The hok mRNA family

The power of small RNAs: A comprehensive review on bacterial stress response and adaptation

Bacteria employ a wide range of RNA-based regulatory systems to adapt to various environmental stressors. Among these, small non-coding RNAs (sRNAs) have emerged as critical regulators of gene expression. These compact RNA molecules modulate numerous cellular functions, including stress adaptation, biofilm development, and virulence. By acting primarily at the post-transcriptional level, sRNAs enable bacteria to swiftly adjust gene expression in response to external challenges. One key mechanism of sRNA action is translational repression, which includes the regulation of toxin-antitoxin systems pathways essential for bacterial persistence and antibiotic resistance. Additionally, sRNAs orchestrate the expression of genes involved in biofilm formation, enhancing surface adhesion, extracellular matrix production, and resistance to antimicrobial agents. Bacterial outer membrane vesicles (OMVs) also play a significant role in stress adaptation and intercellular communication. These vesicles transport a complex cargo of proteins, lipids, and nucleic acids, including sRNAs. The transfer of sRNAs through OMVs can modulate the physiology of neighboring bacterial cells as well as host cells, highlighting their role in cross-kingdom signaling. sRNAs serve as versatile and potent regulatory elements that support bacterial survival under hostile conditions. Advancing our understanding of sRNA-mediated networks offers promising avenues for uncovering bacterial pathogenesis and developing innovative antimicrobial therapies.

Profiling the intragenic toxicity determinants of toxin-antitoxin systems: revisiting hok/Sok regulation

Type I toxin-antitoxin systems (T1TAs) are extremely potent bacterial killing systems difficult to characterize using classical approaches. To assess the killing capability of type I toxins and to identify mutations suppressing the toxin expression or activity, we previously developed the FASTBAC-Seq (Functional AnalysiS of Toxin-Antitoxin Systems in BACteria by Deep Sequencing) method in Helicobacter pylori. This method combines a life and death selection with deep sequencing. Here, we adapted and improved our method to investigate T1TAs in the model organism Escherichia coli. As a proof of concept, we revisited the regulation of the plasmidic hok/Sok T1TA system. We revealed the death-inducing phenotype of the Hok toxin when it is expressed from the chromosome in the absence of the antitoxin and recovered previously described intragenic toxicity determinants of this system. We identified nucleotides that are essential for the transcription, translation or activity of Hok. We also discovered single-nucleotide substitutions leading to structural changes affecting either the translation or the stability of the hok mRNA. Overall, we provide the community with an easy-to-use approach to widely characterize TA systems from diverse types and bacteria.

Cloning of hok gene into anhydrotetracycline inducible pASK75 vector reveals potent antimicrobial effect of 19 amino acid long N-terminal fragment of hok peptide

An important toxin-antitoxin (TA) system hok/sok, encoded by R1 plasmid of Escherichia coli, is involved in the post segregation killing of cells that have lost the plasmid. The lethal properties of hok protein have been utilized for the environmental containment of microbes and the development of potential vaccine candidates. This study aimed to demonstrate the potent anti-microbial property of a 19 amino acid (AA) long N-terminal fragment of hok peptide. This was accomplished by designing a conditional suicide system based on hok gene expression cloned in an anhydrotetracycline (aTc) inducible vector - pASK75. Heat shock and electroporation were utilized for the transformation of Escherichia coli and Vibrio cholerae cells, respectively. The minimal induction concentration (MI_d C) of aTc, determined by analyzing the expression of green fluorescent protein cloned separately into pASK75 vector, was 30 ng/mL. As hok gene was synthesized de novo (using recombinant polymerase chain reaction) in our study, various random sized hok fragments were generated (as a result of the error-prone nature of Taq polymerase). The smallest hok fragment able to bring about effective antimicrobial killing was a 19 AA long N-terminal fragment of hok having the wild type sequence, except for the carboxy terminus AA residue. The MI_d C of aTc in our experiments was 6-fold lower than previously reported, making our bacterial clones suitable for use in mammalian systems as potential vaccine candidates. Based on our experiments, we hypothesize the 19 AA long N-terminal fragment of hok peptide to be the smallest possible hok fragment sufficient to bring about effective antimicrobial killing.

Guidelines for designing the antithetic feedback motif

Integral feedback control is commonly used in mechanical and electrical systems to achieve zero steady-state error following an external disturbance. Equivalently, in biological systems, a property known as robust perfect adaptation guarantees robustness to environmental perturbations and return to the pre-disturbance state. Previously, Briat et al proposed a biomolecular design for integral feedback control (robust perfect adaptation) called the antithetic feedback motif. The antithetic feedback controller uses the sequestration binding reaction of two biochemical species to record the integral of the error between the current and the desired output of the network it controls. The antithetic feedback motif has been successfully built using synthetic components in vivo in Escherichia coli and Saccharomyces cerevisiae cells. However, these previous synthetic implementations of antithetic feedback have not produced perfect integral feedback control due to the degradation and dilution of the two controller species. Furthermore, previous theoretical results have cautioned that integral control can only be achieved under stability conditions that not all antithetic feedback motifs necessarily fulfill. In this paper, we study how to design antithetic feedback motifs that simultaneously achieve good stability and small steady-state error properties, even as the controller species are degraded and diluted. We provide simple tuning guidelines to achieve flexible and practical synthetic biological implementations of antithetic feedback control. We use several tools and metrics from control theory to design antithetic feedback networks, paving the path for the systematic design of synthetic biological controllers.

Cross-Regulations between Bacterial Toxin-Antitoxin Systems: Evidence of an Interconnected Regulatory Network?

Toxin-antitoxin (TA) systems are ubiquitous among bacteria and include stable toxins whose toxicity can be counteracted by RNA or protein antitoxins. They are involved in multiple functions that range from stability maintenance for mobile genetic elements to stress adaptation. Bacterial chromosomes frequently have multiple homologues of TA system loci, and it is unclear why there are so many of them. In this review we focus on cross-regulations between TA systems, which occur between both homologous and nonhomologous systems, from similar or distinct types, whether encoded from plasmids or chromosomes. In addition to being able to modulate RNA expression levels, cross-regulations between these systems can also influence their toxicity. This suggests the idea that they are involved in an interconnected regulatory network.

Functionality and cross-regulation of the four SprG/SprF type I toxin-antitoxin systems in Staphylococcus aureus

Toxin–antitoxin (TA) systems are ubiquitous among bacteria, frequently expressed in multiple copies, and important for functions such as antibiotic resistance and persistence. Type I TA systems are composed of a stable toxic peptide whose expression is repressed by an unstable RNA antitoxin. Here, we investigated the functionalities, regulation, and possible cross-talk between three core genome copies of the pathogenicity island-encoded ‘sprG1/sprF1’ type I TA system in the human pathogen Staphylococcus aureus. Except for SprG4, all RNA from these pairs, sprG2/sprF2, sprG3/sprF3, sprG4/sprF4, are expressed in the HG003 strain. SprG2 and SprG3 RNAs encode toxic peptides whose overexpression triggers bacteriostasis, which is counteracted at the RNA level by the overexpression of SprF2 and SprF3 antitoxins. Complex formation between each toxin and its cognate antitoxin involves their overlapping 3′ ends, and each SprF antitoxin specifically neutralizes the toxicity of its cognate SprG toxin without cross-talk. However, overexpression studies suggest cross-regulations occur at the RNA level between the SprG/SprF TA systems during growth. When subjected to H₂O₂-induced oxidative stress, almost all antitoxin levels dropped, while only SprG1 and SprF1 were reduced during phagocytosis-induced oxidative stress. SprG1, SprF1, SprF2, SprG3 and SprF3 levels also decrease during hyperosmotic stress. This suggests that novel SprG/SprF TA systems are involved in S. aureus persistence.

Antibiotic-free selection in biotherapeutics: now and forever

The continuously improving sophistication of molecular engineering techniques gives access to novel classes of bio-therapeutics and new challenges for their production in full respect of the strengthening regulations. Among these biologic agents are DNA based vaccines or gene therapy products and to a lesser extent genetically engineered live vaccines or delivery vehicles. The use of antibiotic-based selection, frequently associated with genetic manipulation of microorganism is currently undergoing a profound metamorphosis with the implementation and diversification of alternative selection means. This short review will present examples of alternatives to antibiotic selection and their context of application to highlight their ineluctable invasion of the bio-therapeutic world.

Distinct type I and type II toxin-antitoxin modules control Salmonella lifestyle inside eukaryotic cells

Toxin-antitoxin (TA) modules contribute to the generation of non-growing cells in response to stress. These modules abound in bacterial pathogens although the bases for this profusion remain largely unknown. Using the intracellular bacterial pathogen Salmonella enterica serovar Typhimurium as a model, here we show that a selected group of TA modules impact bacterial fitness inside eukaryotic cells. We characterized in this pathogen twenty-seven TA modules, including type I and type II TA modules encoding antisense RNA and proteinaceous antitoxins, respectively. Proteomic and gene expression analyses revealed that the pathogen produces numerous toxins of TA modules inside eukaryotic cells. Among these, the toxins Hok_ST, LdrA_ST, and TisB_ST, encoded by type I TA modules and T4_ST and VapC2_ST, encoded by type II TA modules, promote bacterial survival inside fibroblasts. In contrast, only VapC2_ST shows that positive effect in bacterial fitness when the pathogen infects epithelial cells. These results illustrate how S. Typhimurium uses distinct type I and type II TA modules to regulate its intracellular lifestyle in varied host cell types. This function specialization might explain why the number of TA modules increased in intracellular bacterial pathogens.

e-RNA: a collection of web servers for comparative RNA structure prediction and visualisation

e-RNA offers a free and open-access collection of five published RNA sequence analysis tools, each solving specific problems not readily addressed by other available tools. Given multiple sequence alignments, Transat detects all conserved helices, including those expected in a final structure, but also transient, alternative and pseudo-knotted helices. RNA-Decoder uses unique evolutionary models to detect conserved RNA secondary structure in alignments which may be partly protein-coding. SimulFold simultaneously co-estimates the potentially pseudo-knotted conserved structure, alignment and phylogenetic tree for a set of homologous input sequences. CoFold predicts the minimum-free energy structure for an input sequence while taking the effects of co-transcriptional folding into account, thereby greatly improving the prediction accuracy for long sequences. R-chie is a program to visualise RNA secondary structures as arc diagrams, allowing for easy comparison and analysis of conserved base-pairs and quantitative features. The web site server dispatches user jobs to a cluster, where up to 100 jobs can be processed in parallel. Upon job completion, users can retrieve their results via a bookmarked or emailed link. e-RNA is located at http://www.e-rna.org.

Bioinformatics of prokaryotic RNAs

The genome of most prokaryotes gives rise to surprisingly complex transcriptomes, comprising not only protein-coding mRNAs, often organized as operons, but also harbors dozens or even hundreds of highly structured small regulatory RNAs and unexpectedly large levels of anti-sense transcripts. Comprehensive surveys of prokaryotic transcriptomes and the need to characterize also their non-coding components is heavily dependent on computational methods and workflows, many of which have been developed or at least adapted specifically for the use with bacterial and archaeal data. This review provides an overview on the state-of-the-art of RNA bioinformatics focusing on applications to prokaryotes.

On the importance of cotranscriptional RNA structure formation

The expression of genes, both coding and noncoding, can be significantly influenced by RNA structural features of their corresponding transcripts. There is by now mounting experimental and some theoretical evidence that structure formation in vivo starts during transcription and that this cotranscriptional folding determines the functional RNA structural features that are being formed. Several decades of research in bioinformatics have resulted in a wide range of computational methods for predicting RNA secondary structures. Almost all state-of-the-art methods in terms of prediction accuracy, however, completely ignore the process of structure formation and focus exclusively on the final RNA structure. This review hopes to bridge this gap. We summarize the existing evidence for cotranscriptional folding and then review the different, currently used strategies for RNA secondary-structure prediction. Finally, we propose a range of ideas on how state-of-the-art methods could be potentially improved by explicitly capturing the process of cotranscriptional structure formation.