Insertion sequences drive the emergence of a highly adapted human pathogen

Pathogenicity and virulence of Shigella sonnei: A highly drug-resistant pathogen of increasing prevalence

Shigella spp. are the causative agent of shigellosis (or bacillary dysentery), a diarrhoeal disease characterized for the bacterial invasion of gut epithelial cells. Among the 4 species included in the genus, Shigella flexneri is principally responsible for the disease in the developing world while Shigella sonnei is the main causative agent in high-income countries. Remarkably, as more countries improve their socioeconomic conditions, we observe an increase in the relative prevalence of S. sonnei. To date, the reasons behind this change in aetiology depending on economic growth are not understood. S. flexneri has been widely used as a model to study the pathogenesis of the genus, but as more research data are collected, important discrepancies with S. sonnei have come to light. In comparison to S. flexneri, S. sonnei can be differentiated in numerous aspects; it presents a characteristic O-antigen identical to that of one serogroup of the environmental bacterium Plesiomonas shigelloides, a group 4 capsule, antibacterial mechanisms to outcompete and displace gut commensal bacteria, and a poorer adaptation to an intracellular lifestyle. In addition, the World Health Organization (WHO) have recognized the significant threat posed by antibiotic-resistant strains of S. sonnei, demanding new approaches. This review gathers knowledge on what is known about S. sonnei within the context of other Shigella spp. and aims to open the door for future research on understanding the increasing spread of this pathogen.

Compendium-Wide Analysis of Pseudomonas aeruginosa Core and Accessory Genes Reveals Transcriptional Patterns across Strains PAO1 and PA14

Pseudomonas aeruginosa is an opportunistic pathogen that causes difficult-to-treat infections. Two well-studied divergent P. aeruginosa strain types, PAO1 and PA14, have significant genomic heterogeneity, including diverse accessory genes present in only some strains. Genome content comparisons find core genes that are conserved across both PAO1 and PA14 strains and accessory genes that are present in only a subset of PAO1 and PA14 strains. Here, we use recently assembled transcriptome compendia of publicly available P. aeruginosa RNA sequencing (RNA-seq) samples to create two smaller compendia consisting of only strain PAO1 or strain PA14 samples with each aligned to their cognate reference genome. We confirmed strain annotations and identified other samples for inclusion by assessing each sample's median expression of PAO1-only or PA14-only accessory genes. We then compared the patterns of core gene expression in each strain. To do so, we developed a method by which we analyzed genes in terms of which genes showed similar expression patterns across strain types. We found that some core genes had consistent correlated expression patterns across both compendia, while others were less stable in an interstrain comparison. For each accessory gene, we also determined core genes with correlated expression patterns. We found that stable core genes had fewer coexpressed neighbors that were accessory genes. Overall, this approach for analyzing expression patterns across strain types can be extended to other groups of genes, like phage genes, or applied for analyzing patterns beyond groups of strains, such as samples with different traits, to reveal a deeper understanding of regulation. IMPORTANCE Pseudomonas aeruginosa is a ubiquitous pathogen. There is much diversity among P. aeruginosa strains, including two divergent but well-studied strains, PAO1 and PA14. Understanding how these different strain-level traits manifest is important for identifying targets that regulate different traits of interest. With the availability of thousands of PAO1 and PA14 samples, we created two strain-specific RNA-seq compendia where each one contains hundreds of samples from PAO1 or PA14 strains and used them to compare the expression patterns of core genes that are conserved in both strain types and to determine which core genes have expression patterns that are similar to those of accessory genes that are unique to one strain or the other using an approach that we developed. We found a subset of core genes with different transcriptional patterns across PAO1 and PA14 strains and identified those core genes with expression patterns similar to those of strain-specific accessory genes.

Adaptation and Evolution of Pathogens in the Cystic Fibrosis Lung

As opposed to acute respiratory infections, the persistent bacterial infections of the lung that characterize cystic fibrosis (CF) provide ample time for bacteria to evolve and adapt. The process of adaptation is recorded in mutations that accumulate over time in the genomes of the infecting bacteria. Some of these mutations lead to obvious phenotypic differences such as antibiotic resistance or the well-known mucoid phenotype of Pseudomonas aeruginosa. Other mutations may be just as important but harder to detect such as increased mutation rates, cell surface changes, and shifts in metabolism and nutrient acquisition. Remarkably, many of the adaptations occur again and again in different patients, signaling that bacteria are adapting to solve specific challenges in the CF respiratory tract. This parallel evolution even extends across distinct bacterial species. This review addresses the bacterial systems that are known to change in long-term CF infections with a special emphasis on cross-species comparisons. Consideration is given to how adaptation may impact health in CF, and the possible evolutionary mechanisms that lead to the repeated parallel adaptations.

Using genome-wide expression compendia to study microorganisms

A gene expression compendium is a heterogeneous collection of gene expression experiments assembled from data collected for diverse purposes. The widely varied experimental conditions and genetic backgrounds across samples creates a tremendous opportunity for gaining a systems level understanding of the transcriptional responses that influence phenotypes. Variety in experimental design is particularly important for studying microbes, where the transcriptional responses integrate many signals and demonstrate plasticity across strains including response to what nutrients are available and what microbes are present. Advances in high-throughput measurement technology have made it feasible to construct compendia for many microbes. In this review we discuss how these compendia are constructed and analyzed to reveal transcriptional patterns.

Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach

Fast and accurate identifications of pathogenic bacteria along with their associated antibiotic resistance proteins are of paramount importance for patient treatments and public health. To meet this goal from the mass spectrometry aspect, we have augmented the previously published Microorganism Classification and Identification (MiCId) workflow for this capability. To evaluate the performance of this augmented workflow, we have used MS/MS datafiles from samples of 10 antibiotic resistance bacterial strains belonging to three different species: Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. The evaluation shows that MiCId's workflow has a sensitivity value around 85% (with a lower bound at about 72%) and a precision greater than 95% in identifying antibiotic resistance proteins. In addition to having high sensitivity and precision, MiCId's workflow is fast and portable, making it a valuable tool for rapid identifications of bacteria as well as detection of their antibiotic resistance proteins. It performs microorganismal identifications, protein identifications, sample biomass estimates, and antibiotic resistance protein identifications in 6-17 min per MS/MS sample using computing resources that are available in most desktop and laptop computers. We have also demonstrated other use of MiCId's workflow. Using MS/MS data sets from samples of two bacterial clonal isolates, one being antibiotic-sensitive while the other being multidrug-resistant, we applied MiCId's workflow to investigate possible mechanisms of antibiotic resistance in these pathogenic bacteria; the results showed that MiCId's conclusions agree with the published study. The new version of MiCId (v.07.01.2021) is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Evolution of Subfamily I.1 Lipases in Pseudomonas aeruginosa

The gram-negative Pseudomonas aeruginosa is an opportunistic human pathogen that contains two different types of strains: the "classical" and the "outlier". In the "classical" strain, its bacterial subfamily I.1 lipases, such as LipA and LipC in P. aeruginosa PAO1, play critical roles in its pathogenicity. However, less is known about the subfamily I.1 lipases in the "outlier" strain, nor the evolution paths of those lipases in both types of P. aeruginosa strains. Our genome-scale investigation on I.1 lipases across different bacterial strains demonstrates the presence of one LipA-like and one new type of I.1 lipase (LipC2) in those "outlier" strains. The related genomic islands analyses further suggest that the LipC counterpart gene in the "outlier" strain was lost by gene truncation. In addition, the evolutionary analyses also indicates the horizontal LipC2 gene transfer from other gammaproteobacterial species, as well as the horizontal LipA gene transfer between two different phyla, both suggesting that the gene transfer of bacterial I.1 lipases might occur in different taxonomical levels. Our results not only provide an evidence to understand the pathogenicity among different P. aeruginosa strains, but add to the knowledge of I.1 lipase evolution in bacteria.

Rampant prophage movement among transient competitors drives rapid adaptation during infection

Interactions between bacteria, their close competitors, and viral parasites are common in infections, but understanding of these eco-evolutionary dynamics is limited. Most examples of adaptations caused by phage lysogeny are through the acquisition of new genes. However, integrated prophages can also insert into functional genes and impart a fitness benefit by disrupting their expression, a process called active lysogeny. Here, we show that active lysogeny can fuel rapid, parallel adaptations in establishing a chronic infection. These recombination events repeatedly disrupted genes encoding global regulators, leading to increased cyclic di-GMP levels and elevated biofilm production. The implications of prophage-mediated adaptation are broad, as even transient members of microbial communities can alter the course of evolution and generate persistent phenotypes associated with poor clinical outcomes.

Pangenome Analytics Reveal Two-Component Systems as Conserved Targets in ESKAPEE Pathogens

The ESKAPEE pathogens are the leading cause of health care-associated infections worldwide. Two-component systems (TCSs) can be used as effective targets against pathogenic bacteria since they are ubiquitous and manage various vital functions such as antibiotic resistance, virulence, biofilms, quorum sensing, and pH balance, among others.

The two-component system (TCS) helps bacteria sense and respond to environmental stimuli through histidine kinases and response regulators. TCSs are the largest family of multistep signal transduction processes, and they are involved in many important cellular processes such as antibiotic resistance, pathogenicity, quorum sensing, osmotic stress, and biofilms. Here, we perform the first comprehensive study to highlight the role of TCSs as potential drug targets against ESKAPEE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli) pathogens through annotation, mapping, pangenomic status, gene orientation, and sequence variation analysis. The distribution of the TCSs is group specific with regard to Gram-positive and Gram-negative bacteria, except for KdpDE. The TCSs among ESKAPEE pathogens form closed pangenomes, except for Pseudomonas aeruginosa. Furthermore, their conserved nature due to closed pangenomes might make them good drug targets. Fitness score analysis suggests that any mutation in some TCSs such as BaeSR, ArcBA, EvgSA, and AtoSC, etc., might be lethal to the cell. Taken together, the results of this pangenomic assessment of TCSs reveal a range of strategies deployed by the ESKAPEE pathogens to manifest pathogenicity and antibiotic resistance. This study further suggests that the conserved features of TCSs might make them an attractive group of potential targets with which to address antibiotic resistance.

IMPORTANCE The ESKAPEE pathogens are the leading cause of health care-associated infections worldwide. Two-component systems (TCSs) can be used as effective targets against pathogenic bacteria since they are ubiquitous and manage various vital functions such as antibiotic resistance, virulence, biofilms, quorum sensing, and pH balance, among others. This study provides a comprehensive overview of the pangenomic status of the TCSs among ESKAPEE pathogens. The annotation and pangenomic analysis of TCSs show that they are significantly distributed and conserved among the pathogens, as most of them form closed pangenomes. Furthermore, our analysis also reveals that the removal of the TCSs significantly affects the fitness of the cell. Hence, they may be used as promising drug targets against bacteria.