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Keywords:

  • Chemotaxis;
  • Motility;
  • Energy taxis;
  • Environment;
  • Adaptation

Abstract

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Taxis on a macro scale: microbial habitats
  5. 3Taxis on a micro scale: molecular mechanisms
  6. 4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors
  7. 5Energy taxis is widespread in microbial world
  8. 6Lessons from genomics: what to expect
  9. 7Concluding remarks
  10. Acknowledgements
  11. References

Motile microorganisms rapidly respond to changes in various physico-chemical gradients by directing their motility to more favorable surroundings. Energy generation is one of the most important parameters for the survival of microorganisms in their environment. Therefore it is not surprising that microorganisms are able to monitor changes in the cellular energy generating processes. The signal for this behavioral response, which is called energy taxis, originates within the electron transport system. By coupling energy metabolism and behavior, energy taxis is fine-tuned to the environment a cell finds itself in and allows efficient adaptation to changing conditions that affect cellular energy levels. Thus, energy taxis provides cells with a versatile sensory system that enables them to navigate to niches where energy generation is optimized. This behavior is likely to govern vertical species stratification and the active migration of motile cells in response to shifting gradients of electron donors and/or acceptors which are observed within microbial mats, sediments and soil pores. Energy taxis has been characterized in several species and might be widespread in the microbial world. Genome sequencing revealed that many microorganisms from aquatic and soil environments possess large numbers of chemoreceptors and are likely to be capable of energy taxis. In contrast, species that have a fewer number of chemoreceptors are often found in specific, confined environments, where relatively constant environmental conditions are expected. Future studies focusing on characterizing behavioral responses in species that are adapted to diverse environmental conditions should unravel the molecular mechanisms underlying sensory behavior in general and energy taxis in particular. Such knowledge is critical to a better understanding of the ecological role of energy taxis.


1Introduction

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Taxis on a macro scale: microbial habitats
  5. 3Taxis on a micro scale: molecular mechanisms
  6. 4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors
  7. 5Energy taxis is widespread in microbial world
  8. 6Lessons from genomics: what to expect
  9. 7Concluding remarks
  10. Acknowledgements
  11. References

The ability of motile bacteria to navigate in gradients of various physicochemical parameters is termed taxis. Motile cells are able to respond to environmental cues and alter their movement to navigate to the most favorable niches for growth and survival. Many environmental cues can trigger a tactic response in motile bacteria; these include chemicals (chemotaxis), light (phototaxis), oxygen (aerotaxis), pH (pH taxis), reduction potential (redox taxis), temperature (thermotaxis), osmolarity (osmotaxis), magnetic field (magnetotaxis), etc. [1]. In aquatic and terrestrial environments, microorganisms constantly experience changes in various gradients and the significance of motile sensory behavior for the ecology of microbial cells is reflected by the fact that most microorganisms in these environments are motile [2]. In contrast, many microorganisms that occupy specific habitats where environmental changes are limited (for example, inside eukaryotic hosts) are non-motile. By actively moving toward or away from a stimulus, cells can rapidly adapt to changes in their environment. Microbial taxis is dependent on the presence of the cellular sensory machinery that transmits information from the environment to the motility apparatus. The processing time in bacterial taxis is incredibly fast. A change in the direction of flagellar rotation resulting in the change of swimming direction occurs in less than a second upon binding of a chemical stimulus to the receptor on the cell surface [3], which is considerably faster than the time frame required for initiation of gene expression. Thus, taxis can be considered as an immediate survival strategy.

In a given environment, the availability of nutrients and other chemicals (electron acceptors, etc.) influences the metabolic activities of microorganisms and affects the function and distribution of microbial populations. To survive and thrive in their environment, microbial cells need to navigate in chemical gradients in order to find a position where their metabolism is optimal. Therefore, chemosensory behavior of motile bacteria may contribute to the overall structure of the microbial community in environments where chemical gradients are present, such as soil pores, rhizosphere, microbial mats and sediments.

Continuous energy generation is one of the most important conditions for the survival of microorganisms in their environment. Therefore, it is not surprising to find that microorganisms have evolved mechanisms that allow them to monitor not only the microenvironment outside the cell, but also their own intracellular energy status. The ability of microorganisms to respond to changes in their energy generating processes and, as a result, to navigate to niches that support maximum energy levels is called energy taxis [4–6]. This behavior is in contrast to “classical” chemotaxis where binding of a chemical to the periplasmic domain of a chemoreceptor is the signal for a behavioral response [7]. Energy taxis was described in species that use respiratory (both aerobic and anaerobic) and photosynthetic electron transport as the primary energy generating mechanism. Any environmental factor that affects processes within the electron transport system can act as a sensory stimulus in energy taxis. Many environmental cues encountered by microorganisms in their habitats affect their intracellular energy generating processes and therefore can be detected via the energy taxis mechanism. Therefore, this behavior is likely to govern vertical species stratification as well as the active migration of motile cells in response to shifting gradients of electron donors and/or acceptors, which are observed within microbial mats, sediments and soil pores. Similarly, energy taxis may influence the structure and function of microbial communities in the rhizosphere.

In this review, we will consider the value of energy taxis as an adaptive response to environmental changes, discuss recent advances in understanding the role of this response in microbial ecology and outline some of the challenges brought to this field by microbial genomics.

2Taxis on a macro scale: microbial habitats

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Taxis on a macro scale: microbial habitats
  5. 3Taxis on a micro scale: molecular mechanisms
  6. 4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors
  7. 5Energy taxis is widespread in microbial world
  8. 6Lessons from genomics: what to expect
  9. 7Concluding remarks
  10. Acknowledgements
  11. References

2.1Soil

Soil is a heterogeneous environment and niches for microorganisms include soil pores, soil aggregates and root surfaces (rhizosphere). Soil bacteria are subjected to considerable seasonal fluctuations in environmental conditions. In particular, soil microorganisms experience steep gradients of nutrients and a situation of “feast-or-famine” depending on the entry of organic matter originating in the soil surface and percolating in the deeper layers or roots exudates. Root exudates and rhizodeposition form the main source of nutrients for microorganisms in the rhizosphere. The major compounds found in root exudates are amino acids, sugars and organic acids and are suggested to provide rhizospheric bacteria with essential sources of carbon and nitrogen [8,9]. In addition, respiration by the roots together with the metabolic activities of the indigenous rhizospheric microflora contributes to the formation of gradients of oxygen and to fluctuations in the redox potential in the rhizosphere. Finally, fluctuation in the water content of the soil matrix and the limited diffusion of oxygen in water may also contribute to the formation of oxygen and redox gradients in soil aggregates and soil pores [10,11]. Therefore, soil bacteria that can sense and rapidly navigate toward niches where conditions are optimal for growth and survival will have a competitive advantage. Motile sensory behavior is proposed to play a key role in the establishment of various plant-microbe interactions, such as associative and symbiotic relationships between plants and microorganisms as well as pathogenesis [12–20]. Finally, chemotaxis and related behaviors may also contribute to the localized spread of bacteria within microenvironments, such as soil pores [21–23].

2.2Marine and freshwater environments

Gradients of light from the surface through deeper layers of water are formed in both shallow waters and in the oceans. Active movement of motile phototrophic bacteria toward optimum light conditions (phototaxis) is expected in such environments [24]. However, some marine bacteria, such as certain open-ocean isolates of cyanobacteria, do not display phototaxis, rather they are attracted to simple nitrogenous substrates [25]. In the open ocean, nutrients are scarce and growth of most marine bacteria depends on dissolved low molecular weight organic matter (sugars, phosphate and amino acids) occurring at very low concentrations [25]. In such a heterogeneous environment, a large fraction of planktonic bacteria was found to be motile [2,27,28], suggesting that motile chemosensory behavior may be significant in the ecology of these bacteria. It was observed that clusters of bacteria formed in conjunction with protozoan and algal cell lysis producing localized concentration gradients of dissolved organic molecules. These point sources of nutrients represent resources available within a limited time and space in the water column and attract chemotactic bacteria present around the lyzed cells [26]. In this case, motile sensory behavior provides the cells with an obvious survival and competitive advantage. In addition, it was also recently proposed that bacterial chemotaxis toward these patches of organic matter will affect the ocean carbon cycle by increasing the rate of mineralization in the water column [2]. Therefore, microbial behavior may play a significant role in the biogeochemical cycles of elements.

2.3Microbial mats and sediments

In microbial communities of mats and sediments, very steep gradients of electron donors and acceptors for respiratory metabolism (including hydrogen, sulfate, sulfide, nitrate, etc.) are formed vertically across the mats. Below the surface, oxygen is typically depleted within millimeters by aerobic microorganisms and limitation of diffusion of oxygen from above. Beneath this oxic zone, anaerobic metabolism depends on respiration on alternative electron acceptors or fermentation [29,30]. In addition, in shallow-water sediments and mats, the depth distribution of the different electron acceptor zones varies seasonally and diurnally: during the day, the oxic zone expands downwards owing to photosynthesis and during the night, the anoxic zone expands upward [2,31,32]. Most bacterial species within these microbial communities are motile, and changes in the distribution of various bacteria throughout the mats such as cyanobacteria (Oscillatoria, Spirulina spp.), sulfate-reducing bacteria (Desulfovibrio spp.), and sulfide-oxidizing bacteria (Beggiatoa spp.) were observed due to active vertical movements of bacteria along the gradients of oxygen, alternative electron acceptors and other chemicals [33–35]. Therefore, it appears that behavioral responses to terminal electron acceptors may play a key role in the structure and organization of these microbial communities.

3Taxis on a micro scale: molecular mechanisms

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Taxis on a macro scale: microbial habitats
  5. 3Taxis on a micro scale: molecular mechanisms
  6. 4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors
  7. 5Energy taxis is widespread in microbial world
  8. 6Lessons from genomics: what to expect
  9. 7Concluding remarks
  10. Acknowledgements
  11. References

3.1Random walk in bacteria

In a uniform environment, motile bacteria swim randomly, smooth runs being interrupted every few seconds by directional changes brought about by a transient reversal (or stop, depending on the characteristics of the flagellar motor) in the direction of rotation of the flagellar motor. This causes the cell to tumble (or stop, or reverse) and randomly re-orient in a new direction. In a gradient of increasing concentration of an attractant or decreasing concentration of a repellent, cells tend to suppress directional changes resulting in an increase in the duration of smooth swimming and a net movement up the gradient. On the other hand, in a gradient of increasing concentration of a repellent or decreasing concentration of an attractant, the cells increase the frequency of directional changes and the biased swimming pattern will lead the bacteria away from the stimulus [36,37]. Motile bacteria are too small to sense the direction of a stimulus directly and, therefore, must sample changes in the intensity or concentration of the stimulus temporally. This is possible because chemotactic motile bacteria possess a mechanism of memory and adaptation that allows them to return to the pre-stimulus random swimming behavior after experiencing a concentration gradient [38].

3.2Molecular mechanism of chemotaxis in Escherichia coli

The molecular mechanism controlling flagellar rotation in E. coli chemotaxis is probably the best-understood biological sensory system [39–42]. Changes in concentration gradients are sensed by dedicated transmembrane chemoreceptors, the methyl-accepting chemotaxis proteins (MCPs), also termed chemotaxis transducers (Fig. 1). In E. coli, there are four transmembrane chemoreceptors (Tsr, Tar, Trg and Tap) and one membrane-bound cytoplasmic receptor (Aer) mediating responses to specific attractant and repellent stimuli [7]. Binding of chemoeffectors to the periplasmic domain of an MCP causes a conformational change in the cytoplasmic domain of the MCP. The cytoplasmic domain comprises a conserved module, which consists of a highly conserved signaling domain demarcated by two methylation domains [43]. The conformation of the signaling domain controls the autophosphorylation of the cytoplasmic histidine kinase CheA, which interacts with the chemoreceptor via the CheW docking protein which functions to couple CheA to the MCPs (Fig. 1). Once CheA is autophosphorylated, it can transfer its phosphate to two response regulators, CheB and CheY. Phosphorylated CheA rapidly transfers its phosphate group to CheY. In the phosphorylated form, CheY is able to bind to the switch of the flagellar motor, which causes a change in the direction of the rotation of the flagellum. Phosphorylated CheA can also donate its phospho group to the methylesterase CheB, which is involved in adaptation, but at a much slower rate than the transfer of phosphate from CheA to CheY. This difference in the rate of the phosphotransfer accounts for the short term “memory” of E. coli cells experiencing a gradient. In the phosporylated form, the methylesterase CheB removes methyl groups from the signaling domain of the MCP molecules and balances the activity of the CheR methyltransferase, which methylates the MCP molecules at a constant rate. The activity of CheB is directly dependent on the activation of CheA and results in resetting the MCP molecules to an un-stimulated state so that they can regain sensitivity to ligand binding in their periplasmic domain. Another protein CheZ is involved in terminating the signal by competing with FliM for phospho-CheY binding and bringing about CheY-P dephosphorylation. Recently, it has been shown that receptor clustering at the cell poles [44] accounts for the high sensitivity and amplification of the chemotactic signal [45]. The chemotactic response triggered by binding of chemicals to the extracellular portion of the transmembrane receptor is the dominant behavior in E. coli[7].

image

Figure 1. Schematic representation of the chemosensory pathway in E. coli. Stimuli from the environment are detected by the periplasmic sensory domain of transmembrane chemoreceptors (such as Tsr, Tar, Trg and Tap). The sensory domain of Aer (energy-sensing transducer) is cytoplasmic (see text for details) and detects intracellular changes resulted from the metabolism of stimuli. Recognition of a stimulus by a sensory domain induces a conformational change in the cytoplasmic signaling domain, which is then transmitted to flagellar motors via the signal transduction cascade (see text for details). Small gray circles depict phosphate groups.

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3.3Molecular mechanisms of chemotaxis in other species

Experimental evidence and analysis of completely sequenced genomes suggest that homologous signal transduction proteins govern similar chemosensory pathways in all motile species of Bacteria and Archaea [46–57]. E. coli, Salmonella typhimurium and Bacillus subtilis, model organisms where chemotaxis has been most extensively studied, each possess only one set of chemotaxis genes (confirmed by complete genome sequencing of these species). Unlike these, other bacteria from different lineages contain multiple homologs of chemotaxis genes that are usually organized in operons [51,58,59]. Gene products of some chemotaxis operons appear to control most behavioral responses in an organism, whereas the function of other operons is unclear and cannot be determined by a simple comparison with orthologous operons [51,58–60]. The biological role of different chemotaxis operons in the ecology of an organism is unclear, but it can be assumed that it provides the cell with an opportunity for fine-tuned behavioral responses to different environmental conditions and adds another level of control of the motile chemosensory behavior. This would be especially significant in motile microbial species that experience frequent changes in environmental conditions and possess a versatile metabolism. Experimental evidence obtained with Rhodobacter sphaeroides, a metabolically versatile ubiquitous soil and freshwater bacterium, shows that both chemoreceptors and major chemotaxis operons are not redundant and are environmentally regulated [59,61,62].

4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Taxis on a macro scale: microbial habitats
  5. 3Taxis on a micro scale: molecular mechanisms
  6. 4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors
  7. 5Energy taxis is widespread in microbial world
  8. 6Lessons from genomics: what to expect
  9. 7Concluding remarks
  10. Acknowledgements
  11. References

4.1Energy taxis as a behavior

Historically, behavioral responses of motile microorganisms were defined based on a spatial gradient of a physico-chemical parameter in which motility was observed. For example, chemotaxis is defined as the active movement of cells in gradients of chemicals, aerotaxis, as the movement of cells in a gradient of oxygen, phototaxis, as the movement of cells in a gradient of light (intensity, wavelength), etc. [63]. In contrast, the term “energy taxis” describes the sensory mechanism rather than the type of gradient and refers to the active movement of cells along various types of gradients resulting from monitoring a parameter associated with intracellular energy levels. In energy taxis, the signal for a behavioral response originates within the electron transport system. Motile cells monitor changes in the rate of electron transport (or a related parameter, such as the proton motive force) and subsequent step-up or step-down in energy levels will be detected by the signal transduction system and will elicit a behavioral response [4–6]. Therefore, any physico-chemical parameter that affects electron transport (and therefore cellular energy levels) will trigger a behavioral response in energy taxis. Effectors for energy taxis include terminal electron acceptors (oxygen and alternative electron acceptors), light, redox chemicals and metabolizable substrates that act as donors of reducing equivalents to the electron transport system and therefore affect cellular energy levels (Fig. 2). Energy taxis encompasses some (but not all) types of aerotaxis, taxis to alternative electron acceptors, phototaxis, redox taxis and chemotaxis in some bacterial species [4–6,24]. By energy taxis, cells actively seek a position in a gradient where their cellular energy levels are optimum (Fig. 3). If an appropriate terminal electron acceptor is present, but a metabolizable substrate that donates reducing equivalents to the respiratory chain is the limiting factor for energy generation, a cell will execute chemotaxis (move along the gradient of a substrate) via the energy-sensing mechanism. On the other hand, if the terminal electron acceptor, such as oxygen, is the limiting factor for energy generation, the cell will seek an appropriate concentration of oxygen (e.g., execute aerotaxis) that supports optimum cellular energy levels. Therefore, the behavioral response in energy taxis is fine-tuned to the environmental conditions a cell finds itself in and allows efficient adaptation to changing conditions in parameters that affect energy metabolism.

image

Figure 2. A general scheme of energy taxis. A generic respiratory electron transport system is shown. Energy taxis can also be governed by changes in the photosynthetic electron transport. Energy taxis transducers receive information from the electron transport system in the form of the redox state of its component(s) and/or proton motive force. Changes in the concentration of electron donors or acceptors affect both parameters. Small gray circles depict phosphate groups. Abbreviations: DH, dehydrogenases; FP, flavoproteins; FeS, iron sulfur proteins; Q, quinones and DMSO, dimethyl sulfoxide.

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image

Figure 3. A scenario of spatial localization of three motile bacterial species in opposing gradients of an electron donor and an electron acceptor. Grey rectangles show chemotactic bands (zones of cell accumulation). Thin dashed lines show changes in chemical concentration. Species 1 responds chemotactically to the electron donor (for example, malate) as an attractant using a classical ligand-binding transducer, and cells navigate to a zone where concentration of attractant is maximal. Similarly, species 3 responds to the electron acceptor (for example, oxygen) via a ligand-binding transducer, and cells navigate to a zone where its concentration is maximal. Species number 3 responds to changes in energy levels, such as proton motive force (PMF) that results from oxidation of the electron donor by the electron acceptor (shown as a bold dashed line) by using an energy taxis transducer. Cells accumulate in the zone where the intracellular energy level is maximal.

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4.2Mechanism of energy taxis

Molecular mechanisms underlying energy taxis have been reviewed recently inline image eriod clock protein, inline image ryl hydrocarbon receptor and inline image ingle-minded protein) comprise another large superfamily of domains implicated in signal transduction in both prokaryotes and eukaryotes [76]. FAD is a well-known redox responsive cofactor and its role in the Aer-mediated taxis in E. coli has been clearly established [74,75]. In addition to guiding cells in oxygen and redox gradients, Aer was found to govern active motility along gradients of rapidly oxidizable substrates that donate reducing equivalents directly to the electron transport system [77]. Taken together, all experimental evidence strongly indicates that Aer directly detects the redox status of a component of the electron transport system, which is capable of reducing or oxidizing FAD. The redox status of FAD is likely to affect the conformation of the PAS domain, similarly to the mode of action of other cofactor-containing PAS domains [78,79]. These conformational changes must be passed to the signaling module of the receptor, which interacts with CheW and CheA proteins of the signal transduction cascade thereby controlling the direction of flagellar rotation.

It is not clear how the proton motive force may be detected by a taxis transducer, but it is clear that any behavioral response requires a transducer. The candidate for the role of a proton motive force sensor in E. coli is the Tsr protein, which besides Aer is the only transducer implicated in various behavioral responses associated with energy taxis [73,77]. Although Tsr is an energy taxis transducer, there is no direct experimental evidence to support the hypothesis that Tsr is a proton motive force sensor; however, there are at least two hypotheses on how Tsr might measure the proton motive force. First, it was suggested that pH-sensing abilities of Tsr [80,81] contribute to sensing of the ΔpH component of the proton motive force [5,82]. The second hypothesis is that positively charged residues that participate in anchoring the transducer in the membrane may contribute to the membrane mobility of Tsr in response to changes in the proton motive force [6]. Some other taxis transducers in different bacterial species are thought to be able to detect changes in the electron transport system [83,84]; however, Aer remains the only energy taxis transducer for which the mechanism of sensing can be understood to some extent. It is important to mention that there might also be other yet unknown types of energy taxis transducers that are capable of detecting changes in the redox status of the electron transport system or any other parameter associated with the electron transport and energy generation.

4.3Metabolism-dependent behavior versus energy taxis

Energy taxis is exclusively metabolism-dependent. However, a metabolism-dependent behavior is not necessarily synonymous with energy taxis. In energy taxis, metabolizable substrates elicit a behavioral response because they increase the rate of electron transport (and the proton motive force). Therefore, metabolism of the substrate is required to elicit a behavioral response and energy taxis is thus defined as a metabolism-dependent behavior [4,6]. In Azospirillum brasilense, it was conclusively established that a functional electron transport system is required for chemotaxis to most chemicals [85]. In E. coli, sensing of the rate of electron transport resulting from the metabolism of several chemicals is also involved in chemotaxis [71,77,86]. In both organisms, it was demonstrated that the signal for chemotaxis originated within the electron transport system. Energy taxis is the dominant behavior in A. brasilense, since most chemicals are sensed via this mechanism, whereas a metabolism-independent behavior seems to prevail in E. coli.

Some metabolism-dependent behaviors do not constitute energy taxis. Bacteria may directly detect intracellular metabolic intermediates and not the change in cellular energy that results from their metabolism. Particularly, chemotaxis to several compounds in R. sphaeroides requires transport and partial metabolism of chemoattractants [87], where direct sensing of metabolites intermediates via cytoplasmic chemoreceptors was proposed as a possible sensing mechanism [55,60]. Similarly, sensing intracellular metabolic intermediates was proposed for chemotaxis to some compounds in Sinorhizobium meliloti[60,88] and Pseudomonas putida[89]. Therefore, although a metabolism-dependent behavior toward metabolizable substrates may indicate energy taxis, the role of the electron transport system in triggering the behavioral response should be demonstrated in order to show the behavior is true energy taxis.

5Energy taxis is widespread in microbial world

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Taxis on a macro scale: microbial habitats
  5. 3Taxis on a micro scale: molecular mechanisms
  6. 4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors
  7. 5Energy taxis is widespread in microbial world
  8. 6Lessons from genomics: what to expect
  9. 7Concluding remarks
  10. Acknowledgements
  11. References

By energy taxis, bacteria can couple their behavior directly to their metabolism and conditions in their surroundings. Because it provides the cells with a simple versatile sensory and adaptation system, energy taxis is likely to be widespread in the microbial world.

Energy taxis is best described in E. coli, where taxis to oxygen, alternative electron acceptors, redox potential and oxidizable substrates was described in a great detail [65,68,69,71] and is now understood at the molecular level [72–75]. The ecological significance of behavioral responses, including energy taxis, in E. coli is unknown, which is in striking contrast with the molecular detail to which the signal transduction pathway for its chemotaxis has been elucidated. Homologs of the Aer transducer have also been found in P. putida[90] and Campylobacter jejuni[91]. In C. jejuni, two proteins, CetA and CetB, which show homology to the PAS domain and the conserved signaling chemoreceptor domain of Aer, respectively, function as a bipartite energy taxis system [91]. The Aer homologs navigate the bacteria in gradients of oxygen [90,91] and alternative electron acceptors [91] and thus, are proposed to function in a manner analogous to Aer in E. coli, i.e., by monitoring the redox status of the electron transport system.

Azospirillum brasilense, a diazotrophic α-proteobacterium associated with the roots of various cereals, navigates in gradients of redox molecules, oxygen, alternative electron acceptors and metabolizable substrates by energy taxis, which is the dominant behavior in this bacterium [6,66,85]. The bacteria are attracted to a preferred oxygen concentration that supports a maximal cellular energy level and nitrogen fixation [70]. A functional electron transport system is required for chemical sensing and taxis to electron acceptors in A. brasilense[85,92]. Seeking environments where energy levels are optimal could provide A. brasilense with an effective strategy to reach niches where nitrogen fixation can take place (microaerobic niches in soil and/or in the rhizosphere). A simple laboratory experiment illustrating the value of this strategy is shown in Fig. 4. Such a behavior coupled to the metabolic versatility of Azospirillum spp. is likely to be significant in the ecology of this microorganism and would explain its wide distribution in different soils and rhizospheres [93].

image

Figure 4. Spatial distribution of A. brasilense cells in gradients of oxygen. Wild-type Sp7 (1) and generally non-chemotactic mutant IZ21 (2) [70] were inoculated at equal concentration into nitrogen-free semi-soft malate medium at a specific position indicated by a white arrowhead. Wild-type cells navigated via energy taxis [85] to a preferred oxygen concentration, where they fix atmospheric nitrogen, grow at maximal rates and produce brownish pigments (indicated by an orange arrowhead). In contrast, the non-chemotactic mutant, which swims with the same speed as the wild-type, but cannot orient itself in chemical gradients [70], was unable to locate the zone of preferred oxygen concentration and, therefore, showed very limited growth (no visible pigment) at the point of inoculation.

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Energy taxis is also typical of the behavior of R. sphaeroides in gradients of oxygen and alternative electron acceptors. The signal for these behavioral responses was shown to originate in the electron transport system [94]. Similarly, a functional electron transport system is required for phototaxis in this microorganism [95]. The role of energy taxis in the overall behavior of R. sphaeroides remains to be elucidated, but is likely to be significant since this microorganism is metabolically versatile and is found in a wide range of environments.

Taxis to the terminal electron acceptors, nitrate and nitrite, was also demonstrated in several denitrifying bacteria. R. sphaeroides and Pseudomonas fluorescens can navigate in gradients of nitrate and nitrite under anaerobic conditions [96]. A functional electron transport system is required for the behavioral response in both species, which is indicative of energy taxis [96, L. Miller, L. Philippot and G. Alexandre, unpublished observation]. Similarly, Rhodopseudomonas palustris accumulated in gradients of nitrite, but not nitrate, in anaerobiosis, whereas Agrobacterium tumefaciens displayed taxis to both electron acceptors [96]. These behavioral responses strongly suggest that these microorganisms navigate in gradients of terminal electron acceptor by energy taxis; however, conclusive experimental evidence still remains to be obtained.

A nitrogen-fixing plant symbiont Rhizobium leguminosarum responds chemotactically to a redox gradient of 1,4-benzoquinone (L. Miller, M. Hynes and G. Alexandre, unpublished observation), suggesting that this organism is capable of monitoring its environment by energy taxis. The role of energy taxis in the behavior of R. leguminosarum and the specific chemoreceptor(s) involved in mediating the response are currently under investigation. The closely related species S. meliloti senses and responds to changes in oxygen concentration by aerokinesis (speed acceleration toward preferred oxygen concentration) [97]. Kinesis (change in the swimming speed) is typical of the overall behavior of S. meliloti[98]. Oxygen-dependent behavior and the identification in the complete genome sequence of S. meliloti of a chemoreceptor, named McpY, which is predicted to be cytoplasmic and possesses two tandem PAS domains, may be indicative of energy taxis in this species [88].

Several other bacterial species navigate in gradients of oxygen in a manner analogous to E. coli or A. brasilense, suggesting that they are capable of energy taxis. Particularly, Magnetospirillum magnetotacticum, a magnetotactic microorganism commonly found in marine environments and freshwater sediments [99,100], seeks low concentrations of oxygen by aerotaxis and accumulates in microaerophilic and anaerobic environments that are best suited to its metabolism. At the preferred oxygen concentration, motile cells of M. magnetotacticum and closely related Magnetococcus sp. accumulate and form an aerotactic band [101]. Similarly, several species of the sulfate-reducing bacterium Desulfovibrio are capable of aerotaxis and are attracted to very low oxygen concentrations [102,103]. Desulfovibrio vulgaris Hildenborough not only forms a sharp aerotactic band at 0.04% of dissolved oxygen but also grows at this very low oxygen concentration [102]. The DcrA chemoreceptor from D. vulgaris contains a C-type heme in its periplasmic region [83] and a cytoplasmic PAS domain between the second transmembrane domain and the signaling domain of the chemoreceptor [5]. Therefore, it was proposed that the DcrA chemoreceptor may act as an energy sensor by monitoring the redox status of the electron transport system.

Although a behavioral response to terminal electron acceptors may be indicative of energy taxis, it is not conclusive evidence. Some chemoreceptors sense energy-related parameters, such as oxygen, by binding the stimulus molecule directly, in a manner similar to classical chemical ligand-binding to transmembrane chemoreceptors in E. coli. Specifically, myoglobin-like, heme-containing aerotaxis transducers (HemAT) have been identified in Halobacterium salinarum and B. subtilis and trigger the aerotactic response in these bacteria [104]. Similarly, the C-type heme-sensing domain of DcrA from D. vulgaris may bind oxygen directly [83], and DcrA may function as a dual energy taxis sensor and a direct sensor for oxygen. An unusual heme-binding domain (hemerythrin), which is widely spread in eukaryotes, was identified in another chemotaxis transducer from D. vulgaris, the DcrH protein [105]. This domain appears to bind oxygen directly and, therefore, may not be an energy taxis transducer. It is obvious that a variety of sensing mechanisms have evolved in different microbial species and the observation of a behavior, traditionally described as part of energy taxis (e.g., aerotaxis), is not sufficient evidence to conclude the nature of the sensory mechanism.

6Lessons from genomics: what to expect

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Taxis on a macro scale: microbial habitats
  5. 3Taxis on a micro scale: molecular mechanisms
  6. 4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors
  7. 5Energy taxis is widespread in microbial world
  8. 6Lessons from genomics: what to expect
  9. 7Concluding remarks
  10. Acknowledgements
  11. References

Microbial genome sequencing projects have revolutionized our understanding of microbial physiology. New genomic information appears on a daily basis along with improved tools for data mining and analysis. However, knowledge of the molecular mechanisms governing energy taxis is still very limited and therefore there is no direct way to glean insights into the role of energy taxis in microorganisms from genomic data. Although straight answers to such questions may be elusive, comparative genomics can provide us with new directions to search for these answers. Specifically, comparative genomics analysis resulted in the identification of signaling proteins with novel functions. For example, the function of the chemoreceptor TaxD1 (sll0041) as a phototaxis transducer was initially predicted in silico [106] and then experimentally validated [107]. Similarly, a family of novel nitrate sensors including chemoreceptors was recently predicted using comparative genomics [108] and constitutes novel targets for experimental validation.

6.1How many taxis receptors are out there?

Other than redox-sensing by the Aer protein of E. coli, little is known about the mechanisms underlying energy taxis. However, it is clear that chemoreceptors play the role of sensors in energy taxis. Furthermore, different types of transducers can participate in sensing of the redox status of the electron transport system and proton motive force. Two out of five chemoreceptors in E. coli are implicated in energy taxis, although this is not a dominant behavior in this organism. If a similar ratio of energy transducers vs. ligand-binding transducers could be assumed for other species, the presence of a reasonable number of transducers in a given genome would suggest that the organism might be capable of energy taxis. Analysis of the number of chemoreceptors in available microbial genomes shows that in fact most flagellated species contain many more transducers than does E. coli (Fig. 5). The number of chemoreceptors per genome varies dramatically and there is no direct correlation between the number of transducers and the genome size. For example, the size of M. magnetotacticum and E. coli genomes is exactly the same (4.6 Mb), whereas the difference in the number of transducers is astonishing (65 and 5, respectively). Interestingly, two α-proteobacterial species that contain many chemotaxis transducers, M. magnetotacticum and R. rubrum are close relatives of A. brasilense, a bacterium where energy taxis is the dominant behavior [85]. All three species have similar metabolic requirements (versatile microaerophilic diazotrophs), therefore, it is logical to expect energy taxis to play an important role in the motile behavior of M. magnetotacticum and R. rubrum.

image

Figure 5. The number of chemotaxis transducers in sequenced microbial genomes. Chemotaxis transducers were identified in complete protein sets from sequenced genomes (i) by retrieving proteins containing MA (methyl-accepting chemotaxis protein) domain from the SMART database [122] and (ii) by a BLAST search [123] against the microbial genome database at the National Center for Biotechnology Information using various MA domains as a queries. Here, chemotaxis transducer is defined as any protein containing a full-length MA domain (SMART accession number SM00283). Data on genomes availability and the information on contributing genome-sequencing centers can be found at http://www.ncbi.nlm.nih.gov/PMGifs/Genomes/prokdata.html.

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Large numbers of transducers are found in species that are widely distributed in marine and freshwater environments, sediments and soil. In these environments, microorganisms are expected to experience large amplitude variations in the gradients of different physico-chemical parameters that will affect their ability to grow and thrive. In contrast, species that have a small number of transducers are often found in very specific niches, where rather constant environmental conditions are expected (hydrothermal vents, eukaryotic hosts, etc.). For example, the marine bacterium M. magnetotacticum has 65 putative chemoreceptors whereas the animal pathogen Listeria monocytogenes and the archaeal hyperthermophile Archaeoglobus fulgidis have only 2 each (Fig. 5). These observations favor the hypothesis that energy taxis is widespread in the microbial world [6] and might be especially important for species from aquatic and soil environments.

The existence of large numbers of chemoreceptors in environmental isolates, such as M. magnetotacticum, Vibrio cholera and P. fluorescens (Fig. 5) raises the question of how the cell fine tunes its behavioral response to integrate the different signals originated from these chemoreceptors. First, it is likely that the expression of at least some chemoreceptors is environmentally regulated. Different chemoreceptors are expressed under different environmental conditions in R. sphaeroides[61]. Similarly, the NahY chemoreceptor in P. putida senses naphthalene and is expressed in coordination with the naphthalene degradation genes [89]. This implies that stimuli sensed by the environmentally regulated chemoreceptors will prevail only under certain environmental conditions. Second, the recent finding that a chemosensory pathway regulates developmental gene expression in Myxococcus xanthus[109] suggests that some chemoreceptors may regulate cellular functions other than motility. However, whether there are “dominant” signals and/or significant cross-talk between different chemosensory pathways to produce balanced cellular response remains to be determined.

6.2The diversity of sensory domains in chemotaxis transducers

More than a thousand protein sequences of putative chemotaxis transducers are currently available in public databases. The function (sensory capability) is experimentally determined for fewer than 2% of these chemoreceptors, and as genome sequencing continues to yield information about large numbers of genes whose function has never been studied, the percentage of chemotaxis transducers with known function will only get smaller. In some cases, comparative genomic analysis may produce a reasonable prediction of the transducer specificity [106,108], however, in most cases it will not. This is due to a multi-domain organization of chemotaxis receptors and different evolutionary fate of sensory and signaling modules. The evolution of sensory domains is independent of that of the signaling domains, and the evolutionary changes in sensory domains appear to have much faster rates [110]. This results in a truly remarkable diversity of sensory modules in chemoreceptors.

Recent studies demonstrated that chemotaxis transducers share sensory domains with other types of receptor proteins from diverse signal transduction pathways, such as sensor histidine kinases, diguanylyl and adenylyl cyclases, serine/threonine kinases, phosphatases, etc. [108,111–117]. Some of these signal transduction proteins are known sensors of energy-related parameters. For example, the ArcB histidine kinase from E. coli, which responds to changes in the redox status of the respiratory system [118], contains a PAS domain, as does the energy taxis transducer Aer. Another redox sensor, the AppA protein from R. sphaeroides, contains an FAD-binding BLUF domain (different from the FAD-binding PAS domain in Aer), which is also present in other types of signal transduction proteins [119] and is likely to be found in chemotaxis transducers. Other types of domains capable of accommodating small molecules (including redox-responsive cofactors) are also found in various bacterial signal transduction proteins including chemotaxis transducers [112,116,120]. Thus, comparative genomic analysis may help to identify other putative energy taxis transducers and provide new targets for experimental research.

7Concluding remarks

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Taxis on a macro scale: microbial habitats
  5. 3Taxis on a micro scale: molecular mechanisms
  6. 4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors
  7. 5Energy taxis is widespread in microbial world
  8. 6Lessons from genomics: what to expect
  9. 7Concluding remarks
  10. Acknowledgements
  11. References

Energy-dependent forms of taxis have been known for a long time, and a recent discovery of energy taxis transducers in the model bacterium E. coli has renewed the interest in this type of behavior. Still, our understanding of the role of energy taxis in the ecology of microorganisms remains limited. Adaptation to changing redox conditions in the soil and the rhizosphere appears to be critical in the ecology of the nitrogen-fixing, plant growth-promoting Azospirillum. So far, A. brasilense is the only bacterium, where energy taxis was demonstrated to be the dominant tactic behavior, therefore it is emerging as a model for both molecular analysis and ecological studies on the role of energy taxis. Energy taxis was also demonstrated in several other soil and freshwater bacteria (R. sphaeroides, P. fluorescens and R. leguminosarum) and is likely to be widespread among microorganisms inhabiting these environments. Analysis of completely sequenced microbial genomes revealed that many bacteria from aquatic and soil environments possess very large numbers of chemoreceptors and are likely to be capable of energy taxis. However, the motile behavior of these species is not understood. In particular, it is astonishing to find out that behavior of V. cholerae, which is an important human pathogen, is still poorly described. V. cholerae and other organisms that have large sets of chemoreceptors (e.g., M. magnetotacticum, Bradyrhizobium japonicum and Pseudomonas species) constitute excellent models from which to derive ecological information about the role of behavior in general and energy taxis in particular. Characterizing energy taxis in diverse microbial species will unravel different molecular mechanisms of energy sensing. This knowledge would likely have an impact beyond the field of microbial chemotaxis, because sensory modules of chemoreceptors are shared by other signal transduction proteins in microorganisms.

Ten years ago, it was impossible to imagine that motility of E. coli in oxygen gradients is governed by an energy taxis transducer that has a sensory module (the PAS domain) very similar to that in a human transcription factor regulating circadian rhythm [121]. Hopefully, 10 years from now we will find new types of energy taxis transducers that are not covered even in the most imaginative parts of this review.

Acknowledgements

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Taxis on a macro scale: microbial habitats
  5. 3Taxis on a micro scale: molecular mechanisms
  6. 4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors
  7. 5Energy taxis is widespread in microbial world
  8. 6Lessons from genomics: what to expect
  9. 7Concluding remarks
  10. Acknowledgements
  11. References

We are grateful to Barry L. Taylor for encouragement and many fruitful discussions on energy taxis. We thank the anonymous reviewer for insightful comments and valuable suggestions.

Research in the authors’ laboratories is funded by grants from Georgia State University (to G.A.) and National Science Foundation grant EIA-0219079 (to I.B.Z.).

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  2. Abstract
  3. 1Introduction
  4. 2Taxis on a macro scale: microbial habitats
  5. 3Taxis on a micro scale: molecular mechanisms
  6. 4Energy taxis: sensing a dynamic equilibrium between electron donors and acceptors
  7. 5Energy taxis is widespread in microbial world
  8. 6Lessons from genomics: what to expect
  9. 7Concluding remarks
  10. Acknowledgements
  11. References
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