Inference of Bacterial Small RNA Regulatory Networks and Integration with Transcription Factor-Driven Regulatory Networks

Multiscale regulation of nutrient stress responses in Escherichia coli from chromatin structure to small regulatory RNAs

Recent research has indicated the presence of heterochromatin-like regions of extended protein occupancy and transcriptional silencing of bacterial genomes. We utilized an integrative approach to track chromatin structure and transcription in E. coli K-12 across a wide range of nutrient conditions. In the process, we identified multiple loci which act similarly to facultative heterochromatin in eukaryotes, normally silenced but permitting expression of genes under specific conditions. We also found a strong enrichment of small regulatory RNAs (sRNAs) among the set of differentially expressed transcripts during nutrient stress. Using a newly developed bioinformatic pipeline, the transcription factors regulating sRNA expression were bioinformatically predicted, with experimental follow-up revealing novel relationships for 36 sRNA-transcription factors candidates. Direct regulation of sRNA expression was confirmed by mutational analysis for five sRNAs of metabolic interest: IsrB, CsrB and CsrC, GcvB, and GadY. Our integrative analysis thus reveals additional layers of complexity in the nutrient stress response in E. coli and provides a framework for revealing similar poorly understood regulatory logic in other organisms.

Antisense yycF and BMP-2 co-delivery gelatin methacryloyl and carboxymethyl chitosan hydrogel composite for infective bone defects regeneration

Repairing infected bone defects remains a challenge in clinical work. Intractable bacterial infections and insufficient osseointegration are major concerns for infected bone defects. To address these issues, we developed a gelatin methacryloyl (GelMA) and carboxymethyl chitosan (CMCS) composite hydrogel with BMP-2 growth factor and GO based antisense technology supported by a PLGA spring. In vitro, photo-crosslinked GelMA composite hydrogels shown excellent biocompatibility and degradability. Relying on the release of BMP-2 from the composite hydrogel provides osteogenic effects. The antisense yycF and BMP-2 were released with the degradation of GelMA and CMCS composite hydrogel. In terms of antimicrobial properties, CMCS, GO and post-transcriptional regulatory antisense yycF from the composite hydrogel synergistically kill S. aureus. In vivo, we implanted the composite hydrogel in a rat model of S. aureus infected femur defect, effectively accelerating bone healing in an infectious microenvironment. This research provides a novel biomaterial that is both antimicrobial and promotes bone regeneration, with the potential to treat infected bone defects.

Recent insights into the world of dual-function bacterial sRNAs

Dual-function sRNAs refer to a small subgroup of small regulatory RNAs that merges base-pairing properties of antisense RNAs with peptide-encoding properties of mRNA. Both functions can be part of either same or in another metabolic pathway. Here, we want to update the knowledge of to the already known dual-function sRNAs and review the six new sRNAs found since 2017 regarding their structure, functional mechanisms, evolutionary conservation, and role in the regulation of distinct biological/physiological processes. The increasing identification of dual-function sRNAs through bioinformatics approaches, RNomics and RNA-sequencing and the associated increase in regulatory understanding will likely continue to increase at the same rate in the future. This may improve our understanding of the physiology, virulence and resistance of bacteria, as well as enable their use in technical applications. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

Disrupting the ArcA Regulatory Network Amplifies the Fitness Cost of Tetracycline Resistance in Escherichia coli

There is an urgent need for strategies to discover secondary drugs to prevent or disrupt antimicrobial resistance (AMR), which is causing >700,000 deaths annually. Here, we demonstrate that tetracycline-resistant (Tet^R) Escherichia coli undergoes global transcriptional and metabolic remodeling, including downregulation of tricarboxylic acid cycle and disruption of redox homeostasis, to support consumption of the proton motive force for tetracycline efflux. Using a pooled genome-wide library of single-gene deletion strains, at least 308 genes, including four transcriptional regulators identified by our network analysis, were confirmed as essential for restoring the fitness of Tet^R E. coli during treatment with tetracycline. Targeted knockout of ArcA, identified by network analysis as a master regulator of this new compensatory physiological state, significantly compromised fitness of Tet^R E. coli during tetracycline treatment. A drug, sertraline, which generated a similar metabolome profile as the arcA knockout strain, also resensitized Tet^R E. coli to tetracycline. We discovered that the potentiating effect of sertraline was eliminated upon knocking out arcA, demonstrating that the mechanism of potential synergy was through action of sertraline on the tetracycline-induced ArcA network in the Tet^R strain. Our findings demonstrate that therapies that target mechanistic drivers of compensatory physiological states could resensitize AMR pathogens to lost antibiotics. IMPORTANCE Antimicrobial resistance (AMR) is projected to be the cause of >10 million deaths annually by 2050. While efforts to find new potent antibiotics are effective, they are expensive and outpaced by the rate at which new resistant strains emerge. There is desperate need for a rational approach to accelerate the discovery of drugs and drug combinations that effectively clear AMR pathogens and even prevent the emergence of new resistant strains. Using tetracycline-resistant (Tet^R) Escherichia coli, we demonstrate that gaining resistance is accompanied by loss of fitness, which is restored by compensatory physiological changes. We demonstrate that transcriptional regulators of the compensatory physiologic state are promising drug targets because their disruption increases the susceptibility of Tet^R E. coli to tetracycline. Thus, we describe a generalizable systems biology approach to identify new vulnerabilities within AMR strains to rationally accelerate the discovery of therapeutics that extend the life span of existing antibiotics.

Mathematical models to study the biology of pathogens and the infectious diseases they cause

Mathematical models have many applications in infectious diseases: epidemiologists use them to forecast outbreaks and design containment strategies; systems biologists use them to study complex processes sustaining pathogens, from the metabolic networks empowering microbial cells to ecological networks in the microbiome that protects its host. Here, we (1) review important models relevant to infectious diseases, (2) draw parallels among models ranging widely in scale. We end by discussing a minimal set of information for a model to promote its use by others and to enable predictions that help us better fight pathogens and the diseases they cause.

Mining RNA-seq data reveals the massive regulon of GcvB small RNA and its physiological significance in maintaining amino acid homeostasis in Escherichia coli

Bacterial small RNAs regulate the expression of multiple genes through imperfect base-pairing with target mRNAs mediated by RNA chaperone proteins such as Hfq. GcvB is the master sRNA regulator of amino acid metabolism and transport in a wide range of Gram-negative bacteria. Recently, independent RNA-seq approaches identified a plethora of transcripts interacting with GcvB in Escherichia coli. In this study, the compilation of RIL-seq, CLASH, and MAPS data sets allowed us to identify GcvB targets with high accuracy. We validated 21 new GcvB targets repressed at the posttranscriptional level, raising the number of direct targets to >50 genes in E. coli. Among its multiple seed sequences, GcvB utilizes either R1 or R3 to regulate most of these targets. Furthermore, we demonstrated that both R1 and R3 seed sequences are required to fully repress the expression of gdhA, cstA, and sucC genes. In contrast, the ilvLXGMEDA polycistronic mRNA is targeted by GcvB through at least four individual binding sites in the mRNA. Finally, we revealed that GcvB is involved in the susceptibility of peptidase-deficient E. coli strain (Δpeps) to Ala-Gln dipeptide by regulating both Dpp dipeptide importer and YdeE dipeptide exporter via R1 and R3 seed sequences, respectively.

MicroRNAs Encoded by Virus and Small RNAs Encoded by Bacteria Associated with Oncogenic Processes

Cancer is a deadly disease and, globally, represents the second leading cause of death in the world. Although it is a disease where several factors can help its development, virus induced infections have been associated with different types of neoplasms. However, in bacterial infections, their participation is not known for certain. Among the proposed approaches to oncogenesis risks in different infections are microRNAs (miRNAs). These are small molecules composed of RNA with a length of 22 nucleotides capable of regulating gene expression by directing protein complexes that suppress the untranslated region of mRNA. These miRNAs and other recently described, such as small RNAs (sRNAs), are deregulated in the development of cancer, becoming promising biomarkers. Thus, resulting in a study possibility, searching for new tools with diagnostic and therapeutic approaches to multiple oncological diseases, as miRNAs and sRNAs are main players of gene expression and host–infectious agent interaction. Moreover, sRNAs with limited complementarity are similar to eukaryotic miRNAs in their ability to modulate the activity and stability of multiple mRNAs. Here, we will describe the regulatory RNAs from viruses that have been associated with cancer and how sRNAs in bacteria can be related to this disease.

Quantitative prediction of conditional vulnerabilities in regulatory and metabolic networks using PRIME

The ability of Mycobacterium tuberculosis (Mtb) to adopt heterogeneous physiological states underlies its success in evading the immune system and tolerating antibiotic killing. Drug tolerant phenotypes are a major reason why the tuberculosis (TB) mortality rate is so high, with over 1.8 million deaths annually. To develop new TB therapeutics that better treat the infection (faster and more completely), a systems-level approach is needed to reveal the complexity of network-based adaptations of Mtb. Here, we report a new predictive model called PRIME (Phenotype of Regulatory influences Integrated with Metabolism and Environment) to uncover environment-specific vulnerabilities within the regulatory and metabolic networks of Mtb. Through extensive performance evaluations using genome-wide fitness screens, we demonstrate that PRIME makes mechanistically accurate predictions of context-specific vulnerabilities within the integrated regulatory and metabolic networks of Mtb, accurately rank-ordering targets for potentiating treatment with frontline drugs.

Predictive regulatory and metabolic network models for systems analysis of Clostridioides difficile

We present predictive models for comprehensive systems analysis of Clostridioides difficile, the etiology of pseudomembranous colitis. By leveraging 151 published transcriptomes, we generated an EGRIN model that organizes 90% of C. difficile genes into a transcriptional regulatory network of 297 co-regulated modules, implicating genes in sporulation, carbohydrate transport, and metabolism. By advancing a metabolic model through addition and curation of metabolic reactions including nutrient uptake, we discovered 14 amino acids, diverse carbohydrates, and 10 metabolic genes as essential for C. difficile growth in the intestinal environment. Finally, we developed a PRIME model to uncover how EGRIN-inferred combinatorial gene regulation by transcription factors, such as CcpA and CodY, modulates essential metabolic processes to enable C. difficile growth relative to commensal colonization. The C. difficile interactive web portal provides access to these model resources to support collaborative systems-level studies of context-specific virulence mechanisms in C. difficile.

Specific and Global RNA Regulators in Pseudomonas aeruginosa

Pseudomonas aeruginosa (Pae) is an opportunistic pathogen showing a high intrinsic resistance to a wide variety of antibiotics. It causes nosocomial infections that are particularly detrimental to immunocompromised individuals and to patients suffering from cystic fibrosis. We provide a snapshot on regulatory RNAs of Pae that impact on metabolism, pathogenicity and antibiotic susceptibility. Different experimental approaches such as in silico predictions, co-purification with the RNA chaperone Hfq as well as high-throughput RNA sequencing identified several hundreds of regulatory RNA candidates in Pae. Notwithstanding, using in vitro and in vivo assays, the function of only a few has been revealed. Here, we focus on well-characterized small base-pairing RNAs, regulating specific target genes as well as on larger protein-binding RNAs that sequester and thereby modulate the activity of translational repressors. As the latter impact large gene networks governing metabolism, acute or chronic infections, these protein-binding RNAs in conjunction with their cognate proteins are regarded as global post-transcriptional regulators.

An Integrated Database of Small RNAs and Their Interplay With Transcriptional Gene Regulatory Networks in Corynebacteria

Small RNAs (sRNAs) are one of the key players in the post-transcriptional regulation of bacterial gene expression. These molecules, together with transcription factors, form regulatory networks and greatly influence the bacterial regulatory landscape. Little is known concerning sRNAs and their influence on the regulatory machinery in the genus Corynebacterium, despite its medical, veterinary and biotechnological importance. Here, we expand corynebacterial regulatory knowledge by integrating sRNAs and their regulatory interactions into the transcriptional regulatory networks of six corynebacterial species, covering four human and animal pathogens, and integrate this data into the CoryneRegNet database. To this end, we predicted sRNAs to regulate 754 genes, including 206 transcription factors, in corynebacterial gene regulatory networks. Amongst them, the sRNA Cd-NCTC13129-sRNA-2 is predicted to directly regulate ydfH, which indirectly regulates 66 genes, including the global regulator glxR in C. diphtheriae. All of the sRNA-enriched regulatory networks of the genus Corynebacterium have been made publicly available in the newest release of CoryneRegNet(www.exbio.wzw.tum.de/coryneregnet/) to aid in providing valuable insights and to guide future experiments.

YbeY controls the type III and type VI secretion systems and biofilm formation through RetS in Pseudomonas aeruginosa

YbeY is a highly conserved RNase in bacteria and plays essential roles in the maturation of 16S rRNA, regulation of small RNAs (sRNAs) and bacterial responses to environmental stresses. Previously, we verified the role of YbeY in rRNA processing and ribosome maturation in Pseudomonas aeruginosa and demonstrated YbeY-mediated regulation of rpoS through a sRNA ReaL. In this study, we demonstrate that mutation of the ybeY gene results in upregulation of the type III secretion system (T3SS) genes as well as downregulation of the type VI secretion system (T6SS) genes and reduction of biofilm formation. By examining the expression of the known sRNAs in P. aeruginosa, we found that mutation of the ybeY gene leads to downregulation of the small RNAs RsmY/Z that control the T3SS, the T6SS and biofilm formation. Further studies revealed that the reduced levels of RsmY/Z are due to upregulation of retS Taken together, our results reveal the pleiotropic functions of YbeY and provide detailed mechanisms of YbeY-mediated regulation in P. aeruginosa IMPORTANCE Pseudomonas aeruginosa causes a variety of acute and chronic infections in humans. The type III secretion system (T3SS) plays an important role in acute infection and the type VI secretion system (T6SS) and biofilm formation are associated with chronic infections. Understanding of the mechanisms that control the virulence determinants involved in acute and chronic infections will provide clues for the development of effective treatment strategies. Our results reveal a novel RNase mediated regulation on the T3SS, T6SS and biofilm formation in P. aeruginosa.

Plugging Small RNAs into the Network

Small RNAs (sRNAs) have been discovered in every bacterium examined and have been shown to play important roles in the regulation of a diverse range of behaviors, from metabolism to infection. However, despite a wide range of available techniques for discovering and validating sRNA regulatory interactions, only a minority of these molecules have been well characterized. In part, this is due to the nature of posttranscriptional regulation: the activity of an sRNA depends on the state of the transcriptome as a whole, so characterization is best carried out under the conditions in which it is naturally active. In this issue of mSystems, Arrieta-Ortiz and colleagues (M. L. Arrieta-Ortiz, C. Hafemeister, B. Shuster, N. S. Baliga, et al., mSystems 5:e00057-20, 2020, https://doi.org/10.1128/mSystems.00057-20) present a network inference approach based on estimating sRNA activity across transcriptomic compendia. This shows promise not only for identifying new sRNA regulatory interactions but also for pinpointing the conditions in which these interactions occur, providing a new avenue toward functional characterization of sRNAs.