Upstream region of OprD mutations in imipenem-resistant and imipenem-sensitive Pseudomonas isolates

Advances in Development of Novel Therapeutic Strategies against Multi-Drug Resistant Pseudomonas aeruginosa

Pseudomonas aeruginosa (P. aeruginosa) with multi-drug resistance (MDR) is a major cause of serious healthcare-associated infections, leading to high morbidity and mortality. This opportunistic pathogen is responsible for various infectious diseases, such as those seen in cystic fibrosis, ventilator-associated pneumonia, urinary tract infection, otitis externa, and burn and wound injuries. Due to its relatively large genome, P. aeruginosa has great diversity and can use various molecular mechanisms for antimicrobial resistance. For example, outer membrane permeability can contribute to antimicrobial resistance and is determined by lipopolysaccharide (LPS) and porin proteins. Recent findings on the regulatory interaction between peptidoglycan and LPS synthesis provide additional clues against pathogenic P. aeruginosa. This review focuses on recent advances in antimicrobial agents and inhibitors targeting LPS and porin proteins. In addition, we explore current and emerging treatment strategies for MDR P. aeruginosa, including phages, vaccines, nanoparticles, and their combinatorial therapies. Novel strategies and their corresponding therapeutic agents are urgently needed for combating MDR pathogens.

Bacterial resistance to antibacterial agents: Mechanisms, control strategies, and implications for global health

The spread of bacterial drug resistance has posed a severe threat to public health globally. Here, we cover bacterial resistance to current antibacterial drugs, including traditional herbal medicines, conventional antibiotics, and antimicrobial peptides. We summarize the influence of bacterial drug resistance on global health and its economic burden while highlighting the resistance mechanisms developed by bacteria. Based on the One Health concept, we propose 4A strategies to combat bacterial resistance, including prudent Application of antibacterial agents, Administration, Assays, and Alternatives to antibiotics. Finally, we identify several opportunities and unsolved questions warranting future exploration for combating bacterial resistance, such as predicting genetic bacterial resistance through the use of more effective techniques, surveying both genetic determinants of bacterial resistance and the transmission dynamics of antibiotic resistance genes (ARGs).

Risk Factors and Outcomes for Multidrug Resistant Pseudomonas aeruginosa Infection in Immunocompromised Patients

Background: Pseudomonas aeruginosa (PSA) infection often occurs in immunocompromised patients, which also face an increased risk of multidrug-resistant (MDR) bacteria. A deeper knowledge of the risk factors for MDR-PSA infection in this patient population may help to choose appropriate empirical antibiotic therapy. Methods: a single-center case-control (1:2) retrospective study that included 48 patients with underlying immunosuppression developing MDR-PSA infection (cases) and 96 patients also immunocompromised that were infected with non-MDR-PSA (controls) was conducted. Both groups were matched by site of infection, clinical features and type of immunosuppression. Risk factors for MDR-PSA were assessed by logistic regression. Clinical outcomes were also compared between both groups. Results: immunosuppression was due to solid cancer in 63 (43.8%) patients, solid organ transplantation in 39 (27.1%), hematological disease in 35 (24.3%) and other causes in 7 (4.9%). Independent risk factors for MDR-PSA infection were diabetes mellitus (odds ratio [OR]: 4.74; 95% confidence interval [CI]: 1.63−13.79; p = 0.004), antibiotic therapy in the previous 3 months (OR: 5.32; 95% CI: 1.93−14.73; p = 0.001), previous MDR-PSA colonization (OR: 42.1; 95% CI: 4.49−394.8; p = 0.001) and septic shock (OR: 3.73; 95% CI: 1.36−10.21; p = 0.010). MDR-PSA cases were less likely to receive adequate empirical therapy (14 [29.2%] vs. 69 [71.9%]; p < 0.001). 30-day clinical improvement was less common in MDR-PSA cases (25 [52.1%] vs. 76 [79.2%]; p = 0.001). Conclusions: diabetes mellitus, previous MDR-PSA colonization, prior receipt of antibiotics and septic shock acted as risk factors for developing MDR-PSA infections in immunocompromised patients, who have a poorer outcome than those infected with non-MDR-PSA strains.

Resistance Is Not Futile: The Role of Quorum Sensing Plasticity in Pseudomonas aeruginosa Infections and Its Link to Intrinsic Mechanisms of Antibiotic Resistance

Bacteria use a cell-cell communication process called quorum sensing (QS) to orchestrate collective behaviors. QS relies on the group-wide detection of extracellular signal molecules called autoinducers (AI). Quorum sensing is required for virulence and biofilm formation in the human pathogen Pseudomonas aeruginosa. In P. aeruginosa, LasR and RhlR are homologous LuxR-type soluble transcription factor receptors that bind their cognate AIs and activate the expression of genes encoding functions required for virulence and biofilm formation. While some bacterial signal transduction pathways follow a linear circuit, as phosphoryl groups are passed from one carrier protein to another ultimately resulting in up- or down-regulation of target genes, the QS system in P. aeruginosa is a dense network of receptors and regulators with interconnecting regulatory systems and outputs. Once activated, it is not understood how LasR and RhlR establish their signaling hierarchy, nor is it clear how these pathway connections are regulated, resulting in chronic infection. Here, we reviewed the mechanisms of QS progression as it relates to bacterial pathogenesis and antimicrobial resistance and tolerance.

Comparative genomic analysis of Escherichia coli strains obtained from continuous imipenem stress evolution

The carbapenem-resistant Escherichia coli (E. coli) has aroused increasing attention worldwide, especially in terms of imipenem (IMP) resistance. The molecular mechanism of IMP resistance remains unclear. This study aimed to explore the resistance mechanisms of IMP in E. coli. Susceptible Sx181-0-1 strain was induced into resistance strains by adaptive laboratory evolution. The drug resistance spectrum was measured using the disk diffusion and microbroth dilution methods. Whole-genome sequencing and resequencing were used to analyze the non-synonymous single-nucleotide polymorphisms (nsSNPs) between the primary susceptible strain and resistant strains. The expression levels of these genes with nsSNPs were identified by real-time quantitative PCR (RT-qPCR). Resistance phenotype appeared in the induced 15th generation (induction time = 183 h). Sx181-32 and Sx181-256, which had minimum inhibitory concentrations of IMP of 8 and 64 µg mL-1, were isolated during continuous subculture exposed to increasing concentrations of IMP, respectively. Nineteen nsSNPs were observed both in Sx181-32 and Sx181-256, including rpsU, sdaC, zwf, ttuC, araJ, dacC, mrdA, secF, dacD, lpxD, mrcB, ftsI, envZ, and two unknown function genes (orf01892 and orf01933). Among these 15 genes, five genes (dacC, mrdA, lpxD, mrcB, and ftsI) were mainly involved in cell wall synthesis. The mrdA (V338A, L378P, and M574I) and mrcB (P784L, A736V, and T708A) had three amino acid substitutions, respectively. The expression levels of rpsU, ttuC and orf01933 were elevated in both Sx181-32 and Sx181-256 compared to Sx181-0-1. The expression levels of these genes were elevated in Sx181-256, except for araJ. Bacteria developed resistance to antimicrobials by regulating various biological processes, among which the most involved is the cell wall synthesis (dacC, mrdA, lpxD, mrcB, and ftsI). The combination mutations of mrdA, envZ, and ftsI genes may increase the resistance to IMP. Our study could improve the understanding of the molecular mechanism underlying the IMP resistance of E. coli.