scholarly journals Use of whole-genome sequencing in the epidemiology of Campylobacter jejuni infections: state-of-knowledge

2016 ◽  
Author(s):  
Ann-Katrin Llarena ◽  
Mirko Rossi
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Campylobacter Jejuni ◽  
Genome Sequencing ◽  
Genetic Relationships ◽  
Outbreak Detection ◽  
Epidemiological Methods ◽  
Whole Genome ◽  
Ample Evidence ◽  
Outbreak Investigations

High-throughput whole-genome sequencing (WGS) is a revolutionary tool in public health microbiology and is gradually substituting classical typing methods in surveillance of infectious diseases. In combination with epidemiological methods, WGS is able to identify both sources and transmission-pathways during disease outbreak investigations. This review provides the current state of knowledge on the application of WGS in the epidemiology of Campylobacter jejuni, the leading cause of bacterial gastroenteritis in the European Union. We describe how WGS has improved surveillance and outbreak detection of C. jejuni infections and how WGS has increased our understanding of the evolutionary and epidemiological dynamics of this pathogen. However, the full implementation of this methodology in real-time is still hampered by a few hurdles. The limited insight into the genetic diversity of different lineages of C. jejuni impedes the validity of assumed genetic relationships. Furthermore, efforts are needed to reach a consensus on which analytic pipeline to use and how to define the strains cut-off value for epidemiological association while taking the needs and realities of public health microbiology in consideration. Even so, we claim that ample evidence is available to support the benefit of integrating WGS in the monitoring of C. jejuni infections and outbreak investigations.

scholarly journals Whole-Genome Sequencing in Epidemiology of Campylobacter jejuni Infections

2017 ◽  
Vol 55 (5) ◽  
pp. 1269-1275 ◽  
Author(s):  
Ann-Katrin Llarena ◽  
Eduardo Taboada ◽  
Mirko Rossi
Keyword(s):  
Whole Genome Sequencing ◽  
Campylobacter Jejuni ◽  
Genome Sequencing ◽  
Outbreak Detection ◽  
Whole Genome ◽  
Ample Evidence ◽  
Content Type ◽  
Routine Monitoring ◽  
Outbreak Investigations ◽  
Bacterial Gastroenteritis

ABSTRACT This review describes the current state of knowledge regarding the application of whole-genome sequencing (WGS) in the epidemiology of Campylobacter jejuni , the leading cause of bacterial gastroenteritis worldwide. We describe how WGS has increased our understanding of the evolutionary and epidemiological dynamics of this pathogen and how WGS has the potential to improve surveillance and outbreak detection. We have identified hurdles to the full implementation of WGS in public health settings. Despite these challenges, we think that ample evidence is available to support the benefits of integrating WGS into the routine monitoring of C. jejuni infections and outbreak investigations.

scholarly journals Investigation of Two Mycobacterium abscessus Outbreaks in Quebec Using Whole Genome Sequencing

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Michelle Wuzinski ◽  
Hafid Soualhine ◽  
Emilie Valliere ◽  
Pierre-Marie Akochy ◽  
Nancy Cloutier ◽  
...  
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Mycobacterium Abscessus ◽  
Health Concern ◽  
Whole Genome ◽  
Pediatric Clinic ◽  
Antimicrobial Resistance Genes ◽  
Outbreak Investigations ◽  
Distinct Sequence

In recent decades, nontuberculous mycobacteria (NTM) infections are of emerging public health concern and have contributed towards significant clinical and economic burden globally. One such rapid growing mycobacteria, Mycobacterium abscessus, can cause clonal outbreaks, and these bacteria exhibit a highly resistant antimicrobial susceptibility profile. Here, we present an investigation of two small outbreaks of M. abscessus: first in a pediatric clinic setting and second in a tattoo parlour from Quebec. Two whole genome sequencing approaches were utilized for genotyping: MAB-MLST, a multilocus sequencing typing scheme containing housekeeping, identification, and antimicrobial resistance genes, and SNVPhyl that uses phylogenetics to determine single nucleotide variations between strains. MAB-MLST results showed that the pediatric outbreak strains had two distinct sequence types, demonstrating that one strain did not belong to the outbreak, while all tattoo outbreak isolates belonged to the same sequence type. SNVPhyl results were similar to MAB-MLST results and showed that the pediatric outbreak strains tightly clustered together with 0-1 SNVs between isolates, a sharp contrast between unrelated strains used as controls. Similar results were seen for tattoo outbreak cases with 3-11 SNVs between isolates. NTM infections can be difficult to identify, and outbreak investigations can be complicated. Thus, WGS tools can be used in public health outbreak investigations as they provide high discriminatory power.

scholarly journals Outbreak of Pseudomonas aeruginosa Infections from a Contaminated Gastroscope Detected by Whole Genome Sequencing Surveillance

2020 ◽  
Author(s):  
Alexander J Sundermann ◽  
Jieshi Chen ◽  
James K Miller ◽  
Melissa I Saul ◽  
Kathleen A Shutt ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Blood Stream ◽  
Outbreak Detection ◽  
Whole Genome ◽  
Transmission Route ◽  
Serious Infections ◽  
Outbreak Investigations ◽  
Manual Review

Abstract Background Traditional methods of outbreak investigations utilize reactive whole genome sequencing (WGS) to confirm or refute the outbreak. We have implemented WGS surveillance and a machine learning (ML) algorithm for the electronic health record (EHR) to retrospectively detect previously unidentified outbreaks and determine the responsible transmission routes. Methods We performed WGS surveillance to identify and characterize clusters of genetically-related Pseudomonas aeruginosa infections during a 24 month period. ML of the EHR was used to identify potential transmission routes. A manual review of the EHR was performed by an infection preventionist to determine the most likely route and results were compared to the ML algorithm. Results We identified a cluster of six genetically related P. aeruginosa cases that occurred during a seven-month period. The ML algorithm identified gastroscopy as a potential transmission route for four of the six patients. Manual EHR review confirmed gastroscopy as the most likely route for five patients. This transmission route was confirmed by identification of a genetically-related P. aeruginosa incidentally cultured from a gastroscope used on four of the five patients. Three infections, two of which were blood stream infections, could have been prevented if the ML algorithm had been running in real-time. Conclusions WGS surveillance combined with a ML algorithm of the EHR identified a previously-undetected outbreak of gastroscope-associated P. aeruginosa infections. These results underscore the value of WGS surveillance and ML of the EHR for enhancing outbreak detection in hospitals and preventing serious infections.

Evaluation of Whole Genome Sequencing for outbreak detection of Salmonella enterica serovar Enteritidis

2020 ◽  
Author(s):  
Ainhoa Arrieta-Gisasola ◽  
Aitor Atxaerandio Landa ◽  
Javier Garaizar ◽  
Joseba Bikandi ◽  
José Karkamo ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Salmonella Enterica ◽  
Outbreak Detection ◽  
Whole Genome ◽  
Salmonella Enterica Serovar Enteritidis

scholarly journals Expanding U.S. Laboratory Capacity for Neisseria gonorrhoeae Antimicrobial Susceptibility Testing and Whole-Genome Sequencing through the CDC's Antibiotic Resistance Laboratory Network

2020 ◽  
Vol 58 (4) ◽  
Author(s):  
Ellen N. Kersh ◽  
Cau D. Pham ◽  
John R. Papp ◽  
Robert Myers ◽  
Richard Steece ◽  
...  
Keyword(s):  
Public Health ◽  
Antibiotic Resistance ◽  
Neisseria Gonorrhoeae ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Antimicrobial Susceptibility ◽  
Susceptibility Testing ◽  
Whole Genome ◽  
Content Type ◽  
Laboratory Capacity

ABSTRACT U.S. gonorrhea rates are rising, and antibiotic-resistant Neisseria gonorrhoeae (AR-Ng) is an urgent public health threat. Since implementation of nucleic acid amplification tests for N. gonorrhoeae identification, the capacity for culturing N. gonorrhoeae in the United States has declined, along with the ability to perform culture-based antimicrobial susceptibility testing (AST). Yet AST is critical for detecting and monitoring AR-Ng. In 2016, the CDC established the Antibiotic Resistance Laboratory Network (AR Lab Network) to shore up the national capacity for detecting several resistance threats including N. gonorrhoeae. AR-Ng testing, a subactivity of the CDC’s AR Lab Network, is performed in a tiered network of approximately 35 local laboratories, four regional laboratories (state public health laboratories in Maryland, Tennessee, Texas, and Washington), and the CDC’s national reference laboratory. Local laboratories receive specimens from approximately 60 clinics associated with the Gonococcal Isolate Surveillance Project (GISP), enhanced GISP (eGISP), and the program Strengthening the U.S. Response to Resistant Gonorrhea (SURRG). They isolate and ship up to 20,000 isolates to regional laboratories for culture-based agar dilution AST with seven antibiotics and for whole-genome sequencing of up to 5,000 isolates. The CDC further examines concerning isolates and monitors genetic AR markers. During 2017 and 2018, the network tested 8,214 and 8,628 N. gonorrhoeae isolates, respectively, and the CDC received 531 and 646 concerning isolates and 605 and 3,159 sequences, respectively. In summary, the AR Lab Network supported the laboratory capacity for N. gonorrhoeae AST and associated genetic marker detection, expanding preexisting notification and analysis systems for resistance detection. Continued, robust AST and genomic capacity can help inform national public health monitoring and intervention.

scholarly journals A common protocol for the simultaneous processing of multiple clinically relevant bacterial species for whole genome sequencing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kathy E. Raven ◽  
Sophia T. Girgis ◽  
Asha Akram ◽  
Beth Blane ◽  
Danielle Leek ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Dna Extraction ◽  
Genome Sequencing ◽  
Clinical Microbiology ◽  
Bacterial Species ◽  
Outbreak Detection ◽  
Whole Genome ◽  
Library Preparation ◽  
Simultaneous Processing ◽  
Antimicrobial Resistance Gene

AbstractWhole-genome sequencing is likely to become increasingly used by local clinical microbiology laboratories, where sequencing volume is low compared with national reference laboratories. Here, we describe a universal protocol for simultaneous DNA extraction and sequencing of numerous different bacterial species, allowing mixed species sequence runs to meet variable laboratory demand. We assembled test panels representing 20 clinically relevant bacterial species. The DNA extraction process used the QIAamp mini DNA kit, to which different combinations of reagents were added. Thereafter, a common protocol was used for library preparation and sequencing. The addition of lysostaphin, lysozyme or buffer ATL (a tissue lysis buffer) alone did not produce sufficient DNA for library preparation across the species tested. By contrast, lysozyme plus lysostaphin produced sufficient DNA across all 20 species. DNA from 15 of 20 species could be extracted from a 24-h culture plate, while the remainder required 48–72 h. The process demonstrated 100% reproducibility. Sequencing of the resulting DNA was used to recapitulate previous findings for species, outbreak detection, antimicrobial resistance gene detection and capsular type. This single protocol for simultaneous processing and sequencing of multiple bacterial species supports low volume and rapid turnaround time by local clinical microbiology laboratories.

scholarly journals Whole-Genome Sequencing for Bacterial Strain Typing Using the iSeq100 Platform

2020 ◽  
Vol 41 (S1) ◽  
pp. s434-s434
Author(s):  
Grant Vestal ◽  
Steven Bruzek ◽  
Amanda Lasher ◽  
Amorce Lima ◽  
Suzane Silbert
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Outbreak Detection ◽  
Epidemiological Surveillance ◽  
Whole Genome ◽  
Nucleotide Polymorphisms ◽  
Dna Libraries ◽  
Patient Health ◽  
Hospital Acquired ◽  
Reference Genomes

Background: Hospital-acquired infections pose a significant threat to patient health. Laboratories are starting to consider whole-genome sequencing (WGS) as a molecular method for outbreak detection and epidemiological surveillance. The objective of this study was to assess the use of the iSeq100 platform (Illumina, San Diego, CA) for accurate sequencing and WGS-based outbreak detection using the bioMérieux EPISEQ CS, a novel cloud-based software for sequence assembly and data analysis. Methods: In total, 25 isolates, including 19 MRSA isolates and 6 ATCC strains were evaluated in this study: A. baumannii ATCC 19606, B. cepacia ATCC 25416, E. faecalis ATCC 29212, E. coli ATCC 25922, P. aeruginosa ATCC 27853 and S. aureus ATCC 25923. DNA extraction of all isolates was performed on the QIAcube (Qiagen, Hilden, Germany) using the DNEasy Ultra Clean Microbial kit extraction protocol. DNA libraries were prepared for WGS using the Nextera DNA Flex Library Prep Kit (Illumina) and sequenced at 2×150-bp on the iSeq100 according to the manufacturer’s instructions. The 19 MRSA isolates were previously characterized by the DiversiLab system (bioMérieux, France). Upon validation of the iSeq100 platform, a new outbreak analysis was performed using WGS analysis using EPISEQ CS. ATCC sequences were compared to assembled reference genomes from the NCBI GenBank to assess the accuracy of the iSeq100 platform. The FASTQ files were aligned via BowTie2 version 2.2.6 software, using default parameters, and FreeBayes version 1.1.0.46-0 was used to call homozygous single-nucleotide polymorphisms (SNPs) with a minimum coverage of 5 and an allele frequency of 0.87 using default parameters. ATCC sequences were analyzed using ResFinder version 3.2 and were compared in silico to the reference genome. Results: EPISEQ CS classified 8 MRSA isolates as unrelated and grouped 11 isolates into 2 separate clusters: cluster A (5 isolates) and cluster B (6 isolates) with similarity scores of ≥99.63% and ≥99.50%, respectively. This finding contrasted with the previous characterization by DiversiLab, which identified 3 clusters of 2, 8, and 11 isolates, respectively. The EPISEQ CS resistome data detected the mecA gene in 18 of 19 MRSA isolates. Comparative analysis of the ATCCsequences to the reference genomes showed 99.9986% concordance of SNPs and 100.00% concordance between the resistance genes present. Conclusions: The iSeq100 platform accurately sequenced the bacterial isolates and could be an affordable alternative in conjunction with EPISEQ CS for epidemiological surveillance analysis and infection prevention.Funding: NoneDisclosures: None

Sign in / Sign up

Export Citation Format

Share Document