In bacterial chemotaxis, several types of receptors form mixed clusters. Receptor adaptation is shown to depend on the receptor's own conformational state rather than on the cluster's global activity, enabling cells to differentiate stimuli in complex environments.
We develop here a model for mixed chemoreceptor clusters in which receptors interact directly with their nearest neighbors.A local adaptation scheme is used to describe the methylation kinetics of individual receptors.Predictions made by this model were tested by direct measurements of the receptor methylation dynamics for both Tar and Tsr in response to ligands sensed by either receptor.We show that the local adaptation mechanism tunes each receptor in the mixed cluster to its most responsive state, to maintain the cell's high sensitivity in complex environments with multiple cues.This mechanism also prevents the saturation of the whole receptor cluster with exposure to environments with extreme level of one type of stimulus.
In environments with multiple cues, organisms need to sense different signals and to respond accordingly to enhance their chances of survival (Adler and Tso, 1974). In bacterial chemotaxis systems (see Hazelbauer et al (2008) for a recent review), different chemical stimuli are sensed by different types of chemoreceptors. In Escherichia coli cells, different types of chemoreceptors, e.g., the aspartate-sensing Tar receptor and the serine-sensing Tsr receptor, form mixed receptor cluster (Maddock and Shapiro, 1993; Ames et al, 2002), within which different types of chemoreceptors interact with each other cooperatively to amplify external signals (Bray et al, 1998; Sourjik and Berg, 2002; Mello and Tu, 2003b). The bacterial chemosensory system also adapts to prolonged stimuli by covalently modifying the chemoreceptors (methylation and demethylation). However, despite strong interactions between different receptors in the mixed cluster, the adaptive covalent modifications of individual receptors are observed to be insulated from each other. At moderate stimulation, only the receptors that bind the respective ligand adjust their methylation levels significantly in the adapted state (Silverman and Simon, 1977; Sanders and Koshland, 1988; Antommattei et al, 2004). This observed ligand-specific receptor methylation pattern challenges all-or-none allosteric models, such as the Monod–Wyman–Changdeux model (Monod et al, 1965; Sourjik and Berg, 2004; Mello and Tu, 2005; Keymer et al, 2006), that are commonly used to describe behavior of chemoreceptor clusters. It prompts the fundamental questions of how a highly cooperative mixed chemoreceptor complex adapts to multiple stimuli and whether it can distinguish different signals.
In this paper, we combine theoretical and experimental methods to understand the adaptation mechanism of mixed chemoreceptor clusters. We propose a local adaptation mechanism (model) for the mixed receptor cluster (Figure 1). In our model, receptors interact with their neighboring receptors in the mixed cluster (Figure 1D) and thus act collectively to generate strong response to small external signals. However, the adaptation of an individual receptor in the mixed cluster depends predominantly on its own local conformational state (Figure 1B), rather than the activity of the entire cluster (Figure 1A and C). Much to our surprise, despite strong interaction between different receptors, our model predicts that only the receptor which binds with the external ligand changes its methylation level in steady state when the system adapts, while other types of receptors only change their methylation levels transiently during adaptation. Our model also predicts that permanent (steady state) methylation crosstalk occurs only when the system fails to adapt accurately, and there exists a direct connection between the adaptation error and the degree of permanent methylation crosstalk. Both predictions are verified by direct quantitative measurements of the dynamics of the Tar and Tsr methylation levels in response to MeAsp and serine (Figure 5). These experimental results cannot be explained by the existing models, such as the MWC-type model and the recently proposed independent receptor model by Goldman et al (2009). The predicted transient adaptation dynamics for a mixed receptor cluster also provides a mechanistic explanation for the previously observed overshoot of activity when E. coli cells adapt to a large step stimulus (Berg and Tedesco, 1975).
After establishing the validity of the local adaptation mechanism in E. coli, we next explore the possible advantages of this adaptation mechanism for bacterial chemotaxis. We show that while the previously proposed global adaptation mechanisms compress different external environmental information, e.g., concentrations of different types of attractant ligands into one quantity (the overall activity of the cluster), the local adaptation mechanism preserves environmental information. The concentrations of different chemoeffectors are encoded (‘remembered') by the specific receptor methylation levels in the local adaptation model. These ligand-specific information can then be used by bacterial cells to precisely tune each type of receptor in the mixed cluster to its most responsive state, therefore maintaining high sensitivity and responsiveness in complex environments with multiple stimuli. The local adaptation mechanism, by effectively preventing methylation crosstalk, also prevents the poisoning effect by methylation contamination when bacterial cells are exposed to environments with extreme level of one type of stimulus. In summary, we have developed a modeling framework for understanding how a mixed chemoreceptor cluster adapts to complex environments with multiple cues. The local adaptation and global activation mechanism of the mixed receptor cluster proposed in this paper resolves the seemingly conflicting observations between strong receptor–receptor interactions and the absence of permanent receptor methylation crosstalk within a unified and predictive model. Direct quantitative measurements of the receptor methylation dynamics have confirmed the model predictions. The proposed model also predicts several characteristic consequences of the local adaptation mechanism, e.g., elimination of sensory poisoning, which may be tested in future experiments. Bacterial chemosensory machinery is a paradigm for studying adaptive sensory systems for detecting and adapting to environmental changes and signals, and we expect that the strategy of ‘adapting locally (individually) and acting globally (collectively)' may be used by other sensory systems that utilize multiple receptors to respond complex environmental changes.
In bacterial chemotaxis, several types of ligand-specific receptors form mixed clusters, wherein receptor–receptor interactions lead to signal amplification and integration. However, it remains unclear how a mixed receptor cluster adapts to individual stimuli and whether it can differentiate between different types of ligands. Here, we combine theoretical modeling with experiments to reveal the adaptation dynamics of the mixed chemoreceptor cluster in Escherichia coli. We show that adaptation occurs locally and is ligand-specific: only the receptor that binds the external ligand changes its methylation level when the system adapts, whereas other types of receptors change methylation levels transiently. Permanent methylation crosstalk occurs when the system fails to adapt accurately. This local adaptation mechanism enables cells to differentiate individual stimuli by encoding them into the methylation levels of corresponding types of chemoreceptors. It tunes each receptor to its most responsive state to maintain high sensitivity in complex environments and prevents saturation of the cluster by one signal.