A New Way of Sensing: Need-Based Activation of Antibiotic Resistance by a Flux-Sensing Mechanism

Abstract

Sensing of and responding to environmental changes are of vital importance for microbial cells. Consequently, bacteria have evolved a plethora of signaling systems that usually sense biochemical cues either via direct ligand binding, thereby acting as "concentration sensors," or by responding to downstream effects on bacterial physiology, such as structural damage to the cell. Here, we describe a novel, alternative signaling mechanism that effectively implements a "flux sensor" to regulate antibiotic resistance. It relies on a sensory complex consisting of a histidine kinase and an ABC transporter, in which the transporter fulfills the dual role of both the sensor of the antibiotic and the mediator of resistance against it. Combining systems biological modeling with in vivo experimentation, we show that these systems in fact respond to changes in activity of individual resistance transporters rather than to changes in the antibiotic concentration. Our model shows that the cell thereby adjusts the rate of de novo transporter synthesis to precisely the level needed for protection. Such a flux-sensing mechanism may serve as a cost-efficient produce-to-demand strategy, controlling a widely conserved class of antibiotic resistance systems.

Importance: Bacteria have to be able to accurately perceive their environment to allow adaptation to changing conditions. This is usually accomplished by sensing the concentrations of beneficial or harmful substances or by measuring the effect of the prevailing conditions on the cell. Here we show the existence of a new way of sensing the environment, where the bacteria monitor the activity of an antibiotic resistance transporter. Such a "flux-sensing" mechanism allows the cell to detect its current capacity to deal with the antibiotic challenge and thus precisely respond to the need for more transporters. We propose that this is a cost-efficient way of regulating antibiotic resistance on demand.

FIG 1

Schematic of conceivable sensory scenarios employed by the BceRS-BceAB system. In an external sensing scenario (a), the ABC transporter BceAB might act as a scaffold that keeps the histidine kinase BceS in an active conformation, which would allow BceS to perceive the extracellular concentration of bacitracin (red symbols). Since up-regulation of BceAB is not expected to change the extracellular concentration of bacitracin, the rate of gene expression should be independent of the BceAB level in this scenario (no feedback). In an internal sensing scenario (b), BceAB might be required to translocate bacitracin into the cytoplasm where BceS could sense its abundance. Here, up-regulation of BceAB should lead to an increased rate of bacitracin influx, which would in turn lead to further up-regulation of BceAB expression (positive feedback). In a flux-sensing scenario (c), BceAB itself is the true sensor, which directly signals its transport activity to BceS. In such a scenario, up-regulation of BceAB would reduce the load experienced by each individual transporter and thereby reduce signaling via BceS (negative feedback). (d) Schematic depiction of the expected impact of different levels of the BceAB transporter (low, red curves; high, green curves) on dose-dependent P_bceA activity.

FIG 2

Gene expression driven by the P_bceA promoter rapidly adapts to a wide range of antibiotic concentrations. (A) Exponentially growing cells of strain SGB073 were exposed to sublethal concentrations of bacitracin at 0 min, and luciferase activity from a P_bceA-luxABCDE reporter construct was monitored over time. Data are means and standard deviations for at least three independent biological replicates (lower error bars are not depicted if negative values were reached). Lines show the dynamics predicted by the quantitative mathematical model described in the main text. (B) Experimental dose-response curve of the P_bceA promoter at a fixed time (42.5 min) after induction (symbols) and the fit to the mathematical model (lines). For details, see the text.

FIG 3

Signature of a relative flux sensor. (a) Theoretical prediction of P_bceA-luxABCDE dose-response curves for various levels of constitutive BceAB transporter production (colored curves), compared to the wild type with autoregulated bceAB expression (black curve). The expression levels of bceAB in the legend are percentages of the maximal P_bceA expression level in the wild type. These expression levels were derived from the experimental dose-response curve of the P_xylA promoter in panel b, which drives expression of bceAB in the experimental system in panel c. (b) Xylose-dependent dose-response curve of a P_xylA-luxABCDE reporter strain (black symbols) published previously (22) and fitted by a Hill function (black curve). In addition, the EC₁₀ values , i.e., concentrations at which the dose-response curves in panel c reach 10% of their maximal activity, are shown as a function of xylose concentration (red symbols). (c) Experimental P_bceA-luxABCDE dose-response curves in strain SGB218, in which the endogenous chromosomal bceAB locus has been deleted and transporter expression is constitutively driven from a chromosomally integrated xylose-dependent P_xylA-bceAB construct (colored symbols). The wild-type dose-response curve (black symbols) was derived from strain SGB073. (d) Data from panels a and c with the x axis rescaled by the respective EC₁₀ values. For details, see the text.

FIG 4

Inhibition of cell wall biosynthesis by blocking UPP recycling. (a) Change in the fraction of bacitracin-bound UPP as a function of external bacitracin, predicted by a model with feedback regulation (black curve) and a model with the indicated levels of constitutive bceAB expression (colored curves). In addition to the bceAB expression levels used in Fig. 3, the red curve shows the percentage of bacitracin-bound UPP in the absence of the BceAB transporter. Assuming that cell wall biosynthesis can be maintained as long as the percentage of blocked UPP carrier molecules remains below a given limit (dashed grey line), the intersection with the solid lines leads to a prediction of how the bacitracin MIC should scale with increasing BceAB expression level (dashed grey line in panel b). (b) Growth inhibition of strain SGB218 with constitutive transporter expression from a xylose-dependent P_xylA-bceAB construct (colored symbols). Cultures with a low bceAB expression level (0% xylose) are more susceptible to bacitracin than cultures with a high bceAB expression level (0.2% xylose). The model quantitatively captures the scaling of this growth inhibition line (solid grey line), when background resistance mechanisms, which are reflected in an additive offset for low bceAB expression level, are taken into account.