Controller protein of restriction-modification system Kpn2I affects transcription of its gene by acting as a transcription elongation roadblock

When push comes to shove - RNA polymerase and DNA-bound protein roadblocks

In recent years, transcriptional roadblocking has emerged as a crucial regulatory mechanism in gene expression, whereby other DNA-bound obstacles can block the progression of transcribing RNA polymerase (RNAP), leading to RNAP pausing and ultimately dissociation from the DNA template. In this review, we discuss the mechanisms by which transcriptional roadblocks can impede RNAP progression, as well as how RNAP can overcome these obstacles to continue transcription. We examine different DNA-binding proteins involved in transcriptional roadblocking and their biophysical properties that determine their effectiveness in blocking RNAP progression. The catalytically dead CRISPR-Cas (dCas) protein is used as an example of an engineered programmable roadblock, and the current literature in understanding the polarity of dCas roadblocking is also discussed. Finally, we delve into a stochastic model of transcriptional roadblocking and highlight the importance of transcription factor binding kinetics and its resistance to dislodgement by an elongating RNAP in determining the strength of a roadblock.

Regulation of Gene Expression of phiEco32-like Bacteriophage 7-11

Salmonella enterica serovar Newport bacteriophage 7-11 shares 41 homologous ORFs with Escherichia coli phage phiEco32, and both phages encode a protein similar to bacterial RNA polymerase promoter specificity σ subunit. Here, we investigated the temporal pattern of 7-11 gene expression during infection and compared it to the previously determined transcription strategy of phiEco32. Using primer extension and in vitro transcription assays, we identified eight promoters recognized by host RNA polymerase holoenzyme containing 7-11 σ subunit SaPh711_gp47. These promoters are characterized by a bipartite consensus, GTAAtg-(16)-aCTA, and are located upstream of late phage genes. While dissimilar from single-element middle and late promoters of phiEco32 recognized by holoenzymes formed by the phi32_gp36 σ factor, the 7-11 late promoters are located at genome positions similar to those of phiEco32 middle and late promoters. Two early 7-11 promoters are recognized by the RNA polymerase holoenzyme containing the host primary σ⁷⁰ factor. Unlike the case of phiEco32, no shut-off of σ⁷⁰-dependent transcription is observed during 7-11 infection and there are no middle promoters. These differences can be explained by the fact that phage 7-11 does not encode a homologue of phi32_gp79, an inhibitor of host and early phage transcription and an activator of transcription by the phi32_gp36-holoenzyme.

Transcriptome analyses of cells carrying the Type II Csp231I restriction-modification system reveal cross-talk between two unrelated transcription factors: C protein and the Rac prophage repressor

Restriction-modification (R–M) systems represent an effective mechanism of defence against invading bacteriophages, and are widely spread among bacteria and archaea. In acquiring a Type II R–M system via horizontal gene transfer, the new hosts become more resistant to phage infection, through the action of a restriction endonuclease (REase), which recognizes and cleaves specific target DNAs. To protect the host cell's DNA, there is also a methyltransferase (MTase), which prevents DNA cleavage by the cognate REase. In some R–M systems, the host also accepts a cis-acting transcription factor (C protein), which regulates the counteracting activities of REase and MTase to avoid host self-restriction. Our study characterized the unexpected phenotype of Escherichia coli cells, which manifested as extensive cell filamentation triggered by acquiring the Csp231I R–M system from Citrobacter sp. Surprisingly, we found that the cell morphology defect was solely dependent on the C regulator. Our transcriptome analysis supported by in vivo and in vitro assays showed that C protein directly silenced the expression of the RacR repressor to affect the Rac prophage-related genes. The rac locus ydaST genes, when derepressed, exerted a toxicity indicated by cell filamentation through an unknown mechanism. These results provide an apparent example of transcription factor cross-talk, which can have significant consequences for the host, and may represent a constraint on lateral gene transfer.

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.

Endogenous Gene Regulation as a Predicted Main Function of Type I-E CRISPR/Cas System in E. coli

CRISPR/Cas is an adaptive bacterial immune system, whose CRISPR array can actively change in response to viral infections. However, Type I-E CRISPR/Cas in E. coli (an established model system), appears not to exhibit such active adaptation, which suggests that it might have functions other than immune response. Through computational analysis, we address the involvement of the system in non-canonical functions. To assess targets of CRISPR spacers, we align them against both E. coli genome and an exhaustive (~230) set of E. coli viruses. We systematically investigate the obtained alignments, such as hit distribution with respect to genome annotation, propensity to target mRNA, the target functional enrichment, conservation of CRISPR spacers and putative targets in related bacterial genomes. We find that CRISPR spacers have a statistically highly significant tendency to target i) host compared to phage genomes, ii) one of the two DNA strands, iii) genomic dsDNA rather than mRNA, iv) transcriptionally active regions, and v) sequences (cis-regulatory elements) with slower turn-over rate compared to CRISPR spacers (trans-factors). The results suggest that the Type I-E CRISPR/Cas system has a major role in transcription regulation of endogenous genes, with a potential to rapidly rewire these regulatory interactions, with targets being selected through naïve adaptation.

Effects of Population Dynamics on Establishment of a Restriction-Modification System in a Bacterial Host

In vivo dynamics of protein levels in bacterial cells depend on both intracellular regulation and relevant population dynamics. Such population dynamics effects, e.g., interplay between cell and plasmid division rates, are, however, often neglected in modeling gene expression regulation. Including them in a model introduces additional parameters shared by the dynamical equations, which can significantly increase dimensionality of the parameter inference. We here analyse the importance of these effects, on a case of bacterial restriction-modification (R-M) system. We redevelop our earlier minimal model of this system gene expression regulation, based on a thermodynamic and dynamic system modeling framework, to include the population dynamics effects. To resolve the problem of effective coupling of the dynamical equations, we propose a “mean-field-like” procedure, which allows determining only part of the parameters at a time, by separately fitting them to expression dynamics data of individual molecular species. We show that including the interplay between kinetics of cell division and plasmid replication is necessary to explain the experimental measurements. Moreover, neglecting population dynamics effects can lead to falsely identifying non-existent regulatory mechanisms. Our results call for advanced methods to reverse-engineer intracellular regulation from dynamical data, which would also take into account the population dynamics effects.