Metagenomic perspectives on antibiotic resistance genes in tap water: The environmental characteristic, potential mobility and health threat.

As an emerging environmental contaminant, antibiotic resistance genes (ARGs) in tap water have attracted great attention. Although studies have provided ARG profiles in tap water, research on their abundance levels, composition characteristics, and potential threat is still insufficient. Here, 9 household tap water samples were collected from the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. Additionally, 75 sets of environmental sample data (9 types) were downloaded from the public database. Metagenomics was then performed to explore the differences in the abundance and composition of ARGs. 221 ARG subtypes consisting of 17 types were detected in tap water. Although the ARG abundance in tap water was not significantly different from that found in drinking water plants and reservoirs, their composition varied. In tap water samples, the three most abundant classes of resistance genes were multidrug, fosfomycin and MLS (macrolide-lincosamide-streptogramin) ARGs, and their corresponding subtypes ompR, fosX and macB were also the most abundant ARG subtypes. Regarding the potential mobility, vanS had the highest abundance on plasmids and viruses, but the absence of key genes rendered resistance to vancomycin ineffective. Generally, the majority of ARGs present in tap water were those that have not been assessed and are currently not listed as high-threat level ARG families based on the World Health Organization Guideline. Although the current potential threat to human health posed by ARGs in tap water is limited, with persistent transfer and accumulation, especially in pathogens, the potential danger to human health posed by ARGs should not be ignored.

Metagenome-wide characterization of shared antimicrobial resistance genes in sympatric people and lemurs in rural Madagascar.

Background: Tracking the spread of antibiotic resistant bacteria is critical to reduce global morbidity and mortality associated with human and animal infections. There is a need to understand the role that wild animals in maintenance and transfer of antibiotic resistance genes (ARGs). Methods: This study used metagenomics to identify and compare the abundance of bacterial species and ARGs detected in the gut microbiomes from sympatric humans and wild mouse lemurs in a forest-dominated, roadless region of Madagascar near Ranomafana National Park. We examined the contribution of human geographic location toward differences in ARG abundance and compared the genomic similarity of ARGs between host source microbiomes. Results: Alpha and beta diversity of species and ARGs between host sources were distinct but maintained a similar number of detectable ARG alleles. Humans were differentially more abundant for four distinct tetracycline resistance-associated genes compared to lemurs. There was no significant difference in human ARG diversity from different locations. Human and lemur microbiomes shared 14 distinct ARGs with highly conserved in nucleotide identity. Synteny of ARG-associated assemblies revealed a distinct multidrug-resistant gene cassette carrying dfrA1 and aadA1 present in human and lemur microbiomes without evidence of geographic overlap, suggesting that these resistance genes could be widespread in this ecosystem. Further investigation into intermediary processes that maintain drug-resistant bacteria in wildlife settings is needed.

When does antimicrobial resistance increase bacterial fitness? Effects of dosing, social interactions, and frequency dependence on the benefits of AmpC ß-lactamases in broth, biofilms, and a gut infection model.

One of the longstanding puzzles of antimicrobial resistance is why the frequency of resistance persists at intermediate levels. Theoretical explanations for the lack of fixation of resistance include cryptic costs of resistance or negative frequency-dependence but are seldom explored experimentally. ß-lactamases, which detoxify penicillin-related antibiotics, have well-characterized frequency-dependent dynamics driven by cheating and cooperation. However, bacterial physiology determines whether ß-lactamases are cooperative, and we know little about the sociality or fitness of ß-lactamase producers in infections. Moreover, media-based experiments constrain how we measure fitness and ignore important parameters such as infectivity and transmission among hosts. Here, we investigated the fitness effects of broad-spectrum AmpC ß-lactamases in Enterobacter cloacae in broth, biofilms, and gut infections in a model insect. We quantified frequency- and dose-dependent fitness using cefotaxime, a third-generation cephalosporin. We predicted that infection dynamics would be similar to those observed in biofilms, with social protection extending over a wide dose range. We found evidence for the sociality of ß-lactamases in all contexts with negative frequency-dependent selection, ensuring the persistence of wild-type bacteria, although cooperation was less prevalent in biofilms, contrary to predictions. While competitive fitness in gut infections and broth had similar dynamics, incorporating infectivity into measurements of fitness in infections significantly affected conclusions. Resistant bacteria had reduced infectivity, which limited the fitness benefits of resistance to infections challenged with low antibiotic doses and low initial frequencies of resistance. The fitness of resistant bacteria in more physiologically tolerant states (in biofilms, in infections) could be constrained by the presence of wild-type bacteria, high antibiotic doses, and limited availability of ß-lactamases. One conclusion is that increased tolerance of ß-lactams does not necessarily increase selection pressure for resistance. Overall, both cryptic fitness costs and frequency dependence curtailed the fitness benefits of resistance in this study.

Exceptions to the rule: When does resistance evolution not undermine antibiotic therapy in human bacterial infections?

The use of antibiotics to treat bacterial infections often imposes strong selection for antibiotic resistance. However, the prevalence of antibiotic resistance varies greatly across different combinations of pathogens and drugs. What underlies this variation? Systematic reviews, meta-analyses, and literature surveys capable of integrating data across many studies have tried to answer this question, but the vast majority of these studies have focused only on cases where resistance is common or problematic. Yet much could presumably be learned from the cases where resistance is infrequent or absent. Here we conducted a literature survey and a systematic review to study the evolution of antibiotic resistance across a wide range of pathogen-by-drug combinations (57 pathogens and 53 antibiotics from 15 drug classes). Using Akaike information criterion-based model selection and model-averaged parameter estimation we explored 14 different factors posited to be associated with resistance evolution. We find that the most robust predictors of high resistance are nosocomial transmission (i.e., hospital-acquired pathogens) and indirect transmission (e.g., vector-, water-, air-, or vehicle-borne pathogens). While the former was to be expected based on prior studies, the positive correlation between high resistance frequencies and indirect transmission is, to our knowledge, a novel insight. The most robust predictor of low resistance is zoonosis from wild animal reservoirs. We also found partial support that resistance was associated with pathogen type, horizontal gene transfer, commensalism, and human-to-human transmission. We did not find support for correlations between resistance and environmental reservoirs, mechanisms of drug action, and global drug use. This work explores the relative explanatory power of various pathogen and drug factors on resistance evolution, which is necessary to identify priority targets of stewardship efforts to slow the spread of drug-resistant pathogens.

Filamentous bacteria-induced sludge bulking can alter antibiotic resistance gene profiles and increase potential risks in wastewater treatment systems.

Sludge bulking caused by filamentous bacteria is a prevalent issue in wastewater treatment systems. While previous studies have primarily concentrated on controlling sludge bulking, the biological risks associated with it have been overlooked. This study demonstrates that excessive growth of filamentous bacteria during sludge bulking can significantly increase the abundance of antibiotic resistance genes (ARGs) in activated sludge. Through metagenomic analysis, we identified specific ARGs carried by filamentous bacteria, such as Sphaerotilus and Thiothrix, which are responsible for bulking. Additionally, by examining over 1,000 filamentous bacterial genomes, we discovered a diverse array of ARGs across different filamentous bacteria derived from wastewater treatment systems. Our findings indicate that 74.84% of the filamentous bacteria harbor at least one ARG, with the occurrence frequency of ARGs in these bacteria being approximately 1.5 times higher than that in the overall bacterial population in activated sludge. Furthermore, genomic and metagenomic analyses have shown that the ARGs in filamentous bacteria are closely linked to mobile genetic elements and are frequently found in potentially pathogenic bacteria, highlighting potential risks posed by these filamentous bacteria. These insights enhance our understanding of ARGs in activated sludge and underscore the importance of risk management in wastewater treatment systems.

Detection of the epidemic Pseudomonas aeruginosa AUST-03 (ST242) strain in people with cystic fibrosis in South Africa.

INTRODUCTION: Pseudomonas aeruginosa AUST-03 (ST242) has been reported to cause epidemics in people with CF (pwCF) from Australia and has been associated with multidrug resistance and increased morbidity and mortality. Here, we report an epidemic P. aeruginosa (AUST-03) strain in South African pwCF detected at a public hospital and characterize the genomic antibiotic resistance determinants. METHODS: The P. aeruginosa AUST-03 (ST242) study isolates were analysed with whole genome sequencing using the Illumina NextSeq2000 platform. Raw sequencing reads were processed using the Jekesa pipeline and multilocus sequence typing and genomic antibiotic resistance characterization was performed using public databases. Genetic relatedness between the study isolates and global P. aeruginosa ST242 from public databases was determined using a maximum-likelihood phylogenetic tree. Antibiotic susceptibility testing was performed using the disk diffusion and broth microdilution techniques. RESULTS: A total of 11 P. aeruginosa AUST-03 isolates were isolated from two children with CF. The majority (8/11) of these isolates were multidrug-resistant (MDR) or extensively drug resistant; and the multidrug efflux pumps MexAB-OprM, MexCD-OprJ, MexEF-OprN, and MexXY-OprM were the most clinically relevant antibiotic resistance determinants and were detected in all of the isolates. The study isolates were the most closely related to a 2020 P. aeruginosa AUST-03 (ST242) CF isolate from Russia. CONCLUSION: Epidemic MDR P. aeruginosa strains are present at South African public CF clinics and need to be considered when implementing segregation and infection control strategies to prevent possible spread and outbreaks.

The relationship between resistance evolution and carbon metabolism in Staphylococcus xylosus under ceftiofur sodium stress.

Staphylococcus xylosus has emerged as a bovine mastitis pathogen with increasing drug resistance, resulting in substantial economic impacts. This study utilized iTRAQ analysis to investigate the mechanisms driving resistance evolution in S. xylosus under ceftiofur sodium stress. Findings revealed notable variations in the expression of 143 proteins, particularly glycolysis-related proteins (TpiA, Eno, GlpD, Ldh) and peptidoglycan (PG) hydrolase Atl. Following the induction of ceftiofur sodium resistance in S. xylosus, the emergence of resistant strains displaying characteristics of small colony variants (SCVs) was observed. The transcript levels of TpiA, Eno, GlpD and Ldh were up-regulated, TCA cycle proteins (ICDH, MDH) and Atl were down-regulated, lactate content was increased, and NADH concentration was decreased in SCV compared to the wild strain. That indicates a potential role of carbon metabolism, specifically PG hydrolysis, glycolysis, and the TCA cycle, in the development of resistance to ceftiofur sodium in S. xylosus.

Self-Correcting Method for Highly Effective Office-Based Helicobacter pylori Therapy Using Cumulative Test of Cure Data.

BACKGROUND AND AIM: Helicobacter pylori infections have become resistant to many previously highly effective antimicrobial regimens resulting in clarithromycin, metronidazole, or fluoroquinolone-containing therapies becoming unsuccessful. Pretreatment susceptibility testing is only widely available in the United States but is still rarely done. Here, we propose a framework to monitor H. pylori eradication in small clinical settings by routinely assessing the effectiveness of therapy. METHODS: Because of the small sample size in individual practice's, we assume an acceptable cure rate of ≥80% (preferred cure rate ≥85%) in adherent patients, with a dichotomous outcome (cured vs. failed) and consecutive patient enrollment. To obtain results (feedback) in a timely manner, for individual practices, cure rates can be estimated after 10 patients. Large practices which acquire patients more rapidly can delay analysis until a total of 104 H. pylori-infected patients, assuming a baseline cure rate of at least 85% with the preferred regimen. RESULTS: We show how data from individual practices can be utilized to improve the effectiveness of H. pylori treatment decisions. The method consists of recording and accumulating the confirmation of cure data for successive small groups of patients. These data are then analyzed as binary outcomes (pass-fail) and serve as the basis for studying and improving the effectiveness of H. pylori treatment decisions. CONCLUSION: A simple actuarial method can serve outpatient clinics to ensure a reliable test-to-cure method and avoid futile Hp regimens.

Phytochemical characterisation of dichloromethane and methanolic extracts of the Ziziphora tenuior leaves and evaluation of their antioxidant and antibacterial activities.

Medicinal plants, known for their antibacterial phytocompounds and secondary metabolites, offer promising potential in combating antibiotic-resistant bacteria. This study aimed to perform a phytochemical analysis of the methanol and dichloromethane extracts obtained from Ziziphora tenuior leaves using GC-MS. Furthermore, the antioxidant activity of the extracts was evaluated through the DPPH assay. And, their antibacterial activity was assessed against S. aureus, E. coli, methicillin-resistant S. aureus, and vancomycin-resistant enterococcus (VRE) bacterial strains. Based on the results 90-92% of these extracts consisted of phytocompounds with pharmaceutical properties. Of these, 5-methyl- 2-(1-methylethylidele), Cyclohexanone (Pulegone; C10H16O) comprised the highest percentage of the extracts, constituting 62% of methanolic extract and 81% of dichloromethane extract. Also, both methanolic and dichloromethane extracts showed potent antioxidant activity with IC50 of 277.6 µg/ml and 49.6 µg/ml, respectively. Moreover, these extracts demonstrated considerable antibacterial activity against the tested pathogens, especially against S. aureus and VRE.

Extensively Antibiotic-Resistant Bacterial Infections in Trauma Cases Managed at the Médecins Sans Frontières Tertiary Orthopaedic Center in Mosul, Iraq: A Case Series.

The Médecins Sans Frontières Tertiary Orthopaedic Care center in Mosul, Iraq, provides reconstructive surgery, microbiological analysis, integrated infection prevention and control, and antibiotic stewardship services. Between May 2018 and February 2020, we recorded soft tissue and/or bone infections caused by gram-negative extensively drug-resistant (XDR) bacteria in 4.9% (13/266) of the admitted patients. The XDR bacteria identified among 12 patients in this case series were extended-spectrum ß-lactamase-producing Klebsiella pneumoniae (n = 5, 41.7%) with intermediate sensitivity or resistance to imipenem and/or meropenem, Acinetobacter spp (n = 3, 25.0%; 2 Acinetobacter baumannii strains) resistant to imipenem and/or meropenem, Pseudomonas aeruginosa (n = 2, 16.7%) resistant to imipenem and meropenem, and extended-spectrum ß-lactamase-producing Proteus mirabilis (n = 2, 16.7%) resistant to meropenem. Most XDR isolates were sensitive only to colistin or polymyxin B, neither of which is available in Iraq. Therefore, the only treatment option was multiple rounds of surgical debridement and wound care. The infection was deemed cured before discharge in 7 patients (58.3%). Meanwhile, 4 patients (33.3%) were discharged with unhealed wounds, and outpatient follow-up was planned. One patient died in the intensive care unit of a referral hospital after developing septicemia postsurgery. XDR bacteria pose substantial health risks in Iraq. Thus, improving antimicrobial stewardship and accessibility to essential antibiotics is critical to address this issue.

Genomic profiling of methicillin-sensitive Staphylococcus aureus (MSSA) isolates in Kuwait hospitals.

Background: Staphylococcus aureus is an important pathogen that causes mild to invasive infections in hospitals and the community. Although methicillin-susceptible Staphylococcus aureus (MSSA) isolates continue to cause different infections, there is no data on the genetic backgrounds of the MSSA colonizing or causing infections in Kuwait hospitals. This study aimed to investigate MSSA isolated from patients admitted to Kuwait hospitals for antibiotic resistance and genetic backgrounds to understand their clonal composition. Methods: Consecutive MSSA isolates were collected from single patients during two surveillance periods in 2016 and 2021 in 13 public hospitals. The isolates were characterized using antibiogram, staphylococcal protein A (spa) typing, DNA microarray analysis, and multilocus sequence typing (MLST) using standard protocols. Results: A total of 446 MSSA was cultured from different clinical samples in 2016 (n = 240) and 2021 (n = 206). All isolates were susceptible to vancomycin [minimum inhibitory concentration (MIC) ≤ 2 mg/L], teicoplanin (MIC ≤2 mg/L), linezolid (MIC ≤4 mg/L), ceftaroline (MIC ≤2 mg/L), rifampicin, and mupirocin but were resistant to erythromycin (21.3%), clindamycin (14.0%), gentamicin (3.8%), kanamycin (10.5%), fusidic acid (27.0%), tetracycline (6.9%), trimethoprim (23.1%), and ciprofloxacin (35.2%). Molecular typing identified 155 spa types, dominated by t127 (15.0%), t084 (5.4%), t3841 (5.4%), t267 (2.4%), t442 (2.2%), t091 (2.2%), t021 (2.2%), and t003 (2.2%); 31 clonal complexes (CCs); and 56 sequence types (STs). The majority of the isolates (n = 265; 59.4%) belonged to CC1 (20.6%), CC15 (10.9%), CC22 (5.1%), CC30 (7.6%), CC361 (10.1%), and CC398 (4.7%). Discussion: The MSSA isolates belonged to diverse genetic backgrounds dominated by CC1, CC15, CC22, CC30, CC361, and CC398. The distribution of MSSA clones in 2016 and 2021 showed the stability of these clones over time. The study provides the first comprehensive data on the clonal distribution of MSSA in Kuwait hospitals.

A trait-based ecological perspective on the soil microbial antibiotic-related genetic machinery.

Antibiotic resistance crisis dictates the need for resistance monitoring and the search for new antibiotics. The development of monitoring protocols is hindered by the great diversity of resistance factors, while the "streetlight effect" denies the possibility of discovering novel drugs based on existing databases. In this study, we address these challenges using high-throughput environmental screening viewed from a trait-based ecological perspective. Through an in-depth analysis of the metagenomes of 658 topsoil samples spanning Europe, we explored the distribution of 241 prokaryotic and fungal genes responsible for producing metabolites with antibiotic properties and 485 antibiotic resistance genes. We analyzed the diversity of these gene collections at different levels and modeled the distribution of each gene across environmental gradients. Our analyses revealed several nonparallel distribution patterns of the genes encoding sequential steps of enzymatic pathways synthesizing large antibiotic groups, pointing to gaps in existing databases and suggesting potential for discovering new analogues of known antibiotics. We show that agricultural activity caused a continental-scale homogenization of microbial antibiotic-related machinery, emphasizing the importance of maintaining indigenous ecosystems within the landscape mosaic. Based on the relationships between the proportion of the genes in the metagenomes with the main predictors (soil pH, land cover type, climate temperature and humidity), we illustrate how the properties of chemical structures dictate the distribution of the genes responsible for their synthesis across environments. With this understanding, we propose general principles to facilitate the discovery of antibiotics, including principally new ones, establish abundance baselines for antibiotic resistance genes, and predict their dissemination.

Horizontal plasmid transfer promotes antibiotic resistance in selected bacteria in Chinese frog farms.

The emergence and dissemination of antibiotic resistance genes (ARGs) in the ecosystem are global public health concerns. One Health emphasizes the interconnectivity between different habitats and seeks to optimize animal, human, and environmental health. However, information on the dissemination of antibiotic resistance genes (ARGs) within complex microbiomes in natural habitats is scarce. We investigated the prevalence of antibiotic resistant bacteria (ARB) and the spread of ARGs in intensive bullfrog (Rana catesbeiana) farms in the Shantou area of China. Antibiotic susceptibilities of 361 strains, combined with microbiome analyses, revealed Escherichia coli, Edwardsiella tarda, Citrobacter and Klebsiella sp. as prevalent multidrug resistant bacteria on these farms. Whole genome sequencing of 95 ARB identified 250 large plasmids that harbored a wide range of ARGs. Plasmid sequences and sediment metagenomes revealed an abundance of tetA, sul1, and aph(3″)-Ib ARGs. Notably, antibiotic resistance (against 15 antibiotics) highly correlated with plasmid-borne rather than chromosome-borne ARGs. Based on sequence similarities, most plasmids (62%) fell into 32 distinct groups, indicating a potential for horizontal plasmid transfer (HPT) within the frog farm microbiome. HPT was confirmed in inter- and intra-species conjugation experiments. Furthermore, identical mobile ARGs, flanked by mobile genetic elements (MGEs), were found in different locations on the same plasmid, or on different plasmids residing in the same or different hosts. Our results suggest a synergy between MGEs and HPT to facilitate ARGs dissemination in frog farms. Mining public databases retrieved similar plasmids from different bacterial species found in other environmental niches globally. Our findings underscore the importance of HPT in mediating the spread of ARGs in frog farms and other microbiomes of the ecosystem.

Strategies and mechanisms targeting Enterococcus faecalis biofilms associated with endodontic infections: a comprehensive review.

Enterococcus faecalis is one of the main microorganisms that infects root canals, ranking among the most prevalent microorganisms associated with endodontic treatment failure. Given its pervasive presence in persistent endodontic infections, the successful elimination of Enterococcus faecalis is crucial for effective endodontic treatment and retreatment. Furthermore, Enterococcus faecalis can form biofilms - defense structures that microbes use to fight environmental threats. These biofilms confer resistance against host immune system attacks and antibiotic interventions. Consequently, the presence of biofilms poses a significant challenge in the complete eradication of Enterococcus faecalis and its associated disease. In response, numerous scholars have discovered promising outcomes in addressing Enterococcus faecalis biofilms within root canals and undertaken endeavors to explore more efficacious approaches in combating these biofilms. This study provides a comprehensive review of strategies and mechanisms for the removal of Enterococcus faecalis biofilms.

A new type of Class C ß-lactamases defined by PIB-1. A metal-dependent carbapenem-hydrolyzing ß-lactamase, from Pseudomonas aeruginosa: Structural and functional analysis.

Antibiotic resistance is one of most important health concerns nowadays, and ß-lactamases are the most important resistance determinants. These enzymes, based on their structural and functional characteristics, are grouped in four categories (A, B, C and D). We have solved the structure of PIB-1, a Pseudomonas aeruginosa chromosomally-encoded ß-lactamase, in its apo form and in complex with meropenem and zinc. These crystal structures show that it belongs to the Class C ß-lactamase group, although it shows notable differences, especially in the Ω- and P2-loops, which are important for the enzymatic activity. Functional analysis showed that PIB-1 is able to degrade carbapenems but not cephalosporins, the typical substrate of Class C ß-lactamases, and that its catalytic activity increases in the presence of metal ions, especially zinc. They do not bind to the active-site but they induce the formation of trimers that show an increased capacity for the degradation of the antibiotics, suggesting that this oligomer is more active than the other oligomeric species. While PIB-1 is structurally a Class C ß-lactamase, the low sequence conservation, substrate profile and its metal-dependence, prompts us to position this enzyme as the founder of a new group inside the Class C ß-lactamases. Consequently, its diversity might be wider than expected.

From Data to Decisions: Leveraging Artificial Intelligence and Machine Learning in Combating Antimicrobial Resistance - a Comprehensive Review.

The emergence of drug-resistant bacteria poses a significant challenge to modern medicine. In response, Artificial Intelligence (AI) and Machine Learning (ML) algorithms have emerged as powerful tools for combating antimicrobial resistance (AMR). This review aims to explore the role of AI/ML in AMR management, with a focus on identifying pathogens, understanding resistance patterns, predicting treatment outcomes, and discovering new antibiotic agents. Recent advancements in AI/ML have enabled the efficient analysis of large datasets, facilitating the reliable prediction of AMR trends and treatment responses with minimal human intervention. ML algorithms can analyze genomic data to identify genetic markers associated with antibiotic resistance, enabling the development of targeted treatment strategies. Additionally, AI/ML techniques show promise in optimizing drug administration and developing alternatives to traditional antibiotics. By analyzing patient data and clinical outcomes, these technologies can assist healthcare providers in diagnosing infections, evaluating their severity, and selecting appropriate antimicrobial therapies. While integration of AI/ML in clinical settings is still in its infancy, advancements in data quality and algorithm development suggest that widespread clinical adoption is forthcoming. In conclusion, AI/ML holds significant promise for improving AMR management and treatment outcome.

Molecular detection of extended-spectrum ß-lactamase- and carbapenemase-producing Klebsiella pneumoniae isolates in southwest Iran.

OBJECTIVE: The global emergence of carbapenem-resistant Klebsiella pneumoniae is considered a significant contemporary concern., as carbapenems are the last resort for treating infections caused by multidrug-resistant Gram-negative bacteria. This study aimed to investigate the carbapenem-resistance genes in extended-spectrum ß-lactamase producing K. pneumoniae isolates. METHODS: Seventy-five non-duplicate clinical K. pneumoniae strains were isolated from urine, blood, sputum, and wound samples. Antimicrobial susceptibility tests for 12 different antibiotics were performed using the disk diffusion method, followed by determining minimum inhibitory concentrations of imipenem and meropenem. Phenotypic detection of extended-spectrum ß-lactamase and carbapenemase enzymes was performed by double-disc synergy test and modified Hodge test, respectively. PCR assay further investigated resistant isolates for extended-spectrum ß-lactamase and carbapenemase-encoding genes. RESULTS: The highest and lowest resistance rates were observed against ampicillin (93.3%) and tigecycline (9.3%). According to phenotypic tests, 46.7% of isolates were positive for extended-spectrum ß-lactamase enzymes and 52.8% for carbapenemase. A total of 11 isolates contained carbapenemase genes, with blaOXA-48 (19.4%; 7/36) being the predominant gene, followed by blaNDM (8.3%; 3/36). CONCLUSION: The study's findings reveal the alarming prevalence of beta-lactamase enzymes in K. pneumoniae strains. Early detection of carbapenem-resistant isolates and effective infection control measures are necessary to minimise further spread, as carbapenem resistance has become a public health concern.

Combatting Antibiotic Resistance: Identifying Gaps in Knowledge, Attitude, and Practice Among Medical Interns.

INTRODUCTION: Antibiotic resistance presents a significant global health threat to modern medicine. The awareness and attitude of future doctors undergoing training may play a crucial role in addressing this important issue, influencing the control of resistance and promoting responsible antibiotic stewardship. This study aimed to estimate knowledge, attitudes, and practices regarding antibiotic usage and antimicrobial resistance among tertiary care teaching hospital medical interns. METHODOLOGY: The questionnaire-based cross-sectional study was conducted on 123 MBBS interns from multiple medical institutions. Intern's knowledge, attitudes, and self-reported practices regarding antibiotic use were recorded. RESULTS: Based on survey responses from 123 participants, 116 (94.31%) were aware of the adverse effects of indiscriminate antibiotic use, recognizing the risks of ineffective treatment, increased adverse effects, prolonged illness, bacterial resistance, and higher medical costs. Most (106, 86.18%) acknowledged the challenges of treating antibiotic-resistant infections, and 69 (56.10%) correctly identified that bacteria are not a cause of the common cold and flu. Most (115, 93.5%) recognized antibiotic resistance as a significant global health problem. In attitude, 90 (73%) believed antibiotics should be avoided for colds, but 80 (65%) thought they hastened fever recovery. Only 48 (39%) recognized that antibiotics contribute to resistance, while 102 (83%) agreed skipping doses fosters resistance. Most support hospital policies (118, 96%) and curriculum courses (112, 91%) for rational antibiotic use. Regarding practice, 12 (9.76%) interns admitted to overusing antibiotics, 68 (55.28%) consulted a doctor before starting antibiotics, and 87 (70.73%) checked expiry dates. Additionally, 62 (50.41%) preferred antibiotics for cough and sore throat symptoms. CONCLUSIONS: The study highlights that while interns have a good knowledge and awareness of the harms of antibiotic misuse, they are not translating this knowledge into practice. This indicates a disconnect between understanding and application. Therefore, there is a need to add a rational antibiotic prescription and stewardship module to the medical curriculum to ensure that knowledge is effectively translated into changing beliefs and practices.

Priestia flexa as a Novel Urinary Tract Pathogen in Daloa, Côte d'Ivoire: Insights From Genomic Sequencing.

Bacterial strains coded 21LM367, 21LM07, and 21LM1136 were isolated from the urine of patients with urinary tract infections (UTIs) at the Centre Hospitalier Régional de Daloa in Côte d'Ivoire. Based on average nucleotide identity (ANI) analysis, DNA-DNA digital hybridisation (dDDH), and other comparative genomic methods, strains 21LM07, 21LM367, and 21LM1136 were determined to be Priestia flexa. The size of the assembled complete genomes ranged from 8,624,538 to 4,007,501 bp. The average GC content was 37.76%, 46.33%, and 43.03% for strains 21LM07, 21LM367, and 21LM1136, respectively. The total number of coding regions (CDS) in each genome was 4172, 8497, and 6795, respectively, for strains 21LM07, 21LM367, and 21LM1136. Genomic prediction analysis revealed that a total of 4241, 8583, and 6881 genes were annotated in the 21LM07, 21LM367, and 21LM1136 genomes, respectively. No virulence or resistance genes were predicted in the genomes of strains 21LM07 and 21LM1136. On the other hand, two genes conferring resistance to beta-lactam and tetracyclines as well as nine virulence genes were predicted in the genome of 21LM367. In addition, 438, 350, and 153 mobile genetic elements (MGEs) were predicted in the genomes of strains 21LM367, 21LM1136, and 21LM07, respectively. Strain 21LM07 was characterised by the absence of plasmids in its genome. Two plasmids were predicted in the genomes of isolates 21LM367 and 21LM1136; however, rep7a and IncI2 were predicted to contain the tet(K) resistance gene. No typical multilocus sequences could be characterised in the genomes of the different strains.