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509700.9880Comparing 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
523610.9879Genome characterization of a multi-drug resistant Escherichia coli strain, L1PEag1, isolated from commercial cape gooseberry fruits (Physalis peruviana L.). INTRODUCTION: Foodborne infections, which are frequently linked to bacterial contamination, are a serious concern to public health on a global scale. Whether agricultural farming practices help spread genes linked to antibiotic resistance in bacteria associated with humans or animals is a controversial question. METHODS: This study applied a long-read Oxford Nanopore MinION-based sequencing to obtain the complete genome sequence of a multi-drug resistant Escherichia coli strain (L1PEag1), isolated from commercial cape gooseberry fruits (Physalis peruviana L.) in Ecuador. Using different genome analysis tools, the serotype, Multi Locus Sequence Typing (MLST), virulence genes, and antimicrobial resistance (AMR) genes of the L1PEag1 isolate were determined. Additionally, in vitro assays were performed to demonstrate functional genes. RESULTS: The complete genome sequence of the L1PEag1 isolate was assembled into a circular chromosome of 4825.722 Kbp and one plasmid of 3.561 Kbp. The L1PEag1 isolate belongs to the B2 phylogroup, sequence type ST1170, and O1:H4 serotype based on in silico genome analysis. The genome contains 4,473 genes, 88 tRNA, 8 5S rRNA, 7 16S rRNA, and 7 23S rRNA. The average GC content is 50.58%. The specific annotation consisted of 4,439 and 3,723 genes annotated with KEEG and COG respectively, 3 intact prophage regions, 23 genomic islands (GIs), and 4 insertion sequences (ISs) of the ISAs1 and IS630 families. The L1PEag1 isolate carries 25 virulence genes, and 4 perfect and 51 strict antibiotic resistant gene (ARG) regions based on VirulenceFinder and RGI annotation. Besides, the in vitro antibiotic profile indicated resistance to kanamycin (K30), azithromycin (AZM15), clindamycin (DA2), novobiocin (NV30), amikacin (AMK30), and other antibiotics. The L1PEag1 isolate was predicted as a human pathogen, matching 464 protein families (0.934 likelihood). CONCLUSION: Our work emphasizes the necessity of monitoring environmental antibiotic resistance, particularly in commercial settings to contribute to develop early mitigation techniques for dealing with resistance diffusion.202439104589
511620.9878Prediction of Antimicrobial Resistance in Gram-Negative Bacteria From Whole-Genome Sequencing Data. BACKGROUND: Early detection of antimicrobial resistance in pathogens and prescription of more effective antibiotics is a fast-emerging need in clinical practice. High-throughput sequencing technology, such as whole genome sequencing (WGS), may have the capacity to rapidly guide the clinical decision-making process. The prediction of antimicrobial resistance in Gram-negative bacteria, often the cause of serious systemic infections, is more challenging as genotype-to-phenotype (drug resistance) relationship is more complex than for most Gram-positive organisms. METHODS AND FINDINGS: We have used NCBI BioSample database to train and cross-validate eight XGBoost-based machine learning models to predict drug resistance to cefepime, cefotaxime, ceftriaxone, ciprofloxacin, gentamicin, levofloxacin, meropenem, and tobramycin tested in Acinetobacter baumannii, Escherichia coli, Enterobacter cloacae, Klebsiella aerogenes, and Klebsiella pneumoniae. The input is the WGS data in terms of the coverage of known antibiotic resistance genes by shotgun sequencing reads. Models demonstrate high performance and robustness to class imbalanced datasets. CONCLUSION: Whole genome sequencing enables the prediction of antimicrobial resistance in Gram-negative bacteria. We present a tool that provides an in silico antibiogram for eight drugs. Predictions are accompanied with a reliability index that may further facilitate the decision making process. The demo version of the tool with pre-processed samples is available at https://vancampn.shinyapps.io/wgs2amr/. The stand-alone version of the predictor is available at https://github.com/pieterjanvc/wgs2amr/.202032528441
604530.9876Lacticaseicin 30 and Colistin as a Promising Antibiotic Formulation against Gram-Negative β-Lactamase-Producing Strains and Colistin-Resistant Strains. Antimicrobial resistance is a global health concern across the world and it is foreseen to swell if no actions are taken now. To help curbing this well announced crisis different strategies are announced, and these include the use of antimicrobial peptides (AMP), which are remarkable molecules known for their killing activities towards pathogenic bacteria. Bacteriocins are ribosomally synthesized AMP produced by almost all prokaryotic lineages. Bacteriocins, unlike antibiotics, offer a set of advantages in terms of cytotoxicity towards eukaryotic cells, their mode of action, cross-resistance and impact of microbiota content. Most known bacteriocins are produced by Gram-positive bacteria, and specifically by lactic acid bacteria (LAB). LAB-bacteriocins were steadily reported and characterized for their activity against genetically related Gram-positive bacteria, and seldom against Gram-negative bacteria. The aim of this study is to show that lacticaseicin 30, which is one of the bacteriocins produced by Lacticaseibacillus paracasei CNCM I-5369, is active against Gram-negative clinical strains (Salmonella enterica Enteritidis H10, S. enterica Typhimurium H97, Enterobacter cloacae H51, Escherichia coli H45, E. coli H51, E. coli H66, Klebsiella oxytoca H40, K. pneumoniae H71, K. variicola H77, K. pneumoniae H79, K. pneumoniae H79), whereas antibiotics failed. In addition, lacticaseicin 30 and colistin enabled synergistic interactions towards the aforementioned target Gram-negative clinical strains. Further, the combinations of lacticaseicin 30 and colistin prompted a drastic downregulation of mcr-1 and mcr-9 genes, which are associated with the colistin resistance phenotypes of these clinical strains. This report shows that lacticaseicin 30 is active against Gram-negative clinical strains carrying a rainbow of mcr genes, and the combination of these antimicrobials constitutes a promising therapeutic option that needs to be further exploited.202135052897
512540.9876Do 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
188250.9875Genomic Characterization of Multidrug-Resistant Pathogenic Enteric Bacteria from Healthy Children in Osun State, Nigeria. Antimicrobial resistance (AMR) is responsible for the spread and persistence of bacterial infections. Surveillance of AMR in healthy individuals is usually not considered, though these individuals serve as reservoirs for continuous disease transmission. Therefore, it is essential to conduct epidemiological surveillance of AMR in healthy individuals to fully understand the dynamics of AMR transmission in Nigeria. Thirteen multidrug-resistant Citrobacter spp., Enterobacter spp., Klebsiella pneumoniae, and Escherichia coli isolated from stool samples of healthy children were subjected to whole genome sequencing (WGS) using Illumina and Oxford nanopore sequencing platforms. A bioinformatics analysis revealed antimicrobial resistance genes such as the pmrB_Y358N gene responsible for colistin resistance detected in E. coli ST219, virulence genes such as senB, and ybtP&Q, and plasmids in the isolates sequenced. All isolates harbored more than three plasmid replicons of either the Col and/or Inc type. Plasmid reconstruction revealed an integrated tetA gene, a toxin production caa gene in two E. coli isolates, and a cusC gene in K. quasivariicola ST3879, which induces neonatal meningitis. The global spread of AMR pathogenic enteric bacteria is of concern, and surveillance should be extended to healthy individuals, especially children. WGS for epidemiological surveillance will improve the detection of AMR pathogens for management and control.202438543556
523560.9874Draft genome sequences of rare Lelliottia nimipressuralis strain MEZLN61 and two Enterobacter kobei strains MEZEK193 and MEZEK194 carrying mobile colistin resistance gene mcr-9 isolated from wastewater in South Africa. OBJECTIVES: Antimicrobial-resistant bacteria of the order Enterobacterales are emerging threats to global public and animal health, leading to morbidity and mortality. The emergence of antimicrobial-resistant, livestock-associated pathogens is a great public health concern. The genera Enterobacter and Lelliottia are ubiquitous, facultatively anaerobic, motile, non-spore-forming, rod-shaped Gram-negative bacteria belonging to the Enterobacteriaceae family and include pathogens of public health importance. Here, we report the first draft genome sequences of a rare Lelliottia nimipressuralis strain MEZLN61 and two Enterobacter kobei strains MEZEK193 and MEZEK194 in Africa. METHODS: The bacteria were isolated from environmental wastewater samples. Bacteria were cultured on nutrient agar, and the pure cultures were subjected to whole-genome sequencing. Genomic DNA was sequenced using an Illumina MiSeq platform. Generated reads were trimmed and subjected to de novo assembly. The assembled contigs were analysed for virulence genes, antimicrobial resistance genes, and extra-chromosomal plasmids, and multilocus sequence typing was performed. To compare the sequenced strains with other, previously sequenced E. kobei and L. nimipressuralis strains, available raw read sequences were downloaded, and all sequence files were treated identically to generate core genome bootstrapped maximum likelihood phylogenetic trees. RESULTS: Whole-genome sequencing analyses identified strain MEZLN61 as L. nimipressuralis and strains MEZEK193 and MEZEK194 as E. kobei. MEZEK193 and MEZEK194 carried genes encoding resistance to fosfomycin (fosA), beta-lactam antibiotics (bla(ACT-9)), and colistin (mcr-9). Additionally, MEZEK193 harboured nine different virulence genes, while MEZEK194 harboured eleven different virulence genes. The phenotypic analysis showed that L. nimipressuralis strain MEZLN61 was susceptible to colistin (2 μg/mL), while E. kobei MEZEK193 (64 μg/mL) and MEZEK194 (32 μg/mL) were resistant to colistin. CONCLUSION: The genome sequences of strains L. nimipressuralis MEZLN6, E. kobei MEZEK193, and E. kobei MEZEK194 will serve as a reference point for molecular epidemiological studies of L. nimipressuralis and E. kobei in Africa. In addition, this study provides an in-depth analysis of the genomic structure and offers important information that helps clarify the pathogenesis and antimicrobial resistance of L. nimipressuralis and E. kobei. The detection of mcr-9, which is associated with very low-level colistin resistance in Enterobacter species, is alarming and may indicate the undetected dissemination of mcr genes in bacteria of the order Enterobacterales. Continuous monitoring and surveillance of the prevalence of mcr genes and their associated phenotypic changes in clinically important pathogens and environmentally associated bacteria is necessary to control and prevent the spread of colistin resistance.202336948496
259970.9873Evaluation of whole-genome sequencing protocols for detection of antimicrobial resistance, virulence factors and mobile genetic elements in antimicrobial-resistant bacteria. Introduction. Antimicrobial resistance (AMR) poses a critical threat to global health, underscoring the need for rapid and accurate diagnostic tools. Methicillin-resistant Staphylococcus aureus (MRSA) and extended-spectrum beta-lactamase (ESBL)-producing Klebsiella pneumoniae (ESBL-Kp) are listed among the World Health Organization's priority pathogens.Hypothesis. A rapid nanopore-based protocol can accurately and efficiently detect AMR genes, virulence factors (VFs) and mobile genetic elements (MGEs) in MRSA and ESBL-Kp, offering performance comparable to or superior to traditional sequencing methods.Aim. Evaluate whole-genome sequencing (WGS) protocols for detecting AMR genes, VFs and MGEs in MRSA and ESBL-Kp, to identify the most accurate and efficient tool for pathogen profiling.Methodology. Five distinct WGS protocols, including a rapid nanopore-based protocol (ONT20h) and four slower sequencing methods, were evaluated for their effectiveness in detecting genetic markers. The protocols' performances were compared across AMR genes, VFs and MGEs. Additionally, phenotypic antimicrobial susceptibility testing was performed to assess concordance with the genomic findings.Results. Compared to four slower sequencing protocols, the rapid nanopore-based protocol (ONT20h) demonstrated comparable or superior performance in AMR gene detection and equivalent VF identification. Although MGE detection varied among protocols, ONT20h showed a high level of agreement with phenotypic antimicrobial susceptibility testing.Conclusion. The findings highlight the potential of rapid WGS as a valuable tool for clinical microbiology, enabling timely implementation of infection control measures and informed therapeutic decisions. However, further studies are required to optimize the clinical application of this technology, considering costs, availability of bioinformatics tools and quality of reference databases.202540105741
188380.9873Whole genome sequence of colistin-resistant Escherichia coli from western India. BACKGROUND: With virtually dried out new antibiotic discovery pipeline, emergence and spread of antimicrobial resistance is a cause for global concern. Colistin, a cyclic polypeptide antibiotic, often regarded as last resort for multi drug resistance gram-negative bacteria, is also rendered ineffective by horizontal transfer of resistance genes. Surveillance of colistin resistance in GNB is essential to ascertain molecular epidemiology. METHODS: Whole genome sequencing (WGS) of an unusual colistin resistant urinary isolate of Escherichia coli was performed using Illumina MiSeq platform using 2x250bp V2 chemistry by following the manufactures protocol (Illumina Inc. USA). Multiple web-based bio-informatic tools were utilized to ascertain antibiotic resistant genes. RESULTS: An approximate 5.4 Mb of genome of the urinary isolate AFMC_UC19 was sequenced successfully. Mobile colistin resistance gene (mcr) on the plasmid responsible for horizontal spread was absent in the isolate. CONCLUSION: Colistin resistance has been reported previously in Klebsiella pneumoniae and it is a rare occurrence in Escherichia coli in Indian setting. Although the isolate lack mcr mediated colistin resistance, emergence and spread of colistin resistant in gram-negative bacteria pose a threat.202134305283
588190.9873A novel universal DNA labeling and amplification system for rapid microarray-based detection of 117 antibiotic resistance genes in Gram-positive bacteria. A rapid and simple DNA labeling system has been developed for disposable microarrays and has been validated for the detection of 117 antibiotic resistance genes abundant in Gram-positive bacteria. The DNA was fragmented and amplified using phi-29 polymerase and random primers with linkers. Labeling and further amplification were then performed by classic PCR amplification using biotinylated primers specific for the linkers. The microarray developed by Perreten et al. (Perreten, V., Vorlet-Fawer, L., Slickers, P., Ehricht, R., Kuhnert, P., Frey, J., 2005. Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria. J.Clin.Microbiol. 43, 2291-2302.) was improved by additional oligonucleotides. A total of 244 oligonucleotides (26 to 37 nucleotide length and with similar melting temperatures) were spotted on the microarray, including genes conferring resistance to clinically important antibiotic classes like β-lactams, macrolides, aminoglycosides, glycopeptides and tetracyclines. Each antibiotic resistance gene is represented by at least 2 oligonucleotides designed from consensus sequences of gene families. The specificity of the oligonucleotides and the quality of the amplification and labeling were verified by analysis of a collection of 65 strains belonging to 24 species. Association between genotype and phenotype was verified for 6 antibiotics using 77 Staphylococcus strains belonging to different species and revealed 95% test specificity and a 93% predictive value of a positive test. The DNA labeling and amplification is independent of the species and of the target genes and could be used for different types of microarrays. This system has also the advantage to detect several genes within one bacterium at once, like in Staphylococcus aureus strain BM3318, in which up to 15 genes were detected. This new microarray-based detection system offers a large potential for applications in clinical diagnostic, basic research, food safety and surveillance programs for antimicrobial resistance.201525451460
1881100.9872Genomic Characterisation of Multidrug-Resistant Pathogenic Enteric Bacteria from healthy children in Osun State, Nigeria. Antimicrobial resistance (AMR) has been established to be a significant driver for the persistence and spread of bacterial infections. It is, therefore, essential to conduct epidemiological surveillance of AMR in healthy individuals to understand the actual dynamics of AMR in Nigeria. Multi-drug resistant Klebsiella quasivariicola (n=1), Enterobacter hormaechei (n=1), and Escherichia coli (n=3) from stool samples of healthy children were subjected to whole genome sequencing using Illumina Nextseq1000/2000 and Oxford nanopore. Bioinformatics analysis reveals antimicrobial resistance, virulence genes, and plasmids. This pathogenic enteric bacteria harbored more than three plasmid replicons of either Col and/or Inc type associated with outbreaks and AMR resistant gene pmrB responsible for colistin resistance. Plasmid reconstruction revealed an integrated tetA gene responsible for tetracycline resistance, and caa gene responsible for toxin production in two of the E.coli isolates, and a cusC gene known to induce neonatal meningitis in the K. quasivariicola ST3879. The global spread of MDR pathogenic enteric bacteria is a worrying phenomenon, and close surveillance of healthy individuals, especially children, is strongly recommended to prevent the continuous spread and achieve the elimination and eradication of these infections. Molecular epidemiological surveillance using whole genome sequencing (WGS) will improve the detection of MDR pathogens in Nigeria.202337503211
5038110.9872Simple and quick detection of extended-spectrum β-lactamase and carbapenemase-encoding genes using isothermal nucleic acid amplification techniques. The spread of plasmid-mediated antibiotic-resistant bacteria must be controlled; to this end, developing kits for simple and rapid detection in food and clinical settings is desirable. This review describes the detection of antibiotic resistance genes in extended-spectrum β-lactamase （ESBL）- and carbapenemase-producing bacteria. Loop-mediated isothermal amplification （LAMP）, a technique developed in Japan, is a useful diffusion amplification method that does not require equipment like thermal cyclers, and amplifies the target gene in 30 min at about 65℃. Although most reports targeting ESBL and carbapenemase genes are intended for clinical use, environmental and food samples have also been targeted. Recombinase polymerase amplification （RPA） has recently been developed; in RPA, the reaction proceeds under the human skin with reaction conditions of 30 min at 37℃. Detection of ESBL and carbapenemase-encoding genes in food and clinical samples using RPA has been reported in limited studies. However, research on RPA has just begun, and further development is expected.202338233166
5068120.9871Ultrasensitive 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
5119130.9871ROCker models for reliable detection and typing of short-read sequences carrying mcr, erm, mph, and lnu antibiotic resistance genes. Quantitative monitoring of emerging antimicrobial resistance genes (ARGs) using short-read sequences remains challenging due to the high frequency of amino acid functional domains and motifs shared with related but functionally distinct (non-target) proteins. To facilitate ARG monitoring efforts using unassembled short reads, we present novel ROCker models for mcr, mph, erm, and lnu ARG families, as well as models for variants of special public health concern within these families, including mcr-1, mphA, ermB, lnuF, lnuB, and lnuG genes. For this, we curated target gene sequence sets for model training and built these models using the recently updated ROCker V2 pipeline (Gerhardt et al., in review). To validate our models, we simulated reads from the whole genome of ARG-carrying isolates spanning a range of common read lengths and used them to challenge the filtering efficacy of ROCker versus common static filtering approaches, such as similarity searches using BLASTx with various e-value thresholds or hidden Markov models. ROCker models consistently showed F1 scores up to 10× higher (31% higher on average) and lower false-positive (by 30%, on average) and false-negative (by 16%, on average) rates based on 250 bp reads compared to alternative methods. The ROCker models and all related reference materials and data are freely available through http://enve-omics.ce.gatech.edu/rocker/models, further expanding the available model collection previously developed for other genes. Their application to short-read metagenomes, metatranscriptomes, and PCR amplicon data should facilitate more accurate classification and quantification of unassembled short-read sequences for these ARG families and specific genes.IMPORTANCEAntimicrobial resistance gene families encoding erm and mph genes confer resistance to the macrolide class of antimicrobials, which are used to treat a wide range of infections. Similarly, the mcr gene family confers resistance to polymyxin E (colistin), a drug of last resort for many serious drug-resistant bacterial infections, and the lnu gene family confers resistance to lincomycin, which is reserved for patients allergic to penicillin or where bacteria have developed resistance to other antimicrobials. Assessing the prevalence of these genes in clinical or environmental samples and monitoring their spread to new pathogens are thus important for quantifying the associated public health risk. However, detecting these and other resistance genes in short-read sequence data is technically challenging. Our ROCker bioinformatic pipeline achieves reliable detection and typing of broad-range target gene sequences in complex data sets, thus contributing toward solving an important problem in ongoing surveillance efforts of antimicrobial resistance.202541143534
2462140.9870Genetic diversity, virulence factors and drug resistance of Pantoea strains isolated from samples of fresh fruits, vegetables and soil. INTRODUCTION: Pantoea is a genus of Gram-negative bacteria from the Erwiniaceae family. These bacteria are opportunistic human pathogens which are widely distributed in plants and soil. This study aimed to reveal the genetic diversity of Pantoea isolates from food and soil, characterise them biochemically and evaluate their drug resistance. MATERIAL AND METHODS: Thirty Pantoea strains were isolated from fresh fruit (n = 2), fresh and minimally processed vegetables (n = 12) and soil samples (n = 16). The genomic DNA was isolated from cultures on nutrient agar, and species were identified by amplification of 16S ribosomal RNA and housekeeping gene fragments and confirmed by sequencing. Virulence gene presence was determined by amplification of the hcp (haemolysin-coregulated protein), vgrG (glycine-valine repeat sequence G), acrA (anti-clustered regularly interspaced short palindromic repeat protein A) and acrB genes. Isolate drug resistance was tested using the disc-diffusion and gradient strip methods. The presence of Ambler class C (AmpC) β-lactamase (βL) and extended-spectrum (ES) βL resistance genes was tested for. RESULTS: Five species were identified: P. agglomerans (n = 24), P. ananatis (n = 1), P. eucalypti (n = 1), P. conspicua (n = 1) and P. vagans (n = 2). The hcp and vrgG virulence genes were detected in 7 and 1 strain, respectively. All strains showed high resistance to cephazolin and cephuroxime, and more than half did so to ampicillin. The production of AmpC βL and ESβL was confirmed in 22 and 25 strains, respectively. Three strains of the Pantoea bacteria, including P. ananatis from leeks and P. agglomerans from arugula and soil, showed resistance to three or more antimicrobial classes. CONCLUSION: Pantoea spp., including multidrug-resistant strains, in fresh foods pose a potential risk of infection to consumers.202541064409
5161150.9870Genomic analysis of contaminant Stenotrophomonas maltophilia, from placental swab culture, carrying antibiotic resistance: a potential hospital laboratory contaminant. Acute chorioamnionitis has been considered as reflective of amniotic fluid infection. Standard microbiological work ups for causative microorganism of intra-amniotic infection is based on microbial identification. However, frequency of positive placental culture is varied depending on placental sampling techniques, contaminations, methods of microbiologic work ups or comprehensive microbiologic work ups. In this report, we performed a hybrid whole genome sequencing of a proven bacterial contaminant obtained from placental culture in a patient with preterm labor and acute chorioamnionitis. This is to unveil genetic characterization of contaminant Stenotrophomonas maltophilia habouring antibiotic resistance genes. Stenotrophomonas maltiphilia was proven to be bacterial contaminant since Ureaplasma urealyticum was subsequently demonstrated in amniotic fluid by 16 S rRNA gene Sanger sequencing. Cultivation results from other sources were no growth. We identified Stenotrophomonas maltiphilia strain RAOG732 which carried several antibiotic resistance genes, including aminoglycoside, fluoroquiolone and beta-lactam. Biofilm production genes were also identified in this genome. We firstly utilized a hybrid sequencing approach to investigate the genome of S. maltiphilia in the patient with preterm and acute chorioamnionitis, a proven bacterial laboratory contaminant. The analysis provided several antibiotic resistance-associated and genes biofilm-associated genes. The detection of S. maltiphilia raised the awareness of the colonization of biofilm-producing bacteria in hospitals, where surveillance for decontamination is necessary.202540594762
5124160.9870Oxford nanopore long-read sequencing enables the generation of complete bacterial and plasmid genomes without short-read sequencing. INTRODUCTION: Genome-based analysis is crucial in monitoring antibiotic-resistant bacteria (ARB)and antibiotic-resistance genes (ARGs). Short-read sequencing is typically used to obtain incomplete draft genomes, while long-read sequencing can obtain genomes of multidrug resistance (MDR) plasmids and track the transmission of plasmid-borne antimicrobial resistance genes in bacteria. However, long-read sequencing suffers from low-accuracy base calling, and short-read sequencing is often required to improve genome accuracy. This increases costs and turnaround time. METHODS: In this study, a novel ONT sequencing method is described, which uses the latest ONT chemistry with improved accuracy to assemble genomes of MDR strains and plasmids from long-read sequencing data only. Three strains of Salmonella carrying MDR plasmids were sequenced using the ONT SQK-LSK114 kit with flow cell R10.4.1, and de novo genome assembly was performed with average read accuracy (Q > 10) of 98.9%. RESULTS AND DISCUSSION: For a 5-Mb-long bacterial genome, finished genome sequences with accuracy of >99.99% could be obtained at 75× sequencing coverage depth using Flye and Medaka software. Thus, this new ONT method greatly improves base-calling accuracy, allowing for the de novo assembly of high-quality finished bacterial or plasmid genomes without the need for short-read sequencing. This saves both money and time and supports the application of ONT data in critical genome-based epidemiological analyses. The novel ONT approach described in this study can take the place of traditional combination genome assembly based on short- and long-read sequencing, enabling pangenomic analyses based on high-quality complete bacterial and plasmid genomes to monitor the spread of antibiotic-resistant bacteria and antibiotic resistance genes.202337256057
2249170.9870Tracking Multidrug Resistance in Gram-Negative Bacteria in Alexandria, Egypt (2020-2023): An Integrated Analysis of Patient Data and Diagnostic Tools. BACKGROUND: The rise in carbapenem-resistant Enterobacteriaceae (CRE) in Egypt, particularly in hospital settings, poses a significant public health challenge. This study aims to develop a combined epidemiological surveillance tool utilizing the Microreact online platform (version 269) and molecular microarray technology to track and analyze carbapenem-resistant Escherichia coli strains in Egypt. The objective is to integrate molecular diagnostics and real-time data visualization to better understand the spread and evolution of multidrug-resistant (MDR) bacteria. METHODS: The study analyzed 43 E. coli isolates collected from Egyptian hospitals between 2020 and 2023. Nanopore sequencing and microarray analysis were used to identify carbapenemase genes and other resistance markers, whereas the VITEK2 system was employed for phenotypic antibiotic susceptibility testing. Microreact was used to visualize epidemiological data, mapping the geographic and temporal distribution of resistant strains. RESULTS: We found that 72.09% of the isolates, predominantly from pediatric patients, carried the blaNDM-5 gene, while other carbapenemase genes, including blaOXA-48 and blaVIM, were also detected. The microarray method demonstrated 92.9% diagnostic sensitivity and 87.7% diagnostic specificity compared to whole-genome sequencing. Phenotypic resistance correlated strongly with next-generation sequencing (NGS) genotypic data, achieving 95.6% sensitivity and 95.2% specificity. CONCLUSIONS: This method establishes the utility of combining microarray technology, NGS and real-time data visualization for the surveillance of carbapenem-resistant Enterobacteriaceae, especially E. coli. The high concordance between genotypic and phenotypic data underscores the potential of DNA microarrays as a cost-effective alternative to whole-genome sequencing, especially in resource-limited settings. This integrated approach can enhance public health responses to MDR bacteria in Egypt.202439766575
2229180.9870A pentaplex real-time PCR assay for rapid identification of major beta-lactamase genes KPC, NDM, CTX, CMY, and OXA-48 directly from bacteria in blood. Introduction. Antibiotic resistance, particularly in cases of sepsis, has emerged as a growing global public health concern and economic burden. Current methods of blood culture and antimicrobial susceptibility testing of agents involved in sepsis can take as long as 3-5 days. It is vital to rapidly identify which antimicrobials can be used to effectively treat sepsis cases on an individual basis. Here, we present a pentaplex, real-time PCR-based assay that can quickly identify the most common beta-lactamase genes (Klebsiella pneumoniae carbapenemase (KPC); New Delhi metallo-beta-lactamase (NDM); cefotaximase-Munich (CTX-M); cephamycin AmpC beta-lactamases (CMY); and Oxacillinase-48 (OXA-48)) from pathogens derived directly from the blood of patients presenting with bacterial septicemia.Aim. To develop an assay which can rapidly identify the most common beta-lactamase genes in Carbapenem-resistant Enterobacteriaceae bacteria (CREs) from the United States.Hypothesis/Gap Statement. Septicemia caused by carbapenem-resistant bacteria has a death rate of 40-60 %. Rapid diagnosis of antibiotic susceptibility directly from bacteria in blood by identification of beta-lactamase genes will greatly improve survival rates. In this work, we develop an assay capable of concurrently identifying the five most common beta-lactamase and carbapenemase genes.Methodology. Primers and probes were created which can identify all subtypes of Klebsiella pneumoniae carbapenemase (KPC); New Delhi metallo-beta-lactamase (NDM); cefotaximase-Munich (CTX); cephamycin AmpC beta-lactamase (CMY); and oxacillinase-48 (OXA-48). The assay was validated using 13 isolates containing various PCR targets from the Centre for Disease Control Antimicrobial Resistance Isolate Bank Enterobacterales Carbapenemase Diversity Panel. Blood obtained from volunteers was spiked with CREs and bacteria were separated, lysed, and subjected to analysis via the pentaplex assay.Results. This pentaplex assay successfully identified beta-lactamase genes derived from bacteria separated from blood at concentrations of 4-8 c.f.u. ml(-1).Conclusion. This assay will improve patient outcomes by supplying physicians with critical drug resistance information within 2 h of septicemia onset, allowing them to prescribe effective antimicrobials corresponding to the resistance gene(s) present in the pathogen. In addition, information supplied by this assay will lessen the inappropriate use of broad-spectrum antimicrobials and prevent the evolution of further antibiotic resistance.202134878374
1539190.9869WGS of a lytic phage targeting biofilm-forming carbapenem-resistant Klebsiella pneumoniae prevalent in a tertiary healthcare setup. Carbapenem-resistant Enterobacteriaceae (CRE) are listed as a priority-one critical pathogen category by the WHO because of their abysmal treatment outcomes owing to antibiotic inefficiency. Among CRE, Klebsiella pneumoniae is prevalent in acquiring resistance genes and withstanding the last-resort drugs. Additionally, its ability to form robust biofilms further exacerbates the treatment challenges. The escalating resistance and recalcitrance of biofilm-residing bacteria against standard antibiotic treatments demand an alternative to antibiotics. Phages, being nature-tailored, are a never-ending arsenal against the bacteria because of their capacity to lyse bacteria rapidly and co-evolve with bacteria. In our study, we isolated K. pneumoniae from patients at Madras Medical Mission Hospital (MMMH), India, and assessed their antibiogram profiles, presence of carbapenemase genes, and biofilm-forming abilities. 100 % of the strains were extended-spectrum beta-lactamase producing, multidrug-resistant (ESBL-MDR), with 95 % harbouring carbapenemase genes. Among the isolates, 65 % were strong biofilm formers, and the rest were moderate. Further, we isolated a bacteriophage, SAKp11, from the hospital sewage, which was able to lyse 62 out of 167 clinical isolates and successfully reduced 99.99 % viable bacterial cells of the 24-h-old biofilm of strong biofilm forming MDR K. pneumoniae strains. Whole genome analysis revealed that SAKp11, with a genome size of 59,338bp, belonged to the Casjensviridae family, one of the less explored bacteriophage families. Comprehensive characterization of SAKp11 indicated its suitability for therapeutic use. Our study highlights the severity of drug-resistant K. pneumoniae in Indian healthcare and the inadequacy of current antibiotics, underscoring the potential of phages as an alternative therapeutic option.202540348211