A previously uncharacterized gene, PA2146, contributes to biofilm formation and drug tolerance across the ɣ-Proteobacteria

Virtual Screening and Meta-Analysis Approach Identifies Factors for Inversion Stimulation (Fis) and Other Genes Responsible for Biofilm Production in Pseudomonas aeruginosa: A Corneal Pathogen

Bacterial keratitis caused by Pseudomonas aeruginosa is indeed a serious concern due to its potential to cause blindness and its resistance to antibiotics, partly attributed to biofilm formation and cytotoxicity to the cornea. The present study uses a meta-analysis of a transcriptomics dataset to identify important genes and pathways in biofilm formation of P. aeruginosa induced keratitis. By combining data from several studies, meta-analysis can enhance statistical power and robustness, enabling the identification of 83 differentially expressed candidate genes, including fis that could serve as therapeutic targets. The approach of combining meta-analysis with virtual screening and in vitro methods provides a comprehensive strategy for identifying potential target genes and pathways crucial for bacterial biofilm formation and development anti-biofilm medications against P. aeruginosa infections. The study identified 83 candidate genes that exhibited differential expression in the biofilm state, with fis proposed as an ideal target for therapy for P. aeruginosa biofilm formation. These techniques, meta-analysis, virtual screening, and invitro methods were used in combination to diagnostically identify these genes, which play a significant role in biofilms. This finding has highlighted a hallmark target list for P. aeruginosa anti-biofilm potential treatments.

Direct prediction of antimicrobial resistance in Pseudomonas aeruginosa by metagenomic next-generation sequencing

Objective

Pseudomonas aeruginosa has strong drug resistance and can tolerate a variety of antibiotics, which is a major problem in the management of antibiotic-resistant infections. Direct prediction of multi-drug resistance (MDR) resistance phenotypes of P. aeruginosa isolates and clinical samples by genotype is helpful for timely antibiotic treatment.

Methods

In the study, whole genome sequencing (WGS) data of 494 P. aeruginosa isolates were used to screen key anti-microbial resistance (AMR)-associated genes related to imipenem (IPM), meropenem (MEM), piperacillin/tazobactam (TZP), and levofloxacin (LVFX) resistance in P. aeruginosa by comparing genes with copy number differences between resistance and sensitive strains. Subsequently, for the direct prediction of the resistance of P. aeruginosa to four antibiotics by the AMR-associated features screened, we collected 74 P. aeruginosa positive sputum samples to sequence by metagenomics next-generation sequencing (mNGS), of which 1 sample with low quality was eliminated. Then, we constructed the resistance prediction model.

Results

We identified 93, 88, 80, 140 AMR-associated features for IPM, MEM, TZP, and LVFX resistance in P. aeruginosa. The relative abundance of AMR-associated genes was obtained by matching mNGS and WGS data. The top 20 features with importance degree for IPM, MEM, TZP, and LVFX resistance were used to model, respectively. Then, we used the random forest algorithm to construct resistance prediction models of P. aeruginosa, in which the areas under the curves of the IPM, MEM, TZP, and LVFX resistance prediction models were all greater than 0.8, suggesting these resistance prediction models had good performance.

Conclusion

In summary, mNGS can predict the resistance of P. aeruginosa by directly detecting AMR-associated genes, which provides a reference for rapid clinical detection of drug resistance of pathogenic bacteria.

Exploring solute binding proteins in Pseudomonas aeruginosa that bind to γ-aminobutyrate and 5-aminovalerate and their role in activating sensor kinases

The standard method of receptor activation involves the binding of signals or signal-loaded solute binding proteins (SBPs) to sensor domains. Many sensor histidine kinases (SHKs), which are activated by SBP binding, are encoded adjacent to their corresponding sbp gene. We examined three SBPs of Pseudomonas aeruginosa PAO1, encoded near the genes for the AgtS (PA0600) and AruS (PA4982) SHKs, to determine how common this arrangement is. Ligand screening and microcalorimetric studies revealed that the SBPs PA0602 and PA4985 preferentially bind to GABA (KD = 2.3 and 0.58 μM, respectively), followed by 5-aminovalerate (KD = 30 and 1.6 μM, respectively) and ethanoldiamine (KD = 2.3 and 0.58 μM, respectively). In contrast, AgtB (PA0604) exclusively recognizes 5-aminovaleric acid (KD = 2.9 μM). However, microcalorimetric titrations did not show any binding between the AgtS sensor domain and AgtB or PA0602, regardless of the presence of ligands. Similarly, bacterial two-hybrid assays did not demonstrate an interaction between PA4985 and the AruS sensor domain. Therefore, sbp and shk genes located nearby are not always functionally linked. We previously identified PA0222 as a GABA-specific SBP. The presence of three SBPs for GABA may be linked to GABA's role as a trigger for P. aeruginosa virulence.

Transposon library screening to identify genes with a potential role in Streptococcus suis biofilm formation

Background: Biofilm formation is considered to be one of reasons for difficulty in the prevention and control of Streptococcus suis. Aims: To explore the potential genes involved in the biofilm formation of S. suis. Methods: Transposon mutagenesis technology was used to screen biofilm-defective strains of S. suis, and the potential genes related to biofilm were identified. Results: A total of 19 genes were identified that were involved in bacterial metabolism, peptidoglycan-binding protein, cell wall synthesis, ABC transporters, and so on. Conclusion: This study constructed 979 transposon mutation libraries of S. suis. A total of 19 gene loci related to the formation of S. suis biofilm were identified, providing a reference for exploring the mechanism of S. suis biofilm formation in the future.

MoaB1 Homologs Contribute to Biofilm Formation and Motility by Pseudomonas aeruginosa and Escherichia coli

moaB homologs, encoding the molybdopterin biosynthetic protein B1, have been reported to be expressed under anoxic conditions and during biofilm growth in various microorganisms; however, little is known about MoaB's function. Here, we demonstrate that in Pseudomonas aeruginosa, MoaB1 (PA3915) contributes to biofilm-related phenotypes. Specifically, moaB1 expression is induced in biofilms, and insertional inactivation of moaB1 reduced biofilm biomass accumulation and pyocyanin production while enhancing swarming motility, and pyoverdine abundance without affecting attachment, swimming motility, or c-di-GMP levels. Inactivation of the highly conserved E. coli homolog of moaB1, moaBEc, likewise coincided with reduced biofilm biomass accumulation. In turn, heterologous expression of moaBEc restored biofilm formation and swarming motility by the P. aeruginosa moaB1 mutant to wild-type levels. Moreover, MoaB1 was found to interact with other conserved biofilm-associated proteins, PA2184 and PA2146, as well as the sensor-kinase SagS. However, despite the interaction, MoaB1 failed to restore SagS-dependent expression of brlR encoding the transcriptional regulator BrlR, and inactivation of moaB1 or moaBEc had no effect on the antibiotic susceptibility phenotype of biofilms formed by P. aeruginosa and E. coli, respectively. While our findings did not establish a link between MoaB1 and molybdenum cofactor biosynthesis, they suggest that MoaB1 homologs contribute to biofilm-associated phenotypes across species boundaries, possibly hinting at the existence of a previously undescribed conserved biofilm pathway. IMPORTANCE Proteins contributing to the biogenesis of molybdenum cofactors have been characterized; however, the role of the molybdopterin biosynthetic protein B1 (MoaB1) has remained elusive, and solid evidence to support its role in biosynthesis of molybdenum cofactor is lacking. Here, we demonstrate that, in Pseudomonas aeruginosa, MoaB1 (PA3915) contributes to biofilm-related phenotypes in a manner that does not support a role of MoaB1 in the biosynthesis of molybdenum cofactors.

Recent advances in therapeutic targets identification and development of treatment strategies towards Pseudomonas aeruginosa infections

The opportunistic human pathogen Pseudomonas aeruginosa is the causal agent of a wide variety of infections. This non-fermentative Gram-negative bacillus can colonize zones where the skin barrier is weakened, such as wounds or burns. It also causes infections of the urinary tract, respiratory system or bloodstream. P. aeruginosa infections are common in hospitalized patients for which multidrug-resistant, respectively extensively drug-resistant isolates can be a strong contributor to a high rate of in-hospital mortality. Moreover, chronic respiratory system infections of cystic fibrosis patients are especially concerning, since very tedious to treat. P. aeruginosa exploits diverse cell-associated and secreted virulence factors, which play essential roles in its pathogenesis. Those factors encompass carbohydrate-binding proteins, quorum sensing that monitor the production of extracellular products, genes conferring extensive drug resistance, and a secretion system to deliver effectors to kill competitors or subvert host essential functions. In this article, we highlight recent advances in the understanding of P. aeruginosa pathogenicity and virulence as well as efforts for the identification of new drug targets and the development of new therapeutic strategies against P. aeruginosa infections. These recent advances provide innovative and promising strategies to circumvent infection caused by this important human pathogen.

Distinct Screening Approaches Uncover PA14_36820 and RecA as Negative Regulators of Biofilm Phenotypes in Pseudomonas aeruginosa PA14

Pseudomonas aeruginosa commonly infects hospitalized patients and the lungs of individuals with cystic fibrosis. This species is known for forming biofilms, which are communities of bacterial cells held together and encapsulated by a self-produced extracellular matrix. The matrix provides extra protection to the constituent cells, making P. aeruginosa infections challenging to treat. We previously identified a gene, PA14_16550, which encodes a DNA-binding TetR-type repressor and whose deletion reduced biofilm formation. Here, we assessed the transcriptional impact of the 16550 deletion and found six differentially regulated genes. Among them, our results implicated PA14_36820 as a negative regulator of biofilm matrix production, while the remaining 5 had modest effects on swarming motility. We also screened a transposon library in a biofilm-impaired ΔamrZ Δ16550 strain for restoration of matrix production. Surprisingly, we found that disruption or deletion of recA increased biofilm matrix production, both in biofilm-impaired and wild-type strains. Because RecA functions both in recombination and in the DNA damage response, we asked which function of RecA is important with respect to biofilm formation by using point mutations in recA and lexA to specifically disable each function. Our results implied that loss of either function of RecA impacts biofilm formation, suggesting that enhanced biofilm formation may be one physiological response of P. aeruginosa cells to loss of either RecA function. IMPORTANCE Pseudomonas aeruginosa is a notorious human pathogen well known for forming biofilms, communities of bacteria that protect themselves within a self-secreted matrix. Here, we sought to find genetic determinants that impacted biofilm matrix production in P. aeruginosa strains. We identified a largely uncharacterized protein (PA14_36820) and, surprisingly, RecA, a widely conserved bacterial DNA recombination and repair protein, as negatively regulating biofilm matrix production. Because RecA has two main functions, we used specific mutations to isolate each function and found that both functions influenced matrix production. Identifying negative regulators of biofilm production may suggest future strategies to reduce the formation of treatment-resistant biofilms.