Motility response of Rhodobacter sphaeroides to chemotactic stimulation

Swimming Using a Unidirectionally Rotating, Single Stopping Flagellum in the Alpha Proteobacterium Rhodobacter sphaeroides

Rhodobacter sphaeroides has 2 flagellar operons, one, Fla2, encoding a polar tuft that is not expressed under laboratory conditions and a second, Fla1, encoding a single randomly positioned flagellum. This single flagellum, unlike the flagella of other species studied, only rotates in a counterclockwise direction. Long periods of smooth swimming are punctuated by short stops, caused by the binding of one of 3 competing CheY homologs to the motor. During a stop, the motor is locked, not freely rotating, and the flagellar filament changes conformation to a short wavelength, large amplitude structure, reforming into a driving helix when the motor restarts. The cell has been reoriented during the brief stop and the next period of smooth swimming is a new direction.

Mechanism of Signalling and Adaptation through the Rhodobacter sphaeroides Cytoplasmic Chemoreceptor Cluster

Rhodobacter sphaeroides has two chemotaxis clusters, an Escherichia coli-like cluster with membrane-spanning chemoreceptors and a less-understood cytoplasmic cluster. The cytoplasmic CheA is split into CheA₄, a kinase, and CheA₃, a His-domain phosphorylated by CheA₄ and a phosphatase domain, which together phosphorylate and dephosphorylate motor-stopping CheY₆. In bacterial two-hybrid analysis, one major cytoplasmic chemoreceptor, TlpT, interacted with CheA₄, while the other, TlpC, interacted with CheA₃. Both clusters have associated adaptation proteins. Deleting their methyltransferases and methylesterases singly and together removed chemotaxis, but with opposite effects. The cytoplasmic cluster signal overrode the membrane cluster signal. Methylation and demethylation of specific chemoreceptor glutamates controls adaptation. Tandem mass spectroscopy and bioinformatics identified four putative sites on TlpT, three glutamates and a glutamine. Mutating each glutamate to alanine resulted in smooth swimming and loss of chemotaxis, unlike similar mutations in E. coli chemoreceptors. Cells with two mutated glutamates were more stoppy than wild-type and responded and adapted to attractant addition, not removal. Mutating all four sites amplified the effect. Cells were non-motile, began smooth swimming on attractant addition, and rapidly adapted back to non-motile before attractant removal. We propose that TlpT responds and adapts to the cell's metabolic state, generating the steady-state concentration of motor-stopping CheY₆~P. Membrane-cluster signalling produces a pulse of CheY₃/CheY₄~P that displaces CheY₆~P and allows flagellar rotation and smooth swimming before both clusters adapt.

Functional Regulators of Bacterial Flagella

Bacteria move by a variety of mechanisms, but the best understood types of motility are powered by flagella (72). Flagella are complex machines embedded in the cell envelope that rotate a long extracellular helical filament like a propeller to push cells through the environment. The flagellum is one of relatively few biological machines that experience continuous 360° rotation, and it is driven by one of the most powerful motors, relative to its size, on earth. The rotational force (torque) generated at the base of the flagellum is essential for motility, niche colonization, and pathogenesis. This review describes regulatory proteins that control motility at the level of torque generation.

Optimal chemotactic responses in stochastic environments

Although the “adaptive” strategy used by Escherichia coli has dominated our understanding of bacterial chemotaxis, the environmental conditions under which this strategy emerged is still poorly understood. In this work, we study the performance of various chemotactic strategies under a range of stochastic time- and space-varying attractant distributions in silico. We describe a novel “speculator” response in which the bacterium compare the current attractant concentration to the long-term average; if it is higher then they tumble persistently, while if it is lower than the average, bacteria swim away in search of more favorable conditions. We demonstrate how this response explains the experimental behavior of aerobically-grown Rhodobacter sphaeroides and that under spatially complex but slowly-changing nutrient conditions the speculator response is as effective as the adaptive strategy of E. coli.

Identification of a Chemoreceptor for C2 and C3 Carboxylic Acids

Chemoreceptors are at the beginnings of chemosensory signaling cascades that mediate chemotaxis. Most bacterial chemoreceptors are functionally unannotated and are characterized by a diversity in the structure of their ligand binding domains (LBDs). The data available indicate that there are two major chemoreceptor families at the functional level, namely, those that respond to amino acids or to Krebs cycle intermediates. Since pseudomonads show chemotaxis to many different compounds and possess different types of chemoreceptors, they are model organisms to establish relationships between chemoreceptor structure and function. Here, we identify PP2861 (termed McpP) of Pseudomonas putida KT2440 as a chemoreceptor with a novel ligand profile. We show that the recombinant McpP LBD recognizes acetate, pyruvate, propionate, and l-lactate, with KD (equilibrium dissociation constant) values ranging from 34 to 107 μM. Deletion of the mcpP gene resulted in a dramatic reduction in chemotaxis toward these ligands, and complementation restored a native-like phenotype, indicating that McpP is the major chemoreceptor for these compounds. McpP has a CACHE-type LBD, and we present data indicating that CACHE-containing chemoreceptors of other species also mediate taxis to C2 and C3 carboxylic acids. In addition, the LBD of NbaY of Pseudomonas fluorescens, an McpP homologue mediating chemotaxis to 2-nitrobenzoate, bound neither nitrobenzoates nor the McpP ligands. This work provides further insight into receptor structure-function relationships and will be helpful to annotate chemoreceptors of other bacteria.

Evolution of response dynamics underlying bacterial chemotaxis

Background

The ability to predict the function and structure of complex molecular mechanisms underlying cellular behaviour is one of the main aims of systems biology. To achieve it, we need to understand the evolutionary routes leading to a specific response dynamics that can underlie a given function and how biophysical and environmental factors affect which route is taken. Here, we apply such an evolutionary approach to the bacterial chemotaxis pathway, which is documented to display considerable complexity and diversity.

Results

We construct evolutionarily accessible response dynamics starting from a linear response to absolute levels of attractant, to those observed in current-day Escherichia coli. We explicitly consider bacterial movement as a two-state process composed of non-instantaneous tumbling and swimming modes. We find that a linear response to attractant results in significant chemotaxis when sensitivity to attractant is low and when time spent tumbling is large. More importantly, such linear response is optimal in a regime where signalling has low sensitivity. As sensitivity increases, an adaptive response as seen in Escherichia coli becomes optimal and leads to 'perfect' chemotaxis with a low tumbling time. We find that as tumbling time decreases and sensitivity increases, there exist a parameter regime where the chemotaxis performance of the linear and adaptive responses overlap, suggesting that evolution of chemotaxis responses might provide an example for the principle of functional change in structural continuity.

Conclusions

Our findings explain several results from diverse bacteria and lead to testable predictions regarding chemotaxis responses evolved in bacteria living under different biophysical constraints and with specific motility machinery. Further, they shed light on the potential evolutionary paths for the evolution of complex behaviours from simpler ones in incremental fashion.

Origins and diversification of a complex signal transduction system in prokaryotes

The molecular machinery that controls chemotaxis in bacteria is substantially more complex than any other signal transduction system in prokaryotes, and its origins and variability among living species are unknown. We found that this multiprotein "chemotaxis system" is present in most prokaryotic species and evolved from simpler two-component regulatory systems that control prokaryotic transcription. We discovered, through genomic analysis, signaling systems intermediate between two-component systems and chemotaxis systems. Evolutionary genomics established central and auxiliary components of the chemotaxis system. While tracing its evolutionary history, we also developed a classification scheme that revealed more than a dozen distinct classes of chemotaxis systems, enabling future predictive modeling of chemotactic behavior in unstudied species.

Long lag times and high velocities in the motility of natural assemblages of marine bacteria

The motility characteristics of natural assemblages of coastal marine bacteria were examined. Initially, less than 10% of the bacteria were motile. A single addition of tryptic soy broth caused an increase in the motile fraction of cells but only after 7 to 12 h. Motility peaked at 15 to 30 h, when more than 80% of cells were motile. These results support the proposal that energy limits motility in the marine environment. Cell speeds changed more than an order of magnitude on timescales of milliseconds and hours. The maximum community speed was 144 (mu)m s(sup-1), and the maximum individual burst velocity was 407 (mu)m s(sup-1). In uniform medium, speed was an inverse function of tryptic soy broth concentration, declining linearly over 0.001 to 1.0%. In media where concentration gradients existed, the mean speed was a function of position in a spatial gradient, changing from 69 to 144 (mu)m s(sup-1) over as little as 15 to 30 (mu)m. The results suggest that marine bacteria are capable of previously undescribed quick shifts in speed that may permit the bacteria to rapidly detect and keep up with positional changes in small nutrient sources. These high speeds and quick shifts may reflect the requirements for useful motility in a turbulent ocean.

Chemotactic Responses of Marine Vibrio sp. Strain S14 (CCUG 15956) to Low-Molecular-Weight Substances under Starvation and Recovery Conditions

The chemotactic responses by starved cells of marine Vibrio sp. strain S14 differed from those elicited by cells that were not nutrient limited. The rate of chemotaxis at different concentrations of several attractants varied for starved and growing cells. Vibrio sp. strain S14 showed positive chemotaxis to leucine, valine, arginine, and glucose at the onset of energy and nutrient deprivation. A continued, though decreased, positive response was demonstrated fro leucine, arginine, and glucose at 10 h of starvation. Cells starved for 3 h displayed a stronger response to glucose than those starved for shorter or longer times. However, cells starved for 5 and 10 h responded more strongly to a lower concentration of glucose than did cells starved for 0 and 3 h. Starvation for 24 h elicited no measurable chemotaxis to leucine, arginine, or glucose. The motility decreased by over 95% in the cell population after 24 h of starvation, which resulted in a low sensitivity in the chemotaxis assay. A switch in the response to valine was observed by 3 h of starvation. The addition of nutrients of 22-h-starved cells elicited a temporary positive chemotactic response to leucine by 2 and 4 h of nutrient recovery, while cells at 1 and 6 h of recovery showed no response. At 2 h of recovery, the greatest response was recorded to 10 M leucine, whereas at 4 h it was to 10 M leucine. Ten to fifty percent of the 22-h-starved cell population regained their motility after 4 h of nutrient-aided recovery. It is possible that two types of chemosensory systems exist in marine bacteria. Starved and growing cells responded to different concentrations of the attractant, and growing cells displayed a saturated chemotactic system with leucine as the attractant, unlike the response during starvation.

Evolution of taxis responses in virtual bacteria: non-adaptive dynamics

Bacteria are able to sense and respond to a variety of external stimuli, with responses that vary from stimuli to stimuli and from species to species. The best-understood is chemotaxis in the model organism Escherichia coli, where the dynamics and the structure of the underlying pathway are well characterised. It is not clear, however, how well this detailed knowledge applies to mechanisms mediating responses to other stimuli or to pathways in other species. Furthermore, there is increasing experimental evidence that bacteria integrate responses from different stimuli to generate a coherent taxis response. We currently lack a full understanding of the different pathway structures and dynamics and how this integration is achieved. In order to explore different pathway structures and dynamics that can underlie taxis responses in bacteria, we perform a computational simulation of the evolution of taxis. This approach starts with a population of virtual bacteria that move in a virtual environment based on the dynamics of the simple biochemical pathways they harbour. As mutations lead to changes in pathway structure and dynamics, bacteria better able to localise with favourable conditions gain a selective advantage. We find that a certain dynamics evolves consistently under different model assumptions and environments. These dynamics, which we call non-adaptive dynamics, directly couple tumbling probability of the cell to increasing stimuli. Dynamics that are adaptive under a wide range of conditions, as seen in the chemotaxis pathway of E. coli, do not evolve in these evolutionary simulations. However, we find that stimulus scarcity and fluctuations during evolution results in complex pathway dynamics that result both in adaptive and non-adaptive dynamics depending on basal stimuli levels. Further analyses of evolved pathway structures show that effective taxis dynamics can be mediated with as few as two components. The non-adaptive dynamics mediating taxis responses provide an explanation for experimental observations made in mutant strains of E. coli and in wild-type Rhodobacter sphaeroides that could not be explained with standard models. We speculate that such dynamics exist in other bacteria as well and play a role linking the metabolic state of the cell and the taxis response. The simplicity of mechanisms mediating such dynamics makes them a candidate precursor of more complex taxis responses involving adaptation. This study suggests a strong link between stimulus conditions during evolution and evolved pathway dynamics. When evolution was simulated under conditions of scarce and fluctuating stimulus conditions, the evolved pathway contained features of both adaptive and non-adaptive dynamics, suggesting that these two types of dynamics can have different advantages under distinct environmental circumstances.

Here, we study how signalling networks mediating chemotaxis could have evolved. We simulated the evolution of virtual bacteria, which can explore their environment by alternating between swimming and tumbling. The tumbling frequency is dictated by the output of a signalling network that senses extracellular nutrient levels, while the bacteria's reproductive success is determined by their ability to find nutrients. Under conditions of abundant food, we find that bacteria quickly evolve signalling networks that enable effective chemotaxis, where increasing nutrient levels increase tumbling frequency. Our findings provide explanation for network dynamics underlying similar behaviour as observed in certain mutant strains of Escherichia coli and in other bacterial species. Conversely, wild-type E. coli respond to increasing nutrient levels by decreasing their tumbling frequency and adapting to constant attractant levels. We observe such adaptive network dynamics when we repeat evolutionary simulations under conditions of scarce food. These findings suggest that (i) adaptation is not necessary for effective chemotaxis, (ii) an ancestral minimal chemotaxis system could have used a simple coupling between the signalling network and the metabolic state, and (iii) environmental conditions are one of the determining factors for the evolution of adaptive responses.

Diversity in chemotaxis mechanisms among the bacteria and archaea

The study of chemotaxis describes the cellular processes that control the movement of organisms toward favorable environments. In bacteria and archaea, motility is controlled by a two-component system involving a histidine kinase that senses the environment and a response regulator, a very common type of signal transduction in prokaryotes. Most insights into the processes involved have come from studies of Escherichia coli over the last three decades. However, in the last 10 years, with the sequencing of many prokaryotic genomes, it has become clear that E. coli represents a streamlined example of bacterial chemotaxis. While general features of excitation remain conserved among bacteria and archaea, specific features, such as adaptational processes and hydrolysis of the intracellular signal CheY-P, are quite diverse. The Bacillus subtilis chemotaxis system is considerably more complex and appears to be similar to the one that existed when the bacteria and archaea separated during evolution, so that understanding this mechanism should provide insight into the variety of mechanisms used today by the broad sweep of chemotactic bacteria and archaea. However, processes even beyond those used in E. coli and B. subtilis have been discovered in other organisms. This review emphasizes those used by B. subtilis and these other organisms but also gives an account of the mechanism in E. coli.

CheR- and CheB-dependent chemosensory adaptation system of Rhodobacter sphaeroides

Rhodobacter sphaeroides has multiple homologues of most of the Escherichia coli chemotaxis genes, organized in three major operons and other, unlinked, loci. These include cheA(1) and cheR(1) (che Op(1)) and cheA(2), cheR(2), and cheB(1) (che Op(2)). In-frame deletions of these cheR and cheB homologues were constructed and the chemosensory behaviour of the resultant mutants examined on swarm plates and in tethered cell assays. Under the conditions tested, CheR(2) and CheB(1) were essential for normal chemotaxis, whereas CheR(1) was not. cheR(2) and cheB(1), but not cheR(1), were also able to complement the equivalent E. coli mutants. However, none of the proteins were required for the correct polar localization of the chemoreceptor McpG in R. sphaeroides. In E. coli, CheR binds to the NWETF motif on the high-abundance receptors, allowing methylation of both high- and low-abundance receptors. This motif is not contained on any R. sphaeroides chemoreceptors thus far identified, although 2 of the 13 putative chemoreceptors, McpA and TlpT, do have similar sequences. This suggests that CheR(2) either interacts with the NWETF motif of E. coli methyl-accepting chemotaxis proteins (MCPs), even though its native motif may be slightly different, or with another conserved region of the MCPs. Methanol release measurements show that R. sphaeroides has an adaptation system that is different from that of Bacillus subtilis and E. coli, with methanol release measurable on the addition of attractant but not on its removal. Intriguingly, CheA(2), but not CheA(1), is able to phosphorylate CheB(1), suggesting that signaling through CheA(1) cannot initiate feedback receptor adaptation via CheB(1)-P.

Response kinetics of tethered Rhodobacter sphaeroides to changes in light intensity

Rhodobacter sphaeroides can swim toward a wide range of attractants (a process known as taxis), propelled by a single rotating flagellum. The reversals of motor direction that cause tumbles in Eschericia coli taxis are replaced by brief motor stops, and taxis is controlled by a complex sensory system with multiple homologues of the E. coli sensory proteins. We tethered photosynthetically grown cells of R. sphaeroides by their flagella and measured the response of the flagellar motor to changes in light intensity. The unstimulated bias (probability of not being stopped) was significantly larger than the bias of tethered E. coli but similar to the probability of not tumbling in swimming E. coli. Otherwise, the step and impulse responses were the same as those of tethered E. coli to chemical attractants. This indicates that the single motor and multiple sensory signaling pathways in R. sphaeroides generate the same swimming response as several motors and a single pathway in E. coli, and that the response of the single motor is directly observable in the swimming pattern. Photo-responses were larger in the presence of cyanide or the uncoupler carbonyl cyanide 4-trifluoromethoxyphenylhydrazone (FCCP), consistent with the photo-response being detected via changes in the rate of electron transport.

Identification of a fourth cheY gene in Rhodobacter sphaeroides and interspecies interaction within the bacterial chemotaxis signal transduction pathway

The Escherichia coli chemotaxis signal transduction pathway has: CheA, a histidine protein kinase; CheW, a linker between CheA and sensory proteins; CheY, the effector; and CheZ, a signal terminator. Rhodobacter sphaeroides has multiple copies of these proteins (2 x CheA, 3 x CheW and 3 x CheY, but no CheZ). In this study, we found a fourth cheY and expressed these R. sphaeroides proteins in E. coli. CheA2 (but not CheA1) restored swarming to an E. coli cheA mutant (RP9535). CheW3 (but not CheW2) restored swarming to a cheW mutant of E. coli (RP4606). R. sphaeroides CheYs did not affect E. coli lacking CheY, but restored swarming to a cheZ strain (RP1616), indicating that they can act as signal terminators in E. coli. An E. coli CheY, which is phosphorylated but cannot bind the motor (CheY109KR), was expressed in RP1616 but had no effect. Overexpression of CheA2, CheW2, CheW3, CheY1, CheY3 and CheY4 inhibited chemotaxis of wild-type E. coli (RP437) by increasing its smooth-swimming bias. While some R. sphaeroides proteins restore tumbling to smooth-swimming E. coli mutants, their activity is not controlled by the chemosensory receptors. R. sphaeroides possesses a phosphorelay cascade compatible with that of E. coli, but has additional incompatible homologues.

Motility, chemokinesis, and methylation-independent chemotaxis in Azospirillum brasilense

Observations of free-swimming and antibody-tethered Azospirillum brasilense cells showed that their polar flagella could rotate in both clockwise and counterclockwise directions. Rotation in a counterclockwise direction caused forward movement of free-swimming cells, whereas the occasional change in the direction of rotation to clockwise caused a brief reversal in swimming direction. The addition of a metabolizable chemoattractant, e.g., malate or proline, had two distinct effects on the swimming behavior of the bacteria: (i) a short-term decrease in reversal frequency from 0.33 to 0.17 s-1 and (ii) a long-term increase in the mean population swimming speed from 13 to 23 microns s-1. A. brasilense therefore shows both chemotaxis and chemokinesis in response to temporal gradients of some chemoeffectors. Chemokinesis was dependent on the growth state of the cells and may depend on an increase in the electrochemical proton gradient above a saturation threshold. Analysis of behavior of a methionine auxotroph, assays of in vivo methylation, and the use of specific antibodies raised against the sensory transducer protein Tar of Escherichia coli all failed to demonstrate the methylation-dependent pathway for chemotaxis in A. brasilense. The range of chemicals to which A. brasilense shows chemotaxis and the lack of true repellents indicate an alternative chemosensory pathway probably based on metabolism of chemoeffectors.

Role of metabolism in the chemotactic response of Rhodobacter sphaeroides to ammonia

Rhodobacter sphaeroides only showed chemotaxis towards ammonia if grown under nitrogen-limited conditions. This chemotactic response was completely inhibited by the addition of methionine sulfoximine. There was no effect of methionine sulfoximine treatment on motility or taxis towards propionate, demonstrating that the effect is specific to ammonia taxis. It is known that methionine sulfoximine inhibits glutamine synthetase and hence blocks ammonia assimilation. Methionine sulfoximine does not inhibit ammonia transport in R. sphaeroides; therefore, these results suggest that limited metabolism via a specific pathway is required subsequent to transport to elicit a chemotactic response to ammonia. Bacteria grown on high ammonia show transport but no chemotactic response to ammonia, suggesting that the pathway of assimilation is important in eliciting a chemotactic response.