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Fig 1.

Decay of a drug-susceptible bacterial population in the presence of a bactericidal antibiotic.

The horizontal axis, representing time t (minutes), is linear, while the vertical axis is on a logarithmic scale and represents the proportion of the population that is still alive. Descending full lines represent the exponential decay of the non-persistent population, according to exp(-0.04 t). When t = τ0, only persisters are alive. The broken lines represent decay according to the power-law 1/t2. The dotted lines represent exponential decay, i.e., according to exp(-k t). A: Persisters decay according to constant k = 0.005 min-1. B: Persisters decay according to constant k = 0.0025 min-1.

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Fig 1 Expand

Fig 2.

Indirect resistance and the survival of susceptible cells through persistence.

When exposed to antibiotics, persister cells survive and eventually grow after medium detoxification by resistant cells. Blue circles represent susceptible cells, and orange circles represent resistant cells. In this figure, we assumed that detoxification by resistant cells is the single mechanism responsible for eliminating the antibiotic.

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Fig 2 Expand

Table 1.

Experimental data (mean values ± standard deviation) from ref. [14]*.

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Table 1 Expand

Fig 3.

Flowchart of the program.

After distributing cells in the ’plate’, the program simulates bacterial growth during as many generations as the ones completed in experiments of ref. [14]. The decay of the bacteria varies depending on the time interval in which the simulation is. Dotted lines only happen when the biological assumption is that persister cells leave the dormant state as soon as their site is nontoxic.

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Fig 3 Expand

Table 2.

Pseudocode of the program*.

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Table 2 Expand

Table 3.

Estimation of the number of surviving susceptible cells at inoculation time.

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Table 3 Expand

Table 4.

The parameters of the simulations that explain the experimental results.

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Table 4 Expand

Table 5.

The impact of plasmid transfer to detoxification is low.

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Table 5 Expand