Open AccessAssessing a transmission network of Mycobacterium tuberculosis in an African city using single nucleotide polymorphism threshold analysis
Author(s) -
Yassine Edriss,
Galiwango Ronald,
Ssengooba Willy,
Ashaba Fred,
Joloba Moses L.,
Zalwango Sarah,
Whalen Christopher C.,
Quinn Frederick
Publication year - 2021
Publication title -
microbiologyopen
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.881
H-Index - 36
ISSN - 2045-8827
DOI - 10.1002/mbo3.1211
Subject(s) - tuberculosis , mycobacterium tuberculosis , single nucleotide polymorphism , biology , transmission (telecommunications) , mycobacterium tuberculosis complex , genome , disease , virology , virulence , infectious disease (medical specialty) , genetics , snp , gene , medicine , genotype , pathology , electrical engineering , engineering
Abstract Tuberculosis (TB) is the leading cause of death in humans by a single infectious agent worldwide with approximately two billion humans latently infected with the bacterium Mycobacterium tuberculosis . Currently, the accepted method for controlling the disease is Tuberculosis Directly Observed Treatment Shortcourse (TB‐DOTS). This program is not preventative and individuals may transmit disease before diagnosis, thus better understanding of disease transmission is essential. Using whole‐genome sequencing and single nucleotide polymorphism analysis, we analyzed genomes of 145 M . tuberculosis clinical isolates from active TB cases from the Rubaga Division of Kampala, Uganda. We established that these isolates grouped into M . tuberculosis complex (MTBC) lineages 1, 2, 3, and 4, with the most isolates grouping into lineage 4. Possible transmission pairs containing ≤12 SNPs were identified in lineages 1, 3, and 4 with the prevailing transmission in lineages 3 and 4. Furthermore, investigating DNA codon changes as a result of specific SNPs in prominent virulence genes including plcA and plcB could indicate potentially important modifications in protein function. Incorporating this analysis with corresponding epidemiological data may provide a blueprint for the integration of public health interventions to decrease TB transmission in a region.