scholarly journals Integrative Analysis of Whole Genome Sequencing and Phenotypic Resistance Toward Prediction of Trimethoprim-Sulfamethoxazole Resistance in Staphylococcus aureus

2021 ◽  
Vol 11 ◽  
Author(s):  
Dennis Nurjadi ◽  
Elfi Zizmann ◽  
Quan Chanthalangsy ◽  
Klaus Heeg ◽  
Sébastien Boutin
Keyword(s):  
Staphylococcus Aureus ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Point Mutations ◽  
Genetic Lineage ◽  
Whole Genome ◽  
Single Mutation ◽  
Protein Sequence Analysis ◽  
Sequencing Data ◽  
Phenotypic Resistance

As whole genome sequencing is becoming more accessible and affordable for clinical microbiological diagnostics, the reliability of genotypic antimicrobial resistance (AMR) prediction from sequencing data is an important issue to address. Computational AMR prediction can be performed at multiple levels. The first-level approach, such as simple AMR search relies heavily on the quality of the information fed into the database. However, AMR due to mutations are often undetected, since this is not included in the database or poorly documented. Using co-trimoxazole (trimethoprim-sulfamethoxazole) resistance in Staphylococcus aureus, we compared single-level and multi-level analysis to investigate the strengths and weaknesses of both approaches. The results revealed that a single mutation in the AMR gene on the nucleotide level may produce false positive results, which could have been detected if protein sequence analysis would have been performed. For AMR predictions based on chromosomal mutations, such as the folP gene of S. aureus, natural genetic variations should be taken into account to differentiate between variants linked to genetic lineage (MLST) and not over-estimate the potential resistant variants. Our study showed that careful analysis of the whole genome data and additional criterion such as lineage-independent mutations may be useful for identification of mutations leading to phenotypic resistance. Furthermore, the creation of reliable database for point mutations is needed to fully automatized AMR prediction.

scholarly journals Absolute copy number fitting from shallow whole genome sequencing data

2021 ◽  
Author(s):  
Carolin M Sauer ◽  
Matthew D Eldridge ◽  
Maria Vias ◽  
James A Hall ◽  
Samantha E Boyle ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Cancer Cell ◽  
Genome Sequencing ◽  
Copy Number ◽  
Point Mutations ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Tissue Samples ◽  
Absolute Copy Number

Low-coverage or shallow whole genome sequencing (sWGS) approaches can efficiently detect somatic copy number aberrations (SCNAs) at low cost. This is clinically important for many cancers, in particular cancers with severe chromosomal instability (CIN) that frequently lack actionable point mutations and are characterised by poor disease outcome. Absolute copy number (ACN), measured in DNA copies per cancer cell, is required for meaningful comparisons between copy number states, but is challenging to estimate and in practice often requires manual curation. Using a total of 60 cancer cell lines, 148 patient-derived xenograft (PDX) and 142 clinical tissue samples, we evaluate the performance of available tools for obtaining ACN from sWGS. We provide a validated and refined tool called Rascal (relative to absolute copy number scaling) that provides improved fitting algorithms and enables interactive visualisation of copy number profiles. These approaches are highly applicable to both pre-clinical and translational research studies on SCNA-driven cancers and provide more robust ACN fits from sWGS data than currently available tools.

scholarly journals SomaticSniper: identification of somatic point mutations in whole genome sequencing data

2011 ◽  
Vol 28 (3) ◽  
pp. 311-317 ◽  
Author(s):  
David E. Larson ◽  
Christopher C. Harris ◽  
Ken Chen ◽  
Daniel C. Koboldt ◽  
Travis E. Abbott ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Point Mutations ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

scholarly journals Prediction of antimicrobial resistance in clinical Campylobacter jejuni isolates from whole-genome sequencing data

2020 ◽  
Author(s):  
Louise Gade Dahl ◽  
Katrine Grimstrup Joensen ◽  
Mark Thomas Østerlund ◽  
Kristoffer Kiil ◽  
Eva Møller Nielsen
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Campylobacter Jejuni ◽  
Genome Sequencing ◽  
Resistance Genes ◽  
Point Mutations ◽  
23S Rrna ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

Abstract Campylobacter jejuni is recognised as the leading cause of bacterial gastroenteritis in industrialised countries. Although the majority of Campylobacter infections are self-limiting, antimicrobial treatment is necessary in severe cases. Therefore, the development of antimicrobial resistance (AMR) in Campylobacter is a growing public health challenge and surveillance of AMR is important for bacterial disease control. The aim of this study was to predict antimicrobial resistance in C. jejuni from whole-genome sequencing data. A total of 516 clinical C. jejuni isolates collected between 2014 and 2017 were subjected to WGS. Resistance phenotypes were determined by standard broth dilution, categorising isolates as either susceptible or resistant based on epidemiological cutoffs for six antimicrobials: ciprofloxacin, nalidixic acid, erythromycin, gentamicin, streptomycin, and tetracycline. Resistance genotypes were identified using an in-house database containing reference genes with known point mutations and the presence of resistance genes was determined using the ResFinder database and four bioinformatical methods (modified KMA, ABRicate, ARIBA, and ResFinder Batch Upload). We identified seven resistance genes including tet(O), tet(O/32/O), ant(6)-Ia, aph(2″)-If, blaOXA, aph(3′)-III, and cat as well as mutations in three genes: gyrA, 23S rRNA, and rpsL. There was a high correlation between phenotypic resistance and the presence of known resistance genes and/or point mutations. A correlation above 98% was seen for all antimicrobials except streptomycin with a correlation of 92%. In conclusion, we found that WGS can predict antimicrobial resistance with a high degree of accuracy and have the potential to be a powerful tool for AMR surveillance.

scholarly journals Contribution of vraSR and graSR Point Mutations to Vancomycin Resistance in Vancomycin-Intermediate Staphylococcus aureus

2009 ◽  
Vol 53 (3) ◽  
pp. 1231-1234 ◽  
Author(s):  
Longzhu Cui ◽  
Hui-min Neoh ◽  
Mitsutaka Shoji ◽  
Keiichi Hiramatsu
Keyword(s):  
Staphylococcus Aureus ◽  
Genetic Analysis ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genome Engineering ◽  
Point Mutations ◽  
Vancomycin Resistance ◽  
Whole Genome ◽  
Stepwise Evolution

ABSTRACT We describe here the genetic analysis of a vancomycin-susceptible Staphylococcus aureus (VSSA) strain, Mu50Ω, a strain related to vancomycin-intermediate S. aureus (VISA) strain Mu50. Using a combination of Mu50Ω whole-genome sequencing and genome engineering, we observed a stepwise evolution of vancomycin resistance from VSSA to VISA after the mutated vraS and graR genes of Mu50 were engineered into Mu50Ω.

scholarly journals Whole-Genome Sequencing of Russian Neisseria Gonorrhoeae Isolates Related to ST 1407 Genogroup

Acta Naturae ◽  
2018 ◽  
Vol 10 (3) ◽  
pp. 68-76
Author(s):  
A. A. Kubanov ◽  
A. V. Runina ◽  
A. V. Chestkov ◽  
A. V. Kudryavtseva ◽  
Yu. A. Pekov ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Efflux Pump ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Single Mutation ◽  
Wild Type ◽  
Sequencing Data ◽  
Nucleotide Substitutions ◽  
Resistance Determinants

The whole-genome sequencing data of three N. gonorrhoeae strains isolated in the Russian Federation in 2015 are presented. According to the NG-MAST protocol, these strains are related to the globally spread ST 1407 genogroup. The analysis of their resistomes showed the absence of ermA/B/C/F genes and the presence of wild-type alleles of rpsE, rrs, rrl, rplD, rplV, macAB, and mefA genes, and these patterns explain the susceptibility of the sequenced strains to aminocyclitols (spectinomycin) and macrolides (azithromycin). Conjugative resistance determinants (blaTEM, tetM) were absent in the genomes, and the penC/ pilQ, parE, and norM alleles were shown to be wild-type, whereas single or multiple nucleotide substitutions were identified in the genes encoding targets for -lactams (ponA, penA), tetracyclines (rpsJ), and fluoroquinolones (gyrA, parC). The additional mutations were found in porB gene and the promoter of mtrR gene, which nonspecifically reduced the susceptibility to antimicrobials due to the membrane permeability decrease and efflux pump overexpression. The diversity of mutations observed in the analyzed genomes prompted a revision of the phylogenetic relationships between the strains by comparing more than 790 groups of housekeeping genes. A high homology between the N. gonorrhoeae ST 1407 and N. gonorrhoeae ST 12556 genomes was confirmed; the latter had probably diverged from a common ancestor as a result of single mutation events. On the other hand, N. gonorrhoeae ST 12450 was an example of phenotypic convergence which appeared in the emergence of new drug resistance determinants that partially coincide with those of the ST 1407 genogroup.

scholarly journals High-precision and cost-efficient sequencing for real-time COVID-19 surveillance

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sung Yong Park ◽  
Gina Faraci ◽  
Pamela M. Ward ◽  
Jane F. Emerson ◽  
Ha Youn Lee
Keyword(s):  
Los Angeles ◽  
Whole Genome Sequencing ◽  
Real Time ◽  
Genome Sequencing ◽  
High Precision ◽  
High Throughput Sequencing ◽  
Whole Genome ◽  
Sequencing Data ◽  
Public Health Response ◽  
Cost Efficient

AbstractCOVID-19 global cases have climbed to more than 33 million, with over a million total deaths, as of September, 2020. Real-time massive SARS-CoV-2 whole genome sequencing is key to tracking chains of transmission and estimating the origin of disease outbreaks. Yet no methods have simultaneously achieved high precision, simple workflow, and low cost. We developed a high-precision, cost-efficient SARS-CoV-2 whole genome sequencing platform for COVID-19 genomic surveillance, CorvGenSurv (Coronavirus Genomic Surveillance). CorvGenSurv directly amplified viral RNA from COVID-19 patients’ Nasopharyngeal/Oropharyngeal (NP/OP) swab specimens and sequenced the SARS-CoV-2 whole genome in three segments by long-read, high-throughput sequencing. Sequencing of the whole genome in three segments significantly reduced sequencing data waste, thereby preventing dropouts in genome coverage. We validated the precision of our pipeline by both control genomic RNA sequencing and Sanger sequencing. We produced near full-length whole genome sequences from individuals who were COVID-19 test positive during April to June 2020 in Los Angeles County, California, USA. These sequences were highly diverse in the G clade with nine novel amino acid mutations including NSP12-M755I and ORF8-V117F. With its readily adaptable design, CorvGenSurv grants wide access to genomic surveillance, permitting immediate public health response to sudden threats.

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