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512800.9981Whole genomes from bacteria collected at diagnostic units around the world 2020. The Two Weeks in the World research project has resulted in a dataset of 3087 clinically relevant bacterial genomes with pertaining metadata, collected from 59 diagnostic units in 35 countries around the world during 2020. A relational database is available with metadata and summary data from selected bioinformatic analysis, such as species prediction and identification of acquired resistance genes.202337717051
581910.9981Application 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
582120.9980Direct 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
582030.9979Sequencing 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
178840.9978Draft genome sequence of a multidrug-resistant Stenotrophomonas sp. B1-1 strain isolated from radiation-polluted soil and its pathogenic potential. OBJECTIVES: Stenotrophomonas is a genus of Gram-negative bacteria with several potential industrial uses as well as an increasingly relevant pathogen that may cause dangerous nosocomial infections. Here we present the draft genome sequence of a multidrug-resistant Stenotrophomonas sp. B1-1 isolated from radiation-polluted soil in Xinjiang Uyghur Autonomous Region, China. METHODS: The genome of Stenotrophomonas sp. B1-1 was sequenced using a BGISEQ-500 platform. The generated sequencing reads were de novo assembled using SOAPdenovo and the resulting sequences were predicted and annotated to identify antimicrobial resistance genes and virulence factors using the ARDB and VFDB databases, respectively. RESULTS: The Stenotrophomonas sp. B1-1 genome assembly resulted in a total genome size of 4,723,769 bp with a GC content of 67.47%. There were 4280 predicted genes with 68 tRNAs, 2 rRNAs and 163 sRNAs. A number of antimicrobial resistance genes were identified conferring resistance to various antibiotics as well as numerous virulence genes. CONCLUSION: The genome sequence of Stenotrophomonas sp. B1-1 will provide timely information for comparison of the Stenotrophomonas genus and to help further understand the pathogenesis and antimicrobial resistance of this genus.202133373734
224850.9978Predictive 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
493360.9978Distribution and Classification of Serine β-Lactamases in Brazilian Hospital Sewage and Other Environmental Metagenomes Deposited in Public Databases. β-lactam is the most used antibiotic class in the clinical area and it acts on blocking the bacteria cell wall synthesis, causing cell death. However, some bacteria have evolved resistance to these antibiotics mainly due the production of enzymes known as β-lactamases. Hospital sewage is an important source of dispersion of multidrug-resistant bacteria in rivers and oceans. In this work, we used next-generation DNA sequencing to explore the diversity and dissemination of serine β-lactamases in two hospital sewage from Rio de Janeiro, Brazil (South Zone, SZ and North Zone, NZ), presenting different profiles, and to compare them with public environmental data available. Also, we propose a Hidden-Markov-Model approach to screen potential serine β-lactamases genes (in public environments samples and generated hospital sewage data), exploring its evolutionary relationships. Due to the high variability in β-lactamases, we used a position-specific scoring matrix search method (RPS-BLAST) against conserved domain database profiles (CDD, Pfam, and COG) followed by visual inspection to detect conserved motifs, to increase the reliability of the results and remove possible false positives. We were able to identify novel β-lactamases from Brazilian hospital sewage and to estimate relative abundance of its types. The highest relative abundance found in SZ was the Class A (50%), while Class D is predominant in NZ (55%). CfxA (65%) and ACC (47%) types were the most abundant genes detected in SZ, while in NZ the most frequent were OXA-10 (32%), CfxA (28%), ACC (21%), CEPA (20%), and FOX (19%). Phylogenetic analysis revealed β-lactamases from Brazilian hospital sewage grouped in the same clade and close to sequences belonging to Firmicutes and Bacteroidetes groups, but distant from potential β-lactamases screened from public environmental data, that grouped closer to β-lactamases of Proteobacteria. Our results demonstrated that HMM-based approach identified homologs of serine β-lactamases, indicating the specificity and high sensitivity of this approach in large datasets, contributing for the identification and classification of a large number of homologous genes, comprising possible new ones. Phylogenetic analysis revealed the potential reservoir of β-lactam resistance genes in the environment, contributing to understanding the evolution and dissemination of these genes.201627895627
570170.9978An Acinetobacter non-baumannii Population Study: Antimicrobial Resistance Genes (ARGs). Acinetobacter non-baumannii species are becoming common etiologic agents of nosocomial infections. Furthermore, clinical isolates belonging to this group of bacteria are usually resistant to one or more antibiotics. The current information about antibiotic resistance genes in the different A. non-baumannii species has not yet been studied as a whole. Therefore, we did a comparative study of the resistomes of A. non-baumannii pathogens based on information available in published articles and genome sequences. We searched the available literature and sequences deposited in GenBank to identify the resistance gene content of A. calcoaceticus, A. lwoffii, A. junii, A. soli, A. ursingii, A. bereziniae, A. nosocomialis, A. portensis, A. guerrae, A. baylyi, A. calcoaceticus, A. disperses, A. johnsonii, A. junii, A. lwoffii, A. nosocomialis, A. oleivorans, A. oryzae, A. pittii, A. radioresistens, and A. venetianus. The most common genes were those coding for different β-lactamases, including the carbapenemase genes bla (NDM-1) and bla (OXA-58). A. pittii was the species with the most β-lactamase resistance genes reported. Other genes that were commonly found include those encoding some aminoglycoside modifying enzymes, the most common being aph(6)-Id, ant( 3 ″ )-IIa, and aph( 3 ″ )-Ib, and efflux pumps. All or part of the genes coding for the AdeABC, AdeFGH, and AdeIJK efflux pumps were the most commonly found. This article incorporates all the current information about A. non-baumannii resistance genes. The comparison of the different resistomes shows that there are similarities in the genes present, but there are also significant differences that could impact the efficiency of treatments depending on the etiologic agent. This article is a comprehensive resource about A. non-baumannii resistomes.202033375352
224780.9978Metagenomic 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
582890.9978Target-enriched sequencing enables accurate identification of bloodstream infections in whole blood. Bloodstream infections are within the top ten causes of death globally, with a mortality rate of up to 70%. Gold standard blood culture testing is time-consuming, resulting in delayed, but accurate, treatment. Molecular methods, such as RT-qPCR, have limited targets in one run. We present a new Ampliseq detection system (ADS) combining target amplification and next-generation sequencing for accurate identification of bacteria, fungi, and antimicrobial resistance determinants directly from blood samples. In this study, we included removal of human genomic DNA during nucleic acid extraction, optimized the target sequence set and drug resistance genes, performed antimicrobial resistance profiling of clinical isolates, and evaluated mock specimens and clinical samples by ADS. ADS successfully identified pathogens at the species-level in 36 h, from nucleic acid extraction to results. Besides pathogen identification, ADS can also present drug resistance profiles. ADS enabled detection of all bacteria and accurate identification of 47 pathogens. In 20 spiked samples and 8 clinical specimens, ADS detected at least 92.81% of reads mapped to pathogens. ADS also showed consistency with the three culture-negative samples, and correctly identified pathogens in four of five culture-positive clinical blood specimens. This Ampliseq-based technology promises broad coverage and accurate pathogen identification, helping clinicians to accurately diagnose and treat bloodstream infections.202234915067
5684100.9978Distribution of genes related to antimicrobial resistance in different oral environments: a systematic review. INTRODUCTION: The oral cavity is the main source of microorganisms for odontogenic infections. It is important to perform an extensive analysis regarding the reports on the presence of bacteria that carry resistance genes to antimicrobial agents. The aim of the study was to verify the reports on the distribution of genes associated with resistance to antibiotics prescribed in dentistry in different human oral sites. METHODS: A systematic review was conducted in electronic databases and gray literature to analyze clinical studies that detected genes of bacterial resistance to antibiotics in saliva, supragingival biofilm, and endodontic infections. Data regarding the research group, geographic location, sample source, number of subjects, methods for sample analysis, the targeted gene groups, and the detection rates were collected. Descriptive data analysis was performed. RESULTS: Preliminary analysis was performed in 152 titles; 50 abstracts were reviewed, and 29 full texts were obtained. Nine articles matched the inclusion criteria (saliva = 2, supragingival biofilm = 1, and endodontic infections = 6). The presence of 33 different targeted genes was evaluated. The most frequently investigated groups of genes were tetracycline and lactamics (tetM, tetQ, tetW, and cfxA). There was a wide range for the detection rates of each resistance gene among studies and for each specific gene group. CONCLUSIONS: This systematic review highlights the presence of resistance genes to antimicrobial agents in saliva, dental biofilm, and endodontic infections, especially for tetracycline and lactamics. There is a lack of reports on the presence of genes and resulting outcomes obtained through the therapeutic approaches for infection control.201525748493
4936110.9978A New Tool for Analyses of Whole Genome Sequences Reveals Dissemination of Specific Strains of Vancomycin-Resistant Enterococcus faecium in a Hospital. A new easy-to-use online bioinformatic tool analyzing whole genome sequences of healthcare associated bacteria was used by a local infection control unit to retrospectively map genetic relationship of isolates of E. faecium carrying resistance genes to vancomycin in a hospital. Three clusters of isolates were detected over a period of 5 years, suggesting transmission between patients. Individual relatedness between isolates within each cluster was established by SNP analyses provided by the system. Genetic antimicrobial resistance mechanisms to antibiotics other than vancomycin were identified. The results suggest that the system is suited for hospital surveillance of E. faecium carrying resistance genes to vancomycin in settings with access to next Generation Sequencing without bioinformatic expertise for interpretation of the genome sequences.202134778297
2246120.9978Bayesian network modeling of patterns of antibiotic cross-resistance by bacterial sample source. BACKGROUND: Antimicrobial resistance is a major healthcare burden, aggravated when it extends to multiple drugs. While cross-resistance is well-studied experimentally, it is not the case in clinical settings, and especially not while considering confounding. Here, we estimated patterns of cross-resistance from clinical samples, while controlling for multiple clinical confounders and stratifying by sample sources. METHODS: We employed additive Bayesian network (ABN) modelling to examine antibiotic cross- resistance in five major bacterial species, obtained from different sources (urine, wound, blood, and sputum) in a clinical setting, collected in a large hospital in Israel over a 4-year period. Overall, the number of samples available were 3525 for E coli, 1125 for K pneumoniae, 1828 for P aeruginosa, 701 for P mirabilis, and 835 for S aureus. RESULTS: Patterns of cross-resistance differ across sample sources. All identified links between resistance to different antibiotics are positive. However, in 15 of 18 instances, the magnitudes of the links are significantly different between sources. For example, E coli exhibits adjusted odds ratios of gentamicin-ofloxacin cross-resistance ranging from 3.0 (95%CI [2.3,4.0]) in urine samples to 11.0 (95%CI [5.2,26.1]) in blood samples. Furthermore, we found that for P mirabilis, the magnitude of cross-resistance among linked antibiotics is higher in urine than in wound samples, whereas the opposite is true for K pneumoniae and P aeruginosa. CONCLUSIONS: Our results highlight the importance of considering sample sources when assessing likelihood of antibiotic cross-resistance. The information and methods described in our study can refine future estimation of cross-resistance patterns and facilitate determination of antibiotic treatment regimens.202337130943
5482130.9978Characterization of an Environmental Multidrug-Resistant Acinetobacter seifertii and Comparative Genomic Analysis Reveals Co-occurrence of Antimicrobial Resistance and Metal Tolerance Determinants. Acinetobacter calcoaceticus-Acinetobacter baumannii complex is considered one of the main causes of hospital-acquired infections. Acinetobacter seifertii was recently characterized within this complex and it has been described as an emergent pathogen associated with bacteremia. The emergence of multidrug-resistant (MDR) bacteria, including Acinetobacter sp., is considered a global public health threat and an environmental problem because MDR bacteria have been spreading from several sources. Therefore, this study aimed to characterize an environmental MDR A. seifertii isolate (SAb133) using whole genome sequencing and a comparative genomic analysis was performed with A. seifertii strains recovered from various sources. The SAb133 isolate was obtained from soil of a corn crop field and presented high MICs for antimicrobials and metals. The comparative genomic analyses revealed ANI values higher than 95% of relatedness with other A. seifertii strains than A. calcoaceticus-A. baumannii complex. Resistome and virulome analyses were also performed and showed different antimicrobial resistance determinants and metal tolerance genes as well as virulence genes related to A. baumannii known virulence genes. In addition, genomic islands, IS elements, plasmids and prophage-related sequences were detected. Comparative genomic analysis showed that MDR A. seifertii SAb133 had a high amount of determinants related to antimicrobial resistance and tolerance to metals, besides the presence of virulence genes. To the best of our knowledge, this is the first report of a whole genome sequence of a MDR A. seifertii isolated from soil. Therefore, this study contributed to a better understanding of the genetic relationship among the few known A. seifertii strains worldwide distributed.201931620107
5815140.9978Pangenome Analysis of Helicobacter pylori Isolates from Selected Areas of Africa Indicated Diverse Antibiotic Resistance and Virulence Genes. The challenge facing Helicobacter pylori (H. pylori) infection management in some parts of Africa is the evolution of drug-resistant species, the lack of gold standard in diagnostic methods, and the ineffectiveness of current vaccines against the bacteria. It is being established that even though clinical consequences linked to the bacteria vary geographically, there is rather a generic approach to treatment. This situation has remained problematic in the successful fight against the bacteria in parts of Africa. As a result, this study compared the genomes of selected H. pylori isolates from selected areas of Africa and evaluated their virulence and antibiotic drug resistance, those that are highly pathogenic and are associated with specific clinical outcomes and those that are less virulent and rarely associated with clinical outcomes. 146 genomes of H. pylori isolated from selected locations of Africa were sampled, and bioinformatic tools such as Abricate, CARD RGI, MLST, Prokka, Roary, Phandango, Google Sheets, and iTOLS were used to compare the isolates and their antibiotic resistance or susceptibility. Over 20 k virulence and AMR genes were observed. About 95% of the isolates were genetically diverse, 90% of the isolates harbored shell genes, and 50% harbored cloud and core genes. Some isolates did not retain the cagA and vacA genes. Clarithromycin, metronidazole, amoxicillin, and tinidazole were resistant to most AMR genes (vacA, cagA, oip, and bab). Conclusion. This study found both virulence and AMR genes in all H. pylori strains in all the selected geographies around Africa with differing quantities. MLST, Pangenome, and ORF analyses showed disparities among the isolates. This in general could imply diversities in terms of genetics, evolution, and protein production. Therefore, generic administration of antibiotics such as clarithromycin, amoxicillin, and erythromycin as treatment methods in the African subregion could be contributing to the spread of the bacterium's antibiotic resistance.202438469580
4935150.9978Three Distinct Annotation Platforms Differ in Detection of Antimicrobial Resistance Genes in Long-Read, Short-Read, and Hybrid Sequences Derived from Total Genomic DNA or from Purified Plasmid DNA. Recent advances and lower costs in rapid high-throughput sequencing have engendered hope that whole genome sequencing (WGS) might afford complete resistome characterization in bacterial isolates. WGS is particularly useful for the clinical characterization of fastidious and slow-growing bacteria. Despite its potential, several challenges should be addressed before adopting WGS to detect antimicrobial resistance (AMR) genes in the clinical laboratory. Here, with three distinct ESKAPE bacteria (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.), different approaches were compared to identify best practices for detecting AMR genes, including: total genomic DNA and plasmid DNA extractions, the solo assembly of Illumina short-reads and of Oxford Nanopore Technologies (ONT) long-reads, two hybrid assembly pipelines, and three in silico AMR databases. We also determined the susceptibility of each strain to 21 antimicrobials. We found that all AMR genes detected in pure plasmid DNA were also detectable in total genomic DNA, indicating that, at least in these three enterobacterial genera, the purification of plasmid DNA was not necessary to detect plasmid-borne AMR genes. Illumina short-reads used with ONT long-reads in either hybrid or polished assemblies of total genomic DNA enhanced the sensitivity and accuracy of AMR gene detection. Phenotypic susceptibility closely corresponded with genotypes identified by sequencing; however, the three AMR databases differed significantly in distinguishing mobile dedicated AMR genes from non-mobile chromosomal housekeeping genes in which rare spontaneous resistance mutations might occur. This study indicates that each method employed in a WGS workflow has an impact on the detection of AMR genes. A combination of short- and long-reads, followed by at least three different AMR databases, should be used for the consistent detection of such genes. Further, an additional step for plasmid DNA purification and sequencing may not be necessary. This study reveals the need for standardized biochemical and informatic procedures and database resources for consistent, reliable AMR genotyping to take full advantage of WGS in order to expedite patient treatment and track AMR genes within the hospital and community.202236290058
4976160.9978Trans-Regional and Cross-Host Spread of mcr-Carrying Plasmids Revealed by Complete Plasmid Sequences - 44 Countries, 1998-2020. BACKGROUND: The surveillance of antimicrobial resistance genes (ARGs) and bacteria is one critical approach to prevent and control antimicrobial resistance (AMR). Next-generation sequencing (NGS) is a powerful tool in monitoring the emergence and spread of ARGs and resistant bacteria. The horizontal transfer of ARGs across host bacteria mediated by plasmids is a challenge in NGS surveillance for resistance because short-read sequencing can hardly generate the complete plasmid genome sequence, and the correlation between ARGs and plasmids are difficult to determine. METHODS: The complete genome sequences of 455 mcr-carrying plasmids (pMCRs), and the data of their host bacteria and isolation regions were collected from the NCBI database. Genes of Inc types and ARGs were searched for each plasmid. The genome similarity of these plasmids was analyzed by pangenome clustering and genome alignment. RESULTS: A total of 52 Inc types, including a variety of fusion plasmids containing 2 or more Inc types were identified in these pMCRs and carried by complex host bacteria. The cooccurrence of ARGs in pMCRs was generally observed, with an average of 3.9 ARGs per plasmid. Twenty-two clusters with consistent or highly similar sequences and gene compositions were identified by the pangenome clustering, which were characterized with distributions in different countries/regions, years or host bacteria in each cluster. DISCUSSION: Based on the complete plasmid sequences, distribution of mcr genes in different Inc type plasmids, their co-existence with other AMRs, and transmission of one pMCR across regions and host bacteria can be revealed definitively. Complete plasmid genomes and comparisons in the laboratory network are necessary for spread tracing of ARG-carrying plasmids and risk assessment in AMR surveillance.202235433080
3133170.9977A Study of Resistome in Mexican Chili Powder as a Public Health Risk Factor. Chili powder is an important condiment around the world. However, according to various reports, the presence of pathogenic microorganisms could present a public health risk factor during its consumption. Therefore, microbiological quality assessment is required to understand key microbial functional traits, such as antibiotic resistance genes (ARGs). In this study, metagenomic next-generation sequencing (mNGS) and bioinformatics analysis were used to characterize the comprehensive profiles of the bacterial community and antibiotic resistance genes (ARGs) in 15 chili powder samples from different regions of Mexico. The initial bacterial load showed aerobic mesophilic bacteria (AMB) ranging between 6 × 10(3) and 7 × 10(8) CFU/g, sporulated mesophilic bacteria (SMB) from 4.3 × 10(3) to 2 × 10(9) CFU/g, and enterobacteria (En) from <100 to 2.3 × 10(6) CFU/g. The most representative families in the samples were Bacillaceae and Enterobacteriaceae, in which 18 potential pathogen-associated species were detected. In total, the resistome profile in the chili powder contained 68 unique genes, which conferred antibiotic resistance distributed in 13 different classes. Among the main classes of antibiotic resistance genes with a high abundance in almost all the samples were those related to multidrug, tetracycline, beta-lactam, aminoglycoside, and phenicol resistance. Our findings reveal the utility of mNGS in elucidating microbiological quality in chili powder to reduce the public health risks and the spread of potential pathogens with antibiotic resistance mechanisms.202438391568
4916180.9977A clinical metagenomic study of biopsies from Mexican endophthalmitis patients reveals the presence of complex bacterial communities and a diversity of resistance genes. Infectious endophthalmitis is a severe ophthalmic emergency. This infection can be caused by bacteria and fungi. For efficient treatment, the administration of antimicrobial drugs to which the microbes are susceptible is essential. The aim of this study was to identify micro-organisms in biopsies of Mexican endophthalmitis patients using metagenomic next-generation sequencing and determine which antibiotic resistance genes were present in the biopsy samples. In this prospective case study, 19 endophthalmitis patients were recruited. Samples of vitreous or aqueous humour were extracted for DNA extraction for metagenomic next-generation sequencing. Analysis of the sequencing results revealed the presence of a wide variety of bacteria in the biopsies. Resistome analysis showed that homologues of antibiotic resistance genes were present in several biopsy samples. Genes possibly conferring resistance to ceftazidime and vancomycin were detected in addition to various genes encoding efflux pumps. Our findings contrast with the widespread opinion that only one or a few bacterial strains are present in the infected tissues of endophthalmitis patients. These diverse communities might host many of the resistance genes that were detected, which can further complicate the infections.202439045243
2477190.9977Evaluation of targeted next-generation sequencing for microbiological diagnosis of acute lower respiratory infection. PURPOSE: To evaluate the performance of targeted next-generation sequencing (tNGS) in pathogen detection in acute lower respiratory infection. METHODS: The retrospective study was conducted between July 2023 and May 2024 at the Yantai Yuhuangding Hospital. Patients with acute lower respiratory infections were included. Qualified sputum or bronchoalveolar lavage fluid samples were collected for tNGS and conventional microbiological tests(CMTs), including culture, staining, polymerase chain reaction (PCR), and reverse transcription-PCR (RT-PCR). The time required and cost were counted. RESULTS: A total of 968 patients were enrolled. Study analysis discovered 1,019 strains of bacteria, 259 strains of fungi, 302 strains of viruses, 76 strains of Mycoplasma pneumoniae, and two strains of Chlamydia psittaci using tNGS. In addition, tNGS also identified 39 mecA, four KPC, 19 NDM, and two OXA-48 genes. The positive rates for bacteria, fungi, viruses, mycoplasma, and chlamydia obtained using tNGS were significantly higher than those determined using traditional methods. Among them, tNGS showed high consistence with mycobacterium DNA test, influenza A (H1N1) virus nucleic acid test and COVID-19 nucleic acid test. Poor consistency between drug resistance genes and bacterial resistance phenotypes was found. In addition, tNGS also had advantages over traditional methods in terms of detection time and cost. CONCLUSION: Compared to traditional methods, tNGS had higher sensitivity in detecting bacteria, fungi, viruses, and other pathogens in acute lower respiratory infection, and also had the advantages of timeliness and cost-effectiveness, making it a promising method for guiding clinical diagnosis.202540901079