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493700.9000Fast and Accurate Large-Scale Detection of β-Lactamase Genes Conferring Antibiotic Resistance. Fast detection of β-lactamase (bla) genes allows improved surveillance studies and infection control measures, which can minimize the spread of antibiotic resistance. Although several molecular diagnostic methods have been developed to detect limited bla gene types, these methods have significant limitations, such as their failure to detect almost all clinically available bla genes. We developed a fast and accurate molecular method to overcome these limitations using 62 primer pairs, which were designed through elaborate optimization processes. To verify the ability of this large-scale bla detection method (large-scaleblaFinder), assays were performed on previously reported bacterial control isolates/strains. To confirm the applicability of the large-scaleblaFinder, the assays were performed on unreported clinical isolates. With perfect specificity and sensitivity in 189 control isolates/strains and 403 clinical isolates, the large-scaleblaFinder detected almost all clinically available bla genes. Notably, the large-scaleblaFinder detected 24 additional unreported bla genes in the isolates/strains that were previously studied, suggesting that previous methods detecting only limited types of bla genes can miss unexpected bla genes existing in pathogenic bacteria, and our method has the ability to detect almost all bla genes existing in a clinical isolate. The ability of large-scaleblaFinder to detect bla genes on a large scale enables prompt application to the detection of almost all bla genes present in bacterial pathogens. The widespread use of the large-scaleblaFinder in the future will provide an important aid for monitoring the emergence and dissemination of bla genes and minimizing the spread of resistant bacteria.201526169415
519410.8995Evaluation of the CosmosID Bioinformatics Platform for Prosthetic Joint-Associated Sonicate Fluid Shotgun Metagenomic Data Analysis. We previously demonstrated that shotgun metagenomic sequencing can detect bacteria in sonicate fluid, providing a diagnosis of prosthetic joint infection (PJI). A limitation of the approach that we used is that data analysis was time-consuming and specialized bioinformatics expertise was required, both of which are barriers to routine clinical use. Fortunately, automated commercial analytic platforms that can interpret shotgun metagenomic data are emerging. In this study, we evaluated the CosmosID bioinformatics platform using shotgun metagenomic sequencing data derived from 408 sonicate fluid samples from our prior study with the goal of evaluating the platform vis-à-vis bacterial detection and antibiotic resistance gene detection for predicting staphylococcal antibacterial susceptibility. Samples were divided into a derivation set and a validation set, each consisting of 204 samples; results from the derivation set were used to establish cutoffs, which were then tested in the validation set for identifying pathogens and predicting staphylococcal antibacterial resistance. Metagenomic analysis detected bacteria in 94.8% (109/115) of sonicate fluid culture-positive PJIs and 37.8% (37/98) of sonicate fluid culture-negative PJIs. Metagenomic analysis showed sensitivities ranging from 65.7 to 85.0% for predicting staphylococcal antibacterial resistance. In conclusion, the CosmosID platform has the potential to provide fast, reliable bacterial detection and identification from metagenomic shotgun sequencing data derived from sonicate fluid for the diagnosis of PJI. Strategies for metagenomic detection of antibiotic resistance genes for predicting staphylococcal antibacterial resistance need further development.201930429253
506920.8990MC-PRPA-HLFIA Cascade Detection System for Point-of-Care Testing Pan-Drug-Resistant Genes in Urinary Tract Infection Samples. Recently, urinary tract infection (UTI) triggered by bacteria carrying pan-drug-resistant genes, including carbapenem resistance gene bla(NDM) and bla(KPC), colistin resistance gene mcr-1, and tet(X) for tigecycline resistance, have been reported, posing a serious challenge to the treatment of clinical UTI. Therefore, point-of-care (POC) detection of these genes in UTI samples without the need for pre-culturing is urgently needed. Based on PEG 200-enhanced recombinase polymerase amplification (RPA) and a refined Chelex-100 lysis method with HRP-catalyzed lateral flow immunoassay (LFIA), we developed an MCL-PRPA-HLFIA cascade assay system for detecting these genes in UTI samples. The refined Chelex-100 lysis method extracts target DNA from UTI samples in 20 min without high-speed centrifugation or pre-incubation of urine samples. Following optimization, the cascade detection system achieved an LOD of 10(2) CFU/mL with satisfactory specificity and could detect these genes in both simulated and actual UTI samples. It takes less than an hour to complete the process without the use of high-speed centrifuges or other specialized equipment, such as PCR amplifiers. The MCL-PRPA-HLFIA cascade assay system provides new ideas for the construction of rapid detection methods for pan-drug-resistant genes in clinical UTI samples and provides the necessary medication guidance for UTI treatment.202337047757
974230.8983BOCS: DNA k-mer content and scoring for rapid genetic biomarker identification at low coverage. A single, inexpensive diagnostic test capable of rapidly identifying a wide range of genetic biomarkers would prove invaluable in precision medicine. Previous work has demonstrated the potential for high-throughput, label-free detection of A-G-C-T content in DNA k-mers, providing an alternative to single-letter sequencing while also having inherent lossy data compression and massively parallel data acquisition. Here, we apply a new bioinformatics algorithm - block optical content scoring (BOCS) - capable of using the high-throughput content k-mers for rapid, broad-spectrum identification of genetic biomarkers. BOCS uses content-based sequence alignment for probabilistic mapping of k-mer contents to gene sequences within a biomarker database, resulting in a probability ranking of genes on a content score. Simulations of the BOCS algorithm reveal high accuracy for identification of single antibiotic resistance genes, even in the presence of significant sequencing errors (100% accuracy for no sequencing errors, and >90% accuracy for sequencing errors at 20%), and at well below full coverage of the genes. Simulations for detecting multiple resistance genes within a methicillin-resistant Staphylococcus aureus (MRSA) strain showed 100% accuracy at an average gene coverage of merely 0.515, when the k-mer lengths were variable and with 4% sequencing error within the k-mer blocks. Extension of BOCS to cancer and other genetic diseases met or exceeded the results for resistance genes. Combined with a high-throughput content-based sequencing technique, the BOCS algorithm potentiates a test capable of rapid diagnosis and profiling of genetic biomarkers ranging from antibiotic resistance to cancer and other genetic diseases.201931173943
509740.8981Comparing Graph Sample and Aggregation (SAGE) and Graph Attention Networks in the Prediction of Drug-Gene Associations of Extended-Spectrum Beta-Lactamases in Periodontal Infections and Resistance. INTRODUCTION: Gram-negative bacteria exhibit more antibiotic resistance than gram-positive bacteria due to their cell wall structure and composition differences. Porins, or protein channels in these bacteria, can allow small, hydrophilic antibiotics to diffuse, affecting their susceptibility. Mutations in porin protein genes can also impair antibiotic entry. Predicting drug-gene associations of extended-spectrum beta-lactamases (ESBLs) is crucial as they confer resistance to beta-lactam antibiotics, challenging the treatment of infections. This aids clinicians in selecting suitable treatments, optimizing drug usage, enhancing patient outcomes, and controlling antibiotic resistance in healthcare settings. Graph-based neural networks can predict drug-gene associations in periodontal infections and resistance. The aim of the study was to predict drug-gene associations of ESBLs in periodontal infections and resistance. METHODS: The study focuses on analyzing drug-gene associations using probes and drugs. The data was converted into graph language, assigning nodes and edges for drugs and genes. Graph neural networks (GNNs) and similar algorithms were implemented using Google Colab and Python. Cytoscape and CytoHubba are open-source software platforms used for network analysis and visualization. GNNs were used for tasks like node classification, link prediction, and graph-level prediction. Three graph-based models were used: graph convolutional network (GCN), Graph SAGE, and graph attention network (GAT). Each model was trained for 200 epochs using the Adam optimizer with a learning rate of 0.01 and a weight decay of 5e-4. RESULTS: The drug-gene association network has 57 nodes, 79 edges, and a 2.730 characteristic path length. Its structure, organization, and connectivity are analyzed using the GCN and Graph SAGE, which show high accuracy, precision, recall, and an F1-score of 0.94. GAT's performance metrics are lower, with an accuracy of 0.68, precision of 0.47, recall of 0.68, and F1-score of 0.56, suggesting that it may not be as effective in capturing drug-gene relationships. CONCLUSION: Compared to ESBLs, both GCN and Graph SAGE demonstrate excellent performance with accuracy, precision, recall, and an F1-score of 0.94. These results indicate that GCN and Graph SAGE are highly effective in predicting drug-gene associations related to ESBLs. GCN and Graph SAGE outperform GAT in predicting drug-gene associations for ESBLs. Improvements include data augmentation, regularization, and cross-validation. Ethical considerations, fairness, and open-source implementations are crucial for future research in precision periodontal treatment.202439347119
907650.8978ResiDB: An automated database manager for sequence data. The amount of publicly available DNA sequence data is drastically increasing, making it a tedious task to create sequence databases necessary for the design of diagnostic assays. The selection of appropriate sequences is especially challenging in genes affected by frequent point mutations such as antibiotic resistance genes. To overcome this issue, we have designed the webtool resiDB, a rapid and user-friendly sequence database manager for bacteria, fungi, viruses, protozoa, invertebrates, plants, archaea, environmental and whole genome shotgun sequence data. It automatically identifies and curates sequence clusters to create custom sequence databases based on user-defined input sequences. A collection of helpful visualization tools gives the user the opportunity to easily access, evaluate, edit, and download the newly created database. Consequently, researchers do no longer have to manually manage sequence data retrieval, deal with hardware limitations, and run multiple independent software tools, each having its own requirements, input and output formats. Our tool was developed within the H2020 project FAPIC aiming to develop a single diagnostic assay targeting all sepsis-relevant pathogens and antibiotic resistance mechanisms. ResiDB is freely accessible to all users through https://residb.ait.ac.at/.202133495705
147460.8977Simple, rapid, and cost-effective modified Carba NP test for carbapenemase detection among Gram-negative bacteria. PURPOSE: Detection of carbapenemases among Gram-negative bacteria (GNB) is important for both clinicians and infection control practitioners. The Clinical and Laboratory Standards Institute recommends Carba NP (CNP) as confirmatory test for carbapenemase production. The reagents required for CNP test are costly and hence the test cannot be performed on a routine basis. The present study evaluates modifications of CNP test for rapid detection of carbapenemases among GNB. MATERIALS AND METHODS: The GNB were screened for carbapenemase production using CNP, CarbAcineto NP (CANP), and modified CNP (mCNP) test. A multiplex polymerase chain reaction (PCR) was performed on all the carbapenem-resistant bacteria for carbapenemase genes. The results of three phenotypic tests were compared with PCR. RESULTS: A total of 765 gram negative bacteria were screened for carbapenem resistance. Carbapenem resistance was found in 144 GNB. The metallo-β-lactamases were most common carbapenemases followed by OXA-48-like enzymes. The CANP test was most sensitive (80.6%) for carbapenemases detection. The mCNP test was 62.1% sensitive for detection of carbapenemases. The mCNP, CNP, and CANP tests were equally sensitive (95%) for detection of NDM enzymes among Enterobacteriaceae. The mCNP test had poor sensitivity for detection of OXA-48-like enzymes. CONCLUSION: The mCNP test was rapid, cost-effective, and easily adoptable on routine basis. The early detection of carbapenemases using mCNP test will help in preventing the spread of multidrug-resistant organisms in the hospital settings.201728966495
582870.8975Target-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
148580.8973Evaluation of Verigene Blood Culture Test Systems for Rapid Identification of Positive Blood Cultures. The performance of molecular tests using the Verigene Gram-Positive and Gram-Negative Blood Culture nucleic acid tests (BC-GP and BC-GN, resp.; Naosphere, Northbrook, IL, USA) was evaluated for the identification of microorganisms detected from blood cultures. Ninety-nine blood cultures containing Gram-positive bacteria and 150 containing Gram-negative bacteria were analyzed using the BC-GP and BC-GN assays, respectively. Blood cultures were performed using the Bactec blood culture system (BD Diagnostic Systems, Franklin Lakes, NJ, USA) and conventional identification and antibiotic-susceptibility tests were performed using a MicroScan system (Siemens, West Sacramento, CA, USA). When a single strain of bacteria was isolated from the blood culture, Verigene assays correctly identified 97.9% (94/96) of Gram-positive bacteria and 93.8% (137/146) of Gram-negative bacteria. Resistance genes mecA and vanA were correctly detected by the BC-GP assay, while the extended-spectrum β-lactamase CTX-M and the carbapenemase OXA resistance gene were detected from 30 cases cultures by the BC-GN assay. The BC-GP and BC-GN assays showed high agreement with conventional identification and susceptibility tests. These tests are useful for rapid identification of microorganisms and the detection of clinically important resistance genes from positive Bactec blood cultures.201626904669
512090.8971ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Antimicrobial resistance (AMR) is one of the major threats to human and animal health worldwide, yet few high-throughput tools exist to analyse and predict the resistance of a bacterial isolate from sequencing data. Here we present a new tool, ARIBA, that identifies AMR-associated genes and single nucleotide polymorphisms directly from short reads, and generates detailed and customizable output. The accuracy and advantages of ARIBA over other tools are demonstrated on three datasets from Gram-positive and Gram-negative bacteria, with ARIBA outperforming existing methods.201729177089
1493100.8969Coexistence of blaKPC-2 and blaNDM-1 in one IncHI5 plasmid confers transferable carbapenem resistance from a clinical isolate of Klebsiella michiganensis in China. OBJECTIVES: This study firstly identified an IncHI5 plasmid pK254-KPC_NDM co-carrying two different class carbapenemase genes blaKPC-2 and blaNDM-1 in Klebsiella michiganensis K254. METHODS: The strain K254 was sequenced by high-throughput genome sequencing. A detailed genomic and phenotypic characterization of pK254-KPC_NDM was performed. RESULTS: pK254-KPC_NDM displayed the conserve IncHI5 backbone and carried a resistant accessory region: Tn1696-related transposon Tn7414 containing blaKPC-2 and blaNDM-1. A sequence comparison was applied to a collection of four Tn1696-related transposons (Tn7414-Tn7417) harbouring carbapenemase genes. For all these four transposons, the blaNDM-1 was carried by Tn125 derivatives within three different mobile genetic elements. Tn7414 further acquired another carbapenemase gene, blaKPC-2, because of the integration of the local blaKPC-2 genetic environment from Tn6296, resulting in the high-level carbapenem resistance of K. michiganensis K254. The conjugal transfer and plasmid stability experiments confirmed that pK254-KPC_NDM could be transferred intercellularly and keep the stable vertical inheritance in different bacteria, which would contribute to the further dissemination of multiple carbapenemase genes and enhance the adaption and survival of K. michiganensis under complex and diverse antimicrobial selection pressures. CONCLUSION: This study was the first to report the K. michiganensis isolate coharbouring blaKPC-2 and blaNDM-1 in the Tn1696-related transposon in IncHI5 plasmid. The emergence of novel transposons simultaneously carrying multiple carbapenemase genes might contribute to the further dissemination of high-level carbapenem resistance in the isolates of the hospital settings and pose new challenges for the treatment of nosocomial infection.202337714378
5070110.8968Sequence-specific DNA solid-phase extraction in an on-chip monolith: Towards detection of antibiotic resistance genes. Antibiotic resistance of bacteria is a growing problem and presents a challenge for prompt treatment in patients with sepsis. Currently used methods rely on culturing or amplification; however, these steps are either time consuming or suffer from interference issues. A microfluidic device was made from black polypropylene, with a monolithic column modified with a capture oligonucleotide for sequence selective solid-phase extraction of a complementary target from a lysate sample. Porous properties of the monolith allow flow and hybridization of a target complementary to the probe immobilized on the column surface. Good flow-through properties enable extraction of a 100μL sample and elution of target DNA in 12min total time. Using a fluorescently labeled target oligonucleotide related to Verona Integron-Mediated Metallo-β-lactamase it was possible to extract and detect a 1pM sample with 83% recovery. Temperature-mediated elution by heating above the duplex melting point provides a clean extract without any agents that interfere with base pairing, allowing various labeling methods or further downstream processing of the eluent. Further integration of this extraction module with a system for isolation and lysis of bacteria from blood, as well as combining with single-molecule detection should allow rapid determination of antibiotic resistance.201728734608
5831120.8966Development of a nucleic acid lateral flow immunoassay (NALFIA) for reliable, simple and rapid detection of the methicillin resistance genes mecA and mecC. The gene mecA and its homologue mecC confer methicillin resistance in Staphylococcus aureus and other staphylococci. Methicillin-resistant staphylococci (MRS) are considered resistant to all β-lactam antibiotics. To avoid the use of β-lactam antibiotics for the control of MRS infections, there is an urgent need for a fast and reliable screening assay for mecA and mecC that can easily be integrated in routine laboratory diagnostics. The aim of this study was the development of such a rapid detection method for methicillin resistance based on nucleic acid lateral flow immunoassay (NALFIA) technology. In NALFIA, the target sequences are PCR-amplified, immobilized via antigen-antibody interaction and finally visualized as distinct black bars resulting from neutravidin-labeled carbon particles via biotin-neutravidin interaction. A screening of 60 defined strains (MRS and non-target bacteria) and 28 methicillin-resistant S. aureus (MRSA) isolates from clinical samples was performed with PCR-NALFIA in comparison to PCR with subsequent gel electrophoresis (PCR-GE) and real-time PCR. While all samples were correctly identified with all assays, PCR-NALFIA was superior with respect to limits of detection. Moreover, this assay allowed for differentiation between mecA and mecC by visualizing the two alleles at different positions on NALFIA test stripes. However, since this test system only targets the mecA and mecC genes, it does not allow to determine in which staphylococcal species the mec gene is included. Requiring only a fraction of the time needed for cultural methods (i.e. the gold standard), the PCR-NALFIA presented here is easy to handle and can be readily integrated into laboratory diagnostics.201727569992
5825130.8966Polymerase Chain Reaction (PCR) Profiling of Extensively Drug-Resistant (XDR) Pathogenic Bacteria in Pulmonary Tuberculosis Patients. Introduction Pulmonary tuberculosis (TB) remains a global health concern, exacerbated by the emergence of extensively drug-resistant (XDR) strains of Mycobacterium tuberculosis. This study employs advanced molecular techniques, specifically polymerase chain reaction (PCR) profiling, to comprehensively characterize the genetic landscape of XDR pathogenic bacteria in patients diagnosed with pulmonary TB. The objective of the study is to elucidate the genes that are associated with drug resistance in pulmonary TB strains through the application of PCR and analyze specific genetic loci that contribute to the development of resistance against multiple drugs. Materials and methods A total of 116 clinical samples suspected of TB were collected from the tertiary healthcare setting of Saveetha Medical College and Hospitals for the identification of MTB, which includes sputum (n = 35), nasal swabs (n = 17), blood (n = 44), and bronchoalveolar lavage (BAL) (n = 20). The collected specimens were processed and subjected to DNA extraction. As per the protocol, reconstitution of the DNA pellet was carried out. The reconstituted DNA was stored at -20 °C for the PCR assay. From the obtained positive sample specimens, XDR pulmonary TB specimens were focused on the targeted genes, specifically the rpoB gene for rifampicin resistance, inhA, and katG gene for thepromoter region for isoniazid resistance. Results Out of a total of 116 samples obtained, 53 tested positive for pulmonary TB, indicative of a mycobacterial infection. Among these positive cases, 43 patients underwent treatment at a tertiary healthcare facility. Subsequently, a PCR assay was performed with the extracted DNA for the target genes rpoB, inhA, and katG. Specifically, 22 sputum samples exhibited gene expression for rpoB, inhA, and katG, while nine nasal swabs showed expression of the rpoB and inhA genes. Additionally, rpoB gene expression was detected in seven blood specimens, and both rpoB and inhA genes were expressed in five BAL samples. Conclusion The swift diagnosis and efficient treatment of XDR-TB can be facilitated by employing advanced and rapid molecular tests and oral medication regimens. Utilizing both newly developed and repurposed anti-TB drugs like pretomanid, bedaquiline, linezolid, and ethionamide. Adhering to these current recommendations holds promise for managing XDR-TB effectively. Nevertheless, it is significant to conduct well-designed clinical trials and studies to further evaluate the efficacy of new agents and shorter treatment regimens, thus ensuring continuous improvement in the management of this challenging condition.202438953074
2239140.8966The Direct Semi-Quantitative Detection of 18 Pathogens and Simultaneous Screening for Nine Resistance Genes in Clinical Urine Samples by a High-Throughput Multiplex Genetic Detection System. BACKGROUND: Urinary tract infections (UTIs) are one the most common infections. The rapid and accurate identification of uropathogens, and the determination of antimicrobial susceptibility, are essential aspects of the management of UTIs. However, existing detection methods are associated with certain limitations. In this study, a new urinary tract infection high-throughput multiplex genetic detection system (UTI-HMGS) was developed for the semi-quantitative detection of 18 pathogens and the simultaneously screening of nine resistance genes directly from the clinical urine sample within 4 hours. METHODS: We designed and optimized a multiplex polymerase chain reaction (PCR) involving fluorescent dye-labeled specific primers to detect 18 pathogens and nine resistance genes. The specificity of the UTI-HMGS was tested using standard strains or plasmids for each gene target. The sensitivity of the UTI-HMGS assay was tested by the detection of serial tenfold dilutions of plasmids or simulated positive urine samples. We also collected clinical urine samples and used these to perform urine culture and antimicrobial susceptibility testing (AST). Finally, all urine samples were detected by UTI-HMGS and the results were compared with both urine culture and Sanger sequencing. RESULTS: UTI-HMGS showed high levels of sensitivity and specificity for the detection of uropathogens when compared with culture and sequencing. In addition, ten species of bacteria and three species of fungi were detected semi-quantitatively to allow accurate discrimination of significant bacteriuria and candiduria. The sensitivity of the UTI-HMGS for the all the target genes could reach 50 copies per reaction. In total, 531 urine samples were collected and analyzed by UTI-HMGS, which exhibited high levels of sensitivity and specificity for the detection of uropathogens and resistance genes when compared with Sanger sequencing. The results from UTI-HMGS showed that the detection rates of 15 pathogens were significantly higher (P<0.05) than that of the culture method. In addition, there were 41(7.72%, 41/531) urine samples were positive for difficult-to-culture pathogens, which were missed detected by routine culture method. CONCLUSIONS: UTI-HMGS proved to be an efficient method for the direct semi-quantitative detection of 18 uropathogens and the simultaneously screening of nine antibiotic resistance genes in urine samples. The UTI-HMGS could represent an alternative method for the clinical detection and monitoring of antibiotic resistance.202133912478
2997150.8966Genomic Characterization of Multidrug-Resistant Escherichia coli BH100 Sub-strains. The rapid emergence of multidrug-resistant (MDR) bacteria is a global health problem. Mobile genetic elements like conjugative plasmids, transposons, and integrons are the major players in spreading resistance genes in uropathogenic Escherichia coli (UPEC) pathotype. The E. coli BH100 strain was isolated from the urinary tract of a Brazilian woman in 1974. This strain presents two plasmids carrying MDR cassettes, pBH100, and pAp, with conjugative and mobilization properties, respectively. However, its transposable elements have not been characterized. In this study, we attempted to unravel the factors involved in the mobilization of virulence and drug-resistance genes by assessing genomic rearrangements in four BH100 sub-strains (BH100 MG2014, BH100 MG2017, BH100L MG2017, and BH100N MG2017). Therefore, the complete genomes of the BH100 sub-strains were achieved through Next Generation Sequencing and submitted to comparative genomic analyses. Our data shows recombination events between the two plasmids in the sub-strain BH100 MG2017 and between pBH100 and the chromosome in BH100L MG2017. In both cases, IS3 and IS21 elements were detected upstream of Tn21 family transposons associated with MDR genes at the recombined region. These results integrated with Genomic island analysis suggest pBH100 might be involved in the spreading of drug resistance through the formation of resistance islands. Regarding pathogenicity, our results reveal that BH100 strain is closely related to UPEC strains and contains many IS3 and IS21-transposase-enriched genomic islands associated with virulence. This study concludes that those IS elements are vital for the evolution and adaptation of BH100 strain.202033584554
196160.8965A specialized citric acid cycle requiring succinyl-coenzyme A (CoA):acetate CoA-transferase (AarC) confers acetic acid resistance on the acidophile Acetobacter aceti. Microbes tailor macromolecules and metabolism to overcome specific environmental challenges. Acetic acid bacteria perform the aerobic oxidation of ethanol to acetic acid and are generally resistant to high levels of these two membrane-permeable poisons. The citric acid cycle (CAC) is linked to acetic acid resistance in Acetobacter aceti by several observations, among them the oxidation of acetate to CO2 by highly resistant acetic acid bacteria and the previously unexplained role of A. aceti citrate synthase (AarA) in acetic acid resistance at a low pH. Here we assign specific biochemical roles to the other components of the A. aceti strain 1023 aarABC region. AarC is succinyl-coenzyme A (CoA):acetate CoA-transferase, which replaces succinyl-CoA synthetase in a variant CAC. This new bypass appears to reduce metabolic demand for free CoA, reliance upon nucleotide pools, and the likely effect of variable cytoplasmic pH upon CAC flux. The putative aarB gene is reassigned to SixA, a known activator of CAC flux. Carbon overflow pathways are triggered in many bacteria during metabolic limitation, which typically leads to the production and diffusive loss of acetate. Since acetate overflow is not feasible for A. aceti, a CO(2) loss strategy that allows acetic acid removal without substrate-level (de)phosphorylation may instead be employed. All three aar genes, therefore, support flux through a complete but unorthodox CAC that is needed to lower cytoplasmic acetate levels.200818502856
5798170.8964Rapid identification of bacteria, mecA and van genes from blood cultures. The Genotype technology, a quick molecular genetic assay based on DNA multiplex amplification with biotinylated primers followed by hybridization to membrane bound probes, complies with the requirements for a fast diagnosis of sepsis. We evaluated the new Genotype BC Gram-negative and Gram-positive test kits (Hain Life Science, Germany) which respectively allow for the identification of 15 species of Gram-negative (GN) rods, and the identification of 17 Gram-positive (GP) bacteria species together with the determination of methicillin and vancomycin resistance (mecA and van genes). The study was performed on 60 positive blood cultures from BacT/ALERT bottles (aerobic, anaerobic and pediatric bottles). First, a Gram stain was carried out to select between Genotype BC GP or GN test, then identification were performed by the Genotype BC tests and by biochemical conventional tests after subculture and phenotypic susceptibility determination. The operating procedure was very easy to carry out and required a small amount of starting material (5 to 10 microL of blood culture). The results were available within 4.5 hours. For all the blood cultures, the Genotype BC results correlated with the biochemical identification and phenotypic antibiotics susceptibility. According to our results, this DNA strip technology based assay can easily be incorporated into routine diagnosis.200717913394
5827180.8964Duplex dPCR System for Rapid Identification of Gram-Negative Pathogens in the Blood of Patients with Bloodstream Infection: A Culture-Independent Approach. Early and accurate detection of pathogens is important to improve clinical outcomes of bloodstream infections (BSI), especially in the case of drug-resistant pathogens. In this study, we aimed to develop a culture-independent digital PCR (dPCR) system for multiplex detection of major sepsiscausing gram-negative pathogens and antimicrobial resistance genes using plasma DNA from BSI patients. Our duplex dPCR system successfully detected nine targets (five bacteria-specific targets and four antimicrobial resistance genes) through five reactions within 3 hours. The minimum detection limit was 50 ag of bacterial DNA, suggesting that 1 CFU/ml of bacteria in the blood can be detected. To validate the clinical applicability, cell-free DNA samples from febrile patients were tested with our system and confirmed high consistency with conventional blood culture. This system can support early identification of some drug-resistant gram-negative pathogens, which can help improving treatment outcomes of BSI.202134528911
5824190.8963Evaluation of a micro/nanofluidic chip platform for the high-throughput detection of bacteria and their antibiotic resistance genes in post-neurosurgical meningitis. BACKGROUND: Post-neurosurgical meningitis (PNM) is one of the most severe hospital-acquired infections worldwide, and a large number of pathogens, especially those possessing multi-resistance genes, are related to these infections. Existing methods for detecting bacteria and measuring their response to antibiotics lack sensitivity and stability, and laboratory-based detection methods are inconvenient, requiring at least 24h to complete. Rapid identification of bacteria and the determination of their susceptibility to antibiotics are urgently needed, in order to combat the emergence of multi-resistant bacterial strains. METHODS: This study evaluated a novel, fast, and easy-to-use micro/nanofluidic chip platform (MNCP), which overcomes the difficulties of diagnosing bacterial infections in neurosurgery. This platform can identify 10 genus or species targets and 13 genetic resistance determinants within 1h, and it is very simple to operate. A total of 108 bacterium-containing cerebrospinal fluid (CSF) cultures were tested using the MNCP for the identification of bacteria and determinants of genetic resistance. The results were compared to those obtained with conventional identification and antimicrobial susceptibility testing methods. RESULTS: For the 108 CSF cultures, the concordance rate between the MNCP and the conventional identification method was 94.44%; six species attained 100% consistency. For the production of carbapenemase- and extended-spectrum beta-lactamase (ESBL)-related antibiotic resistance genes, both the sensitivity and specificity of the MNCP tests were high (>90.0%) and could fully meet the requirements of clinical diagnosis. CONCLUSIONS: The MNCP is fast, accurate, and easy to use, and has great clinical potential in the treatment of post-neurosurgical meningitis.201829559366