Stochastic pulse regulation in bacterial stress response

Fundamental principles of energy consumption for gene expression

How energy is consumed in gene expression is largely unknown mainly due to complexity of non-equilibrium mechanisms affecting expression levels. Here, by analyzing a representative gene model that considers complexity of gene expression, we show that negative feedback increases energy consumption but positive feedback has an opposite effect; promoter leakage always reduces energy consumption; generating more bursts needs to consume more energy; and the speed of promoter switching is at the cost of energy consumption. We also find that the relationship between energy consumption and expression noise is multi-mode, depending on both the type of feedback and the speed of promoter switching. Altogether, these results constitute fundamental principles of energy consumption for gene expression, which lay a foundation for designing biologically reasonable gene modules. In addition, we discuss possible biological implications of these principles by combining experimental facts.

[Randomness and cell fate]

Thermal fluctuations at the molecular scale cause random fluctuations of gene expression, which, in association with differentiation circuits, can lead to phenotypic diversification in cell populations. In this synthesis article, we detail the mechanisms that generate this diversification and illustrate their consequences in various organisms. In bacteria, random phenotypic diversification allows to anticipate environmental changes that are otherwise unpredictable, in particular during metabolic transitions and stress responses, for example inducing a transient form of antibiotic resistance. In multi-cellular organisms, similar mechanisms allow the maintenance of healthy tissues, such as intestinal crypts, epidermis and retina, but also seem to play a role in establishment and renewal of tumoral heterogeneity.

Combinatorial gene regulation by modulation of relative pulse timing

Studies of individual living cells have revealed that many transcription factors activate in dynamic, and often stochastic, pulses within the same cell. However, it has remained unclear whether cells might modulate the relative timing of these pulses to control gene expression. Here, using quantitative single-cell time-lapse imaging of Saccharomyces cerevisiae, we show that the pulsatile transcription factors Msn2 and Mig1 combinatorially regulate their target genes through modulation of their relative pulse timing. The activator Msn2 and repressor Mig1 pulsed in either a temporally overlapping or non-overlapping manner during their transient response to different inputs, with only the non-overlapping dynamics efficiently activating target gene expression. Similarly, under constant environmental conditions, where Msn2 and Mig1 exhibit sporadic pulsing, glucose concentration modulated the temporal overlap between pulses of the two factors. Together, these results reveal a time-based mode of combinatorial gene regulation. Regulation through relative signal timing is common in engineering and neurobiology, and these results suggest that it could also function broadly within the signaling and regulatory systems of the cell.

Noise and low-level dynamics can coordinate multicomponent bet hedging mechanisms

To counter future uncertainty, cells can stochastically express stress response mechanisms to diversify their population and hedge against stress. This approach allows a small subset of the population to survive without the prohibitive cost of constantly expressing resistance machinery at the population level. However, expression of multiple genes in concert is often needed to ensure survival, requiring coordination of infrequent events across many downstream targets. This raises the question of how cells orchestrate the timing of multiple rare events without adding cost. To investigate this, we used a stochastic model to study regulation of downstream target genes by a transcription factor. We compared several upstream regulator profiles, including constant expression, pulsatile dynamics, and noisy expression. We found that pulsatile dynamics and noise are sufficient to coordinate expression of multiple downstream genes. Notably, this is true even when fluctuations in the upstream regulator are far below the dissociation constants of the regulated genes, as with infrequently activated genes. As an example, we simulated the dynamics of the multiple antibiotic resistance activator (MarA) and 40 diverse downstream genes it regulates, determining that low-level dynamics in MarA are sufficient to coordinate expression of resistance mechanisms. We also demonstrated that noise can play a similar coordinating role. Importantly, we found that these benefits are present without a corresponding increase in the population-level cost. Therefore, our model suggests that low-level dynamics or noise in a transcription factor can coordinate expression of multiple stress response mechanisms by engaging them simultaneously without adding to the overall cost.

The Rsb Phosphoregulatory Network Controls Availability of the Primary Sigma Factor in Chlamydia trachomatis and Influences the Kinetics of Growth and Development

Chlamydia trachomatis is an obligate intracellular human pathogen that exhibits stage-specific gene transcription throughout a biphasic developmental cycle. The mechanisms that control modulation in transcription and associated phenotypic changes are poorly understood. This study provides evidence that a switch-protein kinase regulatory network controls availability of σ⁶⁶_, the main sigma subunit for transcription in Chlamydia. In vitro analysis revealed that a putative switch-protein kinase regulator, RsbW, is capable of interacting directly with σ⁶⁶, as well as phosphorylating its own antagonist, RsbV1, rendering it inactive. Conversely, the putative PP2C-like phosphatase domain of chlamydial RsbU was capable of reverting RsbV1 into its active state. Recent advances in genetic manipulation of Chlamydia were employed to inactivate rsbV1, as well as to increase the expression levels of rsbW or rsbV1, in vivo. Representative σ⁶⁶-dependent gene transcription was repressed in the absence of rsbV1 or upon increased expression of RsbW, and increased upon elevated expression of RsbV1. These effects on housekeeping transcription were also correlated to several measures of growth and development. A model is proposed where the relative levels of active antagonist (RsbV1) and switch-protein anti-sigma factor (RsbW) control the availability of σ⁶⁶ and subsequently act as a molecular 'throttle' for Chlamydia growth and development.

Chlamydia trachomatis is the leading cause of both bacterial sexually transmitted infection and infection-derived blindness world-wide. No vaccine has proven protective to date in humans. C. trachomatis only replicates from inside a host cell, and has evolved to acquire a variety of nutrients directly from its host. However, a typical human immune response will normally limit the availability of a variety of essential nutrients. Thus, it is thought that the success of C. trachomatis as a human pathogen may lie in its ability to survive these immunological stress situations by slowing growth and development until conditions in the cell have improved. This mode of growth is known as persistence and how C. trachomatis senses stress and responds in this manner is an important area of research. Our report characterizes a complete signaling module, the Rsb network, that is capable of controlling the growth rate or infectivity of Chlamydia. By manipulating the levels of different pathway components, we were able to accelerate and restrict the growth and development of this pathogen. Our results suggest a mechanism by which Chlamydia can tailor its growth rate to the conditions within the host cell. The disruption of this pathway could generate a strain incapable of surviving a typical human immune response and would represent an attractive candidate as an attenuated growth vaccine.

Activation of the General Stress Response of Bacillus subtilis by Visible Light

A key challenge for microbiology is to understand how evolution has shaped the wiring of regulatory networks. This is amplified by the paucity of information of power-spectra of physicochemical stimuli to which microorganisms are exposed. Future studies of genome evolution, driven by altered stimulus regimes, will therefore require a versatile signal transduction system that allows accurate signal dosing. Here, we review the general stress response of Bacillus subtilis, and its upstream signal transduction network, as a candidate system. It can be activated by red and blue light, and by many additional stimuli. Signal integration therefore is an intricate function of this system. The blue-light response is elicited via the photoreceptor YtvA, which forms an integral part of stressosomes, to activate expression of the stress regulon of B. subtilis. Signal transfer through this network can be assayed with reporter enzymes, while intermediate steps can be studied with live-cell imaging of fluorescently tagged proteins. Different parts of this system have been studied in vitro, such that its computational modeling has made significant progress. One can directly relate the microscopic characteristics of YtvA with activation of the general stress regulon, making this system a very well-suited system for network evolution studies.

Accurate encoding and decoding by single cells: amplitude versus frequency modulation

Cells sense external concentrations and, via biochemical signaling, respond by regulating the expression of target proteins. Both in signaling networks and gene regulation there are two main mechanisms by which the concentration can be encoded internally: amplitude modulation (AM), where the absolute concentration of an internal signaling molecule encodes the stimulus, and frequency modulation (FM), where the period between successive bursts represents the stimulus. Although both mechanisms have been observed in biological systems, the question of when it is beneficial for cells to use either AM or FM is largely unanswered. Here, we first consider a simple model for a single receptor (or ion channel), which can either signal continuously whenever a ligand is bound, or produce a burst in signaling molecule upon receptor binding. We find that bursty signaling is more accurate than continuous signaling only for sufficiently fast dynamics. This suggests that modulation based on bursts may be more common in signaling networks than in gene regulation. We then extend our model to multiple receptors, where continuous and bursty signaling are equivalent to AM and FM respectively, finding that AM is always more accurate. This implies that the reason some cells use FM is related to factors other than accuracy, such as the ability to coordinate expression of multiple genes or to implement threshold crossing mechanisms.

Signals, and hence information, can generally be transmitted either by amplitude (AM) or frequency (FM) modulation, as used, for example, in the transmission of radio waves since the 1930s. Both types of modulation are known to play a role in biology with AM conventionally associated with signaling and gene expression, and FM used to reliably transmit electrical signals over large distances between neurons. Surprisingly, FM was recently also observed in gene regulation, making their roles less distinct than previously thought. Although the engineering advantages and disadvantages of AM and FM are well understood, the equivalent question in biological systems is still largely unsolved. Here, we propose a simple model of signaling by receptors (or ion channels) with subsequent gene regulation, thus implementing both AM and FM in different types of biological pathways. We then compare the accuracy in the production of target proteins. We find that FM can be more accurate than AM only for a single receptor with fast signaling, whereas AM is more accurate in slow gene regulation and with signaling by multiple receptors. Finally, we propose possible reasons that cells use FM despite the potential decrease in accuracy.

Technical bias of microcultivation environments on single-cell physiology

Microscale cultivation systems are important tools to elucidate cellular dynamics beyond the population average and understand the functional architecture of single cells. However, there is scant knowledge about the bias of different microcultivation technologies on cellular functions. We therefore performed a systematic cross-platform comparison of three different microscale cultivation systems commonly harnessed in single-cell analysis: microfluidic non-contact cell traps driven by negative dielectrophoresis, microfluidic monolayer growth chambers, and semi-solid agarose pads. We assessed the specific single-cell growth rates, division rates and morphological characteristics of single Corynebacterium glutamicum cells and microcolonies as a bacterial model organism with medical and biotechnological relevance under standardized growth conditions. Strikingly, the specific single-cell and microcolony growth rates, μmax, were robust and conserved for several cell generations with all three microcultivation technologies, whereas the division rates of cells grown on agarose pads deviated by up to 50% from those of cells cultivated in negative dielectrophoresis traps and monolayer growth chambers. Furthermore, morphological characteristics like cell lengths and division symmetries of individual cells were affected when the cells were grown on agarose pads. This indicated a significant impact of solid cultivation supports on cellular traits. The results demonstrate the impact of microcultivation technology on microbial physiology for the first time and show the need for a careful selection and design of the microcultivation technology in order to allow unbiased analysis of cellular behavior.

The cognitive cell: bacterial behavior reconsidered

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

The outer subventricular zone and primate-specific cortical complexification

Evolutionary expansion and complexification of the primate cerebral cortex are largely linked to the emergence of the outer subventricular zone (OSVZ), a uniquely structured germinal zone that generates the expanded primate supragranular layers. The primate OSVZ departs from rodent germinal zones in that it includes a higher diversity of precursor types, inter-related in bidirectional non-hierarchical lineages. In addition, primate-specific regulatory mechanisms are operating in primate cortical precursors via the occurrence of novel miRNAs. Here, we propose that the origin and evolutionary importance of the OSVZ is related to genetic changes in multiple regulatory loops and that cell-cycle regulation is a favored target for evolutionary adaptation of the cortex.

How to train your microbe: methods for dynamically characterizing gene networks

Gene networks regulate biological processes dynamically. However, researchers have largely relied upon static perturbations, such as growth media variations and gene knockouts, to elucidate gene network structure and function. Thus, much of the regulation on the path from DNA to phenotype remains poorly understood. Recent studies have utilized improved genetic tools, hardware, and computational control strategies to generate precise temporal perturbations outside and inside of live cells. These experiments have, in turn, provided new insights into the organizing principles of biology. Here, we introduce the major classes of dynamical perturbations that can be used to study gene networks, and discuss technologies available for creating them in a wide range of microbial pathways.

Microbial individuality: how single-cell heterogeneity enables population level strategies

Much of our knowledge of microbial life is only a description of average population behaviours, but modern technologies provide a more inclusive view and reveal that microbes also have individuality. It is now acknowledged that isogenic cell-to-cell heterogeneity is common across organisms and across different biological processes. This heterogeneity can be regulated and functional, rather than just reflecting tolerance to noisy biochemistry. Here, we review recent advances in our understanding of microbial heterogeneity, with an emphasis on the pervasiveness of heterogeneity, the mechanisms that sustain it, and how heterogeneity enables collective function.

Stress-induced remodeling of the bacterial proteome

Microorganisms live in fluctuating environments, requiring stress response pathways to resist environmental insults and stress. These pathways dynamically monitor cellular status, and mediate adaptive changes by remodeling the proteome, largely accomplished by remodeling transcriptional networks and protein degradation. The complementarity of fast, specific proteolytic degradation and slower, broad transcriptomic changes gives cells the mechanistic repertoire to dynamically adjust cellular processes and optimize response behavior. Together, this enables cells to minimize the 'cost' of the response while maximizing the ability to survive environmental stress. Here we highlight recent progress in our understanding of transcriptional networks and proteolysis that illustrates the design principles used by bacteria to generate the complex behaviors required to resist stress.

Global coordination in adaptation to gene rewiring

Gene rewiring is a common evolutionary phenomenon in nature that may lead to extinction for living organisms. Recent studies on synthetic biology demonstrate that cells can survive genetic rewiring. This survival (adaptation) is often linked to the stochastic expression of rewired genes with random transcriptional changes. However, the probability of adaptation and the underlying common principles are not clear. We performed a systematic survey of an assortment of gene-rewired Escherichia coli strains to address these questions. Three different cell fates, designated good survivors, poor survivors and failures, were observed when the strains starved. Large fluctuations in the expression of the rewired gene were commonly observed with increasing cell size, but these changes were insufficient for adaptation. Cooperative reorganizations in the corresponding operon and genome-wide gene expression largely contributed to the final success. Transcriptome reorganizations that generally showed high-dimensional dynamic changes were restricted within a one-dimensional trajectory for adaptation to gene rewiring, indicating a general path directed toward cellular plasticity for a successful cell fate. This finding of global coordination supports a mechanism of stochastic adaptation and provides novel insights into the design and application of complex genetic or metabolic networks.

Single-cell analysis of mycobacteria using microfluidics and time-lapse microscopy

The crucial role of phenotypic heterogeneity in bacterial physiology and adaptive responses has required the introduction of new ways to investigate bacterial individuality. Time-lapse microscopy is a powerful technique for evaluating phenotypic diversity in bacteria at the single-cell level, whether exploring the dynamics of gene expression and protein localization or characterizing the heterogeneous phenotypic response to perturbations. Here, we present protocols to carry out time-lapse imaging of mycobacteria at the single-cell level using either agarose pads or customized microfluidic devices. The sequences of images obtained can be analyzed using programs such as ImageJ and allow the investigator not only to extract various parameters of growth and gene expression dynamics but also to unravel the physiological basis behind phenomenon such as persistence against stresses.

Single-cell analysis reveals gene-expression heterogeneity in syntrophic dual-culture of Desulfovibrio vulgaris with Methanosarcina barkeri

Microbial syntrophic metabolism has been well accepted as the heart of how methanogenic and other anaerobic microbial communities function. In this work, we applied a single-cell RT-qPCR approach to reveal gene-expression heterogeneity in a model syntrophic system of Desulfovibrio vulgaris and Methanosarcina barkeri, as compared with the D. vulgaris monoculture. Using the optimized primers and single-cell analytical protocol, we quantitatively determine gene-expression levels of 6 selected target genes in each of the 120 single cells of D. vulgaris isolated from its monoculture and dual-culture with M. barkeri. The results demonstrated very significant cell-to-cell gene-expression heterogeneity for the selected D. vulgaris genes in both the monoculture and the syntrophic dual-culture. Interestingly, no obvious increase in gene-expression heterogeneity for the selected genes was observed for the syntrophic dual-culture when compared with its monoculture, although the community structure and cell-cell interactions have become more complicated in the syntrophic dual-culture. In addition, the single-cell RT-qPCR analysis also provided further evidence that the gene cluster (DVU0148-DVU0150) may be involved syntrophic metabolism between D. vulgaris and M. barkeri. Finally, the study validated that single-cell RT-qPCR analysis could be a valuable tool in deciphering gene functions and metabolism in mixed-cultured microbial communities.

A model for sigma factor competition in bacterial cells

Sigma factors control global switches of the genetic expression program in bacteria. Different sigma factors compete for binding to a limited pool of RNA polymerase (RNAP) core enzymes, providing a mechanism for cross-talk between genes or gene classes via the sharing of expression machinery. To analyze the contribution of sigma factor competition to global changes in gene expression, we develop a theoretical model that describes binding between sigma factors and core RNAP, transcription, non-specific binding to DNA and the modulation of the availability of the molecular components. The model is validated by comparison with in vitro competition experiments, with which excellent agreement is found. Transcription is affected via the modulation of the concentrations of the different types of holoenzymes, so saturated promoters are only weakly affected by sigma factor competition. However, in case of overlapping promoters or promoters recognized by two types of sigma factors, we find that even saturated promoters are strongly affected. Active transcription effectively lowers the affinity between the sigma factor driving it and the core RNAP, resulting in complex cross-talk effects. Sigma factor competition is not strongly affected by non-specific binding of core RNAPs, sigma factors and holoenzymes to DNA. Finally, we analyze the role of increased core RNAP availability upon the shut-down of ribosomal RNA transcription during the stringent response. We find that passive up-regulation of alternative sigma-dependent transcription is not only possible, but also displays hypersensitivity based on the sigma factor competition. Our theoretical analysis thus provides support for a significant role of passive control during that global switch of the gene expression program.

Bacteria respond to changing environmental conditions by switching the global pattern of expressed genes. A key mechanism for global switches of the transcriptional program depends on alternative sigma factors that bind the RNA polymerase core enzyme and direct it towards the appropriate stress response genes. Competition of different sigma factors for a limited amount of RNA polymerase is believed to play a central role in this global switch. Here, a theoretical approach is used towards a quantitative understanding of sigma factor competition and its effects on gene expression. The model is used to quantitatively describe in vitro competition assays and to address the question of indirect or passive control in the stringent response upon amino acids starvation. We show that sigma factor competition provides a mechanism for a passive up-regulation of the stress specific sigma-driven genes due to the increased availability of RNA polymerase in the stringent response. Moreover, we find that active separation of sigma factor from the RNA polymerase during early transcript elongation weakens the sigma factor-RNA polymerase equilibrium constant, raising the question of how their in vitro measure is relevant in the cell.

Ultrasensitivity part I: Michaelian responses and zero-order ultrasensitivity

Quantitative studies of signal transduction systems have shown that ultrasensitive responses - switch-like, sigmoidal input/output relationships - are commonplace in cell signaling. Ultrasensitivity is important for various complex signaling systems, including signaling cascades, bistable switches, and oscillators. In this first installment of a series on ultrasensitivity we survey the occurrence of ultrasensitive responses in signaling systems. We review why the simplest mass action systems exhibit Michaelian responses, and then move on to zero-order ultrasensitivity, a phenomenon that occurs when signaling proteins are operating near saturation. We also discuss the physiological relevance of zero-order ultrasensitivity to cellular regulation.

Pulsatile dynamics in the yeast proteome

The activation of transcription factors in response to environmental conditions is fundamental to cellular regulation. Recent work has revealed that some transcription factors are activated in stochastic pulses of nuclear localization, rather than at a constant level, even in a constant environment [1-12]. In such cases, signals control the mean activity of the transcription factor by modulating the frequency, duration, or amplitude of these pulses. Although specific pulsatile transcription factors have been identified in diverse cell types, it has remained unclear how prevalent pulsing is within the cell, how variable pulsing behaviors are between genes, and whether pulsing is specific to transcriptional regulators or is employed more broadly. To address these issues, we performed a proteome-wide movie-based screen to systematically identify localization-based pulsing behaviors in Saccharomyces cerevisiae. The screen examined all genes in a previously developed fluorescent protein fusion library of 4,159 strains [13] in multiple media conditions. This approach revealed stochastic pulsing in ten proteins, all transcription factors. In each case, pulse dynamics were heterogeneous and unsynchronized among cells in clonal populations. Pulsing is the only dynamic localization behavior that we observed, and it tends to occur in pairs of paralogous and redundant proteins. Taken together, these results suggest that pulsatile dynamics play a pervasive role in yeast and may be similarly prevalent in other eukaryotic species.

Optogenetic characterization methods overcome key challenges in synthetic and systems biology

Systems biologists aim to understand how organism-level processes, such as differentiation and multicellular development, are encoded in DNA. Conversely, synthetic biologists aim to program systems-level biological processes, such as engineered tissue growth, by writing artificial DNA sequences. To achieve their goals, these groups have adapted a hierarchical electrical engineering framework that can be applied in the forward direction to design complex biological systems or in the reverse direction to analyze evolved networks. Despite much progress, this framework has been limited by an inability to directly and dynamically characterize biological components in the varied contexts of living cells. Recently, two optogenetic methods for programming custom gene expression and protein localization signals have been developed and used to reveal fundamentally new information about biological components that respond to those signals. This basic dynamic characterization approach will be a major enabling technology in synthetic and systems biology.

BactImAS: a platform for processing and analysis of bacterial time-lapse microscopy movies

Background

The software available to date for analyzing image sequences from time-lapse microscopy works only for certain bacteria and under limited conditions. These programs, mostly MATLAB-based, fail for microbes with irregular shape, indistinct cell division sites, or that grow in closely packed microcolonies. Unfortunately, many organisms of interest have these characteristics, and analyzing their image sequences has been limited to time consuming manual processing.

Results

Here we describe BactImAS – a modular, multi-platform, open-source, Java-based software delivered both as a standalone program and as a plugin for Icy. The software is designed for extracting and visualizing quantitative data from bacterial time-lapse movies. BactImAS uses a semi-automated approach where the user defines initial cells, identifies cell division events, and, if necessary, manually corrects cell segmentation with the help of user-friendly GUI and incorporated ImageJ application. The program segments and tracks cells using a newly-developed algorithm designed for movies with difficult-to-segment cells that exhibit small frame-to-frame differences. Measurements are extracted from images in a configurable, automated fashion and an SQLite database is used to store, retrieve, and exchange all acquired data. Finally, the BactImAS can generate configurable lineage tree visualizations and export data as CSV files. We tested BactImAS on time-lapse movies of Mycobacterium smegmatis and achieved at least 10-fold reduction of processing time compared to manual analysis. We illustrate the power of the visualization tool by showing heterogeneity of both icl expression and cell growth atop of a lineage tree.

Conclusions

The presented software simplifies quantitative analysis of time-lapse movies overall and is currently the only available software for the analysis of mycobacteria-like cells. It will be of interest to the community of both end-users and developers of time-lapse microscopy software.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-251) contains supplementary material, which is available to authorized users.

Studying the organization of DNA repair by single-cell and single-molecule imaging

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Single-cell experiments to study stochastic events and heterogeneity in DNA repair.

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Quantifying DNA repair protein concentration, diffusion, and localization in cells.

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Direct observation of DNA repair using photoactivated single-molecule tracking.

DNA repair safeguards the genome against a diversity of DNA damaging agents. Although the mechanisms of many repair proteins have been examined separately in vitro, far less is known about the coordinated function of the whole repair machinery in vivo. Furthermore, single-cell studies indicate that DNA damage responses generate substantial variation in repair activities across cells. This review focuses on fluorescence imaging methods that offer a quantitative description of DNA repair in single cells by measuring protein concentrations, diffusion characteristics, localizations, interactions, and enzymatic rates. Emerging single-molecule and super-resolution microscopy methods now permit direct visualization of individual proteins and DNA repair events in vivo. We expect much can be learned about the organization of DNA repair by linking cell heterogeneity to mechanistic observations at the molecular level.

Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach

Background

Accurate estimation of parameters of biochemical models is required to characterize the dynamics of molecular processes. This problem is intimately linked to identifying the most informative experiments for accomplishing such tasks. While significant progress has been made, effective experimental strategies for parameter identification and for distinguishing among alternative network topologies remain unclear. We approached these questions in an unbiased manner using a unique community-based approach in the context of the DREAM initiative (Dialogue for Reverse Engineering Assessment of Methods). We created an in silico test framework under which participants could probe a network with hidden parameters by requesting a range of experimental assays; results of these experiments were simulated according to a model of network dynamics only partially revealed to participants.

Results

We proposed two challenges; in the first, participants were given the topology and underlying biochemical structure of a 9-gene regulatory network and were asked to determine its parameter values. In the second challenge, participants were given an incomplete topology with 11 genes and asked to find three missing links in the model. In both challenges, a budget was provided to buy experimental data generated in silico with the model and mimicking the features of different common experimental techniques, such as microarrays and fluorescence microscopy. Data could be bought at any stage, allowing participants to implement an iterative loop of experiments and computation.

Conclusions

A total of 19 teams participated in this competition. The results suggest that the combination of state-of-the-art parameter estimation and a varied set of experimental methods using a few datasets, mostly fluorescence imaging data, can accurately determine parameters of biochemical models of gene regulation. However, the task is considerably more difficult if the gene network topology is not completely defined, as in challenge 2. Importantly, we found that aggregating independent parameter predictions and network topology across submissions creates a solution that can be better than the one from the best-performing submission.

A developmental basis for stochasticity in floral organ numbers

Stochasticity ubiquitously inevitably appears at all levels from molecular traits to multicellular, morphological traits. Intrinsic stochasticity in biochemical reactions underlies the typical intercellular distributions of chemical concentrations, e.g., morphogen gradients, which can give rise to stochastic morphogenesis. While the universal statistics and mechanisms underlying the stochasticity at the biochemical level have been widely analyzed, those at the morphological level have not. Such morphological stochasticity is found in foral organ numbers. Although the floral organ number is a hallmark of floral species, it can distribute stochastically even within an individual plant. The probability distribution of the floral organ number within a population is usually asymmetric, i.e., it is more likely to increase rather than decrease from the modal value, or vice versa. We combined field observations, statistical analysis, and mathematical modeling to study the developmental basis of the variation in floral organ numbers among 50 species mainly from Ranunculaceae and several other families from core eudicots. We compared six hypothetical mechanisms and found that a modified error function reproduced much of the asymmetric variation found in eudicot floral organ numbers. The error function is derived from mathematical modeling of floral organ positioning, and its parameters represent measurable distances in the floral bud morphologies. The model predicts two developmental sources of the organ-number distributions: stochastic shifts in the expression boundaries of homeotic genes and a semi-concentric (whorled-type) organ arrangement. Other models species- or organ-specifically reproduced different types of distributions that reflect different developmental processes. The organ-number variation could be an indicator of stochasticity in organ fate determination and organ positioning.

Promoter activity dynamics in the lag phase of Escherichia coli

Background

Lag phase is a period of time with no growth that occurs when stationary phase bacteria are transferred to a fresh medium. Bacteria in lag phase seem inert: their biomass does not increase. The low number of cells and low metabolic activity make it difficult to study this phase. As a consequence, it has not been studied as thoroughly as other bacterial growth phases. However, lag phase has important implications for bacterial infections and food safety. We asked which, if any, genes are expressed in the lag phase of Escherichia coli, and what is their dynamic expression pattern.

Results

We developed an assay based on imaging flow cytometry of fluorescent reporter cells that overcomes the challenges inherent in studying lag phase. We distinguish between lag1 phase- in which there is no biomass growth, and lag2 phase- in which there is biomass growth but no cell division. We find that in lag1 phase, most promoters are not active, except for the enzymes that utilize the specific carbon source in the medium. These genes show promoter activities that increase exponentially with time, despite the fact that the cells do not measurably increase in size. An oxidative stress promoter, katG, is also active. When cells enter lag2 and begin to grow in size, they switch to a full growth program of promoter activity including ribosomal and metabolic genes.

Conclusions

The observed exponential increase in enzymes for the specific carbon source followed by an abrupt switch to production of general growth genes is a solution of an optimal control model, known as bang-bang control. The present approach contributes to the understanding of lag phase, the least studied of bacterial growth phases.

Functional roles of pulsing in genetic circuits

A fundamental problem in biology is to understand how genetic circuits implement core cellular functions. Time-lapse microscopy techniques are beginning to provide a direct view of circuit dynamics in individual living cells. Unexpectedly, we are discovering that key transcription and regulatory factors pulse on and off repeatedly, and often stochastically, even when cells are maintained in constant conditions. This type of spontaneous dynamic behavior is pervasive, appearing in diverse cell types from microbes to mammalian cells. Here, we review recent work showing how pulsing is generated and controlled by underlying regulatory circuits and how it provides critical capabilities to cells in stress response, signaling, and development. A major theme is the ability of pulsing to enable time-based regulation analogous to strategies used in engineered systems. Thus, pulsatile dynamics is emerging as a central, and still largely unexplored, layer of temporal organization in the cell.

Microfluidic picoliter bioreactor for microbial single-cell analysis: fabrication, system setup, and operation

In this protocol the fabrication, experimental setup and basic operation of the recently introduced microfluidic picoliter bioreactor (PLBR) is described in detail. The PLBR can be utilized for the analysis of single bacteria and microcolonies to investigate biotechnological and microbiological related questions concerning, e.g. cell growth, morphology, stress response, and metabolite or protein production on single-cell level. The device features continuous media flow enabling constant environmental conditions for perturbation studies, but in addition allows fast medium changes as well as oscillating conditions to mimic any desired environmental situation. To fabricate the single use devices, a silicon wafer containing sub micrometer sized SU-8 structures served as the replication mold for rapid polydimethylsiloxane casting. Chips were cut, assembled, connected, and set up onto a high resolution and fully automated microscope suited for time-lapse imaging, a powerful tool for spatio-temporal cell analysis. Here, the biotechnological platform organism Corynebacterium glutamicum was seeded into the PLBR and cell growth and intracellular fluorescence were followed over several hours unraveling time dependent population heterogeneity on single-cell level, not possible with conventional analysis methods such as flow cytometry. Besides insights into device fabrication, furthermore, the preparation of the preculture, loading, trapping of bacteria, and the PLBR cultivation of single cells and colonies is demonstrated. These devices will add a new dimension in microbiological research to analyze time dependent phenomena of single bacteria under tight environmental control. Due to the simple and relatively short fabrication process the technology can be easily adapted at any microfluidics lab and simply tailored towards specific needs.

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.

Tunable stochastic pulsing in the Escherichia coli multiple antibiotic resistance network from interlinked positive and negative feedback loops

Cells live in uncertain, dynamic environments and have many mechanisms for sensing and responding to changes in their surroundings. However, sudden fluctuations in the environment can be catastrophic to a population if it relies solely on sensory responses, which have a delay associated with them. Cells can reconcile these effects by using a tunable stochastic response, where in the absence of a stressor they create phenotypic diversity within an isogenic population, but use a deterministic response when stressors are sensed. Here, we develop a stochastic model of the multiple antibiotic resistance network of Escherichia coli and show that it can produce tunable stochastic pulses in the activator MarA. In particular, we show that a combination of interlinked positive and negative feedback loops plays an important role in setting the dynamics of the stochastic pulses. Negative feedback produces a pulsatile response that is tunable, while positive feedback serves to amplify the effect. Our simulations show that the uninduced native network is in a parameter regime that is of low cost to the cell (taxing resistance mechanisms are expressed infrequently) and also elevated noise strength (phenotypic variability is high). The stochastic pulsing can be tuned by MarA induction such that variability is decreased once stresses are sensed, avoiding the detrimental effects of noise when an optimal MarA concentration is needed. We further show that variability in the expression of MarA can act as a bet hedging mechanism, allowing for survival in time-varying stress environments, however this effect is tunable to allow for a fully induced, deterministic response in the presence of a stressor.

Autonomous bacterial localization and gene expression based on nearby cell receptor density

Escherichia coli were genetically modified to enable programmed motility, sensing, and actuation based on the density of features on nearby surfaces. Then, based on calculated feature density, these cells expressed marker proteins to indicate phenotypic response. Specifically, site-specific synthesis of bacterial quorum sensing autoinducer-2 (AI-2) is used to initiate and recruit motile cells. In our model system, we rewired E. coli's AI-2 signaling pathway to direct bacteria to a squamous cancer cell line of head and neck (SCCHN), where they initiate synthesis of a reporter (drug surrogate) based on a threshold density of epidermal growth factor receptor (EGFR). This represents a new type of controller for targeted drug delivery as actuation (synthesis and delivery) depends on a receptor density marking the diseased cell. The ability to survey local surfaces and initiate gene expression based on feature density represents a new area-based switch in synthetic biology that will find use beyond the proposed cancer model here.

Synthetic biological networks

Despite their obvious relationship and overlap, the field of physics is blessed with many insightful laws, while such laws are sadly absent in biology. Here we aim to discuss how the rise of a more recent field known as synthetic biology may allow us to more directly test hypotheses regarding the possible design principles of natural biological networks and systems. In particular, this review focuses on synthetic gene regulatory networks engineered to perform specific functions or exhibit particular dynamic behaviors. Advances in synthetic biology may set the stage to uncover the relationship of potential biological principles to those developed in physics.

Adaptive noise

In biology, noise implies error and disorder and is therefore something which organisms may seek to minimize and mitigate against. We argue that such noise can be adaptive. Recent studies have shown that gene expression can be noisy, noise can be genetically controlled, genes and gene networks vary in how noisy they are and noise generates phenotypic differences among genetically identical cells. Such phenotypic differences can have fitness benefits, suggesting that evolution can shape noise and that noise may be adaptive. For example, gene networks can generate bistable states resulting in phenotypic diversity and switching among individual cells of a genotype, which may be a bet hedging strategy. Here, we review the sources of noise in gene expression, the extent to which noise in biological systems may be adaptive and suggest that applying evolutionary rigour to the study of noise is necessary to fully understand organismal phenotypes.

Bacterial regulatory networks--from self-organizing molecules to cell shape and patterns in bacterial communities

The ESF-EMBO Conference on 'Bacterial Networks' (BacNet13) was held in March 2013, in Pultusk, Poland. It brought together 164 molecular microbiologists, bacterial systems biologists and synthetic biologists to discuss the architecture, function and dynamics of regulatory networks in bacteria.

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.

A design principle of group-level decision making in cell populations

Populations of cells often switch states as a group to cope with environmental changes such as nutrient availability and cell density. Although the gene circuits that underlie the switches are well understood at the level of single cells, the ways in which such circuits work in concert among many cells to support group-level switches are not fully explored. Experimental studies of microbial quorum sensing show that group-level changes in cellular states occur in either a graded or an all-or-none fashion. Here, we show through numerical simulations and mathematical analysis that these behaviors generally originate from two distinct forms of bistability. The choice of bistability is uniquely determined by a dimensionless parameter that compares the synthesis and the transport of the inducing molecules. The role of the parameter is universal, such that it not only applies to the autoinducing circuits typically found in bacteria but also to the more complex gene circuits involved in transmembrane receptor signaling. Furthermore, in gene circuits with negative feedback, the same dimensionless parameter determines the coherence of group-level transitions from quiescence to a rhythmic state. The set of biochemical parameters in bacterial quorum-sensing circuits appear to be tuned so that the cells can use either type of transition. The design principle identified here serves as the basis for the analysis and control of cellular collective decision making.

Although the genetic circuits underlying state switching at the single-cell level are well understood, how such circuits work in concert among many cells to support the population-level switching of cellular behaviors is not fully explored. Experiments using microbial signaling systems show that group-level changes in cellular state occur in either a graded or an all-or-none fashion. We show that the type of group-level decision making used by populations is uniquely determined by a single dimensionless parameter that compares the quorum-signaling molecules accumulated within the cells with those secreted by the population. Bacterial quorum-sensing circuits appear to be tuned so that the cells can convert between the two types of decision-making in response to slight biochemical variations. Furthermore, the role of the parameter is universal such that it not only applies to the autoinducing circuits typically found in bacteria but also to the more complex gene circuits involved in transmembrane receptor signaling and negative feedback. The design principle that we describe thus serves as the basis for the analysis and control of collective cellular decision making in general.

MstX and a putative potassium channel facilitate biofilm formation in Bacillus subtilis

Biofilms constitute the predominant form of microbial life and a potent reservoir for innate antibiotic resistance in systemic infections. In the spore-forming bacterium Bacillus subtilis, the transition from a planktonic to sessile state is mediated by mutually exclusive regulatory pathways controlling the expression of genes required for flagellum or biofilm formation. Here, we identify mstX and yugO as novel regulators of biofilm formation in B. subtilis. We show that expression of mstX and the downstream putative K+ efflux channel, yugO, is necessary for biofilm development in B. subtilis, and that overexpression of mstX induces biofilm assembly. Transcription of the mstX-yugO operon is under the negative regulation of SinR, a transcription factor that governs the switch between planktonic and sessile states. Furthermore, mstX regulates the activity of Spo0A through a positive autoregulatory loop involving KinC, a histidine kinase that is activated by potassium leakage. The addition of potassium abrogated mstX-mediated biofilm formation. Our findings expand the role of Spo0A and potassium homeostasis in the regulation of bacterial development.

Fluoro-phenyl-styrene-sulfonamide, a novel inhibitor of σB activity, prevents the activation of σB by environmental and energy stresses in Bacillus subtilis

Sigma B (σ(B)) is an alternative sigma factor that regulates the general stress response in Bacillus subtilis and in many other Gram-positive organisms. σ(B) activity in B. subtilis is tightly regulated via at least three distinct pathways within a complex signal transduction cascade in response to a variety of stresses, including environmental stress, energy stress, and growth at high or low temperatures. We probed the ability of fluoro-phenyl-styrene-sulfonamide (FPSS), a small-molecule inhibitor of σ(B) activity in Listeria monocytogenes, to inhibit σ(B) activity in B. subtilis through perturbation of signal transduction cascades under various stress conditions. FPSS inhibited the activation of σ(B) in response to multiple categories of stress known to induce σ(B) activity in B. subtilis. Specifically, FPSS prevented the induction of σ(B) activity in response to energy stress, including entry into stationary phase, phosphate limitation, and azide stress. FPSS also inhibited chill induction of σ(B) activity in a ΔrsbV strain, suggesting that FPSS does not exclusively target the RsbU and RsbP phosphatases or the anti-anti-sigma factor RsbV, all of which contribute to posttranslational regulation of σ(B) activity. Genetic and biochemical experiments, including artificial induction of σ(B), analysis of the phosphorylation state of the anti-anti-sigma factor RsbV, and in vitro transcription assays, indicate that while FPSS does not bind directly to σ(B) to inhibit activity, it appears to prevent the release of B. subtilis σ(B) from its anti-sigma factor RsbW.

Rate of environmental change determines stress response specificity

Cells use general stress response pathways to activate diverse target genes in response to a variety of stresses. However, general stress responses coexist with more specific pathways that are activated by individual stresses, provoking the fundamental question of whether and how cells control the generality or specificity of their response to a particular stress. Here we address this issue using quantitative time-lapse microscopy of the Bacillus subtilis environmental stress response, mediated by σ(B). We analyzed σ(B) activation in response to stresses such as salt and ethanol imposed at varying rates of increase. Dynamically, σ(B) responded to these stresses with a single adaptive activity pulse, whose amplitude depended on the rate at which the stress increased. This rate-responsive behavior can be understood from mathematical modeling of a key negative feedback loop in the underlying regulatory circuit. Using RNAseq we analyzed the effects of both rapid and gradual increases of ethanol and salt stress across the genome. Because of the rate responsiveness of σ(B) activation, salt and ethanol regulons overlap under rapid, but not gradual, increases in stress. Thus, the cell responds specifically to individual stresses that appear gradually, while using σ(B) to broaden the cellular response under more rapidly deteriorating conditions. Such dynamic control of specificity could be a critical function of other general stress response pathways.

Tunable signal processing through modular control of transcription factor translocation

Signaling pathways can induce different dynamics of transcription factor (TF) activation. We explored how TFs process signaling inputs to generate diverse dynamic responses. The budding yeast general stress-responsive TF Msn2 acted as a tunable signal processor that could track, filter, or integrate signals in an input-dependent manner. This tunable signal processing appears to originate from dual regulation of both nuclear import and export by phosphorylation, as mutants with one form of regulation sustained only one signal-processing function. Versatile signal processing by Msn2 is crucial for generating distinct dynamic responses to different natural stresses. Our findings reveal how complex signal-processing functions are integrated into a single molecule and provide a guide for the design of TFs with "programmable" signal-processing functions.

Dynamic persistence of antibiotic-stressed mycobacteria

Exposure of an isogenic bacterial population to a cidal antibiotic typically fails to eliminate a small fraction of refractory cells. Historically, fractional killing has been attributed to infrequently dividing or nondividing "persisters." Using microfluidic cultures and time-lapse microscopy, we found that Mycobacterium smegmatis persists by dividing in the presence of the drug isoniazid (INH). Although persistence in these studies was characterized by stable numbers of cells, this apparent stability was actually a dynamic state of balanced division and death. Single cells expressed catalase-peroxidase (KatG), which activates INH, in stochastic pulses that were negatively correlated with cell survival. These behaviors may reflect epigenetic effects, because KatG pulsing and death were correlated between sibling cells. Selection of lineages characterized by infrequent KatG pulsing could allow nonresponsive adaptation during prolonged drug exposure.

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.