C, D) Simulations of exponentially growing cells following the adder model are carried out for N = 2500 cells. The parameters used are provided in the Simulations section. (C) $\ln (\frac{L_d}{L_b})$ vs $⟨\lambda ⟩T_d$ plot is shown. The trend in binned data shown in red is non-linear and the best linear fit of raw data (yellow) deviates from the y = x line (black dashed line). The black dotted line is the expected trend obtained from theory (Equation 2). For parameters used in the simulations here, the black dotted line follows $\ln (\frac{L_d}{L_b})=1.26⟨\lambda ⟩T_d-0.38{(⟨\lambda ⟩T_d)}^2$. (D) $⟨\lambda ⟩T_d$ vs $\ln (\frac{L_d}{L_b})$ plot is shown with binned data in red and the best linear fit on raw data in yellow closely following the expected trend of y = x line (black dashed line). The theoretical binned data trend (black dotted line) is expected to follow the y = x trend. In all of these plots, the binned data is shown only for those bins with more than 15 data points in them.

Figure 2—figure supplement 1. Experimental data: $\ln \mathbf{}\mathrm{(}\frac{L_d}{L_b}\mathrm{)}$ vs $⟨\lambda ⟩T_d$ (left) and $⟨\lambda ⟩T_d$ vs $\ln (\frac{L_d}{L_b})$ plot (right) is shown for, (A).

Cells growing in glycerol medium ($⟨T_d⟩$ = 164 min, N = 648 cells). (B) Cells growing in glucose-cas medium ($⟨T_d⟩$ = 65 min, N = 737 cells). Binned data (red), and the best linear fit (yellow) obtained by performing linear regression on the raw data deviate from the y = x line (black dashed line) in the case of $\ln (\frac{L_d}{L_b})$ vs $⟨\lambda ⟩T_d$ plots in both media. However, both binned data and the best linear fit are in close agreement with the y = x line (black dashed line) on interchanging the axes. In all of these plots, the binned data is shown only for those bins with more than 15 data points in them.

Figure 2—figure supplement 2. Binned data trend in growth rate ($\lambda$) and inverse generation time ($\frac{\mathrm{1}}{T_d}$) plots.

(A-B) Simulations of the adder model for exponentially growing cells were carried out at multiple growth rates for N = 2500 cells. The size added between birth and division and the mean growth rates were extracted from Kennard et al., 2016. The CV of growth rates was greater for cells growing in slower-growth media. See the Simulations section for the parameter values. For these simulations, we show (A) $\lambda$ vs $\frac{1}{T_d}$ plot. (B) $\frac{1}{T_d}$ vs $\lambda$ plot. The smaller circles show the trend in binned data within a growth medium. Different colors correspond to different growth media. Population means are shown as larger markers. The population means agree with the expected y = $\ln (2)$ x line (black dashed line) in (A) but the trend within a single growth medium is non-linear and deviates from the y = $\ln (2)$ x line. However, in (B), population means across growth conditions and the trend in binned data within a single growth medium follow the expected y = $\frac{1}{\ln (2)}$ x line (black dotted line).