Dataset Information

Epidemiological links between tuberculosis cases identified twice as efficiently by whole genome sequencing than conventional molecular typing: A population-based study.

ABSTRACT: Patients with Mycobacterium tuberculosis isolates sharing identical DNA fingerprint patterns can be epidemiologically linked. However, municipal health services in the Netherlands are able to confirm an epidemiological link in only around 23% of the patients with isolates clustered by the conventional variable number of tandem repeat (VNTR) genotyping. This research aims to investigate whether whole genome sequencing (WGS) is a more reliable predictor of epidemiological links between tuberculosis patients than VNTR genotyping.VNTR genotyping and WGS were performed in parallel on all Mycobacterium tuberculosis complex isolates received at the Netherlands National Institute for Public Health and the Environment in 2016. Isolates were clustered by VNTR when they shared identical 24-loci VNTR patterns; isolates were assigned to a WGS cluster when the pair-wise genetic distance was ≤ 12 single nucleotide polymorphisms (SNPs). Cluster investigation was performed by municipal health services on all isolates clustered by VNTR in 2016. The proportion of epidemiological links identified among patients clustered by either method was calculated.In total, 535 isolates were genotyped, of which 25% (134/535) were clustered by VNTR and 14% (76/535) by WGS; the concordance between both typing methods was 86%. The proportion of epidemiological links among WGS clustered cases (57%) was twice as common than among VNTR clustered cases (31%).When WGS was applied, the number of clustered isolates was halved, while all epidemiologically linked cases remained clustered. WGS is therefore a more reliable tool to predict epidemiological links between tuberculosis cases than VNTR genotyping and will allow more efficient transmission tracing, as epidemiological investigations based on false clustering can be avoided.

SUBMITTER: Jajou R

PROVIDER: S-EPMC5884559 | biostudies-other | 2018

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Epidemiological links between tuberculosis cases identified twice as efficiently by whole genome sequencing than conventional molecular typing: A population-based study.

Jajou Rana R de Neeling Albert A van Hunen Rianne R de Vries Gerard G Schimmel Henrieke H Mulder Arnout A Anthony Richard R van der Hoek Wim W van Soolingen Dick D

PloS one 20180404 4

<h4>Background</h4>Patients with Mycobacterium tuberculosis isolates sharing identical DNA fingerprint patterns can be epidemiologically linked. However, municipal health services in the Netherlands are able to confirm an epidemiological link in only around 23% of the patients with isolates clustered by the conventional variable number of tandem repeat (VNTR) genotyping. This research aims to investigate whether whole genome sequencing (WGS) is a more reliable predictor of epidemiological links ...[more]

PMID: 29617456

Similar Datasets

Project description:INTRODUCTION:Recurrent tuberculosis (TB) is one of the main challenges in TB control. Genotyping based on Mycobacterial Interspersed Repetitive Units-Variable Tandem Repeats (MIRU-VNTR) has been widely used to differentiate between relapse and reinfection, which are the two main causes of recurrent TB. There is a lack of data regarding the causes of TB recurrence in Georgia, and while differentiating between relapse and reinfection plays a key role in defining appropriate interventions, the required genotyping methodologies have not been implemented. The objective of this study was to implement MIRU-VNTR genotyping at the National Center for Tuberculosis and Lung Diseases (NCTBLD) and differentiate between relapse and reinfection in multidrug resistant (MDR-) TB patients from Tbilisi, Georgia. METHODS:Recurrent MDR tuberculosis cases from 2014-2016 diagnosed at NCTLD were included in the study when bacterial samples from both episodes were available. Genotyping based on the MIRU-VNTR 24 loci was implemented and used for differentiating between relapse and reinfection. Paired samples showing the same MIRU-VNTR pattern or one locus difference were classified as relapse, while two and more loci differences were treated as reinfection. Exact logistic regression was used to identify predictors of recurrence. RESULTS:Thirty two MDR-TB patients (64 samples) were included and MIRU-VNTR 24 typing was performed on the corresponding paired samples. Of the 32 patients, 25 (83.3%) were identified as relapse while 5 (16.7%) were due to re-infection. Patients with a history of incarceration were significantly associated with TB reinfection (p< 0.05). CONCLUSION:Recurrent TB in MDR patients in Georgia are mainly caused by relapse, raising concerns on the efficacy of the TB control program. An association between incarceration and reinfection likely reflects high levels of ongoing TB transmission in prisons, indicating the need for better TB infection control measures in these settings. Our results add to the rationale for implementing genotypic surveillance of TB more broadly to support TB control in Georgia.

Project description:Bacterial plasmids play a large role in allowing bacteria to adapt to changing environments and can pose a significant risk to human health if they confer virulence and antimicrobial resistance (AMR). Plasmids differ significantly in the taxonomic breadth of host bacteria in which they can successfully replicate, this is commonly referred to as 'host range' and is usually described in qualitative terms of 'narrow' or 'broad'. Understanding the host range potential of plasmids is of great interest due to their ability to disseminate traits such as AMR through bacterial populations and into human pathogens. We developed the MOB-suite to facilitate characterization of plasmids and introduced a whole-sequence-based classification system based on clustering complete plasmid sequences using Mash distances (https://github.com/phac-nml/mob-suite). We updated the MOB-suite database from 12?091 to 23?671 complete sequences, representing 17?779 unique plasmids. With advances in new algorithms for rapidly calculating average nucleotide identity (ANI), we compared clustering characteristics using two different distance measures - Mash and ANI - and three clustering algorithms on the unique set of plasmids. The plasmid nomenclature is designed to group highly similar plasmids together that are unlikely to have multiple representatives within a single cell. Based on our results, we determined that clusters generated using Mash and complete-linkage clustering at a Mash distance of 0.06 resulted in highly homogeneous clusters while maintaining cluster size. The taxonomic distribution of plasmid biomarker sequences for replication and relaxase typing, in combination with MOB-suite whole-sequence-based clusters have been examined in detail for all high-quality publicly available plasmid sequences. We have incorporated prediction of plasmid replication host range into the MOB-suite based on observed distributions of these sequence features in combination with known plasmid hosts from the literature. Host range is reported as the highest taxonomic rank that covers all of the plasmids which share replicon or relaxase biomarkers or belong to the same MOB-suite cluster code. Reporting host range based on these criteria allows for comparisons of host range between studies and provides information for plasmid surveillance.

Project description:We have previously studied carbapenem non-susceptible Pseudomonas aeruginosa (CNPA) strains from intensive care units (ICUs) in a referral hospital in Jakarta, Indonesia (Pelegrin et al., 2019). We documented that CNPA transmissions and acquisitions among patients were variable over time and that these were not significantly reduced by a set of infection control measures. Three high risk international CNPA clones (sequence type (ST)235, ST823, ST357) dominated, and carbapenem resistance was due to carbapenemase-encoding genes and mutations in the porin OprD. Pelegrin et al. (2019) reported core genome analysis of these strains. We present a more refined and detailed whole genome-based analysis of major clones represented in the same dataset. As per our knowledge, this is the first study reporting Single Nucleotide Polymorphisms (wgSNP) analysis of Pseudomonas strains. With whole genome-based Multi Locus Sequence Typing (wgMLST) of the 3 CNPA clones (ST235, ST357 and ST823), three to eleven subgroups with up to 200 allelic variants were observed for each of the CNPA clones. Furthermore, we analyzed these CNPA clone clusters for the presence of wgSNP to redefine CNPA transmission events during hospitalization. A maximum number 35350 SNPs (including non-informative wgSNPs) and 398 SNPs (ST-specific_informative-wgSNPs) were found in ST235, 34,570 SNPs (including non-informative wgSNPs) and 111 SNPs (ST-specific_informative-wgSNPs) in ST357 and 26,443 SNPs (including non-informative SNPs) and 61 SNPs (ST-specific_informative-wgSNPs) in ST823. ST-specific_Informative-wgSNPs were commonly noticed in sensor-response regulator genes. However, the majority of non-informative wgSNPs was found in conserved hypothetical proteins or in uncharacterized proteins. Of note, antibiotic resistance and virulence genes segregated according to the wgSNP analyses. A total of 8 transmission chains for ST235 strains followed by 9 and 4 possible transmission chains for ST357 and ST823 were traceable on the basis of pairwise distances of informative-wgSNPs (0 to 4 SNPs) among the strains. The present study demonstrates the value of detailed whole genome sequence analysis for highly refined epidemiological analysis of P. aeruginosa.

Dataset Information

Epidemiological links between tuberculosis cases identified twice as efficiently by whole genome sequencing than conventional molecular typing: A population-based study.

Publications

Epidemiological links between tuberculosis cases identified twice as efficiently by whole genome sequencing than conventional molecular typing: A population-based study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets