CURATED - Word Related Documents




#
Rank
Similarity
Title + Abs.
Year
PMID
012345
520100.9859Complete genome of Enterobacter sichuanensis strain SGAir0282 isolated from air in Singapore. BACKGROUND: Enterobacter cloacae complex (ECC) bacteria, such as E. cloacae, E. sichuanensis, E. kobei, and E. roggenkampii, have been emerging as nosocomial pathogens. Many strains isolated from medical clinics were found to be resistant to antibiotics, and in the worst cases, acquired multidrug resistance. We present the whole genome sequence of SGAir0282, isolated from the outdoor air in Singapore, and its relevance to other ECC bacteria by in silico genomic analysis. RESULTS: Complete genome assembly of E. sichuanensis strain SGAir0282 was generated using PacBio RSII and Illumina MiSeq platforms, and the datasets were used for de novo assembly using Hierarchical Genome Assembly Process (HGAP) and error corrected with Pilon. The genome assembly consisted of a single contig of 4.71 Mb and with a G+C content of 55.5%. No plasmid was detected in the assembly. The genome contained 4371 coding genes, 83 tRNA and 25 rRNA genes, as predicted by NCBI's Prokaryotic Genome Annotation Pipeline (PGAP). Among the genes, the antibiotic resistance related genes were included: Streptothricin acetdyltransferase (SatA), fosfomycin resistance protein (FosA) and metal-dependent hydrolases of the beta-lactamase superfamily I (BLI). CONCLUSION: Based on whole genome alignment and phylogenetic analysis, the strain SGAir0282 was identified to be Enterobacter sichuanensis. The strain possesses gene clusters for virulence, disease and defence, that can also be found in other multidrug resistant ECC type strains.202032127921
519310.9856Antibiotic 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
520620.9849Draft genome sequence of an extensively drug-resistant Pseudomonas aeruginosa isolate belonging to ST644 isolated from a footpad infection in a Magellanic penguin (Spheniscus magellanicus). OBJECTIVES: The incidence of multidrug-resistant bacteria in wildlife animals has been investigated to improve our knowledge of the spread of clinically relevant antimicrobial resistance genes. The aim of this study was to report the first draft genome sequence of an extensively drug-resistant (XDR) Pseudomonas aeruginosa ST644 isolate recovered from a Magellanic penguin with a footpad infection (bumblefoot) undergoing rehabilitation process. METHODS: The genome was sequenced on an Illumina NextSeq(®) platform using 150-bp paired-end reads. De novo genome assembly was performed using Velvet v.1.2.10, and the whole genome sequence was evaluated using bioinformatics approaches from the Center of Genomic Epidemiology, whereas an in-house method (mapping of raw whole genome sequence reads) was used to identify chromosomal point mutations. RESULTS: The genome size was calculated at 6436450bp, with 6357 protein-coding sequences and the presence of genes conferring resistance to aminoglycosides, β-lactams, phenicols, sulphonamides, tetracyclines, quinolones and fosfomycin; in addition, mutations in the genes gyrA (Thr83Ile), parC (Ser87Leu), phoQ (Arg61His) and pmrB (Tyr345His), conferring resistance to quinolones and polymyxins, respectively, were confirmed. CONCLUSION: This draft genome sequence can provide useful information for comparative genomic analysis regarding the dissemination of clinically significant antibiotic resistance genes and XDR bacterial species at the human-animal interface.201829277728
519430.9849Evaluation of the CosmosID Bioinformatics Platform for Prosthetic Joint-Associated Sonicate Fluid Shotgun Metagenomic Data Analysis. We previously demonstrated that shotgun metagenomic sequencing can detect bacteria in sonicate fluid, providing a diagnosis of prosthetic joint infection (PJI). A limitation of the approach that we used is that data analysis was time-consuming and specialized bioinformatics expertise was required, both of which are barriers to routine clinical use. Fortunately, automated commercial analytic platforms that can interpret shotgun metagenomic data are emerging. In this study, we evaluated the CosmosID bioinformatics platform using shotgun metagenomic sequencing data derived from 408 sonicate fluid samples from our prior study with the goal of evaluating the platform vis-à-vis bacterial detection and antibiotic resistance gene detection for predicting staphylococcal antibacterial susceptibility. Samples were divided into a derivation set and a validation set, each consisting of 204 samples; results from the derivation set were used to establish cutoffs, which were then tested in the validation set for identifying pathogens and predicting staphylococcal antibacterial resistance. Metagenomic analysis detected bacteria in 94.8% (109/115) of sonicate fluid culture-positive PJIs and 37.8% (37/98) of sonicate fluid culture-negative PJIs. Metagenomic analysis showed sensitivities ranging from 65.7 to 85.0% for predicting staphylococcal antibacterial resistance. In conclusion, the CosmosID platform has the potential to provide fast, reliable bacterial detection and identification from metagenomic shotgun sequencing data derived from sonicate fluid for the diagnosis of PJI. Strategies for metagenomic detection of antibiotic resistance genes for predicting staphylococcal antibacterial resistance need further development.201930429253
511940.9846ROCker 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
520250.9846Complete genome sequence data of multidrug-resistant Stenotrophomonas sp. strain SXG-1. Objectives A multidrug-resistant bacterium, Stenotrophomonas sp. SXG-1, was isolated from the liver of diseased hybrid sturgeon from Guizhou province, China. Methods Whole-genome sequencing was performed on the Illumina HiSeq 2500-PE125 platform with MPS (massively parallel sequencing) Illumina technology. All good quality paired reads were assembled using the SOAPdenovo into a number of scaffolds. PHI (Pathogen Host Interactions), VFDB (Virulence Factors of Pathogenic Bacteria) and ARDB (Antibiotic Resistance Genes Database) were used to analyses pathogenicity and drug resistance. Results Here we reported the complete genome sequence of Stenotrophomonas sp. SXG-1, which comprised 4534,602bp in 4077 coding sequences (CDS) with a G+C content of 66.42%. The genome contained 4 gene islands, 72 tRNAs and 13 rRNAs. According to the annotation analysis, strain SXG-1 encoded 22 genes related to the multidrug resistance. In addition to 10 genes conferring resistance to antimicrobial drugs of different classes via alternative mechanisms, 12 genes of efflux pumps were presented, 9 of which were reported for the first time in Stenotrophomonas maltophilia. Conclusion This was the first complete genome sequence of Stenotrophomonas sp. isolated from the sturgeon. The complete genome sequence of Stenotrophomonas sp. strain SXG-1 may provide insights into the mechanism of antimicrobial resistance and prevent disease.202032311503
512760.9846ResFinderFG v2.0: a database of antibiotic resistance genes obtained by functional metagenomics. Metagenomics can be used to monitor the spread of antibiotic resistance genes (ARGs). ARGs found in databases such as ResFinder and CARD primarily originate from culturable and pathogenic bacteria, while ARGs from non-culturable and non-pathogenic bacteria remain understudied. Functional metagenomics is based on phenotypic gene selection and can identify ARGs from non-culturable bacteria with a potentially low identity shared with known ARGs. In 2016, the ResFinderFG v1.0 database was created to collect ARGs from functional metagenomics studies. Here, we present the second version of the database, ResFinderFG v2.0, which is available on the Center of Genomic Epidemiology web server (https://cge.food.dtu.dk/services/ResFinderFG/). It comprises 3913 ARGs identified by functional metagenomics from 50 carefully curated datasets. We assessed its potential to detect ARGs in comparison to other popular databases in gut, soil and water (marine + freshwater) Global Microbial Gene Catalogues (https://gmgc.embl.de). ResFinderFG v2.0 allowed for the detection of ARGs that were not detected using other databases. These included ARGs conferring resistance to beta-lactams, cycline, phenicol, glycopeptide/cycloserine and trimethoprim/sulfonamide. Thus, ResFinderFG v2.0 can be used to identify ARGs differing from those found in conventional databases and therefore improve the description of resistomes.202337207327
512570.9844Do 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
907180.9843RAC: Repository of Antibiotic resistance Cassettes. Antibiotic resistance in bacteria is often due to acquisition of resistance genes associated with different mobile genetic elements. In Gram-negative bacteria, many resistance genes are found as part of small mobile genetic elements called gene cassettes, generally found integrated into larger elements called integrons. Integrons carrying antibiotic resistance gene cassettes are often associated with mobile elements and here are designated 'mobile resistance integrons' (MRIs). More than one cassette can be inserted in the same integron to create arrays that contribute to the spread of multi-resistance. In many sequences in databases such as GenBank, only the genes within cassettes, rather than whole cassettes, are annotated and the same gene/cassette may be given different names in different entries, hampering analysis. We have developed the Repository of Antibiotic resistance Cassettes (RAC) website to provide an archive of gene cassettes that includes alternative gene names from multiple nomenclature systems and allows the community to contribute new cassettes. RAC also offers an additional function that allows users to submit sequences containing cassettes or arrays for annotation using the automatic annotation system Attacca. Attacca recognizes features (gene cassettes, integron regions) and identifies cassette arrays as patterns of features and can also distinguish minor cassette variants that may encode different resistance phenotypes (aacA4 cassettes and bla cassettes-encoding β-lactamases). Gaps in annotations are manually reviewed and those found to correspond to novel cassettes are assigned unique names. While there are other websites dedicated to integrons or antibiotic resistance genes, none includes a complete list of antibiotic resistance gene cassettes in MRI or offers consistent annotation and appropriate naming of all of these cassettes in submitted sequences. RAC thus provides a unique resource for researchers, which should reduce confusion and improve the quality of annotations of gene cassettes in integrons associated with antibiotic resistance. DATABASE URL: http://www2.chi.unsw.edu.au/rac.201122140215
512690.9843Blanket antimicrobial resistance gene database with structural information, BOARDS, provides insights on historical landscape of resistance prevalence and effects of mutations in enzyme structure. Antimicrobial resistance (AMR) in pathogenic bacteria poses a significant threat to public health, yet there is still a need for development in the tools to deeply understand AMR genes based on genetic or structural information. In this study, we present an interactive web database named Blanket Overarching Antimicrobial-Resistance gene Database with Structural information (BOARDS, sbml.unist.ac.kr), a database that comprehensively includes 3,943 reported AMR gene information for 1,997 extended spectrum beta-lactamase (ESBL) and 1,946 other genes as well as a total of 27,395 predicted protein structures. These structures, which include both wild-type AMR genes and their mutants, were derived from 80,094 publicly available whole-genome sequences. In addition, we developed the rapid analysis and detection tool of antimicrobial-resistance (RADAR), a one-stop analysis pipeline to detect AMR genes across whole-genome sequencing (WGSs). By integrating BOARDS and RADAR, the AMR prevalence landscape for eight multi-drug resistant pathogens was reconstructed, leading to unexpected findings such as the pre-existence of the MCR genes before their official reports. Enzymatic structure prediction-based analysis revealed that the occurrence of mutations found in some ESBL genes was found to be closely related to the binding affinities with their antibiotic substrates. Overall, BOARDS can play a significant role in performing in-depth analysis on AMR.IMPORTANCEWhile the increasing antibiotic resistance (AMR) in pathogen has been a burden on public health, effective tools for deep understanding of AMR based on genetic or structural information remain limited. In this study, a blanket overarching antimicrobial-resistance gene database with structure information (BOARDS)-a web-based database that comprehensively collected AMR gene data with predictive protein structural information was constructed. Additionally, we report the development of a RADAR pipeline that can analyze whole-genome sequences as well. BOARDS, which includes sequence and structural information, has shown the historical landscape and prevalence of the AMR genes and can provide insight into single-nucleotide polymorphism effects on antibiotic degrading enzymes within protein structures.202438085058
5464100.9843Genomic and resistome analysis of Alcaligenes faecalis strain PGB1 by Nanopore MinION and Illumina Technologies. BACKGROUND: Drug-resistant bacteria are important carriers of antibiotic-resistant genes (ARGs). This fact is crucial for the development of precise clinical drug treatment strategies. Long-read sequencing platforms such as the Oxford Nanopore sequencer can improve genome assembly efficiency particularly when they are combined with short-read sequencing data. RESULTS: Alcaligenes faecalis PGB1 was isolated and identified with resistance to penicillin and three other antibiotics. After being sequenced by Nanopore MinION and Illumina sequencer, its entire genome was hybrid-assembled. One chromosome and one plasmid was assembled and annotated with 4,433 genes (including 91 RNA genes). Function annotation and comparison between strains were performed. A phylogenetic analysis revealed that it was closest to A. faecalis ZD02. Resistome related sequences was explored, including ARGs, Insert sequence, phage. Two plasmid aminoglycoside genes were determined to be acquired ARGs. The main ARG category was antibiotic efflux resistance and β-lactamase (EC 3.5.2.6) of PGB1 was assigned to Class A, Subclass A1b, and Cluster LSBL3. CONCLUSIONS: The present study identified the newly isolated bacterium A. faecalis PGB1 and systematically annotated its genome sequence and ARGs.202235443609
5122110.9843Clinical 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
5235120.9842Draft 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
5124130.9841Oxford 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
9070140.9841Automated annotation of mobile antibiotic resistance in Gram-negative bacteria: the Multiple Antibiotic Resistance Annotator (MARA) and database. BACKGROUND: Multiresistance in Gram-negative bacteria is often due to acquisition of several different antibiotic resistance genes, each associated with a different mobile genetic element, that tend to cluster together in complex conglomerations. Accurate, consistent annotation of resistance genes, the boundaries and fragments of mobile elements, and signatures of insertion, such as DR, facilitates comparative analysis of complex multiresistance regions and plasmids to better understand their evolution and how resistance genes spread. OBJECTIVES: To extend the Repository of Antibiotic resistance Cassettes (RAC) web site, which includes a database of 'features', and the Attacca automatic DNA annotation system, to encompass additional resistance genes and all types of associated mobile elements. METHODS: Antibiotic resistance genes and mobile elements were added to RAC, from existing registries where possible. Attacca grammars were extended to accommodate the expanded database, to allow overlapping features to be annotated and to identify and annotate features such as composite transposons and DR. RESULTS: The Multiple Antibiotic Resistance Annotator (MARA) database includes antibiotic resistance genes and selected mobile elements from Gram-negative bacteria, distinguishing important variants. Sequences can be submitted to the MARA web site for annotation. A list of positions and orientations of annotated features, indicating those that are truncated, DR and potential composite transposons is provided for each sequence, as well as a diagram showing annotated features approximately to scale. CONCLUSIONS: The MARA web site (http://mara.spokade.com) provides a comprehensive database for mobile antibiotic resistance in Gram-negative bacteria and accurately annotates resistance genes and associated mobile elements in submitted sequences to facilitate comparative analysis.201829373760
9066150.9840VRprofile: gene-cluster-detection-based profiling of virulence and antibiotic resistance traits encoded within genome sequences of pathogenic bacteria. VRprofile is a Web server that facilitates rapid investigation of virulence and antibiotic resistance genes, as well as extends these trait transfer-related genetic contexts, in newly sequenced pathogenic bacterial genomes. The used backend database MobilomeDB was firstly built on sets of known gene cluster loci of bacterial type III/IV/VI/VII secretion systems and mobile genetic elements, including integrative and conjugative elements, prophages, class I integrons, IS elements and pathogenicity/antibiotic resistance islands. VRprofile is thus able to co-localize the homologs of these conserved gene clusters using HMMer or BLASTp searches. With the integration of the homologous gene cluster search module with a sequence composition module, VRprofile has exhibited better performance for island-like region predictions than the other widely used methods. In addition, VRprofile also provides an integrated Web interface for aligning and visualizing identified gene clusters with MobilomeDB-archived gene clusters, or a variety set of bacterial genomes. VRprofile might contribute to meet the increasing demands of re-annotations of bacterial variable regions, and aid in the real-time definitions of disease-relevant gene clusters in pathogenic bacteria of interest. VRprofile is freely available at http://bioinfo-mml.sjtu.edu.cn/VRprofile.201828077405
5881160.9840A 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
9076170.9839ResiDB: 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
5200180.9839Whole 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
9074190.9839BacAnt: A Combination Annotation Server for Bacterial DNA Sequences to Identify Antibiotic Resistance Genes, Integrons, and Transposable Elements. Whole genome sequencing (WGS) of bacteria has become a routine method in diagnostic laboratories. One of the clinically most useful advantages of WGS is the ability to predict antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) in bacterial sequences. This allows comprehensive investigations of such genetic features but can also be used for epidemiological studies. A plethora of software programs have been developed for the detailed annotation of bacterial DNA sequences, such as rapid annotation using subsystem technology (RAST), Resfinder, ISfinder, INTEGRALL and The Transposon Registry. Unfortunately, to this day, a reliable annotation tool of the combination of ARGs and MGEs is not available, and the generation of genbank files requires much manual input. Here, we present a new webserver which allows the annotation of ARGs, integrons and transposable elements at the same time. The pipeline generates genbank files automatically, which are compatible with Easyfig for comparative genomic analysis. Our BacAnt code and standalone software package are available at https://github.com/xthua/bacant with an accompanying web application at http://bacant.net.202134367079