scholarly journals Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates

2018 ◽  
Author(s):  
Valentina Galata ◽  
Cédric C. Laczny ◽  
Christina Backes ◽  
Georg Hemmrich-Stanisak ◽  
Susanne Schmolke ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Academic Research ◽  
Species Level ◽  
Statistical Testing ◽  
Clinical Isolates ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Resistance Factors ◽  
Resistance Patterns ◽  
Resistance Rates

AbstractEmerging antibiotic resistance is a major global health threat. The analysis of nucleic acid sequences linked to susceptibility phenotypes facilitates the study of genetic antibiotic resistance determinants to inform molecular diagnostics and drug development. We collected genetic data (11,087 newly sequenced whole genomes) and culture-based resistance profiles (10,991 of 11,087 isolates were comprehensively tested against 22 antibiotics in total) of clinical isolates including 18 main species spanning a time period of 30 years. Species and drug specific resistance patterns could be observed including increasing resistance rates forAcinetobacter baumanniito carbapenems and forEscherichia colito fluoroquinolones. Species-level pan-genomes were constructed to reflect the genetic repertoire of the respective species such as conserved essential genes and known resistance factors. Integrating phenotypes and genotypes through species-level pan-genomes allowed to infer gene-drug resistance associations using statistical testing. The isolate collection and the analysis results have been integrated into a resource, GEAR-base, available for academic research use free of charge athttps://gear-base.com.

scholarly journals Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates

2019 ◽  
Vol 17 (2) ◽  
pp. 169-182 ◽  
Author(s):  
Valentina Galata ◽  
Cédric C. Laczny ◽  
Christina Backes ◽  
Georg Hemmrich-Stanisak ◽  
Susanne Schmolke ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Clinical Isolates ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

scholarly journals Prevalence of Virulence Genes and Drug Resistance Profiles of Pseudomonas aeruginosa Isolated From Clinical Specimens

2021 ◽  
Vol 14 (8) ◽  
Author(s):  
Seyed Ali Bazghandi ◽  
Mohsen Arzanlou ◽  
Hadi Peeridogaheh ◽  
Hamid Vaez ◽  
Amirhossein Sahebkar ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Drug Resistance ◽  
Antibiotic Resistance ◽  
Virulence Genes ◽  
Virulence Gene ◽  
Clinical Isolates ◽  
Diffusion Method ◽  
Disk Diffusion Method ◽  
Clinical Specimens ◽  
Resistance Rates

Background: Drug resistance and virulence genes are two key factors for the colonization of Pseudomonas aeruginosa in settings with high antibiotic pressure, such as hospitals, and the development of hospital-acquired infections. Objectives: The objective of this study was to investigate the prevalence of drug resistance and virulence gene profiles in clinical isolates of P. aeruginosa in Ardabil, Iran. Methods: A total of 84 P. aeruginosa isolates were collected from clinical specimens of Ardabil hospitals and confirmed using laboratory standard tests. The disk diffusion method was used for antibiotic susceptibility testing and polymerase chain reaction (PCR) for the identification of P. aeruginosa virulence genes. Results: The highest and the lowest antibiotic resistance rates of P. aeruginosa strains were against ticarcillin-clavulanate (94%) and doripenem (33.3%), respectively. In addition, the frequency of multidrug-resistant (MDR) P. aeruginosa was 55.9%. The prevalence of virulence factor genes was as follows: algD 84.5%, lasB 86.9%, plcH 86.9%, plcN 86.9%, exoU 56%, exoS 51.2%, toxA 81%, nan1 13.1%, and pilB 33.3%. A significant association was observed between resistance to some antibiotics and the prevalence of virulence genes in P. aeruginosa. Conclusions: Our results revealed a high prevalence of antibiotic resistance, especially MDR, and virulence-associated genes in clinical isolates of P. aeruginosa in Ardabil hospitals. Owing to the low resistance rates against doripenem, gentamicin, and tobramycin, these antibiotics are recommended for the treatment of infections caused by highly resistant and virulent P. aeruginosa strains.

scholarly journals An outbreak of methicillin resistant Staphylococcus epidermidis among neonates in a hospital in Saudi Arabia

2011 ◽  
Vol 5 (10) ◽  
pp. 692-699 ◽  
Author(s):  
Maha Abd El Hafez ◽  
Noha G. Khalaf ◽  
Mohamed El Ahmady ◽  
Ahmed Abd El Aziz ◽  
Abd El Gawad Hashim
Keyword(s):  
Saudi Arabia ◽  
Antibiotic Resistance ◽  
Staphylococcus Epidermidis ◽  
Neonatal Intensive Care ◽  
Meca Gene ◽  
Neonatal Intensive Care Units ◽  
Methicillin Resistant ◽  
Resistance Patterns ◽  
Clonal Origin ◽  
Resistance Rates

Introduction: Staphylococcus epidermidis is a pathogen associated with nosocomial infection in neonatal intensive care units (NICU). This study investigates an outbreak of methicillin resistant S. epidermidis in an NICU in a hospital in Saudi Arabia. Methodology: A total of 41 isolates identified as Gram-positive cocci were obtained from blood culture, umbilical wound swabs and endotracheal aspirate specimens of neonates, of which 29 were identified as S. epidermidis. Bacterial identification at the species level and determination of antibiotic resistance were performed by MicroScan (Dade Behring, USA). Genotyping was completed using randomly amplified polymorphic DNA (RAPD) and the mecA gene was detected by PCR. Results: All 29 S. epidermidis isolates were found to be resistant to oxacillin and were positive for the mecA gene. The isolates showed several multidrug-resistance patterns; the resistance rates to gentamicin, erythromycin, clindamycin, and trimethoprim/sulfamethoxazole were 89.7%, 86.2%, 75.9% and 72.4%, respectively. All isolates were susceptible to vancomycin, teicoplanin, rifampin, synercid, and ciprofloxacin. Several genotypic and phenotypic patterns were detected among the S. epidermidis isolates: antibiogram typing showed seven different patterns, one of which was shared by 65% of the isolates, whereas the most prevalent RAPD genotype was shared by only five S. epidermidis isolates, and did not correlate with antibiotic resistance phenotype. Conclusion: The diverse clonal origin of tested isolates indicates the presence of multiple S. epidermidis strains among neonates in the NICU setting

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.

scholarly journals Draft Genome Sequences of Ciprofloxacin-Resistant Salmonella enterica Strains with Multiple-Antibiotic Resistance, Isolated from Imported Foods

2017 ◽  
Vol 5 (45) ◽  
Author(s):  
Ashraf A. Khan ◽  
Bijay K. Khajanchi ◽  
Sana A. Khan ◽  
Christopher A. Elkins ◽  
Steven L. Foley
Keyword(s):  
Antibiotic Resistance ◽  
Salmonella Enterica ◽  
Draft Genome ◽  
Resistance Mechanisms ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Genome Sequences ◽  
Content Type ◽  
Imported Foods ◽  
High Level

ABSTRACT We report here the draft genome sequences of 15 ciprofloxacin-resistant Salmonella enterica strains with resistance to multiple other antibiotics, including aminoglycosides, β-lactams, sulfonamides, tetracycline, and trimethoprim, isolated from different imported foods. Three strains (NCTR75, NCTR281, and NCTR350) showed a high level of ciprofloxacin resistance compared to that of the other isolates. The whole-genome sequencing data provide a better understanding of the antibiotic resistance mechanisms and virulence properties of these isolates.

scholarly journals Network analysis reveals differential metabolic functionality in antibiotic-resistantPseudomonas aeruginosa

2018 ◽  
Author(s):  
Laura J. Dunphy ◽  
Phillip Yen ◽  
Jason A. Papin
Keyword(s):  
Antibiotic Resistance ◽  
Carbon Sources ◽  
Growth Dynamics ◽  
Metabolic Phenotype ◽  
Metabolic Adaptation ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Drug Induced ◽  
Antibiotic Resistant ◽  
A Genome

AbstractMetabolic adaptations accompanying the development of antibiotic resistance in bacteria remain poorly understood. To interrogate this relationship, we profiled the growth of lab-evolved antibiotic-resistant lineages of the opportunistic pathogenPseudomonas aeruginosaacross 190 unique carbon sources. We semi-automatically calculated growth dynamics (maximum growth density, growth rate, and time to mid-exponential phase) of over 2,800 growth curves. These data revealed that the evolution of antibiotic resistance resulted in systems-level changes to growth dynamics and metabolic phenotype. Drug-resistant lineages predominantly displayed decreased growth relative to the ancestral lineage; however, resistant lineages occasionally displayed enhanced growth on certain carbon sources, indicating that adaption to drug can provide a growth advantage in certain environments. A genome-scale metabolic network reconstruction (GENRE) ofP. aeruginosastrain UCBPP-PA14 was paired with whole-genome sequencing data of one of the drug-evolved lineages to predict genes contributing to observed changes in metabolism. Finally, we experimentally validatedin silicopredictions to identify genes mutated in resistantP. aeruginosaaffecting loss of catabolic function. Our results build upon previous mechanistic knowledge of drug-induced metabolic adaptation and provide a framework for the identification of metabolic limitations in antibiotic-resistant pathogens. Robust drug-driven changes in bacterial metabolism have the potential to be exploited to select against antibiotic-resistant populations in chronic infections.

scholarly journals TETyper: a bioinformatic pipeline for classifying variation and genetic contexts of transposable elements from short-read whole-genome sequencing data

2018 ◽  
Author(s):  
Anna E Sheppard ◽  
Nicole Stoesser ◽  
Ian German-Mesner ◽  
Kasi Vegesana ◽  
A Sarah Walker ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Transposable Elements ◽  
Genome Sequencing ◽  
Resistance Genes ◽  
Whole Genome Sequencing Data ◽  
Sequence Variants ◽  
Whole Genome ◽  
Sequencing Data ◽  
Bioinformatic Pipeline ◽  
Short Read

ABSTRACTMuch of the worldwide dissemination of antibiotic resistance has been driven by resistance gene associations with mobile genetic elements (MGEs), such as plasmids and transposons. Although increasing, our understanding of resistance spread remains relatively limited, as methods for tracking mobile resistance genes through multiple species, strains and plasmids are lacking. We have developed a bioinformatic pipeline for tracking variation within, and mobility of, specific transposable elements (TEs), such as transposons carrying antibiotic resistance genes. TETyper takes short-read whole-genome sequencing data as input and identifies single-nucleotide mutations and deletions within the TE of interest, to enable tracking of specific sequence variants, as well as the surrounding genetic context(s), to enable identification of transposition events. To investigate global dissemination of Klebsiella pneumoniae carbapenemase (KPC) and its associated transposon Tn4401, we applied TETyper to a collection of >3000 publicly available Illumina datasets containing blaKPC. This revealed surprising diversity, with >200 distinct flanking genetic contexts for Tn4401, indicating high levels of transposition. Integration of sample metadata revealed insights into associations between geographic locations, host species, Tn4401 sequence variants and flanking genetic contexts. To demonstrate the ability of TETyper to cope with high copy number TEs and to track specific short-term evolutionary changes, we also applied it to the insertion sequence IS26 within a defined K. pneumoniae outbreak. TETyper is implemented in python and is freely available at https://github.com/aesheppard/TETyper.

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