Distinctive topologies of partner-switching signaling networks correlate with their physiological roles

Modularity in Biological Networks

Network modeling, from the ecological to the molecular scale has become an essential tool for studying the structure, dynamics and complex behavior of living systems. Graph representations of the relationships between biological components open up a wide variety of methods for discovering the mechanistic and functional properties of biological systems. Many biological networks are organized into a modular structure, so methods to discover such modules are essential if we are to understand the biological system as a whole. However, most of the methods used in biology to this end, have a limited applicability, as they are very specific to the system they were developed for. Conversely, from the statistical physics and network science perspective, graph modularity has been theoretically studied and several methods of a very general nature have been developed. It is our perspective that in particular for the modularity detection problem, biology and theoretical physics/network science are less connected than they should. The central goal of this review is to provide the necessary background and present the most applicable and pertinent methods for community detection in a way that motivates their further usage in biological research.

Spurious regulatory connections dictate the expression-fitness landscape of translation factors

During steady-state cell growth, individual enzymatic fluxes can be directly inferred from growth rate by mass conservation, but the inverse problem remains unsolved. Perturbing the flux and expression of a single enzyme could have pleiotropic effects that may or may not dominate the impact on cell fitness. Here, we quantitatively dissect the molecular and global responses to varied expression of translation termination factors (peptide release factors, RFs) in the bacterium Bacillus subtilis. While endogenous RF expression maximizes proliferation, deviations in expression lead to unexpected distal regulatory responses that dictate fitness reduction. Molecularly, RF depletion causes expression imbalance at specific operons, which activates master regulators and detrimentally overrides the transcriptome. Through these spurious connections, RF abundances are thus entrenched by focal points within the regulatory network, in one case located at a single stop codon. Such regulatory entrenchment suggests that predictive bottom-up models of expression-fitness landscapes will require near-exhaustive characterization of parts.

Sigma Factor Modulation for Cyanobacterial Metabolic Engineering

Sigma (σ) factors are key regulatory proteins that control the transcription initiation in prokaryotes. In response to environmental or developmental cues, σ factors initiate the transcription of necessary genes responsible for maintaining a life-sustaining metabolic balance. Due to the significant role of σ factors in bacterial metabolism, their rational engineering for commercial metabolite production in photoautotrophic, cyanobacterial cells is a desirable venture. As cyanobacterial genomes typically encode multiple σ factors, effective execution of metabolic engineering efforts largely relies on uncovering the complicated gene regulatory network and further characterization of the members of σ factor regulatory circuits. This review outlines the prospects of σ factor in metabolic engineering of cyanobacteria, summarizes the challenges in the path towards an efficient strain construction and highlights the genomic context of putative regulators of cyanobacterial σ factors.

RskA Is a Dual Function Activator-Inhibitor That Controls SigK Activity Across Distinct Bacterial Genera

It has been previously shown that RskA, the anti-Sigma factor K of Mycobacterium tuberculosis, inhibits SigK and that mutations in RskA promote high expression of the SigK regulon. The latter observation led us to hypothesize that RskA mutations lead to loss of the anti-Sigma factor function. In this report, we used natural and artificial mutations in RskA to determine the basis of the SigK-RskA partnership. Consistent with predictions, the N-terminal cytoplasmic portion of RskA was sufficient on its own to inhibit SigK. Unexpectedly, RskA also served as an activator of SigK. This activation depended on the same N-terminal region and was enhanced by the membrane-extracellular portion of RskA. Based on this, we engineered similar truncations in a Gram-negative bacterium, namely Yersinia enterocolitica. Again, we observed that, with specific alterations of RskA, we were able to enhance SigK activity. Together these results support an alternative mechanism of anti-Sigma factor function, that we could term modulator (activator-inhibitor) in both Actinobacteria and Gram-negative bacteria, suggesting that Sigma factor activation by anti-Sigma factors could be under-recognized.

A partner-switching regulatory system controls hormogonium development in the filamentous cyanobacterium Nostoc punctiforme

Filamentous cyanobacteria exhibit developmental complexity, including the transient differentiation of motile hormogonia in many species. Using a forward genetic approach, a trio of genes unique to filamentous cyanobacteria encoding a putative Rsb-like partner-switching regulatory system (PSRS) was implicated in regulating hormogonium development in the model filamentous cyanobacterium Nostoc punctiforme. Analysis of in-frame deletion strains indicated that HmpU (putative serine phosphatase) and HmpV (STAS domain) enhance, while HmpW (putative serine kinase) represses motility and persistence of the hormogonium state. Protein-protein interaction studies demonstrated specificity between HmpW and HmpV. Epistasis analysis between hmpW and hmpV was consistent with HmpV acting as the downstream effector of the system, rather than regulation of a sigma factor by HmpW. Deletion of hmpU or hmpV reduced accumulation of extracellular PilA and hormogonium polysaccharide (HPS), and expression of type IV pilus- and HPS-specific genes was reduced in the ΔhmpV strain. Expression of the Hmp PSRS is induced in hormogonia, and the cytoplasmic localization of HmpV-GFPuv implies that its downstream target is probably cytoplasmic as well. Collectively, these results support a model where HmpU and HmpW antagonistically regulate the phosphorylation state of HmpV, and subsequently, unphosphorylated HmpV positively regulates an undefined downstream target to affect hormogonium-specific gene expression.

Relatively slow stochastic gene-state switching in the presence of positive feedback significantly broadens the region of bimodality through stabilizing the uninduced phenotypic state

Within an isogenic population, even in the same extracellular environment, individual cells can exhibit various phenotypic states. The exact role of stochastic gene-state switching regulating the transition among these phenotypic states in a single cell is not fully understood, especially in the presence of positive feedback. Recent high-precision single-cell measurements showed that, at least in bacteria, switching in gene states is slow relative to the typical rates of active transcription and translation. Hence using the lac operon as an archetype, in such a region of operon-state switching, we present a fluctuating-rate model for this classical gene regulation module, incorporating the more realistic operon-state switching mechanism that was recently elucidated. We found that the positive feedback mechanism induces bistability (referred to as deterministic bistability), and that the parameter range for its occurrence is significantly broadened by stochastic operon-state switching. We further show that in the absence of positive feedback, operon-state switching must be extremely slow to trigger bistability by itself. However, in the presence of positive feedback, which stabilizes the induced state, the relatively slow operon-state switching kinetics within the physiological region are sufficient to stabilize the uninduced state, together generating a broadened parameter region of bistability (referred to as stochastic bistability). We illustrate the opposite phenotype-transition rate dependence upon the operon-state switching rates in the two types of bistability, with the aid of a recently proposed rate formula for fluctuating-rate models. The rate formula also predicts a maximal transition rate in the intermediate region of operon-state switching, which is validated by numerical simulations in our model. Overall, our findings suggest a biological function of transcriptional “variations” among genetically identical cells, for the emergence of bistability and transition between phenotypic states.

Identifying the mechanism underlying the coexistence of multiple stable phenotypic states has been a challenging scientific problem for more than half a century, and an appropriate mathematical model at the single-cell level is also in high demand. Single-cell measurements conducted in the past ten years have shown that gene-state switching is slow relative to the typical rates of active transcription and translation; hence the recently proposed fluctuating-rate model is a good candidate for describing the single-cell dynamics. We use the classic gene regulation module of the lac operon as an archetype and build a specific fluctuating-rate model based on the recently identified operon-state switching mechanism. This model is analyzed to dissect the interplay between positive feedback and the stochastic switching of gene states in the emergence of bistability/multistablity and the transition between phenotypic states. We show that relatively slow operon-state switching stabilizes the uninduced state and that the positive feedback stabilizes the induced state. Thus, the parameter range for bistability is significantly broadened. In addition, recently proposed landscape theory and rate formula predict opposite phenotype-transition rate dependence on operon-state switching rates for the two types of bistability.

Temporal regulation of σB by partner-switching mechanism at a distinct growth stage in Bacillus cereus

The alternative transcription factor σ^B in Bacillus cereus governs the transcription of a number of genes that confer protection against general stress. This transcription factor is regulated by protein-protein interactions among RsbV, RsbW, σ^B, RsbY, RsbM and RsbK, all encoded in the sigB cluster. Among these regulatory proteins, RsbV, RsbW and σ^B comprise a partner-switching mechanism. Under normal conditions, σ^B remains inactive by associating with anti-sigma factor RsbW, which prevents σ^B from binding to the core RNA polymerase. During environmental stress, RsbK activates RsbY to hydrolyze phosphorylated RsbV, and the dephosphorylated RsbV then sequesters RsbW to liberate σ^B from RsbW. Although the σ^B partner-switching module is thought to be the core mechanism for σ^B regulation, the actual protein-protein interactions among these three proteins in the cell remain to be investigated. In the current study, we show that RsbW and RsbV form a long-lived complex under transient stress treatment, resulting in high persistent expression of RsbV, RsbW and σ^B from mid-log phase to stationary phase. Full sequestration of RsbW by excess RsbV and increased RsbW:RsbV complex stability afforded by cellular ADP contribute to the prolonged activation of σ^B. Interestingly, the high expression levels of RsbV, RsbW and σ^B were dramatically decreased beginning from the transition stage to the stationary phase. Thus, protein interactions among σ^B partner-switching components are required for the continued induction of σ^B during environmental stress in the log phase and significant down-regulation of σ^B is observed in the stationary phase. Our data show that σ^B is temporally regulated in B. cereus.

Role of Autoregulation and Relative Synthesis of Operon Partners in Alternative Sigma Factor Networks

Despite the central role of alternative sigma factors in bacterial stress response and virulence their regulation remains incompletely understood. Here we investigate one of the best-studied examples of alternative sigma factors: the σ^B network that controls the general stress response of Bacillus subtilis to uncover widely relevant general design principles that describe the structure-function relationship of alternative sigma factor regulatory networks. We show that the relative stoichiometry of the synthesis rates of σ^B, its anti-sigma factor RsbW and the anti-anti-sigma factor RsbV plays a critical role in shaping the network behavior by forcing the σ^B network to function as an ultrasensitive negative feedback loop. We further demonstrate how this negative feedback regulation insulates alternative sigma factor activity from competition with the housekeeping sigma factor for RNA polymerase and allows multiple stress sigma factors to function simultaneously with little competitive interference.

Understanding the regulation of bacterial stress response holds the key to tackling the problems of emerging resistance to anti-bacteria’s and antibiotics. To this end, here we study one of the longest serving model systems of bacterial stress response: the σ^B pathway of Bacillus subtilis. The sigma factor σ^B controls the general stress response of Bacillus subtilis to a variety of stress conditions including starvation, antibiotics and harmful environmental perturbations. Recent studies have demonstrated that an increase in stress triggers pulsatile activation of σ^B. Using mathematical modeling we identify the core structural design feature of the network that are responsible for its pulsatile response. We further demonstrate how the same core design features are common to a variety of stress response pathways. As a result of these features, cells can respond to multiple simultaneous stresses without interference or competition between the different pathways.

Reconstruction and topological characterization of the sigma factor regulatory network of Mycobacterium tuberculosis

Accessory sigma factors, which reprogram RNA polymerase to transcribe specific gene sets, activate bacterial adaptive responses to noxious environments. Here we reconstruct the complete sigma factor regulatory network of the human pathogen Mycobacterium tuberculosis by an integrated approach. The approach combines identification of direct regulatory interactions between M. tuberculosis sigma factors in an E. coli model system, validation of selected links in M. tuberculosis, and extensive literature review. The resulting network comprises 41 direct interactions among all 13 sigma factors. Analysis of network topology reveals (i) a three-tiered hierarchy initiating at master regulators, (ii) high connectivity and (iii) distinct communities containing multiple sigma factors. These topological features are likely associated with multi-layer signal processing and specialized stress responses involving multiple sigma factors. Moreover, the identification of overrepresented network motifs, such as autoregulation and coregulation of sigma and anti-sigma factor pairs, provides structural information that is relevant for studies of network dynamics.

Sigma factors are regulatory proteins that reprogram the bacterial RNA polymerase in response to stress conditions to transcribe certain genes, including those for other sigma factors. Here, Chauhan et al. describe the complete sigma factor regulatory network of the pathogen Mycobacterium tuberculosis.

Multiple σEcfG and NepR Proteins Are Involved in the General Stress Response in Methylobacterium extorquens

In Alphaproteobacteria, the general stress response (GSR) is controlled by a conserved partner switch composed of the sigma factor σ^EcfG, its anti-sigma factor NepR and the anti-sigma factor antagonist PhyR. Many species possess paralogues of one or several components of the system, but their roles remain largely elusive. Among Alphaproteobacteria that have been genome-sequenced so far, the genus Methylobacterium possesses the largest number of σ^EcfG proteins. Here, we analyzed the six σ^EcfG paralogues of Methylobacterium extorquens AM1. We show that these sigma factors are not truly redundant, but instead exhibit major and minor contributions to stress resistance and GSR target gene expression. We identify distinct levels of regulation for the different sigma factors, as well as two NepR paralogues that interact with PhyR. Our results suggest that in M. extorquens AM1, ecfG and nepR paralogues have diverged in order to assume new roles that might allow integration of positive and negative feedback loops in the regulatory system. Comparison of the core elements of the GSR regulatory network in Methylobacterium species provides evidence for high plasticity and rapid evolution of the GSR core network in this genus.

Evolutionary tuning of protein expression levels of a positively autoregulated two-component system

Cellular adaptation relies on the development of proper regulatory schemes for accurate control of gene expression levels in response to environmental cues. Over- or under-expression can lead to diminished cell fitness due to increased costs or insufficient benefits. Positive autoregulation is a common regulatory scheme that controls protein expression levels and gives rise to essential features in diverse signaling systems, yet its roles in cell fitness are less understood. It remains largely unknown how much protein expression is 'appropriate' for optimal cell fitness under specific extracellular conditions and how the dynamic environment shapes the regulatory scheme to reach appropriate expression levels. Here, we investigate the correlation of cell fitness and output response with protein expression levels of the E. coli PhoB/PhoR two-component system (TCS). In response to phosphate (Pi)-depletion, the PhoB/PhoR system activates genes involved in phosphorus assimilation as well as genes encoding themselves, similarly to many other positively autoregulated TCSs. We developed a bacteria competition assay in continuous cultures and discovered that different Pi conditions have conflicting requirements of protein expression levels for optimal cell fitness. Pi-replete conditions favored cells with low levels of PhoB/PhoR while Pi-deplete conditions selected for cells with high levels of PhoB/PhoR. These two levels matched PhoB/PhoR concentrations achieved via positive autoregulation in wild-type cells under Pi-replete and -deplete conditions, respectively. The fitness optimum correlates with the wild-type expression level, above which the phosphorylation output saturates, thus further increase in expression presumably provides no additional benefits. Laboratory evolution experiments further indicate that cells with non-ideal protein levels can evolve toward the optimal levels with diverse mutational strategies. Our results suggest that the natural protein expression levels and feedback regulatory schemes of TCSs are evolved to match the phosphorylation output of the system, which is determined by intrinsic activities of TCS proteins.

Biochemical Systems Theory: A Review

Biochemical systems theory (BST) is the foundation for a set of analytical andmodeling tools that facilitate the analysis of dynamic biological systems. This paper depicts major developments in BST up to the current state of the art in 2012. It discusses its rationale, describes the typical strategies and methods of designing, diagnosing, analyzing, and utilizing BST models, and reviews areas of application. The paper is intended as a guide for investigators entering the fascinating field of biological systems analysis and as a resource for practitioners and experts.

Simulations of stressosome activation emphasize allosteric interactions between RsbR and RsbT

BACKGROUND

The stressosome is a bacterial signalling complex that responds to environmental changes by initiating a protein partner switching cascade, which leads to the release of the alternative sigma factor, σB. Stress perception increases the phosphorylation of the stressosome sensor protein, RsbR, and the scaffold protein, RsbS, by the protein kinase, RsbT. Subsequent dissociation of RsbT from the stressosome activates the σB cascade. However, the sequence of physical events that occur in the stressosome during signal transduction is insufficiently understood.

RESULTS

Here, we use computational modelling to correlate the structure of the stressosome with the efficiency of the phosphorylation reactions that occur upon activation by stress. In our model, the phosphorylation of any stressosome protein is dependent upon its nearest neighbours and their phosphorylation status. We compare different hypotheses about stressosome activation and find that only the model representing the allosteric activation of the kinase RsbT, by phosphorylated RsbR, qualitatively reproduces the experimental data.

CONCLUSIONS

Our simulations and the associated analysis of published data support the following hypotheses: (i) a simple Boolean model is capable of reproducing stressosome dynamics, (ii) different stressors induce identical stressosome activation patterns, and we also confirm that (i) phosphorylated RsbR activates RsbT, and (ii) the main purpose of RsbX is to dephosphorylate RsbS-P.

Interplay of gene expression noise and ultrasensitive dynamics affects bacterial operon organization

Bacterial chromosomes are organized into polycistronic cotranscribed operons, but the evolutionary pressures maintaining them are unclear. We hypothesized that operons alter gene expression noise characteristics, resulting in selection for or against maintaining operons depending on network architecture. Mathematical models for 6 functional classes of network modules showed that three classes exhibited decreased noise and 3 exhibited increased noise with same-operon cotranscription of interacting proteins. Noise reduction was often associated with a decreased chance of reaching an ultrasensitive threshold. Stochastic simulations of the lac operon demonstrated that the predicted effects of transcriptional coupling hold for a complex network module. We employed bioinformatic analysis to find overrepresentation of noise-minimizing operon organization compared with randomized controls. Among constitutively expressed physically interacting protein pairs, higher coupling frequencies appeared at lower expression levels, where noise effects are expected to be dominant. Our results thereby suggest an important role for gene expression noise, in many cases interacting with an ultrasensitive switch, in maintaining or selecting for operons in bacterial chromosomes.

In some species, most notably bacteria, chromosomal genes are arranged into clusters called operons. In operons, the process of transcription is physically coupled: a single pass of the RNA polymerase enzyme reading that region of the chromosome simultaneously produces messenger RNA encoding multiple proteins. So far, we do not have a satisfying explanation for what evolutionary forces have maintained operons on bacterial chromosomes. We hypothesized that different types of interactions between operon-coded proteins affect how strongly operons are selected for between two genes. The proposed mechanism for this effect is that operons correlate gene expression noise, changing how it manifests in the post-translational network depending on the type of protein interaction. Mathematical models demonstrate that operons reduce noise for some types of interactions but not others. We found that operon-dependent noise reduction has an underlying dependence on surprisingly high sensitivity of the network to the ratio of proteins from each gene. Databases of genetic information show that E. coli has operons more frequently than random if operons reduce noise for the type of interaction various gene pairs have, but not otherwise. Our study thus provides an example of how the architecture of post-translational networks affects bacterial evolution.

Two surfaces of a conserved interdomain linker differentially affect output from the RST sensing module of the Bacillus subtilis stressosome

The stressosome is a 1.8-MDa cytoplasmic complex that conveys environmental signals to the σ(B) stress factor of Bacillus subtilis. A functionally irreducible complex contains multiple copies of three proteins: the RsbRA coantagonist, RsbS antagonist, and RsbT serine-threonine kinase. Homologues of these proteins are coencoded in different genome contexts in diverse bacteria, forming a versatile sensing and transmission module called RST after its common constituents. However, the signaling pathway within the stressosome itself is not well defined. The N-terminal, nonheme globin domains of RsbRA project from the stressosome and are presumed to channel sensory input to the C-terminal STAS domains that form the complex core. A conserved, 13-residue α-helical linker connects these domains. We probed the in vivo role of the linker using alanine scanning mutagenesis, assaying stressosome output in B. subtilis via a σ(B)-dependent reporter fusion. Substitutions at four conserved residues increased output 4- to 30-fold in unstressed cells, whereas substitutions at four nonconserved residues significantly decreased output. The periodicity of these effects supports a model in which RsbRA functions as a dimer in vivo, with the linkers forming parallel paired helices via a conserved interface. The periodicity further suggests that the opposite, nonconserved faces make additional contacts important for efficient stressosome operation. These results establish that the linker influences stressosome output under steady-state conditions. However, the stress response phenotypes of representative linker substitutions provide less support for the notion that the N-terminal globin domain senses acute environmental challenge and transmits this information via the linker helix.

Non-transcriptional regulatory processes shape transcriptional network dynamics

Information about the extra- or intracellular environment is often captured as biochemical signals that propagate through regulatory networks. These signals eventually drive phenotypic changes, typically by altering gene expression programmes in the cell. Reconstruction of transcriptional regulatory networks has given a compelling picture of bacterial physiology, but transcriptional network maps alone often fail to describe phenotypes. Cellular response dynamics are ultimately determined by interactions between transcriptional and non-transcriptional networks, with dramatic implications for physiology and evolution. Here, we provide an overview of non-transcriptional interactions that can affect the performance of natural and synthetic bacterial regulatory networks.

Stochastic pulse regulation in bacterial stress response

Gene regulatory circuits can use dynamic, and even stochastic, strategies to respond to environmental conditions. We examined activation of the general stress response mediated by the alternative sigma factor, σ(B), in individual Bacillus subtilis cells. We observed that energy stress activates σ(B) in discrete stochastic pulses, with increasing levels of stress leading to higher pulse frequencies. By perturbing and rewiring the endogenous system, we found that this behavior results from three key features of the σ(B) circuit: an ultrasensitive phosphorylation switch; stochasticity ("noise"), which activates that switch; and a mixed (positive and negative) transcriptional feedback, which can both amplify a pulse and switch it off. Together, these results show how prokaryotes encode signals using stochastic pulse frequency modulation through a compact regulatory architecture.

In vivo phosphorylation patterns of key stressosome proteins define a second feedback loop that limits activation of Bacillus subtilis σB

The Bacillus subtilis stressosome is a 1.8 MDa complex that orchestrates activation of the σ(B) transcription factor by environmental stress. The complex comprises members of the RsbR co-antagonist family and the RsbS antagonist, which together form an icosahedral core that sequesters the RsbT serine-threonine kinase. Phosphorylation of this core by RsbT is associated with RsbT release, which activates downstream signalling. RsbRA, the prototype co-antagonist, is phosphorylated on T171 and T205 in vitro. In unstressed cells T171 is already phosphorylated; this is a prerequisite but not the trigger for activation, which correlates with stress-induced phosphorylation of RsbS on S59. In contrast, phosphorylation of RsbRA T205 has not been detected in vivo. Here we find (i) RsbRA is additionally phosphorylated on T205 following strong stresses, (ii) this modification requires RsbT, and (iii) the phosphorylation-deficient T205A substitution greatly increases post-stress activation of σ(B) . We infer that T205 phosphorylation constitutes a second feedback mechanism to limit σ(B) activation, operating in addition to the RsbX feedback phosphatase. Loss of RsbX function increases the fraction of phosphorylated RsbS and doubly phosphorylated RsbRA in unstressed cells. We propose that RsbX both maintains the ready state of the stressosome prior to stress and restores it post-stress.

Bistable responses in bacterial genetic networks: designs and dynamical consequences

A key property of living cells is their ability to react to stimuli with specific biochemical responses. These responses can be understood through the dynamics of underlying biochemical and genetic networks. Evolutionary design principles have been well studied in networks that display graded responses, with a continuous relationship between input signal and system output. Alternatively, biochemical networks can exhibit bistable responses so that over a range of signals the network possesses two stable steady states. In this review, we discuss several conceptual examples illustrating network designs that can result in a bistable response of the biochemical network. Next, we examine manifestations of these designs in bacterial master-regulatory genetic circuits. In particular, we discuss mechanisms and dynamic consequences of bistability in three circuits: two-component systems, sigma-factor networks, and a multistep phosphorelay. Analyzing these examples allows us to expand our knowledge of evolutionary design principles networks with bistable responses.

How mathematical modelling elucidates signalling in Bacillus subtilis

Appropriate stimulus perception, signal processing and transduction ensure optimal adaptation of bacteria to environmental challenges. In the Gram-positive model bacterium Bacillus subtilis signalling networks and molecular interactions therein are well-studied, making this species a suitable candidate for the application of mathematical modelling. Here, we review systems biology approaches, focusing on chemotaxis, sporulation, σ(B) -dependent general stress response and competence. Processes like chemotaxis and Z-ring assembly depend critically on the subcellular localization of proteins. Environmental response strategies, including sporulation and competence, are characterized by phenotypic heterogeneity in isogenic cultures. The examples of mathematical modelling also include investigations that have demonstrated how operon structure and signalling dynamics are intricately interwoven to establish optimal responses. Our review illustrates that these interdisciplinary approaches offer new insights into the response of B. subtilis to environmental challenges. These case studies reveal modelling as a tool to increase the understanding of complex systems, to help formulating hypotheses and to guide the design of more directed experiments that test predictions.

Prokaryotic gene clusters: a rich toolbox for synthetic biology

Bacteria construct elaborate nanostructures, obtain nutrients and energy from diverse sources, synthesize complex molecules, and implement signal processing to react to their environment. These complex phenotypes require the coordinated action of multiple genes, which are often encoded in a contiguous region of the genome, referred to as a gene cluster. Gene clusters sometimes contain all of the genes necessary and sufficient for a particular function. As an evolutionary mechanism, gene clusters facilitate the horizontal transfer of the complete function between species. Here, we review recent work on a number of clusters whose functions are relevant to biotechnology. Engineering these clusters has been hindered by their regulatory complexity, the need to balance the expression of many genes, and a lack of tools to design and manipulate DNA at this scale. Advances in synthetic biology will enable the large-scale bottom-up engineering of the clusters to optimize their functions, wake up cryptic clusters, or to transfer them between organisms. Understanding and manipulating gene clusters will move towards an era of genome engineering, where multiple functions can be "mixed-and-matched" to create a designer organism.

The interplay of multiple feedback loops with post-translational kinetics results in bistability of mycobacterial stress response

Bacterial persistence is the phenomenon in which a genetically identical fraction of a bacterial population can survive exposure to stress by reduction or cessation of growth. Persistence in mycobacteria has been recently linked to a stress-response network, consisting of the MprA/MprB two-component system and alternative sigma factor sigma(E). This network contains multiple positive transcriptional feedback loops which may give rise to bistability, making it a good candidate for controlling the mycobacterial persistence switch. To analyze the possibility of bistability, we develop a method that involves decoupling of the network into transcriptional and post-translational interaction modules. As a result we reduce the dimensionality of the dynamical system and independently analyze input-output relations in the two modules to formulate a necessary condition for bistability in terms of their logarithmic gains. We show that neither the positive autoregulation in the MprA/MprB network nor the sigma(E)-mediated transcriptional feedback is sufficient to induce bistability in a biochemically realistic parameter range. Nonetheless, inclusion of the post-translational regulation of sigma(E) by RseA increases the effective cooperativity of the system, resulting in bistability that is robust to parameter variation. We predict that overexpression or deletion of RseA, the key element controlling the ultrasensitive response, can eliminate bistability.

Biological role of noise encoded in a genetic network motif

Genetic circuits that regulate distinct cellular processes can differ in their wiring pattern of interactions (architecture) and susceptibility to stochastic fluctuations (noise). Whether the link between circuit architecture and noise is of biological importance remains, however, poorly understood. To investigate this problem, we performed a computational study of gene expression noise for all possible circuit architectures of feed-forward loop (FFL) motifs. Results revealed that FFL architectures fall into two categories depending on whether their ON (stimulated) or OFF (unstimulated) steady states exhibit noise. To explore the biological importance of this difference in noise behavior, we analyzed 858 documented FFLs in Escherichia coli that were divided into 39 functional categories. The majority of FFLs were found to regulate two subsets of functional categories. Interestingly, these two functional categories associated with FFLs of opposite noise behaviors. This opposite noise preference revealed two noise-based strategies to cope with environmental constraints where cellular responses are either initiated or terminated stochastically to allow probabilistic sampling of alternative states. FFLs may thus be selected for their architecture-dependent noise behavior, revealing a biological role for noise that is encoded in gene circuit architectures.

Physical and antibiotic stresses require activation of the RsbU phosphatase to induce the general stress response in Listeria monocytogenes

Among pathogenic strains of Listeria monocytogenes, the σ^B transcription factor has a pivotal role in the outcome of food-borne infections. This factor is activated by diverse stresses to provide general protection against multiple challenges, including those encountered during gastrointestinal passage. It also acts with the PrfA regulator to control virulence genes needed for entry into intestinal lumen cells. Environmental and nutritional signals modulate σ^B activity via a network that operates by the partner switching mechanism, in which protein interactions are controlled by serine phosphorylation. This network is well characterized in the related bacterium Bacillus subtilis. A key difference in Listeria is the presence of only one input phosphatase, RsbU, instead of the two found in B. subtilis. Here, we aim to determine whether this sole phosphatase is required to convey physical, antibiotic and nutritional stress signals, or if additional pathways might exist. To that end, we constructed L. monocytogenes 10403S strains bearing single-copy, σ^B-dependent opuCA–lacZ reporter fusions to determine the effects of an rsbU deletion under physiological conditions. All stresses tested, including acid, antibiotic, cold, ethanol, heat, osmotic and nutritional challenge, required RsbU to activate σ^B. This was of particular significance for cold stress activation, which occurs via a phosphatase-independent mechanism in B. subtilis. We also assayed the effects of the D80N substitution in the upstream RsbT regulator that activates RsbU. The mutant had a phenotype consistent with low and uninducible phosphatase activity, but nonetheless responded to nutritional stress. We infer that RsbU activity but not its induction is required for nutritional signalling, which would enter the network downstream from RsbU.

Adaptable functionality of transcriptional feedback in bacterial two-component systems

A widespread mechanism of bacterial signaling occurs through two-component systems, comprised of a sensor histidine kinase (SHK) and a transcriptional response regulator (RR). The SHK activates RR by phosphorylation. The most common two-component system structure involves expression from a single operon, the transcription of which is activated by its own phosphorylated RR. The role of this feedback is poorly understood, but it has been associated with an overshooting kinetic response and with fast recovery of previous interrupted signaling events in different systems. Mathematical models show that overshoot is only attainable with negative feedback that also improves response time. Our models also predict that fast recovery of previous interrupted signaling depends on high accumulation of SHK and RR, which is more likely in a positive feedback regime. We use Monte Carlo sampling of the parameter space to explore the range of attainable model behaviors. The model predicts that the effective feedback sign can change from negative to positive depending on the signal level. Variations in two-component system architectures and parameters may therefore have evolved to optimize responses in different bacterial lifestyles. We propose a conceptual model where low signal conditions result in a responsive system with effectively negative feedback while high signal conditions with positive feedback favor persistence of system output.

Bacteria have evolved various mechanisms for surviving unpredictable changes and stresses in the environment, such as nutrient limitation. One common survival mechanism is the two-component system, where a sensor protein responds to a particular type of stress by activating a regulator in the cell. These regulators can in turn activate genes that produce proteins for stress-appropriate responses. The activated regulator often positively regulates transcription of its own operon containing the sensor and regulator genes leading to a feedback loop. This is interesting, because positive feedback is usually associated with a slower response time than negative feedback and therefore negative feedback would often be selected for by evolution. Here we analyze a mathematical model to study the interplay of this feedback and postranslational mechanisms regulating two-component system signaling. We found that modulation of regulator activity by its operon partner can lead to overall negative feedback to result from autoactivation. This happens if (1) the sensor can both activate and deactivate the regulator, and (2) there is some reaction resulting in regulator activation independently of its cognate sensor. As a result our model predicts that two-component systems may be capable of flexibly switching between positive and negative feedback depending on different circumstances, allowing for appropriate responses in a variety of conditions.

Quiet gene circuit more fragile than its noisy peer

Why is a particular architecture for a pathway chosen over seemingly equivalent alternatives? Cağatay et al. (2009) use a synthetic biology approach to show that fluctuations--or noise--in protein levels may play a key role in determining which network design is selected during evolution.

orf4 of the Bacillus cereus sigB gene cluster encodes a general stress-inducible Dps-like bacterioferritin

The function of orf4 in the sigB cluster in Bacillus cereus ATCC 14579 remains to be explored. Amino-acid sequence analysis has revealed that Orf4 is homologous with bacterioferritins and Dps. In this study, we generated an orf4-null mutant and produced recombinant protein rOrf4 to establish the role of orf4. In vitro, the purified rOrf4 was found to exist in two distinct forms, a dimeric form and a polymer form, through size exclusion analysis. The latter form exhibited a unique filament structure, in contrast to the typical spherical tetracosamer structure of bacterioferritins; the former can be induced to form rOrf4 polymers immediately after the addition of FeCl(2). Catalysis of the oxidation of ferrous irons by ferroxidase activity was detected with rOrf4, and the mineralized irons were subsequently sequestered only in the rOrf4 polymer. Moreover, rOrf4 exerted DNA-protective activity against oxidative damage via DNA binding in a nonspecific manner, as is seen with Dps. In vivo, deletion of orf4 had no effect on activation of the alternative sigma factor sigma(B), and therefore, orf4 is not associated with sigma(B) regulation; however, orf4 can be significantly upregulated upon environmental stress but not H(2)O(2) treatment. B. cereus strains with constitutive Orf4 expression exhibited a viability higher than that of the orf4-null mutant, under specific oxidative stress or heat shock. Taken together, these results suggest that Orf4 functions as a Dps-like bacterioferritin in response to environmental stress and can provide cell protection from oxidative damage through iron sequestration and DNA binding.

Role of RsbU in controlling SigB activity in Staphylococcus aureus following alkaline stress

SigB is an alternative sigma factor that controls a large regulon in Staphylococcus aureus. Activation of SigB requires RsbU, a protein phosphatase 2C (PP2C)-type phosphatase. In a closely related organism, Bacillus subtilis, RsbU activity is stimulated upon interaction with RsbT, a kinase, which following an activating stimulus switches from a 25S high-molecular-weight complex, the stressosome, to the N-terminal domain of RsbU. Active RsbU dephosporylates RsbV and thereby triggers the release of SigB from its inhibitory complex with RsbW. While RsbU, RsbV, RsbW, and SigB are conserved in S. aureus, proteins similar to RsbT and the components of the stressosome are not, raising the question of how RsbU activity and hence SigB activity are controlled in S. aureus. We found that in contrast to the case in B. subtilis, the induced expression of RsbU was sufficient to stimulate SigB-dependent transcription in S. aureus. However, activation of SigB-dependent transcription following alkaline stress did not lead to a clear accumulation of SigB and its regulators RsbV and RsbW or to a change in the RsbV/RsbV-P ratio in S. aureus. When expressed in B. subtilis, the S. aureus RsbU displayed a high activity even in the absence of an inducing stimulus. This high activity could be transferred to the PP2C domain of the B. subtilis RsbU protein by a fusion to the N-terminal domain of the S. aureus RsbU. Collectively, the data suggest that the activity of the S. aureus RsbU and hence SigB may be subjected to different regulation in comparison to that in B. subtilis.

Quantifying global tolerance of biochemical systems: design implications for moiety-transfer cycles

Robustness of organisms is widely observed although difficult to precisely characterize. Performance can remain nearly constant within some neighborhood of the normal operating regime, leading to homeostasis, but then abruptly break down with pathological consequences beyond this neighborhood. Currently, there is no generic approach to identifying boundaries where local performance deteriorates abruptly, and this has hampered understanding of the molecular basis of biological robustness. Here we introduce a generic approach for characterizing boundaries between operational regimes based on the piecewise power-law representation of the system's components. This conceptual framework allows us to define “global tolerance” as the ratio between the normal value of a parameter and the value at such a boundary. We illustrate the utility of this concept for a class of moiety-transfer cycles, which is a widespread module in biology. Our results show a region of “best” local performance surrounded by “poor” regions; also, selection for improved local performance often pushes the operating values away from regime boundaries, thus increasing global tolerance. These predictions agree with experimental data from the reduced nicotinamide adenine dinucleotide phosphate (NADPH) redox cycle of human erythrocytes.

The ability of organisms to survive under a multitude of conditions is readily apparent. This robustness in performance is difficult to precisely characterize and quantify. At a biochemical level, it leads to physiological behavior when the parameters of the system remain within some neighborhood of their normal values. However, this behavior can change abruptly, often becoming pathological, as the boundary of the neighborhood is crossed. Currently, there is no generic approach to identifying and characterizing such boundaries. In this paper, we address the problem by introducing a method that involves quantitative concepts for boundaries between regions and “global tolerance”. To illustrate the power of these concepts, we analyzed a large class of biological modules called moiety-transfer cycles and characterized the specific case of the NADPH redox cycle in human erythrocytes, which is involved in conferring resistance to malaria. Our results show that the wild-type system operates well within a region of “best” local performance that is surrounded by “poor” regions.

Regulation of the mazEF toxin-antitoxin module in Staphylococcus aureus and its impact on sigB expression

In Staphylococcus aureus, the sigB operon codes for the alternative sigma factor sigma(B) and its regulators that enable the bacteria to rapidly respond to environmental stresses via redirection of transcriptional priorities. However, a full model of sigma(B) regulation in S. aureus has not yet emerged. Earlier data has suggested that mazEF, a toxin-antitoxin (TA) module immediately upstream of the sigB operon, was transcribed with the sigB operon. Here we demonstrate that the promoter P(mazE) upstream of mazEF is essential for full sigma(B) activity and that instead of utilizing autorepression typical of TA systems, sigB downregulates this promoter, providing a negative-feedback loop for sigB to repress its own transcription. We have also found that the transcriptional regulator SarA binds and activates P(mazE). In addition, P(mazE) was shown to respond to environmental and antibiotic stresses in a way that provides an additional layer of control over sigB expression. The antibiotic response also appears to occur in two other TA systems in S. aureus, indicating a shared mechanism of regulation.