Sequencing Methods to Study the Microbiome with Antibiotic Resistance Genes in Patients with Pulmonary Infections. - Related Documents




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582001.0000Sequencing Methods to Study the Microbiome with Antibiotic Resistance Genes in Patients with Pulmonary Infections. Various antibiotic-resistant bacteria (ARB) are known to induce repeated pulmonary infections and increase morbidity and mortality. A thorough knowledge of antibiotic resistance is imperative for clinical practice to treat resistant pulmonary infections. In this study, we used a reads-based method and an assembly-based method according to the metagenomic next-generation sequencing (mNGS) data to reveal the spectra of ARB and corresponding antibiotic resistance genes (ARGs) in samples from patients with pulmonary infections. A total of 151 clinical samples from 144 patients with pulmonary infections were collected for retrospective analysis. The ARB and ARGs detection performance was compared by the reads-based method and assembly-based method with the culture method and antibiotic susceptibility testing (AST), respectively. In addition, ARGs and the attribution relationship of common ARB were analyzed by the two methods. The comparison results showed that the assembly-based method could assist in determining pathogens detected by the reads-based method as true ARB and improve the predictive capabilities (46% > 13%). ARG-ARB network analysis revealed that assembly-based method could promote determining clear ARG-bacteria attribution and 101 ARGs were detected both in two methods. 25 ARB were obtained by both methods, of which the most predominant ARB and its ARGs in the samples of pulmonary infections were Acinetobacter baumannii (ade), Pseudomonas aeruginosa (mex), Klebsiella pneumoniae (emr), and Stenotrophomonas maltophilia (sme). Collectively, our findings demonstrated that the assembly-based method could be a supplement to the reads-based method and uncovered pulmonary infection-associated ARB and ARGs as potential antibiotic treatment targets.202439113195
568710.9998The effect of short-course antibiotics on the resistance profile of colonizing gut bacteria in the ICU: a prospective cohort study. BACKGROUND: The need for early antibiotics in the intensive care unit (ICU) is often balanced against the goal of antibiotic stewardship. Long-course antibiotics increase the burden of antimicrobial resistance within colonizing gut bacteria, but the dynamics of this process are not fully understood. We sought to determine how short-course antibiotics affect the antimicrobial resistance phenotype and genotype of colonizing gut bacteria in the ICU by performing a prospective cohort study with assessments of resistance at ICU admission and exactly 72 h later. METHODS: Deep rectal swabs were performed on 48 adults at the time of ICU admission and exactly 72 h later, including patients who did and did not receive antibiotics. To determine resistance phenotype, rectal swabs were cultured for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE). In addition, Gram-negative bacterial isolates were cultured against relevant antibiotics. To determine resistance genotype, quantitative PCR (qPCR) was performed from rectal swabs for 87 established resistance genes. Within-individual changes in antimicrobial resistance were calculated based on culture and qPCR results and correlated with exposure to relevant antibiotics (e.g., did β-lactam antibiotic exposure associate with a detectable change in β-lactam resistance over this 72-h period?). RESULTS: Of 48 ICU patients, 41 (85%) received antibiotics. Overall, there was no increase in the antimicrobial resistance profile of colonizing gut bacteria during the 72-h study period. There was also no increase in antimicrobial resistance after stratification by receipt of antibiotics (i.e., no detectable increase in β-lactam, vancomycin, or macrolide resistance regardless of whether patients received those same antibiotics). This was true for both culture and PCR. Antimicrobial resistance pattern at ICU admission strongly predicted resistance pattern after 72 h. CONCLUSIONS: Short-course ICU antibiotics made little detectable difference in the antimicrobial resistance pattern of colonizing gut bacteria over 72 h in the ICU. This provides an improved understanding of the dynamics of antimicrobial resistance in the ICU and some reassurance that short-course antibiotics may not adversely impact the stewardship goal of reducing antimicrobial resistance.202032646458
582120.9998Direct 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.202438903781
567330.9998Antimicrobial 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.202337627668
258040.9998Insights into the Microbiome and Antibiotic Resistance Genes from Hospital Environmental Surfaces: A Prime Source of Antimicrobial Resistance. Hospital environmental surfaces are potential reservoirs for transmitting hospital-associated pathogens. This study aimed to profile microbiomes and antibiotic resistance genes (ARGs) from hospital environmental surfaces using 16S rRNA amplicon and metagenomic sequencing at a tertiary teaching hospital in Malaysia. Samples were collected from patient sinks and healthcare staff counters at surgery and orthopaedic wards. The samples' DNA were subjected to 16S rRNA amplicon and shotgun sequencing to identify bacterial taxonomic profiles, antibiotic resistance genes, and virulence factor pathways. The bacterial richness was more diverse in the samples collected from patient sinks than those collected from staff counters. Proteobacteria and Verrucomicrobia dominated at the phylum level, while Bacillus, Staphylococcus, Pseudomonas, and Acinetobacter dominated at the genus level. Staphylococcus epidermidis and Staphylococcus aureus were prevalent on sinks while Bacillus cereus dominated the counter samples. The highest counts of ARGs to beta-lactam were detected, followed by ARGs against fosfomycin and cephalosporin. We report the detection of mcr-10.1 that confers resistance to colistin at a hospital setting in Malaysia. The virulence gene pathways that aid in antibiotic resistance gene transfer between bacteria were identified. Environmental surfaces serve as potential reservoirs for nosocomial infections and require mitigation strategies to control the spread of antibiotic resistance bacteria.202438391513
531350.9997Treated wastewater: A hotspot for multidrug- and colistin-resistant Klebsiella pneumoniae. Wastewater treatment plants are hotspots for the release of antimicrobial resistant pathogenic bacteria into aquatic ecosystems, significantly contributing to the cycle of antimicrobial resistance. Special attention should be paid to antimicrobial resistant ESKAPE bacteria, which have been identified as high-priority targets for control measures. Among them, Klebsiella pneumoniae is particularly noteworthy. In this study, we collected wastewater samples from the inlet, sedimentation tank, and effluent water of a wastewater treatment plant in June, July, October, and November of 2018. We detected and characterized 42 K. pneumoniae strains using whole genome sequencing (15 from the inlet, 8 from the sedimentation tank, and 19 from the effluent). Additionally, the strains were tested for their antimicrobial resistance phenotype. Using whole genome sequencing no distinct patterns were observed in terms of their genetic profiles. All strains were resistant to tetracycline, meanwhile 60%, 47%, and 37.5% of strains isolated from the inlet, sedimentation tank, and effluent, respectively, were multidrug resistant. Some of the multidrug resistant isolates were also resistant to colistin, and nearly all tested positive for the eptB and arnT genes, which are associated with polymyxin resistance. Various antimicrobial resistance genes were linked to mobile genetic elements, and they did not correlate with detected virulence groups or defense systems. Overall, our results, although not quantitative, highlight that multidrug resistant K. pneumoniae strains, including those resistant to colistin and genetically unrelated, being discharged into aquatic ecosystems from wastewater treatment plants. This suggests the necessity of monitoring aimed at genetically characterizing these pathogenic bacteria.202439053799
224760.9997Metagenomic identification of pathogens and antimicrobial-resistant genes in bacterial positive blood cultures by nanopore sequencing. Nanopore sequencing workflows have attracted increasing attention owing to their fast, real-time, and convenient portability. Positive blood culture samples were collected from patients with bacterial bloodstream infection and tested by nanopore sequencing. This study compared the sequencing results for pathogen taxonomic profiling and antimicrobial resistance genes to those of species identification and phenotypic drug susceptibility using traditional microbiology testing. A total of 37 bacterial positive blood culture results of strain genotyping by nanopore sequencing were consistent with those of mass spectrometry. Among them, one mixed infection of bacteria and fungi was identified using nanopore sequencing and confirmatory quantitative polymerase chain reaction. The amount of sequencing data was 21.89 ± 8.46 MB for species identification, and 1.0 MB microbial strain data enabled accurate determination. Data volumes greater than or equal to 94.6 MB nearly covered all the antimicrobial resistance genes of the bacteria in our study. In addition, the results of the antimicrobial resistance genes were compared with those of phenotypic drug susceptibility testing for Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus. Therefore, the nanopore sequencing platform for rapid identification of causing pathogens and relevant antimicrobial resistance genes complementary to conventional blood culture outcomes may optimize antimicrobial stewardship management for patients with bacterial bloodstream infection.202338192400
567470.9997Evaluation of Resistance by Clinically Pathogenic Bacteria to Antimicrobials and Common Disinfectants in Beijing, China. BACKGROUND: Antibiotic resistance of pathogenic bacteria is well recognized among clinicians; however, studies that directly evaluate the bacterial resistance to commonly used disinfectants in clinical settings are lacking. Currently available reports focus on the resistance of single strains to single disinfectants and do not adequately examine the degree of resistance and cross-resistance to antimicrobials in the large-scale clinical use of disinfectants. METHODS: We investigated the resistance capacity to 11 antibiotics and 7 chemical disinfectants by bacterial strains collected from body fluids of patients in 10 hospitals in Beijing, China over a 1-year period. Bacterial resistance to disinfectants was tested using minimum inhibitory concentration and minimum bactericidal concentration using agar dilution methods based on commercially available reference strains. RESULTS: A total of 1,104 pathogenic strains were identified, of which 23% were Gram-positive bacteria, 74% were Gram-negative bacteria, and 3% were fungi. Overall, resistance to antibiotics for the most common strains was significantly higher than their resistance to disinfectants. The least effective antibiotics and disinfectants were aztreonam and glutaral, respectively, exhibiting the highest overall resistance rates; while amikacin and alcohol had the lowest resistance rates. Consistently, Acinetobacter baumannii exhibited the most resistance, while Escherichia coli had the least resistance for both antibiotics and disinfectants. CONCLUSIONS: Based on the pathogen spectrum for bacterial infective pathogens evaluated in this study, as well as the status quo of their resistance to antimicrobial agents and common clinical disinfectants, it is essential for healthcare professionals to pay attention not only to the standardized use of antimicrobial agents but also to the rational application of disinfectants.201830568055
581980.9997Application of mNGS in the Etiological Analysis of Lower Respiratory Tract Infections and the Prediction of Drug Resistance. Lower respiratory tract infections (LRTIs) have high morbidity and mortality rates. However, traditional etiological detection methods have not been able to meet the needs for the clinical diagnosis and prognosis of LRTIs. The rapid development of metagenomic next-generation sequencing (mNGS) provides new insights for the diagnosis and treatment of LRTIs; however, little is known about how to interpret the application of mNGS results in LRTIs. In this study, lower respiratory tract specimens from 46 patients with suspected LRTIs were tested simultaneously using conventional microbiological detection methods and mNGS. Receiver operating characteristic (ROC) curves were used to evaluate the performance of the logarithm of reads per kilobase per million mapped reads [lg(RPKM)], genomic coverage, and relative abundance of the organism in predicting the true-positive pathogenic bacteria. True-positive viruses were identified according to the lg(RPKM) threshold of bacteria. We also evaluated the ability to predict drug resistance genes using mNGS. Compared to that using conventional detection methods, the false-positive detection rate of pathogenic bacteria was significantly higher using mNGS. It was concluded from the ROC curves that the lg(RPKM) and genomic coverage contributed to the identification of pathogenic bacteria, with the performance of lg(RPKM) being the best (area under the curve [AUC] = 0.99). The corresponding lg(RPKM) threshold for identifying the pathogenic bacteria was -1.35. Thirty-five strains of true-positive virus were identified based on the lg(RPKM) threshold of bacteria, with the detection of human gammaherpesvirus 4 being the highest and prone to coinfection with Pseudomonas aeruginosa, Acinetobacter baumannii, and Stenotrophomonas maltophilia. Antimicrobial susceptibility tests (AST) revealed the resistance of bacteria containing drug resistance genes (detected by mNGS). However, the drug resistance genes of some multidrug-resistant bacteria were not detected. As an emerging technology, mNGS has shown many advantages for the unbiased etiological detection and the prediction of antibiotic resistance. However, a correct understanding of mNGS results is a prerequisite for its clinical application, especially for LRTIs. IMPORTANCE LRTIs are caused by hundreds of pathogens, and they have become a great threat to human health due to the limitations of traditional etiological detection methods. As an unbiased approach to detect pathogens, mNGS overcomes such etiological diagnostic challenges. However, there is no unified standard on how to use mNGS indicators (the sequencing reads, genomic coverage, and relative abundance of each organism) to distinguish between pathogens and colonizing microorganisms or contaminant microorganisms. Here, we selected the mNGS indicator with the best identification performance and established a cutoff value for the identification of pathogens in LRTIs using ROC curves. In addition, we also evaluated the accuracy of antibiotic resistance prediction using mNGS.202235171007
259690.999716S rRNA amplicon sequencing and antimicrobial resistance profile of intensive care units environment in 41 Brazilian hospitals. INTRODUCTION: Infections acquired during healthcare setting stay pose significant public health threats. These infections are known as Healthcare-Associated Infections (HAI), mostly caused by pathogenic bacteria, which exhibit a wide range of antimicrobial resistance. Currently, there is no knowledge about the global cleaning process of hospitals and the bacterial diversity found in ICUs of Brazilian hospitals contributing to HAI. OBJECTIVE: Characterize the microbiome and common antimicrobial resistance genes present in high-touch Intensive Care Unit (ICU) surfaces, and to identify the potential contamination of the sanitizers/processes used to clean hospital surfaces. METHODS: In this national, multicenter, observational, and prospective cohort, bacterial profiles and several antimicrobial resistance genes from 41 hospitals across 16 Brazilian states were evaluated. Using high-throughput 16S rRNA amplicon sequencing and real-time PCR, the bacterial abundance and resistance genes presence were analyzed in both ICU environments and cleaning products. RESULTS: We identified a wide diversity of microbial populations with a recurring presence of HAI-related bacteria among most of the hospitals. The median bacterial positivity rate in surface samples was high (88.24%), varying from 21.62 to 100% in different hospitals. Hospitals with the highest bacterial load in samples were also the ones with highest HAI-related abundances. Streptococcus spp., Corynebacterium spp., Staphylococcus spp., Bacillus spp., Acinetobacter spp., and bacteria from the Flavobacteriaceae family were the microorganisms most found across all hospitals. Despite each hospital particularities in bacterial composition, clustering profiles were found for surfaces and locations in the ICU. Antimicrobial resistance genes mecA, bla (KPC-like), bla (NDM-like), and bla (OXA-23-like) were the most frequently detected in surface samples. A wide variety of sanitizers were collected, with 19 different active principles in-use, and 21% of the solutions collected showed viable bacterial growth with antimicrobial resistance genes detected. CONCLUSION: This study demonstrated a diverse and spread pattern of bacteria and antimicrobial resistance genes covering a large part of the national territory in ICU surface samples and in sanitizers solutions. This data should contribute to the adoption of surveillance programs to improve HAI control strategies and demonstrate that large-scale epidemiology studies must be performed to further understand the implications of bacterial contamination in hospital surfaces and sanitizer solutions.202439076419
2248100.9997Predictive Application Value of Metagenomic Next-Generation Sequencing in the Resistance of Carbapenem-Resistant Enterobacteriaceae. Objective: Although metagenomic next-generation sequencing (mNGS) technology has achieved notable outcomes in pathogen detection, there remains a gap in the research regarding its application in predicting the antibiotic resistance of pathogenic bacteria. This study aims to analyze the clinical application value of mNGS in predicting the resistance of carbapenem-resistant Enterobacteriaceae (CRE), as well as the relevant influencing factors, thereby providing valuable insights for clinical antimicrobial therapy. Methods: Nonduplicate isolates of Enterobacterales bacteria collected from Liaocheng People's Hospital from April 2023 to June 2024 were selected, and CRE bacteria were screened. mNGS was used to detect resistance genes, and the results were compared with those of polymerase chain reaction (PCR) to evaluate the specificity and sensitivity of gene detection. Furthermore, the performance of mNGS in identifying pathogenic microorganisms and predicting antibiotic resistance was assessed by comparing the sequencing results with those of antimicrobial susceptibility testing (AST). Results: A total of 46 isolates were confirmed as CRE through traditional AST and were further identified using the Vitek MS and Vitek 2 systems. The results indicated 27 isolates of Klebsiella pneumoniae, 14 isolates of Escherichia coli, 2 isolates of Enterobacter hormaechei, 2 isolates of Enterobacter cloacae, and 1 isolate of Citrobacter freundii. These isolates were subjected to both mNGS and PCR for detection. The calculation of the area under the receiver operating characteristic (ROC) curve demonstrated the reliability of mNGS in detecting resistance genes. Conclusion: mNGS demonstrated high sensitivity in predicting the presence of carbapenemase resistance genes in CRE, showing potential in early indication of isolate resistance information, thereby facilitating timely guidance for clinical treatment strategies.202539816186
2552110.9997Bacterial diversity and prevalence of antibiotic resistance genes in the oral microbiome. OBJECTIVES: This study aims to describe the oral microbiome diversity and prevalence of ARGs in periodontal health and disease. BACKGROUND: The human oral cavity harbors a complex microbial community known as the oral microbiome. These organisms are regularly exposed to selective pressures, such as the usage of antibiotics, which drive evolution and acquisition of antibiotic resistance genes (ARGs). Resistance among oral bacteria jeopardizes not only antibiotic therapy for oral infections, but also extra-oral infections caused by bacterial translocation. METHODS: We carried out a cross-sectional investigation. Saliva and subgingival plaque samples were collected during a clinical exam. 16S rRNA gene sequencing was performed to assess microbial diversity. Resistance genes were identified through PCR assays. RESULTS: Of the 110 participants, only 22.7% had healthy periodontium, while the majority was diagnosed with gingivitis (55.4%) and chronic periodontitis (21.8%). The composition of the oral microbiota differed from healthy and diseased samples, being Streptococcus spp. and Rothia spp. predominant in periodontal disease. Regarding ARGs, 80 (72.7%) samples were positive for at least one of genes screened, erm being the most frequent variant (58.2%), followed by blaTEM (16.4%), mecA (2.7%), pbp2b and aac(6 ') (1.8%). Neither genes coding resistance to carbapenems nor metronidazole were detected. CONCLUSIONS: Our findings indicate that there are no significant differences in terms of taxonomic enrichment between healthy and diseased oral microbiomes. However, samples retrieved from healthy patients had a more diverse microbial community, whereas diseased samples have lower taxonomic diversity. We have also identified clinically relevant ARGs, providing baseline information to guide antibiotic prescription in dentistry.202032991620
5317120.9997Effect of anaerobic digestion on pathogens and antimicrobial resistance in the sewage sludge. Antimicrobial resistance (AMR) is recognized as a global threat. AMR bacteria accumulate in sewage sludge however, knowledge on the persistence of human pathogens and AMR in the sludge line of the wastewater treatment is limited. Sludge can be used, with or without additional treatment, as fertilizer in agricultural fields. The aim of this study is to obtain knowledge about presence of human pathogens and AMR in the sewage sludge, before and after the anaerobic digestion (AD) applying innovative combinations of methods. Fifty sludge samples were collected. Cultivation methods combined with matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and Antibiotic Susceptibility Test (AST) were used obtaining knowledge about the microbial community, pathogens, and antibiotic resistant bacteria while the droplet digital Polymerase Chain Reaction (ddPCR) was performed to detect most common AMR genes. In total, 231 different bacterial species were identified in the samples. The most abundant species were spore-forming facultative anaerobic bacteria belonging to Bacillus and Clostridium genera. The AD causes a shift in the microbial composition of the sludge (p = 0.04). Seven pathogenic bacterial species constituting 188 colonies were isolated and tested for susceptibility to Clindamycin, Meropenem, Norfloxacin, Penicillin G, and Tigecycline. Of the Clostridium perfringens and Bacillus cereus isolates 67 and 50 %, respectively, were resistant to Clindamycin. Two B. cereus and two C. perfringens isolates were also resistant to other antibiotics showing multidrug resistance. ARGs (bla(OXA), bla(TEM), ermB, qnrB, tet(A)-(W), sulI-II) were present at 7-8 Log gene copies/kg of sludge. AD is the main driver of a reduction of some ARGs (1 Log) but resistant bacteria were still present. The results showed the usefulness of the integration of the proposed analytical methods and suggest a decrease in the risk of presence of cultivable pathogens including resistant isolates after AD but a persistent risk of ARGs' horizontal transmission.202439244956
2595130.9997Antibiotic resistance pattern of waterborne causative agents of healthcare-associated infections: A call for biofilm control in hospital water systems. BACKGROUND: In recent years, the global spread of antimicrobial resistance has become a concerning issue, often referred to as a "silent pandemic". Healthcare-associated infections (HAIs) caused by antibiotic-resistant bacteria (ARB) are a recurring problem, with some originating from waterborne route. The study aimed to investigate the presence of clinically relevant opportunistic bacteria and antibiotic resistance genes (ARGs) in hospital water distribution systems (WDSs). METHODS: Water and biofilm samples (n = 192) were collected from nine hospitals in Isfahan and Kashan, located in central Iran, between May 2022 and June 2023. The samples were analyzed to determine the presence and quantities of opportunistic bacteria and ARGs using cultural and molecular methods. RESULTS: Staphylococcus spp. were highly detected in WDS samples (90 isolates), with 33 % of them harboring mecA gene. However, the occurrences of E. coli (1 isolate), Acinetobacter baumannii (3 isolates), and Pseudomonas aeruginosa (14 isolates) were low. Moreover, several Gram-negative bacteria containing ARGs were identified in the samples, mainly belonging to Stenotrophomonas, Sphingomonas and Brevundimonas genera. Various ARGs, as well as intI1, were found in hospital WDSs (ranging from 14 % to 60 %), with higher occurrences in the biofilm samples. CONCLUSION: Our results underscore the importance of biofilms in water taps as hotspots for the dissemination of opportunistic bacteria and ARG within hospital environments. The identification of multiple opportunistic bacteria and ARGs raises concerns about the potential exposure and acquisition of HAIs, emphasizing the need for proactive measures, particularly in controlling biofilms, to mitigate infection risks in healthcare settings.202438838607
5663140.9997Development of multiplex Luminex assays for the surveillance of antimicrobial resistance genes in nasal samples. Bovine respiratory disease (BRD) is the major cause of morbidity and mortality in feedlot cattle. It is the major driver for the therapeutic use of antimicrobials in feedlot cattle with their continued use and effectiveness being underpinned through the implementation of stewardship programs that include monitoring of resistance levels. To enable these programs, rapid and user-friendly assays are needed to detect antimicrobial resistance genes (ARG) for efficient monitoring. This study developed multiplex Luminex assays targeting 34 ARGs and validated them using reference strains of Pasteurellaceae and other bacteria, as well as field samples from nasal swabs of cattle (n = 94) undergoing BRD treatment at an Australian feedlot. One swab was collected from each nostril of every animal, with one being used for bacterial culture and conventional PCR analyses for ARGs, while the DNA extracted from the second swab was analyzed using the novel Luminex assays for the presence or absence of the ARGs of interest. The pathogens isolated by culture were tested for macrolide resistance genes erm(42), mph(E) and msr(E); sulfonamide resistance genes, sul1 and sul2; florfenicol resistance gene floR; β-lactam resistance gene bla(Rob-1) and tetracycline resistance genes tet(Q) and tet(Y), by conventional PCR. Kappa statistics suggested a moderate agreement between the tests in detecting the macrolide resistance genes. Luminex based analyses identified more resistance genes than PCR on cultured organisms, revealing the presence of a broader array of these genes than previously reported. In addition to detecting more genes, Luminex assays could process a higher number of samples in a single day, making them well-suited for ongoing surveillance of antimicrobial resistance in BRD affected cattle. This capability is essential for optimising therapeutic use and detecting emerging resistance patterns.202540848749
4939150.9997Identification of bacterial pathogens and antimicrobial resistance directly from clinical urines by nanopore-based metagenomic sequencing. OBJECTIVES: The introduction of metagenomic sequencing to diagnostic microbiology has been hampered by slowness, cost and complexity. We explored whether MinION nanopore sequencing could accelerate diagnosis and resistance profiling, using complicated urinary tract infections as an exemplar. METHODS: Bacterial DNA was enriched from clinical urines (n = 10) and from healthy urines 'spiked' with multiresistant Escherichia coli (n = 5), then sequenced by MinION. Sequences were analysed using external databases and bioinformatic pipelines or, ultimately, using integrated real-time analysis applications. Results were compared with Illumina data and resistance phenotypes. RESULTS: MinION correctly identified pathogens without culture and, among 55 acquired resistance genes detected in the cultivated bacteria by Illumina sequencing, 51 were found by MinION sequencing directly from the urines; with three of the four failures in an early run with low genome coverage. Resistance-conferring mutations and allelic variants were not reliably identified. CONCLUSIONS: MinION sequencing comprehensively identified pathogens and acquired resistance genes from urine in a timeframe similar to PCR (4 h from sample to result). Bioinformatic pipeline optimization is needed to better detect resistances conferred by point mutations. Metagenomic-sequencing-based diagnosis will enable clinicians to adjust antimicrobial therapy before the second dose of a typical (i.e. every 8 h) antibiotic.201727667325
2597160.9997One year cross-sectional study in adult and neonatal intensive care units reveals the bacterial and antimicrobial resistance genes profiles in patients and hospital surfaces. Several studies have shown the ubiquitous presence of bacteria in hospital surfaces, staff, and patients. Frequently, these bacteria are related to HAI (healthcare-associated infections) and carry antimicrobial resistance (AMR). These HAI-related bacteria contribute to a major public health issue by increasing patient morbidity and mortality during or after hospital stay. Bacterial high-throughput amplicon gene sequencing along with identification of AMR genes, as well as whole genome sequencing (WGS), are biotechnological tools that allow multiple-sample screening for a diversity of bacteria. In this paper, we used these methods to perform a one-year cross sectional profiling of bacteria and AMR genes in adult and neonatal intensive care units (ICU and NICU) in a Brazilian public, tertiary hospital. Our results showed high abundances of HAI-related bacteria such as S. epidermidis, S. aureus, K. pneumoniae, A. baumannii complex, E. coli, E. faecalis, and P. aeruginosa in patients and hospital surfaces. Most abundant AMR genes detected throughout ICU and NICU were mecA, blaCTX-M-1 group, blaSHV-like, and blaKPC-like. We found that NICU environment and patients were more widely contaminated with pathogenic bacteria than ICU. Patient samples, despite the higher bacterial load, have lower bacterial diversity than environmental samples in both units. Finally, we also identified contamination hotspots in the hospital environment showing constant frequencies of bacterial and AMR contamination throughout the year. Whole genome sequencing (WGS), 16S rRNA oligotypes, and AMR identification allowed a high-resolution characterization of the hospital microbiome profile.202032492060
3122170.9997Hybrid sequence-based analysis reveals the distribution of bacterial species and genes in the oral microbiome at a high resolution. Bacteria in the oral microbiome are poorly identified owing to the lack of established culture methods for them. Thus, this study aimed to use culture-free analysis techniques, including bacterial single-cell genome sequencing, to identify bacterial species and investigate gene distribution in saliva. Saliva samples from the same individual were classified as inactivated or viable and then analyzed using 16S rRNA sequencing, metagenomic shotgun sequencing, and bacterial single-cell sequencing. The results of 16S rRNA sequencing revealed similar microbiota structures in both samples, with Streptococcus being the predominant genus. Metagenomic shotgun sequencing showed that approximately 80 % of the DNA in the samples was of non-bacterial origin, whereas single-cell sequencing showed an average contamination rate of 10.4 % per genome. Single-cell sequencing also yielded genome sequences for 43 out of 48 wells for the inactivated samples and 45 out of 48 wells for the viable samples. With respect to resistance genes, four out of 88 isolates carried cfxA, which encodes a β-lactamase, and four isolates carried erythromycin resistance genes. Tetracycline resistance genes were found in nine bacteria. Metagenomic shotgun sequencing provided complete sequences of cfxA, ermF, and ermX, whereas other resistance genes, such as tetQ and tetM, were detected as fragments. In addition, virulence factors from Streptococcus pneumoniae were the most common, with 13 genes detected. Our average nucleotide identity analysis also suggested five single-cell-isolated bacteria as potential novel species. These data would contribute to expanding the oral microbiome data resource.202438708423
5000180.9997Spatiotemporal dynamics of multidrug resistant bacteria on intensive care unit surfaces. Bacterial pathogens that infect patients also contaminate hospital surfaces. These contaminants impact hospital infection control and epidemiology, prompting quantitative examination of their transmission dynamics. Here we investigate spatiotemporal and phylogenetic relationships of multidrug resistant (MDR) bacteria on intensive care unit surfaces from two hospitals in the United States (US) and Pakistan collected over one year. MDR bacteria isolated from 3.3% and 86.7% of US and Pakistani surfaces, respectively, include common nosocomial pathogens, rare opportunistic pathogens, and novel taxa. Common nosocomial isolates are dominated by single lineages of different clones, are phenotypically MDR, and have high resistance gene burdens. Many resistance genes (e.g., bla(NDM), bla(OXA) carbapenamases), are shared by multiple species and flanked by mobilization elements. We identify Acinetobacter baumannii and Enterococcus faecium co-association on multiple surfaces, and demonstrate these species establish synergistic biofilms in vitro. Our results highlight substantial MDR pathogen burdens in hospital built-environments, provide evidence for spatiotemporal-dependent transmission, and demonstrate potential mechanisms for multi-species surface persistence.201931594927
5672190.9997Antibiotic Resistance, Biofilm Formation, and Presence of Genes Encoding Virulence Factors in Strains Isolated from the Pharmaceutical Production Environment. The spread of bacterial resistance to antibiotics affects various areas of life. The aim of this study was to assess the occurrence of Pseudomonas aeruginosa, and other bacteria mainly from orders Enterobacterales and Staphylococcus in the pharmaceutical production sites, and to characterize isolated strains in the aspects of antibiotic resistance, biofilm formation, and presence of genes encoding virulence factors. Genes encoding selected virulence factors were detected using PCR techniques. Antimicrobial susceptibility testing was applied in accordance with the EUCAST recommendations. A total of 46 P. aeruginosa strains were isolated and 85% strains showed a strong biofilm-forming ability. The qualitative identification of genes taking part in Quorum Sensing system demonstrated that over 89% of strains contained lasR and rhlI genes. An antimicrobial susceptibility testing revealed nine strains resistant to at least one antibiotic, and two isolates were the metallo-β-lactamase producers. Moreover, the majority of P. aeruginosa strains contained genes encoding various virulence factors. Presence of even low level of pathogenic microorganisms or higher level of opportunistic pathogens and their toxic metabolites might result in the production inefficiency. Therefore, the prevention of microbial contamination, effectiveness of sanitary and hygienic applied protocols, and constant microbiological monitoring of the environment are of great importance.202133513933