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493800.9109Optical maps of plasmids as a proxy for clonal spread of MDR bacteria: a case study of an outbreak in a rural Ethiopian hospital. OBJECTIVES: MDR bacteria have become a prevailing health threat worldwide. We here aimed to use optical DNA mapping (ODM) as a rapid method to trace nosocomial spread of bacterial clones and gene elements. We believe that this method has the potential to be a tool of pivotal importance for MDR control. METHODS: Twenty-four Escherichia coli samples of ST410 from three different wards were collected at an Ethiopian hospital and their plasmids were analysed by ODM. Plasmids were specifically digested with Cas9 targeting the antibiotic resistance genes, stained by competitive binding and confined in nanochannels for imaging. The resulting intensity profiles (barcodes) for each plasmid were compared to identify potential clonal spread of resistant bacteria. RESULTS: ODM demonstrated that a large fraction of the patients carried bacteria with a plasmid of the same origin, carrying the ESBL gene blaCTX-M-15, suggesting clonal spread. The results correlate perfectly with core genome (cg)MLST data, where bacteria with the same plasmid also had very similar cgMLST profiles. CONCLUSIONS: ODM is a rapid discriminatory method for identifying plasmids and antibiotic resistance genes. Long-range deletions/insertions, which are challenging for short-read next-generation sequencing, can be easily identified and used to trace bacterial clonal spread. We propose that plasmid typing can be a useful tool to identify clonal spread of MDR bacteria. Furthermore, the simplicity of the method enables possible future application in low- and middle-income countries.202032653928
147410.9093Simple, 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
974120.9088ARGai 1.0: A GAN augmented in silico approach for identifying resistant genes and strains in E. coli using vision transformer. The emergence of infectious disease and antibiotic resistance in bacteria like Escherichia coli (E. coli) shows the necessity for novel computational techniques for identifying essential genes that contribute to resistance. The task of identifying resistant strains and multi-drug patterns in E. coli is a major challenge with whole genome sequencing (WGS) and next-generation sequencing (NGS) data. To address this issue, we suggest ARGai 1.0 a deep learning architecture enhanced with generative adversarial networks (GANs). We mitigate data scarcity difficulties by augmenting limited experimental datasets with synthetic data generated by GANs. Our in-silico method (augmentation with feature selection) improves the identification of resistance genes in E. coli by using feature extraction techniques to identify valuable features from actual and GAN-generated data. Employing comprehensive validation, we exhibit the effectiveness of our ARGai 1.0 in precisely identifying the informative and resistant genes. In addition, our ARGai 1.0 identifies the resistant strains with a classification accuracy of 98.96 % on Deep Convolutional Generative Adversarial Network (DCGAN) augmented data. Additionally, ARGai 1.0 achieves more than 98 % of sensitivity and specificity. We also benchmark our ARGai 1.0 with several state-of-the-art AI models for resistant strain classification. In the fight against antibiotic resistance, ARGai 1.0 offers a promising avenue for computational genomics. With implications for research and clinical practice, this work shows the potential of deep networks with GAN augmentation as a practical and successful method for gene identification in E. coli.202539813877
999530.9086Direct fluorescence in situ hybridization (FISH) in Escherichia coli with a target-specific quantum dot-based molecular beacon. Quantum dots (QDs) are inorganic fluorescent nanocrystals with excellent properties such as tunable emission spectra and photo-bleaching resistance compared with organic dyes, which make them appropriate for applications in molecular beacons. In this work, quantum dot-based molecular beacons (QD-based MBs) were fabricated to specifically detect β-lactamase genes located in pUC18 which were responsible for antibiotic resistance in bacteria Escherichia coli (E. coli) DH5α. QD-based MBs were constructed by conjugating mercaptoacetic acid-quantum dots (MAA-QDs) with black hole quencher 2 (BHQ2) labeled thiol DNA vial metal-thiol bonds. Two types of molecular beacons, double-strands beacons and hairpin beacons, were observed in product characterization by gel electrophoresis. Using QD-based MBs, one-step FISH in tiny bacteria DH5α was realized for the first time. QD-based MBs retained their bioactivity when hybridizing with complementary target DNA, which showed excellent advantages of eliminating background noise caused by adsorption of non-specific bioprobes and achieving clearer focus of genes in plasmids pUC18, and capability of bacterial cell penetration and signal specificity in one-step in situ hybridization.201020729070
512540.9084Do we still need Illumina sequencing data? Evaluating Oxford Nanopore Technologies R10.4.1 flow cells and the Rapid v14 library prep kit for Gram negative bacteria whole genome assemblies. The best whole genome assemblies are currently built from a combination of highly accurate short-read sequencing data and long-read sequencing data that can bridge repetitive and problematic regions. Oxford Nanopore Technologies (ONT) produce long-read sequencing platforms and they are continually improving their technology to obtain higher quality read data that is approaching the quality obtained from short-read platforms such as Illumina. As these innovations continue, we evaluated how much ONT read coverage produced by the Rapid Barcoding Kit v14 (SQK-RBK114) is necessary to generate high-quality hybrid and long-read-only genome assemblies for a panel of carbapenemase-producing Enterobacterales bacterial isolates. We found that 30× long-read coverage is sufficient if Illumina data are available, and that more (at least 100× long-read coverage is recommended for long-read-only assemblies. Illumina polishing is still improving single nucleotide variants (SNVs) and INDELs in long-read-only assemblies. We also examined if antimicrobial resistance genes could be accurately identified in long-read-only data, and found that Flye assemblies regardless of ONT coverage detected >96% of resistance genes at 100% identity and length. Overall, the Rapid Barcoding Kit v14 and long-read-only assemblies can be an optimal sequencing strategy (i.e., plasmid characterization and AMR detection) but finer-scale analyses (i.e., SNV) still benefit from short-read data.202438354391
221650.9083Ultrafast detection of β-lactamase resistance in Klebsiella pneumoniae from blood culture by nanopore sequencing. Aim: This study aimed to assess the ultra-fast method using MinION™ sequencing for rapid identification of β-lactamase-producing Klebsiella pneumoniae clinical isolates from positive blood cultures. Methods: Spiked-blood positive blood cultures were extracted using the ultra-fast method and automated DNA extraction for MinION sequencing. Raw reads were analyzed for β-lactamase resistance genes. Multilocus sequence typing and β-lactamase variant characterization were performed after assembly. Results: The ultra-fast method identified clinically relevant β-lactamase resistance genes in less than 1 h. Multilocus sequence typing and β-lactamase variant characterization required 3-6 h. Sequencing quality showed no direct correlation with pore number or DNA concentration. Conclusion: Nanopore sequencing, specifically the ultra-fast method, is promising for the rapid diagnosis of bloodstream infections, facilitating timely identification of multidrug-resistant bacteria in clinical samples.202337850345
908360.9081ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences. BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identification of ARGs, particularly from high-throughput sequencing data of the specimens, is the state-of-the-art method for comprehensively monitoring their spread and evolution. Current computational methods to identify ARGs mainly rely on alignment-based sequence similarities with known ARGs. Such approaches are limited by choice of reference databases and may potentially miss novel ARGs. The similarity thresholds are usually simple and could not accommodate variations across different gene families and regions. It is also difficult to scale up when sequence data are increasing. RESULTS: In this study, we developed ARGNet, a deep neural network that incorporates an unsupervised learning autoencoder model to identify ARGs and a multiclass classification convolutional neural network to classify ARGs that do not depend on sequence alignment. This approach enables a more efficient discovery of both known and novel ARGs. ARGNet accepts both amino acid and nucleotide sequences of variable lengths, from partial (30-50 aa; 100-150 nt) sequences to full-length protein or genes, allowing its application in both target sequencing and metagenomic sequencing. Our performance evaluation showed that ARGNet outperformed other deep learning models including DeepARG and HMD-ARG in most of the application scenarios especially quasi-negative test and the analysis of prediction consistency with phylogenetic tree. ARGNet has a reduced inference runtime by up to 57% relative to DeepARG. CONCLUSIONS: ARGNet is flexible, efficient, and accurate at predicting a broad range of ARGs from the sequencing data. ARGNet is freely available at https://github.com/id-bioinfo/ARGNet , with an online service provided at https://ARGNet.hku.hk . Video Abstract.202438725076
907570.9081CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter. BACKGROUND: The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the growth of data at a faster rate than can be effectively analyzed and critical gaps in bioinformatics knowledge. RESULTS: To address both issues, CamPype was developed as a new bioinformatics workflow for the genomics analysis of sequencing data of bacteria, especially Campylobacter, which is the main cause of gastroenteritis worldwide making a negative impact on the economy of the public health systems. CamPype allows fully customization of stages to run and tools to use, including read quality control filtering, read contamination, reads extension and assembly, bacterial typing, genome annotation, searching for antibiotic resistance genes, virulence genes and plasmids, pangenome construction and identification of nucleotide variants. All results are processed and resumed in an interactive HTML report for best data visualization and interpretation. CONCLUSIONS: The minimal user intervention of CamPype makes of this workflow an attractive resource for microbiology laboratories with no expertise in bioinformatics as a first line method for bacterial typing and epidemiological analyses, that would help to reduce the costs of disease outbreaks, or for comparative genomic analyses. CamPype is publicly available at https://github.com/JoseBarbero/CamPype .202337474912
222380.9081Evaluation of a new real-time PCR assay (Check-Direct CPE) for rapid detection of KPC, OXA-48, VIM, and NDM carbapenemases using spiked rectal swabs. To prevent the spread of carbapenemase-producing bacteria, a fast and accurate detection of patients carrying these bacteria is extremely important. The Check-Direct CPE assay (Check-Points, Wageningen, The Netherlands) is a new multiplex real-time PCR assay, which has been developed to detect and differentiate between the most prevalent carbapenemase genes encountered in Enterobacteriaceae (blaKPC, blaOXA-48, blaVIM, and blaNDM) directly from rectal swabs. Evaluation of this assay using 83 non-duplicate isolates demonstrated 100% sensitivity and specificity and the correct identification of the carbapenemase gene(s) present in all carbapenemase-producing isolates. Moreover, the limit of detection (LoD) of the real-time PCR assay in spiked rectal swabs was determined and showed comparable LoDs with the ChromID CARBA agar. With an excellent performance on clinical isolates and spiked rectal swabs, this assay appeared to be an accurate and rapid method to detect blaKPC, blaOXA-48, blaVIM, and blaNDM genes directly from a rectal screening swab.201324135412
247790.9081Evaluation 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
5882100.9079PCR Analysis Methods for Detection and Identification of Beer-Spoilage Lactic Acid Bacteria. Polymerase chain reaction (PCR) analysis enables rapid and accurate detection of beer-spoilage lactic acid bacteria (LAB). Hop resistance genes, horA and horC, are utilized as genetic markers to determine the spoilage ability of LAB strains. PCR analysis of horA and horC, combined with multiplex PCR methods of 12 beer-spoilage species, enables simultaneous and comprehensive detection easily and inexpensively.201930506252
5123110.9077Ultrafast and Cost-Effective Pathogen Identification and Resistance Gene Detection in a Clinical Setting Using Nanopore Flongle Sequencing. Rapid bacterial identification and antimicrobial resistance gene (ARG) detection are crucial for fast optimization of antibiotic treatment, especially for septic patients where each hour of delayed antibiotic prescription might have lethal consequences. This work investigates whether the Oxford Nanopore Technology's (ONT) Flongle sequencing platform is suitable for real-time sequencing directly from blood cultures to identify bacteria and detect resistance-encoding genes. For the analysis, we used pure bacterial cultures of four clinical isolates of Escherichia coli and Klebsiella pneumoniae and two blood samples spiked with either E. coli or K. pneumoniae that had been cultured overnight. We sequenced both the whole genome and plasmids isolated from these bacteria using two different sequencing kits. Generally, Flongle data allow rapid bacterial ID and resistome detection based on the first 1,000-3,000 generated sequences (10 min to 3 h from the sequencing start), albeit ARG variant identification did not always correspond to ONT MinION and Illumina sequencing-based data. Flongle data are sufficient for 99.9% genome coverage within at most 20,000 (clinical isolates) or 50,000 (positive blood cultures) sequences generated. The SQK-LSK110 Ligation kit resulted in higher genome coverage and more accurate bacterial identification than the SQK-RBK004 Rapid Barcode kit.202235369431
5068120.9076Ultrasensitive Label-Free Detection of Unamplified Multidrug-Resistance Bacteria Genes with a Bimodal Waveguide Interferometric Biosensor. Infections by multidrug-resistant bacteria are becoming a major healthcare emergence with millions of reported cases every year and an increasing incidence of deaths. An advanced diagnostic platform able to directly detect and identify antimicrobial resistance in a faster way than conventional techniques could help in the adoption of early and accurate therapeutic interventions, limiting the actual negative impact on patient outcomes. With this objective, we have developed a new biosensor methodology using an ultrasensitive nanophotonic bimodal waveguide interferometer (BiMW), which allows a rapid and direct detection, without amplification, of two prevalent and clinically relevant Gram-negative antimicrobial resistance encoding sequences: the extended-spectrum betalactamase-encoding gene blaCTX-M-15 and the carbapenemase-encoding gene blaNDM-5 We demonstrate the extreme sensitivity and specificity of our biosensor methodology for the detection of both gene sequences. Our results show that the BiMW biosensor can be employed as an ultrasensitive (attomolar level) and specific diagnostic tool for rapidly (less than 30 min) identifying drug resistance. The BiMW nanobiosensor holds great promise as a powerful tool for the control and management of healthcare-associated infections by multidrug-resistant bacteria.202033086716
9076130.9075ResiDB: 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
538140.9075The biochemical and genetic basis for high frequency thiomethyl galactoside resistance in lambda,lambdadg lysogens of Escherichia coli. In a culture of Escherichia coli K12 gal (lambdadg), cells which form large colonies on agar plates containing galactose and thiomethyl beta-D-galactoside (TMG) appear at high frequency. These clones are resistant to growth inhibition by TMG on galactose minimal medium. Biochemical studies of the steady-state levels of galactokinase and UDPgalactose 4-epimerase suggest that the resistant clones have extra copies of the genes for the galactose-metabolizing enzymes. The mutation for TMG resistance is not located in either the bacterial or the bacteriophage genome, but is probably due to an aberrant association between cell and prophage DNA. Mapping the TMG-resistant characteristic by phage P1 indicates that TMG-resistant bacteria posses at least two GAL+ OPERONS, ONE OF WHICH IS COTRANSDUCIBLe with bio+. In addition, TMG-resistant bacteria behave like lambdadg polylysogens when challenged with the phage lambdaI90c17. From these genetic experiments we conclude that TMG-resistant bacteria arise by duplication of the lambdadg prophage. Finally, gal+ bacteria which carry a single, additional, lambdadg prophage are TMG-resistant. TMG resistance is probably a gal+ gene dosage effect.1978344832
5828150.9075Target-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
2238160.9074Rapid detection of carbapenem resistance among gram-negative organisms directly from positive blood culture bottles. BACKGROUND: Carbapenemase producing gram-negative bacteria (GNB) has become a huge problem in majority of tertiary care centers worldwide. They are associated with very high morbidity and mortality rates, especially when they cause invasive infections. Therefore, rapid detection of these organisms is very important for prompt and adequate antibiotic therapy as well as infection control. The aim of this study was rapid detection of carbapenemase genes and thereby likely carbapenem resistance, 24-48 hours in advance, directly from the positive-flagged blood culture bottles using CHROMagar and Xpert® Carba-R. METHODS: Aspirate from positively flagged blood culture bottles was subjected to differential centrifuge. All gram-negative bacilli on gram stain from the deposit were processed in Xpert® Carba-R and inoculated on CHROMagar. The presence of genes and growth on CHROMagar was compared with carbapenem resistance on VITEK-2 Compact. RESULTS: A total of 119 GNB isolates were processed. One or more of the carbapenemase genes were detected in 80 isolates. On comparison with VITEK-2 result, 92 samples showed concordance for carbapenem resistance 48 hours in advance. There was discordance in 21 isolates with 12 major errors and 09 minor errors. The sensitivity of direct Xpert® Carba-R test for rapid detection of carbapenem resistance, 48 hours in advance, was 81.42%. The sensitivity of direct CHROMagar test for accurate detection of carbapenem resistance, 24 hours in advance, was 92.06%. CONCLUSION: The ability to detect carbapenem resistance with very high accuracy, 48 hours in advance, helps in appropriate antibiotic therapy and implementation of effective infection control practices.202337193528
1485170.9074Evaluation 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
3771180.9072RFPlasmid: predicting plasmid sequences from short-read assembly data using machine learning. Antimicrobial-resistance (AMR) genes in bacteria are often carried on plasmids and these plasmids can transfer AMR genes between bacteria. For molecular epidemiology purposes and risk assessment, it is important to know whether the genes are located on highly transferable plasmids or in the more stable chromosomes. However, draft whole-genome sequences are fragmented, making it difficult to discriminate plasmid and chromosomal contigs. Current methods that predict plasmid sequences from draft genome sequences rely on single features, like k-mer composition, circularity of the DNA molecule, copy number or sequence identity to plasmid replication genes, all of which have their drawbacks, especially when faced with large single-copy plasmids, which often carry resistance genes. With our newly developed prediction tool RFPlasmid, we use a combination of multiple features, including k-mer composition and databases with plasmid and chromosomal marker proteins, to predict whether the likely source of a contig is plasmid or chromosomal. The tool RFPlasmid supports models for 17 different bacterial taxa, including Campylobacter, Escherichia coli and Salmonella, and has a taxon agnostic model for metagenomic assemblies or unsupported organisms. RFPlasmid is available both as a standalone tool and via a web interface.202134846288
5069190.9072MC-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