Abstract

Epidemiological contact tracing complemented with genotyping of clinical Mycobacterium tuberculosis isolates is important for understanding disease transmission. In Sweden, tuberculosis (TB) is mostly reported in migrant and homeless where epidemiologic contact tracing could pose a problem. This study compared epidemiologic linking with genotyping in a low burden country. Mycobacterium tuberculosis isolates (n = 93) collected at Scania University Hospital in Southern Sweden were analysed with the standard genotyping method mycobacterial interspersed repetitive units-variable number tandem repeats (MIRU-VNTR) and the results were compared with whole genome sequencing (WGS). Using a maximum of twelve single nucleotide polymorphisms (SNPs) as the upper threshold of genomic relatedness noted among hosts, we identified 18 clusters with WGS comprising 52 patients with overall pairwise genetic maximum distances ranging from zero to nine SNPs. MIRU-VNTR and WGS clustered the same isolates, although the distribution differed depending on MIRU-VNTR limitations. Both genotyping techniques identified clusters where epidemiologic linking was insufficient, although WGS had higher correlation with epidemiologic data. To summarize, WGS provided better resolution of transmission than MIRU-VNTR in a setting with low TB incidence. WGS predicted epidemiologic links better which could consolidate and correct the epidemiologically linked cases, avoiding thus false clustering.

Details

Title
Transmission dynamics study of tuberculosis isolates with whole genome sequencing in southern Sweden
Author
Alaridah Nader 1 ; Hallbäck, Erika Tång 2 ; Tångrot Jeanette 3 ; Winqvist Niclas 4 ; Sturegård Erik 5 ; Florén-Johansson Kerstin 2 ; Jönsson Bodil 2   VIAFID ORCID Logo  ; Tenland Erik 1 ; Welinder-Olsson, Christina 2 ; Medstrand Patrik 6 ; Kaijser Bertil 2 ; Godaly Gabriela 1   VIAFID ORCID Logo 

 Lund University, Laboratory medicine, Department of Microbiology, Immunology and Glycobiology, Lund, Sweden (GRID:grid.4514.4) (ISNI:0000 0001 0930 2361) 
 University of Gothenburg, Department of Infectious Diseases, Sahlgrenska Academy, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582) 
 Umeå University, National Bioinformatics Infrastructure Sweden (NBIS), SciLifeLab, Department of Molecular Biology, Computational Life Science Cluster, Umeå, Sweden (GRID:grid.12650.30) (ISNI:0000 0001 1034 3451) 
 Regional Office for Infectious Disease Control and Prevention, Malmö, Sweden (GRID:grid.12650.30); Lund University, Translational Medicine, Clinical Infection medicine, Lund, Sweden (GRID:grid.4514.4) (ISNI:0000 0001 0930 2361) 
 Lund University, Translational Medicine, Clinical Infection medicine, Lund, Sweden (GRID:grid.4514.4) (ISNI:0000 0001 0930 2361) 
 Lund University, Translational medicine, Department of Clinical Virology, Malmö, Sweden (GRID:grid.4514.4) (ISNI:0000 0001 0930 2361) 
Publication year
2019
Publication date
Dec 2019
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2194569451
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.