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908300.9781ARGNet: 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
516310.9780Multi-omics data elucidate parasite-host-microbiota interactions and resistance to Haemonchus contortus in sheep. BACKGROUND: The integration of molecular data from hosts, parasites, and microbiota can enhance our understanding of the complex biological interactions underlying the resistance of hosts to parasites. Haemonchus contortus, the predominant sheep gastrointestinal parasite species in the tropics, causes significant production and economic losses, which are further compounded by the diminishing efficiency of chemical control owing to anthelmintic resistance. Knowledge of how the host responds to infection and how the parasite, in combination with microbiota, modulates host immunity can guide selection decisions to breed animals with improved parasite resistance. This understanding will help refine management practices and advance the development of new therapeutics for long-term helminth control. METHODS: Eggs per gram (EPG) of feces were obtained from Morada Nova sheep subjected to two artificial infections with H. contortus and used as a proxy to select animals with high resistance or susceptibility for transcriptome sequencing (RNA-seq) of the abomasum and 50 K single-nucleotide genotyping. Additionally, RNA-seq data for H. contortus were generated, and amplicon sequence variants (ASV) were obtained using polymerase chain reaction amplification and sequencing of bacterial and archaeal 16S ribosomal RNA genes from sheep feces and rumen content. RESULTS: The heritability estimate for EPG was 0.12. GAST, GNLY, IL13, MGRN1, FGF14, and RORC genes and transcripts were differentially expressed between resistant and susceptible animals. A genome-wide association study identified regions on chromosomes 2 and 11 that harbor candidate genes for resistance, immune response, body weight, and adaptation. Trans-expression quantitative trait loci were found between significant variants and differentially expressed transcripts. Functional co-expression modules based on sheep genes and ASVs correlated with resistance to H. contortus, showing enrichment in pathways of response to bacteria, immune and inflammatory responses, and hub features of the Christensenellaceae, Bacteroides, and Methanobrevibacter genera; Prevotellaceae family; and Verrucomicrobiota phylum. In H. contortus, some mitochondrial, collagen-, and cuticle-related genes were expressed only in parasites isolated from susceptible sheep. CONCLUSIONS: The present study identified chromosome regions, genes, transcripts, and pathways involved in the elaborate interactions between the sheep host, its gastrointestinal microbiota, and the H. contortus parasite. These findings will assist in the development of animal selection strategies for parasite resistance and interdisciplinary approaches to control H. contortus infection in sheep.202438429820
907520.9777CamPype: 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
519330.9777Antibiotic resistance genes prediction via whole genome sequence analysis of Stenotrophomonas maltophilia. BACKGROUND: Stenotrophomonas maltophilia (S. maltophilia) is the first dominant ubiquitous bacterial species identified from the genus Stenotrophomonas in 1943 from a human source. S. maltophilia clinical strains are resistance to several therapies, this study is designed to investigate the whole genome sequence and antimicrobial resistance genes prediction in Stenotrophomonas maltophilia (S. maltophilia) SARC-5 and SARC-6 strains, isolated from the nasopharyngeal samples of an immunocompromised patient. METHODS: These bacterial strains were obtained from Pakistan Institute of Medical Sciences (PIMS) Hospital, Pakistan. The bacterial genome was sequenced using a whole-genome shotgun via a commercial service that used an NGS (Next Generation Sequencing) technology called as Illumina Hiseq 2000 system for genomic sequencing. Moreover, detailed in-silico analyses were done to predict the presence of antibiotic resistance genes in S. maltophilia. RESULTS: Results showed that S. maltophilia is a rare gram negative, rod-shaped, non sporulating bacteria. The genome assembly results in 24 contigs (>500 bp) having a size of 4668,850 bp with 65.8% GC contents. Phylogenetic analysis showed that SARC-5 and SARC-6 were closely related to S. maltophilia B111, S. maltophilia BAB-5317, S. maltophilia AHL, S. maltophilia BAB-5307, S. maltophilia RD-AZPVI_04, S. maltophilia JFZ2, S. maltophilia RD_MAAMIB_06 and lastly with S. maltophilia sp ROi7. Moreover, the whole genome sequence analysis of both SARC-5 and SARC-6 revealed the presence of four resistance genes adeF, qacG, adeF, and smeR. CONCLUSION: Our study confirmed that S. maltophilia SARC-5 and SARC-6 are one of the leading causes of nosocomial infection which carry multiple antibiotic resistance genes.202438128408
616140.9772Unraveling radiation resistance strategies in two bacterial strains from the high background radiation area of Chavara-Neendakara: A comprehensive whole genome analysis. This paper reports the results of gamma irradiation experiments and whole genome sequencing (WGS) performed on vegetative cells of two radiation resistant bacterial strains, Metabacillus halosaccharovorans (VITHBRA001) and Bacillus paralicheniformis (VITHBRA024) (D10 values 2.32 kGy and 1.42 kGy, respectively), inhabiting the top-ranking high background radiation area (HBRA) of Chavara-Neendakara placer deposit (Kerala, India). The present investigation has been carried out in the context that information on strategies of bacteria having mid-range resistance for gamma radiation is inadequate. WGS, annotation, COG and KEGG analyses and manual curation of genes helped us address the possible pathways involved in the major domains of radiation resistance, involving recombination repair, base excision repair, nucleotide excision repair and mismatch repair, and the antioxidant genes, which the candidate could activate to survive under ionizing radiation. Additionally, with the help of these data, we could compare the candidate strains with that of the extremely radiation resistant model bacterium Deinococccus radiodurans, so as to find the commonalities existing in their strategies of resistance on the one hand, and also the rationale behind the difference in D10, on the other. Genomic analysis of VITHBRA001 and VITHBRA024 has further helped us ascertain the difference in capability of radiation resistance between the two strains. Significantly, the genes such as uvsE (NER), frnE (protein protection), ppk1 and ppx (non-enzymatic metabolite production) and those for carotenoid biosynthesis, are endogenous to VITHBRA001, but absent in VITHBRA024, which could explain the former's better radiation resistance. Further, this is the first-time study performed on any bacterial population inhabiting an HBRA. This study also brings forward the two species whose radiation resistance has not been reported thus far, and add to the knowledge on radiation resistant capabilities of the phylum Firmicutes which are abundantly observed in extreme environment.202438857267
517050.9772Synergistic effect of imp/ostA and msbA in hydrophobic drug resistance of Helicobacter pylori. BACKGROUND: Contamination of endoscopy equipment by Helicobacter pylori (H. pylori) frequently occurs after endoscopic examination of H. pylori-infected patients. In the hospital, manual pre-cleaning and soaking in glutaraldehyde is an important process to disinfect endoscopes. However, this might not be sufficient to remove H. pylori completely, and some glutaraldehyde-resistant bacteria might survive and be passed to the next patient undergoing endoscopic examination through unidentified mechanisms. We identified an Imp/OstA protein associated with glutaraldehyde resistance in a clinical strain, NTUH-C1, from our previous study. To better understand and manage the problem of glutaraldehyde resistance, we further investigated its mechanism. RESULTS: The minimal inhibitory concentrations (MICs) of glutaraldehyde andexpression of imp/ostA RNA in 11 clinical isolates from the National Taiwan University Hospital were determined. After glutaraldehyde treatment, RNA expression in the strains with the MICs of 4-10 microg/ml was higher than that in strains with the MICs of 1-3 microg/ml. We examined the full-genome expression of strain NTUH-S1 after glutaraldehyde treatment using a microarray and found that 40 genes were upregulated and 31 genes were downregulated. Among the upregulated genes, imp/ostA and msbA, two putative lipopolysaccharide biogenesis genes, were selected for further characterization. The sensitivity to glutaraldehyde or hydrophobic drugs increased in both of imp/ostA and msbA single mutants. The imp/ostA and msbA double mutant was also hypersensitive to these chemicals. The lipopolysaccharide contents decreased in individual imp/ostA and msbA mutants and dramatically reduced in the imp/ostA and msbA double mutant. Outer membrane permeability assay demonstrated that the imp/ostA and msbA double mutation resulted in the increase of outer membrane permeability. Ethidium bromide accumulation assay demonstrated that MsbA was involved in efflux of hydrophobic drugs. CONCLUSION: The expression levels of imp/ostA and msbA were correlated with glutaraldehyde resistance in clinical isolates after glutaraldehyde treatment. Imp/OstA and MsbA play a synergistic role in hydrophobic drugs resistance and lipopolysaccharide biogenesis in H. pylori.200919594901
512260.9771Clinical long-read metagenomic sequencing of culture-negative infective endocarditis reveals genomic features and antimicrobial resistance. BACKGROUND: Infective endocarditis (IE) poses significant diagnostic challenges, particularly in blood culture-negative cases where fastidious bacteria evade detection. Metagenomic-based nanopore sequencing enables rapid pathogen detection and provides a new approach for the diagnosis of IE. METHOD: Two cases of blood culture-negative infective endocarditis (IE) were analyzed using nanopore sequencing with an in silico host-depletion approach. Complete genome reconstruction and antimicrobial resistance gene annotation were successfully performed. RESULTS: Within an hour of sequencing, EPI2ME classified nanopore reads, identifying Corynebacterium striatum in IE patient 1 and Granulicatella adiacens in IE patient 2. After 18 h, long-read sequencing successfully reconstructed a single circular genome of C. striatum in IE patient 1, whereas short-read sequencing was used to compare but produced fragmented assemblies. Based on these results, long-read sequencing was exclusively used for IE patient 2, allowing for the complete and accurate assembly of G. adiacens, confirming the presence of these bacteria in the clinical samples. In addition to pathogen identification, antimicrobial resistance (AMR) genes were detected in both genomes. Notably, in C. striatum, regions containing a class 1 integron and multiple novel mobile genetic elements (ISCost1, ISCost2, Tn7838 and Tn7839) were identified, collectively harbouring six AMR genes. This is the first report of such elements in C. striatum, highlighting the potential of nanopore long-read sequencing for comprehensive pathogen characterization in IE cases. CONCLUSIONS: This study highlights the effectiveness of host-depleted, long-read nanopore metagenomics for direct pathogen identification and accurate genome reconstruction, including antimicrobial resistance gene detection. The approach enables same-day diagnostic reporting within a matter of hours. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-025-11741-5.202541087996
520070.9770Whole genome sequencing of the multidrug-resistant Chryseobacterium indologenes isolated from a patient in Brazil. Chryseobacterium indologenes is a non-glucose-fermenting Gram-negative bacillus. This emerging multidrug resistant opportunistic nosocomial pathogen can cause severe infections in neonates and immunocompromised patients. This study aimed to present the first detailed draft genome sequence of a multidrug-resistant C. indologenes strain isolated from the cerebrospinal fluid of an infant hospitalized at the Neonatal Intensive Care Unit of Brazilian Tertiary Hospital. We first analyzed the susceptibility of C. indologenes strain to different antibiotics using the VITEK 2 system. The strain demonstrated an outstanding resistance to all the antibiotic classes tested, including β-lactams, aminoglycosides, glycylcycline, and polymyxin. Next, C. indologenes was whole-genome-sequenced, annotated using Prokka and Rapid Annotation using Subsystems Technology (RAST), and screened for orthologous groups (EggNOG), gene ontology (GO), resistance genes, virulence genes, and mobile genetic elements using different software tools. The draft genome contained one circular chromosome of 4,836,765 bp with 37.32% GC content. The genomic features of the chromosome present numerous genes related to cellular processes that are essential to bacteria. The MDR C. indologenes revealed the presence of genes that corresponded to the resistance phenotypes, including genes to β-lactamases (bla (IND-13), bla (CIA-3), bla (TEM-116), bla (OXA-209), bla (VEB-15)), quinolone (mcbG), tigecycline (tet(X6)), and genes encoding efflux pumps which confer resistance to aminoglycosides (RanA/RanB), and colistin (HlyD/TolC). Amino acid substitutions related to quinolone resistance were observed in GyrA (S83Y) and GyrB (L425I and K473R). A mutation that may play a role in the development of colistin resistance was detected in lpxA (G68D). Chryseobacterium indologenes isolate harbored 19 virulence factors, most of which were involved in infection pathways. We identified 13 Genomic Islands (GIs) and some elements associated with one integrative and conjugative element (ICEs). Other elements linked to mobile genetic elements (MGEs), such as insertion sequence (ISEIsp1), transposon (Tn5393), and integron (In31), were also present in the C. indologenes genome. Although plasmids were not detected, a ColRNAI replicon type and the most resistance genes detected in singletons were identified in unaligned scaffolds. We provided a wide range of information toward the understanding of the genomic diversity of C. indologenes, which can contribute to controlling the evolution and dissemination of this pathogen in healthcare settings.202235966843
906880.9770TnCentral: a Prokaryotic Transposable Element Database and Web Portal for Transposon Analysis. We describe here the structure and organization of TnCentral (https://tncentral.proteininformationresource.org/ [or the mirror link at https://tncentral.ncc.unesp.br/]), a web resource for prokaryotic transposable elements (TE). TnCentral currently contains ∼400 carefully annotated TE, including transposons from the Tn3, Tn7, Tn402, and Tn554 families; compound transposons; integrons; and associated insertion sequences (IS). These TE carry passenger genes, including genes conferring resistance to over 25 classes of antibiotics and nine types of heavy metal, as well as genes responsible for pathogenesis in plants, toxin/antitoxin gene pairs, transcription factors, and genes involved in metabolism. Each TE has its own entry page, providing details about its transposition genes, passenger genes, and other sequence features required for transposition, as well as a graphical map of all features. TnCentral content can be browsed and queried through text- and sequence-based searches with a graphic output. We describe three use cases, which illustrate how the search interface, results tables, and entry pages can be used to explore and compare TE. TnCentral also includes downloadable software to facilitate user-driven identification, with manual annotation, of certain types of TE in genomic sequences. Through the TnCentral homepage, users can also access TnPedia, which provides comprehensive reviews of the major TE families, including an extensive general section and specialized sections with descriptions of insertion sequence and transposon families. TnCentral and TnPedia are intuitive resources that can be used by clinicians and scientists to assess TE diversity in clinical, veterinary, and environmental samples. IMPORTANCE The ability of bacteria to undergo rapid evolution and adapt to changing environmental circumstances drives the public health crisis of multiple antibiotic resistance, as well as outbreaks of disease in economically important agricultural crops and animal husbandry. Prokaryotic transposable elements (TE) play a critical role in this. Many carry "passenger genes" (not required for the transposition process) conferring resistance to antibiotics or heavy metals or causing disease in plants and animals. Passenger genes are spread by normal TE transposition activities and by insertion into plasmids, which then spread via conjugation within and across bacterial populations. Thus, an understanding of TE composition and transposition mechanisms is key to developing strategies to combat bacterial pathogenesis. Toward this end, we have developed TnCentral, a bioinformatics resource dedicated to describing and exploring the structural and functional features of prokaryotic TE whose use is intuitive and accessible to users with or without bioinformatics expertise.202134517763
248490.9765Multilocus sequence typing analysis and second-generation sequencing analysis of Salmonella Wandsworth. BACKGROUND: Salmonella Wandsworth is a rare serotype of Salmonella. This study analyzed the genotyping, genome structure, and molecular biological functions of Salmonella Wandsworth based on the results of multilocus sequence typing and next-generation sequencing genome assembly analysis. METHODS: Serological typing was performed using the slide-agglutination method. The micro broth dilution method was used to test antibiotic susceptibility. Multilocus sequence typing (MLST) was used to perform the homology analysis, while the second-generation sequencing genome analysis was used to analyze the whole genome of the bacteria. RESULTS: Salmonella Wandsworth is Group Q Salmonella. The MLST of this strain was ST1498. Salmonella Wandsworth was sensitive to antibiotics, such as ceftriaxone, imipenem, chloramphenicol, and colistin, but was resistant to ampicillin, cefalotin, gentamicin, and ciprofloxacin. The second-generation sequencing results showed that the genome sequence length of the bacteria was 5109457bp. Annotated COG library analysis generated 3,746 corresponding genes. After the comparison with the KEGG library, 1,340 genes, which participate in 19 types of metabolic pathways, were obtained. A total of 249 pathogenic factors and 2 disease islands were predicted. 2 CRISPR sites and 8 Cas sites were predicted. It can be seen from the evolutionary tree that Salmonella Wandsworth MLST1498 and Paratyphi B str.SPB7 are gathered together. We identified one resistance gene, namely, aac(6')-Iaa accounting for aminoglycoside resistance. CONCLUSION: Salmonella Wandsworth isolated in this study is Salmonella group Q. Consequently, it is necessary to strengthen the understanding of clinical infections of Salmonella Wandsworth and carry out continuous monitoring and research.202134245607
5235100.9765Draft 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
5118110.9764Automated extraction of genes associated with antibiotic resistance from the biomedical literature. The detection of bacterial antibiotic resistance phenotypes is important when carrying out clinical decisions for patient treatment. Conventional phenotypic testing involves culturing bacteria which requires a significant amount of time and work. Whole-genome sequencing is emerging as a fast alternative to resistance prediction, by considering the presence/absence of certain genes. A lot of research has focused on determining which bacterial genes cause antibiotic resistance and efforts are being made to consolidate these facts in knowledge bases (KBs). KBs are usually manually curated by domain experts to be of the highest quality. However, this limits the pace at which new facts are added. Automated relation extraction of gene-antibiotic resistance relations from the biomedical literature is one solution that can simplify the curation process. This paper reports on the development of a text mining pipeline that takes in English biomedical abstracts and outputs genes that are predicted to cause resistance to antibiotics. To test the generalisability of this pipeline it was then applied to predict genes associated with Helicobacter pylori antibiotic resistance, that are not present in common antibiotic resistance KBs or publications studying H. pylori. These genes would be candidates for further lab-based antibiotic research and inclusion in these KBs. For relation extraction, state-of-the-art deep learning models were used. These models were trained on a newly developed silver corpus which was generated by distant supervision of abstracts using the facts obtained from KBs. The top performing model was superior to a co-occurrence model, achieving a recall of 95%, a precision of 60% and F1-score of 74% on a manually annotated holdout dataset. To our knowledge, this project was the first attempt at developing a complete text mining pipeline that incorporates deep learning models to extract gene-antibiotic resistance relations from the literature. Additional related data can be found at https://github.com/AndreBrincat/Gene-Antibiotic-Resistance-Relation-Extraction.202235134132
5097120.9764Comparing 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
5119130.9764ROCker 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
5169140.9764Genetic Adaptation and Acquisition of Macrolide Resistance in Haemophilus spp. during Persistent Respiratory Tract Colonization in Chronic Obstructive Pulmonary Disease (COPD) Patients Receiving Long-Term Azithromycin Treatment. Patients with chronic obstructive pulmonary disease (COPD) benefit from the immunomodulatory effect of azithromycin, but long-term administration may alter colonizing bacteria. Our goal was to identify changes in Haemophilus influenzae and Haemophilus parainfluenzae during azithromycin treatment. Fifteen patients were followed while receiving prolonged azithromycin treatment (Hospital Universitari de Bellvitge, Spain). Four patients (P02, P08, P11, and P13) were persistently colonized by H. influenzae for at least 3 months and two (P04 and P11) by H. parainfluenzae. Isolates from these patients (53 H. influenzae and 18 H. parainfluenzae) were included to identify, by whole-genome sequencing, antimicrobial resistance changes and genetic variation accumulated during persistent colonization. All persistent lineages isolated before treatment were azithromycin-susceptible but developed resistance within the first months, apart from those belonging to P02, who discontinued the treatment. H. influenzae isolates from P08-ST107 acquired mutations in 23S rRNA, and those from P11-ST2480 and P13-ST165 had changes in L4 and L22. In H. parainfluenzae, P04 persistent isolates acquired changes in rlmC, and P11 carried genes encoding MefE/MsrD efflux pumps in an integrative conjugative element, which was also identified in H. influenzae P11-ST147. Other genetic variation occurred in genes associated with cell wall and inorganic ion metabolism. Persistent H. influenzae strains all showed changes in licA and hgpB genes. Other genes (lex1, lic3A, hgpC, and fadL) had variation in multiple lineages. Furthermore, persistent strains showed loss, acquisition, or genetic changes in prophage-associated regions. Long-term azithromycin therapy results in macrolide resistance, as well as genetic changes that likely favor bacterial adaptation during persistent respiratory colonization. IMPORTANCE The immunomodulatory properties of azithromycin reduce the frequency of exacerbations and improve the quality of life of COPD patients. However, long-term administration may alter the respiratory microbiota, such as Haemophilus influenzae, an opportunistic respiratory colonizing bacteria that play an important role in exacerbations. This study contributes to a better understanding of COPD progression by characterizing the clinical evolution of H. influenzae in a cohort of patients with prolonged azithromycin treatment. The emergence of macrolide resistance during the first months, combined with the role of Haemophilus parainfluenzae as a reservoir and source of resistance dissemination, is a cause for concern that may lead to therapeutic failure. Furthermore, genetic variations in cell wall and inorganic ion metabolism coding genes likely favor bacterial adaptation to host selective pressures. Therefore, the bacterial pathoadaptive evolution in these severe COPD patients raise our awareness of the possible spread of macrolide resistance and selection of host-adapted clones.202336475849
5192150.9763Genome Sequencing Analysis of a Rare Case of Blood Infection Caused by Flavonifractor plautii. BACKGROUND Flavonifractor plautii belongs to the clostridium family, which can lead to local infections as well as the bloodstream infections. Flavonifractor plautii caused infection is rarely few in the clinic. To understand better Flavonifractor plautii, we investigated the drug sensitivity and perform genome sequencing of Flavonifractor plautii isolated from blood samples in China and explored the drug resistance and pathogenic mechanism of the bacteria. CASE REPORT The Epsilometer test method was used to detect the sensitivity of flavonoid bacteria to antimicrobial agents. PacBio sequencing technology was employed to sequence the whole genome of Flavonifractor plautii, and gene prediction and functional annotation were also analyzed. Flavonifractor plautii displayed sensitivity to most drugs but resistance to fluoroquinolones and tetracycline, potentially mediated by tet (W/N/W). The total genome size of Flavonifractor plautii was 4,573,303 bp, and the GC content was 59.78%. Genome prediction identified 4,506 open reading frames, including 9 ribosomal RNAs and 66 transfer RNAs. It was detected that the main virulence factor-coding genes of the bacteria were the capsule, polar flagella and FbpABC, which may be associated with bacterial movement, adhesion, and biofilm formation. CONCLUSIONS The results of whole-genome sequencing could provide relevant information about the drug resistance mechanism and pathogenic mechanism of bacteria and offer a basis for clinical diagnosis and treatment.202438881048
2269160.9762Genomic detection of Panton-Valentine Leucocidins encoding genes, virulence factors and distribution of antiseptic resistance determinants among Methicillin-resistant S. aureus isolates from patients attending regional referral hospitals in Tanzania. BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) is a formidable public scourge causing worldwide mild to severe life-threatening infections. The ability of this strain to swiftly spread, evolve, and acquire resistance genes and virulence factors such as pvl genes has further rendered this strain difficult to treat. Of concern, is a recently recognized ability to resist antiseptic/disinfectant agents used as an essential part of treatment and infection control practices. This study aimed at detecting the presence of pvl genes and determining the distribution of antiseptic resistance genes in Methicillin-resistant Staphylococcus aureus isolates through whole genome sequencing technology. MATERIALS AND METHODS: A descriptive cross-sectional study was conducted across six regional referral hospitals-Dodoma, Songea, Kitete-Kigoma, Morogoro, and Tabora on the mainland, and Mnazi Mmoja from Zanzibar islands counterparts using the archived isolates of Staphylococcus aureus bacteria. The isolates were collected from Inpatients and Outpatients who attended these hospitals from January 2020 to Dec 2021. Bacterial analysis was carried out using classical microbiological techniques and whole genome sequencing (WGS) using the Illumina Nextseq 550 sequencer platform. Several bioinformatic tools were used, KmerFinder 3.2 was used for species identification, MLST 2.0 tool was used for Multilocus Sequence Typing and SCCmecFinder 1.2 was used for SCCmec typing. Virulence genes were detected using virulenceFinder 2.0, while resistance genes were detected by ResFinder 4.1, and phylogenetic relatedness was determined by CSI Phylogeny 1.4 tools. RESULTS: Out of the 80 MRSA isolates analyzed, 11 (14%) were found to harbor LukS-PV and LukF-PV, pvl-encoding genes in their genome; therefore pvl-positive MRSA. The majority (82%) of the MRSA isolates bearing pvl genes were also found to exhibit the antiseptic/disinfectant genes in their genome. Moreover, all (80) sequenced MRSA isolates were found to harbor SCCmec type IV subtype 2B&5. The isolates exhibited 4 different sequence types, ST8, ST88, ST789 and ST121. Notably, the predominant sequence type among the isolates was ST8 72 (90%). CONCLUSION: The notably high rate of antiseptic resistance particularly in the Methicillin-resistant S. aureus strains poses a significant challenge to infection control measures. The fact that some of these virulent strains harbor the LukS-PV and LukF-PV, the pvl encoding genes, highlight the importance of developing effective interventions to combat the spreading of these pathogenic bacterial strains. Certainly, strengthening antimicrobial resistance surveillance and stewardship will ultimately reduce the selection pressure, improve the patient's treatment outcome and public health in Tanzania.202539833938
8472170.9762Genetic architecture of resistance to plant secondary metabolites in Photorhabdus entomopathogenic bacteria. BACKGROUND: Entomopathogenic nematodes of the genus Heterorhabditis establish a symbiotic association with Photorhabdus bacteria. Together, they colonize and rapidly kill insects, making them important biological control agents against agricultural pests. Improving their biocontrol traits by engineering resistance to plant secondary metabolites (benzoxazinoids) in Photorhabdus symbiotic bacteria through experimental evolution has been shown to increase their lethality towards benzoxazinoid-defended larvae of the western corn rootworm, a serious crop pest of maize, and it is therefore a promising approach to develop more efficient biocontrol agents to manage this pest. To enhance our understanding of the genetic bases of benzoxazinoid resistance in Photorhabdus bacteria, we conducted an experimental evolution experiment with a phylogenetically diverse collection of Photorhabdus strains from different geographic origins. We cultured 27 different strains in medium containing 6-methoxy-2-benzoxazolinone (MBOA), a highly active benzoxazinoid breakdown product, for 35 24 h-cycles to select for benzoxazinoid-resistant strains. Then, we carried out genome-wide sequence comparisons to uncover the genetic alterations associated with benzoxazinoid resistance. Lastly, we evaluated the resistance of the newly isolated resistant Photorhabdus strains to eight additional bioactive compounds, including 2-benzoxazolinone (BOA), nicotine, caffeine, 6-chloroacetyl-2-benzoxazolinone (CABOA), digitoxin, fenitrothion, ampicillin, and kanamycin. RESULTS: We found that benzoxazinoid resistance evolves rapidly in Photorhabdus in a strain-specific manner. Across the different Photorhabdus strains, a total of nineteen nonsynonymous point mutations, two stop codon gains, and one frameshift were associated with higher benzoxazinoid resistance. The different genetic alterations were polygenic and occurred in genes coding for the EnvZ/OmpR two-component regulatory system, the different subunits of the DNA-directed RNA polymerase, and the AcrABZ-TolC multidrug efflux pump. Apart from increasing MBOA resistance, the different mutations were also associated with cross-resistance to 2-benzoxazolinone (BOA), nicotine, caffeine, and 6-chloroacetyl-2-benzoxazolinone (CABOA) and with collateral sensitivity to fenitrothion, ampicillin, and kanamycin. Targeted mutagenesis will provide a deeper mechanistic understanding, including the relative contribution of the different mutation types. CONCLUSIONS: Our study reveals several genomic features that are associated with resistance to xenobiotics in this important group of biological control agents and enhances the availability of molecular tools to develop better biological control agents, which is essential for more sustainable and ecologically friendly agricultural practices.202541168779
5098180.9762Feature selection and aggregation for antibiotic resistance GWAS in Mycobacterium tuberculosis: a comparative study. INTRODUCTION: Drug resistance (DR) of pathogens remains a global healthcare concern. In contrast to other bacteria, acquiring mutations in the core genome is the main mechanism of drug resistance for Mycobacterium tuberculosis (MTB). For some antibiotics, the resistance of a particular isolate can be reliably predicted by identifying specific mutations, while for other antibiotics the knowledge of resistance mechanisms is limited. Statistical machine learning (ML) methods are used to infer new genes implicated in drug resistance leveraging large collections of isolates with known whole-genome sequences and phenotypic states for different drugs. However, high correlations between the phenotypic states for commonly used drugs complicate the inference of true associations of mutations with drug phenotypes by ML approaches. METHODS: Recently, several new methods have been developed to select a small subset of reliable predictors of the dependent variable, which may help reduce the number of spurious associations identified. In this study, we evaluated several such methods, namely, logistic regression with different regularization penalty functions, a recently introduced algorithm for solving the best-subset selection problem (ABESS) and "Hungry, Hungry SNPos" (HHS) a heuristic algorithm specifically developed to identify resistance-associated genetic variants in the presence of resistance co-occurrence. We assessed their ability to select known causal mutations for resistance to a specific drug while avoiding the selection of mutations in genes associated with resistance to other drugs, thus we compared selected ML models for their applicability for MTB genome wide association studies. RESULTS AND DISCUSSION: In our analysis, ABESS significantly outperformed the other methods, selecting more relevant sets of mutations. Additionally, we demonstrated that aggregating rare mutations within protein-coding genes into markers indicative of changes in PFAM domains improved prediction quality, and these markers were predominantly selected by ABESS, suggesting their high informativeness. However, ABESS yielded lower prediction accuracy compared to logistic regression methods with regularization.202540606161
5145190.9761Genome sequence and comparative analysis of a putative entomopathogenic Serratia isolated from Caenorhabditis briggsae. BACKGROUND: Entomopathogenic associations between nematodes in the genera Steinernema and Heterorhabdus with their cognate bacteria from the bacterial genera Xenorhabdus and Photorhabdus, respectively, are extensively studied for their potential as biological control agents against invasive insect species. These two highly coevolved associations were results of convergent evolution. Given the natural abundance of bacteria, nematodes and insects, it is surprising that only these two associations with no intermediate forms are widely studied in the entomopathogenic context. Discovering analogous systems involving novel bacterial and nematode species would shed light on the evolutionary processes involved in the transition from free living organisms to obligatory partners in entomopathogenicity. RESULTS: We report the complete genome sequence of a new member of the enterobacterial genus Serratia that forms a putative entomopathogenic complex with Caenorhabditis briggsae. Analysis of the 5.04 MB chromosomal genome predicts 4599 protein coding genes, seven sets of ribosomal RNA genes, 84 tRNA genes and a 64.8 KB plasmid encoding 74 genes. Comparative genomic analysis with three of the previously sequenced Serratia species, S. marcescens DB11 and S. proteamaculans 568, and Serratia sp. AS12, revealed that these four representatives of the genus share a core set of ~3100 genes and extensive structural conservation. The newly identified species shares a more recent common ancestor with S. marcescens with 99% sequence identity in rDNA sequence and orthology across 85.6% of predicted genes. Of the 39 genes/operons implicated in the virulence, symbiosis, recolonization, immune evasion and bioconversion, 21 (53.8%) were present in Serratia while 33 (84.6%) and 35 (89%) were present in Xenorhabdus and Photorhabdus EPN bacteria respectively. CONCLUSION: The majority of unique sequences in Serratia sp. SCBI (South African Caenorhabditis briggsae Isolate) are found in ~29 genomic islands of 5 to 65 genes and are enriched in putative functions that are biologically relevant to an entomopathogenic lifestyle, including non-ribosomal peptide synthetases, bacteriocins, fimbrial biogenesis, ushering proteins, toxins, secondary metabolite secretion and multiple drug resistance/efflux systems. By revealing the early stages of adaptation to this lifestyle, the Serratia sp. SCBI genome underscores the fact that in EPN formation the composite end result - killing, bioconversion, cadaver protection and recolonization- can be achieved by dissimilar mechanisms. This genome sequence will enable further study of the evolution of entomopathogenic nematode-bacteria complexes.201526187596