Figure 3
Biofoundry validation of SDC evolution under stronger segregation. (A) Frequency distribution of the lag times of the population dynamics for 3 ~ 4 colonies when $\lambda$ = 2. The lag time measurement was detailed in the Materials and Methods and Fig. S6a. (B) Illustration of an automated SGSP workflow with the biofoundry technology (see Materials and Methods for details). (C) Experimental and simulated results showed that the$\Delta R$ decreased with $\lambda$. A positive$\Delta R$ ($\Delta R$  $\ge$ 0) indicated an increase in SDCs, whereas a negative $\Delta R$($\Delta R$< 0) showed an increase in cheaters. The error bar represented the standard deviation for three technical replicates, and the antibiotic stress was set at 0.4 mg/ml 6-APA. Exp., experiment; Simu., simulation.

Biofoundry validation of SDC evolution under stronger segregation. (A) Frequency distribution of the lag times of the population dynamics for 3 ~ 4 colonies when |$\lambda$| = 2. The lag time measurement was detailed in the Materials and Methods and Fig. S6a. (B) Illustration of an automated SGSP workflow with the biofoundry technology (see Materials and Methods for details). (C) Experimental and simulated results showed that the|$\Delta R$| decreased with |$\lambda$|⁠. A positive|$\Delta R$| (⁠|$\Delta R$|  |$\ge$| 0) indicated an increase in SDCs, whereas a negative |$\Delta R$|(⁠|$\Delta R$|< 0) showed an increase in cheaters. The error bar represented the standard deviation for three technical replicates, and the antibiotic stress was set at 0.4 mg/ml 6-APA. Exp., experiment; Simu., simulation.

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