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Molecular investigation of multiple strain infections in patients with tuberculosis in Mubende district, Uganda

Research output: Contribution to journalArticle

  • Adrian Muwonge
  • Clovice Kankya
  • Francisco Olea-Popelka
  • Demelash Biffa
  • Willy Ssengooba
  • Djønne Berit
  • Eystein Skjerve
  • Tone B Johansen

Related Edinburgh Organisations

Original languageEnglish
Pages (from-to)16-22
Number of pages7
JournalInfection, Genetics and Evolution
Volume17
DOIs
Publication statusPublished - Jul 2013

Abstract

Multiple strain tuberculosis (TB) infections are now an acceptable facet of tuberculosis epidemiology. Identification of patients infected with more than one strain gives an insight in disease dynamics at individual and population level. This study therefore aimed at identifying multiple strain infections among TB infected patients. Furthermore, to determine factors associated with multiple strain infections in Mubende district of Uganda. A total of 72 Mycobacterium tuberculosis isolates from patients at Mubende regional referral hospital were characterized using 15 loci MIRU-VNTR, Spoligotyping and deletion analysis. Genotypic and epidemiological data were analyzed using MIRU-VNTR plus, Bionumerics software version 6.1 and an exact logistic regression model respectively. Eight (11.1%) of the 72 patients had mixed TB infections. Five were exclusively pulmonary mixed infections while three had both pulmonary and extra-pulmonary infections (Compartmentalized TB infections). Unlike previous studies that have linked this phenomenon to Beijing strains, multiple strains in this study belonged to T2-Uganda, X2 and T1 lineages. Two of the pulmonary mixed infections were resistant to rifampicin or isoniazid. All except one were HIV positive, newly diagnosed cases and urban residents of Mubende district. The study revealed that one in nine urban dwelling, HIV/TB co-infected patient were infected with more than one M. tuberculosis strains. The molecular findings give indications of a vital component of the disease dynamics that is most likely under looked at clinical level.

ID: 8279128