Stochastic expression of a multiple antibiotic resistance activator confers transient resistance in single cells

Abstract

Transient resistance can allow microorganisms to temporarily survive lethal concentrations of antibiotics. This can be accomplished through stochastic mechanisms, where individual cells within a population display diverse phenotypes to hedge against the appearance of an antibiotic. To date, research on transient stochastic resistance has focused primarily on mechanisms where a subpopulation of cells enters a dormant, drug-tolerant state. However, a fundamental question is whether stochastic gene expression can also generate variable resistance levels among growing cells in a population. We hypothesized that stochastic expression of antibiotic-inducible resistance mechanisms might play such a role. To investigate this, we focused on a prototypical example of such a system: the multiple antibiotic resistance activator MarA. Previous studies have shown that induction of MarA can lead to a multidrug resistant phenotype at the population level. We asked whether MarA expression also has a stochastic component, even when uninduced. Time lapse microscopy showed that isogenic cells express heterogeneous, dynamic levels of MarA, which were correlated with transient antibiotic survival. This finding has important clinical implications, as stochastic expression of resistance genes may be widespread, allowing populations to hedge against the sudden appearance of an antibiotic.

Figure 1. Cell-to-cell variability in the multiple antibiotic resistance activator MarA.

(a) Schematic view of the marRAB operon. MarA activates the operon by binding to one site within the operator, MarR represses its expression by binding to two sites, and MarB indirectly represses expression of the operon. (b) Minimum inhibitory concentration of carbenicillin for the strains P_marA-cfp (wildtype) and MarA-CFP (+MarA). Error bars show standard deviations from three biological replicates. (c) A representative filmstrip of time-lapse microscopy images showing variability in P_marA-cfp fluorescence levels within a microcolony. Supplementary Movie 1 shows additional details.

Figure 2. Variability in MarA expression is correlated with a heterogeneous response to carbenicillin treatment.

(a,c,e) Time-lapse microscopy images of (a) P_marA-cfp, (c) P_marA-cfp ΔmarRAB, and (e) MarA-CFP in the presence of 50 μg/ml carbenicillin and 10 μg/ml propidium iodide. Cells were introduced onto agarose pads containing carbenicillin and propidium iodide at t = 0 mins and imaged over the course of 400 mins in two color channels. Cyan indicates CFP levels from the MarA reporter; red indicates the death marker propidium iodide. Supplementary Movie 2 shows additional details for the P_marA-cfp strain. Note that in the MarA-CFP strain the localization patterns in CFP are due to binding of MarA to DNA. (b,d,f) Outcomes of individual cells after 400 mins of carbenicillin exposure, plotted versus CFP fluorescence at t = 0 mins for (b) P_marA-cfp, (d) P_marA-cfp ΔmarRAB, and (f) MarA-CFP. Each blue dot corresponds to one cell, which has an outcome ‘lysed’ or ‘filamented’ and an initial fluorescence value. The number of cells exhibiting each outcome is listed on the x-axis. The mean ranks are statistically different for only the P_marA-cfp strain (P < 0.01 by a Mann-Whitney rank sum test). Histograms and further details are provided in Supplementary Fig. 4.

Figure 3. Resistance to carbenicillin is transient and cells that survive resume normal growth.

Time-lapse microscopy images of P_marA-cfp ΔfliC cells growing inside a microfluidic chamber subjected to two sequential steps of 50 μg/ml carbenicillin. Cyan indicates CFP levels from the MarA reporter; red indicates the death marker propidium iodide, which was added at the same time as carbenicillin. Supplementary Movie 3 shows additional details.

Figure 4. Level of MarA achieved by isogenic cells plays a key role in transient resistance to carbenicillin.

(a) Representative fluorescence data extracted from a P_marA-cfp microcolony. Gray traces show all cells within the microcolony, where branching indicates cell division. Green traces highlight representative lineages. (b) Representative fluorescence data for a P_marA-cfp ΔmarRAB microcolony. (c) Histograms showing frequency (%) of cells with a given fluorescence value. Data comes from six microcolonies for P_marA-cfp and three microcolonies each for P_marA-cfp ΔmarRAB and P_lac-cfp. (d) Autocorrelation of CFP signals for P_marA-cfp (gray), P_marA-cfp ΔmarRAB (magenta), and P_lac-cfp (cyan). For each, we calculated the average autocorrelation for all cells within a microcolony. Error bars represent the standard deviation across replicates, which are described above. (e) Percentage of filamented P_marA-cfp (gray) and P_lac-cfp (cyan) cells as a function of the fluorescence threshold level. The percentage is calculated as the number of filamented cells divided by the total number of filamented and lysed cells.

Figure 5. Transient resistance to antibiotics depends on MarA level achieved in the cell.

Illustration showing expression of diverse downstream resistance genes as a function of MarA. Antibiotic susceptible cells are represented in red, resistant cells in cyan. As MarA levels increase, a larger number of downstream genes are turned on, providing antibiotic resistance. At low to intermediate levels of MarA, only a subset of the population has sufficient MarA, and consequently downstream gene expression, to ensure survival.