Quantitative modeling of multi-signal quorum-sensing maps environment to bacterial regulatory responses

Bacterial quorum sensing is often mediated by multiple signaling systems that interact with each other. The quorum-sensing systems of Pseudomonas aeruginosa, for example, are considered hierarchical, with the las system acting as a master regulator. By experimentally controlling the concentration of auto-inducer signals in a signal deficient strain (PAO1ΔlasIΔrhlI), we show that the two primary quorum-sensing systems-las and rhl-act reciprocally rather than hierarchically. Just as the las system's 3‑oxo‑C12‑HSL can induce increased expression of rhlI, the rhl system's C4‑HSL increases the expression level of lasI. We develop a mathematical model to quantify relationships both within and between the las and rhl quorum-sensing systems and the downstream genes they influence. The results show that not only do the systems interact in a reciprocal manner, but they do so asymmetrically, cooperatively, and nonlinearly, with the combination of C4‑HSL and 3‑oxo‑C12‑HSL increasing expression level far more than the sum of their individual effects. We next extend our parameterized mathematical model to generate quantitative predictions on how a QS-controlled effector gene (lasB) responds to changes in wildtype bacterial stationary phase density and find close quantitative agreement with an independent dataset. Finally, we use our parameterized model to assess how changes in multi-signal interactions modulate functional responses to variation in social (population density) and physical (mass transfer) environment and demonstrate that a reciprocal architecture is more responsive to density and more robust to mass transfer than a strict hierarchy.