The expanding targetome of small RNAs in Salmonella Typhimurium

STnc1280, a trans-coding sRNA is involved in virulence modulation via targeting gldA mRNA in Salmonella Typhimurium

Introduction. Salmonella Typhimurium (STM) is a food-borne Gram-negative bacterium, which can infect humans and a wide range of livestock and poultry, causing a variety of diseases such as septicaemia, enteritis and abortion.Hypothesis/Gap Statement. We will decipher the impacts of sRNA STnc1280 on STM virulence and provide a theoretical basis to reveal the regulatory role and molecular mechanism of STnc1280.Aim. The main objective of this study was to clarify whether sRNA STnc1280 exerts regulatory roles on STM pathogenicity.Methodology. The STnc1280 gene was amplified and its molecular characteristics were analysed in this study. Then, STnc1280 gene deletion strain (STM-ΔSTnc1280) and the complementary strain (ΔSTnc1280/STnc1280) were constructed by λ-Red homologous recombination method, respectively, to analyse of adhesion and invasive ability and pathogenicity of different strains. Subsequently, the potential target gene regulated by STnc1280 was predicted using target RNA2 software, followed by the verification of the interaction between STnc1280 and target mRNA using the dual plasmid reporter system (DPRS). Furthermore, the mRNA and protein level of target gene was determined using qRT-PCR and Western blot, respectively.Results. The results revealed that the cell adhesion and invasive ability and pathogenicity of STM-ΔSTnc1280 were significantly reduced compared to STM-SL1344 strain, indicating that the deficiency of STnc1280 gene significantly influenced STM pathogenicity. The DPRS results showed that STnc1280 can interact with the mRNA of target gene gldA, thus suppressing the expression of lacZ gene. Furthermore, the level of gldA mRNA was not influenced in STM-ΔSTnc1280, but the expression of GldA protein decreased significantly.Conclusion. Combining the bioinformatic analysis, these findings suggested that STnc1280 may bind to the SD sequence of gldA mRNA, hindering the binding of ribosomes to gldA mRNA, thereby inhibiting the expression of GldA protein to modulate the virulence of STM.

Propionate and Butyrate Inhibit Biofilm Formation of Salmonella Typhimurium Grown in Laboratory Media and Food Models

Salmonella is among the most frequently isolated foodborne pathogens, and biofilm formed by Salmonella poses a potential threat to food safety. Short-chain fatty acids (SCFAs), especially propionate and butyrate, have been demonstrated to exhibit a beneficial effect on promoting intestinal health and regulating the host immune system, but their anti-biofilm property has not been well studied. This study aims to investigate the effects of propionate or butyrate on the biofilm formation and certain virulence traits of Salmonella. We investigated the effect of propionate or butyrate on the biofilm formation of Salmonella enterica serovar Typhimurium (S. Typhimurium) SL1344 grown in LB broth or food models (milk or chicken juice) by crystal violet staining methods. Biofilm formation was significantly reduced in LB broth and food models and the reduction was visualized using a scanning electron microscope (SEM). Biofilm metabolic activity was attenuated in the presence of propionate or butyrate. Meanwhile, both SCFAs decreased AI-2 quorum sensing based on reporter strain assay. Butyrate, not propionate, could effectively reduce bacterial motility. Bacterial adhesion to and invasion of Caco-2 cells were also significantly inhibited in the presence of both SCFAs. Finally, two SCFAs downregulated virulence genes related to biofilm formation and invasion through real-time polymerase chain reaction (RT-PCR). These findings demonstrate the potential application of SCFAs in the mitigation of Salmonella biofilm in food systems, but future research mimicking food environments encountered during the food chain is necessitated.

sRNARFTarget: a fast machine-learning-based approach for transcriptome-wide sRNA target prediction

Bacterial small regulatory RNAs (sRNAs) are key regulators of gene expression in many processes related to adaptive responses. A multitude of sRNAs have been identified in many bacterial species; however, their function has yet to be elucidated. A key step to understand sRNAs function is to identify the mRNAs these sRNAs bind to. There are several computational methods for sRNA target prediction, and the most accurate one is CopraRNA which is based on comparative-genomics. However, species-specific sRNAs are quite common and CopraRNA cannot be used for these sRNAs. The most commonly used transcriptome-wide sRNA target prediction method and second-most-accurate method is IntaRNA. However, IntaRNA can take hours to run on a bacterial transcriptome. Here we present sRNARFTarget, a machine-learning-based method for transcriptome-wide sRNA target prediction applicable to any sRNA. We comparatively assessed the performance of sRNARFTarget, CopraRNA and IntaRNA in three bacterial species. Our results show that sRNARFTarget outperforms IntaRNA in terms of accuracy, ranking of true interacting pairs, and running time. However, CopraRNA substantially outperforms the other two programsin terms of accuracy. Thus, we suggest using CopraRNA when homolog sequences of the sRNA are available, and sRNARFTarget for transcriptome-wide prediction or for species-specific sRNAs. sRNARFTarget is available at https://github.com/BioinformaticsLabAtMUN/sRNARFTarget.

Salmonella Genomics in Public Health and Food Safety

The species Salmonella enterica comprises over 2,600 serovars, many of which are known to be intracellular pathogens of mammals, birds, and reptiles. It is now apparent that Salmonella is a highly adapted environmental microbe and can readily persist in a number of environmental niches, including water, soil, and various plant (including produce) species. Much of what is known about the evolution and diversity of nontyphoidal Salmonella serovars (NTS) in the environment is the result of the rise of the genomics era in enteric microbiology. There are over 340,000 Salmonella genomes available in public databases. This extraordinary breadth of genomic diversity now available for the species, coupled with widespread availability and affordability of whole-genome sequencing (WGS) instrumentation, has transformed the way in which we detect, differentiate, and characterize Salmonella enterica strains in a timely way. Not only have WGS data afforded a detailed and global examination of the molecular epidemiological movement of Salmonella from diverse environmental reservoirs into human and animal hosts, but they have also allowed considerable consolidation of the diagnostic effort required to test for various phenotypes important to the characterization of Salmonella. For example, drug resistance, serovar, virulence determinants, and other genome-based attributes can all be discerned using a genome sequence. Finally, genomic analysis, in conjunction with functional and phenotypic approaches, is beginning to provide new insights into the precise adaptive changes that permit persistence of NTS in so many diverse and challenging environmental niches.

Antibiofilm activity of coenzyme Q0 against Salmonella Typhimurium and its effect on adhesion-invasion and survival-replication

Salmonella Typhimurium, a common Gram-negative foodborne pathogen, threatens public health and hinders the development of the food industry. In this study, we evaluated the antibiofilm activity of coenzyme Q0 (CoQ0) against S. Typhimurium. Besides, the inhibition of the S. Typhimurium's adhesion to and invasion of Caco-2 cells and its survival and replication in RAW 264.7 cells by CoQ0 were also explored. The minimum inhibitory concentrations and minimal bactericidal concentrations of CoQ0 against Salmonella were both 100-400 μg/mL. Salmonella Typhimurium biofilm formation was effectively inhibited by subinhibitory concentrations (SICs) of CoQ0. The CoQ0-affected biofilm morphology was observed with light microscopy and field-emission scanning electron microscopy. CoQ0 at SICs reduced the swimming motility and quorum sensing of S. Typhimurium and repressed the transcription of critical virulence-related genes. CoQ0 at SICs also clearly reduced the adhesion of S. Typhimurium to and its invasion of Caco-2 cells and reduced its survival and replication within RAW 264.7 macrophage cells. These findings suggest that CoQ0 has strong antibiofilm activity and can be used as an anti-infectious agent against Salmonella.

sRNA Target Prediction Organizing Tool (SPOT) Integrates Computational and Experimental Data To Facilitate Functional Characterization of Bacterial Small RNAs

Small RNAs (sRNAs) regulate gene expression in diverse bacteria by interacting with mRNAs to change their structure, stability, or translation. Hundreds of sRNAs have been identified in bacteria, but characterization of their regulatory functions is limited by difficulty with sensitive and accurate identification of mRNA targets. Thus, new robust methods of bacterial sRNA target identification are in demand. Here, we describe our small RNA target prediction organizing tool (SPOT), which streamlines the process of sRNA target prediction by providing a single pipeline that combines available computational prediction tools with customizable results filtering based on experimental data. SPOT allows the user to rapidly produce a prioritized list of predicted sRNA-target mRNA interactions that serves as a basis for further experimental characterization. This tool will facilitate elucidation of sRNA regulons in bacteria, allowing new discoveries regarding the roles of sRNAs in bacterial stress responses and metabolic regulation.

Small RNAs (sRNAs) posttranscriptionally regulate mRNA targets, typically under conditions of environmental stress. Although hundreds of sRNAs have been discovered in diverse bacterial genomes, most sRNAs remain uncharacterized, even in model organisms. Identification of mRNA targets directly regulated by sRNAs is rate-limiting for sRNA functional characterization. To address this, we developed a computational pipeline that we named SPOT for sRNA target prediction organizing tool. SPOT incorporates existing computational tools to search for sRNA binding sites, allows filtering based on experimental data, and organizes the results into a standardized report. SPOT sensitivity (number of correctly predicted targets/number of total known targets) was equal to or exceeded any individual method when used on 12 characterized sRNAs. Using SPOT, we generated a set of target predictions for the sRNA RydC, which was previously shown to positively regulate cfa mRNA, encoding cyclopropane fatty acid synthase. SPOT identified cfa along with additional putative mRNA targets, which we then tested experimentally. Our results demonstrated that in addition to cfa mRNA, RydC also regulates trpE and pheA mRNAs, which encode aromatic amino acid biosynthesis enzymes. Our results suggest that SPOT can facilitate elucidation of sRNA target regulons to expand our understanding of the many regulatory roles played by bacterial sRNAs.

IMPORTANCE Small RNAs (sRNAs) regulate gene expression in diverse bacteria by interacting with mRNAs to change their structure, stability, or translation. Hundreds of sRNAs have been identified in bacteria, but characterization of their regulatory functions is limited by difficulty with sensitive and accurate identification of mRNA targets. Thus, new robust methods of bacterial sRNA target identification are in demand. Here, we describe our small RNA target prediction organizing tool (SPOT), which streamlines the process of sRNA target prediction by providing a single pipeline that combines available computational prediction tools with customizable results filtering based on experimental data. SPOT allows the user to rapidly produce a prioritized list of predicted sRNA-target mRNA interactions that serves as a basis for further experimental characterization. This tool will facilitate elucidation of sRNA regulons in bacteria, allowing new discoveries regarding the roles of sRNAs in bacterial stress responses and metabolic regulation.

Biological and regulatory roles of acid-induced small RNA RyeC in Salmonella Typhimurium

Salmonella Typhimurium is an enteric pathogen that has evolved masterful strategies to enable survival under stress conditions both within and outside a host. The acid tolerance response (ATR) is one such mechanism that enhances the viability of acid adapted bacteria to lethal pH levels. While numerous studies exist on the protein coding components of this response, there is very little data on the roles of small RNAs (sRNAs). These non-coding RNA molecules have recently been shown to play roles as regulators of bacterial stress response and virulence pathways. They function through complementary base pairing interactions with target mRNAs and affect their translation and/or stability. There are also a few that directly bind to proteins by mimicking their respective targets. Here, we identify several sRNAs expressed during the ATR of S. Typhimurium and characterize one highly induced candidate, RyeC. Further, we identify ptsI as a trans-encoded target that is directly regulated by this sRNA. From a functional perspective, over-expression of RyeC in Salmonella produced a general attenuation of several in vitro phenotypes including acid survival, motility, adhesion and invasion of epithelial cell lines as well as replication within macrophages. Together, this study highlights the diverse roles played by sRNAs in acid tolerance and virulence of S. Typhimurium.