Coordination of QS processes often involves multi-step signal transduction pathways that control the expression of master transcription factors, which in turn, regulate genes responsible for group behaviors. QS networks must be designed to precisely translate external AI concentrations into proper patterns of internal QS target gene expression. The molecular components making up the V. harveyi QS circuit have been defined and characterized, allowing us to undertake an analysis of the regulatory features of the network that optimize the QS output response. Here, we identified two cooperative negative regulatory feedback loops involving LuxO and the Qrr sRNAs. Specifically, LuxO negatively regulates its own transcription by virtue of a LuxO-binding site in the luxO promoter (). Negative regulation does not depend on the phosphorylation state of LuxO (), suggesting that LuxO competition with RNAP for DNA-binding at this LuxO/−35 site sets the level of luxO transcription. LuxO is also subject to posttranscriptional feedback regulation by the Qrr sRNAs (); thus luxO mRNA constitutes a new target of the Qrr sRNAs in V. harveyi. The two feedback loops function to make V. harveyi more sensitive to changes in external AI concentrations and thereby set the threshold population density at which cells reach a quorum (–).
The negative feedback loop is a common network-design motif in signal transduction pathways and gene regulatory networks. Negative feedbacks are generally believed to play three major roles: reducing “noise”, i.e. temporal fluctuation or cell-to-cell variation (Becskei and Serrano, 2000
; Thattai and van Oudenaarden, 2001
); decreasing response rise times (Alon, 2007
; Rosenfeld et al., 2002
; Savageau, 1974
); and producing graded responses (Nevozhay et al., 2009
). All three roles have been demonstrated for negatively auto-regulated transcription factors (TF). First, high concentration of a TF will result in repression, while low concentration will result in increased production, leading to a narrower distribution of protein levels than for proteins that are not auto-regulated. This feature reduces expression noise of the TF. Second, a TF subject to negative feedback with a stronger promoter than a non-self-regulated one, can nonetheless reach the identical steady-state level. The negatively regulated TF will increase rapidly until it reaches the threshold level required for repressing its own expression. This feature results in a shorter gene-expression rise time (Rosenfeld et al., 2002
). Third, a particular amount of inducer will result in a lower level of a negatively auto-regulated TF than a non-regulated one due to auto-repression of expression. This feature decreases the slope of the dose-response curve and generates a graded response.
We determined whether the two negative feedback loops under study play any of these three canonical roles. In order to measure noise in the QS response, we used single-cell fluorescence microscopy to quantify LuxR levels of V. harveyi in individual cells at various AI concentrations. The relative noise, namely the standard deviation over the mean, is only 20% at high AI concentrations (). Thus, V. harveyi cells act in unison at HCD. However, surprisingly, there is no discernable difference in relative noise in the various feedback loop mutants, whether in the presence of a single or multiple sRNAs. A possible explanation for this observation is that the two central transcriptional regulators in the QS circuit – LuxO and LuxR – are both subject to transcriptional and posttranscriptional negative feedback regulation. The feedback loops on LuxO may primarily contribute to noise reduction in LuxO expression levels, while the feedback loops on LuxR filter out noise originating from various sources, including noise in LuxO levels, to stabilize the LuxR expression level. In any event, we find that the two feedback loops on LuxO do not noticeably contribute to the low relative noise in LuxR expression.
To test whether the translational repression of LuxO by Qrr sRNAs decreases rise time relative to steady-state levels of the Qrrs during the HCD to LCD transition, we measured Qrr sRNA levels in both wildtype cells and in the engineered strains with the feedback loops disabled (). Our results show that the transition happens rapidly – Qrr levels reach maxima within 10 minutes – in all strains. There is no discernible difference either in the rise times or the plateau levels of Qrrs in the presence or absence of the feedback loops. Therefore, the LuxO-Qrr feedback loop does not function to allow a fast transition out of HCD mode.
We also considered whether the feedback loops involving LuxO and Qrr sRNAs might function to generate a graded response. However, as shown in , the slopes of the LuxR dose-response curves are not substantially different for wildtype and the various loop mutants. All the Hill coefficients are ~1 from the fitting curves, suggesting a non-cooperative graded QS response irrespective of whether or not the negative feedbacks were present. With only a single Qrr present, the Hill coefficients for the loop mutants are modestly larger than when both loops are present (, 1.5–1.7 vs. 1.1), but the difference is within our experimental error. The dose-response curves of LuxR target genes (bioluminescence and qrgA) also showed constancy in the Hill coefficients for wildtype and various loop mutants. Thus, we conclude that the negative feedback loops do not make the QS response to autoinducers more graded.
In summary, the two negative feedback loops reported here do not appear to play any of the usual roles of negative feedback loops in gene-regulatory networks. However, the feedback loops clearly do function to tune the sensitivity of the QS response to AI concentrations, and in so doing, establish the point at which the population of V. harveyi reaches a quorum, and thus set the timing of downstream QS target gene expression. It is puzzling why this fine-tuning of the QS threshold is achieved via negative feedbacks rather than, e.g., by adjusting parameters of reactions in the signaling and gene regulatory circuit.
If these two negative feedback loops were not wired into the QS circuit, we speculate that there would be a loss of homeostatic control due to unchecked LuxO and LuxR levels. Specifically, we suggest that the two negative feedback loops have evolved to couple the natural dynamic range of AI concentrations with the desired dynamic range of downstream QS-regulated gene expression. Likewise, negative feedback regulation increases signaling fidelity in the mating pheromone pathway in yeast (Yu et al., 2008). In particular, the specific architecture of the LuxO-Qrr negative feedback loop prevents over-accumulation of Qrrs, and thus prevents the targets of Qrrs from “bottoming out”, i.e. declining to extremely low levels. Intuitively, the obligate activation of Qrr sRNAs by LuxO~P/LuxR places a cap on Qrr expression: if Qrr levels start to become too high, luxO
mRNA is decreased due to the excess of Qrrs, and as a consequence, qrr
expression declines due to decreased levels of LuxO~P/LuxR. Therefore, all targets of the Qrrs are protected from “bottoming out” (approaching zero) by the feedback loops in which the Qrrs negatively regulate their own activators, LuxO~P and LuxR. Consider the following simplified kinetic equation for a target mRNA (e.g. luxR
is a constant transcription rate of the mRNA, μ
is the coefficient for the rate of mutual degradation (or sequestration) of sRNA and mRNA, and δ
is the rate of ordinary degradation/dilution of mRNA. At steady state, the time derivative of the mRNA concentration must be zero, and so the cellular mRNA level is:
If the sRNA level becomes very high, the denominator in Equation (2)
will be extremely large and result in a “bottoming out” of the mRNA. It is obvious that by setting an upper limit on Qrr sRNA levels, mRNA levels are thereby prevented from approaching zero. Physiologically, it is likely to be important to maintain a basal level of translation of the mRNAs of key QS players – including LuxO and LuxR – otherwise these proteins will be diluted out during cell growth and division. Thus, the multiple negative feedback loops function to keep LuxO, the Qrrs, and LuxR levels in check, and therefore aid in maintaining the expression of both Qrrs and QS-regulated target genes within restricted windows. We suggest that sRNA-based regulation of mRNAs of the essential QS components is indispensible for proper functioning of QS signaling.
Our results suggest that there are roles negative feedback loops can play in signaling and gene regulatory networks beyond those already recognized. While the LuxR-Qrr feedback loop accelerates the HCD to LCD transition (Tu et al., 2008
), the topologically identical LuxO-Qrr feedback loop appears to play a different role – namely fine-tuning the threshold where the bacterial population reaches a quorum while controlling the dynamic range of expression of QS target gene expression. We suggest that bacterial sRNA posttranscriptional negative regulatory feedback loops, and potentially, eukaryotic miRNA negative feedback loops may prove to be a common network design motif. They provide features such as noise reduction, rise time shortening, grading of responses, as well as new ones including the dynamic range control proposed here in the context of the V. harveyi