BackgroundOne of the puzzles in bacterial quorum sensing is understanding how an organism integrates the information gained from multiple input signals. The marine bacterium Vibrio fischeri regulates its bioluminescence through a quorum sensing mechanism that receives input from three pheromone signals, including two acyl homoserine lactone (HSL) signals. While the role of the 3-oxo-C6 homoserine lactone (3OC6HSL) signal in activating the lux genes has been extensively studied and modeled, the role of the C8 homoserine lactone (C8HSL) is less obvious, as it can either activate luminescence or block its activation. It remains unclear how crosstalk between C8HSL and 3OC6HSL affects the information that the bacterium obtains through quorum sensing.ResultsWe have used microfluidic methods to measure the response of individual V.fischeri cells to combinations of C8HSL and 3OC6HSL. By measuring the fluorescence of individual V.fischeri cells containing a chromosomal gfp-reporter for the lux genes, we study how combinations of exogenous HSLs affect both the population average and the cell-to-cell variability of lux activation levels. At the level of a population average, the crosstalk between the C8HSL and 3OC6HSL inputs is well-described by a competitive inhibition model. At the level of individual cells, the heterogeneity in the lux response depends only on the average degree of activation, so that the noise in the output is not reduced by the presence of the second HSL signal. Overall we find that the mutual information between the signal inputs and the lux output is less than one bit. A nonlinear correlation between fluorescence and bioluminescence outputs from lux leads to different noise properties for these reporters.ConclusionsThe lux genes in V.fischeri do not appear to distinguish between the two HSL inputs, and even with two signal inputs the regulation of lux is extremely noisy. Hence the role of crosstalk from the C8HSL input may not be to improve sensing precision, but rather to suppress the sensitivity of the switch for as long as possible during colony growth.

The chemical signaling mechanism known as "bacterial quorum sensing" (QS) is normally interpreted as allowing bacteria to detect their own population density, in order to coordinate gene expression across a colony. However, the release of the chemical signal can also be interpreted as a means for one or a few cells to probe the local physical properties of their microenvironment. We have studied the behavior of the LuxI/LuxR QS circuit of Vibrio fischeri in tightly confining environments where individual cells detect their own released signals. We find that the lux genes become activated in these environments, although the activation onset time shows substantial cell-to-cell variability and little sensitivity to the confining volume. Our data suggest that noise in gene expression could significantly impact the utility of LuxI/LuxR as a probe of the local physical environment.

Many biological networks are robust to a wide variety of internal and external perturbations, yet fragile to a select group of uncommon perturbations. Because fragile system modes are highly sensitive to certain biochemical parameters, it is unclear how precisely biochemical parameters must be known a priori in order to accurately predict the robustness portrait of a system. Here, we examined a previously well-characterized model of the cardiac beta-adrenergic signaling network and found that its robustness portrait was well conserved, even when parameters were rounded to their nearest 1-2 orders of magnitude (r = 0.82 and 0.63, respectively). This analysis was then extended to 10 additional networks of diverse biological processes, including E. Coli chemotaxis, stem cell differentiation, and cytokine signaling. Nine out of 10 of these networks exhibited conserved robustness portraits (r > 0.75) despite systematic order-of-magnitude variations in their biochemical parameters. These results illustrate the ability to predict both fragile and robust aspects of diverse biological networks despite imprecise biochemical parameters. Additionally, this work suggests a strategy from which approximate models can be used to prioritize experiments towards fragile system modes, leading to efficient model validation and revision.