scholarly journals Whole-genome sequence analyses of Glaesserella parasuis isolates reveals extensive genomic variation and diverse antibiotic resistance determinants

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9293
Author(s):  
Xiulin Wan ◽  
Xinhui Li ◽  
Todd Osmundson ◽  
Chunling Li ◽  
He Yan
Keyword(s):  
Antibiotic Resistance ◽  
Genetic Variation ◽  
Genome Sequence ◽  
Resistance Genes ◽  
Genomic Variation ◽  
Whole Genome Sequence ◽  
Comparative Genomic ◽  
Broad Host Range ◽  
Whole Genome ◽  
Resistance Determinants

Background Glaesserella parasuis (G. parasuis) is a respiratory pathogen of swine and the etiological agent of Glässer’s disease. The structural organization of genetic information, antibiotic resistance genes, potential pathogenicity, and evolutionary relationships among global G. parasuis strains remain unclear. The aim of this study was to better understand patterns of genetic variation, antibiotic resistance factors, and virulence mechanisms of this pathogen. Methods The whole-genome sequence of a ST328 isolate from diseased swine in China was determined using Pacbio RS II and Illumina MiSeq platforms and compared with 54 isolates from China sequenced in this study and 39 strains from China and eigtht other countries sequenced by previously. Patterns of genetic variation, antibiotic resistance, and virulence mechanisms were investigated in relation to the phylogeny of the isolates. Electrotransformation experiments were performed to confirm the ability of pYL1—a plasmid observed in ST328—to confer antibiotic resistance. Results The ST328 genome contained a novel Tn6678 transposon harbouring a unique resistance determinant. It also contained a small broad-host-range plasmid pYL1 carrying aac(6’)-Ie-aph(2”)-Ia and blaROB-1; when transferred to Staphylococcus aureus RN4220 by electroporation, this plasmid was highly stable under kanamycin selection. Most (85.13–91.74%) of the genetic variation between G. parasuis isolates was observed in the accessory genomes. Phylogenetic analysis revealed two major subgroups distinguished by country of origin, serotype, and multilocus sequence type (MLST). Novel virulence factors (gigP, malQ, and gmhA) and drug resistance genes (norA, bacA, ksgA, and bcr) in G. parasuis were identified. Resistance determinants (sul2, aph(3”)-Ib, norA, bacA, ksgA, and bcr) were widespread across isolates, regardless of serovar, isolation source, or geographical location. Conclusions Our comparative genomic analysis of worldwide G. parasuis isolates provides valuable insight into the emergence and transmission of G. parasuis in the swine industry. The result suggests the importance of transposon-related and/or plasmid-related gene variations in the evolution of G. parasuis.

scholarly journals Whole-Genome Sequence of ablaOXA-48-Harboring Raoultella ornithinolytica Clinical Isolate from Lebanon

2016 ◽  
Vol 60 (4) ◽  
pp. 2548-2550 ◽  
Author(s):  
Charbel Al-Bayssari ◽  
Abiola Olumuyiwa Olaitan ◽  
Thongpan Leangapichart ◽  
Liliane Okdah ◽  
Fouad Dabboussi ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Clinical Isolate ◽  
Genome Sequence ◽  
Resistance Genes ◽  
Molecular Mechanisms ◽  
Antibiotic Resistance Genes ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Content Type ◽  
Genetic Organization

ABSTRACTWe analyzed the whole-genome sequence of ablaOXA-48-harboringRaoultella ornithinolyticaclinical isolate from a patient in Lebanon. The size of theRaoultella ornithinolyticaCMUL058 genome was 5,622,862 bp, with a G+C content of 55.7%. We deciphered all the molecular mechanisms of antibiotic resistance, and we compared our genome to other availableR. ornithinolyticagenomes in GenBank. The resistome consisted of 9 antibiotic resistance genes, including a plasmidicblaOXA-48gene whose genetic organization is also described.

Identification of bacterial antibiotic resistance genes in next-generation sequencing data (review of literature)

2021 ◽  
Vol 66 (11) ◽  
pp. 684-688
Author(s):  
A. V. Chaplin ◽  
M. Korzhanova ◽  
D. O. Korostin
Keyword(s):  
Antibiotic Resistance ◽  
Genome Sequence ◽  
Protein Sequence ◽  
Susceptibility Testing ◽  
Sequence Data ◽  
Genetic Resistance ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
Resistance Determinants

The spread of antibiotic-resistant human bacterial pathogens is a serious threat to modern medicine. Antibiotic susceptibility testing is essential for treatment regimens optimization and preventing dissemination of antibiotic resistance. Therefore, development of antibiotic susceptibility testing methods is a priority challenge of laboratory medicine. The aim of this review is to analyze the capabilities of the bioinformatics tools for bacterial whole genome sequence data processing. The PubMed database, Russian scientific electronic library eLIBRARY, information networks of World health organization and European Society of Clinical Microbiology and Infectious Diseases (ESCMID) were used during the analysis. In this review, the platforms for whole genome sequencing, which are suitable for detection of bacterial genetic resistance determinants, are described. The classic step of genetic resistance determinants searching is an alignment between the query nucleotide/protein sequence and the subject (database) nucleotide/protein sequence, which is performed using the nucleotide and protein sequence databases. The most commonly used databases are Resfinder, CARD, Bacterial Antimicrobial Resistance Reference Gene Database. The results of the resistance determinants searching in genome assemblies is more correct in comparison to results of the searching in contigs. The new resistance genes searching bioinformatics tools, such as neural networks and machine learning, are discussed in the review. After critical appraisal of the current antibiotic resistance databases we designed a protocol for predicting antibiotic resistance using whole genome sequence data. The designed protocol can be used as a basis of the algorithm for qualitative and quantitative antimicrobial susceptibility testing based on whole genome sequence data.

Genome Assessment of Antibiotic Resistance Genes in Probiotic Bacteria and a Literature Review

2021 ◽  
Author(s):  
Mehdi Fatahi-Bafghi ◽  
Sara Naseri ◽  
Ali Alizehi
Keyword(s):  
Antibiotic Resistance ◽  
Genome Sequence ◽  
Resistance Genes ◽  
Pathogenic Bacteria ◽  
Antibiotic Resistance Genes ◽  
Probiotic Bacteria ◽  
Whole Genome Sequence ◽  
Probiotic Properties ◽  
Antibiotic Resistant ◽  
To Come

Abstract Having various clinical applications, probiotic bacteria are currently used in the diet. There are reports of antibiotic resistance genes (ARGs) in these bacteria that can be transferred to other microflora and pathogenic bacteria. The aim of the study is to examine whole-genome sequence analysis in bacteria with probiotic properties. Moreover, this study follows existing issues about the importance and presence of ARGs in these bacteria the dangers of which may affect human health in the years to come. In the present study, 126 complete probiotic bacterial genomes were collected and analysed for ARGs. The results of the study shows there are various antibiotic resistant genes of in these bacteria some of which can be transmitted to other bacteria. We propose microorganisms be applied as a probiotic element in various types of products, antibiogram be conducted for a large number of antibiotics and analysis of complete genome sequence for ARGs prediction.

scholarly journals MTBseq: a comprehensive pipeline for whole genome sequence analysis of Mycobacterium tuberculosis complex isolates

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5895 ◽  
Author(s):  
Thomas Andreas Kohl ◽  
Christian Utpatel ◽  
Viola Schleusener ◽  
Maria Rosaria De Filippo ◽  
Patrick Beckert ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Mycobacterium Tuberculosis ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome Sequencing Data ◽  
Phylogenomic Analysis ◽  
Whole Genome ◽  
Sequencing Data ◽  
Desktop Computer

Analyzing whole-genome sequencing data of Mycobacterium tuberculosis complex (MTBC) isolates in a standardized workflow enables both comprehensive antibiotic resistance profiling and outbreak surveillance with highest resolution up to the identification of recent transmission chains. Here, we present MTBseq, a bioinformatics pipeline for next-generation genome sequence data analysis of MTBC isolates. Employing a reference mapping based workflow, MTBseq reports detected variant positions annotated with known association to antibiotic resistance and performs a lineage classification based on phylogenetic single nucleotide polymorphisms (SNPs). When comparing multiple datasets, MTBseq provides a joint list of variants and a FASTA alignment of SNP positions for use in phylogenomic analysis, and identifies groups of related isolates. The pipeline is customizable, expandable and can be used on a desktop computer or laptop without any internet connection, ensuring mobile usage and data security. MTBseq and accompanying documentation is available from https://github.com/ngs-fzb/MTBseq_source.

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