Prospective Whole-Genome Sequencing in Tuberculosis Outbreak Investigation, France, 2017-2018.
Ontology highlight
ABSTRACT:
SUBMITTER: Genestet C
PROVIDER: S-EPMC6390740 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Two Southeast Asian students attending the same school in the United Kingdom presented with pulmonary tuberculosis. An epidemiological investigation failed to link the two cases, and drug resistance profiles of the Mycobacterium tuberculosis isolates were discrepant. Whole-genome sequencing of the isolates found them to be genetically identical, suggesting a missed transmission event.
| S-EPMC3553910 | biostudies-literature
Project description:Clusters of Salmonella Enteritidis cases were identified by the Minnesota Department of Health using both pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) single nucleotide polymorphism analysis from 1 January 2015 through 31 December 2017. The median turnaround time for obtaining WGS results was 11 days longer than for PFGE (12 vs. 1 day). WGS analysis more than doubled the number of clusters compared to PFGE analysis, but reduced the total number of cases included in clusters by 34%. The median cluster size was two cases for WGS compared to four for PFGE, and the median duration of WGS clusters was 27 days shorter than PFGE clusters. While the percentage of PFGE clusters with a confirmed source (46%) was higher than WGS clusters (32%), a higher percentage of cases in clusters that were confirmed as outbreaks reported the vehicle or exposure of interest for WGS (78%) than PFGE (46%). WGS cluster size was a significant predictor of an outbreak source being confirmed. WGS data have enhanced S. Enteritidis cluster investigations in Minnesota by improving the specificity of cluster case definitions and has become an integral part of the S. Enteritidis surveillance process.
| S-EPMC7689598 | biostudies-literature
Project description:Dengue fever is expanding as a global public health threat including countries within Africa. For the past few decades, Cameroon has experienced sporadic cases of arboviral infections including dengue fever. Here, we conducted genomic analyses to investigate the origin and phylogenetic profile of Cameroon DENV-1 outbreak strains and predict the impact of emerging therapeutics on these strains. Bayesian and maximum-likelihood phylogenetic inference approaches were employed in virus evolutionary analyses. An in silico analysis was performed to assess the divergence in immunotherapeutic and vaccine targets in the new genomes. Six complete DENV-1 genomes were generated from 50 samples that met a clinical definition for DENV infection. Phylogenetic analyses revealed that the strains from the current study belong to a sub-lineage of DENV-1 genotype V and form a monophyletic taxon with a 2012 strain from Gabon. The most recent common ancestor (TMRCA) of the Cameroon and Gabon strains was estimated to have existed around 2008. Comparing our sequences to the vaccine strains, 19 and 15 amino acid (aa) substitutions were observed in the immuno-protective prM-E protein segments of the Dengvaxia® and TetraVax-DV-TV003 vaccines, respectively. Epitope mapping revealed mismatches in aa residues at positions E155 and E161 located in the epitope of the human anti-DENV-1 monoclonal antibody HMAb 1F4. The new DENV strains constitute a conserved genomic pool of viruses endemic to the Central African region that needs prospective monitoring to track local viral evolution. Further work is needed to ascertain the performance of emerging therapeutics in DENV strains from the African region.
| S-EPMC10732222 | biostudies-literature
Project description:BACKGROUND: Understanding Mycobacterium tuberculosis (Mtb) transmission is essential to guide efficient tuberculosis control strategies. Traditional strain typing lacks sufficient discriminatory power to resolve large outbreaks. Here, we tested the potential of using next generation genome sequencing for identification of outbreak-related transmission chains. METHODS AND FINDINGS: During long-term (1997 to 2010) prospective population-based molecular epidemiological surveillance comprising a total of 2,301 patients, we identified a large outbreak caused by an Mtb strain of the Haarlem lineage. The main performance outcome measure of whole genome sequencing (WGS) analyses was the degree of correlation of the WGS analyses with contact tracing data and the spatio-temporal distribution of the outbreak cases. WGS analyses of the 86 isolates revealed 85 single nucleotide polymorphisms (SNPs), subdividing the outbreak into seven genome clusters (two to 24 isolates each), plus 36 unique SNP profiles. WGS results showed that the first outbreak isolates detected in 1997 were falsely clustered by classical genotyping. In 1998, one clone (termed "Hamburg clone") started expanding, apparently independently from differences in the social environment of early cases. Genome-based clustering patterns were in better accordance with contact tracing data and the geographical distribution of the cases than clustering patterns based on classical genotyping. A maximum of three SNPs were identified in eight confirmed human-to-human transmission chains, involving 31 patients. We estimated the Mtb genome evolutionary rate at 0.4 mutations per genome per year. This rate suggests that Mtb grows in its natural host with a doubling time of approximately 22 h (400 generations per year). Based on the genome variation discovered, emergence of the Hamburg clone was dated back to a period between 1993 and 1997, hence shortly before the discovery of the outbreak through epidemiological surveillance. CONCLUSIONS: Our findings suggest that WGS is superior to conventional genotyping for Mtb pathogen tracing and investigating micro-epidemics. WGS provides a measure of Mtb genome evolution over time in its natural host context.
| S-EPMC3570532 | biostudies-literature
Project description:Listeria monocytogenes (Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all US Lm isolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Whole-genome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens.
| S-EPMC4946012 | biostudies-other
Project description:Isolates of methicillin-resistant Staphylococcus aureus (MRSA) belonging to a single lineage are often indistinguishable by means of current typing techniques. Whole-genome sequencing may provide improved resolution to define transmission pathways and characterize outbreaks.We investigated a putative MRSA outbreak in a neonatal intensive care unit. By using rapid high-throughput sequencing technology with a clinically relevant turnaround time, we retrospectively sequenced the DNA from seven isolates associated with the outbreak and another seven MRSA isolates associated with carriage of MRSA or bacteremia in the same hospital.We constructed a phylogenetic tree by comparing single-nucleotide polymorphisms (SNPs) in the core genome to a reference genome (an epidemic MRSA clone, EMRSA-15 [sequence type 22]). This revealed a distinct cluster of outbreak isolates and clear separation between these and the nonoutbreak isolates. A previously missed transmission event was detected between two patients with bacteremia who were not part of the outbreak. We created an artificial "resistome" of antibiotic-resistance genes and demonstrated concordance between it and the results of phenotypic susceptibility testing; we also created a "toxome" consisting of toxin genes. One outbreak isolate had a hypermutator phenotype with a higher number of SNPs than the other outbreak isolates, highlighting the difficulty of imposing a simple threshold for the number of SNPs between isolates to decide whether they are part of a recent transmission chain.Whole-genome sequencing can provide clinically relevant data within a time frame that can influence patient care. The need for automated data interpretation and the provision of clinically meaningful reports represent hurdles to clinical implementation. (Funded by the U.K. Clinical Research Collaboration Translational Infection Research Initiative and others.).
| S-EPMC3715836 | biostudies-literature
Project description:Cross-discipline collaboration among state and local health departments improved foodborne illness surveillance for a 2018 Salmonella enterica serovar Enteritidis outbreak in Massachusetts, USA. Prompt linking of epidemiologic and laboratory data and implementation of in-state whole-genome sequencing and analysis improved public health surveillance capacity for outbreak detection and control.
| S-EPMC7323519 | biostudies-literature
Project description:Legionella pneumophila is the main pathogen responsible for outbreaks of Legionnaires' disease, which can be related to contaminated water supplies such as cooling towers or water pipes. We combined conventional molecular methods and whole genome sequence (WGS) analysis to investigate an outbreak of L. pneumophila in a large Australian hospital. Typing of these isolates using sequence-based typing and virulence gene profiling, was unable to discriminate between outbreak and non-outbreak isolates. WGS analysis was performed on isolates during the outbreak, as well as on unlinked isolates from the Public Health Microbiology reference collection. The more powerful resolution provided by analysis of whole genome sequences allowed outbreak isolates to be distinguished from isolates that were temporally and spatially unassociated with the outbreak, demonstrating that this technology can be used in real-time to investigate L. pneumophila outbreaks.
| S-EPMC9151283 | biostudies-literature
Project description:In South Africa, a progressive increase in listeriosis cases was noted from mid-June 2017, heralding what was to become the world's largest listeriosis outbreak. A total of 1060 cases were reported for the period January 1, 2017 to July 17, 2018. We describe laboratory activities, experiences, and results of whole-genome sequencing (WGS) analysis of Listeria monocytogenes isolates associated with this outbreak. Bacteria were identified using the VITEK-2 COMPACT 15 microbial identification system. WGS was performed using Illumina MiSeq technology. WGS data were analyzed using CLC Genomics Workbench Software and free-to-use on-line analysis tools/pipelines. Multilocus sequence typing (MLST) showed that 91% of clinical isolates were sequence type 6 (ST6), determining that the outbreak was largely associated with L. monocytogenes ST6. Epidemiological and laboratory findings led to investigation of a large ready-to-eat processed meat production facility in South Africa, named Enterprise Foods. L. monocytogenes ST6 was found in environmental sampling swabs of the production facility and in ready-to-eat processed meat products (including polony, a product similar to bologna sausage) manufactured at the facility. ST6 isolates, sourced at the Enterprise Foods production facility and from Enterprise food products, were shown by single nucleotide polymorphism (SNP) analysis to be highly related to clinical isolates; these nonclinical ST6 isolates showed <10 SNP differences when compared to clinical ST6 isolates. Core-genome MLST showed that clinical ST6 isolates and Enterprise-related ST6 isolates had no more than 4 allele differences between each other, suggestive of a high probability of epidemiological relatedness. WGS data interpreted together with epidemiological data concluded that the source of the listeriosis outbreak was ready-to-eat processed meat products manufactured by Enterprise Foods. Listeriosis has now been added to the South African list of mandatory notifiable medical conditions. Surveillance systems have been strengthened to facilitate prevention and early detection of listeriosis outbreaks.
| S-EPMC6653791 | biostudies-literature
Project description:Whole genome sequencing (WGS) has become the new gold standard for bacterial outbreak investigation, due to the high resolution available for typing. While sequencing is currently predominantly performed on Illumina devices, the preceding library preparation can be performed using various protocols. Enzymatic fragmentation library preparation protocols are fast, have minimal hands-on time, and work with small quantities of DNA. The aim of our study was to compare three library preparation protocols for molecular typing: Nextera XT (Illumina); Nextera Flex (Illumina); and QIAseq FX (Qiagen). We selected 12 ATCC strains from human Gram-positive and Gram-negative pathogens with %G+C-content ranging from 27% (Fusobacterium nucleatum) to 73% (Micrococcus luteus), each having a high quality complete genome assembly available, to allow in-depth analysis of the resulting Illumina sequence data quality. Additionally, we selected isolates from previously analyzed cases of vancomycin-resistant Enterococcus faecium (VRE) (n = 7) and a local outbreak of Klebsiella aerogenes (n = 5). The number of protocol steps and time required were compared, in order to test the suitability for routine laboratory work. Data analyses were performed with standard tools commonly used in outbreak situations: Ridom SeqSphere+ for cgMLST; CLC genomics workbench for SNP analysis; and open source programs. Nextera Flex and QIAseq FX were found to be less sensitive than Nextera XT to variable %G+C-content, resulting in an almost uniform distribution of read-depth. Therefore, low coverage regions are reduced to a minimum resulting in a more complete representation of the genome. Thus, with these two protocols, more alleles were detected in the cgMLST analysis, producing a higher resolution of closely related isolates. Furthermore, they result in a more complete representation of accessory genes. In particular, the high data quality and relative simplicity of the workflow of Nextera Flex stood out in this comparison. This thorough comparison within an ISO/IEC 17025 accredited environment will be of interest to those aiming to optimize their clinical microbiological genome sequencing.
| S-EPMC6719548 | biostudies-literature