Genetic Diversity, Distribution, and Genomic Characterization of Antibiotic Resistance and Virulence of Clinical Pseudomonas aeruginosa Strains in Kenya

Diagnosis and Therapeutic Strategies Based on Nucleic Acid Aptamers Selected against Pseudomonas aeruginosa: The Challenge of Cystic Fibrosis

Antimicrobial resistance (AMR) is a rapidly spreading global health problem, and approximately five million deaths associated with AMR pathogens were identified prior to the COVID-19 pandemic. Pseudomonas aeruginosa has developed increasing AMR, and in patients with cystic fibrosis (CF) colonized by this bacterium, rare phenotypes have emerged that complicate the diagnosis and treatment of the hosts, in addition to multiple associated "epidemic strains" with high morbidities and mortalities. The conjugation of aptamers with fluorochromes or nanostructures has allowed the design of new identification strategies for Pseudomonas aeruginosa with detection limits of up to 1 cell ⋅ mL-1 , and the synergy of aptamers with antibiotics, antimicrobial peptides and nanostructures has exhibited promising therapeutic qualities. Some selected aptamers against this bacterium have shown intrinsic antimicrobial activity. However, these aptamers have been poorly evaluated in clinical isolates and have shown decreased interactions for CF isolates, demonstrating, in these cases, uncommon phenotypes resulting from the selective qualities of this disease as well as the great adaptive capacity of the pathogen. Therefore, finding an aptamer or set of aptamers that have the ability to recognize strange phenotypes of this bacillus is crucial in the battle against AMR.

Machine learning identification of Pseudomonas aeruginosa strains from colony image data

When grown on agar surfaces, microbes can produce distinct multicellular spatial structures called colonies, which contain characteristic sizes, shapes, edges, textures, and degrees of opacity and color. For over one hundred years, researchers have used these morphology cues to classify bacteria and guide more targeted treatment of pathogens. Advances in genome sequencing technology have revolutionized our ability to classify bacterial isolates and while genomic methods are in the ascendancy, morphological characterization of bacterial species has made a resurgence due to increased computing capacities and widespread application of machine learning tools. In this paper, we revisit the topic of colony morphotype on the within-species scale and apply concepts from image processing, computer vision, and deep learning to a dataset of 69 environmental and clinical Pseudomonas aeruginosa strains. We find that colony morphology and complexity under common laboratory conditions is a robust, repeatable phenotype on the level of individual strains, and therefore forms a potential basis for strain classification. We then use a deep convolutional neural network approach with a combination of data augmentation and transfer learning to overcome the typical data starvation problem in biological applications of deep learning. Using a train/validation/test split, our results achieve an average validation accuracy of 92.9% and an average test accuracy of 90.7% for the classification of individual strains. These results indicate that bacterial strains have characteristic visual 'fingerprints' that can serve as the basis of classification on a sub-species level. Our work illustrates the potential of image-based classification of bacterial pathogens and highlights the potential to use similar approaches to predict medically relevant strain characteristics like antibiotic resistance and virulence from colony data.

Spread of Pseudomonas aeruginosa ST274 Clone in Different Niches: Resistome, Virulome, and Phylogenetic Relationship

Pseudomonas aeruginosa ST274 is an international epidemic high-risk clone, mostly associated with hospital settings and appears to colonize cystic fibrosis (CF) patients worldwide. To understand the relevant mechanisms for its success, the biological and genomic characteristics of 11 ST274-P. aeruginosa strains from clinical and non-clinical origins were analyzed. The extensively drug-resistant (XDR/DTR), the non-susceptible to at least one agent (modR), and the lasR-truncated (by ISPsp7) strains showed a chronic infection phenotype characterized by loss of serotype-specific antigenicity and low motility. Furthermore, the XDR/DTR and modR strains presented low pigment production and biofilm formation, which were very high in the lasR-truncated strain. Their whole genome sequences were compared with other 14 ST274-P. aeruginosa genomes available in the NCBI database, and certain associations have been primarily detected: blaOXA-486 and blaPDC-24 genes, serotype O:3, exoS+/exoU- genotype, group V of type IV pili, and pyoverdine locus class II. Other general molecular markers highlight the absence of vqsM and pldA/tleS genes and the presence of the same mutational pattern in genes involving two-component sensor-regulator systems PmrAB and CreBD, exotoxin A, quorum-sensing RhlI, beta-lactamase expression regulator AmpD, PBP1A, or FusA2 elongation factor G. The proportionated ST274-P. aeruginosa results could serve as the basis for more specific studies focused on better antibiotic stewardship and new therapeutic developments.

Endemic High-Risk Clone ST277 Is Related to the Spread of SPM-1-Producing Pseudomonas aeruginosa during the COVID-19 Pandemic Period in Northern Brazil

Pseudomonas aeruginosa is a high-priority bacterial agent that causes healthcare-acquired infections (HAIs), which often leads to serious infections and poor prognosis in vulnerable patients. Its increasing resistance to antimicrobials, associated with SPM production, is a case of public health concern. Therefore, this study aims to determine the antimicrobial resistance, virulence, and genotyping features of P. aeruginosa strains producing SPM-1 in the Northern region of Brazil. To determine the presence of virulence and resistance genes, the PCR technique was used. For the susceptibility profile of antimicrobials, the Kirby-Bauer disk diffusion method was performed on Mueller-Hinton agar. The MLST technique was used to define the ST of the isolates. The exoS+/exoU- virulotype was standard for all strains, with the aprA, lasA, toxA, exoS, exoT, and exoY genes as the most prevalent. All the isolates showed an MDR or XDR profile against the six classes of antimicrobials tested. HRC ST277 played a major role in spreading the SPM-1-producing P. aeruginosa strains.

Enhancing capacity for national genomics surveillance of antimicrobial resistance in public health laboratories in Kenya

Genomic surveillance is vital for detecting outbreaks and understanding the epidemiology and transmission of bacterial strains, yet it is not integrated into many national antimicrobial resistance (AMR) surveillance programmes. Key factors are that few scientists in the public health sector are trained in bacterial genomics, and the diverse sequencing platforms and bioinformatic tools make it challenging to generate reproducible outputs. In Kenya, these gaps were addressed by training public health scientists to conduct genomic surveillance on isolates from the national AMR surveillance repository and produce harmonized reports. The 2-week training combined theory and laboratory and bioinformatic experiences with Klebsiella pneumoniae isolates from the surveillance repository. Whole-genome sequences generated on Illumina and Nanopore sequencers were analysed using publicly available bioinformatic tools, and a harmonized report was generated using the HAMRonization tool. Pre- and post-training tests and self-assessments were used to assess the effectiveness of the training. Thirteen scientists were trained and generated data on the K. pneumoniae isolates, summarizing the AMR genes present consistently with the reported phenotypes and identifying the plasmid replicons that could transmit antibiotic resistance. Ninety per cent of the participants demonstrated an overall improvement in their post-training test scores, with an average increase of 14 %. Critical challenges were experienced in delayed delivery of equipment and supplies, power fluctuations and internet connections that were inadequate for bioinformatic analysis. Despite this, the training built the knowledge and skills to implement bacterial genomic surveillance. More advanced and immersive training experiences and building supporting infrastructure would solidify these gains to produce tangible public health outcomes.

Antimicrobial Resistance, Genetic Lineages, and Biofilm Formation in Pseudomonas aeruginosa Isolated from Human Infections: An Emerging One Health Concern

Pseudomonas aeruginosa (PA) is a leading nosocomial pathogen and has great versatility due to a complex interplay between antimicrobial resistance and virulence factors. PA has also turned into one the most relevant model organisms for the study of biofilm-associated infections. The objective of the study focused on analyzing the antimicrobial susceptibility, resistance genes, virulence factors, and biofilm formation ability of thirty-two isolates of PA. PA isolates were characterized by the following analyses: susceptibility to 12 antimicrobial agents, the presence of resistance genes and virulence factors in PCR assays, and the quantification of biofilm production as evaluated by two distinct assays. Selected PA isolates were analyzed through multilocus sequence typing (MLST). Thirty PA isolates have a multi-resistant phenotype, and most of the isolates showed high levels of resistance to the tested antibiotics. Carbapenems showed the highest prevalence of resistance. Various virulence factors were detected and, for the quantification of biofilm production, the effectiveness of different methods was assessed. The microtiter plate method showed the highest accuracy and reproducibility for detecting biofilm-producing bacteria. MLST revealed four distinct sequence types (STs) in clinical PA, with three of them considered high-risk clones of PA, namely ST175, ST235, and ST244. These clones are associated with multidrug resistance and are prevalent in hospitals worldwide. Overall, the study highlights the high prevalence of antibiotic resistance, the presence of carbapenemase genes, the diversity of virulence factors, and the importance of biofilm formation in PA clinical isolates. Understanding these factors is crucial for effective infection control measures and the development of targeted treatment strategies.

Multi-Drug Resistance in Bacterial Genomes-A Comprehensive Bioinformatic Analysis

Antimicrobial resistance is presently one of the greatest threats to public health. The excessive and indiscriminate use of antibiotics imposes a continuous selective pressure that triggers the emergence of multi-drug resistance. We performed a large-scale analysis of closed bacterial genomes to identify multi-drug resistance considering the ResFinder antimicrobial classes. We found that more than 95% of the genomes harbor genes associated with resistance to disinfectants, glycopeptides, macrolides, and tetracyclines. On average, each genome encodes resistance to more than nine different classes of antimicrobial drugs. We found higher-than-expected co-occurrences of resistance genes in both plasmids and chromosomes for several classes of antibiotic resistance, including classes categorized as critical according to the World Health Organization (WHO). As a result of antibiotic-resistant priority pathogens, higher-than-expected co-occurrences appear in plasmids, increasing the potential for resistance dissemination. For the first time, co-occurrences of antibiotic resistance have been investigated for priority pathogens as defined by the WHO. For critically important pathogens, co-occurrences appear in plasmids, not in chromosomes, suggesting that the resistances may be epidemic and probably recent. These results hint at the need for new approaches to treating infections caused by critically important bacteria.

Abundant diversity of accessory genetic elements and associated antimicrobial resistance genes in pseudomonas aeruginosa isolates from a single Chinese hospital

OBJECTIVES

Pseudomonas aeruginosa has intrinsic antibiotic resistance and the strong ability to acquire additional resistance genes. However, a limited number of investigations provide detailed modular structure dissection and evolutionary analysis of accessory genetic elements (AGEs) and associated resistance genes (ARGs) in P. aeruginosa isolates. The objective of this study is to reveal the prevalence and transmission characteristics of ARGs by epidemiological investigation and bioinformatics analysis of AGEs of P. aeruginosa isolates taken from a Chinese hospital.

METHODS

Draft-genome sequencing was conducted for P. aeruginosa clinical isolates (n = 48) collected from a single Chinese hospital between 2019 and 2021. The clones of P. aeruginosa isolates, type 3 secretion system (T3SS)-related virulotypes, and the resistance spectrum were identified using multilocus sequence typing (MLST), polymerase chain reaction (PCR), and antimicrobial susceptibility tests. In addition, 17 of the 48 isolates were fully sequenced. An extensive modular structure dissection and genetic comparison was applied to AGEs of the 17 sequenced P. aeruginosa isolates.

RESULTS

From the draft-genome sequencing, 13 STs were identified, showing high genetic diversity. BLAST search and PCR detection of T3SS genes (exoT, exoY, exoS, and exoU) revealed that the exoS+/exoU- virulotype dominated. At least 69 kinds of acquired ARGs, involved in resistance to 10 different categories of antimicrobials, were identified in the 48 P. aeruginosa isolates. Detailed genetic dissection and sequence comparisons were applied to 25 AGEs from the 17 isolates, together with five additional prototype AGEs from GenBank. These 30 AGEs were classified into five groups -- integrative and conjugative elements (ICEs), unit transposons, Inc_pPBL16 plasmids, Inc_p60512-IMP plasmids, and Inc_pPA7790 plasmids.

CONCLUSION

This study provides a broad-scale and deeper genomics understanding of P. aeruginosa isolates taken from a single Chinese hospital. The isolates collected are characterized by high genetic diversity, high virulence, and multiple drug resistance. The AGEs in P. aeruginosa chromosomes and plasmids, as important genetic platforms for the spread of ARGs, contribute to enhancing the adaptability of P. aeruginosa in hospital settings.

The Intriguing Carbapenemases of Pseudomonas aeruginosa: Current Status, Genetic Profile, and Global Epidemiology

Worldwide, Pseudomonas aeruginosa remains a leading nosocomial pathogen that is difficult to treat and constitutes a challenging menace to healthcare systems. P. aeruginosa shows increased and alarming resistance to carbapenems, long acknowledged as last-resort antibiotics for treatment of resistant infections. Varied and recalcitrant pathways of resistance to carbapenems can simultaneously occur in P. aeruginosa, including the production of carbapenemases, broadest spectrum types of β-lactamases that hydrolyze virtually almost all β-lactams, including carbapenems. The organism can produce chromosomal, plasmid-encoded, and integron- or transposon-mediated carbapenemases from different molecular classes. These include Ambler class A (KPC and some types of GES enzymes), class B (different metallo-β-lactamases such as IMP, VIM, and NDM), and class D (oxacillinases with carbapenem-hydrolyzing capacity like OXA-198) enzymes. Additionally, derepression of chromosomal AmpC cephalosporinases in P. aeruginosa contributes to carbapenem resistance in the presence of other concomitant mechanisms such as impermeability or efflux overexpression. Epidemiologic and molecular evidence of carbapenemases in P. aeruginosa has been long accumulating, and reports of their existence in different geographical areas of the world currently exist. Such reports are continuously being updated and reveal emerging varieties of carbapenemases and/or new genetic environments. This review summarizes carbapenemases of importance in P. aeruginosa, highlights their genetic profile, and presents current knowledge about their global epidemiology.

Antimicrobial Resistance Rates and Surveillance in Sub-Saharan Africa: Where Are We Now?

Introduction

Although antimicrobials have traditionally been used to treat infections and improve health outcomes, resistance to commonly used antimicrobials has posed a major challenge. An estimated 700,000 deaths occur globally every year as a result of infections caused by antimicrobial-resistant pathogens. Antimicrobial resistance (AMR) also contributes directly to the decline in the global economy. In 2019, sub-Saharan Africa (SSA) had the highest mortality rate (23.5 deaths per 100,000) attributable to AMR compared to other regions.

Methods

We searched PubMed for articles relevant to AMR in pathogens in the WHO-GLASS list and in other infections of local importance in SSA. In this review, we focused on AMR rates and surveillance of AMR for these priority pathogens and some of the most encountered pathogens of public health significance. In addition, we reviewed the implementation of national action plans to mitigate against AMR in countries in SSA.

Results and Discussion

The SSA region is disproportionately affected by AMR, in part owing to the prevailing high levels of poverty, which result in a high burden of infectious diseases, poor regulation of antimicrobial use, and a lack of alternatives to ineffective antimicrobials. The global action plan as a strategy for prevention and combating AMR has been adopted by most countries, but fewer countries are able to fully implement country-specific action plans, and several challenges exist in many settings.

Conclusion

A concerted One Health approach will be required to ramp up implementation of action plans in the region. In addition to AMR surveillance, effective implementation of infection prevention and control, water, sanitation, and hygiene, and antimicrobial stewardship programs will be key cost-effective strategies in helping to tackle AMR.

Are Virulence and Antibiotic Resistance Genes Linked? A Comprehensive Analysis of Bacterial Chromosomes and Plasmids

Although pathogenic bacteria are the targets of antibiotics, these drugs also affect hundreds of commensal or mutualistic species. Moreover, the use of antibiotics is not only restricted to the treatment of infections but is also largely applied in agriculture and in prophylaxis. During this work, we tested the hypothesis that there is a correlation between the number and the genomic location of antibiotic resistance (AR) genes and virulence factor (VF) genes. We performed a comprehensive study of 16,632 reference bacterial genomes in which we identified and counted all orthologues of AR and VF genes in each of the locations: chromosomes, plasmids, or in both locations of the same genome. We found that, on a global scale, no correlation emerges. However, some categories of AR and VF genes co-occur preferentially, and in the mobilome, which supports the hypothesis that some bacterial pathogens are under selective pressure to be resistant to specific antibiotics, a fact that can jeopardize antimicrobial therapy for some human-threatening diseases.

Methylene Blue-Mediated Antimicrobial ​Photodynamic Therapy Against Clinical Isolates of Extensively Drug Resistant ​Gram-Negative Bacteria Causing Nosocomial Infections in Thailand, An In Vitro Study

BACKGROUND/PURPOSE

Some multidrug-resistant gram-negative bacteria as a global threat have been recently prioritized for research and development of new treatments. We studied the efficacy of methylene blue-mediated antimicrobial photodynamic therapy (MB-aPDT) for the reduction of extensively drug-resistant Acinetobacter baumannii (XDR-AB) and Pseudomonas aeruginosa (XDR-PS) and multidrug-resistant Klebsiella pneumoniae (MDR-KP) isolated in a university hospital setting in Thailand.

METHOD

Two isolates of each selected bacterium were collected, XDR-AB1 and AB2, XDR- PS1 and PS2, and MDR-KP1 and KP2. Three triplicate experiments using various MB concentrations alone, various red light fluences alone, as well as the selected non-toxic doses of MB and fluences of red light combined as MB-aPDT were applied on each selected isolate. The colonies were counted [colony forming units (CFU)/ml]. Estimation of the lethal treatment dose defined as reduction of > 2 log₁₀ in CFU/ml compared with untreated bacteria.

RESULT

There were generally negligible changes in the viable counts of the bacterial suspensions treated with all the MB concentrations (p > 0.05). In the second experiment with the only red light treatments, at fluences higher than 2 J/cm, reduction trend in viable counts across all the isolates was observed. Only for MDR-KP1, however, the lethal dose was achieved with the highest fluence of red light (80 J/cm). With the concentration of MB, 50 and 150 mg/L in the third experiment (MB-aPDT), the greater bacterial reduction was observed in all clinical isolates leading to their lethal viable cell reduction when escalating the light fluence to 80 J/cm.

CONCLUSIONS

MB-aPDT evidently killed the selected XDR and MDR-gram negative bacteria. In highly drug-resistant crisis era, MB-aPDT could be a promising option, particularly for local infections and infection complicating chronic wounds.