The Bacillus subtilis sin operon: an evolvable network motif

Genetic circuit characterization by inferring RNA polymerase movement and ribosome usage

To perform their computational function, genetic circuits change states through a symphony of genetic parts that turn regulator expression on and off. Debugging is frustrated by an inability to characterize parts in the context of the circuit and identify the origins of failures. Here, we take snapshots of a large genetic circuit in different states: RNA-seq is used to visualize circuit function as a changing pattern of RNA polymerase (RNAP) flux along the DNA. Together with ribosome profiling, all 54 genetic parts (promoters, ribozymes, RBSs, terminators) are parameterized and used to inform a mathematical model that can predict circuit performance, dynamics, and robustness. The circuit behaves as designed; however, it is riddled with genetic errors, including cryptic sense/antisense promoters and translation, attenuation, incorrect start codons, and a failed gate. While not impacting the expected Boolean logic, they reduce the prediction accuracy and could lead to failures when the parts are used in other designs. Finally, the cellular power (RNAP and ribosome usage) required to maintain a circuit state is calculated. This work demonstrates the use of a small number of measurements to fully parameterize a regulatory circuit and quantify its impact on host.

Clostridioides difficile SinR' regulates toxin, sporulation and motility through protein-protein interaction with SinR

Clostridioides difficile is a Gram-positive, anaerobic bacterium. It is known that C. difficile is one of the major causes of antibiotic associated diarrhea. The enhanced antibiotic resistance observed in C. difficile is the result of highly resistant spores produced by the bacterium. In Bacillus subtilis, the sin operon is involved in sporulation inhibition. Two proteins coded within this operon, SinR and SinI, have an antagonistic relationship; SinR acts as an inhibitor to sporulation whereas SinI represses the activity of SinR, thus allowing the bacterium to sporulate. In a previous study, we examined the sin locus in C. difficile and named the two genes associated with this operon sinR and sinR', analogous to sinR and sinI in B. subtilis, respectively. We have shown that SinR and SinR' have pleiotropic roles in pathogenesis pathways and interact antagonistically with each other. Unlike B. subtilis SinI, SinR' in C. difficile carries two domains: the HTH domain and the Multimerization Domain (MD). In this study, we first performed a GST Pull-down experiment to determine the domain within SinR' that interacts with SinR. Second, the effect of these two domains on three phenotypes; sporulation, motility, and toxin production was examined. The findings of this study confirmed the prediction that the Multimerization Domain (MD) of SinR' is responsible for the interaction between SinR and SinR'. It was also discovered that SinR' regulates sporulation, toxin production and motility primarily by inhibiting SinR activity through the Multimerization Domain (MD).

Cellular checkpoint control using programmable sequential logic

Biological processes that require orderly progression, such as growth and differentiation, proceed via regulatory checkpoints where the cell waits for signals before continuing to the next state. Implementing such control would allow genetic engineers to divide complex tasks into stages. We present genetic circuits that encode sequential logic to instruct Escherichia coli to proceed through a linear or cyclical sequence of states. These are built with 11 set-reset latches, designed with repressor-based NOR gates, which can connect to each other and sensors. The performance of circuits with up to three latches and four sensors, including a gated D latch, closely match predictions made by using nonlinear dynamics. Checkpoint control is demonstrated by switching cells between multiple circuit states in response to external signals over days.

Self-Amplifying Pulsatile Protein Dynamics without Positive Feedback

Many proteins exhibit dynamic activation patterns in the form of irregular pulses. Such behavior is typically attributed to a combination of positive and negative feedback loops in the underlying regulatory network. However, the presence of positive feedbacks is difficult to demonstrate unequivocally, raising the question of whether stochastic pulses can arise from negative feedback only. Here, we use the protein kinase A (PKA) system, a key regulator of the yeast pulsatile transcription factor Msn2, as a case example to show that irregular pulses of protein activity can arise from a negative feedback loop alone. Simplification to two variables reveals that a combination of zero-order ultrasensitivity, timescale separation between the activator and the repressor, and an effective delay in the feedback are sufficient to amplify a perturbation into a pulse. The same circuit topology can account for both activation and inactivation pulses, pointing toward a general mechanism of stochastic pulse generation.

Pleiotropic roles of Clostridium difficile sin locus

Clostridium difficile is the primary cause of nosocomial diarrhea and pseudomembranous colitis. It produces dormant spores, which serve as an infectious vehicle responsible for transmission of the disease and persistence of the organism in the environment. In Bacillus subtilis, the sin locus coding SinR (113 aa) and SinI (57 aa) is responsible for sporulation inhibition. In B. subtilis, SinR mainly acts as a repressor of its target genes to control sporulation, biofilm formation, and autolysis. SinI is an inhibitor of SinR, so their interaction determines whether SinR can inhibit its target gene expression. The C. difficile genome carries two sinR homologs in the operon that we named sinR and sinR’, coding for SinR (112 aa) and SinR’ (105 aa), respectively. In this study, we constructed and characterized sin locus mutants in two different C. difficile strains R20291 and JIR8094, to decipher the locus’s role in C. difficile physiology. Transcriptome analysis of the sinRR’ mutants revealed their pleiotropic roles in controlling several pathways including sporulation, toxin production, and motility in C. difficile. Through various genetic and biochemical experiments, we have shown that SinR can regulate transcription of key regulators in these pathways, which includes sigD, spo0A, and codY. We have found that SinR’ acts as an antagonist to SinR by blocking its repressor activity. Using a hamster model, we have also demonstrated that the sin locus is needed for successful C. difficile infection. This study reveals the sin locus as a central link that connects the gene regulatory networks of sporulation, toxin production, and motility; three key pathways that are important for C. difficile pathogenesis.

In Bacillus subtilis, sporulation, competence and biofilm formation are regulated by a pleiotropic regulator called SinR. Two sinR homologs are present in C. difficile genome as an operon and henceforth labeled as sinR and sinR’. Our detailed investigation revealed that in C. difficile, the SinR and SinR’ are key master regulators needed for the regulation of several pathways including sporulation, toxin production, and motility.

Reconfigurable Analog Signal Processing by Living Cells

Living cells are known for their capacity for versatile signal processing, particularly the ability to respond differently to the same stimuli using biochemical networks that integrate environmental signals and reconfigure their dynamic responses. However, the complexity of natural biological networks confounds the discovery of fundamental mechanisms behind versatile signaling. Here, we study one specific aspect of reconfigurable signal processing in which a minimal biological network integrates two signals, using one to reconfigure the network's transfer function with respect to the other, producing an emergent switch between induction and repression. In contrast to known mechanisms, the new mechanism reconfigures transfer functions through genetic networks without extensive protein-protein interactions. These results provide a novel explanation for the versatility of genetic programs, and suggest a new mechanism of signal integration that may govern flexibility and plasticity of gene expression.

Elements of biological oscillations in time and space

Oscillations in time and space are ubiquitous in nature and play critical roles in dynamic cellular processes. Although the molecular mechanisms underlying the generation of the dynamics are diverse, several distinct regulatory elements have been recognized as being critical in producing and modulating oscillatory dynamics. These include negative and positive feedback, time delay, nonlinearity in regulation, and random fluctuations ('noise'). Here we discuss the specific roles of these five elements in promoting or attenuating oscillatory dynamics, by drawing on insights from quantitative analyses of natural or synthetic biological networks.

Modeling of the ComRS Signaling Pathway Reveals the Limiting Factors Controlling Competence in Streptococcus thermophilus

In streptococci, entry in competence is dictated by ComX abundance. In Streptococcus thermophilus, production of ComX is transient and tightly regulated during growth: it is positively regulated by the cell-cell communication system ComRS during the activation phase and negatively regulated during the shut-off phase by unidentified late competence gene(s). Interestingly, most S. thermophilus strains are not or weakly transformable in permissive growth conditions (i.e., chemically defined medium, CDM), suggesting that some players of the ComRS regulatory pathway are limiting. Here, we combined mathematical modeling and experimental approaches to identify the components of the ComRS system which are critical for both dynamics and amplitude of ComX production in S. thermophilus. We built a deterministic, population-scaled model of the time-course regulation of specific ComX production in CDM growth conditions. Strains LMD-9 and LMG18311 were respectively selected as representative of highly and weakly transformable strains. Results from in silico simulations and in vivo luciferase activities show that ComR concentration is the main limiting factor for the level of comX expression and controls the kinetics of spontaneous competence induction in strain LMD-9. In addition, the model predicts that the poor transformability of strain LMG18311 results from a 10-fold lower comR expression level compared to strain LMD-9. In agreement, comR overexpression in both strains was shown to induce higher competence levels with deregulated kinetics patterns during growth. In conclusion, we propose that the level of ComR production is one important factor that could explain competence heterogeneity among S. thermophilus strains.

Cis-Antisense Transcription Gives Rise to Tunable Genetic Switch Behavior: A Mathematical Modeling Approach

Antisense transcription has been extensively recognized as a regulatory mechanism for gene expression across all kingdoms of life. Despite the broad importance and extensive experimental determination of cis-antisense transcription, relatively little is known about its role in controlling cellular switching responses. Growing evidence suggests the presence of non-coding cis-antisense RNAs that regulate gene expression via antisense interaction. Recent studies also indicate the role of transcriptional interference in regulating expression of neighboring genes due to traffic of RNA polymerases from adjacent promoter regions. Previous models investigate these mechanisms independently, however, little is understood about how cells utilize coupling of these mechanisms in advantageous ways that could also be used to design novel synthetic genetic devices. Here, we present a mathematical modeling framework for antisense transcription that combines the effects of both transcriptional interference and cis-antisense regulation. We demonstrate the tunability of transcriptional interference through various parameters, and that coupling of transcriptional interference with cis-antisense RNA interaction gives rise to hypersensitive switches in expression of both antisense genes. When implementing additional positive and negative feed-back loops from proteins encoded by these genes, the system response acquires a bistable behavior. Our model shows that combining these multiple-levels of regulation allows fine-tuning of system parameters to give rise to a highly tunable output, ranging from a simple-first order response to biologically complex higher-order response such as tunable bistable switch. We identify important parameters affecting the cellular switch response in order to provide the design principles for tunable gene expression using antisense transcription. This presents an important insight into functional role of antisense transcription and its importance towards design of synthetic biological switches.

Principles of genetic circuit design

Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.

Design of orthogonal genetic switches based on a crosstalk map of σs, anti-σs, and promoters

Cells react to their environment through gene regulatory networks. Network integrity requires minimization of undesired crosstalk between their biomolecules. Similar constraints also limit the use of regulators when building synthetic circuits for engineering applications. Here, we mapped the promoter specificities of extracytoplasmic function (ECF) σs as well as the specificity of their interaction with anti-σs. DNA synthesis was used to build 86 ECF σs (two from every subgroup), their promoters, and 62 anti-σs identified from the genomes of diverse bacteria. A subset of 20 σs and promoters were found to be highly orthogonal to each other. This set can be increased by combining the -35 and -10 binding domains from different subgroups to build chimeras that target sequences unrepresented in any subgroup. The orthogonal σs, anti-σs, and promoters were used to build synthetic genetic switches in Escherichia coli. This represents a genome-scale resource of the properties of ECF σs and a resource for synthetic biology, where this set of well-characterized regulatory parts will enable the construction of sophisticated gene expression programs.

Modeling gene expression in time and space

Cell populations rarely exhibit gene-expression profiles that are homogeneous in time and space. In the temporal domain, dynamical behaviors such as oscillations and pulses of protein production pervade cell biology, underlying phenomena as diverse as circadian rhythmicity, cell cycle control, stress and damage responses, and stem-cell pluripotency. In multicellular populations, spatial heterogeneities are crucial for decision making and development, among many other functions. Cells need to exquisitely coordinate this temporal and spatial variation to survive. Although the spatiotemporal character of gene expression is challenging to quantify experimentally at the level of individual cells, it is beneficial from the modeling viewpoint, because it provides strong constraints that can be probed by theoretically analyzing mathematical models of candidate gene and protein circuits. Here, we review recent examples of temporal dynamics and spatial patterning in gene expression to show how modeling such phenomenology can help us unravel the molecular mechanisms of cellular function.

Molecular mechanisms of multiple toxin-antitoxin systems are coordinated to govern the persister phenotype

Toxin-antitoxin systems are ubiquitous and have been implicated in persistence, the multidrug tolerance of bacteria, biofilms, and, by extension, most chronic infections. However, their purpose, apparent redundancy, and coordination remain topics of debate. Our model relates molecular mechanisms to population dynamics for a large class of toxin-antitoxin systems and suggests answers to several of the open questions. The generic architecture of toxin-antitoxin systems provides the potential for bistability, and even when the systems do not exhibit bistability alone, they can be coupled to create a strongly bistable, hysteretic switch between normal and toxic states. Stochastic fluctuations can spontaneously switch the system to the toxic state, creating a heterogeneous population of growing and nongrowing cells, or persisters, that exist under normal conditions, rather than as an induced response. Multiple toxin-antitoxin systems can be cooperatively marshaled for greater effect, with the dilution determined by growth rate serving as the coordinating signal. The model predicts and elucidates experimental results that show a characteristic correlation between persister frequency and the number of toxin-antitoxin systems.

The putative influence of the agr operon upon survival mechanisms used by Clostridium acetobutylicum

The bacterium Clostridium acetobutylicum produces acids as an energy-yielding process during exponential growth. An acidic environment, however, is toxic to the cells and two survival mechanisms are in place to prevent them from dying. Firstly, during a solventogenesis phase, the cells take up these acids and convert them to solvents, thus raising the environmental pH. Secondly, the cells undergo sporulation to form highly resistant spores capable of surviving extreme conditions. One possible regulatory mechanism for these processes is the accessory gene regulatory (agr) quorum-sensing system, which is thought to coordinate cell population density with cell phenotype. We model this system to monitor its putative effect upon solventogenesis and the sporulation-initiation network responsible for triggering spore formation. We demonstrate that a high population density should be able to induce both solventogenesis and sporulation, with variations to the parameter set allowing sporulation alone to be triggered; additional distinct signals are capable of restoring the solventogenic response. We compare the agr system of C. acetobutylicum with that of Staphylococcus aureus in order to investigate why the differences in feedback between the two systems may have evolved. Our findings indicate that, depending upon the mechanism of interaction between the agr system and the sporulation-initiation network, the clostridial agr circuitry may be in place either to moderate the number of spores that are formed (in order for this number to reflect the urgency of the situation), or simply as an energy-saving strategy.

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.

Prediction by promoter logic in bacterial quorum sensing

Quorum-sensing systems mediate chemical communication between bacterial cells, coordinating cell-density-dependent processes like biofilm formation and virulence-factor expression. In the proteobacterial LuxI/LuxR quorum sensing paradigm, a signaling molecule generated by an enzyme (LuxI) diffuses between cells and allosterically stimulates a transcriptional regulator (LuxR) to activate its cognate promoter (pR). By expressing either LuxI or LuxR in positive feedback from pR, these versatile systems can generate smooth (monostable) or abrupt (bistable) density-dependent responses to suit the ecological context. Here we combine theory and experiment to demonstrate that the promoter logic of pR - its measured activity as a function of LuxI and LuxR levels - contains all the biochemical information required to quantitatively predict the responses of such feedback loops. The interplay of promoter logic with feedback topology underlies the versatility of the LuxI/LuxR paradigm: LuxR and LuxI positive-feedback systems show dramatically different responses, while a dual positive/negative-feedback system displays synchronized oscillations. These results highlight the dual utility of promoter logic: to probe microscopic parameters and predict macroscopic phenotype.

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.

Convergent transcription in the butyrolactone regulon in Streptomyces coelicolor confers a bistable genetic switch for antibiotic biosynthesis

cis-encoded antisense RNAs (cis asRNA) have been reported to participate in gene expression regulation in both eukaryotic and prokaryotic organisms. Its presence in Streptomyces coelicolor has also been reported recently; however, its role has yet to be fully investigated. Using mathematical modeling we explore the role of cis asRNA produced as a result of convergent transcription in scbA-scbR genetic switch. scbA and scbR gene pair, encoding repressor–amplifier proteins respectively, mediates the synthesis of a signaling molecule, the γ-butyrolactone SCB1 and controls the onset of antibiotic production. Our model considers that transcriptional interference caused by convergent transcription of two opposing RNA polymerases results in fatal collision and transcriptional termination, which suppresses transcription efficiency. Additionally, convergent transcription causes sense and antisense interactions between complementary sequences from opposing strands, rendering the full length transcript inaccessible for translation. We evaluated the role of transcriptional interference and the antisense effect conferred by convergent transcription on the behavior of scbA-scbR system. Stability analysis showed that while transcriptional interference affects the system, it is asRNA that confers scbA-scbR system the characteristics of a bistable switch in response to the signaling molecule SCB1. With its critical role of regulating the onset of antibiotic synthesis the bistable behavior offers this two gene system the needed robustness to be a genetic switch. The convergent two gene system with potential of transcriptional interference is a frequent feature in various genomes. The possibility of asRNA regulation in other such gene-pairs is yet to be examined.

Robust network topologies for generating switch-like cellular responses

Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity) and extent of memory (bistability). Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability). Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28%) and bistability (up to 18%); strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3%) or bistable (up to 1%) responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

Network news: innovations in 21st century systems biology

A decade ago, seminal perspectives and papers set a strong vision for the field of systems biology, and a number of these themes have flourished. Here, we describe key technologies and insights that have elucidated the evolution, architecture, and function of cellular networks, ultimately leading to the first predictive genome-scale regulatory and metabolic models of organisms. Can systems approaches bridge the gap between correlative analysis and mechanistic insights?

Evolutionary computation for the design of a stochastic switch for synthetic genetic circuits

Biological systems are inherently stochastic, a fact which is often ignored when simulating genetic circuits. Synthetic biology aims to design genetic circuits de novo, and cannot therefore afford to ignore the effects of stochastic behavior. Since computational design tools will be essential for large-scale synthetic biology, it is important to develop an understanding of the role of stochasticity in molecular biology, and incorporate this understanding into computational tools for genetic circuit design. We report upon an investigation into the combination of evolutionary algorithms and stochastic simulation for genetic circuit design, to design regulatory systems based on the Bacillus subtilis sin operon.

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.

The promise of evolutionary systems biology: lessons from bacterial chemotaxis

Bacterial chemotaxis and the signaling networks underlying it provide us with a model system for studying the molecular basis of behavior and information processing. Although chemotaxis is well characterized at both the phenotype and genotype levels in the model organism Escherichia coli, it is not yet possible to predict chemotaxis behavior in diverse bacteria on the basis of their environment or genome sequence. Moreover, we still cannot propose a plausible evolutionary trajectory from minimal systems to present-day chemotaxis networks. The analysis of all sequenced bacterial genomes provides a prediction of their chemotaxis networks and reveals substantial structural diversity. Additionally, it uncovers a set of previously unknown proteins that could be the "missing" link between complex present-day chemotaxis networks and simpler, ancestral systems composed of a few proteins. Further evaluation of these findings with experimental and modeling studies will allow us to distill evolutionary design principles in chemotaxis signaling networks.

Mathematical modelling of the sporulation-initiation network in Bacillus subtilis revealing the dual role of the putative quorum-sensing signal molecule PhrA

Bacillus subtilis cells may opt to forgo normal cell division and instead form spores if subjected to certain environmental stimuli, for example nutrient deficiency or extreme temperature. The resulting spores are extremely resilient and can survive for extensive periods of time, importantly under particularly harsh conditions such as those mentioned above. The sporulation process is highly time and energy consuming and essentially irreversible. The bacteria must therefore ensure that this route is only undertaken under appropriate circumstances. The gene regulation network governing sporulation initiation accordingly incorporates a variety of signals and is of significant complexity. We present a model of this network that includes four of these signals: nutrient levels, DNA damage, the products of the competence genes, and cell population size. Our results can be summarised as follows: (i) the model displays the correct phenotypic behaviour in response to these signals; (ii) a basal level of sda expression may prevent sporulation in the presence of nutrients; (iii) sporulation is more likely to occur in a large population of cells than in a small one; (iv) finally, and of most interest, PhrA can act simultaneously as a quorum-sensing signal and as a timing mechanism, delaying sporulation when the cell has damaged DNA, possibly thereby allowing the cell time to repair its DNA before forming a spore.

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.

Deciding fate in adverse times: sporulation and competence in Bacillus subtilis

Bacteria serve as the central arena for understanding how gene networks and proteins process information and control cellular behaviors. Recently, much effort has been devoted to the investigation of specific bacteria gene circuits as functioning modules. The next challenge is the integrative modeling of complex cellular networks composed of many such modules. A tractable integrative model of the sophisticated decision-making signal transduction system that determines the fate between sporulation and competence is presented. This model provides an understanding of how information is sensed and processed to reach an "informative" decision in the context of cell state and signals from other cells. The competence module (ComK dynamics) is modeled as a stochastic switch whose transition rate is controlled by a quorum-sensing unit. The sporulation module (Spo0A dynamics) is modeled as a timer whose clock rate is adjusted by a stress-sensing unit. The interplay between these modules is mediated via the Rap assessment system, which gates the sensing units, and the AbrB-Rok decision module, which creates an opportunity for competence within a specific window of the sporulation timer. The timer is regulated via a special repressilator-like inhibition of Spo0A* by Spo0E, which is itself inhibited by AbrB. For some stress and input signals, this repressilator can generate a frustration state with large variations (fluctuations or oscillations) in Spo0A* and AbrB concentrations, which might serve an important role in generating cell variability. This integrative framework is a starting point that can be extended to include transition into cannibalism and the role of colony organization.

Stochastic kinetic model of two component system signalling reveals all-or-none, graded and mixed mode stochastic switching responses

Two-component systems (TCSs) are prevalent signal transduction systems in bacteria that control innumerable adaptive responses to environmental cues and host-pathogen interactions. We constructed a detailed stochastic kinetic model of two component signalling based on published data. Our model has been validated with flow cytometry data and used to examine reporter gene expression in response to extracellular signal strength. The model shows that, depending on the actual kinetic parameters, TCSs exhibit all-or-none, graded or mixed mode responses. In accordance with other studies, positively autoregulated TCSs exhibit all-or-none responses. Unexpectedly, our model revealed that TCSs lacking a positive feedback loop exhibit not only graded but also mixed mode responses, in which variation of the signal strength alters the level of gene expression in induced cells while the regulated gene continues to be expressed at the basal level in a substantial fraction of cells. The graded response of the TCS changes to mixed mode response by an increase of the translation initiation rate of the histidine kinase. Thus, a TCS is an evolvable design pattern capable of implementing deterministic regulation and stochastic switches associated with both graded and threshold responses. This has implications for understanding the emergence of population diversity in pathogenic bacteria and the design of genetic circuits in synthetic biology applications. The model is available in systems biology markup language (SBML) and systems biology graphical notation (SBGN) formats and can be used as a component of large-scale biochemical reaction network models.

The combination of positive and negative feedback loops confers exquisite flexibility to biochemical switches

A wide range of cellular processes require molecular regulatory pathways to convert a graded signal into a discrete response. One prevalent switching mechanism relies on the coexistence of two stable states (bistability) caused by positive feedback regulations. Intriguingly, positive feedback is often supplemented with negative feedback, raising the question of whether and how these two types of feedback can cooperate to control discrete cellular responses. To address this issue, we formulate a canonical model of a protein-protein interaction network and analyze the dynamics of a prototypical two-component circuit. The appropriate combination of negative and positive feedback loops can bring a bistable circuit close to the oscillatory regime. Notably, sharply activated negative feedback can give rise to a bistable regime wherein two stable fixed points coexist and may collide pairwise with two saddle points. This specific type of bistability is found to allow for separate and flexible control of switch-on and switch-off events, for example (i) to combine fast and reversible transitions, (ii) to enable transient switching responses and (iii) to display tunable noise-induced transition rates. Finally, we discuss the relevance of such bistable switching behavior, and the circuit topologies considered, to specific biological processes such as adaptive metabolic responses, stochastic fate decisions and cell-cycle transitions. Taken together, our results suggest an efficient mechanism by which positive and negative feedback loops cooperate to drive the flexible and multifaceted switching behaviors arising in biological systems.

Tuning a genetic switch: experimental evolution and natural variation of prophage induction

Genetic switches allow organisms to modulate their phenotype in response to environmental changes. Understanding the evolutionary processes by which switches are tuned is central to understanding how phenotypic variation is realized. Prophage induction by phage lambda is the classic example of a genetic switch and allows lambda to move between two different modes of transmission: as a lysogen it reproduces vertically as a component of the host genome; as a free phage it reproduces horizontally by infectious epidemic spread. We show that the lambda switch can respond rapidly to selection for alteration in sensitivity and threshold. Sequencing of candidate genes in the genetic circuitry underlying the switch revealed mutations of likely adaptive significance in some, but not all candidates, suggesting that the core genetic circuitry plays a limited role in the fine-tuning of the switch in vivo. The relative ease with which the switch could be tuned by selection was further indicated by extensive variation in sensitivity and threshold of its response function among wild lambdoid phages. Together, our findings emphasize the adaptive significance of a finely tuned switch and draw attention to the selective factors shaping prophage induction in natural phage populations.

Specialized or flexible feed-forward loop motifs: a question of topology

Background

Network motifs are recurrent interaction patterns, which are significantly more often encountered in biological interaction graphs than expected from random nets. Their existence raises questions concerning their emergence and functional capacities. In this context, it has been shown that feed forward loops (FFL) composed of three genes are capable of processing external signals by responding in a very specific, robust manner, either accelerating or delaying responses. Early studies suggested a one-to-one mapping between topology and dynamics but such view has been repeatedly questioned. The FFL's function has been attributed to this specific response. A general response analysis is difficult, because one is dealing with the dynamical trajectory of a system towards a new regime in response to external signals.

Results

We have developed an analytical method that allows us to systematically explore the patterns and probabilities of the emergence for a specific dynamical response. The method is based on a rather simple, but powerful geometrical analysis of the system's nullclines complemented by an appropriate formalization of the response probability.

Conclusion

Our analysis allows to determine unambiguously the relationship between motif topology and the set of potentially implementable functions. The distribution probability distributions are linked to the degree of specialization or flexibility of the given network topology. The implications for the emergence of different motif topologies in complex networks are outlined.

Design principles for riboswitch function

Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence–function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands.

Riboswitches are RNA-based components that integrate ligand binding and gene regulation to dynamically respond to molecular signals within cells. Natural riboswitches are employed to regulate metabolism and other cellular processes, while synthetic riboswitches have been constructed to expand the sensory and regulatory capabilities exhibited in nature. Characterization studies have revealed that sequence modifications can tune properties of the riboswitch response curve, which links ligand concentration to expression levels. Tunability is critical when matching component properties to the regulatory demands of biological systems; however, the characterization of riboswitch tuning strategies is complicated by the integration of numerous regulatory mechanisms and various processes, such as RNA folding and turnover, that impact riboswitch performance. To develop a generalized framework for examining quantitative aspects of riboswitch tuning, we modeled the kinetics of riboswitch function operating under common regulatory mechanisms. Our results reveal that riboswitch performance is primarily dictated by the competition between reversible and mechanism-specific irreversible rate constants. We demonstrate that practical system restrictions can significantly alter the requirements for riboswitch performance, necessitating a variety of tuning strategies. We developed design principles to guide the construction of synthetic riboswitches and a quantitative framework from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands.

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.

Toward scalable parts families for predictable design of biological circuits

Our current ability to engineer biological circuits is hindered by design cycles that are costly in terms of time and money, with constructs failing to operate as desired, or evolving away from the desired function once deployed. Synthetic biologists seek to understand biological design principles and use them to create technologies that increase the efficiency of the genetic engineering design cycle. Central to the approach is the creation of biological parts--encapsulated functions that can be composited together to create new pathways with predictable behaviors. We define five desirable characteristics of biological parts--independence, reliability, tunability, orthogonality and composability, and review studies of small natural and synthetic biological circuits that provide insights into each of these characteristics. We propose that the creation of appropriate sets of families of parts with these properties is a prerequisite for efficient, predictable engineering of new function in cells and will enable a large increase in the sophistication of genetic engineering applications.

A bistable gene switch for antibiotic biosynthesis: the butyrolactone regulon in Streptomyces coelicolor

Many microorganisms, including bacteria of the class Streptomycetes, produce various secondary metabolites including antibiotics to gain a competitive advantage in their natural habitat. The production of these compounds is highly coordinated in a population to expedite accumulation to an effective concentration. Furthermore, as antibiotics are often toxic even to their producers, a coordinated production allows microbes to first arm themselves with a defense mechanism to resist their own antibiotics before production commences. One possible mechanism of coordination among individuals is through the production of signaling molecules. The gamma-butyrolactone system in Streptomyces coelicolor is a model of such a signaling system for secondary metabolite production. The accumulation of these signaling molecules triggers antibiotic production in the population. A pair of repressor-amplifier proteins encoded by scbA and scbR mediates the production and action of one particular gamma-butyrolactone, SCB1. Based on the proposed interactions of scbA and scbR, a mathematical model was constructed and used to explore the ability of this system to act as a robust genetic switch. Stability analysis shows that the butyrolactone system exhibits bistability and, in response to a threshold SCB1 concentration, can switch from an OFF state to an ON state corresponding to the activation of genes in the cryptic type I polyketide synthase gene cluster, which are responsible for production of the hypothetical polyketide. The switching time is inversely related to the inducer concentration above the threshold, such that short pulses of low inducer concentration cannot switch on the system, suggesting its possible role in noise filtering. In contrast, secondary metabolite production can be triggered rapidly in a population of cells producing the butyrolactone signal due to the presence of an amplification loop in the system. S. coelicolor was perturbed experimentally by varying concentrations of SCB1, and the model simulations match the experimental data well. Deciphering the complexity of this butyrolactone switch will provide valuable insights into how robust and efficient systems can be designed using "simple" two-protein networks.

Memory in microbes: quantifying history-dependent behavior in a bacterium

Memory is usually associated with higher organisms rather than bacteria. However, evidence is mounting that many regulatory networks within bacteria are capable of complex dynamics and multi-stable behaviors that have been linked to memory in other systems. Moreover, it is recognized that bacteria that have experienced different environmental histories may respond differently to current conditions. These “memory” effects may be more than incidental to the regulatory mechanisms controlling acclimation or to the status of the metabolic stores. Rather, they may be regulated by the cell and confer fitness to the organism in the evolutionary game it participates in. Here, we propose that history-dependent behavior is a potentially important manifestation of memory, worth classifying and quantifying. To this end, we develop an information-theory based conceptual framework for measuring both the persistence of memory in microbes and the amount of information about the past encoded in history-dependent dynamics. This method produces a phenomenological measure of cellular memory without regard to the specific cellular mechanisms encoding it. We then apply this framework to a strain of Bacillus subtilis engineered to report on commitment to sporulation and degradative enzyme (AprE) synthesis and estimate the capacity of these systems and growth dynamics to ‘remember’ 10 distinct cell histories prior to application of a common stressor. The analysis suggests that B. subtilis remembers, both in short and long term, aspects of its cell history, and that this memory is distributed differently among the observables. While this study does not examine the mechanistic bases for memory, it presents a framework for quantifying memory in cellular behaviors and is thus a starting point for studying new questions about cellular regulation and evolutionary strategy.

Induction and relaxation dynamics of the regulatory network controlling the type III secretion system encoded within Salmonella pathogenicity island 1

Bacterial pathogenesis requires the precise spatial and temporal control of gene expression, the dynamics of which are controlled by regulatory networks. A network encoded within Salmonella Pathogenicity Island 1 controls the expression of a type III protein secretion system involved in the invasion of host cells. The dynamics of this network are measured in single cells using promoter-green fluorescent protein (gfp) reporters and flow cytometry. During induction, there is a temporal order of gene expression, with transcriptional inputs turning on first, followed by structural and effector genes. The promoters show varying stochastic properties, where graded inputs are converted into all-or-none and hybrid responses. The relaxation dynamics are measured by shifting cells from inducing to noninducing conditions and by measuring fluorescence decay. The gfp expressed from promoters controlling the transcriptional inputs (hilC and hilD) and structural genes (prgH) decay exponentially, with a characteristic time of 50-55 min. In contrast, the gfp expressed from a promoter controlling the expression of effectors (sicA) persists for 110+/-9 min. This promoter is controlled by a genetic circuit, formed by a transcription factor (InvF), a chaperone (SicA), and a secreted protein (SipC), that regulates effector expression in response to the secretion capacity of the cell. A mathematical model of this circuit demonstrates that the delay is due to a split positive feedback loop. This model is tested in a DeltasicA knockout strain, where sicA is complemented with and without the feedback loop. The delay is eliminated when the feedback loop is deleted. Furthermore, a robustness analysis of the model predicts that the delay time can be tuned by changing the affinity of SicA:InvF multimers for an operator in the sicA promoter. This prediction is used to construct a targeted library, which contains mutants with both longer and shorter delays. This combination of theory and experiments provides a platform for predicting how genetic perturbations lead to changes in the global dynamics of a regulatory network.

Implications of rewiring bacterial quorum sensing

Bacteria employ quorum sensing, a form of cell-cell communication, to sense changes in population density and regulate gene expression accordingly. This work investigated the rewiring of one quorum-sensing module, the lux circuit from the marine bacterium Vibrio fischeri. Steady-state experiments demonstrate that rewiring the network architecture of this module can yield graded, threshold, and bistable gene expression as predicted by a mathematical model. The experiments also show that the native lux operon is most consistent with a threshold, as opposed to a bistable, response. Each of the rewired networks yielded functional population sensors at biologically relevant conditions, suggesting that this operon is particularly robust. These findings (i) permit prediction of the behaviors of quorum-sensing operons in bacterial pathogens and (ii) facilitate forward engineering of synthetic gene circuits.

Optimal signal processing in small stochastic biochemical networks

We quantify the influence of the topology of a transcriptional regulatory network on its ability to process environmental signals. By posing the problem in terms of information theory, we do this without specifying the function performed by the network. Specifically, we study the maximum mutual information between the input (chemical) signal and the output (genetic) response attainable by the network in the context of an analytic model of particle number fluctuations. We perform this analysis for all biochemical circuits, including various feedback loops, that can be built out of 3 chemical species, each under the control of one regulator. We find that a generic network, constrained to low molecule numbers and reasonable response times, can transduce more information than a simple binary switch and, in fact, manages to achieve close to the optimal information transmission fidelity. These high-information solutions are robust to tenfold changes in most of the networks' biochemical parameters; moreover they are easier to achieve in networks containing cycles with an odd number of negative regulators (overall negative feedback) due to their decreased molecular noise (a result which we derive analytically). Finally, we demonstrate that a single circuit can support multiple high-information solutions. These findings suggest a potential resolution of the "cross-talk" phenomenon as well as the previously unexplained observation that transcription factors that undergo proteolysis are more likely to be auto-repressive.

The two faces of Janus: virulence gene regulation by CovR/S in group A streptococci

The group A streptococcus (GAS) causes a variety of human diseases, including toxic shock syndrome and necrotizing fasciitis, which are both associated with significant mortality. Even the superficial self-limiting diseases caused by GAS, such as pharyngitis, impose a significant economic burden on society. GAS can cause a wide spectrum of diseases because it elaborates virulence factors that enable it to spread and survive in different environmental niches within the human host. The production of many of these virulence factors is directly controlled by the activity of the CovR/S two-component regulatory system. CovS acts in one direction as a kinase primarily to activate the response regulator CovR and repress the expression of major virulence factors and in the other direction as a phosphatase to permit gene expression in response to environmental changes that mimic conditions found during human infection. This Janus-like behaviour of the CovR/S system is recapitulated in the binding of CovR to the promoters that it directly regulates. Interactions between different faces of the CovR DNA binding domain appear to depend upon DNA sequence, leading to the potential for differential regulation of virulence gene expression.

Model-based definition of population heterogeneity and its effects on metabolism in sporulating Bacillus subtilis

The soil bacterium Bacillus subtilis forms dormant, robust spores as a tactic to ensure survival under conditions of starvation. However, the sporulating culture includes sporulating and non-sporulating cells, because a portion of the cell population initiates sporulation in wild-type strain. We anticipated that the population effect must be considered carefully to analyse samples yielding population heterogeneity. We first built a mathematical model and simulated for signal transduction of the sporulation cue to see what mechanisms are responsible for generating the heterogeneity. The simulated results were confirmed experimentally, where heterogeneity is primarily modulated by negative feedback circuits, resulting in generation of a bistable response within the sporulating culture. We also confirmed that mutants relevant to negative feedback yield either sporulating or non-sporulating subpopulations. To see the effect of molecular mechanism between sporulating and non-sporulating cells in distinct manner, metabolome analysis was conducted using the above mutants. The metabolic profiles exhibited distinct characteristics with time regardless of whether sporulation was initiated or not. In addition, several distinct characteristics of metabolites were observed between strains, which was inconsistent with previously reported data. The results imply that careful consideration must be made in the interpretation of data obtained from cells yielding population heterogeneity.

Mutations leading to loss of sporulation ability in Bacillus subtilis are sufficiently frequent to favor genetic canalization

We measured the rate of mutations impairing sporulation ability in Bacillus subtilis as 0.003 in a mutator population, following 6000 generations of strong selection for sporulation that have previously been described. This means that the product of the population size and the functional mutation rate is approximately 10(5), well within the parameter range for which genetic canalization of sporulation ability is expected.

Construction of an in vitro bistable circuit from synthetic transcriptional switches

Information processing using biochemical circuits is essential for survival and reproduction of natural organisms. As stripped-down analogs of genetic regulatory networks in cells, we engineered artificial transcriptional networks consisting of synthetic DNA switches, regulated by RNA signals acting as transcription repressors, and two enzymes, bacteriophage T7 RNA polymerase and Escherichia coli ribonuclease H. The synthetic switch design is modular with programmable connectivity and allows dynamic control of RNA signals through enzyme-mediated production and degradation. The switches support sharp and adjustable thresholds using a competitive hybridization mechanism, allowing arbitrary analog or digital circuits to be created in principle. As an example, we constructed an in vitro bistable memory by wiring together two synthetic switches and performed a systematic quantitative characterization. Good agreement between experimental data and a simple mathematical model was obtained for switch input/output functions, phase plane trajectories, and the bifurcation diagram for bistability. Construction of larger synthetic circuits provides a unique opportunity for evaluating model inference, prediction, and design of complex biochemical systems and could be used to control nanoscale devices and artificial cells.

Targets of the master regulator of biofilm formation in Bacillus subtilis

Wild strains of the spore-forming bacterium Bacillus subtilis are capable of forming architecturally complex communities of cells. The formation of these biofilms is mediated in part by the 15-gene exopolysaccharide operon, epsA-O, which is under the direct negative control of the SinR repressor. We report the identification of an additional operon, yqxM-sipW-tasA, that is required for biofilm formation and is under the direct negative control of SinR. We now show that all three members of the operon are required for the formation of robust biofilms and that SinR is a potent repressor of the operon that acts by binding to multiple sites in the promoter region. Genome-wide analysis of SinR-controlled transcription indicates that the epsA-O and yqxM-sipW-tasA operons constitute many of the most strongly controlled genes in the SinR regulon. These findings reinforce the view that SinR is a master regulator for biofilm formation and further suggest that a principal biological function of SinR is to govern the assembly of complex multicellular communities.

Plasticity of the cis-regulatory input function of a gene

The transcription rate of a gene is often controlled by several regulators that bind specific sites in the gene's cis-regulatory region. The combined effect of these regulators is described by a cis-regulatory input function. What determines the form of an input function, and how variable is it with respect to mutations? To address this, we employ the well-characterized lac operon of Escherichia coli, which has an elaborate input function, intermediate between Boolean AND-gate and OR-gate logic. We mapped in detail the input function of 12 variants of the lac promoter, each with different point mutations in the regulator binding sites, by means of accurate expression measurements from living cells. We find that even a few mutations can significantly change the input function, resulting in functions that resemble Pure AND gates, OR gates, or single-input switches. Other types of gates were not found. The variant input functions can be described in a unified manner by a mathematical model. The model also lets us predict which functions cannot be reached by point mutations. The input function that we studied thus appears to be plastic, in the sense that many of the mutations do not ruin the regulation completely but rather result in new ways to integrate the inputs.

A few point mutations in the lac operon of Escherichia coli are sufficient to change the nature of the transcriptional computation.

Signal transduction networks: topology, response and biochemical processes

Conventionally, biological signal transduction networks are analysed using experimental and theoretical methods to describe specific protein components, interactions, and biochemical processes and to model network behavior under various conditions. While these studies provide crucial information on specific networks, this information is not easily converted to a broader understanding of signal transduction systems. Here, using a specific model of protein interaction we analyse small network topologies to understand their response and general properties. In particular, we catalogue the response for all possible topologies of a given network size to generate a response distribution, analyse the effects of specific biochemical processes on this distribution, and analyse the robustness and diversity of responses with respect to internal fluctuations or mutations in the network. The results show that even three- and four-protein networks are capable of creating diverse and biologically relevant responses, that the distribution of response types changes drastically as a function of biochemical processes at protein level, and that certain topologies strongly pre-dispose a specific response type while others allow for diverse types of responses. This study sheds light on the response types and properties that could be expected from signal transduction networks, provides possible explanations for the role of certain biochemical processes in signal transduction and suggests novel approaches to interfere with signaling pathways at the molecular level. Furthermore it shows that network topology plays a key role on determining response type and properties and that proper representation of network topology is crucial to discover and understand so-called building blocks of large networks.

Phosphatase localization in bacterial chemotaxis: divergent mechanisms, convergent principles

Chemotaxis is the process by which cells sense changes in their chemical environment and move towards more favorable conditions. In divergent species of bacteria, the chemotaxis proteins localize to the poles of the cell and information is transferred to the flagellar motors through the phosphorylation of a soluble protein CheY. Using mathematical models and computer simulation, we demonstrate that phosphatase localization controls the spatial distribution of CheY-P in the cytosol at steady state. Remarkably, the location of the phosphatase is not conserved in different species of bacteria. The sole phosphatase in Escherichia coli is localized with the signaling complex and the primary phosphatase in Bacillus subtilis is localized at the flagellar motors. Despite these alternate pathway structures, both designs minimize differences in the concentration of phosphorylated CheY proximal to each motor unlike a design where the phosphatase is freely diffusing in the cytoplasm. These results suggest that motile bacteria have evolved alternate mechanisms to ensure that each motor receives roughly the same signal at steady state. The hypothesis is that complex networks have evolved to satisfy certain design principles in order to function robustly. While specific mechanisms are different, the underlying principles of phosphatase localization in E. coli and B. subtilis appear to be the same.

A coherent feed-forward loop with a SUM input function prolongs flagella expression in Escherichia coli

Complex gene-regulation networks are made of simple recurring gene circuits called network motifs. The functions of several network motifs have recently been studied experimentally, including the coherent feed-forward loop (FFL) with an AND input function that acts as a sign-sensitive delay element. Here, we study the function of the coherent FFL with a sum input function (SUM-FFL). We analyze the dynamics of this motif by means of high-resolution expression measurements in the flagella gene-regulation network, the system that allows Escherichia coli to swim. In this system, the master regulator FlhDC activates a second regulator, FliA, and both activate in an additive fashion the operons that produce the flagella motor. We find that this motif prolongs flagella expression following deactivation of the master regulator, protecting flagella production from transient loss of input signal. Thus, in contrast to the AND-FFL that shows a delay following signal activation, the SUM-FFL shows delays after signal deactivation. The SUM-FFL in this system works as theoretically predicted despite being embedded in at least two additional feedback loops. The present function might be carried out by the SUM-FFL in systems found across organisms.