Autogenous and nonautogenous control of response in a genetic network

Regulatory roles of the AraC family transcription factor yeaM in the virulence and biofilm formation of Salmonella Typhimurium

Salmonella Typhimurium (S. typhimurium) is a significant zoonotic pathogen responsible for gastroenteritis and severe systemic infections in various hosts. The AraC family transcription factors are key gene expression regulators in prokaryotes, essential for bacterial adaptation to the environment and virulence. Despite their importance, the role of yeaM, a member of this family in S. typhimurium, remains unexplored. To elucidate yeaM regulatory function in virulence and biofilm formation, we engineered mutant and complementary strains of the yeaM gene using homologous recombination. We assessed their capabilities in biofilm formation under different conditions, macrophage adherence and invasion, and virulence in mice. Additionally, we identified potential target genes regulated by yeaM through transcriptome sequencing and confirmed these findings using an electrophoretic mobility shift assay (EMSA) and a dual-luciferase reporter assay. Our results demonstrate that, compared to the parental strain SL1344 and the complemented strain CΔyeaM, the ΔyeaM strain exhibited significantly enhanced biofilm formation, increased invasion of mouse intestinal epithelial cells, enhanced intracellular proliferation within macrophages, and elevated induction of macrophage apoptosis. Furthermore, the ΔyeaM deletion strain displayed significantly increased virulence in mice and enhanced proliferation in milk. Transcriptome analysis revealed that S. typhimurium pathogenicity island 4 (SPI4) genes (siiA, siiB, siiC, siiD, siiF, and siiE) were significantly upregulated following the deletion of the yeaM gene. EMSA and dual-luciferase reporter assays further showed that the yeaM protein can bind to the promoter of the siiA gene and suppress its expression, thereby modulating the biofilm formation and virulence of S. typhimurium.

Dynamical model of antibiotic responses linking expression of resistance genes to metabolism explains emergence of heterogeneity during drug exposures

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistancetetoperon inE. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

Competition and evolutionary selection among core regulatory motifs in gene expression control

Gene products that are beneficial in one environment may become burdensome in another, prompting the emergence of diverse regulatory schemes that carry their own bioenergetic cost. By ensuring that regulators are only expressed when needed, we demonstrate that autoregulation generally offers an advantage in an environment combining mutation and time-varying selection. Whether positive or negative feedback emerges as dominant depends primarily on the demand for the target gene product, typically to ensure that the detrimental impact of inevitable mutations is minimized. While self-repression of the regulator curbs the spread of these loss-of-function mutations, self-activation instead facilitates their propagation. By analyzing the transcription network of multiple model organisms, we reveal that reduced bioenergetic cost may contribute to the preferential selection of autoregulation among transcription factors. Our results not only uncover how seemingly equivalent regulatory motifs have fundamentally different impact on population structure, growth dynamics, and evolutionary outcomes, but they can also be leveraged to promote the design of evolutionarily robust synthetic gene circuits.

Dynamical model of antibiotic responses linking expression of resistance to metabolism explains emergence of heterogeneity during drug exposures

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistance tet operon in E. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

Optimal transcriptional regulation of dynamic bacterial responses to sudden drug exposures

Cellular responses to the presence of toxic compounds in their environment require prompt expression of the correct levels of the appropriate enzymes, which are typically regulated by transcription factors that control gene expression for the duration of the response. The characteristics of each response dictate the choice of regulatory parameters such as the affinity of the transcription factor to its binding sites and the strength of the promoters it regulates. Although much is known about the dynamics of cellular responses, we still lack a framework to understand how different regulatory strategies evolved in natural systems relate to the selective pressures acting in each particular case. Here, we analyze a dynamical model of a typical antibiotic response in bacteria, where a transcriptionally repressed enzyme is induced by a sudden exposure to the drug that it processes. We identify strategies of gene regulation that optimize this response for different types of selective pressures, which we define as a set of costs associated with the drug, enzyme, and repressor concentrations during the response. We find that regulation happens in a limited region of the regulatory parameter space. While responses to more costly (toxic) drugs favor the usage of strongly self-regulated repressors, responses where expression of enzyme is more costly favor the usage of constitutively expressed repressors. Only a very narrow range of selective pressures favor weakly self-regulated repressors. We use this framework to determine which costs and benefits are most critical for the evolution of a variety of natural cellular responses that satisfy the approximations in our model and to analyze how regulation is optimized in new environments with different demands.

DNA cytosine methylation at the lexA promoter of Escherichia coli is stationary phase specific

The bacterial DNA damage response pathway (SOS response) is composed of a network of genes regulated by a single transcriptional repressor, LexA. The lexA promoter, itself, contains two LexA operators, enabling negative feedback. In Escherichia coli, the downstream operator contains a conserved DNA cytosine methyltransferase (Dcm) site that is predicted to be methylated to 5-methylcytosine (5mC) specifically during stationary phase growth, suggesting a regulatory role for DNA methylation in the SOS response. To test this, we quantified 5mC at the lexA locus, and then examined the effect of LexA on Dcm activity, as well as the impact of this 5mC mark on LexA binding, lexA transcription, and SOS response induction. We found that 5mC at the lexA promoter is specific to stationary phase growth, but that it does not affect lexA expression. Our data support a model where LexA binding at the promoter inhibits Dcm activity without an effect on the SOS regulon.

Differences in evolutionary accessibility determine which equally effective regulatory motif evolves to generate pulses

Transcriptional regulatory networks (TRNs) are enriched for certain "motifs." Motif usage is commonly interpreted in adaptationist terms, i.e., that the optimal motif evolves. But certain motifs can also evolve more easily than others. Here, we computationally evolved TRNs to produce a pulse of an effector protein. Two well-known motifs, type 1 incoherent feed-forward loops (I1FFLs) and negative feedback loops (NFBLs), evolved as the primary solutions. The relative rates at which these two motifs evolve depend on selection conditions, but under all conditions, either motif achieves similar performance. I1FFLs generally evolve more often than NFBLs. Selection for a tall pulse favors NFBLs, while selection for a fast response favors I1FFLs. I1FFLs are more evolutionarily accessible early on, before the effector protein evolves high expression; when NFBLs subsequently evolve, they tend to do so from a conjugated I1FFL-NFBL genotype. In the empirical S. cerevisiae TRN, output genes of NFBLs had higher expression levels than those of I1FFLs. These results suggest that evolutionary accessibility, and not relative functionality, shapes which motifs evolve in TRNs, and does so as a function of the expression levels of particular genes.

N-acetylcysteine blocks SOS induction and mutagenesis produced by fluoroquinolones in Escherichia coli

BACKGROUND

Fluoroquinolones such as ciprofloxacin induce the mutagenic SOS response and increase the levels of intracellular reactive oxygen species (ROS). Both the SOS response and ROS increase bacterial mutagenesis, fuelling the emergence of resistant mutants during antibiotic treatment. Recently, there has been growing interest in developing new drugs able to diminish the mutagenic effect of antibiotics by modulating ROS production and the SOS response.

OBJECTIVES

To test whether physiological concentrations of N-acetylcysteine, a clinically safe antioxidant drug currently used in human therapy, is able to reduce ROS production, SOS induction and mutagenesis in ciprofloxacin-treated bacteria without affecting antibiotic activity.

METHODS

The Escherichia coli strain IBDS1 and its isogenic mutant deprived of SOS mutagenesis (TLS-) were treated with different concentrations of ciprofloxacin, N-acetylcysteine or both drugs in combination. Relevant parameters such as MICs, growth rates, ROS production, SOS induction, filamentation and antibiotic-induced mutation rates were evaluated.

RESULTS

Treatment with N-acetylcysteine reduced intracellular ROS levels (by ∼40%), as well as SOS induction (by up to 75%) and bacterial filamentation caused by subinhibitory concentrations of ciprofloxacin, without affecting ciprofloxacin antibacterial activity. Remarkably, N-acetylcysteine completely abolished SOS-mediated mutagenesis.

CONCLUSIONS

Collectively, our data strongly support the notion that ROS are a key factor in antibiotic-induced SOS mutagenesis and open the possibility of using N-acetylcysteine in combination with antibiotic therapy to hinder the development of antibiotic resistance.

The Parameter-Fitness Landscape of lexA Autoregulation in Escherichia coli

Feedback mechanisms are critical to control physiological responses. In gene regulation, one important example, termed negative autoregulation (NAR), occurs when a transcription factor (TF) inhibits its own production. NAR is common across the tree of life, enabling rapid homeostatic control of gene expression. NAR behavior can be described in accordance with its core biochemical parameters, but how constrained these parameters are by evolution is unclear. Here, we describe a model genetic network controlled by an NAR circuit within the bacterium Escherichia coli and elucidate these constraints by experimentally changing a key parameter and measuring its effect on circuit response and fitness. This analysis yielded a parameter-fitness landscape representing the genetic network, providing a window into what gene-environment conditions favor evolution of this regulatory strategy.

Feedback mechanisms are fundamental to the control of physiological responses. One important example in gene regulation, termed negative autoregulation (NAR), occurs when a transcription factor (TF) inhibits its own production through transcriptional repression. This enables more-rapid homeostatic control of gene expression. NAR circuits presumably evolve to limit the fitness costs of gratuitous gene expression. The key biochemical reactions of NAR can be parameterized using a mathematical model of promoter activity; however, this model of NAR has been studied mostly in the context of synthetic NAR circuits that are disconnected from the target genes of the TFs. Thus, it remains unclear how constrained NAR parameters are in a native circuit context, where the TF target genes can have fitness effects on the cell. To quantify these constraints, we created a panel of Escherichia coli strains with different lexA-NAR circuit parameters and analyzed the effect on SOS response function and bacterial fitness. Using a mathematical model for NAR, these experimental data were used to calculate NAR parameter values and derive a parameter-fitness landscape. Without feedback, survival of DNA damage was decreased due to high LexA concentrations and slower SOS “turn-on” kinetics. However, we show that, even in the absence of DNA damage, the lexA promoter is strong enough that, without feedback, high levels of lexA expression result in a fitness cost to the cell. Conversely, hyperfeedback can mimic lexA deletion, which is also costly. This work elucidates the lexA-NAR parameter values capable of balancing the cell’s requirement for rapid SOS response activation with limiting its toxicity.

IMPORTANCE Feedback mechanisms are critical to control physiological responses. In gene regulation, one important example, termed negative autoregulation (NAR), occurs when a transcription factor (TF) inhibits its own production. NAR is common across the tree of life, enabling rapid homeostatic control of gene expression. NAR behavior can be described in accordance with its core biochemical parameters, but how constrained these parameters are by evolution is unclear. Here, we describe a model genetic network controlled by an NAR circuit within the bacterium Escherichia coli and elucidate these constraints by experimentally changing a key parameter and measuring its effect on circuit response and fitness. This analysis yielded a parameter-fitness landscape representing the genetic network, providing a window into what gene-environment conditions favor evolution of this regulatory strategy.

Regulatory Dynamics Determine Cell Fate following Abrupt Antibiotic Exposure

Bacterial resistance mechanisms must cope with transient fast-changing conditions. These systems are often repressed in the absence of the drug, and it is unclear how their regulation can provide a quick response when challenged. Here, we focus on the tet operon, which provides resistance to tetracycline through efflux pump TetA. We show that, somewhat counterintuitively, prompt expression of the TetA repressor TetR is key for cellular survival upon abrupt drug exposure. Tracking individual cells upon exposure, we find that differences in the rate of TetR elevation result in three distinct cell fates: recovery (high rate), death due to excess TetA (intermediate rate), and death from the drug (low rate). A surge of TetR expression optimizes the response by allowing sensitive detection of both the initial rise and the later decline of intracellular drug, avoiding an undesirable overshoot in TetA expression. These results show how regulatory circuits of resistance genes have evolved for optimized dynamics.

Deconstructing a multiple antibiotic resistance regulation through the quantification of its input function

Many essential bacterial responses present complex transcriptional regulation of gene expression. To what extent can the study of these responses substantiate the logic of their regulation? Here, we show how the input function of the genes constituting the response, i.e., the information of how their transcription rates change as function of the signals acting on the regulators, can serve as a quantitative tool to deconstruct the corresponding regulatory logic. To demonstrate this approach, we consider the multiple antibiotic resistance (mar) response in Escherichia coli. By characterizing the input function of its representative genes in wild-type and mutant bacteria, we recognize a dual autoregulation motif as main determinant of the response, which is further adjusted by the interplay with other regulators. We show that basic attributes, like its reaction to a wide range of stress or its moderate expression change, are associated with a strong negative autoregulation, while others, like the buffering of metabolic signals or the lack of memory to previous stress, are related to a weak positive autoregulation. With a mathematical model of the input functions, we identify some constraints fixing the molecular attributes of the regulators, and also notice the relevance of the bicystronic architecture harboring the dual autoregulation that is unique in E. coli. The input function emerges then as a tool to disentangle the rationale behind most of the attributes defining the mar phenotype. Overall, the present study supports the value of characterizing input functions to deconstruct the complexity of regulatory architectures in prokaryotic and eukaryotic systems.

Many cellular responses result from the integration of numerous regulatory signals. To deconstruct the regulation of one of these responses, which enables resistance to multiple antibiotics in Escherichia coli, a team led by Juan F. Poyatos at the National Center for Biotechnology in Madrid studied the response input function by combining theoretical models and experiments. This function quantifies the rate of transcription of the genes constituting the response with respect to the signals acting on its cognate regulators. By examining how the shape of the function changes in different situations, e.g., when a given regulator is mutated, the team identified the implications for the specificity and dynamics of the response of a dual autoregulation at the core of the control architecture. The use of input functions as quantitative tools allows us to reverse engineer the complex regulations that dictate essential physiological functions in both prokaryotic and eukaryotic cells.

A stochastic analysis of autoregulation of gene expression

This paper analyzes, in the context of a prokaryotic cell, the stochastic variability of the number of proteins when there is a control of gene expression by an autoregulation scheme. The goal of this work is to estimate the efficiency of the regulation to limit the fluctuations of the number of copies of a given protein. The autoregulation considered in this paper relies mainly on a negative feedback: the proteins are repressors of their own gene expression. The efficiency of a production process without feedback control is compared to a production process with an autoregulation of the gene expression assuming that both of them produce the same average number of proteins. The main characteristic used for the comparison is the standard deviation of the number of proteins at equilibrium. With a Markovian representation and a simple model of repression, we prove that, under a scaling regime, the repression mechanism follows a Hill repression scheme with an hyperbolic control. An explicit asymptotic expression of the variance of the number of proteins under this regulation mechanism is obtained. Simulations are used to study other aspects of autoregulation such as the rate of convergence to equilibrium of the production process and the case where the control of the production process of proteins is achieved via the inhibition of mRNAs.

Negative Autogenous Control of the Master Type III Secretion System Regulator HrpL in Pseudomonas syringae

The type III secretion system (T3SS) is a principal virulence determinant of the model bacterial plant pathogen Pseudomonas syringae T3SS effector proteins inhibit plant defense signaling pathways in susceptible hosts and elicit evolved immunity in resistant plants. The extracytoplasmic function sigma factor HrpL coordinates the expression of most T3SS genes. Transcription of hrpL is dependent on sigma-54 and the codependent enhancer binding proteins HrpR and HrpS for hrpL promoter activation. hrpL is oriented adjacently to and divergently from the HrpL-dependent gene hrpJ, sharing an intergenic upstream regulatory region. We show that association of the RNA polymerase (RNAP)-HrpL complex with the hrpJ promoter element imposes negative autogenous control on hrpL transcription in P. syringae pv. tomato DC3000. The hrpL promoter was upregulated in a ΔhrpL mutant and was repressed by plasmid-borne hrpL In a minimal Escherichia coli background, the activity of HrpL was sufficient to achieve repression of reconstituted hrpL transcription. This repression was relieved if both the HrpL DNA-binding function and the hrp-box sequence of the hrpJ promoter were compromised, implying dependence upon the hrpJ promoter. DNA-bound RNAP-HrpL entirely occluded the HrpRS and partially occluded the integration host factor (IHF) recognition elements of the hrpL promoter in vitro, implicating inhibition of DNA binding by these factors as a cause of negative autogenous control. A modest increase in the HrpL concentration caused hypersecretion of the HrpA1 pilus protein but intracellular accumulation of later T3SS substrates. We argue that negative feedback on HrpL activity fine-tunes expression of the T3SS regulon to minimize the elicitation of plant defenses.

IMPORTANCE

The United Nations Food and Agriculture Organization has warned that agriculture will need to satisfy a 50% to 70% increase in global food demand if the human population reaches 9 billion by 2050 as predicted. However, diseases caused by microbial pathogens represent a major threat to food security, accounting for over 10% of estimated yield losses in staple wheat, rice, and maize crops. Understanding the decision-making strategies employed by pathogens to coordinate virulence and to evade plant defenses is vital for informing crop resistance traits and management strategies. Many plant-pathogenic bacteria utilize the needle-like T3SS to inject virulence factors into host plant cells to suppress defense signaling. Pseudomonas syringae is an economically and environmentally devastating plant pathogen. We propose that the master regulator of its entire T3SS gene set, HrpL, downregulates its own expression to minimize elicitation of plant defenses. Revealing such conserved regulatory strategies will inform future antivirulence strategies targeting plant pathogens.

Antagonistic autoregulation speeds up a homogeneous response in Escherichia coli

By integrating positive and negative feedback loops, biological systems establish intricate gene expression patterns linked to multistability, pulsing, and oscillations. This depends on the specific characteristics of each interlinked feedback, and thus one would expect additional expression programs to be found. Here, we investigate one such program associated with an antagonistic positive and negative transcriptional autoregulatory motif derived from the multiple antibiotic resistance (mar) system of Escherichia coli. We studied the dynamics of the system by combining a predictive mathematical model with high-resolution experimental measures of the response both at the population and single-cell level. We show that in this motif the weak positive autoregulation does not slow down but rather enhances response speedup in combination with a strong negative feedback loop. This balance of feedback strengths anticipates a homogeneous population phenotype, which we corroborate experimentally. Theoretical analysis also emphasized the specific molecular properties that determine the dynamics of the mar phenotype. More broadly, response acceleration could provide a rationale for the presence of weak positive feedbacks in other biological scenarios exhibiting these interlinked regulatory architectures.

Cooperativity of Negative Autoregulation Confers Increased Mutational Robustness

Negative autoregulation is universally found across organisms. In the bacterium Escherichia coli, transcription factors often repress their own expression to form a negative feedback network motif that enables robustness to changes in biochemical parameters. Here we present a simple phenomenological model of a negative feedback transcription factor repressing both itself and another target gene. The strength of the negative feedback is characterized by three parameters: the cooperativity in self-repression, the maximal expression rate of the transcription factor, and the apparent dissociation constant of the transcription factor binding to its own promoter. Analysis of the model shows that the target gene levels are robust to mutations in the transcription factor, and that the robustness improves as the degree of cooperativity in self-repression increases. The prediction is tested in the LexA transcriptional network of E. coli by altering cooperativity in self-repression and promoter strength. Indeed, we find robustness is correlated with the former. Considering the proposed importance of gene regulation in speciation, parameters governing a transcription factor's robustness to mutation may have significant influence on a cell or organism's capacity to evolve.

A synthetic gene circuit for measuring autoregulatory feedback control

Autoregulatory feedback loops occur in the regulation of molecules ranging from ATP to MAP kinases to zinc. Negative feedback loops can increase a system's robustness, while positive feedback loops can mediate transitions between cell states. Recent genome-wide experimental and computational studies predict hundreds of novel feedback loops. However, not all physical interactions are regulatory, and many experimental methods cannot detect self-interactions. Our understanding of regulatory feedback loops is therefore hampered by the lack of high-throughput methods to experimentally quantify the presence, strength and temporal dynamics of autoregulatory feedback loops. Here we present a mathematical and experimental framework for high-throughput quantification of feedback regulation and apply it to RNA binding proteins (RBPs) in yeast. Our method is able to determine the existence of both direct and indirect positive and negative feedback loops, and to quantify the strength of these loops. We experimentally validate our model using two RBPs which lack native feedback loops and by the introduction of synthetic feedback loops. We find that RBP Puf3 does not natively participate in any direct or indirect feedback regulation, but that replacing the native 3'UTR with that of COX17 generates an auto-regulatory negative feedback loop which reduces gene expression noise. Likewise, RBP Pub1 does not natively participate in any feedback loops, but a synthetic positive feedback loop involving Pub1 results in increased expression noise. Our results demonstrate a synthetic experimental system for quantifying the existence and strength of feedback loops using a combination of high-throughput experiments and mathematical modeling. This system will be of great use in measuring auto-regulatory feedback by RNA binding proteins, a regulatory motif that is difficult to quantify using existing high-throughput methods.

Effect on β-galactosidase synthesis and burden on growth of osmotic stress in Escherichia coli

Osmotic Shock is known to negatively affect growth rate along with an extended lag phase. The reduction in growth rate can be characterized as burden due to the osmotic stress. Studies have shown that production of unnecessary protein also burdens cellular growth. This has been demonstrated by growing Escherichia coli on glycerol in the presence of Isopropyl-β-D-1-thiogalactopyranoside (IPTG) to induce β-galactosidase synthesis which does not offer any benefit towards growth. The trade off between osmotic stress and burden on growth due to unnecessary gene expression has not been enumerated. The influence of osmotic stress on β-galactosidase synthesis and activity is not clearly understood. Here, we study the effect of salt concentration on β-galactosidase activity and burden on growth due to unnecessary gene expression in E.coli. We characterize the burden on growth in presence of varying concentrations of salt in the presence of IPTG using three strains, namely wild type, ∆lacI and ∆lacIlacZ mutant strains. We demonstrate that the salt concentrations, sensitively inhibits enzyme synthesis thereby influencing the burden on growth. In a wild type strain, addition of lactose into the medium demonstrated growth benefit at low salt concentration but not at higher concentrations. The extent of burden due to osmotic shock was higher in a lactose M9 medium than in a glycerol M9 medium. A linear relationship was observed between enzyme activity and burden on growth in various media types studied.

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.

Negative feedback and transcriptional overshooting in a regulatory network for horizontal gene transfer

Horizontal gene transfer (HGT) is a major force driving bacterial evolution. Because of their ability to cross inter-species barriers, bacterial plasmids are essential agents for HGT. This ability, however, poses specific requisites on plasmid physiology, in particular the need to overcome a multilevel selection process with opposing demands. We analyzed the transcriptional network of plasmid R388, one of the most promiscuous plasmids in Proteobacteria. Transcriptional analysis by fluorescence expression profiling and quantitative PCR revealed a regulatory network controlled by six transcriptional repressors. The regulatory network relied on strong promoters, which were tightly repressed in negative feedback loops. Computational simulations and theoretical analysis indicated that this architecture would show a transcriptional burst after plasmid conjugation, linking the magnitude of the feedback gain with the intensity of the transcriptional burst. Experimental analysis showed that transcriptional overshooting occurred when the plasmid invaded a new population of susceptible cells. We propose that transcriptional overshooting allows genome rebooting after horizontal gene transfer, and might have an adaptive role in overcoming the opposing demands of multilevel selection.

In the environment, bacteria often evolve by the acquisition of new genes from different species. Plasmids are small DNA molecules that mediate horizontal gene transfer in bacteria, thus they are fundamental agents for the spread of antibiotic resistances. Plasmids replicate inside the bacterial cytoplasm, and propagate infectiously by contact. Plasmids control these two ways of multiplication, but like many other symbionts they suffer from a tradeoff. If plasmids become very infective, they can spread fast and successfully, but this damages the bacterial hosts they depend upon. If, on the contrary, plasmids become very mild, the host is able to grow better but the ability of plasmids to infect new hosts is hampered. We have studied the regulatory mechanisms plasmids use to overcome this paradox. We discovered that negative feedback, a regulatory motif ubiquitous in the plasmid network, allows transient activation of plasmid functions immediately after plasmids invade a new host. This might be an adaptive strategy for plasmids to be highly infective without damaging their hosts, and it illustrates a natural mechanism for DNA transplantation that could be implemented in synthetic genomic transplants.

Erythropoiesis: from molecular pathways to system properties

Erythropoiesis is regulated through a long-range negative feedback loop, whereby tissue hypoxia stimulates erythropoietin (Epo) secretion, which promotes an increase in erythropoietic rate. However, this long-range feedback loop, by itself, cannot account for the observed system properties of erythropoiesis, namely, a wide dynamic range, stability in the face of random perturbations, and a rapid stress response. Here, we show that three Epo-regulated erythroblast survival pathways each give rise to distinct system properties. The induction of Bcl-xL by signal transducer and activator of transcription 5 (Stat5) is responsive to the rate of change in Epo levels, rather than to its absolute level, and is therefore maximally but transiently activated in acute stress. By contrast, Epo-mediated suppression of the pro-survival Fas and Bim pathways is proportional to the levels of stress/Epo and persists throughout chronic stress. Together, these elements operate in a manner reminiscent of a "proportional-integral-derivative (PID)" feedback controller frequently found in engineering applications. A short-range negative autoregulatory loop within the early erythroblast compartment, operated by Fas/FasL, filters out random noise and controls a reserve pool of early erythroblasts that is poised to accelerate the response to acute stress. Both these properties have previously been identified as inherent to negative regulatory motifs. Finally, we show that signal transduction by Stat5 combines binary and graded modalities, thereby increasing signaling fidelity over the wide dynamic range of Epo found in health and disease.

On the search for design principles in biological systems

The search for basic concepts and underlying principles was at the core of the systems approach to science and technology. This approach was somehow abandoned in mainstream biology after its initial proposal, due to the rise and success of molecular biology. This situation has changed. The accumulated knowledge of decades of molecular studies in combination with new technological advances, while further highlighting the intricacies of natural systems, is also bringing back the quest-for-principles research program. Here, I present two lessons that I derived from my own quest: the importance of studying biological information processing to identify common principles in seemingly unrelated contexts and the adequacy of using known design principles at one level of biological organization as a valuable tool to help recognizing principles at an alternative one. These and additional lessons should contribute to the ultimate goal of establishing principles able to integrate the many scales of biological complexity.

The Escherichia coli SOS gene dinF protects against oxidative stress and bile salts

DNA is constantly damaged by physical and chemical factors, including reactive oxygen species (ROS), such as superoxide radical (O₂⁻), hydrogen peroxide (H₂O₂) and hydroxyl radical (•OH). Specific mechanisms to protect and repair DNA lesions produced by ROS have been developed in living beings. In Escherichia coli the SOS system, an inducible response activated to rescue cells from severe DNA damage, is a network that regulates the expression of more than 40 genes in response to this damage, many of them playing important roles in DNA damage tolerance mechanisms. Although the function of most of these genes has been elucidated, the activity of some others, such as dinF, remains unknown. The DinF deduced polypeptide sequence shows a high homology with membrane proteins of the multidrug and toxic compound extrusion (MATE) family. We describe here that expression of dinF protects against bile salts, probably by decreasing the effects of ROS, which is consistent with the observed decrease in H₂O₂-killing and protein carbonylation. These results, together with its ability to decrease the level of intracellular ROS, suggests that DinF can detoxify, either direct or indirectly, oxidizing molecules that can damage DNA and proteins from both the bacterial metabolism and the environment. Although the exact mechanism of DinF activity remains to be identified, we describe for the first time a role for dinF.

Effect of substrate and IPTG concentrations on the burden to growth of Escherichia coli on glycerol due to the expression of Lac proteins

Expression of proteins unneeded for growth diverts cellular resources from making necessary protein and leads to a reduction in the growth rate of an organism. This reduction in growth rate is termed as cost. Cost plays an important role in determining the selected expression of a protein in a particular environment. Characterization of cost is important in biotechnology industries where microorganisms are used to produce foreign proteins. We have used the lactose system in Escherichia coli to quantify the cost of growth on glycerol in the presence of isopropyl-β-D-thiogalactopyranoside (IPTG), an inducer of the lactose system. The effect of the concentration of the carbon source, glycerol, and the inducer of Lac enzymes, IPTG, is studied. The results show that the cost is dependent on the glycerol concentration with a decreasing trend with increasing concentration of glycerol. Also as expected, the cost increases and saturates at a higher concentration of IPTG. The studies also demonstrate that the cost is higher in early exponential phase relative to late exponential phase during the growth as has been reported in the literature. Hill equation fit yielded a typical Monod-type expression for growth on glycerol with and without IPTG. An apparent half-saturation constant was defined which was used to characterize the burden on growth due to protein expression.

Negative auto-regulation increases the input dynamic-range of the arabinose system of Escherichia coli

Background

Gene regulation networks are made of recurring regulatory patterns, called network motifs. One of the most common network motifs is negative auto-regulation, in which a transcription factor represses its own production. Negative auto-regulation has several potential functions: it can shorten the response time (time to reach halfway to steady-state), stabilize expression against noise, and linearize the gene's input-output response curve. This latter function of negative auto-regulation, which increases the range of input signals over which downstream genes respond, has been studied by theory and synthetic gene circuits. Here we ask whether negative auto-regulation preserves this function also in the context of a natural system, where it is embedded within many additional interactions. To address this, we studied the negative auto-regulation motif in the arabinose utilization system of Escherichia coli, in which negative auto-regulation is part of a complex regulatory network.

Results

We find that when negative auto-regulation is disrupted by placing the regulator araC under constitutive expression, the input dynamic range of the arabinose system is reduced by 10-fold. The apparent Hill coefficient of the induction curve changes from about n = 1 with negative auto-regulation, to about n = 2 when it is disrupted. We present a mathematical model that describes how negative auto-regulation can increase input dynamic-range, by coupling the transcription factor protein level to the input signal.

Conclusions

Here we demonstrate that the negative auto-regulation motif in the native arabinose system of Escherichia coli increases the range of arabinose signals over which the system can respond. In this way, negative auto-regulation may help to increase the input dynamic-range while maintaining the specificity of cooperative regulatory systems. This function may contribute to explaining the common occurrence of negative auto-regulation in biological systems.

Negative autoregulation by Fas stabilizes adult erythropoiesis and accelerates its stress response

Erythropoiesis maintains a stable hematocrit and tissue oxygenation in the basal state, while mounting a stress response that accelerates red cell production in anemia, blood loss or high altitude. Thus, tissue hypoxia increases secretion of the hormone erythropoietin (Epo), stimulating an increase in erythroid progenitors and erythropoietic rate. Several cell divisions must elapse, however, before Epo-responsive progenitors mature into red cells. This inherent delay is expected to reduce the stability of erythropoiesis and to slow its response to stress. Here we identify a mechanism that helps to offset these effects. We recently showed that splenic early erythroblasts, 'EryA', negatively regulate their own survival by co-expressing the death receptor Fas, and its ligand, FasL. Here we studied mice mutant for either Fas or FasL, bred onto an immune-deficient background, in order to avoid an autoimmune syndrome associated with Fas deficiency. Mutant mice had a higher hematocrit, lower serum Epo, and an increased number of splenic erythroid progenitors, suggesting that Fas negatively regulates erythropoiesis at the level of the whole animal. In addition, Fas-mediated autoregulation stabilizes the size of the splenic early erythroblast pool, since mutant mice had a significantly more variable EryA pool than matched control mice. Unexpectedly, in spite of the loss of a negative regulator, the expansion of EryA and ProE progenitors in response to high Epo in vivo, as well as the increase in erythropoietic rate in mice injected with Epo or placed in a hypoxic environment, lagged significantly in the mutant mice. This suggests that Fas-mediated autoregulation accelerates the erythropoietic response to stress. Therefore, Fas-mediated negative autoregulation within splenic erythropoietic tissue optimizes key dynamic features in the operation of the erythropoietic network as a whole, helping to maintain erythroid homeostasis in the basal state, while accelerating the stress response.

Impulse control: temporal dynamics in gene transcription

Regulatory circuits controlling gene expression constantly rewire to adapt to environmental stimuli, differentiation cues, and disease. We review our current understanding of the temporal dynamics of gene expression in eukaryotes and prokaryotes and the molecular mechanisms that shape them. We delineate several prototypical temporal patterns, including "impulse" (or single-pulse) patterns in response to transient environmental stimuli, sustained (or state-transitioning) patterns in response to developmental cues, and oscillating patterns. We focus on impulse responses and their higher-order temporal organization in regulons and cascades and describe how core protein circuits and cis-regulatory sequences in promoters integrate with chromatin architecture to generate these responses.

Failure tolerance of motif structure in biological networks

Complex networks serve as generic models for many biological systems that have been shown to share a number of common structural properties such as power-law degree distribution and small-worldness. Real-world networks are composed of building blocks called motifs that are indeed specific subgraphs of (usually) small number of nodes. Network motifs are important in the functionality of complex networks, and the role of some motifs such as feed-forward loop in many biological networks has been heavily studied. On the other hand, many biological networks have shown some degrees of robustness in terms of their efficiency and connectedness against failures in their components. In this paper we investigated how random and systematic failures in the edges of biological networks influenced their motif structure. We considered two biological networks, namely, protein structure network and human brain functional network. Furthermore, we considered random failures as well as systematic failures based on different strategies for choosing candidate edges for removal. Failure in the edges tipping to high degree nodes had the most destructive role in the motif structure of the networks by decreasing their significance level, while removing edges that were connected to nodes with high values of betweenness centrality had the least effect on the significance profiles. In some cases, the latter caused increase in the significance levels of the motifs.

Early Career Research Award Lecture. Structure, evolution and dynamics of transcriptional regulatory networks

The availability of entire genome sequences and the wealth of literature on gene regulation have enabled researchers to model an organism's transcriptional regulation system in the form of a network. In such a network, TFs (transcription factors) and TGs (target genes) are represented as nodes and regulatory interactions between TFs and TGs are represented as directed links. In the present review, I address the following topics pertaining to transcriptional regulatory networks. (i) Structure and organization: first, I introduce the concept of networks and discuss our understanding of the structure and organization of transcriptional networks. (ii) Evolution: I then describe the different mechanisms and forces that influence network evolution and shape network structure. (iii) Dynamics: I discuss studies that have integrated information on dynamics such as mRNA abundance or half-life, with data on transcriptional network in order to elucidate general principles of regulatory network dynamics. In particular, I discuss how cell-to-cell variability in the expression level of TFs could permit differential utilization of the same underlying network by distinct members of a genetically identical cell population. Finally, I conclude by discussing open questions for future research and highlighting the implications for evolution, development, disease and applications such as genetic engineering.

SOS response induces persistence to fluoroquinolones in Escherichia coli

Bacteria can survive antibiotic treatment without acquiring heritable antibiotic resistance. We investigated persistence to the fluoroquinolone ciprofloxacin in Escherichia coli. Our data show that a majority of persisters to ciprofloxacin were formed upon exposure to the antibiotic, in a manner dependent on the SOS gene network. These findings reveal an active and inducible mechanism of persister formation mediated by the SOS response, challenging the prevailing view that persisters are pre-existing and formed purely by stochastic means. SOS-induced persistence is a novel mechanism by which cells can counteract DNA damage and promote survival to fluoroquinolones. This unique survival mechanism may be an important factor influencing the outcome of antibiotic therapy in vivo.

Effect of subinhibitory concentrations of antibiotics on intrachromosomal homologous recombination in Escherichia coli

Subinhibitory concentrations of some antibiotics, such as fluoroquinolones, have been reported to stimulate mutation and, consequently, bacterial adaptation to different stresses, including antibiotic pressure. In Escherichia coli, this stimulation is mediated by alternative DNA polymerases induced via the SOS response. Sublethal concentrations of the fluoroquinolone ciprofloxacin have been shown to stimulate recombination between divergent sequences in E. coli. However, the effect of ciprofloxacin on recombination between homologous sequences and its SOS dependence have not been studied. Moreover, the possible effects of other antibiotics on homologous recombination remain untested. The aim of this work was to study the effects of sublethal concentrations of ciprofloxacin and 10 additional antibiotics, including different molecular families with different molecular targets, on the rate of homologous recombination of DNA in E. coli. The antibiotics tested were ciprofloxacin, ampicillin, ceftazidime, imipenem, chloramphenicol, tetracycline, gentamicin, rifampin (rifampicin), trimethoprim, fosfomycin, and colistin. Our results indicate that only ciprofloxacin consistently stimulates the intrachromosomal recombinogenic capability of homologous sequences in E. coli. The ciprofloxacin-based stimulation occurs at concentrations and times that apparently do not dramatically compromise the viability of the whole population, and it is dependent on RecA and partially dependent on SOS induction. One of the main findings of this work is that, apart from quinolone antibiotics, none of the most used antibiotics, including trimethoprim (a known inducer of the SOS response), has a clear side effect on homologous recombination in E. coli. In addition to the already described effects of some antibiotics on mutagenicity, DNA transfer, and genetic transformability in naturally competent species, the effect of increasing intrachromosomal recombination of homologous DNA sequences can be uniquely ascribed to fluoroquinolones, at least for E. coli.

Activating and inhibiting connections in biological network dynamics

Background

Many studies of biochemical networks have analyzed network topology. Such work has suggested that specific types of network wiring may increase network robustness and therefore confer a selective advantage. However, knowledge of network topology does not allow one to predict network dynamical behavior – for example, whether deleting a protein from a signaling network would maintain the network's dynamical behavior, or induce oscillations or chaos.

Results

Here we report that the balance between activating and inhibiting connections is important in determining whether network dynamics reach steady state or oscillate. We use a simple dynamical model of a network of interacting genes or proteins. Using the model, we study random networks, networks selected for robust dynamics, and examples of biological network topologies. The fraction of activating connections influences whether the network dynamics reach steady state or oscillate.

Conclusion

The activating fraction may predispose a network to oscillate or reach steady state, and neutral evolution or selection of this parameter may affect the behavior of biological networks. This principle may unify the dynamics of a wide range of cellular networks.

Reviewers

Reviewed by Sergei Maslov, Eugene Koonin, and Yu (Brandon) Xia (nominated by Mark Gerstein). For the full reviews, please go to the Reviewers' comments section.

What determines the assembly of transcriptional network motifs in Escherichia coli?

Transcriptional networks are constituted by a collection of building blocks known as network motifs. Why do motifs appear? An adaptive model of motif emergence was recently questioned in favor of neutralist scenarios. Here, we provide a new picture of motif assembly in Escherichia coli which partially clarifies these contrasting explanations. This is based on characterizing the linkage between motifs and sensing or response specificity of their constituent transcriptional factors (TFs). We find that sensing specificity influences the distribution of autoregulation, while the tendency of a TF to establish feed-forward loops (FFLs) depends on response specificity, i.e., regulon size. Analysis of the latter pattern reveals that coregulation between large regulon-size TFs is common under a network neutral model, leading to the assembly of a great number of FFLs and bifans. In addition, neutral exclusive regulation also leads to a collection of single input modules -the fourth basic motif. On the whole, and even under the conservative neutralist scenario considered, a substantial group of regulatory structures revealed adaptive. These structures visibly function as fully-fledged working units.

A negative feedback loop involving small RNAs accelerates Vibrio cholerae's transition out of quorum-sensing mode

Quorum sensing is a cell-to-cell communication process that allows bacteria to measure their population numbers and to synchronously alter gene expression in response to changes in cell population density. At the core of the Vibrio cholerae quorum-sensing signal transduction pathway lie four redundant small RNAs (sRNAs), named the Quorum Regulatory RNAs (Qrr1-4). Expression of qrr1-4 is cell population density-dependent due to a requirement for the quorum-sensing controlled phosphorylated response regulator LuxO-P, which is abundant only at low cell population density. When expressed, Qrr1-4 repress translation of HapR, the "master" quorum-sensing transcription factor. Here we show a negative feedback loop in which HapR activates transcription of the qrr genes, which indirectly leads to hapR repression. Efficient feedback activation of the qrr genes requires the simultaneous presence of LuxO-P (present only at low cell population density) and HapR (present only at high cell population density). For this reason, the feedback loop does not influence quorum sensing at steady-state low or high cell population density. However, LuxO-P and HapR are simultaneously present immediately following the switch from high to low cell density conditions. In this state, the HapR feedback loop dramatically accelerates V. cholerae's transition from the high to the low cell density mode.

Dynamical pathway analysis

Background

Although a great deal is known about one gene or protein and its functions under different environmental conditions, little information is available about the complex behaviour of biological networks subject to different environmental perturbations. Observing differential expressions of one or more genes between normal and abnormal cells has been a mainstream method of discovering pertinent genes in diseases and therefore valuable drug targets. However, to date, no such method exists for elucidating and quantifying the differential dynamical behaviour of genetic regulatory networks, which can have greater impact on phenotypes than individual genes.

Results

We propose to redress the deficiency by formulating the functional study of biological networks as a control problem of dynamical systems. We developed mathematical methods to study the stability, the controllability, and the steady-state behaviour, as well as the transient responses of biological networks under different environmental perturbations. We applied our framework to three real-world datasets: the SOS DNA repair network in E. coli under different dosages of radiation, the GSH redox cycle in mice lung exposed to either poisonous air or normal air, and the MAPK pathway in mammalian cell lines exposed to three types of HIV type I Vpr, a wild type and two mutant types; and we found that the three genetic networks exhibited fundamentally different dynamical properties in normal and abnormal cells.

Conclusion

Difference in stability, relative stability, degrees of controllability, and transient responses between normal and abnormal cells means considerable difference in dynamical behaviours and different functioning of cells. Therefore differential dynamical properties can be a valuable tool in biomedical research.

Network motifs: theory and experimental approaches

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

A novel role for RecA under non-stress: promotion of swarming motility in Escherichia coli K-12

Background

Bacterial motility is a crucial factor in the colonization of natural environments. Escherichia coli has two flagella-driven motility types: swimming and swarming. Swimming motility consists of individual cell movement in liquid medium or soft semisolid agar, whereas swarming is a coordinated cellular behaviour leading to a collective movement on semisolid surfaces. It is known that swimming motility can be influenced by several types of environmental stress. In nature, environmentally induced DNA damage (e.g. UV irradiation) is one of the most common types of stress. One of the key proteins involved in the response to DNA damage is RecA, a multifunctional protein required for maintaining genome integrity and the generation of genetic variation.

Results

The ability of E. coli cells to develop swarming migration on semisolid surfaces was suppressed in the absence of RecA. However, swimming motility was not affected. The swarming defect of a ΔrecA strain was fully complemented by a plasmid-borne recA gene. Although the ΔrecA cells grown on semisolidsurfaces exhibited flagellar production, they also presented impaired individual movement as well as a fully inactive collective swarming migration. Both the comparative analysis of gene expression profiles in wild-type and ΔrecA cells grown on a semisolid surface and the motility of lexA1 [Ind-] mutant cells demonstrated that the RecA effect on swarming does not require induction of the SOS response. By using a RecA-GFP fusion protein we were able to segregate the effect of RecA on swarming from its other functions. This protein fusion failed to regulate the induction of the SOS response, the recombinational DNA repair of UV-treated cells and the genetic recombination, however, it was efficient in rescuing the swarming motility defect of the ΔrecA mutant. The RecA-GFP protein retains a residual ssDNA-dependent ATPase activity but does not perform DNA strand exchange.

Conclusion

The experimental evidence presented in this work supports a novel role for RecA: the promotion of swarming motility. The defective swarming migration of ΔrecA cells does not appear to be associated with defective flagellar production; rather, it seems to be associated with an abnormal flagellar propulsion function. Our results strongly suggest that the RecA effect on swarming motility does not require an extensive canonical RecA nucleofilament formation. RecA is the first reported cellular factor specifically affecting swarming but not swimming motility in E. coli. The integration of two apparently disconnected biologically important processes, such as the maintenance of genome integrity and motility in a unique protein, may have important evolutive consequences.

Antibiotic-mediated recombination: ciprofloxacin stimulates SOS-independent recombination of divergent sequences in Escherichia coli

The widespread use and abuse of antibiotics as therapeutic agents has produced a major challenge for bacteria, leading to the selection and spread of antibiotic resistant variants. However, antibiotics do not seem to be mere selectors of these variants. Here we show that the fluoroquinolone antibiotic ciprofloxacin, an inhibitor of type II DNA topoisomerases, stimulates intrachromosomal recombination of DNA sequences. The stimulation of recombination between divergent sequences occurs via either the RecBCD or RecFOR pathways and is, surprisingly, independent of SOS induction. Additionally, this stimulation also occurs in a hyperrecombinogenic mismatch repair mutS mutant. It is worth noting that ciprofloxacin also stimulates the conjugational recombination of an antibiotic resistance gene. Finally, we demonstrate that Escherichia coli is able to recover from treatments with recombination-stimulating concentrations of the antibiotic. Thus, fluoroquinolones can increase genetic variation by the stimulation of the recombinogenic capability of treated bacteria (via an SOS-independent mechanism) and consequently may favour the acquisition, evolution and spread of antibiotic resistance determinants.