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Abstract While different stages of mutualism can be observed in natural communities, the dynamics and mechanisms underlying the gradual erosion of independence of the initially autonomous organisms are not yet fully understood. In this study, by conducting the laboratory evolution on an engineered microbial community, we reproduce and molecularly track the stepwise progression towards enhanced partner entanglement. We observe that the evolution of the community both strengthens the existing metabolic interactions and leads to the emergence of de novo interdependence between partners for nitrogen metabolism, which is a common feature of natural symbiotic interactions. Selection for enhanced metabolic entanglement during the community evolution repeatedly occurred indirectly, via pleiotropies and trade-offs within cellular regulatory networks, and with no evidence of group selection. The indirect positive selection of metabolic dependencies between microbial community members, which results from the direct selection of other coupled traits in the same regulatory network, may therefore be a common but underappreciated driving force guiding the evolution of natural mutualistic communities.

ABSTRACT Bacteria sense changes in their environment and transduce signals to adjust their cellular functions accordingly. For this purpose, bacteria employ various sensors feeding into multiple signal transduction pathways. Signal recognition by bacterial sensors is studied mainly in a few model organisms, but advances in genome sequencing and analysis offer new ways of exploring the sensory repertoire of many understudied organisms. The human gut is a natural target of this line of study: it is a nutrient-rich and dynamic environment and is home to thousands of bacterial species whose activities impact human health. Many gut commensals are also poorly studied compared to model organisms and are mainly known through their genome sequences. To begin exploring the signals human gut commensals sense and respond to, we have designed a framework that enables the identification of sensory domains, prediction of signals that they recognize, and experimental verification of these predictions. We validate this framework’s functionality by systematically identifying amino acid sensors in selected bacterial genomes and metagenomes, characterizing their amino acid binding properties, and demonstrating their signal transduction potential.IMPORTANCESignal transduction is a central process governing how bacteria sense and respond to their environment. The human gut is a complex environment with many living organisms and fluctuating streams of nutrients. One gut inhabitant, Escherichia coli, is a model organism for studying signal transduction. However, E. coli is not representative of most gut microbes, and signaling pathways in the thousands of other organisms comprising the human gut microbiota remain poorly understood. This work provides a foundation for how to explore signals recognized by these organisms.

Abstract The operation of the central metabolism is typically assumed to be deterministic, but dynamics and high connectivity of the metabolic network make it potentially prone to generating fluctuations. However, time-resolved measurements of metabolite levels in individual cells that are required to characterize such fluctuations remained a challenge, particularly in small bacterial cells. Here we use single-cell metabolite measurements based on Förster resonance energy transfer, combined with computer simulations, to explore the real-time dynamics of the metabolic network of Escherichia coli. We observe that steplike exposure of starved E. coli to glycolytic carbon sources elicits large periodic fluctuations in the intracellular concentration of pyruvate in individual cells. These fluctuations are consistent with predicted oscillatory dynamics of E. coli metabolic network, and they are primarily controlled by biochemical reactions around the pyruvate node. Our results further indicate that fluctuations in glycolysis propagate to other cellular processes, possibly leading to temporal heterogeneity of cellular states within a population.

ABSTRACT The chemotaxis network, one of the most prominent prokaryotic sensory systems, is present in most motile bacteria and archaea. Although the conserved signaling core of this network is well characterized, ligand specificities of a large majority of diverse chemoreceptors encoded in bacterial genomes remain unknown. Here, we performed a systematic identification and characterization of new chemoeffectors for the opportunistic pathogen Pseudomonas aeruginosa, which has 26 chemoreceptors possessing most of the common types of ligand binding domains. By performing capillary chemotaxis assays for a library of growth-promoting compounds, we first identified a number of novel chemoattractants of varying strength. We subsequently mapped specificities of these ligands by performing Förster resonance energy transfer and microfluidic measurements for 16 hybrid chemoreceptors that combine the periplasmic ligand binding domains of P. aeruginosa receptors and the cytoplasmic signaling domain of the Escherichia coli Tar receptor. Direct binding of putative ligands to chemoreceptors was further confirmed using thermal shift assay and microcalorimetry. Altogether, the combination of methods enabled us to assign several new attractants, including methyl 4-aminobutyrate, 5-aminovalerate, L-ornithine, 2-phenylethylamine, and tyramine, to previously characterized chemoreceptors and to annotate a novel purine-specific receptor PctP. Responses of hybrid receptors to changes in pH further revealed a complex bidirectional pH sensing mechanism in P. aeruginosa, which involves at least four chemoreceptors PctA, PctC, TlpQ, and PctP. Our screening strategy could be applied for the systematic characterization of unknown sensory domains in a wide range of bacterial species. IMPORTANCE Chemotaxis of motile bacteria has multiple physiological functions. It enables bacteria to locate optimal ecological niches, mediates collective behaviors, and can play an important role in infection. These multiple functions largely depend on ligand specificities of chemoreceptors, and the number and identities of chemoreceptors show high diversity between organisms. Similar diversity is observed for the spectra of chemoeffectors, which include not only chemicals of high metabolic value but also bacterial, plant, and animal signaling molecules. However, the systematic identification of chemoeffectors and their mapping to specific chemoreceptors remains a challenge. Here, we combined several in vivo and in vitro approaches to establish a systematic screening strategy for the identification of receptor ligands and we applied it to identify a number of new physiologically relevant chemoeffectors for the important opportunistic human pathogen P. aeruginosa. This strategy can be equally applicable to map specificities of sensory domains from a wide variety of receptor types and bacteria.

Curli amyloid fibers are a major constituent of the extracellular biofilm matrix formed by bacteria of the Enterobacteriaceae family. Within Escherichia coli biofilms, curli gene expression is limited to a subpopulation of bacteria, leading to heterogeneity of extracellular matrix synthesis. Here we show that bimodal activation of curli gene expression also occurs in well-mixed planktonic cultures of E. coli, resulting in all-or-none stochastic differentiation into distinct subpopulations of curli-positive and curli-negative cells at the entry into the stationary phase of growth. Stochastic curli activation in individual E. coli cells could further be observed during continuous growth in a conditioned medium in a microfluidic device, which further revealed that the curli-positive state is only metastable. In agreement with previous reports, regulation of curli gene expression by the second messenger c-di-GMP via two pairs of diguanylate cyclase and phosphodiesterase enzymes, DgcE/PdeH and DgcM/PdeR, modulates the fraction of curli-positive cells. Unexpectedly, removal of this regulatory network does not abolish the bimodality of curli gene expression, although it affects dynamics of activation and increases heterogeneity of expression levels among individual cells. Moreover, the fraction of curli-positive cells within an E. coli population shows stronger dependence on growth conditions in the absence of regulation by DgcE/PdeH and DgcM/PdeR pairs. We thus conclude that, while not required for the emergence of bimodal curli gene expression in E. coli, this c-di-GMP regulatory network attenuates the frequency and dynamics of gene activation and increases its robustness to cellular heterogeneity and environmental variation.

Inside prokaryotic cells, passive translational diffusion typically limits the rates with which cytoplasmic proteins can reach their locations. Diffusion is thus fundamental to most cellular processes, but the understanding of protein mobility in the highly crowded and non-homogeneous environment of a bacterial cell is still limited. Here, we investigated the mobility of a large set of proteins in the cytoplasm of Escherichia coli, by employing fluorescence correlation spectroscopy (FCS) combined with simulations and theoretical modeling. We conclude that cytoplasmic protein mobility could be well described by Brownian diffusion in the confined geometry of the bacterial cell and at the high viscosity imposed by macromolecular crowding. We observed similar size dependence of protein diffusion for the majority of tested proteins, whether native or foreign to E. coli. For the faster-diffusing proteins, this size dependence is well consistent with the Stokes-Einstein relation once taking into account the specific dumbbell shape of protein fusions. Pronounced subdiffusion and hindered mobility are only observed for proteins with extensive interactions within the cytoplasm. Finally, while protein diffusion becomes markedly faster in actively growing cells, at high temperature, or upon treatment with rifampicin, and slower at high osmolarity, all of these perturbations affect proteins of different sizes in the same proportions, which could thus be described as changes of a well-defined cytoplasmic viscosity.

ABSTRACT Bacteria have evolved many different signal transduction systems to sense and respond to changing environmental conditions. Signal integration is mainly achieved by signal recognition at extracytosolic ligand-binding domains (LBDs) of receptors. Hundreds of different LBDs have been reported, and our understanding of their sensing properties is growing. Receptors must function over a range of environmental pH values, but there is little information available on the robustness of sensing as a function of pH. Here, we have used isothermal titration calorimetry to determine the pH dependence of ligand recognition by nine LBDs that cover all major LBD superfamilies, of periplasmic solute-binding proteins, and cytosolic LBDs. We show that periplasmic LBDs recognize ligands over a very broad pH range, frequently stretching over eight pH units. This wide pH range contrasts with a much narrower pH response range of the cytosolic LBDs analyzed. Many LBDs must be dimeric to bind ligands, and analytical ultracentrifugation studies showed that the LBD of the Tar chemoreceptor forms dimers over the entire pH range tested. The pH dependences of Pseudomonas aeruginosa motility and chemotaxis were bell-shaped and centered at pH 7.0. Evidence for pH robustness of signaling in vivo was obtained by Förster Resonance Energy Transfer (FRET) measurements of the chemotaxis pathway responses in Escherichia coli. Bacteria have evolved several strategies to cope with extreme pH, such as periplasmic chaperones for protein refolding. The intrinsic pH resistance of periplasmic LBDs appears to be another strategy that permits bacteria to survive under adverse conditions. IMPORTANCE Demonstration of the pH robustness of extracytoplasmic sensing reveals a previously undescribed evolutionary mechanism that enables bacteria to monitor environmental changes under changing conditions. This mechanism includes the maintenance of the dimeric state of four-helixbundle ligand-binding domains (LBDs). The construction of biosensors is a rapidly growing field of research, and their use to monitor the progression of the COVID-19 pandemic has impressively demonstrated their usefulness. LBDs represent an enormous reservoir of binding modules that can be used to create novel biosensors. Among ligands recognized by LBDs are neurotransmitters, hormones, and quorum-sensing signals. The demonstration that extracytosolic LBDs bind their signals over a wide range of pH values will facilitate the design of biosensors that function under highly variable conditions of acidity and alkalinity.

ABSTRACT Acetylcholine is a central biological signal molecule present in all kingdoms of life. In humans, acetylcholine is the primary neurotransmitter of the peripheral nervous system; it mediates signal transmission at neuromuscular junctions. Here, we show that the opportunistic human pathogen Pseudomonas aeruginosa exhibits chemoattraction toward acetylcholine over a concentration range of 1 μM to 100 mM. The maximal magnitude of the response was superior to that of many other P. aeruginosa chemoeffectors. We demonstrate that this chemoattraction is mediated by the PctD (PA4633) chemoreceptor. Using microcalorimetry, we show that the PctD ligand-binding domain (LBD) binds acetylcholine with a equilibrium dissociation constant (KD) of 23 μM. It also binds choline and with lower affinity betaine. Highly sensitive responses to acetylcholine and choline, and less sensitive responses to betaine and l-carnitine, were observed in Escherichia coli expressing a chimeric receptor comprising the PctD-LBD fused to the Tar chemoreceptor signaling domain. We also identified the PacA (ECA_RS10935) chemoreceptor of the phytopathogen Pectobacterium atrosepticum, which binds choline and betaine but fails to recognize acetylcholine. To identify the molecular determinants for acetylcholine recognition, we report high-resolution structures of PctD-LBD (with bound acetylcholine and choline) and PacA-LBD (with bound betaine). We identified an amino acid motif in PctD-LBD that interacts with the acetylcholine tail. This motif is absent in PacA-LBD. Significant acetylcholine chemotaxis was also detected in the plant pathogens Agrobacterium tumefaciens and Dickeya solani. To the best of our knowledge, this is the first report of acetylcholine chemotaxis and extends the range of host signals perceived by bacterial chemoreceptors. IMPORTANCE P. aeruginosa causes a significant number of deaths annually worldwide. For many pathogens, chemotaxis plays an import role in the initial stages of infection, and deciphering the key chomoeffectors and their cognate chemoreceptors may permit the development of strategies to inhibit this process. Genome analyses have shown that many bacteria possess a large number of chemoreceptors. The chemoeffectors recognized by the large majority of chemoreceptors are unknown. However, identifying these chemoeffectors is crucial for deciphering the evolutionary forces that have shaped chemosensory signaling mechanisms in bacteria with different lifestyles. Our current understanding of the relationship between bacterial lifestyle and chemoreceptor repertoire is limited, and this work contributes to closing this gap in our knowledge. By expanding the list of known chemoeffectors and chemoreceptors, progress is made toward identifying functional receptor homologs in other bacteria.

Cellular signalling networks provide information to the cell, but the trade-off between accuracy of information transfer and energetic cost of doing so has not been assessed. Here, the authors investigate a MAPK signalling cascade in budding yeast and find that information is maximised per unit energetic cost.

Abstract Endocytosis is a fundamental cellular trafficking pathway, which requires an organized assembly of the multiprotein endocytic coat to pull the plasma membrane into the cell. Although the protein composition of the endocytic coat is known, its functional architecture is not well understood. Here, we determine the nanoscale organization of the endocytic coat by FRET microscopy in yeast Saccharomyces cerevisiae. We assessed pairwise proximities of 18 conserved coat‐associated proteins and used clathrin subunits and protein truncations as molecular rulers to obtain a high‐resolution protein map of the coat. Furthermore, we followed rearrangements of coat proteins during membrane invagination and their binding dynamics at the endocytic site. We show that the endocytic coat proteins are not confined inside the clathrin lattice, but form distinct functional layers above and below the lattice. Importantly, key endocytic proteins transverse the clathrin lattice deeply into the cytoplasm connecting thus the membrane and cytoplasmic parts of the coat. We propose that this design enables an efficient and regulated function of the endocytic coat during endocytic vesicle formation.

Gram-positive bacteria can release signaling peptides that are ‘probed’ by intracellular receptors after being pumped into the cytoplasm. Here, Babel et al. show that these pump-probe networks can infer the fraction of signal-producing cells in a mixed population, and do not necessarily mediate typical quorum-sensing control.

Swimming bacteria perform collective motion at high cell density, yet it is unclear how this behaviour affects their ability to follow substance gradients in the environment. Here, Colin et al. address this question by studying motion of Escherichia coli in controlled chemical gradients.

Summary: Temperature is one of the key cues that enable microorganisms to adjust their physiology in response to environmental changes. Here we show that motility is the major cellular function of Escherichia coli that is differentially regulated between growth at normal host temperature of 37°C and the febrile temperature of 42°C. Expression of both class II and class III flagellar genes is reduced at 42°C because of lowered level of the upstream activator FlhD. Class III genes are additionally repressed because of the destabilization and malfunction of secretion apparatus at high temperature, which prevents secretion of the anti-sigma factor FlgM. This mechanism of repression apparently accelerates loss of motility at 42°C. We hypothesize that E. coli perceives high temperature as a sign of inflammation, downregulating flagella to escape detection by the immune system of the host. Secretion-dependent coupling of gene expression to the environmental temperature is likely common among many bacteria. : Microbiology; Microbial Physiology; Microbial Cell Structure; Molecular Microbiology Subject Areas: Microbiology, Microbial Physiology, Microbial Cell Structure, Molecular Microbiology

ABSTRACT Bacterial flagellar motility plays an important role in many processes that occur at surfaces or in hydrogels, including adhesion, biofilm formation, and bacterium-host interactions. Consequently, expression of flagellar genes, as well as genes involved in biofilm formation and virulence, can be regulated by the surface contact. In a few bacterial species, flagella themselves are known to serve as mechanosensors, where an increased load on flagella experienced during surface contact or swimming in viscous media controls gene expression. In this study, we show that gene regulation by motility-dependent mechanosensing is common among pathogenic Escherichia coli strains. This regulatory mechanism requires flagellar rotation, and it enables pathogenic E. coli to repress flagellar genes at low loads in liquid culture, while activating motility in porous medium (soft agar) or upon surface contact. It also controls several other cellular functions, including metabolism and signaling. The mechanosensing response in pathogenic E. coli depends on the negative regulator of motility, RflP (YdiV), which inhibits basal expression of flagellar genes in liquid. While no conditional inhibition of flagellar gene expression in liquid and therefore no upregulation in porous medium was observed in the wild-type commensal or laboratory strains of E. coli, mechanosensitive regulation could be recovered by overexpression of RflP in the laboratory strain. We hypothesize that this conditional activation of flagellar genes in pathogenic E. coli reflects adaptation to the dual role played by flagella and motility during infection. IMPORTANCE Flagella and motility are widespread virulence factors among pathogenic bacteria. Motility enhances the initial host colonization, but the flagellum is a major antigen targeted by the host immune system. Here, we demonstrate that pathogenic E. coli strains employ a mechanosensory function of the flagellar motor to activate flagellar expression under high loads, while repressing it in liquid culture. We hypothesize that this mechanism allows pathogenic E. coli to regulate its motility dependent on the stage of infection, activating flagellar expression upon initial contact with the host epithelium, when motility is beneficial, but reducing it within the host to delay the immune response.

Bacteria use chemotaxis receptors to perceive environmental factors. Here, the authors show that mutations in a chemotaxis receptor can invert the sensory response, e.g. from attractant to repellent, and use these mutants to map regions that enable the receptor to sense multiple environmental factors.

Regulatory networks play a central role in the relationship between genotype and phenotype in all organisms. However, the mechanisms that underpin the evolutionary plasticity of these networks remain poorly understood. Here, we used experimental selection for enhanced bacterial motility in a porous environment to explore the adaptability of one of the most complex networks known in bacteria. We found that the resulting phenotypic changes are mediated by adaptive mutations in several functionally different proteins, including multiple components of the flagellar motor. Nevertheless, this evolutionary adaptation could be explained by a single mechanism, namely remodeling of the checkpoint regulating flagellar gene expression. Supported by computer simulations, our findings suggest that the specific “bow-tie” topology of the checkpoint facilitates evolutionary tuning of the cost-benefit trade-off between motility and growth. We propose that bow-tie regulatory motifs, which are widespread in cellular networks, play a general role in evolutionary adaptation.

ABSTRACT Bacterial viruses, or bacteriophages, are highly abundant in the biosphere and have a major impact on microbial populations. Many examples of phage interactions with their hosts, including establishment of dormant lysogenic and active lytic states, have been characterized at the level of the individual cell. However, much less is known about the dependence of these interactions on host metabolism and signal exchange within bacterial communities. In this report, we describe a lysogenic state of the enterobacterial phage T1, previously known as a classical lytic phage, and characterize the underlying regulatory circuitry. We show that the transition from lysogeny to lysis depends on bacterial population density, perceived via interspecies autoinducer 2. Lysis is further controlled by the metabolic state of the cell, mediated by the cyclic-3′,5′-AMP (cAMP) receptor protein (CRP) of the host. We hypothesize that such combinations of cell density and metabolic sensing may be common in phage-host interactions. IMPORTANCE The dynamics of microbial communities are heavily shaped by bacterium-bacteriophage interactions. But despite the apparent importance of bacteriophages, our understanding of the mechanisms controlling phage dynamics in bacterial populations, and particularly of the differences between the decisions that are made in the dormant lysogenic and active lytic states, remains limited. In this report, we show that enterobacterial phage T1, previously described as a lytic phage, is able to undergo lysogeny. We further demonstrate that the lysogeny-to-lysis decision occurs in response to changes in the density of the bacterial population, mediated by interspecies quorum-sensing signal AI-2, and in the metabolic state of the cell, mediated by cAMP receptor protein. We hypothesize that this strategy enables the phage to maximize its chances of self-amplification and spreading in bacterial population upon induction of the lytic cycle and that it might be common in phage-host interactions.

A small molecule (autoinducer 2, or AI-2) regulates biofilm formation and virulence in several bacteria, but its role in Escherichia coli is unknown. Here, Laganenka et al. show that chemotaxis towards self-produced AI-2 mediates autoaggregation and promotes stress resistance and biofilm formation in E. coli.

Cells of the yeast Saccharomyces cerevisiaecan mate with other cells of opposite mating type. Here, the authors show that the combination of a pheromone and a pheromone-degrading enzyme allows yeast cells to monitor relative mate abundance within a population and adjust their commitment to sexual reproduction.

Cellular networks are intrinsically subject to stochastic fluctuations, but analysis of the resulting noise remained largely limited to gene expression. The pathway controlling chemotaxis of Escherichia coli provides one example where posttranslational signaling noise has been deduced from cellular behavior. This noise was proposed to result from stochasticity in chemoreceptor methylation, and it is believed to enhance environment exploration by bacteria. Here we combined single-cell FRET measurements with analysis based on the fluctuation-dissipation theorem (FDT) to characterize origins of activity fluctuations within the chemotaxis pathway. We observed surprisingly large methylation-independent thermal fluctuations of receptor activity, which contribute to noise comparably to the energy-consuming methylation dynamics. Interactions between clustered receptors involved in amplification of chemotactic signals are also necessary to produce the observed large activity fluctuations. Our work thus shows that the high response sensitivity of this cellular pathway also increases its susceptibility to noise, from thermal and out-of-equilibrium processes.

In bacteria various tactic responses are mediated by the same cellular pathway, but sensing of physical stimuli remains poorly understood. Here, we combine an in-vivo analysis of the pathway activity with a microfluidic taxis assay and mathematical modeling to investigate the thermotactic response of Escherichia coli. We show that in the absence of chemical attractants E. coli exhibits a steady thermophilic response, the magnitude of which decreases at higher temperatures. Adaptation of wild-type cells to high levels of chemoattractants sensed by only one of the major chemoreceptors leads to inversion of the thermotactic response at intermediate temperatures and bidirectional cell accumulation in a thermal gradient. A mathematical model can explain this behavior based on the saturation-dependent kinetics of adaptive receptor methylation. Lastly, we find that the preferred accumulation temperature corresponds to optimal growth in the presence of the chemoattractant serine, pointing to a physiological relevance of the observed thermotactic behavior.

Abstract The mechanisms underlying chromosome segregation in prokaryotes remain a subject of debate and no unifying view has yet emerged. Given that the initial disentanglement of duplicated chromosomes could be achieved by purely entropic forces, even the requirement of an active prokaryotic segregation machinery has been questioned. Using computer simulations, we show that entropic forces alone are not sufficient to achieve and maintain full separation of chromosomes. This is, however, possible by assuming repeated binding of chromosomes along a gradient of membrane‐associated tethering sites toward the poles. We propose that, in Escherichia coli, such a gradient of membrane tethering sites may be provided by the oscillatory Min system, otherwise known for its role in selecting the cell division site. Consistent with this hypothesis, we demonstrate that MinD binds to DNA and tethers it to the membrane in an ATP‐dependent manner. Taken together, our combined theoretical and experimental results suggest the existence of a novel mechanism of chromosome segregation based on the Min system, further highlighting the importance of active segregation of chromosomes in prokaryotic cell biology.

Many bacteria primarily exist in nature as structured multicellular communities, so called biofilms. Biofilm formation is a highly regulated process that includes the transition from the motile planktonic to sessile biofilm lifestyle. Cellular differentiation within a biofilm is a commonly accepted concept but it remains largely unclear when, where and how exactly such differentiation arises. Here we used fluorescent transcriptional reporters to quantitatively analyze spatio-temporal expression patterns of several groups of genes during the formation of submerged Escherichia coli biofilms in an open static system. We first confirm that formation of such submerged biofilms as well as pellicles at the liquid-air interface requires the major matrix component, curli, and flagella-mediated motility. We further demonstrate that in this system, diversification of gene expression leads to emergence of at least three distinct subpopulations of E. coli, which differ in their levels of curli and flagella expression, and in the activity of the stationary phase sigma factor σS. Our study reveals mutually exclusive expression of curli fibers and flagella at the single cell level, with high curli levels being confined to dense cell aggregates/microcolonies and flagella expression showing an opposite expression pattern. Interestingly, despite the known σS-dependence of curli induction, there was only a partial correlation between the σS activity and curli expression, with subpopulations of cells having high σS activity but low curli expression and vice versa. Finally, consistent with different physiology of the observed subpopulations, we show striking differences between the growth rates of cells within and outside of aggregates.

The phosphotransferase system (PTS) plays a pivotal role in the uptake of multiple sugars in Escherichia coli and many other bacteria. In the cell, individual sugar-specific PTS branches are interconnected through a series of phosphotransfer reactions, thus creating a global network that not only phosphorylates incoming sugars but also regulates a number of cellular processes. Despite the apparent importance of the PTS network in bacterial physiology, the holistic function of the network in the cell remains unclear. Here we used Förster resonance energy transfer (FRET) to investigate the PTS network in E. coli, including the dynamics of protein interactions and the processing of different stimuli and their transmission to the chemotaxis pathway. Our results demonstrate that despite the seeming complexity of the cellular PTS network, its core part operates in a strikingly simple way, sensing the overall influx of PTS sugars irrespective of the sugar identity and distributing this information equally through all studied branches of the network. Moreover, it also integrates several other specific metabolic inputs. The integrated output of the PTS network is then transmitted linearly to the chemotaxis pathway, in stark contrast to the amplification of conventional chemotactic stimuli. Finally, we observe that default uptake through the uninduced PTS network correlates well with the quality of the carbon source, apparently representing an optimal regulatory strategy.

The spindle position checkpoint (SPOC) is a spindle pole body (SPB, equivalent of mammalian centrosome) associated surveillance mechanism that halts mitotic exit upon spindle mis-orientation. Here, we monitored the interaction between SPB proteins and the SPOC component Bfa1 by FRET microscopy. We show that Bfa1 binds to the scaffold-protein Nud1 and the γ-tubulin receptor Spc72. Spindle misalignment specifically disrupts Bfa1-Spc72 interaction by a mechanism that requires the 14-3-3-family protein Bmh1 and the MARK/PAR-kinase Kin4. Dissociation of Bfa1 from Spc72 prevents the inhibitory phosphorylation of Bfa1 by the polo-like kinase Cdc5. We propose Spc72 as a regulatory hub that coordinates the activity of Kin4 and Cdc5 towards Bfa1. In addition, analysis of spc72∆ cells shows that a mitotic-exit-promoting dominant signal, which is triggered upon elongation of the spindle into the bud, overrides the SPOC. Our data reinforce the importance of daughter-cell-associated factors and centrosome-based regulations in mitotic exit and SPOC control.

Abstract 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.

Abstract How cells manage to get equal distribution of their structures and molecules at cell division is a crucial issue in biology. In principle, a feedback mechanism could always ensure equality by measuring and correcting the distribution in the progeny. However, an elegant alternative could be a mechanism relying on self‐organization, with the interplay between system properties and cell geometry leading to the emergence of equal partitioning. The problem is exemplified by the bacterial Min system that defines the division site by oscillating from pole to pole. Unequal partitioning of Min proteins at division could negatively impact system performance and cell growth because of loss of Min oscillations and imprecise mid‐cell determination. In this study, we combine live cell and computational analyses to show that known properties of the Min system together with the gradual reduction of protein exchange through the constricting septum are sufficient to explain the observed highly precise spontaneous protein partitioning. Our findings reveal a novel and effective mechanism of protein partitioning in dividing cells and emphasize the importance of self‐organization in basic cellular processes.

Abstract Protein–protein interactions play key roles in virtually all cellular processes, often forming complex regulatory networks. A powerful tool to study interactions in vivo is fluorescence resonance energy transfer (FRET), which is based on the distance‐dependent energy transfer from an excited donor to an acceptor fluorophore. Here, we used FRET to systematically map all protein interactions in the chemotaxis signaling pathway in Escherichia coli, one of the most studied models of signal transduction, and to determine stimulation‐induced changes in the pathway. Our FRET analysis identified 19 positive FRET pairs out of the 28 possible protein combinations, with 9 pairs being responsive to chemotactic stimulation. Six stimulation‐dependent and five stimulation‐independent interactions were direct, whereas other interactions were apparently mediated by scaffolding proteins. Characterization of stimulation‐induced responses revealed an additional regulation through activity dependence of interactions involving the adaptation enzyme CheB, and showed complex rearrangement of chemosensory receptors. Our study illustrates how FRET can be efficiently employed to study dynamic protein networks in vivo.

Abstract Like many sensory receptors, bacterial chemotaxis receptors form clusters. In bacteria, large‐scale clusters are subdivided into signaling teams that act as ‘antennas’ allowing detection of ligands with remarkable sensitivity. The range of sensitivity is greatly extended by adaptation of receptors to changes in concentrations through covalent modification. However, surprisingly little is known about the sizes of receptor signaling teams. Here, we combine measurements of the signaling response, obtained from in vivo fluorescence resonance energy transfer, with the statistical method of principal component analysis, to quantify the size of signaling teams within the framework of the previously successful Monod–Wyman–Changeux model. We find that size of signaling teams increases 2‐ to 3‐fold with receptor modification, indicating an additional, previously unrecognized level of adaptation of the chemotaxis network. This variation of signaling‐team size shows that receptor cooperativity is dynamic and likely optimized for sensing noisy ligand concentrations.

Protein-protein interactions are important layers of regulation in all kingdoms of life. Identification and characterization of these interactions is one challenging task of the post-genomic era and crucial for understanding of molecular processes within a cell. Several methods have been successfully employed during the past decades to identify protein-protein interactions in bacteria, but most of them include tedious and time-consuming manipulations of DNA. In contrast, the MultiSite Gateway system is a fast tool for transfer of multiple DNA fragments between plasmids enabling simultaneous and site directed cloning of up to four fragments into one construct. Here we developed a new set of Gateway vectors including custom made entry vectors and modular Destination vectors for studying protein-protein interactions via Fluorescence Resonance Energy Transfer (FRET), Bacterial two Hybrid (B2H) and split Gaussia luciferase (Gluc), as well as for fusions with SNAP-tag and HaloTag for dual-color super-resolution microscopy. As proof of principle, we characterized the interaction between the Salmonella effector SipA and its chaperone InvB via split Gluc and B2H approach. The suitability for FRET analysis as well as functionality of fusions with SNAP- and HaloTag could be demonstrated by studying the transient interaction between chemotaxis response regulator CheY and its phosphatase CheZ.

Bacteria navigate within inhomogeneous environments by temporally comparing concentrations of chemoeffectors over the course of a few seconds and biasing their rate of reorientations accordingly, thereby drifting towards more favorable conditions. This navigation requires a short-term memory achieved through the sequential methylations and demethylations of several specific glutamate residues on the chemotaxis receptors, which progressively adjusts the receptors' activity to track the levels of stimulation encountered by the cell with a delay. Such adaptation also tunes the receptors' sensitivity according to the background ligand concentration, enabling the cells to respond to fractional rather than absolute concentration changes, i.e. to perform logarithmic sensing. Despite the adaptation system being principally well understood, the need for a specific number of methylation sites remains relatively unclear. Here we systematically substituted the four glutamate residues of the Tar receptor of Escherichia coli by non-methylated alanine, creating a set of 16 modified receptors with a varying number of available methylation sites and explored the effect of these substitutions on the performance of the chemotaxis system. Alanine substitutions were found to desensitize the receptors, similarly but to a lesser extent than glutamate methylation, and to affect the methylation and demethylation rates of the remaining sites in a site-specific manner. Each substitution reduces the dynamic range of chemotaxis, by one order of magnitude on average. The substitution of up to two sites could be partly compensated by the adaptation system, but the full set of methylation sites was necessary to achieve efficient logarithmic sensing.

Sensory systems have evolved to respond to input stimuli of certain statistical properties, and to reliably transmit this information through biochemical pathways. Hence, for an experimentally well-characterized sensory system, one ought to be able to extract valuable information about the statistics of the stimuli. Based on dose-response curves from in vivo fluorescence resonance energy transfer (FRET) experiments of the bacterial chemotaxis sensory system, we predict the chemical gradients chemotactic Escherichia coli cells typically encounter in their natural environment. To predict average gradients cells experience, we revaluate the phenomenological Weber's law and its generalizations to the Weber-Fechner law and fold-change detection. To obtain full distributions of gradients we use information theory and simulations, considering limitations of information transmission from both cell-external and internal noise. We identify broad distributions of exponential gradients, which lead to log-normal stimuli and maximal drift velocity. Our results thus provide a first step towards deciphering the chemical nature of complex, experimentally inaccessible cellular microenvironments, such as the human intestine.

Cellular signaling systems show astonishing precision in their response to external stimuli despite strong fluctuations in the molecular components that determine pathway activity. To control the effects of noise on signaling most efficiently, living cells employ compensatory mechanisms that reach from simple negative feedback loops to robustly designed signaling architectures. Here, we report on a novel control mechanism that allows living cells to keep precision in their signaling characteristics - stationary pathway output, response amplitude, and relaxation time - in the presence of strong intracellular perturbations. The concept relies on the surprising fact that for systems showing perfect adaptation an exponential signal amplification at the receptor level suffices to eliminate slowly varying multiplicative noise. To show this mechanism at work in living systems, we quantified the response dynamics of the E. coli chemotaxis network after genetically perturbing the information flux between upstream and downstream signaling components. We give strong evidence that this signaling system results in dynamic invariance of the activated response regulator against multiplicative intracellular noise. We further demonstrate that for environmental conditions, for which precision in chemosensing is crucial, the invariant response behavior results in highest chemotactic efficiency. Our results resolve several puzzling features of the chemotaxis pathway that are widely conserved across prokaryotes but so far could not be attributed any functional role.

Adaptability is an essential property of many sensory systems, enabling maintenance of a sensitive response over a range of background stimulus levels. In bacterial chemotaxis, adaptation to the preset level of pathway activity is achieved through an integral feedback mechanism based on activity-dependent methylation of chemoreceptors. It has been argued that this architecture ensures precise and robust adaptation regardless of the ambient ligand concentration, making perfect adaptation a celebrated property of the chemotaxis system. However, possible deviations from such ideal adaptive behavior and its consequences for chemotaxis have not been explored in detail. Here we show that the chemotaxis pathway in Escherichia coli shows increasingly imprecise adaptation to higher concentrations of attractants, with a clear correlation between the time of adaptation to a step-like stimulus and the extent of imprecision. Our analysis suggests that this imprecision results from a gradual saturation of receptor methylation sites at high levels of stimulation, which prevents full recovery of the pathway activity by violating the conditions required for precise adaptation. We further use computer simulations to show that limited imprecision of adaptation has little effect on the rate of chemotactic drift of a bacterial population in gradients, but hinders precise accumulation at the peak of the gradient. Finally, we show that for two major chemoeffectors, serine and cysteine, failure of adaptation at concentrations above 1 mM might prevent bacteria from accumulating at toxic concentrations of these amino acids.

The molecular chaperone Hsp90 is essential in eukaryotes, in which it facilitates the folding of developmental regulators and signal transduction proteins known as Hsp90 clients. In contrast, Hsp90 is not essential in bacteria, and a broad characterization of its molecular and organismal function is lacking. To enable such characterization, we used a genome-scale phylogenetic analysis to identify genes that co-evolve with bacterial Hsp90. We find that genes whose gain and loss were coordinated with Hsp90 throughout bacterial evolution tended to function in flagellar assembly, chemotaxis, and bacterial secretion, suggesting that Hsp90 may aid assembly of protein complexes. To add to the limited set of known bacterial Hsp90 clients, we further developed a statistical method to predict putative clients. We validated our predictions by demonstrating that the flagellar protein FliN and the chemotaxis kinase CheA behaved as Hsp90 clients in Escherichia coli, confirming the predicted role of Hsp90 in chemotaxis and flagellar assembly. Furthermore, normal Hsp90 function is important for wild-type motility and/or chemotaxis in E. coli. This novel function of bacterial Hsp90 agreed with our subsequent finding that Hsp90 is associated with a preference for multiple habitats and may therefore face a complex selection regime. Taken together, our results reveal previously unknown functions of bacterial Hsp90 and open avenues for future experimental exploration by implicating Hsp90 in the assembly of membrane protein complexes and adaptation to novel environments.

Microorganisms use multiple two-component sensory systems to detect changes in their environment and elicit physiological responses. Despite their wide spread and importance, the intracellular organization of two-component sensory proteins in bacteria remains little investigated. A notable exception is the well-studied clustering of the chemoreceptor-kinase complexes that mediate chemotaxis behaviour. However, these chemosensory complexes differ fundamentally from other systems, both structurally and functionally. Therefore, studying the organization of typical sensory kinases in bacteria is essential for understanding the general role of receptor clustering in bacterial sensory signalling. Here, by studying mYFP-tagged sensory kinases in Escherichia coli, we show that the tagged TorS and EvgS sensors have a clear tendency for self-association and clustering. These sensors clustered even when expressed at a level of a few hundred copies per cell. Moreover, the mYFP-tagged response regulator TorR showed clear TorS-dependent clustering, indicating that untagged TorS sensors also tend to form clusters. We also provide evidence for the functionality of these tagged sensors. Experiments with truncated TorS or EvgS proteins suggested that clustering of EvgS sensors depends on the cytoplasmic part of the protein, whereas clustering of TorS sensors can be potentially mediated by the periplasmic/transmembrane domain. Overall, these findings support the notion that sensor clustering plays a role in bacterial sensory signalling beyond chemotaxis.

Nature Communications 7: Article number: 12984 (2016); Published: 30 September 2016; Updated: 15 December 2016 Two previous studies describing the effects of autoinducer 2 (AI-2) on biofilm formation and chemotaxis in Escherichia coli were inadvertently omitted from the reference list of this Article.

Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations.

Adaptation of the chemotaxis sensory pathway of the bacterium Escherichia coli is integral for detecting chemicals over a wide range of background concentrations, ultimately allowing cells to swim towards sources of attractant and away from repellents. Its biochemical mechanism based on methylation and demethylation of chemoreceptors has long been known. Despite the importance of adaptation for cell memory and behavior, the dynamics of adaptation are difficult to reconcile with current models of precise adaptation. Here, we follow time courses of signaling in response to concentration step changes of attractant using in vivo fluorescence resonance energy transfer measurements. Specifically, we use a condensed representation of adaptation time courses for efficient evaluation of different adaptation models. To quantitatively explain the data, we finally develop a dynamic model for signaling and adaptation based on the attractant flow in the experiment, signaling by cooperative receptor complexes, and multiple layers of feedback regulation for adaptation. We experimentally confirm the predicted effects of changing the enzyme-expression level and bypassing the negative feedback for demethylation. Our data analysis suggests significant imprecision in adaptation for large additions. Furthermore, our model predicts highly regulated, ultrafast adaptation in response to removal of attractant, which may be useful for fast reorientation of the cell and noise reduction in adaptation.

Chemotactic movement of Escherichia coli is one of the most thoroughly studied paradigms of simple behavior. Due to significant competitive advantage conferred by chemotaxis and to high evolution rates in bacteria, the chemotaxis system is expected to be strongly optimized. Bacteria follow gradients by performing temporal comparisons of chemoeffector concentrations along their runs, a strategy which is most efficient given their size and swimming speed. Concentration differences are detected by a sensory system and transmitted to modulate rotation of flagellar motors, decreasing the probability of a tumble and reorientation if the perceived concentration change during a run is positive. Such regulation of tumble probability is of itself sufficient to explain chemotactic drift of a population up the gradient, and is commonly assumed to be the only navigation mechanism of chemotactic E. coli. Here we use computer simulations to predict existence of an additional mechanism of gradient navigation in E. coli. Based on the experimentally observed dependence of cell tumbling angle on the number of switching motors, we suggest that not only the tumbling probability but also the degree of reorientation during a tumble depend on the swimming direction along the gradient. Although the difference in mean tumbling angles up and down the gradient predicted by our model is small, it results in a dramatic enhancement of the cellular drift velocity along the gradient. We thus demonstrate a new level of optimization in E. coli chemotaxis, which arises from the switching of several flagellar motors and a resulting fine tuning of tumbling angle. Similar strategy is likely to be used by other peritrichously flagellated bacteria, and indicates yet another level of evolutionary development of bacterial chemotaxis.

Chemotaxis allows bacteria to colonize their environment more efficiently and to find optimal growth conditions, and is consequently under strong evolutionary selection. Theoretical and experimental analyses of bacterial chemotaxis suggested that the pathway has been evolutionarily optimized to produce robust output under conditions of such physiological perturbations as stochastic intercellular variations in protein levels while at the same time minimizing complexity and cost of protein expression. Pathway topology in Escherichia coli apparently evolved to produce an invariant output under concerted variations in protein levels, consistent with experimentally observed transcriptional coupling of chemotaxis genes. Here, we show that the pathway robustness is further enhanced through the pairwise translational coupling of adjacent genes. Computer simulations predicted that the robustness of the pathway against the uncorrelated variations in protein levels can be enhanced by a selective pairwise coupling of individual chemotaxis genes on one mRNA, with the order of genes in E. coli ranking among the best in terms of noise compensation. Translational coupling between chemotaxis genes was experimentally confirmed, and coupled expression of these genes was shown to improve chemotaxis. Bioinformatics analysis further revealed that E. coli gene order corresponds to consensus in sequenced bacterial genomes, confirming evolutionary selection for noise reduction. Since polycistronic gene organization is common in bacteria, translational coupling between adjacent genes may provide a general mechanism to enhance robustness of their signaling and metabolic networks. Moreover, coupling between expression of neighboring genes is also present in eukaryotes, and similar principles of noise reduction might thus apply to all cellular networks.

Simulation of cellular behavior on multiple scales requires models that are sufficiently detailed to capture central intracellular processes but at the same time enable the simulation of entire cell populations in a computationally cheap way. In this paper we present RapidCell, a hybrid model of chemotactic Escherichia coli that combines the Monod-Wyman-Changeux signal processing by mixed chemoreceptor clusters, the adaptation dynamics described by ordinary differential equations, and a detailed model of cell tumbling. Our model dramatically reduces computational costs and allows the highly efficient simulation of E. coli chemotaxis. We use the model to investigate chemotaxis in different gradients, and suggest a new, constant-activity type of gradient to systematically study chemotactic behavior of virtual bacteria. Using the unique properties of this gradient, we show that optimal chemotaxis is observed in a narrow range of CheA kinase activity, where concentration of the response regulator CheY-P falls into the operating range of flagellar motors. Our simulations also confirm that the CheB phosphorylation feedback improves chemotactic efficiency by shifting the average CheY-P concentration to fit the motor operating range. Our results suggest that in liquid media the variability in adaptation times among cells may be evolutionary favorable to ensure coexistence of subpopulations that will be optimally tactic in different gradients. However, in a porous medium (agar) such variability appears to be less important, because agar structure poses mainly negative selection against subpopulations with low levels of adaptation enzymes. RapidCell is available from the authors upon request.