scholarly journals Predicting Antimicrobial Resistance and Associated Genomic Features from Whole-Genome Sequencing

2018 ◽  
Vol 57 (2) ◽  
Author(s):  
Jonathan M. Monk
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Error Rate ◽  
Pathogenic Bacteria ◽  
The United States ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Major Error ◽  
Wide Range

ABSTRACT Thanks to the genomics revolution, thousands of strain-specific whole-genome sequences are now accessible for a wide range of pathogenic bacteria. This availability enables big data informatics approaches to be used to study the spread and acquisition of antimicrobial resistance (AMR). In this issue of the Journal of Clinical Microbiology, Nguyen et al. (M. Nguyen, S. W. Long, P. F. McDermott, R. J. Olsen, R. Olson, R. L. Stevens, G. H. Tyson, S. Zhao, and J. J. Davis, J Clin Microbiol 57:e01260-18, 2019, https://doi.org/10.1128/JCM.01260-18) report the results obtained with their machine learning models based on whole-genome sequencing data to predict the MICs of antibiotics for 5,728 nontyphoidal Salmonella genomes collected over 15 years in the United States. Their major finding demonstrates that MICs can be predicted with an average accuracy of 95% within ±1 2-fold dilution step (confidence interval, 95% to 95%), an average very major error rate of 2.7%, and an average major error rate of 0.1%. Importantly, these models predict MICs with no a priori information about the underlying gene content or resistance phenotypes of the strains, enabling the possibility to identify AMR determinants and rapidly diagnose and prioritize antibiotic use directly from the organism sequence. Employing such tools to diagnose and limit the spread of resistance-conferring mechanisms could help ameliorate the looming antibiotic resistance crisis.

scholarly journals Whole-Genome Sequencing for Detecting Antimicrobial Resistance in Nontyphoidal Salmonella

2016 ◽  
Vol 60 (9) ◽  
pp. 5515-5520 ◽  
Author(s):  
Patrick F. McDermott ◽  
Gregory H. Tyson ◽  
Claudine Kabera ◽  
Yuansha Chen ◽  
Cong Li ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Resistance Genes ◽  
The United States ◽  
Whole Genome ◽  
Content Type ◽  
Structural Resistance ◽  
Retail Meat

ABSTRACTLaboratory-basedin vitroantimicrobial susceptibility testing is the foundation for guiding anti-infective therapy and monitoring antimicrobial resistance trends. We used whole-genome sequencing (WGS) technology to identify known antimicrobial resistance determinants among strains of nontyphoidalSalmonellaand correlated these with susceptibility phenotypes to evaluate the utility of WGS for antimicrobial resistance surveillance. Six hundred fortySalmonellaof 43 different serotypes were selected from among retail meat and human clinical isolates that were tested for susceptibility to 14 antimicrobials using broth microdilution. The MIC for each drug was used to categorize isolates as susceptible or resistant based on Clinical and Laboratory Standards Institute clinical breakpoints or National Antimicrobial Resistance Monitoring System (NARMS) consensus interpretive criteria. Each isolate was subjected to whole-genome shotgun sequencing, and resistance genes were identified from assembled sequences. A total of 65 unique resistance genes, plus mutations in two structural resistance loci, were identified. There were more unique resistance genes (n =59) in the 104 human isolates than in the 536 retail meat isolates (n =36). Overall, resistance genotypes and phenotypes correlated in 99.0% of cases. Correlations approached 100% for most classes of antibiotics but were lower for aminoglycosides and beta-lactams. We report the first finding of extended-spectrum β-lactamases (ESBLs) (blaCTX-M1andblaSHV2a) in retail meat isolates ofSalmonellain the United States. Whole-genome sequencing is an effective tool for predicting antibiotic resistance in nontyphoidalSalmonella, although the use of more appropriate surveillance breakpoints and increased knowledge of new resistance alleles will further improve correlations.

scholarly journals eSCAN: Scan Regulatory Regions for Aggregate Association Testing using Whole Genome Sequencing Data

2020 ◽  
Author(s):  
Yingxi Yang ◽  
Yuchen Yang ◽  
Le Huang ◽  
Jai G. Broome ◽  
Adolfo Correa ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
New Technologies ◽  
Real Data ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Association Testing ◽  
Wide Range ◽  
Sequencing Studies

AbstractWith advances in whole genome sequencing (WGS) technology, multiple statistical methods for aggregate association testing have been developed. Many common approaches aggregate variants in a given genomic window of a fixed/varying size and are not reliant on existing knowledge to define appropriate test units, resulting in most identified regions not being clearly linked to genes, limiting biological understanding. Functional information from new technologies (such as Hi-C and its derivatives), which can help link enhancers to the genes they affect, can be leveraged to predefine variant sets for aggregate testing in WGS. Therefore, in this paper we propose the eSCAN (Scan the Enhancers) method for genome-wide assessment of enhancer regions in sequencing studies, combining the advantages of dynamic window selection in SCANG with the advantages of increased incorporation of genomic annotation. eSCAN searches biologically meaningful searching windows, increasing power and aiding biological interpretation, as demonstrated by simulation studies under a wide range of scenarios. We also apply eSCAN for association analysis of blood cell traits using TOPMed WGS data from Women’s Health Initiative (WHI) and Jackson Heart Study (JHS). Results from this real data example show that eSCAN is able to capture more significant signals, and these signals are of shorter length and drive association of larger regions detected by other methods.

scholarly journals Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: An inter-laboratory study

2019 ◽  
Author(s):  
Ronan M. Doyle ◽  
Denise M. O’Sullivan ◽  
Sean D. Aller ◽  
Sebastian Bruchmann ◽  
Taane Clark ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Laboratory Study ◽  
Clinical Microbiology ◽  
Sequence Data ◽  
Clinical Samples ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

AbstractBackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a ‘one-stop’ test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.MethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams (‘participants’) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.ResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.ConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

scholarly journals SeqSero2: Rapid and Improved Salmonella Serotype Determination Using Whole-Genome Sequencing Data

2019 ◽  
Vol 85 (23) ◽  
Author(s):  
Shaokang Zhang ◽  
Hendrik C. den Bakker ◽  
Shaoting Li ◽  
Jessica Chen ◽  
Blake A. Dinsmore ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Large Scale ◽  
Draft Genome ◽  
The United States ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Link Type

ABSTRACT SeqSero, launched in 2015, is a software tool for Salmonella serotype determination from whole-genome sequencing (WGS) data. Despite its routine use in public health and food safety laboratories in the United States and other countries, the original SeqSero pipeline is relatively slow (minutes per genome using sequencing reads), is not optimized for draft genome assemblies, and may assign multiple serotypes for a strain. Here, we present SeqSero2 (github.com/denglab/SeqSero2; denglab.info/SeqSero2), an algorithmic transformation and functional update of the original SeqSero. Major improvements include (i) additional sequence markers for identification of Salmonella species and subspecies and certain serotypes, (ii) a k-mer based algorithm for rapid serotype prediction from raw reads (seconds per genome) and improved serotype prediction from assemblies, and (iii) a targeted assembly approach for specific retrieval of serotype determinants from WGS for serotype prediction, new allele discovery, and prediction troubleshooting. Evaluated using 5,794 genomes representing 364 common U.S. serotypes, including 2,280 human isolates of 117 serotypes from the National Antimicrobial Resistance Monitoring System, SeqSero2 is up to 50 times faster than the original SeqSero while maintaining equivalent accuracy for raw reads and substantially improving accuracy for assemblies. SeqSero2 further suggested that 3% of the tested genomes contained reads from multiple serotypes, indicating a use for contamination detection. In addition to short reads, SeqSero2 demonstrated potential for accurate and rapid serotype prediction directly from long nanopore reads despite base call errors. Testing of 40 nanopore-sequenced genomes of 17 serotypes yielded a single H antigen misidentification. IMPORTANCE Serotyping is the basis of public health surveillance of Salmonella. It remains a first-line subtyping method even as surveillance continues to be transformed by whole-genome sequencing. SeqSero allows the integration of Salmonella serotyping into a whole-genome-sequencing-based laboratory workflow while maintaining continuity with the classic serotyping scheme. SeqSero2, informed by extensive testing and application of SeqSero in the United States and other countries, incorporates important improvements and updates that further strengthen its application in routine and large-scale surveillance of Salmonella by whole-genome sequencing.

scholarly journals Whole-Genome Sequencing Analysis Accurately Predicts Antimicrobial Resistance Phenotypes in Campylobacter spp.

2015 ◽  
Vol 82 (2) ◽  
pp. 459-466 ◽  
Author(s):  
S. Zhao ◽  
G. H. Tyson ◽  
Y. Chen ◽  
C. Li ◽  
S. Mukherjee ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Resistance Genes ◽  
Antimicrobial Agents ◽  
The United States ◽  
23S Rrna ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Content Type

ABSTRACTThe objectives of this study were to identify antimicrobial resistance genotypes forCampylobacterand to evaluate the correlation between resistance phenotypes and genotypes usingin vitroantimicrobial susceptibility testing and whole-genome sequencing (WGS). A total of 114Campylobacterspecies isolates (82C. coliand 32C. jejuni) obtained from 2000 to 2013 from humans, retail meats, and cecal samples from food production animals in the United States as part of the National Antimicrobial Resistance Monitoring System were selected for study. Resistance phenotypes were determined using broth microdilution of nine antimicrobials. Genomic DNA was sequenced using the Illumina MiSeq platform, and resistance genotypes were identified using assembled WGS sequences through blastx analysis. Eighteen resistance genes, includingtet(O),blaOXA-61,catA,lnu(C),aph(2″)-Ib,aph(2″)-Ic,aph(2′)-If,aph(2″)-Ig,aph(2″)-Ih,aac(6′)-Ie-aph(2″)-Ia,aac(6′)-Ie-aph(2″)-If,aac(6′)-Im,aadE,sat4,ant(6′),aad9,aph(3′)-Ic, andaph(3′)-IIIa, and mutations in two housekeeping genes (gyrAand 23S rRNA) were identified. There was a high degree of correlation between phenotypic resistance to a given drug and the presence of one or more corresponding resistance genes. Phenotypic and genotypic correlation was 100% for tetracycline, ciprofloxacin/nalidixic acid, and erythromycin, and correlations ranged from 95.4% to 98.7% for gentamicin, azithromycin, clindamycin, and telithromycin. All isolates were susceptible to florfenicol, and no genes associated with florfenicol resistance were detected. There was a strong correlation (99.2%) between resistance genotypes and phenotypes, suggesting that WGS is a reliable indicator of resistance to the nine antimicrobial agents assayed in this study. WGS has the potential to be a powerful tool for antimicrobial resistance surveillance programs.

scholarly journals The Role of Whole Genome Sequencing in the Surveillance of Antimicrobial Resistant Enterococcus spp.: A Scoping Review

2021 ◽  
Vol 9 ◽  
Author(s):  
Lindsay A. Rogers ◽  
Kayla Strong ◽  
Susan C. Cork ◽  
Tim A. McAllister ◽  
Karen Liljebjelke ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Scoping Review ◽  
Companion Animals ◽  
Surveillance Program ◽  
Whole Genome ◽  
Antimicrobial Resistance Genes ◽  
Wide Range ◽  
Scoping Reviews

Enterococcus spp. have arisen as important nosocomial pathogens and are ubiquitous in the gastrointestinal tracts of animals and the environment. They carry many intrinsic and acquired antimicrobial resistance genes. Because of this, surveillance of Enterococcus spp. has become important with whole genome sequencing emerging as the preferred method for the characterization of enterococci. A scoping review was designed to determine how the use of whole genome sequencing in the surveillance of Enterococcus spp. adds to our knowledge of antimicrobial resistance in Enterococcus spp. Scoping review design was guided by the PRISMA extension and checklist and JBI Reviewer's Guide for scoping reviews. A total of 72 articles were included in the review. Of the 72 articles included, 48.6% did not state an association with a surveillance program and 87.5% of articles identified Enterococcus faecium. The majority of articles included isolates from human clinical or screening samples. Significant findings from the articles included novel sequence types, the increasing prevalence of vancomycin-resistant enterococci in hospitals, and the importance of surveillance or screening for enterococci. The ability of enterococci to adapt and persist within a wide range of environments was also a key finding. These studies emphasize the importance of ongoing surveillance of enterococci from a One Health perspective. More studies are needed to compare the whole genome sequences of human enterococcal isolates to those from food animals, food products, the environment, and companion animals.

scholarly journals Genomic Analysis of a Pan-Resistant Isolate ofKlebsiella pneumoniae, United States 2016

mBio ◽  
2018 ◽  
Vol 9 (2) ◽  
Author(s):  
Tom J. B. de Man ◽  
Joseph D. Lutgring ◽  
David R. Lonsway ◽  
Karen F. Anderson ◽  
Julia A. Kiehlbauch ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Antimicrobial Resistance ◽  
Klebsiella Pneumoniae ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
The United States ◽  
Whole Genome ◽  
Beta Lactams ◽  
Content Type

ABSTRACTAntimicrobial resistance is a threat to public health globally and leads to an estimated 23,000 deaths annually in the United States alone. Here, we report the genomic characterization of an unusualKlebsiella pneumoniae, nonsusceptible to all 26 antibiotics tested, that was isolated from a U.S. patient. The isolate harbored four known beta-lactamase genes, including plasmid-mediatedblaNDM-1andblaCMY-6, as well as chromosomalblaCTX-M-15andblaSHV-28, which accounted for resistance to all beta-lactams tested. In addition, sequence analysis identified mechanisms that could explain all other reported nonsusceptibility results, including nonsusceptibility to colistin, tigecycline, and chloramphenicol. Two plasmids, IncA/C2 and IncFIB, were closely related to mobile elements described previously and isolated from Gram-negative bacteria from China, Nepal, India, the United States, and Kenya, suggesting possible origins of the isolate and plasmids. This is one of the firstK. pneumoniaeisolates in the United States to have been reported to the Centers for Disease Control and Prevention (CDC) as nonsusceptible to all drugs tested, including all beta-lactams, colistin, and tigecycline.IMPORTANCEAntimicrobial resistance is a major public health threat worldwide. Bacteria that are nonsusceptible or resistant to all antimicrobials available are of major concern to patients and the public because of lack of treatment options and potential for spread. AKlebsiella pneumoniaestrain that was nonsusceptible to all tested antibiotics was isolated from a U.S. patient. Mechanisms that could explain all observed phenotypic antimicrobial resistance phenotypes, including resistance to colistin and beta-lactams, were identified through whole-genome sequencing. The large variety of resistance determinants identified demonstrates the usefulness of whole-genome sequencing for detecting these genes in an outbreak response. Sequencing of isolates with rare and unusual phenotypes can provide information on how these extremely resistant isolates develop, including whether resistance is acquired on mobile elements or accumulated through chromosomal mutations. Moreover, this provides further insight into not only detecting these highly resistant organisms but also preventing their spread.

scholarly journals Genome Sequence of the Wolbachia Endosymbiont of Culex quinquefasciatus JHB

2008 ◽  
Vol 191 (5) ◽  
pp. 1725-1725 ◽  
Author(s):  
Steven L. Salzberg ◽  
Daniela Puiu ◽  
Daniel D. Sommer ◽  
Vish Nene ◽  
Norman H. Lee
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genome Sequence ◽  
Culex Quinquefasciatus ◽  
Cytoplasmic Incompatibility ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Wide Range ◽  
Wolbachia Endosymbiont

ABSTRACT Wolbachia species are endosymbionts of a wide range of invertebrates, including mosquitoes, fruit flies, and nematodes. The wPip strains can cause cytoplasmic incompatibility in some strains of the Culex mosquito. Here we describe the genome sequence of a Wolbachia strain that was discovered in the whole-genome sequencing data for the mosquito Culex quinquefasciatus strain JHB.

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