A comprehensive library of DNA-binding site matrices for 55 proteins applied to the complete Escherichia coli K-12 genome

Comprehensive Characterization of fucAO Operon Activation in Escherichia coli

Wildtype Escherichia coli cells cannot grow on L-1,2-propanediol, as the fucAO operon within the fucose (fuc) regulon is thought to be silent in the absence of L-fucose. Little information is available concerning the transcriptional regulation of this operon. Here, we first confirm that fucAO operon expression is highly inducible by fucose and is primarily attributable to the upstream operon promoter, while the fucO promoter within the 3'-end of fucA is weak and uninducible. Using 5'RACE, we identify the actual transcriptional start site (TSS) of the main fucAO operon promoter, refuting the originally proposed TSS. Several lines of evidence are provided showing that the fucAO locus is within a transcriptionally repressed region on the chromosome. Operon activation is dependent on FucR and Crp but not SrsR. Two Crp-cAMP binding sites previously found in the regulatory region are validated, where the upstream site plays a more critical role than the downstream site in operon activation. Furthermore, two FucR binding sites are identified, where the downstream site near the first Crp site is more important than the upstream site. Operon transcription relies on Crp-cAMP to a greater degree than on FucR. Our data strongly suggest that FucR mainly functions to facilitate the binding of Crp to its upstream site, which in turn activates the fucAO promoter by efficiently recruiting RNA polymerase.

GeF-seq: A Simple Procedure for Base-Pair Resolution ChIP-seq

Nucleotide sequences recognized and bound by DNA-binding proteins (DBPs) are critical to controlling and maintaining gene expression, replication, chromosome segregation, cell division, and nucleoid structure in bacterial cells. Therefore, determination of the binding sequences of DBPs is important not only to study DBP recognition mechanisms but also to understand the fundamentals of cell homeostasis. While ChIP-seq analysis appears to be an effective way to determine DBP binding sites on the genome, the resolution is sometimes not sufficient to identify the sites precisely. Here we introduce a simple and effective method named Genome Footprinting with high-throughput sequencing (GeF-seq) to determine binding sites of DBPs with single base-pair resolution. GeF-seq detects binding sites of DBPs as sharp peaks and thus makes it possible to identify the recognition sequence in each "binding peak" more easily and accurately compared to the common ChIP-seq.

Deep-learning-assisted Sort-Seq enables high-throughput profiling of gene expression characteristics with high precision

Owing to the nondeterministic and nonlinear nature of gene expression, the steady-state intracellular protein abundance of a clonal population forms a distribution. The characteristics of this distribution, including expression strength and noise, are closely related to cellular behavior. However, quantitative description of these characteristics has so far relied on arrayed methods, which are time-consuming and labor-intensive. To address this issue, we propose a deep-learning-assisted Sort-Seq approach (dSort-Seq) in this work, enabling high-throughput profiling of expression properties with high precision. We demonstrated the validity of dSort-Seq for large-scale assaying of the dose-response relationships of biosensors. In addition, we comprehensively investigated the contribution of transcription and translation to noise production in Escherichia coli, from which we found that the expression noise is strongly coupled with the mean expression level. We also found that the transcriptional interference caused by overlapping RpoD-binding sites contributes to noise production, which suggested the existence of a simple and feasible noise control strategy in E. coli.

Unleashing the Influence of cAMP Receptor Protein: The Master Switch of Bacteriocin Export in Pectobacterium carotovorum subsp. carotovorum

Pectobacterium carotovorum subsp. carotovorum (Pcc) is a Gram-negative phytopathogenic bacterium that produces carocin, a low-molecular-weight bacteriocin that can kill related strains in response to factors in the environment such as UV exposure or nutritional deficiency. The function of the catabolite activator protein (CAP), also known as the cyclic AMP receptor protein (CRP), as a regulator of carocin synthesis was examined. The crp gene was knocked out as part of the investigation, and the outcomes were assessed both in vivo and in vitro. Analysis of the DNA sequence upstream of the translation initiation site of carocin S3 revealed two putative binding sites for CRP that were confirmed using a biotinylated probe pull-down experiment. This study revealed that the deletion of crp inhibited genes involved in extracellular bacteriocin export via the flagellar type III secretion system and impacted the production of many low-molecular-weight bacteriocins. The biotinylated probe pull-down test demonstrated that when UV induction was missing, CRP preferentially attached to one of the two CAP sites while binding to both when UV induction was present. In conclusion, our research aimed to simulate the signal transduction system that controls the expression of the carocin gene in response to UV induction.

RpoN Regulon in Erwinia amylovora Revealed by Transcriptional Profiling and In Silico Binding Site Analysis

Erwinia amylovora causes a devastating fire blight disease in apples and pears. One of the main virulence determinants in E. amylovora is the hypersensitive response (HR) and pathogenicity (hrp)-type III secretion system (T3SS), which is activated by the RpoN-HrpL sigma factor cascade. However, the RpoN regulon in E. amylovora has not been investigated. In this study, we determined the RpoN regulon in E. amylovora by combining RNA-seq transcriptomic analysis with in silico binding site analysis. RNA-seq revealed that 262 genes, approximately 7.5% genes in the genome of E. amylovora, were differentially transcribed in the rpoN mutant as compared with the wild type. Specifically, genes associated with virulence, motility, nitrogen assimilation, the PspF system, stress response, and arginine biosynthesis are positively regulated by RpoN, whereas genes associated with biosynthesis of amino acids and sorbitol transport are negatively regulated by RpoN. In silico binding site analysis identified 46 potential target genes with a putative RpoN binding site, and the upstream sequences of six, three, and three genes also contain putative GlnG, PspF, and YfhA binding sites, respectively. Overall, RpoN directly regulates genes associated with virulence, nitrogen assimilation, the PspF system, motility and the YfhA/YfhK two-component regulatory system.

Interpretation of organizational role of proteins on E. coli nucleoid via Hi-C integrated model

Several proteins in Escherichia coli work together to maintain the complex organization of its chromosome. However, the individual roles of these so-called nucleoid-associated proteins (NAPs) in chromosome architectures are not well characterized. Here, we quantitatively dissect the organizational roles of Heat Unstable (HU), a ubiquitous protein in E. coli and MatP, an NAP specifically binding to the Ter macrodomain of the chromosome. Toward this end, we employ a polymer physics-based computer model of wild-type chromosome and their HU- and MatP-devoid counterparts by incorporating their respective experimentally derived Hi-C contact matrix, cell dimensions, and replication status of the chromosome commensurate with corresponding growth conditions. Specifically, our model for the HU-devoid chromosome corroborates well with the microscopy observation of compaction of chromosome at short genomic range but diminished long-range interactions, justifying precedent hypothesis of segregation defect upon HU removal. Control simulations point out that the change in cell dimension and chromosome content in the process of HU removal holds the key to the observed differences in chromosome architecture between wild-type and HU-devoid cells. On the other hand, simulation of MatP-devoid chromosome led to locally enhanced contacts between Ter and its flanking macrodomains, consistent with previous recombination assay experiments and MatP's role in insulation of the Ter macrodomain from the rest of the chromosome. However, the simulation indicated no change in matS sites' localization. Rather, a set of designed control simulations showed that insulation of Ter is not caused by bridging of distant matS sites, also lending credence to a recent mobility experiment on various loci of the E. coli chromosome. Together, the investigations highlight the ability of an integrative model of the bacterial genome in elucidating the role of NAPs and in reconciling multiple experimental observations.

Abundance of integrons in halophilic bacteria

Integrons are genetic platforms used for expressing open reading frames (ORFs) arranged in gene cassettes. Excision and integration of gene cassettes is controlled by their associated integron integrase (IntI). Using IntegronFinder software, we analyzed all complete halophilic genomes available in the HaloDom database, along with selected partial halophilic genomes. We identified 18 new complete bacterial integrons and 46 clusters of attC sites lacking a neighboring integron-integrase (CALINs). Different classes of insertion sequences (ISs) were also identified within and nearby integrons and CALINs; with the abundance of IS1182 elements and different ISs that can presumably mobilize adjacent genomic structures. Different promoters for intI genes (PintI) showed nearby binding sites for arginine repressor (ArgR), raising the possibility that IntIs expression and recombination activity are regulated by these proteins. Our findings reveal the existence of new integrons in halophilic bacteria with possible adaptive roles.

MetaLogo: a heterogeneity-aware sequence logo generator and aligner

Sequence logos are used to visually display conservations and variations in short sequences. They can indicate the fixed patterns or conserved motifs in a batch of DNA or protein sequences. However, most of the popular sequence logo generators are based on the assumption that all the input sequences are from the same homologous group, which will lead to an overlook of the heterogeneity among the sequences during the sequence logo making process. Heterogeneous groups of sequences may represent clades of different evolutionary origins, or genes families with different functions. Therefore, it is essential to divide the sequences into different phylogenetic or functional groups to reveal their specific sequence motifs and conservation patterns. To solve these problems, we developed MetaLogo, which can automatically cluster the input sequences after multiple sequence alignment and phylogenetic tree construction, and then output sequence logos for multiple groups and aligned them in one figure. User-defined grouping is also supported by MetaLogo to allow users to investigate functional motifs in a more delicate and dynamic perspective. MetaLogo can highlight both the homologous and nonhomologous sites among sequences. MetaLogo can also be used to annotate the evolutionary positions and gene functions of unknown sequences, together with their local sequence characteristics. We provide users a public MetaLogo web server (http://metalogo.omicsnet.org), a standalone Python package (https://github.com/labomics/MetaLogo), and also a built-in web server available for local deployment. Using MetaLogo, users can draw informative, customized and publishable sequence logos without any programming experience to present and investigate new knowledge on specific sequence sets.

Dynamics of Proteins and Macromolecular Machines in Escherichia coli

Proteins are major contributors to the composition and the functions in the cell. They often assemble into larger structures, macromolecular machines, to carry out intricate essential functions. Although huge progress in understanding how macromolecular machines function has been made by reconstituting them in vitro, the role of the intracellular environment is still emerging. The development of fluorescence microscopy techniques in the last 2 decades has allowed us to obtain an increased understanding of proteins and macromolecular machines in cells. Here, we describe how proteins move by diffusion, how they search for their targets, and how they are affected by the intracellular environment. We also describe how proteins assemble into macromolecular machines and provide examples of how frequent subunit turnover is used for them to function and to respond to changes in the intracellular conditions. This review emphasizes the constant movement of molecules in cells, the stochastic nature of reactions, and the dynamic nature of macromolecular machines.

Uncovering Transcriptional Regulators and Targets of sRNAs Using an Integrative Data-Mining Approach: H-NS-Regulated RseX as a Case Study

Bacterial small RNAs (sRNAs) play a vital role in pathogenesis by enabling rapid, efficient networks of gene attenuation during infection. In recent decades, there has been a surge in the number of proposed and biochemically-confirmed sRNAs in both Gram-positive and Gram-negative pathogens. However, limited homology, network complexity, and condition specificity of sRNA has stunted complete characterization of the activity and regulation of these RNA regulators. To streamline the discovery of the expression of sRNAs, and their post-transcriptional activities, we propose an integrative in vivo data-mining approach that couples DNA protein occupancy, RNA-seq, and RNA accessibility data with motif identification and target prediction algorithms. We benchmark the approach against a subset of well-characterized E. coli sRNAs for which a degree of in vivo transcriptional regulation and post-transcriptional activity has been previously reported, finding support for known regulation in a large proportion of this sRNA set. We showcase the abilities of our method to expand understanding of sRNA RseX, a known envelope stress-linked sRNA for which a cellular role has been elusive due to a lack of native expression detection. Using the presented approach, we identify a small set of putative RseX regulators and targets for experimental investigation. These findings have allowed us to confirm native RseX expression under conditions that eliminate H-NS repression as well as uncover a post-transcriptional role of RseX in fimbrial regulation. Beyond RseX, we uncover 163 putative regulatory DNA-binding protein sites, corresponding to regulation of 62 sRNAs, that could lead to new understanding of sRNA transcription regulation. For 32 sRNAs, we also propose a subset of top targets filtered by engagement of regions that exhibit binding site accessibility behavior in vivo. We broadly anticipate that the proposed approach will be useful for sRNA-reliant network characterization in bacteria. Such investigations under pathogenesis-relevant environmental conditions will enable us to deduce complex rapid-regulation schemes that support infection.

Optimized expression and purification of a soluble BMP2 variant based on in-silico design

Bone morphogenetic protein 2 (BMP2¹) is a highly interesting therapeutic growth factor due to its strong osteogenic/osteoinductive potential. However, its pronounced aggregation tendency renders recombinant and soluble production troublesome and complex. While prokaryotic expression systems can provide BMP2 in large amounts, the typically insoluble protein requires complex denaturation-renaturation procedures with medically hazardous reagents to obtain natively folded homodimeric BMP2. Based on a detailed aggregation analysis of wildtype BMP2, we designed a hydrophilic variant of BMP2 additionally containing an improved heparin binding site (BMP2-2Hep-7M). Consecutive optimization of BMP2-2Hep-7M expression and purification enabled production of soluble dimeric BMP2-2Hep-7M in high yield in E. coli. This was achieved by a) increasing protein hydrophilicity via introducing seven point mutations within aggregation hot spots of wildtype BMP2 and a longer N-terminus resulting in higher affinity for heparin, b) by employing E. coli strain SHuffle® T7, which enables the structurally essential disulfide-bond formation in BMP2 in the cytoplasm, c) by using BMP2 variant characteristic soluble expression conditions and application of l-arginine as solubility enhancer. The BMP2 variant BMP2-2Hep-7M shows strongly attenuated although not completely eliminated aggregation tendency.

High-pressure processing-induced transcriptome response during recovery of Listeria monocytogenes

Background

High-pressure processing (HPP) is a commonly used technique in the food industry to inactivate pathogens, including L. monocytogenes. It has been shown that L. monocytogenes is able to recover from HPP injuries and can start to grow again during long-term cold storage. To date, the gene expression profiling of L. monocytogenes during HPP damage recovery at cooling temperature has not been studied. In order identify key genes that play a role in recovery of the damage caused by HPP treatment, we performed RNA-sequencing (RNA-seq) for two L. monocytogenes strains (barotolerant RO15 and barosensitive ScottA) at nine selected time points (up to 48 h) after treatment with two pressure levels (200 and 400 MPa).

Results

The results showed that a general stress response was activated by SigB after HPP treatment. In addition, the phosphotransferase system (PTS; mostly fructose-, mannose-, galactitol-, cellobiose-, and ascorbate-specific PTS systems), protein folding, and cobalamin biosynthesis were the most upregulated genes during HPP damage recovery. We observed that cell-division-related genes (divIC, dicIVA, ftsE, and ftsX) were downregulated. By contrast, peptidoglycan-synthesis genes (murG, murC, and pbp2A) were upregulated. This indicates that cell-wall repair occurs as a part of HPP damage recovery. We also observed that prophage genes, including anti-CRISPR genes, were induced by HPP. Interestingly, a large amount of RNA-seq data (up to 85%) was mapped to Rli47, which is a non-coding RNA that is upregulated after HPP. Thus, we predicted that Rli47 plays a role in HPP damage recovery in L. monocytogenes. Moreover, gene-deletion experiments showed that amongst peptidoglycan biosynthesis genes, pbp2A mutants are more sensitive to HPP.

Conclusions

We identified several genes and mechanisms that may play a role in recovery from HPP damage of L. monocytogenes. Our study contributes to new information on pathogen inactivation by HPP.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07407-6.

Transcriptomic time-series analysis of cold- and heat-shock response in psychrotrophic lactic acid bacteria

BACKGROUND

Psychrotrophic lactic acid bacteria (LAB) species are the dominant species in the microbiota of cold-stored modified-atmosphere-packaged food products and are the main cause of food spoilage. Despite the importance of psychrotrophic LAB, their response to cold or heat has not been studied. Here, we studied the transcriptome-level cold- and heat-shock response of spoilage lactic acid bacteria with time-series RNA-seq for Le. gelidum, Lc. piscium, and P. oligofermentans at 0 °C, 4 °C, 14 °C, 25 °C, and 28 °C.

RESULTS

We observed that the cold-shock protein A (cspA) gene was the main cold-shock protein gene in all three species. Our results indicated that DEAD-box RNA helicase genes (cshA, cshB) also play a critical role in cold-shock response in psychrotrophic LAB. In addition, several RNase genes were involved in cold-shock response in Lc. piscium and P. oligofermentans. Moreover, gene network inference analysis provided candidate genes involved in cold-shock response. Ribosomal proteins, tRNA modification, rRNA modification, and ABC and efflux MFS transporter genes clustered with cold-shock response genes in all three species, indicating that these genes could be part of the cold-shock response machinery. Heat-shock treatment caused upregulation of Clp protease and chaperone genes in all three species. We identified transcription binding site motifs for heat-shock response genes in Le. gelidum and Lc. piscium. Finally, we showed that food spoilage-related genes were upregulated at cold temperatures.

CONCLUSIONS

The results of this study provide new insights on the cold- and heat-shock response of psychrotrophic LAB. In addition, candidate genes involved in cold- and heat-shock response predicted using gene network inference analysis could be used as targets for future studies.

The NtrYX Two-Component System Regulates the Bacterial Cell Envelope

The bacterial cell envelope provides many important functions. It protects cells from harsh environments, serves as a selective permeability barrier, houses bioenergetic functions, defines sensitivity to antibacterial agents, and plays a crucial role in biofilm formation, symbiosis, and virulence. Despite the important roles of this cellular compartment, we lack a detailed understanding of the biosynthesis and remodeling of the cell envelope. Here, we report that the R. sphaeroides two-component signaling system NtrYX is a previously undescribed regulator of cell envelope processes, providing evidence that it is directly involved in controlling transcription of genes involved in cell envelope assembly, structure, and function in this and possibly other bacteria. Thus, our data report on a newly discovered process used by bacteria to assemble and remodel the cell envelope.

Activity of the NtrYX two-component system has been associated with important processes in diverse bacteria, ranging from symbiosis to nitrogen and energy metabolism. In the facultative alphaproteobacterium Rhodobacter sphaeroides, loss of the two-component system NtrYX results in increased lipid production and sensitivity to some known cell envelope-active compounds. In this study, we show that NtrYX directly controls multiple properties of the cell envelope. We find that the response regulator NtrX binds upstream of cell envelope genes, including those involved in peptidoglycan biosynthesis and modification and in cell division. We show that loss of NtrYX impacts the cellular levels of peptidoglycan precursors and lipopolysaccharide and alters cell envelope structure, increasing cell length and the thickness of the periplasm. Cell envelope function is also disrupted in the absence of NtrYX, resulting in increased outer membrane permeability. Based on the properties of R. sphaeroides cells lacking NtrYX and the target genes under direct control of this two-component system, we propose that NtrYX plays a previously undescribed, and potentially conserved, role in the assembly, structure, and function of the cell envelope in a variety of bacteria.

UV oxidation of cyclic AMP receptor protein, a global bacterial gene regulator, decreases DNA binding and cleaves DNA at specific sites

UV light is a widely-employed, and environmentally-sensitive bactericide but its mechanism of action is not fully defined. Proteins are major chromophores and targets for damage due to their abundance, but the role of proteins in inducing damage to bound DNA, and the effects on DNA-protein interactions is less well characterized. In E. coli (and other Gram-negative bacteria) the cyclic AMP receptor protein (CRP/CAP) regulates more than 500 genes. In this study we show that exposure of isolated dimeric CRP-cAMP to UV modifies specific Met, Trp, Tyr, and Pro side-chains, induces inter-protein Tyr63-Tyr41 cross-links, and decreases DNA binding via oxidation of Met114/Pro110 residues in close proximity at the CRP dimer interface. UV exposure also modifies DNA-bound cAMP-CRP, with this resulting in DNA cleavage at specific G/C residues within the sequence bound to CRP, but not at other G/C sites. Oxidation also increases CRP dissociation from DNA. The modifications at the CRP dimer interface, and the site-specific DNA strand cleavage are proposed to occur via oxidation of two species Met residues (Met114 and Met189, respectively) to reactive persulfoxides that damage neighbouring amino acids and DNA bases. These data suggest that modification to CRP, and bound DNA, contributes to UV sensitivity.

The Escherichia coli MarA protein regulates the ycgZ-ymgABC operon to inhibit biofilm formation

The Escherichia coli marRAB operon is a paradigm for chromosomally encoded antibiotic resistance. The operon exerts its effect via an encoded transcription factor called MarA that modulates efflux pump and porin expression. In this work, we show that MarA is also a regulator of biofilm formation. Control is mediated by binding of MarA to the intergenic region upstream of the ycgZ-ymgABC operon. The operon, known to influence the formation of curli fibres and colanic acid, is usually expressed during periods of starvation. Hence, the ycgZ-ymgABC promoter is recognised by σ³⁸ (RpoS)-associated RNA polymerase (RNAP). Surprisingly, MarA does not influence σ³⁸ -dependent transcription. Instead, MarA drives transcription by the housekeeping σ⁷⁰ -associated RNAP. The effects of MarA on ycgZ-ymgABC expression are coupled with biofilm formation by the rcsCDB phosphorelay system, with YcgZ, YmgA and YmgB forming a complex that directly interacts with the histidine kinase domain of RcsC.

New insights into the molecular physiology of sulfoxide reduction in bacteria

Sulfoxides occur in biology as products of the S-oxygenation of small molecules as well as in peptides and proteins and their formation is often associated with oxidative stress and can affect biological function. In bacteria, sulfoxide damage can be reversed by different types of enzymes. Thioredoxin-dependent peptide methionine sulfoxide reductases (MSR proteins) repair oxidized methionine residues and are found in all Domains of life. In bacteria MSR proteins are often found in the cytoplasm but in some bacteria, including pathogenic Neisseria, Streptococci, and Haemophilus they are extracytoplasmic. Mutants lacking MSR proteins are often sensitive to oxidative stress and in pathogens exhibit decreased virulence as indicated by reduced survival in host cell or animal model systems. Molybdenum enzymes are also known to reduce S-oxides and traditionally their physiological role was considered to be in anaerobic respiration using dimethylsulfoxide (DMSO) as an electron acceptor. However, it now appears that some enzymes (MtsZ) of the DMSO reductase family of Mo enzymes use methionine sulfoxide as preferred physiological substrate and thus may be involved in scavenging/recycling of this amino acid. Similarly, an enzyme (MsrP/YedY) of the sulfite oxidase family of Mo enzymes has been shown to be involved in repair of methionine sulfoxides in periplasmic proteins. Again, some mutants deficient in Mo-dependent sulfoxide reductases exhibit reduced virulence, and there is evidence that these Mo enzymes and some MSR systems are induced by hypochlorite produced by the innate immune system. This review describes recent advances in the understanding of the molecular microbiology of MSR systems and the broadening of the role of Mo-dependent sulfoxide reductase to encompass functions beyond anaerobic respiration.

From biophysics to 'omics and systems biology

Recent decades brought a revolution to biology, driven mainly by exponentially increasing amounts of data coming from "'omics" sciences. To handle these data, bioinformatics often has to combine biologically heterogeneous signals, for which methods from statistics and engineering (e.g. machine learning) are often used. While such an approach is sometimes necessary, it effectively treats the underlying biological processes as a black box. Similarly, systems biology deals with inherently complex systems, characterized by a large number of degrees of freedom, and interactions that are highly non-linear. To deal with this complexity, the underlying physical interactions are often (over)simplified, such as in Boolean modelling of network dynamics. In this review, we argue for the utility of applying a biophysical approach in bioinformatics and systems biology, including discussion of two examples from our research which address sequence analysis and understanding intracellular gene expression dynamics.

Induction of the immunoprotective coat of Yersinia pestis at body temperature is mediated by the Caf1R transcription factor

BACKGROUND

Thermal regulation of gene expression occurs in many microorganisms, and is mediated via several typical mechanisms. Yersinia pestis is the causative agent of the plague and spreads by zoonotic transfer from fleas to mammalian blood with a concomitant rapid temperature change, from ambient to 37 °C, which induces the expression of capsular antigen (Caf1) that inhibits phagocytosis. Caf1 is formed into long polymeric fimbriae by a periplasmic chaperone (Caf1M) and outer membrane usher (Caf1A). All three are encoded on an operon regulated by an AraC-type transcription factor Caf1R. The aim of this study was to determine the role of Caf1R in the thermal control of caf1 operon gene expression.

RESULTS

PCR analysis of cDNA demonstrated that the genes of the operon are transcribed as a single polycistronic mRNA. Bioinformatic analysis, supported by deletion mutagenesis, then revealed a region containing the promoter of this polycistronic transcript that was critical for Caf1 protein expression. Caf1R was found to be essential for Caf1 protein production. Finally, RT-PCR analysis and western blot experiments showed large, Caf1R dependent increases in caf1 operon transcripts upon a shift in temperature from 25 °C to 35 °C.

CONCLUSIONS

The results show that thermal control of Caf1 polymer production is established at the transcriptional level, in a Caf1R dependent manner. This gives us new insights into how a virulent pathogen evades destruction by the immune system by detecting and responding to environmental changes.

Escherichia coli OxyS RNA triggers cephalothin resistance by modulating the expression of CRP-associated genes

Antibiotics have been one of the most successful forms of therapy in medicine. However, the efficiency of antibiotics is compromised by the emergence of antibiotic-resistant pathogens. To reduce antibiotic resistance, complete understanding of bacterial tactics to defend themselves against antibiotics is necessary. Small-noncoding RNAs (sRNAs) modulate gene expression by base-pairing with multiple target mRNAs. Cellular levels of Hfq-dependent sRNAs influence antibiotic resistance by modulating expression of specific target genes; therefore, such sRNAs could be a good tool to identify target mRNAs that modulate antibiotic susceptibility and may themselves be used as druggable molecules. Here, we report the identification of genes and pathways associated with OxyS RNA-mediated cephalothin resistance using phenotypic and expression analyses of OxyS-regulated genes identified by RNA-seq, literature mining, or predictions. From our studies we found that the differential expression of 27 OxyS-regulated genes was involved in cephalothin susceptibility. Among them, 17 gene knockouts showed resistance to the drug and nine from them is associated with cAMP receptor protein (CRP), a transcriptional dual regulator in E. coli. Moreover, levels of OxyS and OxyS-modulated genes (cycA and cysH) were also altered in multidrug-resistant (MDR) E. coli strains. Together, our data suggest that OxyS extensively modulates gene expression in multiple pathways to develop cephalothin resistance. In addition, OxyS and its regulated target genes, either individually or in combination, could be used as molecular markers and targets for the identification and eradication of cephalothin-resistant strains.

Feedbacks from the metabolic network to the genetic network reveal regulatory modules in E. coli and B. subtilis

The genetic regulatory network (GRN) plays a key role in controlling the response of the cell to changes in the environment. Although the structure of GRNs has been the subject of many studies, their large scale structure in the light of feedbacks from the metabolic network (MN) has received relatively little attention. Here we study the causal structure of the GRNs, namely the chain of influence of one component on the other, taking into account feedback from the MN. First we consider the GRNs of E. coli and B. subtilis without feedback from MN and illustrate their causal structure. Next we augment the GRNs with feedback from their respective MNs by including (a) links from genes coding for enzymes to metabolites produced or consumed in reactions catalyzed by those enzymes and (b) links from metabolites to genes coding for transcription factors whose transcriptional activity the metabolites alter by binding to them. We find that the inclusion of feedback from MN into GRN significantly affects its causal structure, in particular the number of levels and relative positions of nodes in the hierarchy, and the number and size of the strongly connected components (SCCs). We then study the functional significance of the SCCs. For this we identify condition specific feedbacks from the MN into the GRN by retaining only those enzymes that are essential for growth in specific environmental conditions simulated via the technique of flux balance analysis (FBA). We find that the SCCs of the GRN augmented by these feedbacks can be ascribed specific functional roles in the organism. Our algorithmic approach thus reveals relatively autonomous subsystems with specific functionality, or regulatory modules in the organism. This automated approach could be useful in identifying biologically relevant modules in other organisms for which network data is available, but whose biology is less well studied.

An Integrated Proteomic Approach Uncovers Novel Substrates and Functions of the Lon Protease in Escherichia coli

Controlling the cellular abundance and proper function of proteins by proteolysis is a universal process in all living organisms. In Escherichia coli, the ATP-dependent Lon protease is crucial for protein quality control and regulatory processes. To understand how diverse substrates are selected and degraded, unbiased global approaches are needed. We employed a quantitative Super-SILAC (stable isotope labeling with amino acids in cell culture) mass spectrometry approach and compared the proteomes of a lon mutant and a strain producing the protease to discover Lon-dependent physiological functions. To identify Lon substrates, we took advantage of a Lon trapping variant, which is able to translocate substrates but unable to degrade them. Lon-associated proteins were identified by label-free LC-MS/MS. The combination of both approaches revealed a total of 14 novel Lon substrates. Besides the identification of known pathways affected by Lon, for example, the superoxide stress response, our cumulative data suggests previously unrecognized fundamental functions of Lon in sulfur assimilation, nucleotide biosynthesis, amino acid and central energy metabolism.

Scoring Targets of Transcription in Bacteria Rather than Focusing on Individual Binding Sites

Reliable identification of targets of bacterial regulators is necessary to understand bacterial gene expression regulation. These targets are commonly predicted by searching for high-scoring binding sites in the upstream genomic regions, which typically leads to a large number of false positives. In contrast to the common approach, here we propose a novel concept, where overrepresentation of the scoring distribution that corresponds to the entire searched region is assessed, as opposed to predicting individual binding sites. We explore two implementations of this concept, based on Kolmogorov-Smirnov (KS) and Anderson-Darling (AD) tests, which both provide straightforward P-value estimates for predicted targets. This approach is implemented for pleiotropic bacterial regulators, including σ70 (bacterial housekeeping σ factor) target predictions, which is a classical bioinformatics problem characterized by low specificity. We show that KS based approach is both faster and more accurate, departing from the current paradigm of AD being slower, but more accurate. Moreover, KS approach leads to a significant increase in the search accuracy compared to the standard approach, while at the same time straightforwardly assigning well established P-values to each potential target. Consequently, the new KS based method proposed here, which assigns P-values to fixed length upstream regions, provides a fast and accurate approach for predicting bacterial transcription targets.

Development of oriC-Based Plasmids for Mesoplasma florum

The near-minimal bacterium Mesoplasma florum constitutes an attractive model for systems biology and for the development of a simplified cell chassis in synthetic biology. However, the lack of genetic engineering tools for this microorganism has limited our capacity to understand its basic biology and modify its genome. To address this issue, we have evaluated the susceptibility of M. florum to common antibiotics and developed the first generation of artificial plasmids able to replicate in this bacterium. Selected regions of the predicted M. florum chromosomal origin of replication (oriC) were used to create different plasmid versions that were tested for their transformation frequency and stability. Using polyethylene glycol-mediated transformation, we observed that plasmids harboring both rpmH-dnaA and dnaA-dnaN intergenic regions, interspaced or not with a copy of the dnaA gene, resulted in a frequency of ∼4.1 × 10^-6 transformants per viable cell and were stably maintained throughout multiple generations. In contrast, plasmids containing only one M. florumoriC intergenic region or the heterologous oriC region of Mycoplasma capricolum, Mycoplasma mycoides, or Spiroplasma citri failed to produce any detectable transformants. We also developed alternative transformation procedures based on electroporation and conjugation from Escherichia coli, reaching frequencies up to 7.87 × 10^-6 and 8.44 × 10^-7 transformants per viable cell, respectively. Finally, we demonstrated the functionality of antibiotic resistance genes active against tetracycline, puromycin, and spectinomycin/streptomycin in M. florum Taken together, these valuable genetic tools will facilitate efforts toward building an M. florum-based near-minimal cellular chassis for synthetic biology.IMPORTANCEMesoplasma florum constitutes an attractive model for systems biology and for the development of a simplified cell chassis in synthetic biology. M. florum is closely related to the mycoides cluster of mycoplasmas, which has become a model for whole-genome cloning, genome transplantation, and genome minimization. However, M. florum shows higher growth rates than other Mollicutes, has no known pathogenic potential, and possesses a significantly smaller genome that positions this species among some of the simplest free-living organisms. So far, the lack of genetic engineering tools has limited our capacity to understand the basic biology of M. florum in order to modify its genome. To address this issue, we have evaluated the susceptibility of M. florum to common antibiotics and developed the first artificial plasmids and transformation methods for this bacterium. This represents a strong basis for ongoing genome engineering efforts using this near-minimal microorganism.

Unsupervised statistical discovery of spaced motifs in prokaryotic genomes

BACKGROUND

DNA sequences contain repetitive motifs which have various functions in the physiology of the organism. A number of methods have been developed for discovery of such sequence motifs with a primary focus on detection of regulatory motifs and particularly transcription factor binding sites. Most motif-finding methods apply probabilistic models to detect motifs characterized by unusually high number of copies of the motif in the analyzed sequences.

RESULTS

We present a novel method for detection of pairs of motifs separated by spacers of variable nucleotide sequence but conserved length. Unlike existing methods for motif discovery, the motifs themselves are not required to occur at unusually high frequency but only to exhibit a significant preference to occur at a specific distance from each other. In the present implementation of the method, motifs are represented by pentamers and all pairs of pentamers are evaluated for statistically significant preference for a specific distance. An important step of the algorithm eliminates motif pairs where the spacers separating the two motifs exhibit a high degree of sequence similarity; such motif pairs likely arise from duplications of the whole segment including the motifs and the spacer rather than due to selective constraints indicative of a functional importance of the motif pair. The method was used to scan 569 complete prokaryotic genomes for novel sequence motifs. Some motifs detected were previously known but other motifs found in the search appear to be novel. Selected motif pairs were subjected to further investigation and in some cases their possible biological functions were proposed.

CONCLUSIONS

We present a new motif-finding technique that is applicable to scanning complete genomes for sequence motifs. The results from analysis of 569 genomes suggest that the method detects previously known motifs that are expected to be found as well as new motifs that are unlikely to be discovered by traditional motif-finding methods. We conclude that our approach to detection of significant motif pairs can complement existing motif-finding techniques in discovery of novel functional sequence motifs in complete genomes.

Contribution of bacterial promoter elements to transcription start site detection accuracy

Accurately detecting transcription start sites (TSS) is a starting point for understanding gene transcription, and an important ingredient in a number of applications necessary for functional gene annotation, such as gene and operon predictions. Available methods for TSS detection in bacteria use very different description of the bacterial promoter structure and all of them show low accuracy. It is therefore unclear which promoter features should be included in TSS recognition, and how their accuracy impacts the search detection. We here address this question for [Formula: see text] and [Formula: see text] (an alternative [Formula: see text] factor) promoters in E. coli. We find that [Formula: see text]35 element, which is considered exchangeable, and is often not included in TSS search, contributes to the search accuracy equally (for [Formula: see text], or more (for [Formula: see text] than the ubiquitous [Formula: see text]10 element. Surprisingly, the sequence of the spacer between [Formula: see text]35 and [Formula: see text]10 promoter elements, which is commonly included in TSS detection, significantly decreases the search accuracy for [Formula: see text] promoters. However, the spacer sequence improves the search accuracy for [Formula: see text] promoters, which we attribute to a presence of sequence conservation. Overall, there is as much as [Formula: see text]50% false positive reduction for optimally implemented promoter features in [Formula: see text], underlying necessity for accurate promoter element alignments.

SELMAP - SELEX affinity landscape MAPping of transcription factor binding sites using integrated microfluidics

Transcription factors (TFs) alter gene expression in response to changes in the environment through sequence-specific interactions with the DNA. These interactions are best portrayed as a landscape of TF binding affinities. Current methods to study sequence-specific binding preferences suffer from limited dynamic range, sequence bias, lack of specificity and limited throughput. We have developed a microfluidic-based device for SELEX Affinity Landscape MAPping (SELMAP) of TF binding, which allows high-throughput measurement of 16 proteins in parallel. We used it to measure the relative affinities of Pho4, AtERF2 and Btd full-length proteins to millions of different DNA binding sites, and detected both high and low-affinity interactions in equilibrium conditions, generating a comprehensive landscape of the relative TF affinities to all possible DNA 6-mers, and even DNA10-mers with increased sequencing depth. Low quantities of both the TFs and DNA oligomers were sufficient for obtaining high-quality results, significantly reducing experimental costs. SELMAP allows in-depth screening of hundreds of TFs, and provides a means for better understanding of the regulatory processes that govern gene expression.

The unexpected complexity of bacterial genomes

Gene organization and control are described by models conceived in the 1960s. These models explain basic gene regulatory mechanisms and underpin current genome annotation. However, such models struggle to explain recent genome-scale observations. For example, accounts of RNA synthesis initiating within genes, widespread antisense transcription and non-canonical DNA binding by gene regulatory proteins are difficult to reconcile with traditional thinking. As a result, unexpected observations have often been dismissed and downstream consequences ignored. In this paper I will argue that, to fully understand the biology of bacterial chromosomes, we must embrace their hidden layers of complexity.

Composing a Tumor Specific Bacterial Promoter

Systemically applied Salmonella enterica spp. have been shown to invade and colonize neoplastic tissues where it retards the growth of many tumors. This offers the possibility to use the bacteria as a vehicle for the tumor specific delivery of therapeutic molecules. Specificity of such delivery is solely depending on promoter sequences that control the production of a target molecule. We have established the functional structure of bacterial promoters that are transcriptionally active exclusively in tumor tissues after systemic application. We observed that the specific transcriptional activation is accomplished by a combination of a weak basal promoter and a strong FNR binding site. This represents a minimal set of control elements required for such activation. In natural promoters, additional DNA remodeling elements are found that alter the level of transcription quantitatively. Inefficiency of the basal promoter ensures the absence of transcription outside tumors. As a proof of concept, we compiled an artificial promoter sequence from individual motifs representing FNR and basal promoter and showed specific activation in a tumor microenvironment. Our results open possibilities for the generation of promoters with an adjusted level of expression of target proteins in particular for applications in bacterial tumor therapy.

Cis regulatory motifs and antisense transcriptional control in the apicomplexan Theileria parva

Background

Theileria parva is an intracellular parasite that causes a lymphoproliferative disease in cattle. It does so by inducing cancer-like phenotypes in the host cells it infects, although the molecular and regulatory mechanisms involved remain poorly understood. RNAseq data, and the resulting updated genome annotation now available for this parasite, offer an unprecedented opportunity to characterize the genomic features associated with gene regulation in this species. Our previous analyses revealed a T. parva genome even more gene-dense than previously thought, with many adjacent loci overlapping each other, not only at the level of untranslated sequences (UTRs) but even in coding sequences.

Results

Despite this compactness, Theileria intergenic regions show a pattern of size distribution indicative of monocistronic gene transcription. Three previously described motifs are conserved among Theileria species and highly prevalent in promoter regions near or at the transcription start sites. We found novel motifs at many transcription termination sites, as well as upstream of parasite genes thought to be critical for host transformation. Adjacent genes that could be regulated by antisense transcription from an overlapping transcriptional unit are syntenic between T. parva and P. falciparum at a frequency higher than expected by chance, suggesting the presence of common, and evolutionary old, regulatory mechanisms in the phylum Apicomplexa.

Conclusions

We propose a model of transcription with conserved sense and antisense transcription from a few taxonomically ubiquitous and several species-specific promoter motifs. Interestingly, the gene networks regulated by conserved promoters are themselves, in most cases, not conserved between species or genera.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2444-5) contains supplementary material, which is available to authorized users.

Analysis of the optimality of the standard genetic code

Many theories have been proposed attempting to explain the origin of the genetic code. In this work, we compare performance of the standard genetic code against millions of randomly generated codes. On left, ability of genetic codes to encode additional information and their robustness to frameshift mutations.

S- and N-Oxide Reductases

Escherichia coli is a versatile facultative anaerobe that can respire on a number of terminal electron acceptors, including oxygen, fumarate, nitrate, and S- and N-oxides. Anaerobic respiration using S- and N-oxides is accomplished by enzymatic reduction of these substrates by dimethyl sulfoxide reductase (DmsABC) and trimethylamine N-oxide reductase (TorCA). Both DmsABC and TorCA are membrane-associated redox enzymes that couple the oxidation of menaquinol to the reduction of S- and N-oxides in the periplasm. DmsABC is membrane bound and is composed of a membrane-extrinsic dimer with a 90.4-kDa catalytic subunit (DmsA) and a 23.1-kDa electron transfer subunit (DmsB). These subunits face the periplasm and are held to the membrane by a 30.8-kDa membrane anchor subunit (DmsC). The enzyme provides the scaffold for an electron transfer relay composed of a quinol binding site, five [4Fe-4S] clusters, and a molybdo-bis(molybdopterin guanine dinucleotide) (present nomenclature: Mo-bis-pyranopterin) (Mo-bisMGD) cofactor. TorCA is composed of a soluble periplasmic subunit (TorA, 92.5 kDa) containing a Mo-bis-MGD. TorA is coupled to the quinone pool via a pentaheme c subunit (TorC, 40.4 kDa) in the membrane. Both DmsABC and TorCA require system-specific chaperones (DmsD or TorD) for assembly, cofactor insertion, and/or targeting to the Tat translocon. In this chapter, we discuss the complex regulation of the dmsABC and torCAD operons, the poorly understood paralogues, and what is known about the assembly and translocation to the periplasmic space by the Tat translocon.

Revisiting bacterial cyclic nucleotide phosphodiesterases: cyclic AMP hydrolysis and beyond

Cyclic-3',5'-adenosine monophosphate (cAMP) is a universal second messenger that regulates vital activities in bacteria and eukaryotes. Enzymes that hydrolyze cAMP, called phosphodiesterases (PDEs), negatively regulate the levels of this messenger molecule and are therefore crucial for signal 'termination'. In this minireview, I shall summarize the available literature on bacterial cAMP-PDEs, with particular emphasis on enzymes belonging to the ubiquitously encoded Class III PDE family exemplified by CpdA from Escherichia coli and Rv0805 from Mycobacterium tuberculosis. Using available biochemical, structural and biological information, I shall make a case for re-examining the functions of these enzymes as merely regulators of intrabacterial cAMP levels and suggest that some members of this class may have evolved cAMP-independent functions as well. Finally, I shall highlight the major lacunae in our understanding of these enzymes and present unanswered questions in the area.

Evolution of bacterial transcription factors: how proteins take on new tasks, but do not always stop doing the old ones

Many bacterial transcription factors do not behave as per the textbook operon model. We draw on whole genome work, as well as reported diversity across different bacteria, to argue that transcription factors may have evolved from nucleoid-associated proteins. This view would explain a large amount of recent data gleaned from high-throughput sequencing and bioinformatic analyses.

Inferring bacteriophage infection strategies from genome sequence: analysis of bacteriophage 7-11 and related phages

Background

Analyzing regulation of bacteriophage gene expression historically lead to establishing major paradigms of molecular biology, and may provide important medical applications in the future. Temporal regulation of bacteriophage transcription is commonly analyzed through a labor-intensive combination of biochemical and bioinformatic approaches and macroarray measurements. We here investigate to what extent one can understand gene expression strategies of lytic phages, by directly analyzing their genomes through bioinformatic methods. We address this question on a recently sequenced lytic bacteriophage 7 - 11 that infects bacterium Salmonella enterica.

Results

We identify novel promoters for the bacteriophage-encoded σ factor, and test the predictions through homology with another bacteriophage (phiEco32) that has been experimentally characterized in detail. Interestingly, standard approach based on multiple local sequence alignment (MLSA) fails to correctly identify the promoters, but a simpler procedure that is based on pairwise alignment of intergenic regions identifies the desired motifs; we argue that such search strategy is more effective for promoters of bacteriophage-encoded σ factors that are typically well conserved but appear in low copy numbers, which we also verify on two additional bacteriophage genomes. Identifying promoters for bacteriophage encoded σ factors together with a more straightforward identification of promoters for bacterial encoded σ factor, allows clustering the genes in putative early, middle and late class, and consequently predicting the temporal regulation of bacteriophage gene expression, which we demonstrate on phage 7-11.

Conclusions

While MLSA algorithms proved highly useful in computational analysis of transcription regulation, we here established that a simpler procedure is more successful for identifying promoters that are recognized by bacteriophage encoded σ factor/RNA polymerase. We here used this approach for predicting sequence specificity of a novel (bacteriophage encoded) σ factor, and consequently inferring phage 7-11 transcription strategy. Therefore, direct analysis of bacteriophage genome sequences is a plausible first-line approach for efficiently inferring phage transcription strategies, and may provide a wealth of information on transcription initiation by diverse σ factors/RNA polymerases.

Evolutionary meandering of intermolecular interactions along the drift barrier

Many cellular functions depend on highly specific intermolecular interactions, for example transcription factors and their DNA binding sites, microRNAs and their RNA binding sites, the interfaces between heterodimeric protein molecules, the stems in RNA molecules, and kinases and their response regulators in signal-transduction systems. Despite the need for complementarity between interacting partners, such pairwise systems seem to be capable of high levels of evolutionary divergence, even when subject to strong selection. Such behavior is a consequence of the diminishing advantages of increasing binding affinity between partners, the multiplicity of evolutionary pathways between selectively equivalent alternatives, and the stochastic nature of evolutionary processes. Because mutation pressure toward reduced affinity conflicts with selective pressure for greater interaction, situations can arise in which the expected distribution of the degree of matching between interacting partners is bimodal, even in the face of constant selection. Although biomolecules with larger numbers of interacting partners are subject to increased levels of evolutionary conservation, their more numerous partners need not converge on a single sequence motif or be increasingly constrained in more complex systems. These results suggest that most phylogenetic differences in the sequences of binding interfaces are not the result of adaptive fine tuning but a simple consequence of random genetic drift.

Transcription factor MrpC binds to promoter regions of hundreds of developmentally-regulated genes in Myxococcus xanthus

Background

Myxococcus xanthus is a bacterium that undergoes multicellular development when starved. Cells move to aggregation centers and form fruiting bodies in which cells differentiate into dormant spores. MrpC appears to directly activate transcription of fruA, which also codes for a transcription factor. Both MrpC and FruA are crucial for aggregation and sporulation. The two proteins bind cooperatively in promoter regions of some developmental genes.

Results

Chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) and bioinformatic analysis of cells that had formed nascent fruiting bodies revealed 1608 putative MrpC binding sites. These sites included several known to bind MrpC and they were preferentially distributed in likely promoter regions, especially those of genes up-regulated during development. The up-regulated genes include 22 coding for protein kinases. Some of these are known to be directly involved in fruiting body formation and several negatively regulate MrpC accumulation. Our results also implicate MrpC as a direct activator or repressor of genes coding for several transcription factors known to be important for development, for a major spore protein and several proteins important for spore formation, for proteins involved in extracellular A- and C-signaling, and intracellular ppGpp-signaling during development, and for proteins that control the fate of other proteins or play a role in motility. We found that the putative MrpC binding sites revealed by ChIP-seq are enriched for DNA sequences that strongly resemble a consensus sequence for MrpC binding proposed previously. MrpC2, an N-terminally truncated form of MrpC, bound to DNA sequences matching the consensus in all 11 cases tested. Using longer DNA segments containing 15 of the putative MrpC binding sites from our ChIP-seq analysis as probes in electrophoretic mobility shift assays, evidence for one or more MrpC2 binding site was observed in all cases and evidence for cooperative binding of MrpC2 and FruA was seen in 13 cases.

Conclusions

We conclude that MrpC and MrpC2 bind to promoter regions of hundreds of developmentally-regulated genes in M. xanthus, in many cases cooperatively with FruA. This binding very likely up-regulates protein kinases, and up- or down-regulates other proteins that profoundly influence the developmental process.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1123) contains supplementary material, which is available to authorized users.

darR and darS are regulatory genes that modulate 2-hexyl, 5-propyl resorcinol transcription in Pseudomonas chlororaphis PCL1606

Pseudomonas chlororaphis PCL1606 synthesizes the antifungal antibiotic 2-hexyl, 5-propyl resorcinol (HPR), which is crucial for the biocontrol of fungal soil-borne pathogens. The genetic basis for HPR production lies in the dar genes, which are directly involved in the biosynthesis of HPR. In the present study, we elucidated the genetic features of the dar genes. Reverse transcription PCR experiments revealed an independent organization of the dar genes, except for darBC, which was transcribed as a polycistronic mRNA. In silico analysis of each gene revealed putative promoters and terminator sequences, validating the proposed gene arrangement. Moreover, experiments utilizing 5' rapid amplification of cDNA ends were used to determine the transcriptional initiation sites for the darA, darBC, darS and darR gene promoters, and subsequently to confirm the functionality of these regions. The results of quantitative real-time PCR experiments indicated that biosynthetic dar genes were not only modulated through the global regulator gacS, but also through darS and darR. The interplay between darS and darR revealed transcriptional cross-inhibition. However, these results also showed that other regulatory parameters play a role in HPR production, such as the environmental conditions and additional regulatory genes.

Two mechanisms for putrescine-dependent transcriptional expression of the putrescine aminotransferase gene, ygjG, in Escherichia coli

In this study, on evaluating the physiological function and mechanism of putrescine, we found that putrescine supplementation (1 mM) increases transcription of the putrescine aminotransferase gene, ygjG. Putrescine-dependent expression was confirmed by measuring β-galactosidase activity and with reverse transcription-polymerase chain reaction. To understand the role of putrescine in ygjG expression, we genetically characterized and found that a knockout mutation in an alternative sigma factor, rpoS, abolished putrescine-dependent ygjG-lacZ expression. In the rpoS mutant, RpoS overexpression complemented the mutant phenotype. However, RpoS overexpression induced ygjG-lacZ expression with putrescine supplementation but not without supplementation. We also found that the loss of putrescine-dependent ygjG-lacZ expression induced by rpoS was completely restored under nitrogen-starvation conditions. The putrescine-dependent expression of ygjG-lacZ under this condition was clearly dependent on another alternative sigma factor, rpoN, and its cognate activator ntrC. These results show that rpoS is required for putrescine-dependent ygjG-lacZ expression, but the effect of putrescine on this expression is not caused by simple modulation of RpoS synthesis. Putrescine-dependent expression of ygjG-lacZ was controlled by at least two sigma factors: rpoS under excess nitrogen conditions and rpoN under nitrogen-starvation conditions. These results suggest that putrescine plays an important role in the nitrogen regulation system.

Unprecedented high-resolution view of bacterial operon architecture revealed by RNA sequencing

We analyzed the transcriptome of Escherichia coli K-12 by strand-specific RNA sequencing at single-nucleotide resolution during steady-state (logarithmic-phase) growth and upon entry into stationary phase in glucose minimal medium. To generate high-resolution transcriptome maps, we developed an organizational schema which showed that in practice only three features are required to define operon architecture: the promoter, terminator, and deep RNA sequence read coverage. We precisely annotated 2,122 promoters and 1,774 terminators, defining 1,510 operons with an average of 1.98 genes per operon. Our analyses revealed an unprecedented view of E. coli operon architecture. A large proportion (36%) of operons are complex with internal promoters or terminators that generate multiple transcription units. For 43% of operons, we observed differential expression of polycistronic genes, despite being in the same operons, indicating that E. coli operon architecture allows fine-tuning of gene expression. We found that 276 of 370 convergent operons terminate inefficiently, generating complementary 3′ transcript ends which overlap on average by 286 nucleotides, and 136 of 388 divergent operons have promoters arranged such that their 5′ ends overlap on average by 168 nucleotides. We found 89 antisense transcripts of 397-nucleotide average length, 7 unannotated transcripts within intergenic regions, and 18 sense transcripts that completely overlap operons on the opposite strand. Of 519 overlapping transcripts, 75% correspond to sequences that are highly conserved in E. coli (>50 genomes). Our data extend recent studies showing unexpected transcriptome complexity in several bacteria and suggest that antisense RNA regulation is widespread.

We precisely mapped the 5′ and 3′ ends of RNA transcripts across the E. coli K-12 genome by using a single-nucleotide analytical approach. Our resulting high-resolution transcriptome maps show that ca. one-third of E. coli operons are complex, with internal promoters and terminators generating multiple transcription units and allowing differential gene expression within these operons. We discovered extensive antisense transcription that results from more than 500 operons, which fully overlap or extensively overlap adjacent divergent or convergent operons. The genomic regions corresponding to these antisense transcripts are highly conserved in E. coli (including Shigella species), although it remains to be proven whether or not they are functional. Our observations of features unearthed by single-nucleotide transcriptome mapping suggest that deeper layers of transcriptional regulation in bacteria are likely to be revealed in the future.

Agent-based modeling of oxygen-responsive transcription factors in Escherichia coli

In the presence of oxygen (O₂) the model bacterium Escherichia coli is able to conserve energy by aerobic respiration. Two major terminal oxidases are involved in this process - Cyo has a relatively low affinity for O₂ but is able to pump protons and hence is energetically efficient; Cyd has a high affinity for O₂ but does not pump protons. When E. coli encounters environments with different O₂ availabilities, the expression of the genes encoding the alternative terminal oxidases, the cydAB and cyoABCDE operons, are regulated by two O₂-responsive transcription factors, ArcA (an indirect O₂ sensor) and FNR (a direct O₂ sensor). It has been suggested that O₂-consumption by the terminal oxidases located at the cytoplasmic membrane significantly affects the activities of ArcA and FNR in the bacterial nucleoid. In this study, an agent-based modeling approach has been taken to spatially simulate the uptake and consumption of O₂ by E. coli and the consequent modulation of ArcA and FNR activities based on experimental data obtained from highly controlled chemostat cultures. The molecules of O₂, transcription factors and terminal oxidases are treated as individual agents and their behaviors and interactions are imitated in a simulated 3-D E. coli cell. The model implies that there are two barriers that dampen the response of FNR to O₂, i.e. consumption of O₂ at the membrane by the terminal oxidases and reaction of O₂ with cytoplasmic FNR. Analysis of FNR variants suggested that the monomer-dimer transition is the key step in FNR-mediated repression of gene expression.

The model bacterium Escherichia coli has a modular electron transport chain that allows it to successfully compete in environments with differing oxygen (O₂) availabilities. It has two well-characterized terminal oxidases, Cyd and Cyo. Cyd has a very high affinity for O₂, whereas Cyo has a lower affinity, but is energetically more efficient. Expression of the genes encoding Cyd and Cyo is controlled by two O₂-responsive regulators, ArcBA and FNR. However, it is not clear how O₂ molecules enter the E. coli cell and how the locations of the terminal oxidases and the regulators influence the system. An agent-based model is presented that simulates the interactions of O₂ with the regulators and the oxidases in an E. coli cell. The model suggests that O₂ consumption by the oxidases at the cytoplasmic membrane and by FNR in the cytoplasm protects FNR bound to DNA in the nucleoid from inactivation and that dimerization of FNR in response to O₂ depletion is the key step in FNR-mediated repression. Thus, the focus of the agent-based model on spatial events provides information and new insight, allowing the effects of dysregulation of system components to be explored by facile addition or removal of agents.

An improved systematic approach to predicting transcription factor target genes using support vector machine

Biological prediction of transcription factor binding sites and their corresponding transcription factor target genes (TFTGs) makes great contribution to understanding the gene regulatory networks. However, these approaches are based on laborious and time-consuming biological experiments. Numerous computational approaches have shown great potential to circumvent laborious biological methods. However, the majority of these algorithms provide limited performances and fail to consider the structural property of the datasets. We proposed a refined systematic computational approach for predicting TFTGs. Based on previous work done on identifying auxin response factor target genes from Arabidopsis thaliana co-expression data, we adopted a novel reverse-complementary distance-sensitive n-gram profile algorithm. This algorithm converts each upstream sub-sequence into a high-dimensional vector data point and transforms the prediction task into a classification problem using support vector machine-based classifier. Our approach showed significant improvement compared to other computational methods based on the area under curve value of the receiver operating characteristic curve using 10-fold cross validation. In addition, in the light of the highly skewed structure of the dataset, we also evaluated other metrics and their associated curves, such as precision-recall curves and cost curves, which provided highly satisfactory results.

Informational requirements for transcriptional regulation

Transcription factors (TFs) regulate transcription by binding to specific sites in promoter regions. Information theory provides a useful mathematical framework to analyze the binding motifs associated with TFs but imposes several assumptions that limit their applicability to specific regulatory scenarios. Explicit simulations of the co-evolution of TFs and their binding motifs allow the study of the evolution of regulatory networks with a high degree of realism. In this work we analyze the impact of differential regulatory demands on the information content of TF-binding motifs by means of evolutionary simulations. We generalize a predictive index based on information theory, and we validate its applicability to regulatory scenarios in which the TF binds significantly to the genomic background. Our results show a logarithmic dependence of the evolved information content on the occupancy of target sites and indicate that TFs may actively exploit pseudo-sites to modulate their occupancy of target sites. In regulatory networks with differentially regulated targets, we observe that information content in TF-binding motifs is dictated primarily by the fraction of total probability mass that the TF assigns to its target sites, and we provide a predictive index to estimate the amount of information associated with arbitrarily complex regulatory systems. We observe that complex regulatory patterns can exert additional demands on evolved information content, but, given a total occupancy for target sites, we do not find conclusive evidence that this effect is because of the range of required binding affinities.

Determining the control circuitry of redox metabolism at the genome-scale

Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during electron acceptor shifts. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs), ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r(2) (p<1e-6) correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. Finally, we are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network.

Identification of a predicted partner-switching system that affects production of the gene transfer agent RcGTA and stationary phase viability in Rhodobacter capsulatus

Background

Production of the gene transfer agent RcGTA in the α-proteobacterium Rhodobacter capsulatus is dependent upon the response regulator protein CtrA. Loss of this regulator has widespread effects on transcription in R. capsulatus, including the dysregulation of numerous genes encoding other predicted regulators. This includes a set of putative components of a partner-switching signaling pathway with sequence homology to the σ-regulating proteins RsbV, RsbW, and RsbY that have been extensively characterized for their role in stress responses in gram-positive bacteria. These R. capsulatus homologues, RbaV, RbaW, and RbaY, have been investigated for their possible role in controlling RcGTA gene expression.

Results

A mutant strain lacking rbaW showed a significant increase in RcGTA gene expression and production. Mutation of rbaV or rbaY led to a decrease in RcGTA gene expression and production, and these mutants also showed decreased viability in the stationary phase and produced unusual colony morphologies. In vitro and in vivo protein interaction assays demonstrated that RbaW and RbaV interact. A combination of gene disruptions and protein-protein interaction assays were unsuccessful in attempts to identify a cognate σ factor, and the genetic data support a model where the RbaV protein that is the determinant regulator of RcGTA gene expression in this system.

Conclusions

These findings provide new information about RcGTA regulation by a putative partner-switching system and further illustrate the integration of RcGTA production into R. capsulatus physiology.

Modular composition of gene transcription networks

Predicting the dynamic behavior of a large network from that of the composing modules is a central problem in systems and synthetic biology. Yet, this predictive ability is still largely missing because modules display context-dependent behavior. One cause of context-dependence is retroactivity, a phenomenon similar to loading that influences in non-trivial ways the dynamic performance of a module upon connection to other modules. Here, we establish an analysis framework for gene transcription networks that explicitly accounts for retroactivity. Specifically, a module's key properties are encoded by three retroactivity matrices: internal, scaling, and mixing retroactivity. All of them have a physical interpretation and can be computed from macroscopic parameters (dissociation constants and promoter concentrations) and from the modules' topology. The internal retroactivity quantifies the effect of intramodular connections on an isolated module's dynamics. The scaling and mixing retroactivity establish how intermodular connections change the dynamics of connected modules. Based on these matrices and on the dynamics of modules in isolation, we can accurately predict how loading will affect the behavior of an arbitrary interconnection of modules. We illustrate implications of internal, scaling, and mixing retroactivity on the performance of recurrent network motifs, including negative autoregulation, combinatorial regulation, two-gene clocks, the toggle switch, and the single-input motif. We further provide a quantitative metric that determines how robust the dynamic behavior of a module is to interconnection with other modules. This metric can be employed both to evaluate the extent of modularity of natural networks and to establish concrete design guidelines to minimize retroactivity between modules in synthetic systems.

Biological modules are inherently context-dependent as the input/output behavior of a module often changes upon connection with other modules. One source of context-dependence is retroactivity, a loading phenomenon by which a downstream system affects the behavior of an upstream system upon interconnection. This fact renders it difficult to predict how modules will behave once connected to each other. In this paper, we propose a general modeling framework for gene transcription networks to accurately predict how retroactivity affects the dynamic behavior of interconnected modules, based on salient physical properties of the same modules in isolation. We illustrate how our framework predicts surprising and counter-intuitive dynamic properties of naturally occurring network structures, which cannot be captured by existing models of the same dimension. We describe implications of our findings on the bottom-up approach to designing synthetic circuits, and on the top-down approach to identifying functional modules in natural networks, revealing trade-offs between robustness to interconnection and dynamic performance. Our framework carries substantial conceptual analogies with electrical network theory based on equivalent representations. We believe that the framework we have proposed, also based on equivalent network representations, can be similarly useful for the analysis and design of biological networks.

Investigating the interplay between nucleoid-associated proteins, DNA curvature, and CRISPR elements using comparative genomics

Many prokaryotic and eukaryotic genomes feature a characteristic periodic signal in distribution of short runs of A or T (A-tracts) phased with the DNA helical period of ∼10-11 bp. Such periodic spacing of A-tracts has been associated with intrinsic DNA curvature. In eukaryotes, this periodicity is a major component of the nucleosome positioning signal but its physiological role in prokaryotes is not clear. One hypothesis centers on possible role of intrinsic DNA bends in nucleoid compaction. We use comparative genomics to investigate possible relationship between the A-tract periodicity and nucleoid-associated proteins in prokaryotes. We found that genomes with DNA-bridging proteins tend to exhibit stronger A-tract periodicity, presumably indicative of more prevalent intrinsic DNA curvature. A weaker relationship was detected for nucleoid-associated proteins that do not form DNA bridges. We consider these results an indication that intrinsic DNA curvature acts collaboratively with DNA-bridging proteins in maintaining the compact structure of the nucleoid, and that previously observed differences among prokaryotic genomes in terms DNA curvature-related sequence periodicity may reflect differences in nucleoid organization. We subsequently investigated the relationship between A-tract periodicity and presence of CRISPR elements and we found that genomes with CRISPR tend to have stronger A-tract periodicity. This result is consistent with our earlier hypothesis that extensive A-tract periodicity could help protect the chromosome against integration of prophages, possibly due to its role in compaction of the nucleoid.

Efficient transcription initiation in bacteria: an interplay of protein-DNA interaction parameters

As the first, and usually rate-limiting, step of transcription initiation, bacterial RNA polymerase (RNAP) binds to double stranded DNA (dsDNA) and subsequently opens the two strands of DNA (the open complex formation). The rate determining step in the open complex formation is opening of a short (6 bp) DNA called the -10 region, which interacts with RNAP in both dsDNA and single stranded (ssDNA) forms. Accordingly, formation of the open complex depends on (physically independent) domains of RNAP that interact with ssDNA and dsDNA, as well as on parameters of DNA melting and sequences of -10 regions. We here aim to understand how these different interactions are mutually related to ensure efficient open complex formation. To achieve this, we use a recently developed biophysical model of transcription initiation, which allows the calculation of the kinetic parameters of transcription initiation on the scale of whole genome. We consequently investigate kinetic properties of sequences derived from all E. coli intergenic regions, and from more than 300 experimentally confirmed E. coli σ(70) promoters. We find that interaction specificities of σ(70) DNA binding domains reduce the number of sequences where RNAP binds strongly, but forms the open complex too slowly to achieve functional transcription (so-called poised promoters). However, we find that, despite this reduction, there is still a significant number of such poised promoters in the intergenic regions, which may provide a major source of false positives in genome-wide searches of transcription start sites. Furthermore, we surprisingly find that sequences of -10 regions of the functional promoters increase the extent of RNAP poising, which we interpret in terms of an extension of a recently proposed model of promoter recognition ('mix-and-match model') to kinetic parameters. Overall, our results allow better understanding of the design of σ(70) DNA binding domains and promoter sequences, and place a fundamental limit on accuracy of methods for promoter detection that are based on strong RNAP binding (e.g. ChIP-chip).