PMID- 30948181
OWN - NLM
STAT- MEDLINE
DCOM- 20200107
LR  - 20200107
IS  - 1873-281X (Electronic)
IS  - 1472-9792 (Linking)
VI  - 115
DP  - 2019 Mar
TI  - Evaluation of a gene-by-gene approach for prospective whole-genome 
      sequencing-based surveillance of multidrug resistant Mycobacterium tuberculosis.
PG  - 81-88
LID - S1472-9792(18)30474-8 [pii]
LID - 10.1016/j.tube.2019.02.006 [doi]
AB  - Whole-genome sequencing (WGS) offers unprecedented resolution for tracking 
      Mycobacterium tuberculosis transmission and antibiotic-resistance spread. Still, 
      the establishment of standardized WGS-based pipelines and the definition of 
      epidemiological clusters based on genetic relatedness are under discussion. We 
      aimed to implement a dynamic gene-by-gene approach, fully relying on freely 
      available software, for prospective WGS-based tuberculosis surveillance, 
      demonstrating its application for detecting transmission chains by 
      retrospectively analysing all M/XDR strains isolated in 2013-2017 in Portugal. We 
      observed a good correlation between genetic relatedness and epidemiological 
      links, with strongly epilinked clusters displaying mean pairwise allele 
      differences (AD) always below 0.3% (ratio of mean AD over the total number of 
      shared loci between same-cluster strains). This data parallels the genetic 
      distances acquired by the core-SNV analysis, while providing higher resolution 
      and epidemiological concordance than MIRU-VNTR genotyping. The dynamic analysis 
      of strain sub-sets (i.e., increasing the number of shared loci within each 
      sub-set) also strengthens the confidence in detecting epilinked clusters. This 
      gene-by-gene strategy also offers several practical benefits (e.g., reliance on 
      freely-available software, scalability and low computational requirements) that 
      further consolidated its suitability for a timely and robust prospective 
      WGS-based laboratory surveillance of M/XDR-TB cases.
CI  - Copyright (c) 2019. Published by Elsevier Ltd.
FAU - Macedo, Rita
AU  - Macedo R
AD  - National Reference Laboratory for Mycobacteria, Department of Infectious 
      Diseases, National Institute of Health, 1649-016 Lisbon, Portugal. Electronic 
      address: rita.macedo@insa.min-saude.pt.
FAU - Pinto, Miguel
AU  - Pinto M
AD  - Bioinformatics Unit, Department of Infectious Diseases, National Institute of 
      Health, 1649-016 Lisbon, Portugal. Electronic address: 
      miguel.pinto@insa.min-saude.pt.
FAU - Borges, Vitor
AU  - Borges V
AD  - Bioinformatics Unit, Department of Infectious Diseases, National Institute of 
      Health, 1649-016 Lisbon, Portugal. Electronic address: 
      vitor.borges@insa.min-saude.pt.
FAU - Nunes, Alexandra
AU  - Nunes A
AD  - Bioinformatics Unit, Department of Infectious Diseases, National Institute of 
      Health, 1649-016 Lisbon, Portugal. Electronic address: 
      alexandra.nunes@insa.min-saude.pt.
FAU - Oliveira, Olena
AU  - Oliveira O
AD  - Life and Health Sciences Research Institute (ICVS), School of Medicine, 
      University of Minho, 4710-057 Braga, Portugal; ICVS/3B, PT Government Associate 
      Laboratory, 4710-057, Braga/4805-017, Guimaraes, Portugal; EPI Unit, Institute of 
      Public Health, University of Porto, 4050-600 Porto, Portugal. Electronic address: 
      radomoliveira@gmail.com.
FAU - Portugal, Isabel
AU  - Portugal I
AD  - iMed.ULisboa-Research Institute for Medicines, University of Lisbon, Lisbon, 
      Portugal. Electronic address: iportugal@ff.ulisboa.pt.
FAU - Duarte, Raquel
AU  - Duarte R
AD  - EPI Unit, Institute of Public Health, University of Porto, 4050-600 Porto, 
      Portugal; Clinical Epidemiology, Predictive Medicine and Public Health 
      Department, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal; 
      Pulmonology Department, Centro Hospitalar de Vila Nova de Gaia/Espinho EPE, 
      4400-129 Vila Nova de Gaia, Portugal. Electronic address: 
      raquelafduarte@gmail.com.
FAU - Gomes, Joao Paulo
AU  - Gomes JP
AD  - Bioinformatics Unit, Department of Infectious Diseases, National Institute of 
      Health, 1649-016 Lisbon, Portugal. Electronic address: 
      j.paulo.gomes@insa.min-saude.pt.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20190225
PL  - Scotland
TA  - Tuberculosis (Edinb)
JT  - Tuberculosis (Edinburgh, Scotland)
JID - 100971555
SB  - IM
MH  - Genes, Bacterial/*genetics
MH  - Genome, Bacterial
MH  - Genotype
MH  - Humans
MH  - Mycobacterium tuberculosis/*genetics
MH  - Phylogeny
MH  - Polymorphism, Single Nucleotide/genetics
MH  - Portugal/epidemiology
MH  - Prospective Studies
MH  - Tuberculosis, Multidrug-Resistant/epidemiology/*genetics
MH  - *Whole Genome Sequencing
OTO - NOTNLM
OT  - Gene-by-gene approach
OT  - Multidrug-resistance
OT  - Mycobacterium tuberculosis
OT  - Surveillance
OT  - Whole-genome sequencing
EDAT- 2019/04/06 06:00
MHDA- 2020/01/08 06:00
CRDT- 2019/04/06 06:00
PHST- 2018/11/08 00:00 [received]
PHST- 2019/01/15 00:00 [revised]
PHST- 2019/02/22 00:00 [accepted]
PHST- 2019/04/06 06:00 [entrez]
PHST- 2019/04/06 06:00 [pubmed]
PHST- 2020/01/08 06:00 [medline]
AID - S1472-9792(18)30474-8 [pii]
AID - 10.1016/j.tube.2019.02.006 [doi]
PST - ppublish
SO  - Tuberculosis (Edinb). 2019 Mar;115:81-88. doi: 10.1016/j.tube.2019.02.006. Epub 
      2019 Feb 25.