Antimicrobials as Single and Combination Therapy for Colistin-Resistant Pseudomonas aeruginosa at a University Hospital in Thailand

Prevalence of some metallo β-lactamase enzymes genes in P. aeruginosa isolated from different clinical sample in Baghdad, Iraq

The increasing challenge of carbapenem antibiotics resistance caused by Pseudomonas aeruginosa is one of the global healthcare problems. P. aeruginosa is a significant opportunistic infection. For epidemiological reasons, identifying resistance genes is essential, and it is also desirable to quickly identify the techniques for producing carbapenemase enzymes. So, the study aims to determine the prevalence of beta-lactamase encoding genes (blaIMP, blaVIM, bla GIM, and bla SPM) phenotypically and genotypically in P. aeruginosa isolates to address the epidemiological spread of these genes in Baghdad city. The study identified P. aeruginosa isolates from various clinical sources by chemical characterization and VITEK 2 system, the antibiogram test, phenotypic screening carbapenem resistance by Combined disk synergy test (CDST), and conventional PCR were used to detect presence of VIM, IMP, SPM, and GIM genes. Bacterial susceptibility testing revealed (40 %) of isolates were resistant to Imipenem and (85 %) of them positive to CDST. Genotypic screening on phenotypic Metallo-β-lactamase isolates showed that (100 %) isolates contained blaVIM genes, blaGIM genes (88 %), whereas (65 %) isolates carried blaSPM genes. In this investigation, there was no evidence of blaIMP among carbapenem-resistant isolates. The study appeared high prevalence of multi-drug resistance P. aeruginosa isolates that produce carbapenemase enzymes and having β-lactamase genes in local hospitalized patients compared to global ratio. Expanding the sample size and types of enzymes screening in MDR P. aeruginosa should be the main focus in the future research.

Case Report: Pan-Drug Resistant Pseudomonas aeruginosa from a Child with an Infected Burn Wound at the University Teaching Hospital of Kigali, Rwanda

Background

Pseudomonas aeruginosa is a significant cause of morbidity and mortality in intensive care units, and is prevalent in nosocomial infections and cystic fibrosis. The increasing rates of antimicrobial resistance (AMR) complicate the treatment of P. aeruginosa infections, especially because of the multidrug resistance (MDR), extensively drug-resistant (XDR), and pan-drug resistant (PDR) strains.

Case Presentation

We report the case of a 4-year-old male with severe burns covering 45% of his body surface who developed nosocomial PDR P. aeruginosa infection at the University Teaching Hospital of Kigali (CHUK) in Rwanda. A wound culture yielded a PDR P. aeruginosa isolate that was resistant to all the tested antimicrobials, with intermediate resistance to colistin. However, the patient improved with a combination of ceftazidime and amikacin following cessation of fever and successful skin grafting. The patient was discharged on day 95.

Conclusion

P. aeruginosa is a common hospital-acquired pathogen that is particularly challenging to treat, owing to its antimicrobial resistance profile and biofilm production. Antibiotic-resistant strains are a significant public health threat, especially in pediatric burn units. This case underscores the critical need to strengthen infection prevention and control measures together with robust antimicrobial stewardship programs. Molecular characterization of this PDR strain will yield further details regarding its virulence and genotyping.

Transfer learning predicts species-specific drug interactions in emerging pathogens

Machine learning (ML) algorithms are necessary to efficiently identify potent drug combinations within a large candidate space to combat drug resistance. However, existing ML approaches cannot be applied to emerging and under-studied pathogens with limited training data. To address this, we developed a transfer learning and crowdsourcing framework (TACTIC) to train ML models on data from multiple bacteria. TACTIC was built using 2,965 drug interactions from 12 bacterial strains and outperformed traditional ML models in predicting drug interaction outcomes for species that lack training data. Top TACTIC model features revealed genetic and metabolic factors that influence cross-species and species-specific drug interaction outcomes. Upon analyzing ~600,000 predicted drug interactions across 9 metabolic environments and 18 bacterial strains, we identified a small set of drug interactions that are selectively synergistic against Gram-negative (e.g., A. baumannii) and non-tuberculous mycobacteria (NTM) pathogens. We experimentally validated synergistic drug combinations containing clarithromycin, ampicillin, and mecillinam against M. abscessus, an emerging pathogen with growing levels of antibiotic resistance. Lastly, we leveraged TACTIC to propose selectively synergistic drug combinations to treat bacterial eye infections (endophthalmitis).

Class 1, 2 and 3 integrons in clinical Pseudomonas aeruginosa isolated from Tanta University Hospitals, Egypt

Pseudomonas aeruginosa has become a significant health threat, as it has developed resistance to multiple antimicrobial drugs. In this study, we aimed to identify class 1, 2 and 3 integrons in clinical P. aeruginosa isolates for the first time in Egypt, and detect their relationship with antibiotic resistance. A total of 192 clinical P. aeruginosa isolates were gathered from Tanta University Hospitals. One hundred and thirteen isolates (58.9%) were multidrug- resistant, and 38 isolates (19.8%) were resistant to all drugs tested. Class 1 integrons were detected in 87 isolates (45.3%), while class 2 and 3 integrons were not detected. This is the first report of a profile of integrons in P. aeruginosa from Egypt. The detection of only class 1 integrons in our isolates suggests that other genetic elements may be responsible for the distribution of antibiotic resistance in our setting. Aztreonam and colistin were the drugs of choice for the treatment of infections with P. aeruginosa.

Correlation between phenotypic virulence traits and antibiotic resistance in Pseudomonas aeruginosa clinical isolates

Pseudomonas aeruginosa is a ubiquitous pathogen capable of infecting virtually all tissues and its one of the standout amongst the most hazardous microorganisms of high morbidity and mortality rates especially in debilitated patients with few successful antibiotic choices available. This pathogen regulating most virulence traits by that so-called quorum sensing (QS), a cell to cell communication system. the present study was intended to phenotypically evaluate the activity of specific virulence traits (including swarming and swimming motility, protease, pyocyanin, and biofilm production) in Pseudomonas aeruginosa clinical isolates and assess the statistical correlation between these traits and antibiotic resistance. One hundred and thirteen bacterial isolates were obtained from different clinical samples and identified as P. aeruginosa, among them, 73.4% have the ability to forming biofilm with different degrees; 59.2% were able to produce pyocyanin pigment while all isolates having the ability to make swarming and swimming motility and able to produce protease enzyme with different degrees. The isolates that produce the higher levels of the virulence traits were identified by both biochemical using Vitek2 automated system and genetically via 16s rRNA gene analysis. The statistical analysis results indicate that a positive significant correlation was found between biofilm formation and other studied virulence traits except for protease (r = 0.584: 0.324, P < 0.05) while a non-significant correlation was found between biofilm formation and protease activity (r = 0.105, P ˃ 0.05). Swimming and swarming motility have a positive significant correlation with other studied virulence traits (r = 0.613: 0.297, P < 0.05) except for protease. Pyocyanin pigment production have a positive significant correlation with other studied virulence traits (r = 0.33: 0.297, P < 0.05) except for protease. on the other hand, negative significant correlations were found between biofilm formation, swimming; and swarming motility, Pyocyanin pigment production, and the susceptibility of antibiotics (r = -0.512: -0.281, P < 0.05). Detection of such correlations in P. aeruginosa is useful for study the behavior of this pathogen and may be provide a new target for the treatment of MDR infections.

Bacterial Antibiotic Resistance: The Most Critical Pathogens

Antibiotics have made it possible to treat bacterial infections such as meningitis and bacteraemia that, prior to their introduction, were untreatable and consequently fatal. Unfortunately, in recent decades overuse and misuse of antibiotics as well as social and economic factors have accelerated the spread of antibiotic-resistant bacteria, making drug treatment ineffective. Currently, at least 700,000 people worldwide die each year due to antimicrobial resistance (AMR). Without new and better treatments, the World Health Organization (WHO) predicts that this number could rise to 10 million by 2050, highlighting a health concern not of secondary importance. In February 2017, in light of increasing antibiotic resistance, the WHO published a list of pathogens that includes the pathogens designated by the acronym ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) to which were given the highest "priority status" since they represent the great threat to humans. Understanding the resistance mechanisms of these bacteria is a key step in the development of new antimicrobial drugs to tackle drug-resistant bacteria. In this review, both the mode of action and the mechanisms of resistance of commonly used antimicrobials will be examined. It also discusses the current state of AMR in the most critical resistant bacteria as determined by the WHO's global priority pathogens list.

Bacterial Antibiotic Resistance: The Most Critical Pathogens

Antibiotics have made it possible to treat bacterial infections such as meningitis and bacteraemia that, prior to their introduction, were untreatable and consequently fatal. Unfortunately, in recent decades overuse and misuse of antibiotics as well as social and economic factors have accelerated the spread of antibiotic-resistant bacteria, making drug treatment ineffective. Currently, at least 700,000 people worldwide die each year due to antimicrobial resistance (AMR). Without new and better treatments, the World Health Organization (WHO) predicts that this number could rise to 10 million by 2050, highlighting a health concern not of secondary importance. In February 2017, in light of increasing antibiotic resistance, the WHO published a list of pathogens that includes the pathogens designated by the acronym ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) to which were given the highest "priority status" since they represent the great threat to humans. Understanding the resistance mechanisms of these bacteria is a key step in the development of new antimicrobial drugs to tackle drug-resistant bacteria. In this review, both the mode of action and the mechanisms of resistance of commonly used antimicrobials will be examined. It also discusses the current state of AMR in the most critical resistant bacteria as determined by the WHO's global priority pathogens list.

Antimicrobial Resistance Situational Analysis 2019-2020: Design and Performance for Human Health Surveillance in Uganda

Antibiotic resistance and its mechanisms have been known for over six decades, but global efforts to characterize its routine drivers have only gained momentum in the recent past. Drivers of clinical and community resistance go beyond just clinical practice, which is why one-health approaches offer the most realistic option for controlling antibiotic resistance. It is noteworthy that the emergence of resistance occurs naturally in the environment, but akin to climate change, the current accelerated emergence and spread bears hallmarks of anthropomorphic influence. If left unchecked, this can undo the medical and agricultural advancements of the last century. The WHO recommends that nations develop, adopt, and implement strategies that track the changing trends in antibiotic resistance levels to tackle this problem. This article examines efforts and progress in developing and implementing a human health antimicrobial resistance surveillance strategy in Uganda. We do so within the context of the National Action Plan for tackling antimicrobial resistance (AMR-NAP) launched in 2018. We discuss the technical milestones and progress in implementing surveillance of GLASS priority pathogens under this framework. The preliminary output of the framework examines the performance and compares AMR and AMU surveillance data to explain observed trends. We conclude that Uganda is making progress in developing and implementing a functional AMR surveillance strategy for human health.

Molecular Detection of Carbapenemases and Extended-Spectrum β-Lactamases-Encoding Genes in Clinical Isolates of Pseudomonas aeruginosa in Iran

Background: Pseudomonas aeruginosa is a unique Gram-negative opportunistic pathogen that is the leading cause of nosocomial infections. Objectives: This study aimed to investigate the prevalence of the main carbapenemase and extended-spectrum β-lactamases encoding genes in P. aeruginosa clinical isolates. Methods: In the present study, we collected 85 P. aeruginosa clinical isolates from different wards of three military hospitals in Tehran, Iran. We used disk diffusion and agar dilution methods to determine resistance to 12 different antibiotics in these isolates. Also, we assessed the blaIMP, blaVIM, blaSHV, blaTEM, and blaCTX genes by polymerase chain reaction methods among all isolates. Results: Our results revealed that all isolates were resistant to two antibiotics, and 76 (89.4%) of isolates were multidrug-resistant. We observed maximum and minimum resistance rates against ticarcillin (n = 77; 90.5%) and colistin (n = 7; 8.2%), respectively. The blaVIM, blaIPM, blaTEM, blaSHV, and blaCTX genes were harbored by 44 (51.8%), 20 (23.5%), 41 (48.2%), 24 (28.2%), and 16 (18.8%) isolates, respectively. Conclusions: The resistance rate among P. aeruginosa strains is significantly increasing that causes nosocomial infections due to different mechanisms, including the high frequency of metallo-β-lactamases and extended-spectrum β-lactamases genes.