A Bacterial Cell-Cycle Regulatory Network Operating in Time and Space

Model-based deconvolution of cell cycle time-series data reveals gene expression details at high resolution

In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure “just-in-time” assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract “single-cell”-like information from population-level time-series expression data. This method removes the effects of 1) variance in growth rate and 2) variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell.

Time-series analyses of cellular regulatory processes have successfully drawn attention to the importance of temporal regulation in biological systems. A number of model systems can be synchronized such that data collected on cell populations better reflect the dynamic properties of the individual cell. However, experimental synchronization is never perfect, and the degree of synchrony that does exist at the outset of an experiment is quickly lost over time as cells grow at different rates and enter different developmental or physiological states on cell division. Thus, data collected from a population of synchronized cells can lead to incorrect models of temporal regulation. Here we demonstrate that the problem of relating population data to the individual cell can be resolved with a computational method that effectively removes the effects of both imperfect synchrony and time-dependent loss of synchrony. Application of this deconvolution algorithm to a cell cycle time-series data set from the model bacterium Caulobacter crescentus uncovers critical temporal details in the expression of essential genes that are not evident in the raw population-based data. The deconvolution routine presented here is a robust and general tool for extracting biochemical parameters of the average single cell from population time-series data.

Adapting the machine: adaptor proteins for Hsp100/Clp and AAA+ proteases

Members of the AAA+ protein superfamily contribute to many diverse aspects of protein homeostasis in prokaryotic cells. As a fundamental component of numerous proteolytic machines in bacteria, AAA+ proteins play a crucial part not only in general protein quality control but also in the regulation of developmental programmes, through the controlled turnover of key proteins such as transcription factors. To manage these many, varied tasks, Hsp100/Clp and AAA+ proteases use specific adaptor proteins to enhance or expand the substrate recognition abilities of their cognate protease. Here, we review our current knowledge of the modulation of bacterial AAA+ proteases by these cellular arbitrators.

Comparative analysis of Caulobacter chromosome replication origins

Caulobacter crescentus (CB15) initiates chromosome replication only in stalked cells and not in swarmers. To better understand this dimorphic control of chromosome replication, we isolated replication origins (oris) from freshwater Caulobacter (FWC) and marine Caulobacter (MCS) species. Previous studies implicated integration host factor (IHF) and CcrM DNA methylation sites in replication control. However, ori IHF and CcrM sites identified in the model FWC CB15 were only conserved among closely related FWCs. DnaA boxes and CtrA binding sites are established CB15 ori components. CtrA is a two-component regulator that blocks chromosome replication selectively in CB15 swarmers. DnaA boxes and CtrA sites were found in five FWC and three MCS oris. Usually, a DnaA box and a CtrA site were paired, suggesting that CtrA binding regulates DnaA activity. We tested this hypothesis by site-directed mutagenesis of an MCS10 ori which contains only one CtrA binding site overlapping a critical DnaA box. This overlapping site is unique in the whole MCS10 genome. Selective DnaA box mutations decreased replication, while selective CtrA binding site mutations increased replication of MCS10 ori plasmids. Therefore, both FWC and MCS oris use CtrA to repress replication. Despite this similarity, phylogenetic analysis unexpectedly shows that CtrA usage evolved separately among these Caulobacter oris. We discuss consensus oris and convergent ori evolution in differentiating bacteria.

Networking opportunities for bacteria

In this post-genomic era, our capacity to explore biological networks and predict network architectures has been greatly expanded, accelerating interest in systems biology. Here, we highlight recent systems biology studies in prokaryotes, consider the challenges ahead, and suggest opportunities for future studies in bacterial models.

Kinetic modeling of biological systems

The dynamics of how the constituent components of a natural system interact defines the spatio-temporal response of the system to stimuli. Modeling the kinetics of the processes that represent a biophysical system has long been pursued with the aim of improving our understanding of the studied system. Due to the unique properties of biological systems, in addition to the usual difficulties faced in modeling the dynamics of physical or chemical systems, biological simulations encounter difficulties that result from intrinsic multi-scale and stochastic nature of the biological processes.This chapter discusses the implications for simulation of models involving interacting species with very low copy numbers, which often occur in biological systems and give rise to significant relative fluctuations. The conditions necessitating the use of stochastic kinetic simulation methods and the mathematical foundations of the stochastic simulation algorithms are presented. How the well-organized structural hierarchies often seen in biological systems can lead to multi-scale problems and the possible ways to address the encountered computational difficulties are discussed. We present the details of the existing kinetic simulation methods and discuss their strengths and shortcomings. A list of the publicly available kinetic simulation tools and our reflections for future prospects are also provided.

Growth phase- and cell division-dependent activation and inactivation of the {sigma}32 regulon in Escherichia coli

Alternative sigma factors allow bacteria to reprogram global transcription rapidly and to adapt to changes in the environment. Here we report on growth- and cell division-dependent sigma(32) regulon activity in Escherichia coli in batch culture. By analyzing sigma(32) expression in growing cells, an increase in sigma(32) protein levels is observed during the first round of cell division after exit from stationary phase. Increased sigma(32) protein levels result from transcriptional activation of the rpoH gene. After the first round of bulk cell division, rpoH transcript levels and sigma(32) protein levels decrease again. The late-logarithmic phase and the transition to stationary phase are accompanied by a second increase in sigma(32) levels and enhanced stability of sigma(32) protein but not by enhanced transcription of rpoH. Throughout growth, sigma(32) target genes show expression patterns consistent with oscillating sigma(32) protein levels. However, during the transition to early-stationary phase, despite high sigma(32) protein levels, the transcription of sigma(32) target genes is downregulated, suggesting functional inactivation of sigma(32). It is deduced from these data that there may be a link between sigma(32) regulon activity and cell division events. Further support for this hypothesis is provided by the observation that in cells in which FtsZ is depleted, sigma(32) regulon activation is suppressed.

A bacterial control circuit integrates polar localization and proteolysis of key regulatory proteins with a phospho-signaling cascade

Dynamic protein localization is an integral component of the regulatory circuit that drives the Caulobacter cell cycle. The ClpXP protease is localized to the Caulobacter cell pole, where it catalyzes the degradation of the CtrA master regulator at specific times in the cell cycle. Clearance of active CtrA at the G1/S transition allows the initiation of DNA replication and cell-cycle progression. The polar localization of ClpXP is dependent on the polar positioning of the CpdR single-domain response regulator. Only the unphosphorylated form of CpdR localizes and activates ClpXP. We demonstrate that another single domain response regulator, DivK, promotes the polar accumulation of unphosphorylated CpdR and that CpdR is subsequently degraded at the cell pole by the localized ClpXP protease. Thus, CpdR function is regulated by a feedback loop that incorporates its differential phosphorylation, the transient polar localization and activity of the ClpXP protease, and the clearance of the CpdR by polar ClpXP that, in turn, releases ClpXP from the pole relieving the degradation of CtrA. CtrA approximately P then accumulates and activates the transcription of cpdR, completing the regulatory loop, establishing an integrated network that controls a robust cell-cycle transition.

Modelling and analysis of gene regulatory networks

Gene regulatory networks have an important role in every process of life, including cell differentiation, metabolism, the cell cycle and signal transduction. By understanding the dynamics of these networks we can shed light on the mechanisms of diseases that occur when these cellular processes are dysregulated. Accurate prediction of the behaviour of regulatory networks will also speed up biotechnological projects, as such predictions are quicker and cheaper than lab experiments. Computational methods, both for supporting the development of network models and for the analysis of their functionality, have already proved to be a valuable research tool.

Architecture and inherent robustness of a bacterial cell-cycle control system

A closed-loop control system drives progression of the coupled stalked and swarmer cell cycles of the bacterium Caulobacter crescentus in a near-mechanical step-like fashion. The cell-cycle control has a cyclical genetic circuit composed of four regulatory proteins with tight coupling to processive chromosome replication and cell division subsystems. We report a hybrid simulation of the coupled cell-cycle control system, including asymmetric cell division and responses to external starvation signals, that replicates mRNA and protein concentration patterns and is consistent with observed mutant phenotypes. An asynchronous sequential digital circuit model equivalent to the validated simulation model was created. Formal model-checking analysis of the digital circuit showed that the cell-cycle control is robust to intrinsic stochastic variations in reaction rates and nutrient supply, and that it reliably stops and restarts to accommodate nutrient starvation. Model checking also showed that mechanisms involving methylation-state changes in regulatory promoter regions during DNA replication increase the robustness of the cell-cycle control. The hybrid cell-cycle simulation implementation is inherently extensible and provides a promising approach for development of whole-cell behavioral models that can replicate the observed functionality of the cell and its responses to changing environmental conditions.

From databases to modelling of functional pathways

This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell.

Short time-series microarray analysis: methods and challenges

The detection and analysis of steady-state gene expression has become routine. Time-series microarrays are of growing interest to systems biologists for deciphering the dynamic nature and complex regulation of biosystems. Most temporal microarray data only contain a limited number of time points, giving rise to short-time-series data, which imposes challenges for traditional methods of extracting meaningful information. To obtain useful information from the wealth of short-time series data requires addressing the problems that arise due to limited sampling. Current efforts have shown promise in improving the analysis of short time-series microarray data, although challenges remain. This commentary addresses recent advances in methods for short-time series analysis including simplification-based approaches and the integration of multi-source information. Nevertheless, further studies and development of computational methods are needed to provide practical solutions to fully exploit the potential of this data.

Ralstonia eutropha H16 flagellation changes according to nutrient supply and state of poly(3-hydroxybutyrate) accumulation

Two-dimensional polyacrylamide gel electrophoresis (2D PAGE), in combination with matrix-assisted laser desorption ionization-time of flight analysis, and the recently revealed genome sequence of Ralstonia eutropha H16 were employed to detect and identify proteins that are differentially expressed during different phases of poly(3-hydroxybutyric acid) (PHB) metabolism. For this, a modified protein extraction protocol applicable to PHB-harboring cells was developed to enable 2D PAGE-based proteome analysis of such cells. Subsequently, samples from (i) the exponential growth phase, (ii) the stationary growth phase permissive for PHB biosynthesis, and (iii) a phase permissive for PHB mobilization were analyzed. Among several proteins exhibiting quantitative changes during the time course of a cultivation experiment, flagellin, which is the main protein of bacterial flagella, was identified. Initial investigations that report on changes of flagellation for R. eutropha were done, but 2D PAGE and electron microscopic examinations of cells revealed clear evidence that R. eutropha exhibited further significant changes in flagellation depending on the life cycle, nutritional supply, and, in particular, PHB metabolism. The results of our study suggest that R. eutropha is strongly flagellated in the exponential growth phase and loses a certain number of flagella in transition to the stationary phase. In the stationary phase under conditions permissive for PHB biosynthesis, flagellation of cells admittedly stagnated. However, under conditions permissive for intracellular PHB mobilization after a nitrogen source was added to cells that are carbon deprived but with full PHB accumulation, flagella are lost. This might be due to a degradation of flagella; at least, the cells stopped flagellin synthesis while normal degradation continued. In contrast, under nutrient limitation or the loss of phasins, cells retained their flagella.

Allosteric regulation of histidine kinases by their cognate response regulator determines cell fate

The two-component phosphorylation network is of critical importance for bacterial growth and physiology. Here, we address plasticity and interconnection of distinct signal transduction pathways within this network. In Caulobacter crescentus antagonistic activities of the PleC phosphatase and DivJ kinase localized at opposite cell poles control the phosphorylation state and subcellular localization of the cell fate determinator protein DivK. We show that DivK functions as an allosteric regulator that switches PleC from a phosphatase into an autokinase state and thereby mediates a cyclic di-GMP-dependent morphogenetic program. Through allosteric activation of the DivJ autokinase, DivK also stimulates its own phosphorylation and polar localization. These data suggest that DivK is the central effector of an integrated circuit that operates via spatially organized feedback loops to control asymmetry and cell fate determination in C. crescentus. Thus, single domain response regulators can facilitate crosstalk, feedback control, and long-range communication among members of the two-component network.

Using chemistry and microfluidics to understand the spatial dynamics of complex biological networks

Understanding the spatial dynamics of biochemical networks is both fundamentally important for understanding life at the systems level and also has practical implications for medicine, engineering, biology, and chemistry. Studies at the level of individual reactions provide essential information about the function, interactions, and localization of individual molecular species and reactions in a network. However, analyzing the spatial dynamics of complex biochemical networks at this level is difficult. Biochemical networks are nonequilibrium systems containing dozens to hundreds of reactions with nonlinear and time-dependent interactions, and these interactions are influenced by diffusion, flow, and the relative values of state-dependent kinetic parameters. To achieve an overall understanding of the spatial dynamics of a network and the global mechanisms that drive its function, networks must be analyzed as a whole, where all of the components and influential parameters of a network are simultaneously considered. Here, we describe chemical concepts and microfluidic tools developed for network-level investigations of the spatial dynamics of these networks. Modular approaches can be used to simplify these networks by separating them into modules, and simple experimental or computational models can be created by replacing each module with a single reaction. Microfluidics can be used to implement these models as well as to analyze and perturb the complex network itself with spatial control on the micrometer scale. We also describe the application of these network-level approaches to elucidate the mechanisms governing the spatial dynamics of two networkshemostasis (blood clotting) and early patterning of the Drosophila embryo. To investigate the dynamics of the complex network of hemostasis, we simplified the network by using a modular mechanism and created a chemical model based on this mechanism by using microfluidics. Then, we used the mechanism and the model to predict the dynamics of initiation and propagation of blood clotting and tested these predictions with human blood plasma by using microfluidics. We discovered that both initiation and propagation of clotting are regulated by a threshold response to the concentration of activators of clotting, and that clotting is sensitive to the spatial localization of stimuli. To understand the dynamics of patterning of the Drosophila embryo, we used microfluidics to perturb the environment around a developing embryo and observe the effects of this perturbation on the expression of Hunchback, a protein whose localization is essential to proper development. We found that the mechanism that is responsible for Hunchback positioning is asymmetric, time-dependent, and more complex than previously proposed by studies of individual reactions. Overall, these approaches provide strategies for simplifying, modeling, and probing complex networks without sacrificing the functionality of the network. Such network-level strategies may be most useful for understanding systems with nonlinear interactions where spatial dynamics is essential for function. In addition, microfluidics provides an opportunity to investigate the mechanisms responsible for robust functioning of complex networks. By creating nonideal, stressful, and perturbed environments, microfluidic experiments could reveal the function of pathways thought to be nonessential under ideal conditions.

Screen for localized proteins in Caulobacter crescentus

Precise localization of individual proteins is required for processes such as motility, chemotaxis, cell-cycle progression, and cell division in bacteria, but the number of proteins that are localized in bacterial species is not known. A screen based on transposon mutagenesis and fluorescence activated cell sorting was devised to identify large numbers of localized proteins, and employed in Caulobacter crescentus. From a sample of the clones isolated in the screen, eleven proteins with no previously characterized localization in C. crescentus were identified, including six hypothetical proteins. The localized hypothetical proteins included one protein that was localized in a helix-like structure, and two proteins for which the localization changed as a function of the cell cycle, suggesting that complex three-dimensional patterns and cell cycle-dependent localization are likely to be common in bacteria. Other mutants produced localized fusion proteins even though the transposon has inserted near the 5′ end of a gene, demonstrating that short peptides can contain sufficient information to localize bacterial proteins. The screen described here could be used in most bacterial species.

A quantitative study of the division cycle of Caulobacter crescentus stalked cells

Progression of a cell through the division cycle is tightly controlled at different steps to ensure the integrity of genome replication and partitioning to daughter cells. From published experimental evidence, we propose a molecular mechanism for control of the cell division cycle in Caulobacter crescentus. The mechanism, which is based on the synthesis and degradation of three “master regulator” proteins (CtrA, GcrA, and DnaA), is converted into a quantitative model, in order to study the temporal dynamics of these and other cell cycle proteins. The model accounts for important details of the physiology, biochemistry, and genetics of cell cycle control in stalked C. crescentus cell. It reproduces protein time courses in wild-type cells, mimics correctly the phenotypes of many mutant strains, and predicts the phenotypes of currently uncharacterized mutants. Since many of the proteins involved in regulating the cell cycle of C. crescentus are conserved among many genera of α-proteobacteria, the proposed mechanism may be applicable to other species of importance in agriculture and medicine.

The cell cycle is the sequence of events by which a growing cell replicates all its components and divides them more or less evenly between two daughter cells. The timing and spatial organization of these events are controlled by gene–protein interaction networks of great complexity. A challenge for computational biology is to build realistic, accurate, predictive mathematical models of these control systems in a variety of organisms, both eukaryotes and prokaryotes. To this end, we present a model of a portion of the molecular network controlling DNA synthesis, cell cycle–related gene expression, DNA methylation, and cell division in stalked cells of the α-proteobacterium Caulobacter crescentus. The model is formulated in terms of nonlinear ordinary differential equations for the major cell cycle regulatory proteins in Caulobacter: CtrA, GcrA, DnaA, CcrM, and DivK. Kinetic rate constants are estimated, and the model is tested against available experimental observations on wild-type and mutant cells. The model is viewed as a starting point for more comprehensive models of the future that will account, in addition, for the spatial asymmetry of Caulobacter reproduction (swarmer cells as well as stalked cells), the correlation of cell growth and division, and cell cycle checkpoints.

Probabilistic modeling of DNA mismatch repair effects on cell cycle dynamics and iododeoxyuridine-DNA incorporation

Previous studies in our laboratory have described increased and preferential radiosensitization of mismatch repair-deficient (MMR(-)) HCT116 colon cancer cells with 5-iododeoxyuridine (IUdR). Indeed, our studies showed that MMR is involved in the repair (removal) of IUdR-DNA, principally the G:IU mispair. Consequently, we have shown that MMR(-) cells incorporate 25% to 42% more IUdR than MMR(+) cells, and that IUdR and ionizing radiation (IR) interact to produce up to 3-fold greater cytotoxicity in MMR(-) cells. The present study uses the integration of probabilistic mathematical models and experimental data on MMR(-) versus MMR(+) cells to describe the effects of IUdR incorporation upon the cell cycle for the purpose of increasing IUdR-mediated radiosensitivity in MMR(-) cells. Two computational models have been developed. The first is a stochastic model of the progression of cell cycle states, which is applied to experimental data for two synchronized isogenic MMR(+) and MMR(-) colon cancer cell lines treated with and without IUdR. The second model defines the relation between the percentage of cells in the different cell cycle states and the corresponding IUdR-DNA incorporation at a particular time point. These models can be combined to predict IUdR-DNA incorporation at any time in the cell cycle. These mathematical models will be modified and used to maximize therapeutic gain in MMR(-) tumors versus MMR(+) normal tissues by predicting the optimal dose of IUdR and optimal timing for IR treatment to increase the synergistic action using xenograft models and, later, in clinical trials.

Modes of cytometric bacterial DNA pattern: a tool for pursuing growth

Analyses of DNA pattern provide an excellent tool to determine activity states of bacteria. Bacterial cell cycle behaviour is generally different from the eukaryotic one and is pre-determined by the bacteria's diversity within the phylogenetic tree, and their metabolic traits. As a result, every species creates its specific proliferation pattern that differs from every other one. Up to now, just few bacterial species have been investigated and little information is available concerning DNA cycling even in already known species. This prevents understanding of the complexity and diversity of ongoing bacterial interactions in many ecosystems or in biotechnology. Flow cytometry is the only possible technique to shed light on the dynamics of bacterial communities and DNA patterns will help to unlock the hidden principles of their life. This review provides basic knowledge about the molecular background of bacterial cell cycling, discusses modes of cell cycle phases and presents techniques to both obtain DNA patterns and to combine the contained information with physiological cell states.

Peptide signals encode protein localization

Many bacterial proteins are localized to precise intracellular locations, but in most cases the mechanism for encoding localization information is not known. Screening libraries of peptides fused to green fluorescent protein identified sequences that directed the protein to helical structures or to midcell. These peptides indicate that protein localization can be encoded in 20-amino-acid peptides instead of complex protein-protein interactions and raise the possibility that the location of a protein within the cell could be predicted from bioinformatic data.

Bacterial morphogenesis: learning how cells make cells

Bacteria furnish tractable models for complex biological processes, and morphogenesis is now taking its turn. We can already explain in general terms how such elementary forms as rods and cocci are produced, and the shapes of several individual organisms are coming into focus. In most bacteria shape is maintained by the cell wall, specifically the peptidoglycan layer, which has the attributes of a strong stiff fabric. Compliance of that fabric with turgor pressure is an important aspect of morphogenesis. The shape of the wall sacculus is determined by the way it is deposited, which is controlled by a cytoskeleton made up of two molecular families. One, related to the eukaryotic tubulins, is responsible for the construction of the septum and the poles. The other, related to eukaryotic actins, localizes peptidoglycan synthesis in the lateral walls of rod-shaped cells. Just how the cytoskeleton itself is organized remains to be discovered, but it seems likely that, as in eukaryotes, the cytoskeleton is produced by self-organized assembly, guided by the fabric of the cell.

Network motifs: theory and experimental approaches

Transcription regulation networks control the expression of genes. The transcription networks of well-studied microorganisms appear to be made up of a small set of recurring regulation patterns, called network motifs. The same network motifs have recently been found in diverse organisms from bacteria to humans, suggesting that they serve as basic building blocks of transcription networks. Here I review network motifs and their functions, with an emphasis on experimental studies. Network motifs in other biological networks are also mentioned, including signalling and neuronal networks.

The quorum-sensing molecule autoinducer 2 regulates motility and flagellar morphogenesis in Helicobacter pylori

The genome of the gastric pathogen Helicobacter pylori contains a homologue of the gene luxS, which has been shown to be responsible for production of the quorum-sensing signal autoinducer 2 (AI-2). We report here that deletion of the luxS gene in strain G27 resulted in decreased motility on soft agar plates, a defect that was complemented by a wild-type copy of the luxS gene and by the addition of cell-free supernatant containing AI-2. The flagella of the luxS mutant appeared normal; however, in genetic backgrounds lacking any of three flagellar regulators--the two-component sensor kinase flgS, the sigma factor sigma28 (also called fliA), and the anti-sigma factor flgM--loss of luxS altered flagellar morphology. In all cases, the double mutant phenotypes were restored to the luxS+ phenotype by the addition of synthetic 4,5-dihydroxy-2,3-pentanedione (DPD), which cyclizes to form AI-2. Furthermore, in all mutant backgrounds loss of luxS caused a decrease in transcript levels of the flagellar regulator flhA. Addition of DPD to luxS cells induced flhA transcription in a dose-dependent manner. Deletion of flhA in a wild-type or luxS mutant background resulted in identical loss of motility, flagella, and flagellar gene expression. These data demonstrate that AI-2 functions as a secreted signaling molecule upstream of FlhA and plays a critical role in global regulation of flagellar gene transcription in H. pylori.

A scale-free systems theory of motivation and addiction

Scale-free organizations, characterized by uneven distributions of linkages between nodal elements, describe the structure and function of many life-based complex systems developing under evolutionary pressures. We explore motivated behavior as a scale-free map toward a comprehensive translational theory of addiction. Motivational and behavioral repertoires are reframed as link and nodal element sets, respectively, comprising a scale-free structure. These sets are generated by semi-independent information-processing streams within cortical-striatal circuits that cooperatively provide decision-making and sequential processing functions necessary for traversing maps of motivational links connecting behavioral nodes. Dopamine modulation of cortical-striatal plasticity serves a central-hierarchical mechanism for survival-adaptive sculpting and development of motivational-behavioral repertoires by guiding a scale-free design. Drug-induced dopamine activity promotes drug taking as a highly connected behavioral hub at the expense of natural-adaptive motivational links and behavioral nodes. Conceptualizing addiction as pathological alteration of scale-free motivational-behavioral repertoires unifies neurobiological, neurocomputational and behavioral research while addressing addiction vulnerability in adolescence and psychiatric illness. This model may inform integrative research in defining more effective prevention and treatment strategies for addiction.

Regulation of the initiation of chromosomal replication in bacteria

The initiation of chromosomal replication occurs only once during the cell cycle in both prokaryotes and eukaryotes. Initiation of chromosome replication is the first and tightly controlled step of a DNA synthesis. Bacterial chromosome replication is initiated at a single origin, oriC, by the initiator protein DnaA, which specifically interacts with 9-bp non-palindromic sequences (DnaA boxes) at oriC. In Escherichia coli, a model organism used to study the mechanism of DNA replication and its regulation, the control of initiation relies on a reduction of the availability and/or activity of the two key elements, DnaA and the oriC region. This review summarizes recent research into the regulatory mechanisms of the initiation of chromosomal replication in bacteria, with emphasis on organisms other than E. coli.

Bacterial response regulators: versatile regulatory strategies from common domains

Response regulators (RRs) comprise a major family of signaling proteins in prokaryotes. A modular architecture that consists of a conserved receiver domain and a variable effector domain enables RRs to function as phosphorylation-regulated switches that couple a wide variety of cellular behaviors to environmental cues. Recently, advances have been made in understanding RR functions both at genome-wide and molecular levels. Global techniques have been developed to analyze RR input and output, expanding the scope of characterization of these versatile components. Meanwhile, structural studies have revealed that, despite common structures and mechanisms of function within individual domains, a range of interactions between receiver and effector domains confer great diversity in regulatory strategies, optimizing individual RRs for the specific regulatory needs of different signaling systems.

High-throughput identification of transcription start sites, conserved promoter motifs and predicted regulons

Using 62 probe-level datasets obtained with a custom-designed Caulobacter crescentus microarray chip, we identify transcriptional start sites of 769 genes, 53 of which are transcribed from multiple start sites. Transcriptional start sites are identified by analyzing probe signal cross-correlation matrices created from probe pairs tiled every 5 bp upstream of the genes. Signals from probes binding the same message are correlated. The contribution of each promoter for genes transcribed from multiple promoters is identified. Knowing the transcription start site enables targeted searching for regulatory-protein binding motifs in the promoter regions of genes with similar expression patterns. We identified 27 motifs, 17 of which share no similarity to the characterized motifs of other C. crescentus transcriptional regulators. Using these motifs, we predict coregulated genes. We verified novel promoter motifs that regulate stress-response genes, including those responding to uranium challenge, a stress-response sigma factor and a stress-response noncoding RNA.

Mechanisms of cyclic-di-GMP signaling in bacteria

Cyclic-di-GMP is a ubiquitous second messenger in bacteria. The recent discovery that c-di-GMP antagonistically controls motility and virulence of single, planktonic cells on one hand and cell adhesion and persistence of multicellular communities on the other has spurred interest in this regulatory compound. Cellular levels of c-di-GMP are controlled through the opposing activities of diguanylate cyclases and phosphodiesterases, which represent two large families of output domains found in bacterial one- and two-component systems. This review concentrates on structural and functional aspects of diguanylate cyclases and phosphodiesterases, and on their role in transmitting environmental stimuli into a range of different cellular functions. In addition, we examine several well-established model systems for c-di-GMP signaling, including Pseudomonas, Vibrio, Caulobacter, and Salmonella.

Exploration into the spatial and temporal mechanisms of bacterial polarity

The recognition of bacterial asymmetry is not new: the first high-resolution microscopy studies revealed that bacteria come in a multitude of shapes and sometimes carry asymmetrically localized external structures such as flagella on the cell surface. Even so, the idea that bacteria could have an inherent overall polarity, which affects not only their outer appearance but also many of their vital processes, has only recently been appreciated. In this review, we focus on recent advances in our understanding of the molecular mechanisms underlying the establishment of polarized functions and cell polarity in bacteria.

Regulation of the bacterial cell cycle by an integrated genetic circuit

How bacteria regulate cell cycle progression at a molecular level is a fundamental but poorly understood problem. In Caulobacter crescentus, two-component signal transduction proteins are crucial for cell cycle regulation, but the connectivity of regulators involved has remained elusive and key factors are unidentified. Here we identify ChpT, an essential histidine phosphotransferase that controls the activity of CtrA, the master cell cycle regulator. We show that the essential histidine kinase CckA initiates two phosphorelays, each requiring ChpT, which lead to the phosphorylation and stabilization of CtrA. Downregulation of CckA activity therefore results in the dephosphorylation and degradation of CtrA, which in turn allow the initiation of DNA replication. Furthermore, we show that CtrA triggers its own destruction by promoting cell division and inducing synthesis of the essential regulator DivK, which feeds back to downregulate CckA immediately before S phase. Our results define a single integrated circuit whose components and connectivity can account for the cell cycle oscillations of CtrA in Caulobacter.

Characterization of intact subcellular bodies in whole bacteria by cryo-electron tomography and spectroscopic imaging

We illustrate the combined use of cryo-electron tomography and spectroscopic difference imaging in the study of subcellular structure and subcellular bodies in whole bacteria. We limited our goal and focus to bodies with a distinct elemental composition that was in a sufficiently high concentration to provide the necessary signal-to-noise level at the relatively large sample thicknesses of the intact cell. This combination proved very powerful, as demonstrated by the identification of a phosphorus-rich body in Caulobacter crescentus. We also confirmed the presence of a body rich in carbon, demonstrated that these two types of bodies are readily recognized and distinguished from each other, and provided, for the first time to our knowledge, structural information about them in their intact state. In addition, we also showed the presence of a similar type of phosphorus-rich body in Deinococcus grandis, a member of a completely unrelated bacteria genus. Cryo-electron microscopy and tomography allowed the study of the biogenesis and morphology of these bodies at resolutions better than 10 nm, whereas spectroscopic difference imaging provided a direct identification of their chemical composition.

Optimal gene partition into operons correlates with gene functional order

Gene arrangement into operons varies between bacterial species. Genes in a given system can be on one operon in some organisms and on several operons in other organisms. Existing theories explain why genes that work together should be on the same operon, since this allows for advantageous lateral gene transfer and accurate stoichiometry. But what causes the frequent separation into multiple operons of co-regulated genes that act together in a pathway? Here we suggest that separation is due to benefits made possible by differential regulation of each operon. We present a simple mathematical model for the optimal distribution of genes into operons based on a balance of the cost of operons and the benefit of regulation that provides 'just-when-needed' temporal order. The analysis predicts that genes are arranged such that genes on the same operon do not skip functional steps in the pathway. This prediction is supported by genomic data from 137 bacterial genomes. Our work suggests that gene arrangement is not only the result of random historical drift, genome re-arrangement and gene transfer, but has elements that are solutions of an evolutionary optimization problem. Thus gene functional order may be inferred by analyzing the operon structure across different genomes.

NFAT dysregulation by increased dosage of DSCR1 and DYRK1A on chromosome 21

Trisomy 21 results in Down's syndrome, but little is known about how a 1.5-fold increase in gene dosage produces the pleiotropic phenotypes of Down's syndrome. Here we report that two genes, DSCR1 and DYRK1A , lie within the critical region of human chromosome 21 and act synergistically to prevent nuclear occupancy of NFATc transcription factors, which are regulators of vertebrate development. We use mathematical modelling to predict that autoregulation within the pathway accentuates the effects of trisomy of DSCR1 and DYRK1A, leading to failure to activate NFATc target genes under specific conditions. Our observations of calcineurin-and Nfatc-deficient mice, Dscr1- and Dyrk1a-overexpressing mice, mouse models of Down's syndrome and human trisomy 21 are consistent with these predictions. We suggest that the 1.5-fold increase in dosage of DSCR1 and DYRK1A cooperatively destabilizes a regulatory circuit, leading to reduced NFATc activity and many of the features of Down's syndrome. More generally, these observations suggest that the destabilization of regulatory circuits can underlie human disease.

Regulation of flagella

Flagellar gene networks are fascinating, owing to their complexity - they usually coordinate the expression of more than 40 genes - and particular wiring that elicits temporal expression coupled to organelle morphogenesis. Moreover, many of the lessons learned from flagellar regulation are generally applicable to type III secretion systems. Our understanding of flagellar networks is rapidly expanding to include diverse organisms, as well as deepening to enable the development of predictive wiring diagrams. Numerous regulators control the regulation of flagella, and one of the next challenges in the field is to integrate flagellar gene control into master blueprints of global gene expression.

ExbBD-dependent transport of maltodextrins through the novel MalA protein across the outer membrane of Caulobacter crescentus

Analysis of the genome sequence of Caulobacter crescentus predicts 67 TonB-dependent outer membrane proteins. To demonstrate that among them are proteins that transport nutrients other than chelated Fe(3+) and vitamin B(12)-the substrates hitherto known to be transported by TonB-dependent transporters-the outer membrane protein profile of cells grown on different substrates was determined by two-dimensional electrophoresis. Maltose induced the synthesis of a hitherto unknown 99.5-kDa protein, designated here as MalA, encoded by the cc2287 genomic locus. MalA mediated growth on maltodextrins and transported [(14)C]maltodextrins from [(14)C]maltose to [(14)C]maltopentaose. [(14)C]maltose transport showed biphasic kinetics, with a fast initial rate and a slower second rate. The initial transport had a K(d) of 0.2 microM, while the second transport had a K(d) of 5 microM. It is proposed that the fast rate reflects binding to MalA and the second rate reflects transport into the cells. Energy depletion of cells by 100 microM carbonyl cyanide 3-chlorophenylhydrazone abolished maltose binding and transport. Deletion of the malA gene diminished maltose transport to 1% of the wild-type malA strain and impaired transport of the larger maltodextrins. The malA mutant was unable to grow on maltodextrins larger than maltotetraose. Deletion of two C. crescentus genes homologous to the exbB exbD genes of Escherichia coli abolished [(14)C]maltodextrin binding and transport and growth on maltodextrins larger than maltotetraose. These mutants also showed impaired growth on Fe(3+)-rhodotorulate as the sole iron source, which provided evidence of energy-coupled transport. Unexpectedly, a deletion mutant of a tonB homolog transported maltose at the wild-type rate and grew on all maltodextrins tested. Since Fe(3+)-rhodotorulate served as an iron source for the tonB mutant, an additional gene encoding a protein with a TonB function is postulated. Permeation of maltose and maltotriose through the outer membrane of the C. crescentus malA mutant was slower than permeation through the outer membrane of an E. coli lamB mutant, which suggests a low porin activity in C. crescentus. The pores of the C. crescentus porins are slightly larger than those of E. coli K-12, since maltotetraose supported growth of the C. crescentus malA mutant but failed to support growth of the E. coli lamB mutant. The data are consistent with the proposal that binding of maltodextrins to MalA requires energy and MalA actively transports maltodextrins with K(d) values 1,000-fold smaller than those for the LamB porin and 100-fold larger than those for the vitamin B(12) and ferric siderophore outer membrane transporters. MalA is the first example of an outer membrane protein for which an ExbB/ExbD-dependent transport of a nutrient other than iron and vitamin B(12) has been demonstrated.

Whole-genome transcriptional analysis of heavy metal stresses in Caulobacter crescentus

The bacterium Caulobacter crescentus and related stalk bacterial species are known for their distinctive ability to live in low-nutrient environments, a characteristic of most heavy metal-contaminated sites. Caulobacter crescentus is a model organism for studying cell cycle regulation with well-developed genetics. We have identified the pathways responding to heavy-metal toxicity in C. crescentus to provide insights for the possible application of Caulobacter to environmental restoration. We exposed C. crescentus cells to four heavy metals (chromium, cadmium, selenium, and uranium) and analyzed genome-wide transcriptional activities postexposure using an Affymetrix GeneChip microarray. C. crescentus showed surprisingly high tolerance to uranium, a possible mechanism for which may be the formation of extracellular calcium-uranium-phosphate precipitates. The principal response to these metals was protection against oxidative stress (up-regulation of manganese-dependent superoxide dismutase sodA). Glutathione S-transferase, thioredoxin, glutaredoxins, and DNA repair enzymes responded most strongly to cadmium and chromate. The cadmium and chromium stress response also focused on reducing the intracellular metal concentration, with multiple efflux pumps employed to remove cadmium, while a sulfate transporter was down-regulated to reduce nonspecific uptake of chromium. Membrane proteins were also up-regulated in response to most of the metals tested. A two-component signal transduction system involved in the uranium response was identified. Several differentially regulated transcripts from regions previously not known to encode proteins were identified, demonstrating the advantage of evaluating the transcriptome by using whole-genome microarrays.

A Circadian Timing Mechanism in the Cyanobacteria

Cyanobacteria such as Synechococcus elongatus PCC 7942, Thermosynechococcus elongatus BP-1, and Synechocystis species strain PCC 6803 have an endogenous timing mechanism that can generate and maintain a 24 h (circadian) periodicity to global (whole genome) gene expression patterns. This rhythmicity extends to many other physiological functions, including chromosome compaction. These rhythmic patterns seem to reflect the periodicity of availability of the primary energy source for these photoautotrophic organisms, the Sun. Presumably, eons of environmentally derived rhythmicity--light/dark cycles--have simply been mechanistically incorporated into the regulatory networks of these cyanobacteria. Genetic and biochemical experimentation over the last 15 years has identified many key components of the primary timing mechanism that generates rhythmicity, the input pathways that synchronize endogenous rhythms to exogenous rhythms, and the output pathways that transduce temporal information from the timekeeper to the regulators of gene expression and function. Amazingly, the primary timing mechanism has evidently been extracted from S. elongatus PCC 7942 and can also keep time in vitro. Mixing the circadian clock proteins KaiA, KaiB, and KaiC from S. elongatus PCC 7942 in vitro and adding ATP results in a circadian rhythm in the KaiC protein phosphorylation state. Nonetheless, many questions still loom regarding how this circadian clock mechanism works, how it communicates with the environment and how it regulates temporal patterns of gene expression. Many details regarding structure and function of the individual clock-related proteins are provided here as a basis to discuss these questions. A strong, data-intensive foundation has been developed to support the working model for the cyanobacterial circadian regulatory system. The eventual addition to that model of the metabolic parameters participating in the command and control of this circadian global regulatory system will ultimately allow a fascinating look into whole-cell physiology and metabolism and the consequential organization of global gene expression patterns.

Single-particle tracking of oriC-GFP fluorescent spots during chromosome segregation in Escherichia coli

DNA regions close to the origin of replication were visualized by the green fluorescent protein (GFP)-Lac repressor/lac operator system. The number of oriC-GFP fluorescent spots per cell and per nucleoid in batch-cultured cells corresponded to the theoretical DNA replication pattern. A similar pattern was observed in cells growing on microscope slides used for time-lapse experiments. The trajectories of 124 oriC-GFP spots were monitored by time-lapse microscopy of 31 cells at time intervals of 1, 2, and 3 min. Spot positions were determined along the short and long axis of cells. The lengthwise movement of spots was corrected for cell elongation. The step sizes of the spots showed a Gaussian distribution with a standard deviation of approximately 110 nm. Plots of the mean square displacement versus time indicated a free diffusion regime for spot movement along the long axis of the cell, with a diffusion coefficient of 4.3+/-2.6x10(-5) microm2/s. Spot movement along the short axis showed confinement in a region of the diameter of the nucleoid ( approximately 800 nm) with an effective diffusion coefficient of 2.9+/-1.7x10(-5) microm2/s. Confidence levels for the mean square displacement analysis were obtained from numerical simulations. We conclude from the analysis that within the experimental accuracy--the limits of which are indicated and discussed--there is no evidence that spot segregation requires any other mechanism than that of cell (length) growth.

Molecules into cells: specifying spatial architecture

A living cell is not an aggregate of molecules but an organized pattern, structured in space and in time. This article addresses some conceptual issues in the genesis of spatial architecture, including how molecules find their proper location in cell space, the origins of supramolecular order, the role of the genes, cell morphology, the continuity of cells, and the inheritance of order. The discussion is framed around a hierarchy of physiological processes that bridge the gap between nanometer-sized molecules and cells three to six orders of magnitude larger. Stepping stones include molecular self-organization, directional physiology, spatial markers, gradients, fields, and physical forces. The knowledge at hand leads to an unconventional interpretation of biological order. I have come to think of cells as self-organized systems composed of genetically specified elements plus heritable structures. The smallest self that can be fairly said to organize itself is the whole cell. If structure, form, and function are ever to be computed from data at a lower level, the starting point will be not the genome, but a spatially organized system of molecules. This conclusion invites us to reconsider our understanding of what genes do, what organisms are, and how living systems could have arisen on the early Earth.

Distinct constrictive processes, separated in time and space, divide caulobacter inner and outer membranes

Cryoelectron microscope tomography (cryoEM) and a fluorescence loss in photobleaching (FLIP) assay were used to characterize progression of the terminal stages of Caulobacter crescentus cell division. Tomographic cryoEM images of the cell division site show separate constrictive processes closing first the inner membrane (IM) and then the outer membrane (OM) in a manner distinctly different from that of septum-forming bacteria. FLIP experiments had previously shown cytoplasmic compartmentalization (when cytoplasmic proteins can no longer diffuse between the two nascent progeny cell compartments) occurring 18 min before daughter cell separation in a 135-min cell cycle so the two constrictive processes are separated in both time and space. In the very latest stages of both IM and OM constriction, short membrane tether structures are observed. The smallest observed pre-fission tethers were 60 nm in diameter for both the inner and outer membranes. Here, we also used FLIP experiments to show that both membrane-bound and periplasmic fluorescent proteins diffuse freely through the FtsZ ring during most of the constriction procession.

Rhodopseudomonas palustris regulons detected by cross-species analysis of alphaproteobacterial genomes

Rhodopseudomonas palustris, an alpha-proteobacterium, carries out three of the chemical reactions that support life on this planet: the conversion of sunlight to chemical-potential energy; the absorption of carbon dioxide, which it converts to cellular material; and the fixation of atmospheric nitrogen into ammonia. Insight into the transcription-regulatory network that coordinates these processes is fundamental to understanding the biology of this versatile bacterium. With this goal in mind, we predicted regulatory signals genomewide, using a two-step phylogenetic-footprinting and clustering process that we had developed previously. In the first step, 4,963 putative transcription factor binding sites, upstream of 2,044 genes and operons, were identified using cross-species Gibbs sampling. Bayesian motif clustering was then employed to group the cross-species motifs into regulons. We have identified 101 putative regulons in R. palustris, including 8 that are of particular interest: a photosynthetic regulon, a flagellar regulon, an organic hydroperoxide resistance regulon, the LexA regulon, and four regulons related to nitrogen metabolism (FixK2, NnrR, NtrC, and sigma54). In some cases, clustering allowed us to assign functions to proteins that previously had been annotated with only putative functions; we have identified RPA0828 as the organic hydroperoxide resistance regulator and RPA1026 as a cell cycle methylase. In addition to predicting regulons, we identified a novel inverted repeat that likely forms a highly conserved stem-loop and that occurs downstream of over 100 genes.

Two-component signal transduction pathways regulating growth and cell cycle progression in a bacterium: a system-level analysis

Two-component signal transduction systems, comprised of histidine kinases and their response regulator substrates, are the predominant means by which bacteria sense and respond to extracellular signals. These systems allow cells to adapt to prevailing conditions by modifying cellular physiology, including initiating programs of gene expression, catalyzing reactions, or modifying protein–protein interactions. These signaling pathways have also been demonstrated to play a role in coordinating bacterial cell cycle progression and development. Here we report a system-level investigation of two-component pathways in the model organism Caulobacter crescentus. First, by a comprehensive deletion analysis we show that at least 39 of the 106 two-component genes are required for cell cycle progression, growth, or morphogenesis. These include nine genes essential for growth or viability of the organism. We then use a systematic biochemical approach, called phosphotransfer profiling, to map the connectivity of histidine kinases and response regulators. Combining these genetic and biochemical approaches, we identify a new, highly conserved essential signaling pathway from the histidine kinase CenK to the response regulator CenR, which plays a critical role in controlling cell envelope biogenesis and structure. Depletion of either cenK or cenR leads to an unusual, severe blebbing of cell envelope material, whereas constitutive activation of the pathway compromises cell envelope integrity, resulting in cell lysis and death. We propose that the CenK–CenR pathway may be a suitable target for new antibiotic development, given previous successes in targeting the bacterial cell wall. Finally, the ability of our in vitro phosphotransfer profiling method to identify signaling pathways that operate in vivo takes advantage of an observation that histidine kinases are endowed with a global kinetic preference for their cognate response regulators. We propose that this system-wide selectivity insulates two-component pathways from one another, preventing unwanted cross-talk.

Histidine kinases and their (sensory) response regulators are screened for in C. crescentus. Follow-up experiments determine several essential components, including one pair critical for cell envelope biogenesis and structure.

Is Escherichia coli getting old?

Whether or not bacteria divide symmetrically, the inheritance of cell poles is always asymmetrical. Because each cell carries an old and a new pole, its daughters will not be the same. Tracking poles of cells and measuring their lengths and doubling times in micro-colonies, Stewart et al.1 observed that growth rate diminished in cells inheriting old poles and concluded that these cells are susceptible to aging. Here, their results are compared with studies on the variabilities of length and age at division. It is argued that the decreased growth rate in old pole cells falls within the expected variation and may therefore be sufficiently far from a catastrophe-like cell death through aging.

Transcriptional stochasticity in gene expression

Due to the small number of copies of molecular species involved, such as DNA, mRNA and regulatory proteins, gene expression is a stochastic phenomenon. In eukaryotic cells, the stochastic effects primarily originate in regulation of gene activity. Transcription can be initiated by a single transcription factor binding to a specific regulatory site in the target gene. Stochasticity of transcription factor binding and dissociation is then amplified by transcription and translation, since target gene activation results in a burst of mRNA molecules, and each mRNA copy serves as a template for translating numerous protein molecules. In the present paper, we explore a mathematical approach to stochastic modeling. In this approach, the ordinary differential equations with a stochastic component for mRNA and protein levels in a single cells yield a system of first-order partial differential equations (PDEs) for two-dimensional probability density functions (pdf). We consider the following examples: Regulation of a single auto-repressing gene, and regulation of a system of two mutual repressors and of an activator-repressor system. The resulting PDEs are approximated by a system of many ordinary equations, which are then numerically solved.

Phenotype analysis using network motifs derived from changes in regulatory network dynamics

The intrinsic dynamic response of a transcriptional regulatory network depends directly on molecular interactions in the cellular transcription, translation, and degradation machineries. These interactions can be incorporated into dynamic mathematical models of the biochemical system using the biophysical relationship with the model parameters. Modifications of such interactions bring changes to the biological behavior of the cells, and therefore, many normal and pathological cellular states depend on them. It is important for analysis, prediction, diagnosis, and treatment of cellular function to have an experimentally derived model with parameters that adequately represent the molecular interactions of interest. Finding the model and parameters of a transcriptional regulatory network is a difficult task that has been approached at different levels and with different techniques. We develop here a new analysis method (based on previous work on network inference, modeling, and parameter identification) that finds the most changed parameters from yeast oligonucleotide microarray expression patterns in cases where a phenotype difference exists between two samples. We then relate and examine the changed parameters with their associated genes, corresponding genetic functional categories, and particular subnetworks and connectivities. The biophysical bases for these changes are also identified by studying the relationship of the changed parameters with the transcription, translation, and degradation mechanisms. The method is improved to cases where there are two or more transcription factors influencing transcription, and a statistical analysis is performed to give a measurement of the uniqueness and robustness of the parameter fit.

Intracellular Signaling: Spatial and Temporal Control

Cells integrate many inputs through complex networks of interacting signaling pathways. Systems approaches as well as computer-aided reductionist approaches attempt to “untangle the wires” and gain an intimate understanding of cells. But “understanding” any system is just the way that the human mind gains the ability to predict behavior. Computer simulations are an alternative way to achieve this goal—quite possibly the only way for complex systems. We have new tools to probe large sets of unknown interactions, and we have amassed enough detailed information to quantitatively describe many functional modules. Cell physiology has passed the threshold: the time to begin modeling is now.

Conserved modular design of an oxygen sensory/signaling network with species-specific output

Principles of modular design are evident in signaling networks that detect and integrate a given signal and, depending on the organism in which the network module is present, transduce this signal to affect different metabolic or developmental pathways. Here we report a global transcriptional analysis of an oxygen sensory/signaling network in Caulobacter crescentus consisting of the sensor histidine kinase FixL, its cognate response regulator FixJ, the transcriptional regulator FixK, and the kinase inhibitor FixT. It is known that in rhizobial bacteria these proteins form a network that regulates transcription of genes required for symbiotic nitrogen fixation, anaerobic and microaerobic respiration, and hydrogen metabolism under hypoxic conditions. We have identified a positive feedback loop in this network and present evidence that the negative feedback regulator, FixT, acts to inhibit FixL by mimicking a response regulator. Overall, the core circuit topology of the Fix network is conserved between the rhizobia and C. crescentus, a free-living aerobe that cannot fix nitrogen, respire anaerobically, or metabolize hydrogen. In C. crescentus, the Fix network is required for normal cellular growth during hypoxia and controls expression of genes encoding four distinct aerobic respiratory terminal oxidases and multiple carbon and nitrogen metabolic enzymes. Thus, the Fix network is a conserved sensory/signaling module whose transcriptional output has been adapted to the unique physiologies of C. crescentus and the nitrogen-fixing rhizobia.