Functional organisation of Escherichia coli transcriptional regulatory network

Iron limitation induces motility in uropathogenic E. coli CFT073 partially through action of LpdA

More than half of women will experience a urinary tract infection (UTI) with most cases caused by uropathogenic Escherichia coli (UPEC). Bacterial swimming motility enhances UPEC pathogenicity, resulting in more severe disease outcomes including kidney infection. Surprisingly, the connection between motility and iron limitation is mostly unexplored despite the lack of free iron available in the host. We sought to investigate a potential connection between iron restriction and regulation of motility in UPEC. We cultured E. coli CFT073, a prototypical UPEC strain, under iron limitation and observed that CFT073 had elevated fliC (flagella) promoter activity, and this iron-specific response was repressed by the addition of exogenous iron. We confirmed increased flagellar expression in CFT073 by measuring fliC transcript, FliC protein, and surface-expressed flagella under iron-limited conditions. Interestingly, known motility regulator flhDC did not have altered transcription under these conditions. To define the regulatory mechanism of this response, we constructed single knockouts of eight master regulators and found the iron-regulated response was lost in crp, arcA, and fis mutants. Thus, we focused on the five genes regulated by all three regulators. Of the five genes knocked out, the iron-regulated motility response was most strongly dysregulated in the lpdA mutant, which also resulted in significantly lowered fitness in the murine model of ascending UTI, both against the WT and a non-motile fliC mutant. Collectively, we demonstrated that iron-mediated motility in CFT073 is partially regulated by lpdA, which contributes to the understanding of how uropathogens differentially regulate motility mechanisms in the iron-restricted host.

IMPORTANCE

Urinary tract infections (UTIs) are ubiquitous and responsible for over five billion dollars in associated health care costs annually. Both iron acquisition and motility are highly studied virulence factors associated with uropathogenic Escherichia coli (UPEC), the main causative agent of uncomplicated UTI. This work is innovative by providing mechanistic insight into the synergistic relationship between these two critical virulence properties. Here, we demonstrate that iron limitation has pleiotropic effects with consequences that extend beyond metabolism and impact other virulence mechanisms. Indeed, targeting iron acquisition as a therapy may lead to an undesirable enhancement of UPEC pathogenesis through increased motility. It is vital to understand the full breadth of UPEC pathogenesis to adequately respond to this common infection, especially with the increase of antibiotic-resistant pathogens.

Inferred regulons are consistent with regulator binding sequences in E. coli

The transcriptional regulatory network (TRN) of E. coli consists of thousands of interactions between regulators and DNA sequences. Regulons are typically determined either from resource-intensive experimental measurement of functional binding sites, or inferred from analysis of high-throughput gene expression datasets. Recently, independent component analysis (ICA) of RNA-seq compendia has shown to be a powerful method for inferring bacterial regulons. However, it remains unclear to what extent regulons predicted by ICA structure have a biochemical basis in promoter sequences. Here, we address this question by developing machine learning models that predict inferred regulon structures in E. coli based on promoter sequence features. Models were constructed successfully (cross-validation AUROC > = 0.8) for 85% (40/47) of ICA-inferred E. coli regulons. We found that: 1) The presence of a high scoring regulator motif in the promoter region was sufficient to specify regulatory activity in 40% (19/47) of the regulons, 2) Additional features, such as DNA shape and extended motifs that can account for regulator multimeric binding, helped to specify regulon structure for the remaining 60% of regulons (28/47); 3) investigating regulons where initial machine learning models failed revealed new regulator-specific sequence features that improved model accuracy. Finally, we found that strong regulatory binding sequences underlie both the genes shared between ICA-inferred and experimental regulons as well as genes in the E. coli core pan-regulon of Fur. This work demonstrates that the structure of ICA-inferred regulons largely can be understood through the strength of regulator binding sites in promoter regions, reinforcing the utility of top-down inference for regulon discovery.

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.

Fibration symmetry uncovers minimal regulatory networks for logical computation in bacteria

Symmetry principles have proven important in physics, deep learning and geometry, allowing for the reduction of complicated systems to simpler, more comprehensible models that preserve the system's features of interest. Biological systems often show a high level of complexity and consist of a high number of interacting parts. Using symmetry fibrations, the relevant symmetries for biological 'message-passing' networks, we reduced the gene regulatory networks of E. coli and B. subtilis bacteria in a way that preserves information flow and highlights the computational capabilities of the network. Nodes that share isomorphic input trees are grouped into equivalence classes called fibers, whereby genes that receive signals with the same 'history' belong to one fiber and synchronize. We further reduce the networks to its computational core by removing "dangling ends" via k-core decomposition. The computational core of the network consists of a few strongly connected components in which signals can cycle while signals are transmitted between these "information vortices" in a linear feed-forward manner. These components are in charge of decision making in the bacterial cell by employing a series of genetic toggle-switch circuits that store memory, and oscillator circuits. These circuits act as the central computation machine of the network, whose output signals then spread to the rest of the network.

Altered motility in response to iron-limitation is regulated by lpdA in uropathogenic E. coli CFT073

More than half of all women will experience a urinary tract infection (UTI) in their lifetime with most cases caused by uropathogenic Escherichia coli (UPEC). Bacterial motility enhances UPEC pathogenicity, resulting in more severe disease outcomes including kidney infection. Surprisingly, the connection between motility and iron limitation is mostly unexplored, despite the lack of free iron available in the host. Therefore, we sought to explore the potential connection between iron restriction and regulation of motility in UPEC. We cultured E. coli CFT073, a prototypical UPEC strain, in media containing an iron chelator. Under iron limitation, CFT073 had elevated fliC (flagella) promoter activity, driving motility on the leading edge of the colony. Furthermore, this iron-specific response was repressed by the addition of exogenous iron. We confirmed increased flagella expression in CFT073 by measuring fliC transcript, FliC protein, and surface-expressed flagella under iron-limited conditions. To define the regulatory mechanism, we constructed single knockouts of eight master regulators. The iron-regulated response was lost in crp, arcA, and fis mutants. Thus, we focused on the five genes regulated by all three transcription factors. Of the five genes knocked out, the iron-regulated motility response was most strongly dysregulated in an lpdA mutant, which also resulted in significantly lowered fitness in the murine model of ascending UTI. Collectively, we demonstrated that iron-mediated motility in CFT073 is regulated by lpdA , which contributes to the understanding of how uropathogens differentially regulate motility mechanisms in the iron-restricted host.

Importance

Urinary tract infections (UTIs) are ubiquitous and responsible for over five billion dollars in associated health care costs annually. Both iron acquisition and motility are highly studied virulence factors associated with uropathogenic E. coli (UPEC), the main causative agent of uncomplicated UTI. This work is innovative by providing mechanistic insight into the synergistic relationship between these two critical virulence properties. Here, we demonstrate that iron limitation has pleiotropic effects with consequences that extend beyond metabolism, and impact other virulence mechanisms. Indeed, targeting iron acquisition as a therapy may lead to an undesirable enhancement of UPEC pathogenesis through increased motility. It is vital to understand the full breadth of UPEC pathogenesis to adequately respond to this common infection, especially with the increase of antibiotic resistant pathogens.

Efforts to Minimise the Bacterial Genome as a Free-Living Growing System

Exploring the minimal genetic requirements for cells to maintain free living is an exciting topic in biology. Multiple approaches are employed to address the question of the minimal genome. In addition to constructing the synthetic genome in the test tube, reducing the size of the wild-type genome is a practical approach for obtaining the essential genomic sequence for living cells. The well-studied Escherichia coli has been used as a model organism for genome reduction owing to its fast growth and easy manipulation. Extensive studies have reported how to reduce the bacterial genome and the collections of genomic disturbed strains acquired, which were sufficiently reviewed previously. However, the common issue of growth decrease caused by genetic disturbance remains largely unaddressed. This mini-review discusses the considerable efforts made to improve growth fitness, which was decreased due to genome reduction. The proposal and perspective are clarified for further accumulated genetic deletion to minimise the Escherichia coli genome in terms of genome reduction, experimental evolution, medium optimization, and machine learning.

Retron-mediated multiplex genome editing and continuous evolution in Escherichia coli

While there are several genome editing techniques available, few are suitable for dynamic and simultaneous mutagenesis of arbitrary targeted sequences in prokaryotes. Here, to address these limitations, we present a versatile and multiplex retron-mediated genome editing system (REGES). First, through systematic optimization of REGES, we achieve efficiency of ∼100%, 85 ± 3%, 69 ± 14% and 25 ± 14% for single-, double-, triple- and quadruple-locus genome editing, respectively. In addition, we employ REGES to generate pooled and barcoded variant libraries with degenerate RBS sequences to fine-tune the expression level of endogenous and exogenous genes, such as transcriptional factors to improve ethanol tolerance and biotin biosynthesis. Finally, we demonstrate REGES-mediated continuous in vivo protein evolution, by combining retron, polymerase-mediated base editing and error-prone transcription. By these case studies, we demonstrate REGES as a powerful multiplex genome editing and continuous evolution tool with broad applications in synthetic biology and metabolic engineering.

The role of replication-induced chromosomal copy numbers in spatio-temporal gene regulation and evolutionary chromosome plasticity

For a coherent response to environmental changes, bacterial evolution has formed a complex transcriptional regulatory system comprising classical DNA binding proteins sigma factors and modulation of DNA topology. In this study, we investigate replication-induced gene copy numbers - a regulatory concept that is unlike the others not based on modulation of promoter activity but on replication dynamics. We show that a large fraction of genes are predominantly affected by transient copy numbers and identify cellular functions and central pathways governed by this mechanism in Escherichia coli. Furthermore, we show quantitatively that the previously observed spatio-temporal expression pattern between different growth phases mainly emerges from transient chromosomal copy numbers. We extend the analysis to the plant pathogen Dickeya dadantii and the biotechnologically relevant organism Vibrio natriegens. The analysis reveals a connection between growth phase dependent gene expression and evolutionary gene migration in these species. A further extension to the bacterial kingdom indicates that chromosome evolution is governed by growth rate related transient copy numbers.

Understanding the Genome-Wide Transcription Response To Various cAMP Levels in Bacteria Using Phenomenological Models

Attempts to understand gene regulation by global transcription factors have largely been limited to expression studies under binary conditions of presence and absence of the transcription factor. Studies addressing genome-wide transcriptional responses to changing transcription factor concentration at high resolution are lacking. Here, we create a data set containing the entire Escherichia coli transcriptome in Luria-Bertani (LB) broth as it responds to 10 different cAMP concentrations spanning the biological range. We use the Hill's model to accurately summarize individual gene responses into three intuitively understandable parameters, Emax, n, and k, reflecting the sensitivity, nonlinearity, and midpoint of the dynamic range. Our data show that most cAMP-regulated genes have an n of >2, with their k values centered around the wild-type concentration of cAMP. Additionally, cAMP receptor protein (CRP) affinity to a promoter is correlated with Emax but not k, hinting that a high-affinity CRP promoter need not ensure transcriptional activation at lower cAMP concentrations and instead affects the magnitude of the response. Finally, genes belonging to different functional classes are tuned to have different k, n, and Emax values. We demonstrate that phenomenological models are a better alternative for studying gene expression trends than classical clustering methods, with the phenomenological constants providing greater insights into how genes are tuned in a regulatory network. IMPORTANCE Different genes may follow different trends in response to various transcription factor concentrations. In this study, we ask two questions: (i) what are the trends that different genes follow in response to changing transcription factor concentrations and (ii) what methods can be used to extract information from the gene trends so obtained. We demonstrate a method to analyze transcription factor concentration-dependent genome-wide expression data using phenomenological models. Conventional clustering methods and principal-component analysis (PCA) can be used to summarize trends in data but have limited interpretability. The use of phenomenological models greatly enhances the interpretability and thus utility of conventional clustering. Transformation of dose-response data into phenomenological constants opens up avenues to ask and answer many different kinds of question. We show that the phenomenological constants obtained from the model fits can be used to generate insights about network topology and allows integration of other experimental data such as chromatin immunoprecipitation sequencing (ChIP-seq) to understand the system in greater detail.

The Spatial Organization of Bacterial Transcriptional Regulatory Networks

The transcriptional regulatory network (TRN) is the central pivot of a prokaryotic organism to receive, process and respond to internal and external environmental information. However, little is known about its spatial organization so far. In recent years, chromatin interaction data of bacteria such as Escherichia coli and Bacillus subtilis have been published, making it possible to study the spatial organization of bacterial transcriptional regulatory networks. By combining TRNs and chromatin interaction data of E. coli and B. subtilis, we explored the spatial organization characteristics of bacterial TRNs in many aspects such as regulation directions (positive and negative), central nodes (hubs, bottlenecks), hierarchical levels (top, middle, bottom) and network motifs (feed-forward loops and single input modules) of the TRNs and found that the bacterial TRNs have a variety of stable spatial organization features under different physiological conditions that may be closely related with biological functions. Our findings provided new insights into the connection between transcriptional regulation and the spatial organization of chromosome in bacteria and might serve as a factual foundation for trying spatial-distance-based gene circuit design in synthetic biology.

Molecular basis for lethal cross-talk between two unrelated bacterial transcription factors - the regulatory protein of a restriction-modification system and the repressor of a defective prophage

Bacterial gene expression depends on the efficient functioning of global transcriptional networks, however their interconnectivity and orchestration rely mainly on the action of individual DNA binding proteins called transcription factors (TFs). TFs interact not only with their specific target sites, but also with secondary (off-target) sites, and vary in their promiscuity. It is not clear yet what mechanisms govern the interactions with secondary sites, and how such rewiring affects the overall regulatory network, but this could clearly constrain horizontal gene transfer. Here, we show the molecular mechanism of one such off-target interaction between two unrelated TFs in Escherichia coli: the C regulatory protein of a Type II restriction-modification system, and the RacR repressor of a defective prophage. We reveal that the C protein interferes with RacR repressor expression, resulting in derepression of the toxic YdaT protein. These results also provide novel insights into regulation of the racR-ydaST operon. We mapped the C regulator interaction to a specific off-target site, and also visualized C protein dynamics, revealing intriguing differences in single molecule dynamics in different genetic contexts. Our results demonstrate an apparent example of horizontal gene transfer leading to adventitious TF cross-talk with negative effects on the recipient's viability. More broadly, this study represents an experimentally-accessible model of a regulatory constraint on horizontal gene transfer.

An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851

BACKGROUND

Healthcare-associated infections due to multidrug-resistant (MDR) bacteria such as Pseudomonas aeruginosa are significant public health issues worldwide. A system biology approach can help understand bacterial behaviour and provide novel ways to identify potential therapeutic targets and develop new drugs. Gene regulatory networks (GRN) are examples of in silico representation of interaction between regulatory genes and their targets.

OBJECTIVES

In this work, we update the MDR P. aeruginosa CCBH4851 GRN reconstruction and analyse and discuss its structural properties.

METHODS

We based this study on the gene orthology inference methodology using the reciprocal best hit method. The P. aeruginosa CCBH4851 genome and GRN, published in 2019, and the P. aeruginosa PAO1 GRN, published in 2020, were used for this update reconstruction process.

FINDINGS

Our result is a GRN with a greater number of regulatory genes, target genes, and interactions compared to the previous networks, and its structural properties are consistent with the complexity of biological networks and the biological features of P. aeruginosa.

MAIN CONCLUSIONS

Here, we present the largest and most complete version of P. aeruginosa GRN published to this date, to the best of our knowledge.

Advanced transcriptomic analysis reveals the role of efflux pumps and media composition in antibiotic responses of Pseudomonas aeruginosa

Pseudomonas aeruginosa is an opportunistic pathogen and major cause of hospital-acquired infections. The virulence of P. aeruginosa is largely determined by its transcriptional regulatory network (TRN). We used 411 transcription profiles of P. aeruginosa from diverse growth conditions to construct a quantitative TRN by identifying independently modulated sets of genes (called iModulons) and their condition-specific activity levels. The current study focused on the use of iModulons to analyze the biofilm production and antibiotic resistance of P. aeruginosa. Our analysis revealed: (i) 116 iModulons, 81 of which show strong association with known regulators; (ii) novel roles of regulators in modulating antibiotics efflux pumps; (iii) substrate-efflux pump associations; (iv) differential iModulon activity in response to beta-lactam antibiotics in bacteriological and physiological media; (v) differential activation of 'Cell Division' iModulon resulting from exposure to different beta-lactam antibiotics and (vi) a role of the PprB iModulon in the stress-induced transition from planktonic to biofilm lifestyle. In light of these results, the construction of an iModulon-based TRN provides a transcriptional regulatory basis for key aspects of P. aeruginosa infection, such as antibiotic stress responses and biofilm formation. Taken together, our results offer a novel mechanistic understanding of P. aeruginosa virulence.

An expanded whole-cell model of E. coli links cellular physiology with mechanisms of growth rate control

Growth and environmental responses are essential for living organisms to survive and adapt to constantly changing environments. In order to simulate new conditions and capture dynamic responses to environmental shifts in a developing whole-cell model of E. coli, we incorporated additional regulation, including dynamics of the global regulator guanosine tetraphosphate (ppGpp), along with dynamics of amino acid biosynthesis and translation. With the model, we show that under perturbed ppGpp conditions, small molecule feedback inhibition pathways, in addition to regulation of expression, play a role in ppGpp regulation of growth. We also found that simulations with dysregulated amino acid synthesis pathways provide average amino acid concentration predictions that are comparable to experimental results but on the single-cell level, concentrations unexpectedly show regular fluctuations. Additionally, during both an upshift and downshift in nutrient availability, the simulated cell responds similarly with a transient increase in the mRNA:rRNA ratio. This additional simulation functionality should support a variety of new applications and expansions of the E. coli Whole-Cell Modeling Project.

Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference

Accurate inference of gene regulatory networks (GRNs) is important to unravel unknown regulatory mechanisms and processes, which can lead to the identification of treatment targets for genetic diseases. A variety of GRN inference methods have been proposed that, under suitable data conditions, perform well in benchmarks that consider the entire spectrum of false-positives and -negatives. However, it is very challenging to predict which single network sparsity gives the most accurate GRN. Lacking criteria for sparsity selection, a simplistic solution is to pick the GRN that has a certain number of links per gene, which is guessed to be reasonable. However, this does not guarantee finding the GRN that has the correct sparsity or is the most accurate one. In this study, we provide a general approach for identifying the most accurate and sparsity-wise relevant GRN within the entire space of possible GRNs. The algorithm, called SPA, applies a “GRN information criterion” (GRNIC) that is inspired by two commonly used model selection criteria, Akaike and Bayesian Information Criterion (AIC and BIC) but adapted to GRN inference. The results show that the approach can, in most cases, find the GRN whose sparsity is close to the true sparsity and close to as accurate as possible with the given GRN inference method and data. The datasets and source code can be found at https://bitbucket.org/sonnhammergrni/spa/.

Mitigating Host Burden of Genetic Circuits by Engineering Autonegatively Regulated Parts and Improving Functional Prediction

Mitigating unintended interferences between circuits and host cells is key to realize applications of synthetic regulatory systems both for bacteria and mammalian cells. Here, we demonstrated that growth burden and circuit dysregulation occurred in a concentration-dependent manner for specific transcription factors (CymR*/CymR) in E.coli, and direct negative feedback modules were able to control the concentration of CymR*/CymR, mitigate growth burden, and restore circuit functions. A quantitative design scheme was developed for circuits embedded with autorepression modules. Four key parameters were theoretically identified to determine the performance of autoregulated switches and were experimentally modified by fine-tuning promoter architectures and cooperativity. Using this strategy, we synthesized a number of switches and demonstrated its improvement of product titers and host growth controlling the complex deoxyviolacein biosynthesis pathway. Furthermore, we restored functions of a dysregulated multilayer NOR gate by integrating autorepression modules. Our work provides a blueprint for engineering host-adaptable synthetic systems.

Gene Regulatory Network Inference and Gene Module Regulating Virulence in Fusarium oxysporum

In this work, we inferred the gene regulatory network (GRN) of the fungus Fusarium oxysporum by using the regulatory networks of Aspergillus nidulans FGSC A4, Neurospora crassa OR74A, Saccharomyces cerevisiae S288c, and Fusarium graminearum PH-1 as templates for sequence comparisons. Topological properties to infer the role of transcription factors (TFs) and to identify functional modules were calculated in the GRN. From these analyzes, five TFs were identified as hubs, including FOXG_04688 and FOXG_05432, which regulate 2,404 and 1,864 target genes, respectively. In addition, 16 communities were identified in the GRN, where the largest contains 1,923 genes and the smallest contains 227 genes. Finally, the genes associated with virulence were extracted from the GRN and exhaustively analyzed, and we identified a giant module with ten TFs and 273 target genes, where the most highly connected node corresponds to the transcription factor FOXG_05265, homologous to the putative bZip transcription factor CPTF1 of Claviceps purpurea, which is involved in ergotism disease that affects cereal crops and grasses. The results described in this work can be used for the study of gene regulation in this organism and open the possibility to explore putative genes associated with virulence against their host.

The Fis Nucleoid Protein Negatively Regulates the Phase Variation fimS Switch of the Type 1 Pilus Operon in Enteropathogenic Escherichia coli

In Escherichia coli the expression of type 1 pili (T1P) is determined by the site-specific inversion of the fimS ON–OFF switch located immediately upstream of major fimbrial subunit gene fimA. Here we investigated the role of virulence (Ler, GrlR, and GrlA) and global regulators (H-NS, IHF, and Fis) in the regulation of the fimS switch in the human enteropathogenic E. coli (EPEC) O127:H6 strain E2348/69. This strain does not produce detectable T1P and PCR analysis of the fimS switch confirmed that it is locked in the OFF orientation. Among the regulator mutants analyzed, only the ∆fis mutant produced significantly high levels of T1P on its surface and yielded high titers of agglutination of guinea pig erythrocytes. Expression analysis of the fimA, fimB, and fimE promoters using lacZ transcriptional fusions indicated that only PfimA activity is enhanced in the absence of Fis. Collectively, these data demonstrate that Fis is a negative regulator of T1P expression in EPEC and suggest that it is required for the FimE-dependent inversion of the fimS switch from the ON-to-OFF direction. It is possible that a similar mechanism of T1P regulation exists in other intestinal and extra-intestinal pathogenic classes of E. coli.

HyfF subunit of hydrogenase 4 is crucial for regulating FOF1 dependent proton/potassium fluxes during fermentation of various concentrations of glucose

Escherichia coli anaerobically ferment glucose and perform proton/potassium exchange at pH 7.5. The role of hyf (hydrogenase 4) subunits (HyfBDF) in sensing different concentrations of glucose (2 g L^-1 or 8 g L^-1) via regulating H⁺/K⁺ exchange was studied. HyfB, HyfD and HyfF part of a protein family of NADH-ubiquinone oxidoreductase ND2, ND4 and ND5 subunits is predicted to operate as proton pump. Specific growth rate was optimal in wild type and mutants grown on 2 g L^-1 glucose reaching ~ 0.8 h^-1. It was shown that in wild type cells proton but not potassium fluxes were stimulated ~ 1.7 fold reaching up to 1.95 mmol/min when cells were grown in the presence of 8 g L^-1 glucose. Interestingly, cells grown on peptone only had similar proton/potassium fluxes as grown on 2 g L^-1glucose. H⁺/K⁺ fluxes of the cells grown on 2 g L^-1 but not 8 g L^-1 glucose depend on externally added glucose concentration in the assays. DCCD-sensitive H⁺ fluxes were tripled and K⁺ fluxes doubled in wild type cells grown on 8 g L^-1 glucose compared to 2 g L^-1 when in the assays 2 g L^-1glucose was added. Interestingly, in hyfF mutant when cells were grown on 2 g L^-1glucose and in 2 g L^-1 assays DCCD-sensitive fluxes were not determined compared to wild type while in hyfD mutant it was doubled reaching up to 0.657 mmol/min. In hyf mutants DCCD-sensitive K⁺ fluxes were stimulated in hyfD and hyfF mutants compared to wild type but depend on external glucose concentration. DCCD-sensitive H⁺/K⁺ ratio was equal to ~ 2 except hyfF mutant grown and assayed on 2 g L^-1glucose while in 8 g L^-1 conditions role of hyfB and hyfD is considered. Taken together it can be concluded that Hyd-4 subunits (HyfBDF) play key role in sensing glucose concentration for regulation of DCCD-sensitive H⁺/K⁺ fluxes for maintaining proton motive force generation.

Phylogeny and potential virulence of cryptic clade Escherichia coli species complex isolates derived from an arable field trial

Analysis of Escherichia coli taxonomy has expanded into a species-complex with the identification of divergent cryptic clades. A key question is the evolutionary trajectory of these clades and their relationship to isolates of clinical or veterinary importance. Since they have some environmental association, we screened a collection of E. coli isolated from a long-term spring barley field trial for their presence. While most isolates clustered into the enteric-clade, four of them clustered into Clade-V, and one in Clade-IV. The Clade -V isolates shared >96% intra-clade average nucleotide sequence identity but <91% with other clades. Although pan-genomics analysis confirmed their taxonomy as Clade -V (E. marmotae), retrospective phylogroup PCR did not discriminate them correctly. Differences in metabolic and adherence gene alleles occurred in the Clade -V isolates compared to E. coli sensu scricto. They also encoded the bacteriophage phage-associated cyto-lethal distending toxin (CDT) and antimicrobial resistance (AMR) genes, including an ESBL, blaOXA-453. Thus, the isolate collection encompassed a genetic diversity, and included cryptic clade isolates that encode potential virulence factors. The analysis has determined the phylogenetic relationship of cryptic clade isolates with E. coli sensu scricto and indicates a potential for horizontal transfer of virulence factors.

Unraveling the functions of uncharacterized transcription factors in Escherichia coli using ChIP-exo

Bacteria regulate gene expression to adapt to changing environments through transcriptional regulatory networks (TRNs). Although extensively studied, no TRN is fully characterized since the identity and activity of all the transcriptional regulators comprising a TRN are not known. Here, we experimentally evaluate 40 uncharacterized proteins in Escherichia coli K-12 MG1655, which were computationally predicted to be transcription factors (TFs). First, we used a multiplexed chromatin immunoprecipitation method combined with lambda exonuclease digestion (multiplexed ChIP-exo) assay to characterize binding sites for these candidate TFs; 34 of them were found to be DNA-binding proteins. We then compared the relative location between binding sites and RNA polymerase (RNAP). We found 48% (283/588) overlap between the TFs and RNAP. Finally, we used these data to infer potential functions for 10 of the 34 TFs with validated DNA binding sites and consensus binding motifs. Taken together, this study: (i) significantly expands the number of confirmed TFs to 276, close to the estimated total of about 280 TFs; (ii) provides putative functions for the newly discovered TFs and (iii) confirms the functions of four representative TFs through mutant phenotypes.

Multiscale Dynamic Structuring of Bacterial Chromosomes

Since the nucleoid was isolated from bacteria in the 1970s, two fundamental questions emerged and are still in the spotlight: how bacteria organize their chromosomes to fit inside the cell and how nucleoid organization enables essential biological processes. During the last decades, knowledge of bacterial chromosome organization has advanced considerably, and today, such chromosomes are considered to be highly organized and dynamic structures that are shaped by multiple factors in a multiscale manner. Here we review not only the classical well-known factors involved in chromosome organization but also novel components that have recently been shown to dynamically shape the 3D structuring of the bacterial genome. We focus on the different functional elements that control short-range organization and describe how they collaborate in the establishment of the higher-order folding and disposition of the chromosome. Recent advances have opened new avenues for a deeper understanding of the principles and mechanisms of chromosome organization in bacteria. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Predicting synchronized gene coexpression patterns from fibration symmetries in gene regulatory networks in bacteria

BACKGROUND

Gene regulatory networks coordinate the expression of genes across physiological states and ensure a synchronized expression of genes in cellular subsystems, critical for the coherent functioning of cells. Here we address the question whether it is possible to predict gene synchronization from network structure alone. We have recently shown that synchronized gene expression can be predicted from symmetries in the gene regulatory networks described by the concept of symmetry fibrations. We showed that symmetry fibrations partition the genes into groups called fibers based on the symmetries of their 'input trees', the set of paths in the network through which signals can reach a gene. In idealized dynamic gene expression models, all genes in a fiber are perfectly synchronized, while less idealized models-with gene input functions differencing between genes-predict symmetry breaking and desynchronization.

RESULTS

To study the functional role of gene fibers and to test whether some of the fiber-induced coexpression remains in reality, we analyze gene fibrations for the gene regulatory networks of E. coli and B. subtilis and confront them with expression data. We find approximate gene coexpression patterns consistent with symmetry fibrations with idealized gene expression dynamics. This shows that network structure alone provides useful information about gene synchronization, and suggest that gene input functions within fibers may be further streamlined by evolutionary pressures to realize a coexpression of genes.

CONCLUSIONS

Thus, gene fibrations provide a sound conceptual tool to describe tunable coexpression induced by network topology and shaped by mechanistic details of gene expression.

Comparative Analysis of the IclR-Family of Bacterial Transcription Factors and Their DNA-Binding Motifs: Structure, Positioning, Co-Evolution, Regulon Content

The IclR-family is a large group of transcription factors (TFs) regulating various biological processes in diverse bacteria. Using comparative genomics techniques, we have identified binding motifs of IclR-family TFs, reconstructed regulons and analyzed their content, finding co-occurrences between the regulated COGs (clusters of orthologous genes), useful for future functional characterizations of TFs and their regulated genes. We describe two main types of IclR-family motifs, similar in sequence but different in the arrangement of the half-sites (boxes), with GKTYCRYW_3-4RYGRAMC and TGRAACAN_1-2TGTTYCA consensuses, and also predict that TFs in 32 orthologous groups have binding sites comprised of three boxes with alternating direction, which implies two possible alternative modes of dimerization of TFs. We identified trends in site positioning relative to the translational gene start, and show that TFs in 94 orthologous groups bind tandem sites with 18-22 nucleotides between their centers. We predict protein-DNA contacts via the correlation analysis of nucleotides in binding sites and amino acids of the DNA-binding domain of TFs, and show that the majority of interacting positions and predicted contacts are similar for both types of motifs and conform well both to available experimental data and to general protein-DNA interaction trends.

Antibiotic tolerance is associated with a broad and complex transcriptional response in E. coli

Antibiotic treatment kills a large portion of a population, while a small, tolerant subpopulation survives. Tolerant bacteria disrupt antibiotic efficacy and increase the likelihood that a population gains antibiotic resistance, a growing health concern. We examined how E. coli transcriptional networks changed in response to lethal ampicillin concentrations. We are the first to apply transcriptional regulatory network (TRN) analysis to antibiotic tolerance by leveraging existing knowledge and our transcriptional data. TRN analysis shows that gene expression changes specific to ampicillin treatment are likely caused by specific sigma and transcription factors typically regulated by proteolysis. These results demonstrate that to survive lethal concentration of ampicillin specific regulatory proteins change activity and cause a coordinated transcriptional response that leverages multiple gene systems.

Ways to minimize bacterial infections, with special reference to Escherichia coli, to cope with the first-week mortality in chicks: an updated overview

On the commercial level, the poultry industry strives to find new techniques to combat bird's infection. During the first week, mortality rate increases in birds because of several bacterial infections of about ten bacterial species, especially colisepticemia. This affects the flock production, uniformity, and suitability for slaughter because of chronic infections. Escherichia coli (E. coli) causes various disease syndromes in poultry, including yolk sac infection (omphalitis), respiratory tract infection, and septicemia. The E. coli infections in the neonatal poultry are being characterized by septicemia. The acute septicemia may cause death, while the subacute form could be characterized through pericarditis, airsacculitis, and perihepatitis. Many E. coli isolates are commonly isolated from commercial broiler chickens as serogroups O₁, O₂, and O₇₈. Although prophylactic antibiotics were used to control mortality associated with bacterial infections of neonatal poultry in the past, the commercial poultry industry is searching for alternatives. This is because of the consumer's demand for reduced antibiotic-resistant bacteria. Despite the vast and rapid development in vaccine technologies against common chicken infectious diseases, no antibiotic alternatives are commercially available to prevent bacterial infections of neonatal chicks. Recent research confirmed the utility of probiotics to improve the health of neonatal poultry. However, probiotics were not efficacious to minimize death and clinical signs associated with neonatal chicks' bacterial infections. This review focuses on the causes of the increased mortality in broiler chicks during the first week of age and the methods used to minimize death.

Uncovering cancer gene regulation by accurate regulatory network inference from uninformative data

The interactions among the components of a living cell that constitute the gene regulatory network (GRN) can be inferred from perturbation-based gene expression data. Such networks are useful for providing mechanistic insights of a biological system. In order to explore the feasibility and quality of GRN inference at a large scale, we used the L1000 data where ~1000 genes have been perturbed and their expression levels have been quantified in 9 cancer cell lines. We found that these datasets have a very low signal-to-noise ratio (SNR) level causing them to be too uninformative to infer accurate GRNs. We developed a gene reduction pipeline in which we eliminate uninformative genes from the system using a selection criterion based on SNR, until reaching an informative subset. The results show that our pipeline can identify an informative subset in an overall uninformative dataset, allowing inference of accurate subset GRNs. The accurate GRNs were functionally characterized and potential novel cancer-related regulatory interactions were identified.

Filtering input fluctuations in intensity and in time underlies stochastic transcriptional pulses without feedback

Stochastic pulsatile dynamics have been observed in an increasing number of biological circuits with known mechanism involving feedback control and bistability. Surprisingly, recent single-cell experiments in Escherichia coli flagellar synthesis showed that flagellar genes are activated in stochastic pulses without the means of feedback. However, the mechanism for pulse generation in these feedbackless circuits has remained unclear. Here, by developing a system-level stochastic model constrained by a large set of single-cell E. coli flagellar synthesis data from different strains and mutants, we identify the general underlying design principles for generating stochastic transcriptional pulses without feedback. Our study shows that an inhibitor (YdiV) of the transcription factor (FlhDC) creates a monotonic ultrasensitive switch that serves as a digital filter to eliminate small-amplitude FlhDC fluctuations. Furthermore, we find that the high-frequency (fast) fluctuations of FlhDC are filtered out by integration over a timescale longer than the timescale of the input fluctuations. Together, our results reveal a filter-and-integrate design for generating stochastic pulses without feedback. This filter-and-integrate mechanism enables a general strategy for cells to avoid premature activation of the expensive downstream gene expression by filtering input fluctuations in both intensity and time so that the system only responds to input signals that are both strong and persistent.

Hfq CLASH uncovers sRNA-target interaction networks linked to nutrient availability adaptation

By shaping gene expression profiles, small RNAs (sRNAs) enable bacteria to efficiently adapt to changes in their environment. To better understand how Escherichia coli acclimatizes to nutrient availability, we performed UV cross-linking, ligation and sequencing of hybrids (CLASH) to uncover Hfq-associated RNA-RNA interactions at specific growth stages. We demonstrate that Hfq CLASH robustly captures bona fide RNA-RNA interactions. We identified hundreds of novel sRNA base-pairing interactions, including many sRNA-sRNA interactions and involving 3’UTR-derived sRNAs. We rediscovered known and identified novel sRNA seed sequences. The sRNA-mRNA interactions identified by CLASH have strong base-pairing potential and are highly enriched for complementary sequence motifs, even those supported by only a few reads. Yet, steady state levels of most mRNA targets were not significantly affected upon over-expression of the sRNA regulator. Our results reinforce the idea that the reproducibility of the interaction, not base-pairing potential, is a stronger predictor for a regulatory outcome.

Stochastic transcriptional pulses orchestrate flagellar biosynthesis in Escherichia coli

The classic picture of flagellum biosynthesis in Escherichia coli, inferred from population measurements, depicts a deterministic program where promoters are sequentially up-regulated and are maintained steadily active throughout exponential growth. However, complex regulatory dynamics at the single-cell level can be masked by bulk measurements. Here, we discover that in individual E. coli cells, flagellar promoters are stochastically activated in pulses. These pulses are coordinated within specific classes of promoters and comprise "on" and "off" states, each of which can span multiple generations. We demonstrate that in this pulsing program, the regulatory logic of flagellar assembly dictates which promoters skip pulses. Surprisingly, pulses do not require specific transcriptional or translational regulation of the flagellar master regulator, FlhDC, but instead appears to be essentially governed by an autonomous posttranslational circuit. Our results suggest that even topologically simple transcriptional networks can generate unexpectedly rich temporal dynamics and phenotypic heterogeneities.

Overcoming the Cost of Positive Autoregulation by Accelerating the Response with a Coupled Negative Feedback

A fundamental trade-off between rapid response and optimal expression of genes below cytotoxic levels exists for many signaling circuits, particularly for positively autoregulated systems with an inherent response delay. Here, we describe a regulatory scheme in the E. coli PhoB-PhoR two-component system, which overcomes the cost of positive feedback and achieves both fast and optimal steadystate response for maximal fitness across different environments. Quantitation of the cellular activities enables accurate modeling of the response dynamics to describe how requirements for optimal protein concentrations place limits on response speed. An observed fast response that exceeds the limit led to the prediction and discovery of a coupled negative autoregulation, which allows fast gene expression without increasing steady-state levels. We demonstrate the fitness advantages for the coupled feedbacks in both dynamic and stable environments. Such regulatory schemes offer great flexibility for accurate control of gene expression levels and dynamics upon environmental changes.

Positive autoregulation of transcription produces a delayed response. Gao and Stock describe the limit of response delay caused by requirements of optimal protein levels in the PhoBR twocomponent system. Coupled negative autoregulation is discovered to allow a strong promoter for fast response without incurring cost of increasing protein expression levels.

Gene regulatory network inference and analysis of multidrug-resistant Pseudomonas aeruginosa

BACKGROUND

Healthcare-associated infections caused by bacteria such as Pseudomonas aeruginosa are a major public health problem worldwide. Gene regulatory networks (GRN) computationally represent interactions among regulatory genes and their targets. They are an important approach to help understand bacterial behaviour and to provide novel ways of overcoming scientific challenges, including the identification of potential therapeutic targets and the development of new drugs.

OBJECTIVES

The goal of this study was to reconstruct the multidrug-resistant (MDR) P. aeruginosa GRN and to analyse its topological properties.

METHODS

The methodology used in this study was based on gene orthology inference using the reciprocal best hit method. We used the genome of P. aeruginosa CCBH4851 as the basis of the reconstruction process. This MDR strain is representative of the sequence type 277, which was involved in an endemic outbreak in Brazil.

FINDINGS

We obtained a network with a larger number of regulatory genes, target genes and interactions as compared to the previously reported network. Topological analysis results are in accordance with the complex network representation of biological processes.

MAIN CONCLUSIONS

The properties of the network were consistent with the biological features of P. aeruginosa. To the best of our knowledge, the P. aeruginosa GRN presented here is the most complete version available to date.

Added value of autoregulation and multi-step kinetics of transcription initiation

Bacterial gene expression regulation occurs mostly during transcription, which has two main rate-limiting steps: the close complex formation, when the RNA polymerase binds to an active promoter, and the subsequent open complex formation, after which it follows elongation. Tuning these steps' kinetics by the action of e.g. transcription factors, allows for a wide diversity of dynamics. For example, adding autoregulation generates single-gene circuits able to perform more complex tasks. Using stochastic models of transcription kinetics with empirically validated parameter values, we investigate how autoregulation and the multi-step transcription initiation kinetics of single-gene autoregulated circuits can be combined to fine-tune steady state mean and cell-to-cell variability in protein expression levels, as well as response times. Next, we investigate how they can be jointly tuned to control complex behaviours, namely, time counting, switching dynamics and memory storage. Overall, our finding suggests that, in bacteria, jointly regulating a single-gene circuit's topology and the transcription initiation multi-step dynamics allows enhancing complex task performance.

Sources, propagation and consequences of stochasticity in cellular growth

Growth impacts a range of phenotypic responses. Identifying the sources of growth variation and their propagation across the cellular machinery can thus unravel mechanisms that underpin cell decisions. We present a stochastic cell model linking gene expression, metabolism and replication to predict growth dynamics in single bacterial cells. Alongside we provide a theory to analyse stochastic chemical reactions coupled with cell divisions, enabling efficient parameter estimation, sensitivity analysis and hypothesis testing. The cell model recovers population-averaged data on growth-dependence of bacterial physiology and how growth variations in single cells change across conditions. We identify processes responsible for this variation and reconstruct the propagation of initial fluctuations to growth and other processes. Finally, we study drug-nutrient interactions and find that antibiotics can both enhance and suppress growth heterogeneity. Our results provide a predictive framework to integrate heterogeneous data and draw testable predictions with implications for antibiotic tolerance, evolutionary and synthetic biology.

The drivers of growth rate variability in bacteria are yet unknown. Here, the authors present a theory to predict the growth dynamics of individual cells and use a stochastic cell model integrating metabolism, gene expression and replication to identify the processes that underlie growth variation.

Influence of Glucose Availability and CRP Acetylation on the Genome-Wide Transcriptional Response of Escherichia coli: Assessment by an Optimized Factorial Microarray Analysis

Background: While in eukaryotes acetylation/deacetylation regulation exerts multiple pleiotropic effects, in Escherichia coli it seems to be more limited and less known. Hence, we aimed to progress in the characterization of this regulation by dealing with three convergent aspects: the effector enzymes involved, the master regulator CRP, and the dependence on glucose availability.

Methods: The transcriptional response of E. coli BW25113 was analyzed across 14 relevant scenarios. These conditions arise when the wild type and four isogenic mutants (defective in deacetylase CobB, defective in N(ε)-lysine acetyl transferase PatZ, Q- and R-type mutants of protein CRP) are studied under three levels of glucose availability (glucose-limited chemostat and glucose-excess or glucose-exhausted in batch culture). The Q-type emulates a permanent stage of CRP^acetylated, whereas the R-type emulates a permanent stage of CRP^deacetylated. The data were analyzed by an optimized factorial microarray method (Q-GDEMAR).

Results: (a) By analyzing one mutant against the other, we were able to unravel the true genes that participate in the interaction between ΔcobB/ΔpatZ mutations and glucose availability; (b) Increasing stages of glucose limitation appear to be associated with the up-regulation of specific sets of target genes rather than with the loss of genes present when glucose is in excess; (c) Both CRP^deacetylated and CRP^acetylated produce extensive changes in specific subsets of genes, but their number and identity depend on the glucose availability; (d) In other sub-sets of genes, the transcriptional effect of CRP seems to be independent of its acetylation or deacetylation; (e) Some specific ontology functions can be associated with each of the different sets of genes detected herein.

Conclusions: CRP cannot be thought of only as an effector of catabolite repression, because it acts along all the glucose conditions tested (excess, limited, and exhausted), exerting both positive and negative effects through different sets of genes. Acetylation of CRP does not seem to be a binary form of regulation, as there is not a univocal relationship between its activation/inhibitory effect and its acetylation/deacetylation stage. All the combinatorial possibilities are observed. During the exponential growth phase, CRP also exerts a very significant transcriptional effect, mainly on flagellar assembly and chemotaxis (FDR = 7.2 × 10⁻⁴⁴).

Systematic identification of novel regulatory interactions controlling biofilm formation in the bacterium Escherichia coli

Here, we investigated novel interactions of three global regulators of the network that controls biofilm formation in the model bacterium Escherichia coli using computational network analysis, an in vivo reporter assay and physiological validation experiments. We were able to map critical nodes that govern planktonic to biofilm transition and identify 8 new regulatory interactions for CRP, IHF or Fis responsible for the control of the promoters of rpoS, rpoE, flhD, fliA, csgD and yeaJ. Additionally, an in vivo promoter reporter assay and motility analysis revealed a key role for IHF as a repressor of cell motility through the control of FliA sigma factor expression. This investigation of first stage and mature biofilm formation indicates that biofilm structure is strongly affected by IHF and Fis, while CRP seems to provide a fine-tuning mechanism. Taken together, the analysis presented here shows the utility of combining computational and experimental approaches to generate a deeper understanding of the biofilm formation process in bacteria.

Global role of the bacterial post-transcriptional regulator CsrA revealed by integrated transcriptomics

CsrA is a post-transcriptional regulatory protein that is widely distributed among bacteria. This protein influences bacterial lifestyle decisions by binding to the 5′ untranslated and/or early coding regions of mRNA targets, causing changes in translation initiation, RNA stability, and/or transcription elongation. Here, we assess the contribution of CsrA to gene expression in Escherichia coli on a global scale. UV crosslinking immunoprecipitation and sequencing (CLIP-seq) identify RNAs that interact directly with CsrA in vivo, while ribosome profiling and RNA-seq uncover the impact of CsrA on translation, RNA abundance, and RNA stability. This combination of approaches reveals unprecedented detail about the regulatory role of CsrA, including novel binding targets and physiological roles, such as in envelope function and iron homeostasis. Our findings highlight the integration of CsrA throughout the E. coli regulatory network, where it orchestrates vast effects on gene expression.

The RNA-binding protein CsrA regulates the expression of hundreds of bacterial genes. Here, Potts et al. use several approaches to assess the contribution of CsrA to global gene expression in E. coli, revealing new binding targets and physiological roles such as in envelope function and iron homeostasis.

Sickeningly Sweet: L-rhamnose stimulates Flavobacterium columnare biofilm formation and virulence

Flavobacterium columnare, the causative agent of columnaris disease, causes substantial mortality worldwide in numerous freshwater finfish species. Due to its global significance and impact on the aquaculture industry continual efforts to better understand basic mechanisms that contribute to disease are urgently needed. The current work sought to evaluate the effect of L-rhamnose on the growth characteristics of F. columnare. While we initially did not observe any key changes during the total growth of F. columnare isolates tested when treated with L-rhamnose, it soon became apparent that the difference lies in the ability of this carbohydrate to facilitate the formation of biofilms. The addition of different concentrations of L-rhamnose consistently promoted the development of biofilms among different F. columnare isolates; however, it does not appear to be sufficient as a sole carbon source for biofilm growth. Our data also suggest that iron acquisition machinery is required for biofilm development. Finally, the addition of different concentrations of L-rhamnose to F. columnare prior to a laboratory challenge increased mortality rates in channel catfish (Ictalurus punctatus) as compared to controls. These results provide further evidence that biofilm formation is an integral virulence factor in the initiation of disease in fish.

The Global Regulatory Cyclic AMP Receptor Protein (CRP) Controls Multifactorial Fluoroquinolone Susceptibility in Salmonella enterica Serovar Typhimurium

Fluoroquinolone antibiotics are prescribed for the treatment of Salmonella enterica infections, but resistance to this family of antibiotics is growing. Here we report that loss of the global regulatory protein cyclic AMP (cAMP) receptor protein (CRP) or its allosteric effector, cAMP, reduces susceptibility to fluoroquinolones. A Δcrp mutation was synergistic with the primary fluoroquinolone resistance allele gyrA83, thus able to contribute to clinically relevant resistance. Decreased susceptibility to fluoroquinolones could be partly explained by decreased expression of the outer membrane porin genes ompA and ompF with a concomitant increase in the expression of the ciprofloxacin resistance efflux pump gene acrB in Δcrp cells. Expression of gyrAB, which encode the DNA supercoiling enzyme GyrAB, which is blocked by fluoroquinolones, and expression of topA, which encodes the dominant supercoiling-relaxing enzyme topoisomerase I, were unchanged in Δcrp cells. Yet Δcrp cells maintained a more relaxed state of DNA supercoiling, correlating with an observed increase in topoisomerase IV (parCE) expression. Surprisingly, the Δcrp mutation had the unanticipated effect of enhancing fitness in the presence of fluoroquinolone antibiotics, which can be explained by the observation that exposure of Δcrp cells to ciprofloxacin had the counterintuitive effect of restoring wild-type levels of DNA supercoiling. Consistent with this, Δcrp cells did not become elongated or induce the SOS response when challenged with ciprofloxacin. These findings implicate the combined action of multiple drug resistance mechanisms in Δcrp cells: reduced permeability and elevated efflux of fluoroquinolones coupled with a relaxed DNA supercoiling state that buffers cells against GyrAB inhibition by fluoroquinolones.

Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities

Transcriptional regulatory networks (TRNs) have been studied intensely for >25 y. Yet, even for the Escherichia coli TRN-probably the best characterized TRN-several questions remain. Here, we address three questions: (i) How complete is our knowledge of the E. coli TRN; (ii) how well can we predict gene expression using this TRN; and (iii) how robust is our understanding of the TRN? First, we reconstructed a high-confidence TRN (hiTRN) consisting of 147 transcription factors (TFs) regulating 1,538 transcription units (TUs) encoding 1,764 genes. The 3,797 high-confidence regulatory interactions were collected from published, validated chromatin immunoprecipitation (ChIP) data and RegulonDB. For 21 different TF knockouts, up to 63% of the differentially expressed genes in the hiTRN were traced to the knocked-out TF through regulatory cascades. Second, we trained supervised machine learning algorithms to predict the expression of 1,364 TUs given TF activities using 441 samples. The algorithms accurately predicted condition-specific expression for 86% (1,174 of 1,364) of the TUs, while 193 TUs (14%) were predicted better than random TRNs. Third, we identified 10 regulatory modules whose definitions were robust against changes to the TRN or expression compendium. Using surrogate variable analysis, we also identified three unmodeled factors that systematically influenced gene expression. Our computational workflow comprehensively characterizes the predictive capabilities and systems-level functions of an organism's TRN from disparate data types.

The combination of the functionalities of feedback circuits is determinant for the attractors' number and size in pathway-like Boolean networks

Molecular regulation was initially assumed to follow both a unidirectional and a hierarchical organization forming pathways. Regulatory processes, however, form highly interlinked networks with non-hierarchical and non-unidirectional structures that contain statistically overrepresented circuits or motifs. Here, we analyze the behavior of pathways containing non-unidirectional (i.e. bidirectional) and non-hierarchical interactions that create motifs. In comparison with unidirectional and hierarchical pathways, our pathways have a high diversity of behaviors, characterized by the size and number of attractors. Motifs have been studied individually showing that feedback circuit motifs regulate the number and size of attractors. It is less clear what happens in molecular networks that usually contain multiple feedbacks. Here, we find that the way feedback circuits couple to each other (i.e., the combination of the functionalities of feedback circuits) regulate both the number and size of the attractors. We show that the different expected results of epistasis analysis (a method to infer regulatory interactions) are produced by many non-hierarchical and non-unidirectional structures. Thus, these structures cannot be correctly inferred by epistasis analysis. Finally, we show that the combinations of functionalities, combined with other network properties, allow for a better characterization of regulatory structures.

Few regulatory metabolites coordinate expression of central metabolic genes in Escherichia coli

Transcription networks consist of hundreds of transcription factors with thousands of often overlapping target genes. While we can reliably measure gene expression changes, we still understand relatively little why expression changes the way it does. How does a coordinated response emerge in such complex networks and how many input signals are necessary to achieve it? Here, we unravel the regulatory program of gene expression in Escherichia coli central carbon metabolism with more than 30 known transcription factors. Using a library of fluorescent transcriptional reporters, we comprehensively quantify the activity of central metabolic promoters in 26 environmental conditions. The expression patterns were dominated by growth rate‐dependent global regulation for most central metabolic promoters in concert with highly condition‐specific activation for only few promoters. Using an approximate mathematical description of promoter activity, we dissect the contribution of global and specific transcriptional regulation. About 70% of the total variance in promoter activity across conditions was explained by global transcriptional regulation. Correlating the remaining specific transcriptional regulation of each promoter with the cell's metabolome response across the same conditions identified potential regulatory metabolites. Remarkably, cyclic AMP, fructose‐1,6‐bisphosphate, and fructose‐1‐phosphate alone explained most of the specific transcriptional regulation through their interaction with the two major transcription factors Crp and Cra. Thus, a surprisingly simple regulatory program that relies on global transcriptional regulation and input from few intracellular metabolites appears to be sufficient to coordinate E. coli central metabolism and explain about 90% of the experimentally observed transcription changes in 100 genes.

Conserved Units of Co-Expression in Bacterial Genomes: An Evolutionary Insight into Transcriptional Regulation

Genome-wide measurements of transcriptional activity in bacteria indicate that the transcription of successive genes is strongly correlated beyond the scale of operons. Here, we analyze hundreds of bacterial genomes to identify supra-operonic segments of genes that are proximal in a large number of genomes. We show that these synteny segments correspond to genomic units of strong transcriptional co-expression. Structurally, the segments contain operons with specific relative orientations (co-directional or divergent) and nucleoid-associated proteins are found to bind at their boundaries. Functionally, operons inside a same segment are highly co-expressed even in the apparent absence of regulatory factors at their promoter regions. Remote operons along DNA can also be co-expressed if their corresponding segments share a transcriptional or sigma factor, without requiring these factors to bind directly to the promoters of the operons. As evidence that these results apply across the bacterial kingdom, we demonstrate them both in the Gram-negative bacterium Escherichia coli and in the Gram-positive bacterium Bacillus subtilis. The underlying process that we propose involves only RNA-polymerases and DNA: it implies that the transcription of an operon mechanically enhances the transcription of adjacent operons. In support of a primary role of this regulation by facilitated co-transcription, we show that the transcription en bloc of successive operons as a result of transcriptional read-through is strongly and specifically enhanced in synteny segments. Finally, our analysis indicates that facilitated co-transcription may be evolutionary primitive and may apply beyond bacteria.

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

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

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

Temperature Change Induces the Expression of vuuA Encoding Vulnibactin Receptor and crp Encoding Cyclic AMP Receptor Protein in Vibrio vulnificus

Upon entering the human body, Vibrio vulnificus, a gram-negative marine bacterium, must withstand a temperature change (TC) from 25 to 37 °C. This bacterium acquires iron mainly via the vulnibactin receptor (VuuA)-mediated iron uptake system (IUS), which is under the positive control of cyclic AMP receptor protein (CRP), a global regulator responsible for catabolite repression. In this study, we examined the effect of TC on the expression of vuuA and crp, and the reciprocal relation between VuuA-mediated IUS and CRP under iron-limited conditions. Iron limitation increased vuuA expression but decreased crp expression. TC resulted in increased vuuA and crp expression. A crp or vuuA mutation reciprocally decreased vuuA or crp expression. TC could increase vuuA or crp expression even in a crp- or vuuA-mutated background. These results indicate that TC increases the expression of both vuuA and crp by facilitating metabolism under iron-limited conditions, and that CRP and VuuA-mediated IUS interact coordinately toward optimal metabolism in V. vulnificus.

Regulation of Expression of Uropathogenic Escherichia coli Nonfimbrial Adhesin TosA by PapB Homolog TosR in Conjunction with H-NS and Lrp

Urinary tract infections (UTIs) are a major burden to human health. The overwhelming majority of UTIs are caused by uropathogenic Escherichia coli (UPEC) strains. Unlike some pathogens, UPEC strains do not have a fixed core set of virulence and fitness factors but do have a variety of adhesins and regulatory pathways. One such UPEC adhesin is the nonfimbrial adhesin TosA, which mediates adherence to the epithelium of the upper urinary tract. The tos operon is AT rich, resides on pathogenicity island aspV, and is not expressed under laboratory conditions. Because of this, we hypothesized that tosA expression is silenced by H-NS. Lrp, based on its prominent function in the regulation of other adhesins, is also hypothesized to contribute to tos operon regulation. Using a variety of in vitro techniques, we mapped both the tos operon promoter and TosR binding sites. We have now identified TosR as a dual regulator of the tos operon, which could control the tos operon in association with H-NS and Lrp. H-NS is a negative regulator of the tos operon, and Lrp positively regulates the tos operon. Exogenous leucine also inhibits Lrp-mediated tos operon positive regulation. In addition, TosR binds to the pap operon, which encodes another important UPEC adhesin, P fimbria. Induction of TosR synthesis reduces production of P fimbria. These studies advance our knowledge of regulation of adhesin expression associated with uropathogen colonization of a host.

The propagation of perturbations in rewired bacterial gene networks

What happens to gene expression when you add new links to a gene regulatory network? To answer this question, we profile 85 network rewirings in E. coli. Here we report that concerted patterns of differential expression propagate from reconnected hub genes. The rewirings link promoter regions to different transcription factor and σ-factor genes, resulting in perturbations that span four orders of magnitude, changing up to ∼ 70% of the transcriptome. Importantly, factor connectivity and promoter activity both associate with perturbation size. Perturbations from related rewirings have more similar transcription profiles and a statistical analysis reveals ∼ 20 underlying states of the system, associating particular gene groups with rewiring constructs. We examine two large clusters (ribosomal and flagellar genes) in detail. These represent alternative global outcomes from different rewirings because of antagonism between these major cell states. This data set of systematically related perturbations enables reverse engineering and discovery of underlying network interactions.

Systems analysis of methylerythritol-phosphate pathway flux in E. coli: insights into the role of oxidative stress and the validity of lycopene as an isoprenoid reporter metabolite

Background

High-throughput screening methods assume that the output measured is representative of changes in metabolic flux toward the desired product and is not affected by secondary phenotypes. However, metabolic engineering can result in unintended phenotypes that may go unnoticed in initial screening. The red pigment lycopene, a carotenoid with antioxidant properties, has been used as a reporter of isoprenoid pathway flux in metabolic engineering for over a decade. Lycopene production is known to vary between wild-type Escherichia coli hosts, but the reasons behind this variation have never been fully elucidated.

Results

In an examination of six E. coli strains we observed that strains also differ in their capacity for increased lycopene production in response to metabolic engineering. A combination of genetic complementation, quantitative SWATH proteomics, and biochemical analysis in closely-related strains was used to examine the mechanistic reasons for variation in lycopene accumulation. This study revealed that rpoS, a gene previously identified in lycopene production association studies, exerts its effect on lycopene accumulation not through modulation of pathway flux, but through alteration of cellular oxidative status. Specifically, absence of rpoS results in increased accumulation of reactive oxygen species during late log and stationary phases. This change in cellular redox has no effect on isoprenoid pathway flux, despite the presence of oxygen-sensitive iron-sulphur cluster enzymes and the heavy redox requirements of the methylerythritol phosphate pathway. Instead, decreased cellular lycopene in the ΔrpoS strain is caused by degradation of lycopene in the presence of excess reactive oxygen species.

Conclusions

Our results demonstrate that lycopene is not a reliable indicator of isoprenoid pathway flux in the presence of oxidative stress, and suggest that caution should be exercised when using lycopene as a screening tool in genome-wide metabolic engineering studies. More extensive use of systems biology for strain analysis will help elucidate such unpredictable side-effects in metabolic engineering projects.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-015-0381-7) contains supplementary material, which is available to authorized users.