Temporal stimulation of chemotaxis in Escherichia coli

Individual bacterial cells can use spatial sensing of chemical gradients to direct chemotaxis on surfaces

Swimming bacteria navigate chemical gradients using temporal sensing to detect changes in concentration over time. Here we show that surface-attached bacteria use a fundamentally different mode of sensing during chemotaxis. We combined microfluidic experiments, massively parallel cell tracking and fluorescent reporters to study how Pseudomonas aeruginosa senses chemical gradients during pili-based 'twitching' chemotaxis on surfaces. Unlike swimming cells, we found that temporal changes in concentration did not induce motility changes in twitching cells. We then quantified the chemotactic behaviour of stationary cells by following changes in the sub-cellular localization of fluorescent proteins as cells are exposed to a gradient that alternates direction. These experiments revealed that P. aeruginosa cells can directly sense differences in concentration across the lengths of their bodies, even in the presence of strong temporal fluctuations. Our work thus overturns the widely held notion that bacterial cells are too small to directly sense chemical gradients in space.

C. elegans foraging as a model for understanding the neuronal basis of decision-making

Animals have evolved to seek, select, and exploit food sources in their environment. Collectively termed foraging, these ubiquitous behaviors are necessary for animal survival. As a foundation for understanding foraging, behavioral ecologists established early theoretical and mathematical frameworks which have been subsequently refined and supported by field and laboratory studies of foraging animals. These simple models sought to explain how animals decide which strategies to employ when locating food, what food items to consume, and when to explore the environment for new food sources. These foraging decisions involve integration of prior experience with multimodal sensory information about the animal's current environment and internal state. We suggest that the nematode Caenorhabditis elegans is well-suited for a high-resolution analysis of complex goal-oriented behaviors such as foraging. We focus our discussion on behavioral studies highlighting C. elegans foraging on bacteria and summarize what is known about the underlying neuronal and molecular pathways. Broadly, we suggest that this simple model system can provide a mechanistic understanding of decision-making and present additional avenues for advancing our understanding of complex behavioral processes.

Twists and turns: 40 years of investigating how and why bacteria swim

Fifty years of research has transformed our understanding of bacterial movement from one of description, based on a limited number of electron micrographs and some low-magnification studies of cells moving towards or away from chemical effectors, to probably the best understood behavioural system in biology. We have a molecular understanding of how bacteria sense and respond to changes in their environment and detailed structural insights into the workings of one of the most complex motor structures we know of. Thanks to advances in genomics we also understand how, through evolution, different species have tuned and adapted a core shared system to optimize behaviour in their specific environment. In this review, I will highlight some of the unexpected findings we made during my over 40-year career, how those findings changed some of our understanding of bacterial behaviour and biochemistry and some of the battles to have those observations accepted.

Directed colloidal assembly and banding via DC electrokinetics

Manipulating the transport and assembly of colloidal particles to form segregated bands or ordered supracolloidal structures plays an important role in many aspects of science and technology, from understanding the origin of life to synthesizing new materials for next-generation manufacturing, electronics, and therapeutics. One commonly used method to direct colloidal transport and assembly is the application of electric fields, either AC or DC, due to its feasibility. However, as colloidal segregation and assembly both require active redistribution of colloidal particles across multiple length scales, it is not apparent at first sight how a DC electric field, either externally applied or internally induced, can lead to colloidal structuring. In this Perspective, we briefly review and highlight recent advances and standing challenges in colloidal transport and assembly enabled by DC electrokinetics.

Direct measurement of the aerotactic response in a bacterial suspension

Aerotaxis is the ability of motile cells to navigate toward oxygen. A key question is the dependence of the aerotactic velocity with the local oxygen concentration c. Here we combine simultaneous bacteria tracking and local oxygen concentration measurements using Ruthenium encapsulated in micelles to characterize the aerotactic response of Burkholderia contaminans, a motile bacterium ubiquitous in the environment. In our experiments, an oxygen gradient is produced by the bacterial respiration in a sealed glass capillary permeable to oxygen at one end, producing a bacterial band traveling toward the oxygen source. We compute the aerotactic response χ(c) both at the population scale, from the drift velocity in the bacterial band, and at the bacterial scale, from the angular modulation of the run times. Both methods are consistent with a power-law χ∝c^{-2}, in good agreement with existing models based on the biochemistry of bacterial membrane receptors.

Tuning chemotactic and diffusiophoretic spreading via hydrodynamic flows

The transport of microorganisms by chemotaxis is described by the same "log-sensing" response as colloids undergoing diffusiophoresis, despite their different mechanistic origins. We employ a recently-developed macrotransport theory to analyze the advective-diffusive transport of a chemotactic or diffusiophoretic colloidal species (both referred to as "colloids") in a circular tube under a steady pressure-driven flow (referred to as hydrodynamic flow) and transient solute gradient. First, we derive an exact solution to the log-sensing chemotactic/diffusiophoretic macrotransport equation. We demonstrate that a strong hydrodynamic flow can reduce spreading of solute-repelled colloids, by eliminating super-diffusion which occurs in an otherwise quiescent system. In contrast, hydrodynamic flows always enhance spreading of solute-attracted colloids. Second, we generalize the exact solution to show that the above tunable spreading phenomena by hydrodynamic flows persist quantitatively for decaying colloids, as may occur with cell death, for example. Third, we examine the spreading of chemotactic colloids by employing a more general model that captures a hallmark of chemotaxis, that log-sensing occurs only over a finite range of solute concentration. Apart from demonstrating for the first time the generality of the macrotransport theory to incorporate an arbitrary chemotactic flow model, we reveal via numerical solutions new regimes of anomalous spreading, which match qualitatively with experiments and are tunable by hydrodynamic flows. The results presented here could be employed to tailor chemotactic/diffusiophoretic colloid transport using hydrodynamic flows, which are central to applications such as oil recovery and bioremediation of aquifers.

Cellular Memory of HipA-Induced Growth Arrest: The Length of Cell Growth Arrest Becomes Shorter for Each Successive Induction

Toxin-antitoxin (TA) systems are genetic modules found commonly in bacterial genomes. HipA is a toxin protein encoded from the hipBA TA system in the genome of Escherichia coli. Ectopic expression of hipA induces cell growth arrest. Unlike the cell growth arrest caused by other TA toxins, cells resume growth from the HipA-induced cell growth arrest phase after a defined period of time. In this article, we describe the change in the length of growth arrest while cells undergo repeated cycles of hipA induction, growth arrest and regrowth phases. In the multiple conditions tested, we observed that the length of growth arrest became successively shorter for each round of induction. We verified that this was not due to the appearance of HipA-resistant mutants. Additionally, we identified conditions, such as the growth phase of the starting culture and growth vessels, that alter the length of growth arrest. Our results showed that the length of HipA-induced growth arrest was dependent on environmental factors-in particular, the past growth environment of cells, such as a previous hipA induction. These effects lasted even after multiple rounds of cell divisions, indicating the presence of cellular "memory" that impacts cells' response to HipA-induced toxicity.

Evolution of glutamatergic signaling and synapses

Glutamate (Glu) is the primary excitatory transmitter in the mammalian brain. But, we know little about the evolutionary history of this adaptation, including the selection of l-glutamate as a signaling molecule in the first place. Here, we used comparative metabolomics and genomic data to reconstruct the genealogy of glutamatergic signaling. The origin of Glu-mediated communications might be traced to primordial nitrogen and carbon metabolic pathways. The versatile chemistry of L-Glu placed this molecule at the crossroad of cellular biochemistry as one of the most abundant metabolites. From there, innovations multiplied. Many stress factors or injuries could increase extracellular glutamate concentration, which led to the development of modular molecular systems for its rapid sensing in bacteria and archaea. More than 20 evolutionarily distinct families of ionotropic glutamate receptors (iGluRs) have been identified in eukaryotes. The domain compositions of iGluRs correlate with the origins of multicellularity in eukaryotes. Although L-Glu was recruited as a neuro-muscular transmitter in the early-branching metazoans, it was predominantly a non-neuronal messenger, with a possibility that glutamatergic synapses evolved more than once. Furthermore, the molecular secretory complexity of glutamatergic synapses in invertebrates (e.g., Aplysia) can exceed their vertebrate counterparts. Comparative genomics also revealed 15+ subfamilies of iGluRs across Metazoa. However, most of this ancestral diversity had been lost in the vertebrate lineage, preserving AMPA, Kainate, Delta, and NMDA receptors. The widespread expansion of glutamate synapses in the cortical areas might be associated with the enhanced metabolic demands of the complex brain and compartmentalization of Glu signaling within modular neuronal ensembles.

Bacterial motility: machinery and mechanisms

Bacteria have developed a large array of motility mechanisms to exploit available resources and environments. These mechanisms can be broadly classified into swimming in aqueous media and movement over solid surfaces. Swimming motility involves either the rotation of rigid helical filaments through the external medium or gyration of the cell body in response to the rotation of internal filaments. On surfaces, bacteria swarm collectively in a thin layer of fluid powered by the rotation of rigid helical filaments, they twitch by assembling and disassembling type IV pili, they glide by driving adhesins along tracks fixed to the cell surface and, finally, non-motile cells slide over surfaces in response to outward forces due to colony growth. Recent technological advances, especially in cryo-electron microscopy, have greatly improved our knowledge of the molecular machinery that powers the various forms of bacterial motility. In this Review, we describe the current understanding of the physical and molecular mechanisms that allow bacteria to move around.

Effects of internal dynamics on chemotactic aggregation of bacteria

The effects of internal adaptation dynamics on the self-organized aggregation of chemotactic bacteria are investigated by Monte Carlo (MC) simulations based on a two-stream kinetic transport equation coupled with a reaction-diffusion equation of the chemoattractant that bacteria produce. A remarkable finding is a nonmonotonic behavior of the peak aggregation density with respect to the adaptation time; more specifically, aggregation is the most enhanced when the adaptation time is comparable to or moderately larger than the mean run time of bacteria. Another curious observation is the formation of a trapezoidal aggregation profile occurring at a very large adaptation time, where the biased motion of individual cells is rather hindered at the plateau regimes due to the boundedness of the tumbling frequency modulation. Asymptotic analysis of the kinetic transport system is also carried out, and a novel asymptotic equation is obtained at the large adaptation-time regime while the Keller-Segel type equations are obtained when the adaptation time is moderate. Numerical comparison of the asymptotic equations with MC results clarifies that trapezoidal aggregation is well described by the novel asymptotic equation, and the nonmonotonic behavior of the peak aggregation density is interpreted as the transient of the asymptotic solutions between different adaptation time regimes.

Ligand sensing enhances bacterial flagellar motor output via stator recruitment

It is well known that flagellated bacteria, such as Escherichia coli, sense chemicals in their environment by a chemoreceptor and relay the signals via a well-characterized signaling pathway to the flagellar motor. It is widely accepted that the signals change the rotation bias of the motor without influencing the motor speed. Here, we present results to the contrary and show that the bacteria is also capable of modulating motor speed on merely sensing a ligand. Step changes in concentration of non-metabolizable ligand cause temporary recruitment of stator units leading to a momentary increase in motor speeds. For metabolizable ligand, the combined effect of sensing and metabolism leads to higher motor speeds for longer durations. Experiments performed with mutant strains delineate the role of metabolism and sensing in the modulation of motor speed and show how speed changes along with changes in bias can significantly enhance response to changes in its environment.

Direct Mapping from Intracellular Chemotaxis Signaling to Single-Cell Swimming Behavior

Bacterial chemotaxis allows bacteria to sense the chemical environment and modulate their swimming behavior accordingly. Although the intracellular chemotaxis signaling pathway has been studied extensively, experimental studies are still lacking that could provide direct link from the pathway output (the intracellular concentration of the phosphorylated form of the response regulator phosphorylated CheY (CheY-P)) to single-cell swimming behavior. Here, we measured the swimming behavior of individual Escherichia coli cells while simultaneously detecting the intracellular CheY-P concentration, thereby providing a direct relationship between the intracellular CheY-P concentration and the single-cell run-and-tumble behavior. The measured relationship is consistent with the ultrasensitivity of the motor switch and a "veto model" that describes the interaction among individual flagella, although contribution from the voting mechanism could not be ruled out.

Howard Berg's Random Walk through Biology

This minireview presents the career of biophysicist Howard Berg from his first interest in bacterial chemotaxis and motility through the present. After a summary of some of his early work, a series of reminiscences of students, postdocs, colleagues, and family members is presented. In sum, these recollections capture the effect that Howard's scientific life has had on the field of bacterial chemotaxis and motility and on the careers and lives of those who have interacted with him.

Aggregation Temperature of Escherichia coli Depends on Steepness of the Thermal Gradient

Bacterial chemotaxis, the directed migration of bacteria in a gradient of chemoattractant, is one of the most well-studied and well-understood processes in cell biology. On the other hand, bacterial thermotaxis, the directed migration of bacteria in a gradient of temperature, is understood relatively poorly, with somewhat conflicting reports by different groups. One of the reasons for that is the relative technical difficulty of the generation of well-defined gradients of temperature that are sufficiently steep to elicit readily detectable thermotaxis. Here, we used a specially designed microfluidic device to study thermotaxis of Escherichia coli in a broad range of thermal gradients with a high rate of data collection. We found that in shallow temperature gradients with narrow temperature ranges, E. coli tended to aggregate near a sidewall of the gradient channel at either the lowest or the highest temperature. On the other hand, in sufficiently steep gradients with wide temperature ranges, E. coli aggregated at intermediate temperatures, with maximal cell concentrations found away from the sidewalls. We observed this intermediate temperature aggregation in a motility buffer that did not contain any major chemoattractants of E. coli, in contradiction to some previous reports, which suggested that this type of aggregation required the presence of at least one major chemoattractant in the medium. Even more surprisingly, the aggregation temperature strongly depended on the gradient steepness, decreasing by ∼10° as the steepness was increased from 27 to 53°C/mm. Our experiments also highlight the fact that assessments of thermal gradients by changes in fluorescence of temperature-sensitive fluorescent dyes need to account for thermophoresis of the dyes.

Bioinspired reorientation strategies for application in micro/nanorobotic control

Engineers have recently been inspired by swimming methodologies of microorganisms in creating micro-/nanorobots for biomedical applications. Future medicine may be revolutionized by the application of these small machines in diagnosing, monitoring, and treating diseases. Studies over the past decade have often concentrated on propulsion generation. However, there are many other challenges to address before the practical use of robots at the micro-/nanoscale. The control and reorientation ability of such robots remain as some of these challenges. This paper reviews the strategies of swimming microorganisms for reorientation, including tumbling, reverse and flick, direction control of helical-path swimmers, by speed modulation, using complex flagella, and the help of mastigonemes. Then, inspired by direction change in microorganisms, methods for orientation control for microrobots and possible directions for future studies are discussed. Further, the effects of solid boundaries on the swimming trajectories of microorganisms and microrobots are examined. In addition to propulsion systems for artificial microswimmers, swimming microorganisms are promising sources of control methodologies at the micro-/nanoscale.

A model of strongly biased chemotaxis reveals the trade-offs of different bacterial migration strategies

Many bacteria actively bias their motility towards more favourable nutrient environments. In liquid, cells rotate their corkscrew-shaped flagella to swim, but in surface attached biofilms cells instead use grappling hook-like appendages called pili to pull themselves along. In both forms of motility, cells selectively alternate between relatively straight 'runs' and sharp reorientations to generate biased random walks up chemoattractant gradients. However, recent experiments suggest that swimming and biofilm cells employ fundamentally different strategies to generate chemotaxis: swimming cells typically suppress reorientations when moving up a chemoattractant gradient, whereas biofilm cells increase reorientations when moving down a chemoattractant gradient. The reason for this difference remains unknown. Here we develop a mathematical framework to understand how these different chemotactic strategies affect the distribution of cells at the population level. Current continuum models typically assume a weak bias in the reorientation rate and are not able to distinguish between these two strategies, so we derive a model for strong chemotaxis that resolves how both the drift and diffusive components depend on the underlying chemotactic strategy. We then test predictions from our continuum model against individual-based simulations and identify further refinements that allow our continuum model to resolve boundary effects. Our analyses reveal that the strategy employed by swimming cells yields a larger chemotactic drift, but the strategy used by biofilm cells allows them to more tightly aggregate where the chemoattractant is most abundant. This new modelling framework provides new quantitative insights into how the different chemical landscapes experienced by swimming and biofilm cells might select for divergent ways of generating chemotaxis.

Modelling bacterial chemotaxis for indirectly binding attractants

In bacterial chemotaxis, chemoattractant molecules may bind either directly or indirectly with receptors within the cell periplasmic space. The indirect binding mechanism, which involves an intermediate periplasmic binding protein, has been reported to increase sensitivity to dilute attractant concentrations as well as range of response. Current mathematical models for bacterial chemotaxis at the population scale do not appear to take the periplasmic binding protein (BP) concentration or the indirect binding mechanics into account. We formulate an indirect binding extension to the existing Rivero equation for chemotactic velocity based on fundamental reversible enzyme kinetics. The formulated indirect binding expression accounts for the periplasmic BP concentration and the dissociation constants for binding between attractant and periplasmic BP, as well as between BP and chemoreceptor. We validate the indirect-binding model using capillary assay simulations of the chemotactic responses of E. coli to the indirectly-binding attractants maltose and AI-2. The predicted response agrees well with experimental data from a number of maltose capillary assay studies conducted in previous literature. The model is also able to achieve good agreement with AI-2 capillary assay data of one study out of two tested. The chemotactic response of E. coli towards AI-2 appears to be of higher complexity due to reports of variable periplasmic BP concentration as well as the low concentration of periplasmic BP relative to the total receptor concentration. Our current model is thus suitable for indirect binding chemotactic response systems with constant periplasmic BP concentration that is significantly larger than the total receptor concentration, such as the response of E. coli towards maltose. Further considerations may be taken into account to model the chemotactic response towards AI-2 with greater accuracy.

Chemotaxis in external fields: Simulations for active magnetic biological matter

The movement of microswimmers is often described by active Brownian particle models. Here we introduce a variant of these models with several internal states of the swimmer to describe stochastic strategies for directional swimming such as run and tumble or run and reverse that are used by microorganisms for chemotaxis. The model includes a mechanism to generate a directional bias for chemotaxis and interactions with external fields (e.g., gravity, magnetic field, fluid flow) that impose forces or torques on the swimmer. We show how this modified model can be applied to various scenarios: First, the run and tumble motion of E. coli is used to establish a paradigm for chemotaxis and investigate how it is affected by external forces. Then, we study magneto-aerotaxis in magnetotactic bacteria, which is biased not only by an oxygen gradient towards a preferred concentration, but also by magnetic fields, which exert a torque on an intracellular chain of magnets. We study the competition of magnetic alignment with active reorientation and show that the magnetic orientation can improve chemotaxis and thereby provide an advantage to the bacteria, even at rather large inclination angles of the magnetic field relative to the oxygen gradient, a case reminiscent of what is expected for the bacteria at or close to the equator. The highest gain in chemotactic velocity is obtained for run and tumble with a magnetic field parallel to the gradient, but in general a mechanism for reverse motion is necessary to swim against the magnetic field and a run and reverse strategy is more advantageous in the presence of a magnetic torque. This finding is consistent with observations that the dominant mode of directional changes in magnetotactic bacteria is reversal rather than tumbles. Moreover, it provides guidance for the design of future magnetic biohybrid swimmers.

In this paper, we propose a modified Active Brownian particle model to describe bacterial swimming behavior under the influence of external forces and torques, in particular of a magnetic torque. This type of interaction is particularly important for magnetic biohybrids (i.e. motile bacteria coupled to a synthetic magnetic component) and for magnetotactic bacteria (i.e. bacteria with a natural intracellular magnetic chain), which perform chemotaxis to swim along chemical gradients, but are also directed by an external magnetic field. The model allows us to investigate the benefits and disadvantages of such coupling between two different directionality mechanisms. In particular we show that the magnetic torque can speed chemotaxis up in some conditions, while it can hinder it in other cases. In addition to an understanding of the swimming strategies of naturally magnetotactic organisms, the results may guide the design of future biomedical devices.

Modeling Barrier Properties of Intestinal Mucus Reinforced with IgG and Secretory IgA against Motile Bacteria

The gastrointestinal (GI) tract is lined with a layer of viscoelastic mucus gel, characterized by a dense network of entangled and cross-linked mucins together with an abundance of antibodies (Ab). Secretory IgA (sIgA), the predominant Ab isotype in the GI tract, is a dimeric molecule with 4 antigen-binding domains capable of inducing efficient clumping of bacteria, or agglutination. IgG, another common Ab at mucosal surfaces, can cross-link individual viruses to the mucin mesh through multiple weak bonds between IgG-Fc and mucins, a process termed muco-trapping. Relative contributions by agglutination versus muco-trapping in blocking permeation of motile bacteria through mucus remain poorly understood. Here, we developed a mathematical model that takes into account physiologically relevant spatial dimensions and time scales, binding and unbinding rates between Ab and bacteria as well as between Ab and mucins, the diffusivities of Ab, and run-tumble motion of active bacteria. Our model predicts both sIgA and IgG can accumulate on the surface of individual bacteria at sufficient quantities and rates to enable trapping individual bacteria in mucins before they penetrate the mucus layer. Furthermore, our model predicts that agglutination only modestly improves the ability for antibodies to block bacteria permeation through mucus. These results suggest that while sIgA is the most potent Ab isotype overall at stopping bacterial penetration, IgG may represent a practical alternative for mucosal prophylaxis and therapy. Our work improves the mechanistic understanding of Ab-enhanced barrier properties of mucus and highlights the ability for muco-trapping Ab to protect against motile pathogens at mucosal surfaces.

Bacteria push the limits of chemotactic precision to navigate dynamic chemical gradients

Ephemeral aggregations of bacteria are ubiquitous in the environment, where they serve as hotbeds of metabolic activity, nutrient cycling, and horizontal gene transfer. In many cases, these regions of high bacterial concentration are thought to form when motile cells use chemotaxis to navigate to chemical hotspots. However, what governs the dynamics of bacterial aggregations is unclear. Here, we use an experimental platform to create realistic submillimeter-scale nutrient pulses with controlled nutrient concentrations. By combining experiments, mathematical theory, and agent-based simulations, we show that individual Vibrio ordalii bacteria begin chemotaxis toward hotspots of dissolved organic matter (DOM) when the magnitude of the chemical gradient rises sufficiently far above the sensory noise that is generated by stochastic encounters with chemoattractant molecules. Each DOM hotspot is surrounded by a dynamic ring of chemotaxing cells, which congregate in regions of high DOM concentration before dispersing as DOM diffuses and gradients become too noisy for cells to respond to. We demonstrate that V. ordalii operates close to the theoretical limits on chemotactic precision. Numerical simulations of chemotactic bacteria, in which molecule counting noise is explicitly taken into account, point at a tradeoff between nutrient acquisition and the cost of chemotactic precision. More generally, our results illustrate how limits on sensory precision can be used to understand the location, spatial extent, and lifespan of bacterial behavioral responses in ecologically relevant environments.

Elementary sensory-motor transformations underlying olfactory navigation in walking fruit-flies

Odor attraction in walking Drosophila melanogaster is commonly used to relate neural function to behavior, but the algorithms underlying attraction are unclear. Here, we develop a high-throughput assay to measure olfactory behavior in response to well-controlled sensory stimuli. We show that odor evokes two behaviors: an upwind run during odor (ON response), and a local search at odor offset (OFF response). Wind orientation requires antennal mechanoreceptors, but search is driven solely by odor. Using dynamic odor stimuli, we measure the dependence of these two behaviors on odor intensity and history. Based on these data, we develop a navigation model that recapitulates the behavior of flies in our apparatus, and generates realistic trajectories when run in a turbulent boundary layer plume. The ability to parse olfactory navigation into quantifiable elementary sensori-motor transformations provides a foundation for dissecting neural circuits that govern olfactory behavior.

Combined influence of hydrodynamics and chemotaxis in the distribution of microorganisms around spherical nutrient sources

We study how the interaction between hydrodynamics and chemotaxis affects the colonization of nutrient sources by microorganisms. We use an individual-based model and perform probabilistic simulations to ascertain the impact of important environmental and motility characteristics on the spatial distribution of microorganisms around a spherical nutrient source. In general, we unveil four distinct regimes based on the distribution of the microorganisms: (i) strong surface colonization, (ii) rotary-diffusion-induced "off-surface" accumulation, (iii) a depletion zone in the spatial distribution, and (iv) no appreciable aggregation, with their occurrence being contingent on the relative strengths of hydrodynamic and chemotactic effects. More specifically, we show that the extent of surface colonization first increases, then reaches a plateau, and finally decreases as the nutrient availability is increased. We also show that surface colonization reduces monotonically as the mean run length of the chemotactic microorganisms increases. Our study provides insight into the interplay of two important mechanisms governing microorganism behavior near nutrient sources, isolates each of their effects, and thus offers greater predictability of this nontrivial phenomenon.

Statistical signatures of a targeted search by bacteria

Chemoattractant gradients are rarely well-controlled in nature and recent attention has turned to bacterial chemotaxis toward typical bacterial food sources such as food patches or even bacterial prey. In environments with localized food sources reminiscent of a bacterium's natural habitat, striking phenomena-such as the volcano effect or banding-have been predicted or expected to emerge from chemotactic models. However, in practice, from limited bacterial trajectory data it is difficult to distinguish targeted searches from an untargeted search strategy for food sources. Here we use a theoretical model to identify statistical signatures of a targeted search toward point food sources, such as prey. Our model is constructed on the basis that bacteria use temporal comparisons to bias their random walk, exhibit finite memory and are subject to random (Brownian) motion as well as signaling noise. The advantage with using a stochastic model-based approach is that a stochastic model may be parametrized from individual stochastic bacterial trajectories but may then be used to generate a very large number of simulated trajectories to explore average behaviors obtained from stochastic search strategies. For example, our model predicts that a bacterium's diffusion coefficient increases as it approaches the point source and that, in the presence of multiple sources, bacteria may take substantially longer to locate their first source giving the impression of an untargeted search strategy.

Modeling of active swimmer suspensions and their interactions with the environment

In this article, we review mathematical models used to study the behaviour of suspensions of micro-swimmers and the accompanying biophysical phenomena, with specific focus on stimulus response. The methods discussed encompass a range of interactions exhibited by the micro-swimmers; including passive hydrodynamic (gyrotaxis) and gravitational (gravitaxis) effects, and active responses to chemical cues (chemotaxis) and light intensities (phototaxis). We introduce the simplest models first, and then build towards more sophisticated recent developments, in the process, identifying the limitations of the former and the new results obtained by the latter. We comment on the accuracy/validity of the models adopted, based on the agreement between theoretical results and experimental observations. We conclude by identifying some of the open problems and associated challenges faced by researchers in the realm of active suspensions.

Mechanism of bidirectional thermotaxis in Escherichia coli

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.

Many bacteria can move towards or away from chemicals, heat and other stimuli in their environment. The ability of bacteria to move in response to nutrients and other chemicals, known as chemotaxis, is the best understood of these phenomena. Bacteria generally swim in a fairly random way and frequently change direction. During chemotaxis, however, the bacteria sense changes in the concentrations of a chemical in their surroundings and this biases the direction in which they swim so that they spend more time swimming towards or away from the source of the chemical. The bacteria have various receptor proteins that can detect different chemicals. For example, the Tar and Tsr receptors can recognize chemicals called aspartate and serine, respectively, which are – amongst other things – nutrients that are used to build proteins.

Tar and Tsr are also involved in the response to temperature, referred to as thermotaxis. At low temperatures, a bacterium Escherichia coli will move towards sources of heat. Yet when the bacteria detect both serine and aspartate they may reverse the response and move towards colder areas instead. However, it was not clear why the bacteria do this, and what roles Tar and Tsr play in this response.

Paulick et al. have now combined approaches that directly visualise signalling inside living bacteria and that track the movements of individual bacterial cellswith mathematical modelling to investigate thermotaxis in E. coli. The experiments show that the bacteria’s behaviour could be explained by interplay between the responses mediated by Tar and Tsr. In the absence of both serine and aspartate, both receptors stimulate heat-seeking responses, causing the bacteria to move towards hotter areas. When only aspartate is present, Tsr continues to stimulate the heat-seeking response, but the aspartate causes Tar to switch to promoting a cold-seeking response instead. This leads to the bacteria accumulating in areas of intermediate temperature. In the presence of serine only, the bacteria behave in a similar way because the receptors swap roles so that Tsr stimulates the cold-seeking response, while Tar promotes the heat-seeking one.

The intermediate temperature at which the bacteria accumulate in response to serine is also around the optimal temperature for E.coli growth in presence of this chemical, suggesting that thermotaxis might play an important role in allowing bacteria to survive and grow in many different environments, including in the human body. Thus, understanding how chemotaxis and thermotaxis are regulated may lead to new ways to control how bacteria behave in patients and natural environments.

Morphologies of Bacillus subtilis communities responding to environmental variation

Bacterial communities exhibit a variety of growth morphologies in constructing robust systems under different environmental conditions. We review the diverse morphologies of Bacillus subtilis communities and their mechanisms of self-organization. B. subtilis uses different cell types to suit environmental conditions and cell density. The subpopulation of each cell type exhibits various environment-sensitive properties. Furthermore, division of labor among the subpopulations results in flexible development for the community as a whole. We review how B. subtilis community morphologies and growth strategies respond to environmental perturbations.

Environment determines evolutionary trajectory in a constrained phenotypic space

Constraints on phenotypic variation limit the capacity of organisms to adapt to the multiple selection pressures encountered in natural environments. To better understand evolutionary dynamics in this context, we select Escherichia coli for faster migration through a porous environment, a process which depends on both motility and growth. We find that a trade-off between swimming speed and growth rate constrains the evolution of faster migration. Evolving faster migration in rich medium results in slow growth and fast swimming, while evolution in minimal medium results in fast growth and slow swimming. In each condition parallel genomic evolution drives adaptation through different mutations. We show that the trade-off is mediated by antagonistic pleiotropy through mutations that affect negative regulation. A model of the evolutionary process shows that the genetic capacity of an organism to vary traits can qualitatively depend on its environment, which in turn alters its evolutionary trajectory.

DOI:http://dx.doi.org/10.7554/eLife.24669.001

In nature organisms face many challenges, and species adapt to their environment by changing heritable traits over the course of many generations. How organisms adapt is often limited by trade-offs, in which improving one trait can only come at the expense of another.

In the laboratory, scientists use well-controlled environments to study how populations adapt to specific challenges without interference from their natural habitat. Most experiments, however, only look at simple challenges and do not take into account that organisms in the wild face many pressures at the same time. Fraebel et al. wanted to know what happens when an organism’s performance depends on two traits that are restricted by a trade-off. The experiments used populations of the bacterium Escherichia coli, which can go through hundreds of generations in a week, providing ample opportunity to study mutations and their impact on heritable traits.

Through a combination of mathematical modeling and experiments, Fraebel et al. found that the environment is crucial for determining how bacteria adapt when their swimming speed and population growth rate are restricted by a trade-off. When nutrients are plentiful, E. coli populations evolve to spread faster by swimming more quickly despite growing more slowly. Yet, if nutrients are scarcer, the bacteria evolve to spread faster by growing more quickly despite swimming more slowly. In each scenario, the experiments identified single mutations that changed both swimming speed and growth rate by modifying regulatory activity in the cell.

A better understanding of how an organism’s genetic architecture, its environment and trade-offs are connected may help identify the traits that are most easily changed by mutations. The ultimate goal would be to be able to predict evolutionary responses to complex selection pressures.

DOI:http://dx.doi.org/10.7554/eLife.24669.002

Self-organization of bacterial communities against environmental pH variation: Controlled chemotactic motility arranges cell population structures in biofilms

As with many living organisms, bacteria often live on the surface of solids, such as foods, organisms, buildings and soil. Compared with dispersive behavior in liquid, bacteria on surface environment exhibit significantly restricted mobility. They have access to only limited resources and cannot be liberated from the changing environment. Accordingly, appropriate collective strategies are necessarily required for long-term growth and survival. However, in spite of our deepening knowledge of the structure and characteristics of individual cells, strategic self-organizing dynamics of their community is poorly understood and therefore not yet predictable. Here, we report a morphological change in Bacillus subtilis biofilms due to environmental pH variations, and present a mathematical model for the macroscopic spatio-temporal dynamics. We show that an environmental pH shift transforms colony morphology on hard agar media from notched 'volcano-like' to round and front-elevated 'crater-like'. We discover that a pH-dependent dose-response relationship between nutritional resource level and quantitative bacterial motility at the population level plays a central role in the mechanism of the spatio-temporal cell population structure design in biofilms.

The Flux of Euglena gracilis Cells Depends on the Gradient of Light Intensity

We have quantified the photomovement behavior of a suspension of Euglena gracilis representing a behavioral response to a light gradient. Despite recent measurements of phototaxis and photophobicity, the details of macroscopic behavior of cell photomovements under conditions of light intensity gradients, which are critical to understand recent experiments on spatially localized bioconvection patterns, have not been fully understood. In this paper, the flux of cell number density under a light intensity gradient was measured by the following two experiments. In the first experiment, a capillary containing the cell suspension was illuminated with different light intensities in two regions. In the steady state, the differences of the cell numbers in the two regions normalized by the total number were proportional to the light difference, where the light intensity difference ranged from 0.5-2.0 μmol m-2 s-1. The proportional coefficient was positive (i.e., the bright region contained many microorganisms) when the mean light intensity was weak (1.25 μmol m-2 s-1), whereas it was negative when the mean intensity was strong (13.75 μmol m-2 s-1). In the second experiment, a shallow rectangular container of the suspension was illuminated with stepwise light intensities. The cell number density distribution exhibited a single peak at the position where the light intensity was about Ic ≃ 3.8 μmol m-2 s-1. These results suggest that the suspension of E. gracilis responded to the light gradient and that the favorable light intensity was Ic.

Physical limits on bacterial navigation in dynamic environments

Many chemotactic bacteria inhabit environments in which chemicals appear as localized pulses and evolve by processes such as diffusion and mixing. We show that, in such environments, physical limits on the accuracy of temporal gradient sensing govern when and where bacteria can accurately measure the cues they use to navigate. Chemical pulses are surrounded by a predictable dynamic region, outside which bacterial cells cannot resolve gradients above noise. The outer boundary of this region initially expands in proportion to the square root of time before rapidly contracting. Our analysis also reveals how chemokinesis-the increase in swimming speed many bacteria exhibit when absolute chemical concentration exceeds a threshold-may serve to enhance chemotactic accuracy and sensitivity when the chemical landscape is dynamic. More generally, our framework provides a rigorous method for partitioning bacteria into populations that are 'near' and 'far' from chemical hotspots in complex, rapidly evolving environments such as those that dominate aquatic ecosystems.

Chemotaxis of bio-hybrid multiple bacteria-driven microswimmers

In this study, in a bio-hybrid microswimmer system driven by multiple Serratia marcescens bacteria, we quantify the chemotactic drift of a large number of microswimmers towards L-serine and elucidate the associated collective chemotaxis behavior by statistical analysis of over a thousand swimming trajectories of the microswimmers. The results show that the microswimmers have a strong heading preference for moving up the L-serine gradient, while their speed does not change considerably when moving up and down the gradient; therefore, the heading bias constitutes the major factor that produces the chemotactic drift. The heading direction of a microswimmer is found to be significantly more persistent when it moves up the L-serine gradient than when it travels down the gradient; this effect causes the apparent heading preference of the microswimmers and is the crucial reason that enables the seemingly cooperative chemotaxis of multiple bacteria on a microswimmer. In addition, we find that their chemotactic drift velocity increases superquadratically with their mean swimming speed, suggesting that chemotaxis of bio-hybrid microsystems can be enhanced by designing and building faster microswimmers. Such bio-hybrid microswimmers with chemotactic steering capability may find future applications in targeted drug delivery, bioengineering, and lab-on-a-chip devices.

Natural search algorithms as a bridge between organisms, evolution, and ecology

The ability to navigate is a hallmark of living systems, from single cells to higher animals. Searching for targets, such as food or mates in particular, is one of the fundamental navigational tasks many organisms must execute to survive and reproduce. Here, we argue that a recent surge of studies of the proximate mechanisms that underlie search behavior offers a new opportunity to integrate the biophysics and neuroscience of sensory systems with ecological and evolutionary processes, closing a feedback loop that promises exciting new avenues of scientific exploration at the frontier of systems biology.

Singly Flagellated Pseudomonas aeruginosa Chemotaxes Efficiently by Unbiased Motor Regulation

Pseudomonas aeruginosa is an opportunistic human pathogen that has long been known to chemotax. More recently, it has been established that chemotaxis is an important factor in the ability of P. aeruginosa to make biofilms. Genes that allow P. aeruginosa to chemotax are homologous with genes in the paradigmatic model organism for chemotaxis, Escherichia coli. However, P. aeruginosa is singly flagellated and E. coli has multiple flagella. Therefore, the regulation of counterclockwise/clockwise flagellar motor bias that allows E. coli to efficiently chemotax by runs and tumbles would lead to inefficient chemotaxis by P. aeruginosa, as half of a randomly oriented population would respond to a chemoattractant gradient in the wrong sense. How P. aeruginosa regulates flagellar rotation to achieve chemotaxis is not known. Here, we analyze the swimming trajectories of single cells in microfluidic channels and the rotations of cells tethered by their flagella to the surface of a variable-environment flow cell. We show that P. aeruginosa chemotaxes by symmetrically increasing the durations of both counterclockwise and clockwise flagellar rotations when swimming up the chemoattractant gradient and symmetrically decreasing rotation durations when swimming down the chemoattractant gradient. Unlike the case for E. coli, the counterclockwise/clockwise bias stays constant for P. aeruginosa. We describe P. aeruginosa’s chemotaxis using an analytical model for symmetric motor regulation. We use this model to do simulations that show that, given P. aeruginosa’s physiological constraints on motility, its distinct, symmetric regulation of motor switching optimizes chemotaxis.

Chemotaxis has long been known to strongly affect biofilm formation by the opportunistic human pathogen P. aeruginosa, whose essential chemotaxis genes have homologues in E. coli, which achieves chemotaxis by biasing the relative probability of counterclockwise and clockwise flagellar rotation. However, the physiological difference between multiflagellated E. coli and singly flagellated P. aeruginosa implies that biased motor regulation should prevent P. aeruginosa populations from chemotaxing efficiently. Here, we used experiments, analytical modeling, and simulations to demonstrate that P. aeruginosa uses unbiased, symmetric regulation of the flagellar motor to maximize its chemotaxis efficiency. This mode of chemotaxis was not previously known and demonstrates a new variant of a paradigmatic signaling system in an important human pathogen.

A Diffusion Approximation Based on Renewal Processes with Applications to Strongly Biased Run-Tumble Motion

We consider organisms which use a renewal strategy such as run-tumble when moving in space, for example to perform chemotaxis in chemical gradients. We derive a diffusion approximation for the motion, applying a central limit theorem due to Anscombe for renewal-reward processes; this theorem has not previously been applied in this context. Our results extend previous work, which has established the mean drift but not the diffusivity. For a classical model of tumble rates applied to chemotaxis, we find that the resulting chemotactic drift saturates to the swimming velocity of the organism when the chemical gradients grow increasingly steep. The dispersal becomes anisotropic in steep gradients, with larger dispersal across the gradient than along the gradient. In contrast to one-dimensional settings, strong bias increases dispersal. We next include Brownian rotation in the model and find that, in limit of high chemotactic sensitivity, the chemotactic drift is 64% of the swimming velocity, independent of the magnitude of the Brownian rotation. We finally derive characteristic timescales of the motion that can be used to assess whether the diffusion limit is justified in a given situation. The proposed technique for obtaining diffusion approximations is conceptually and computationally simple, and applicable also when statistics of the motion is obtained empirically or through Monte Carlo simulation of the motion.

Strategies to Block Bacterial Pathogenesis by Interference with Motility and Chemotaxis

Infections by motile, pathogenic bacteria, such as Campylobacter species, Clostridium species, Escherichia coli, Helicobacter pylori, Listeria monocytogenes, Neisseria gonorrhoeae, Pseudomonas aeruginosa, Salmonella species, Vibrio cholerae, and Yersinia species, represent a severe economic and health problem worldwide. Of special importance in this context is the increasing emergence and spread of multidrug-resistant bacteria. Due to the shortage of effective antibiotics for the treatment of infections caused by multidrug-resistant, pathogenic bacteria, the targeting of novel, virulence-relevant factors constitutes a promising, alternative approach. Bacteria have evolved distinct motility structures for movement across surfaces and in aqueous environments. In this review, I will focus on the bacterial flagellum, the associated chemosensory system, and the type-IV pilus as motility devices, which are crucial for bacterial pathogens to reach a preferred site of infection, facilitate biofilm formation, and adhere to surfaces or host cells. Thus, those nanomachines constitute potential targets for the development of novel anti-infectives that are urgently needed at a time of spreading antibiotic resistance. Both bacterial flagella and type-IV pili (T4P) are intricate macromolecular complexes made of dozens of different proteins and their motility function relies on the correct spatial and temporal assembly of various substructures. Specific type-III and type-IV secretion systems power the export of substrate proteins of the bacterial flagellum and type-IV pilus, respectively, and are homologous to virulence-associated type-III and type-II secretion systems. Accordingly, bacterial flagella and T4P represent attractive targets for novel antivirulence drugs interfering with synthesis, assembly, and function of these motility structures.

Inferring Models of Bacterial Dynamics toward Point Sources

Experiments have shown that bacteria can be sensitive to small variations in chemoattractant (CA) concentrations. Motivated by these findings, our focus here is on a regime rarely studied in experiments: bacteria tracking point CA sources (such as food patches or even prey). In tracking point sources, the CA detected by bacteria may show very large spatiotemporal fluctuations which vary with distance from the source. We present a general statistical model to describe how bacteria locate point sources of food on the basis of stochastic event detection, rather than CA gradient information. We show how all model parameters can be directly inferred from single cell tracking data even in the limit of high detection noise. Once parameterized, our model recapitulates bacterial behavior around point sources such as the “volcano effect”. In addition, while the search by bacteria for point sources such as prey may appear random, our model identifies key statistical signatures of a targeted search for a point source given any arbitrary source configuration.

Response thresholds in bacterial chemotaxis

Stimulation of Escherichia coli by exponential ramps of chemoattractants generates step changes in the concentration of the response regulator, CheY-P. Because flagellar motors are ultrasensitive, this should change the fraction of time that motors spin clockwise, the CWbias. However, early work failed to show changes in CWbias when ramps were shallow. This was explained by a model for motor remodeling that predicted plateaus in plots of CWbias versus [CheY-P]. We looked for these plateaus by examining distributions of CWbias in populations of cells with different mean [CheY-P]. We did not find such plateaus. Hence, we repeated the work on shallow ramps and found that motors did indeed respond. These responses were quantitatively described by combining motor remodeling with ultrasensitivity in a model that exhibited high sensitivities over a wide dynamic range.

A Delicate Nanoscale Motor Made by Nature-The Bacterial Flagellar Motor

The bacterial flagellar motor (BFM) is a molecular complex ca. 45 nm in diameter that rotates the propeller that makes nearly all bacteria swim. The motor self-assembles out of ca. 20 different proteins and can not only rotate at up to 50 000 rpm, but can also switch rotational direction in milliseconds and navigate its environment to maneuver, on average, towards regions of greater benefit. The BFM is a pinnacle of evolution that informs and inspires the design of novel nanotechnology in the new era of synthetic biology.

pH-Taxis of Biohybrid Microsystems

The last decade has seen an increasing number of studies developing bacteria and other cell-integrated biohybrid microsystems. However, the highly stochastic motion of these microsystems severely limits their potential use. Here, we present a method that exploits the pH sensing of flagellated bacteria to realize robust drift control of multi-bacteria propelled microrobots. Under three specifically configured pH gradients, we demonstrate that the microrobots exhibit both unidirectional and bidirectional pH-tactic behaviors, which are also observed in free-swimming bacteria. From trajectory analysis, we find that the swimming direction and speed biases are two major factors that contribute to their tactic drift motion. The motion analysis of microrobots also sheds light on the propulsion dynamics of the flagellated bacteria as bioactuators. It is expected that similar driving mechanisms are shared among pH-taxis, chemotaxis, and thermotaxis. By identifying the mechanism that drives the tactic behavior of bacteria-propelled microsystems, this study opens up an avenue towards improving the control of biohybrid microsystems. Furthermore, assuming that it is possible to tune the preferred pH of bioactuators by genetic engineering, these biohybrid microsystems could potentially be applied to sense the pH gradient induced by cancerous cells in stagnant fluids inside human body and realize targeted drug delivery.

Modeling oscillations and spiral waves in Dictyostelium populations

Unicellular organisms exhibit elaborate collective behaviors in response to environmental cues. These behaviors are controlled by complex biochemical networks within individual cells and coordinated through cell-to-cell communication. Describing these behaviors requires new mathematical models that can bridge scales-from biochemical networks within individual cells to spatially structured cellular populations. Here we present a family of "multiscale" models for the emergence of spiral waves in the social amoeba Dictyostelium discoideum. Our models exploit new experimental advances that allow for the direct measurement and manipulation of the small signaling molecule cyclic adenosine monophosphate (cAMP) used by Dictyostelium cells to coordinate behavior in cellular populations. Inspired by recent experiments, we model the Dictyostelium signaling network as an excitable system coupled to various preprocessing modules. We use this family of models to study spatially unstructured populations of "fixed" cells by constructing phase diagrams that relate the properties of population-level oscillations to parameters in the underlying biochemical network. We then briefly discuss an extension of our model that includes spatial structure and show how this naturally gives rise to spiral waves. Our models exhibit a wide range of novel phenomena. including a density-dependent frequency change, bistability, and dynamic death due to slow cAMP dynamics. Our modeling approach provides a powerful tool for bridging scales in modeling of Dictyostelium populations.

The cognitive cell: bacterial behavior reconsidered

Research on how bacteria adapt to changing environments underlies the contemporary biological understanding of signal transduction (ST), and ST provides the foundation of the information-processing approach that is the hallmark of the ‘cognitive revolution,’ which began in the mid-20th century. Yet cognitive scientists largely remain oblivious to research into microbial behavior that might provide insights into problems in their own domains, while microbiologists seem equally unaware of the potential importance of their work to understanding cognitive capacities in multicellular organisms, including vertebrates. Evidence in bacteria for capacities encompassed by the concept of cognition is reviewed. Parallels exist not only at the heuristic level of functional analogue, but also at the level of molecular mechanism, evolution and ecology, which is where fruitful cross-fertilization among disciplines might be found.

Maximally informative foraging by Caenorhabditis elegans

Animals have evolved intricate search strategies to find new sources of food. Here, we analyze a complex food seeking behavior in the nematode Caenorhabditis elegans (C. elegans) to derive a general theory describing different searches. We show that C. elegans, like many other animals, uses a multi-stage search for food, where they initially explore a small area intensively ('local search') before switching to explore a much larger area ('global search'). We demonstrate that these search strategies as well as the transition between them can be quantitatively explained by a maximally informative search strategy, where the searcher seeks to continuously maximize information about the target. Although performing maximally informative search is computationally demanding, we show that a drift-diffusion model can approximate it successfully with just three neurons. Our study reveals how the maximally informative search strategy can be implemented and adopted to different search conditions.

Analytical modeling and experimental characterization of chemotaxis in Serratia marcescens

This paper presents a modeling and experimental framework to characterize the chemotaxis of Serratia marcescens (S. marcescens) relying on two-dimensional and three-dimensional tracking of individual bacteria. Previous studies mainly characterized bacterial chemotaxis based on population density analysis. Instead, this study focuses on single-cell tracking and measuring the chemotactic drift velocity V(C) from the biased tumble rate of individual bacteria on exposure to a concentration gradient of l-aspartate. The chemotactic response of S. marcescens is quantified over a range of concentration gradients (10^{-3} to 5 mM/mm) and average concentrations (0.5 × 10(-3) to 2.5 mM). Through the analysis of a large number of bacterial swimming trajectories, the tumble rate is found to have a significant bias with respect to the swimming direction. We also verify the relative gradient sensing mechanism in the chemotaxis of S. marcescens by measuring the change of V(C) with the average concentration and the gradient. The applied full pathway model with fitted parameters matches the experimental data. Finally, we show that our measurements based on individual bacteria lead to the determination of the motility coefficient μ (7.25 × 10(-6) cm(2)/s) of a population. The experimental characterization and simulation results for the chemotaxis of this bacterial species contribute towards using S. marcescens in chemically controlled biohybrid systems.

A bacterial pathogen uses dimethylsulfoniopropionate as a cue to target heat-stressed corals

Diseases are an emerging threat to ocean ecosystems. Coral reefs, in particular, are experiencing a worldwide decline because of disease and bleaching, which have been exacerbated by rising seawater temperatures. Yet, the ecological mechanisms behind most coral diseases remain unidentified. Here, we demonstrate that a coral pathogen, Vibrio coralliilyticus, uses chemotaxis and chemokinesis to target the mucus of its coral host, Pocillopora damicornis. A primary driver of this response is the host metabolite dimethylsulfoniopropionate (DMSP), a key element in the global sulfur cycle and a potent foraging cue throughout the marine food web. Coral mucus is rich in DMSP, and we found that DMSP alone elicits chemotactic responses of comparable intensity to whole mucus. Furthermore, in heat-stressed coral fragments, DMSP concentrations increased fivefold and the pathogen's chemotactic response was correspondingly enhanced. Intriguingly, despite being a rich source of carbon and sulfur, DMSP is not metabolized by the pathogen, suggesting that it is used purely as an infochemical for host location. These results reveal a new role for DMSP in coral disease, demonstrate the importance of chemical signaling and swimming behavior in the recruitment of pathogens to corals and highlight the impact of increased seawater temperatures on disease pathways.