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520100.9923Complete 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
520210.9923Complete 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
519320.9922Antibiotic 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
512730.9918ResFinderFG 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
512240.9916Clinical 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
546450.9916Genomic 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
254060.9915Equine sinusitis aetiology is linked to sinus microbiome by amplicon sequencing. BACKGROUND: Information regarding the microbiome in sinusitis using genetic sequencing is lacking and more-in-depth understanding of the microbiome could improve antimicrobial selection and treatment outcomes for cases of primary sinusitis. OBJECTIVES: To describe sinus microbiota in samples from horses with sinusitis and compare microbiota and the presence of antimicrobial resistance genes between primary, dental-related and other secondary causes of sinusitis. STUDY DESIGN: Retrospective case series. METHODS: Records of equine sinusitis from 2017 to 2021 were reviewed and historical microbial amplicon sequence data were obtained from clinical diagnostic testing of sinus secretions. Following bioinformatic processing of bacterial and fungal sequence data, the sinus microbiota and importance of sinusitis aetiology among other factors were investigated from the perspectives of alpha diversity (e.g., number of operational taxonomic units [OTUs], Hill1 Diversity), beta diversity, and differentially abundant taxa. Quantitative PCR allowed for comparisons of estimated bacterial abundance and detection rate of common antibiotic resistance-associated genes. In a smaller subset, longitudinal analysis was performed to evaluate similarity in samples over time. RESULTS: Of 81 samples analysed from 70 horses, the bacterial microbiome was characterised in 66, and fungal in five. Only sinusitis aetiology was shown to significantly influence microbiome diversity and composition (p < 0.05). Dental-related sinusitis (n = 44) was associated with a significantly higher proportion of obligate anaerobic bacteria, whereas primary sinusitis (n = 12) and other (n = 10) groups were associated with fewer bacteria and higher proportions of facultative anaerobic and aerobic genera. Antimicrobial resistance genes and fungal components were exclusively identified in dental-related sinusitis. MAIN LIMITATIONS: Retrospective nature, incomplete prior antimicrobial administration data. CONCLUSIONS: Molecular characterisation in sinusitis identifies microbial species which may be difficult to isolate via culture, and microbiome profiling can differentiate sinusitis aetiology, which may inform further treatment, including antimicrobial therapy.202336199163
546870.9914Whole-genome sequence of a putative pathogenic Bacillus sp. strain SD-4 isolated from cattle feed. OBJECTIVES: The present study describes the draft genome sequence of a novel Bacillus sp. strain SD-4 isolated from animal feed. The study aims to get a deeper insight into antimicrobial resistance and secondary metabolite biosynthetic gene clusters (BGCs) and the association between them. METHODS: The strain SD-4 was preliminarily evaluated for antibacterial activities, motility, biofilm formation, and enterotoxin production using in vitro assays. The genome of strain SD-4 was sequenced using the Illumina HiSeq 2500 platform with paired-end reads. The reads were assembled and annotated using SPAdes and PGAP, respectively. The genome was further analysed using several bioinformatics tools, including TYGS, AntiSMASH, RAST, PlasmidFinder, VFDB, VirulenceFinder, CARD, PathogenFinder, MobileElement finder, IslandViewer, and CRISPRFinder. RESULTS: In vitro assays showed that the strain is motile, synthesises biofilm, and produces an enterotoxin and antibacterial metabolites. The genome analysis revealed that the strain SD-4 carries antimicrobial resistance genes (ARGs), virulence factors, and beneficial secondary metabolite BGCs. Further genome analysis showed interesting genome architectures containing several mobile genetic elements, including two plasmid replicons (repUS22 and rep20), five prophages, and at least four genomic islands (GIs), including one Listeria pathogenicity island LIPI-1. Moreover, the strain SD-4 is identified as a putative human pathogen. CONCLUSION: The genome of strain SD-4 harbours several BGCs coding for biologically active metabolites. It also contains antimicrobial resistance genes and is identified as a potential human pathogen. These results can be used to better comprehend antibiotic resistance in environmental bacteria that are not influenced by human intervention.202235413450
306880.9913Metagenomic profiling of pigeon faecal microbiota: insights into microbial diversity, pathogens, and antimicrobial resistance genes. Rock pigeon (Columba livia) droppings harbour diverse microorganisms, including potential pathogens. This study utilised shotgun metagenomic sequencing to analyse pigeon faecal microbiota and identify potential pathogens. Fresh faecal samples (273) were collected within Universiti Tunku Abdul Rahman Kampar campus, Malaysia. Total genome and viral genomes were extracted and sequenced using the Illumina NovaSeq 6000 platform. Taxonomic assignment, antimicrobial resistance (AMR) gene detection, and viral genome assembly were conducted using the CZ ID platform. The microbial diversity was predominated by bacteria, followed by eukaryotic viruses and fungi, with no archaea were detected. Pseudomonadota (84.44%) and Bacillota (15.26%) were the predominant bacterial phyla, with Pseudomonadota being 5.5 times more abundant, indicating potential enteric-like issues within the pigeon flocks. Approximately 5.11% of the bacterial community (comprising 38 species), was identified as potential pathogens, could primarily cause human enteric and respiratory infections. Nineteen AMR genes were detected, primarily associated with pathogenic Shigella, Salmonella, and Klebsiella. The presence of AMR genes and possible co-circulation among pathogenic bacteria impose the risk of emergence of multidrug-resistant bacteria. Nine avian virus species were detected. The predominant DNA virus, pigeon circovirus (73.23%) could cause immunosuppression, predisposing pigeons to secondary infections by E. coli, K. pneumoniae, and rotaviruses. The predominant RNA virus, rotaviruses (80.43%) could cause enteric diseases in both humans and birds. The fungal community comprised Kazachstania (94.11%) and Trichosporon (3.56%), with K. bovina and T. asahii identified as human pathogens. This study highlights the compelling need for effective pigeon control in dining areas, ventilation systems, and healthcare facilities.202540833454
523690.9912Genome 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
5161100.9912Genomic 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
5465110.9912The genotypic characterization of Streptococcus pluranimalium from aborted bovine fetuses in British Columbia, Canada. INTRODUCTION: Bovine abortions result in significant economic losses to dairy producers, and bacteria are among the most common causes of these abortions. In 2021, Streptococcus pluranimalium was isolated from a dairy abortion case for the first time in British Columbia (BC), Canada. This bacterium has previously been recovered from the reproductive tracts of dairy cattle and various other species, including humans. METHODS: Between 2021 and 2023, S. pluranimalium was isolated from the placenta, fetal lung, and/or fetal abomasal contents of 10 aborted dairy fetuses submitted for routine abortion diagnostics. This study was conducted to better characterize the genotype of these 10 isolates. The histopathology of the bovine abortions was examined, and the BC strains were sequenced using Nanopore technology and underwent bioinformatic analysis. RESULTS: The BC strains had an average genome size of 2,313,582 base pairs and an average GC content of 38.59%. Based on whole genome phylogeny, the BC strains were clustered together and distinctly separated from other publicly available strains of this species from different regions and isolation sources. Through Clusters of Orthologous Groups analysis, the BC strains contained a larger proportion of genes associated with the mobilome. Additionally, although we identified only a few antibiotic resistance genes or virulence factors (VFs) in these strains, several of these genes were located within prophage sequences. DISCUSSION: Although the clinical and pathological significance of these bacteria in most abortion cases remains unclear, our findings underscore the importance of continued surveillance and research into uncommon pathogens to better understand their biology and potential impact on human and animal health.202540574982
5124120.9912Oxford 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
9083130.9911ARGNet: 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
2484140.9911Multilocus 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
5126150.9911Blanket 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
3117160.9911Detection of antimicrobial resistance genes in urban air. To understand antibiotic resistance in pathogenic bacteria, we need to monitor environmental microbes as reservoirs of antimicrobial resistance genes (ARGs). These bacteria are present in the air and can be investigated with the whole metagenome shotgun sequencing approach. This study aimed to investigate the feasibility of a method for metagenomic analysis of microbial composition and ARGs in the outdoor air. Air samples were collected with a Harvard impactor in the PM(10) range at 50 m from a hospital in Budapest. From the DNA yielded from samples of PM(10) fraction single-end reads were generated with an Ion Torrent sequencer. During the metagenomic analysis, reads were classified taxonomically. The core bacteriome was defined. Reads were assembled to contigs and the ARG content was analyzed. The dominant genera in the core bacteriome were Bacillus, Acinetobacter, Leclercia and Paenibacillus. Among the identified ARGs best hits were vanRA, Bla1, mphL, Escherichia coli EF-Tu mutants conferring resistance to pulvomycin; BcI, FosB, and mphM. Despite the low DNA content of the samples of PM(10) fraction, the number of detected airborne ARGs was surprisingly high.202134964297
7741170.9911Microbial diversity of a full-scale UASB reactor applied to poultry slaughterhouse wastewater treatment: integration of 16S rRNA gene amplicon and shotgun metagenomic sequencing. The 16S rRNA gene amplicon and whole-genome shotgun metagenomic (WGSM) sequencing approaches were used to investigate wide-spectrum profiles of microbial composition and metabolic diversity from a full-scale UASB reactor applied to poultry slaughterhouse wastewater treatment. The data were generated by using MiSeq 2 × 250 bp and HiSeq 2 × 150 bp Illumina sequencing platforms for 16S amplicon and WGSM sequencing, respectively. Each approach revealed a distinct microbial community profile, with Pseudomonas and Psychrobacter as predominant genus for the WGSM dataset and Clostridium and Methanosaeta for the 16S rRNA gene amplicon dataset. The virome characterization revealed the presence of two viral families with Bacteria and Archaea as host, Myoviridae, and Siphoviridae. A wide functional diversity was found with predominance of genes involved in the metabolism of acetone, butanol, and ethanol synthesis; and one-carbon metabolism (e.g., methanogenesis). Genes related to the acetotrophic methanogenesis pathways were more abundant than methylotrophic and hydrogenotrophic, corroborating the taxonomic results that showed the prevalence of the acetotrophic genus Methanosaeta. Moreover, the dataset indicated a variety of metabolic genes involved in sulfur, nitrogen, iron, and phosphorus cycles, with many genera able to act in all cycles. BLAST analysis against Antibiotic Resistance Genes Database (ARDB) revealed that microbial community contained 43 different types of antibiotic resistance genes, some of them were associated with growth chicken promotion (e.g., bacitracin, tetracycline, and polymyxin).201728229558
3485180.9910Abundance and Diversity of Phages, Microbial Taxa, and Antibiotic Resistance Genes in the Sediments of the River Ganges Through Metagenomic Approach. In this study, we have analyzed the metagenomic DNA from the pooled sediment sample of the river Ganges to explore the abundance and diversity of phages, microbial community, and antibiotic resistance genes (ARGs). Utilizing data from Illumina platform, 4,174 (∼0.0013%) reads were classified for the 285 different DNA viruses largely dominated by the group of 260 distinctive phages (3,602 reads, ∼86.3%). Among all, Microcystis (782 hits), Haemophilus (403), Synechococcus (386), Pseudomonas (279), Enterococcus (232), Bacillus (196), Rhodococcus (166), Caulobacter (163), Salmonella (146), Enterobacteria (143), Mycobacterium and (128) phages show the highest abundance and account for ∼90% of the total identified phages. In addition, we have also identified corresponding host pertaining to these phages. Mainly, Proteobacteria (∼69.3%) dominates the microbial population structure. Primarily, orders such as Caulobacterales (∼28%), Burkholderiales (∼13.9%), Actinomycetales (∼13.7%), and Pseudomonadales (∼7.5%) signify the core section. Furthermore, 21,869 (∼0.00695%) reads were classified in 20 ARG types (classes) and 240 ARGs (subtypes), among which 4 ARG types, namely multidrug resistance (12,041 reads, ∼55%), bacitracin (3,202 reads, ∼15%), macrolide-lincosamide-streptogramin (1,744 reads, ∼7.98%), and fosmidomycin (990 reads, ∼4.53%), have the highest abundance. Simultaneously, six resistance mechanisms were also recognized with the dominance of antibiotic efflux (72.8%, 15,919 reads). The results unveil the distribution of (pro)-phages; microbial community; and various ARGs in the Ganges river sediments.202133913739
2594190.9910Longitudinal changes in the nasopharyngeal resistome of South African infants using shotgun metagenomic sequencing. INTRODUCTION: Nasopharyngeal (NP) colonization with antimicrobial-resistant bacteria is a global public health concern. Antimicrobial-resistance (AMR) genes carried by the resident NP microbiota may serve as a reservoir for transfer of resistance elements to opportunistic pathogens. Little is known about the NP antibiotic resistome. This study longitudinally investigated the composition of the NP antibiotic resistome in Streptococcus-enriched samples in a South African birth cohort. METHODS: As a proof of concept study, 196 longitudinal NP samples were retrieved from a subset of 23 infants enrolled as part of broader birth cohort study. These were selected on the basis of changes in serotype and antibiogram over time. NP samples underwent short-term enrichment for streptococci prior to total nucleic acid extraction and whole metagenome shotgun sequencing (WMGS). Reads were assembled and aligned to pneumococcal reference genomes for the extraction of streptococcal and non-streptococcal bacterial reads. Contigs were aligned to the Antibiotic Resistance Gene-ANNOTation database of acquired AMR genes. RESULTS: AMR genes were detected in 64% (125/196) of the samples. A total of 329 AMR genes were detected, including 36 non-redundant genes, ranging from 1 to 14 genes per sample. The predominant AMR genes detected encoded resistance mechanisms to beta-lactam (52%, 172/329), macrolide-lincosamide-streptogramin (17%, 56/329), and tetracycline antibiotics (12%, 38/329). MsrD, ermB, and mefA genes were only detected from streptococcal reads. The predominant genes detected from non- streptococcal reads included blaOXA-60, blaOXA-22, and blaBRO-1. Different patterns of carriage of AMR genes were observed, with only one infant having a stable carriage of mefA, msrD and tetM over a long period. CONCLUSION: This study demonstrates that WMGS can provide a broad snapshot of the NP resistome and has the potential to provide a comprehensive assessment of resistance elements present in this niche.202032320455