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Updated: Aug 19, 2026

A Tuberculosis Molecular Bacterial Load Assay (TB-MBLA)
Published on: April 30, 2020
Long-term molecular analysis of tuberculosis strains in alabama, a state characterized by a largely indigenous,
Mirjam-Colette Kempf1, Nancy E Dunlap, Kerry H Lok
1Division of Pulmonary and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA. Mkempf@uab.edu
Abstract:
With a tuberculosis case detection rate of 5.9 per 100,000 population in 2001, Alabama ranked twelfth highest in the United States. However, cases among foreign-born and human immunodeficiency virus-infected individuals remain low in Alabama. To understand the endemic statewide disease pattern, tuberculosis strains were studied for clustering in a long-term population-based study from January 1994 to May 2000. IS6110 restriction fragment length polymorphism analysis was performed for 1,834 strains. Spoligotyping was used as a secondary typing method for the 37% of isolates displaying a restriction fragment length polymorphism pattern with <6 IS6110 copies. A total of 721 (41%) patients provided isolates that composed 114 clusters, each containing isolates from 2 to 136 patients, suggesting that recent transmission accounted for 35% of tuberculosis cases. Demographic, behavioral, and clinical characteristics of patients with clustered versus nonclustered isolates stratified by low-copy-number strains (<6 IS6110 copies) versus high-copy-number strains (> or =6 IS6110 copies) were evaluated. Younger age, black race, a history of alcohol abuse, and homelessness were predictors of clustering of low-copy-number, strains and younger age, urban residency, alcohol abuse, homelessness, noninjection drug use, and a history of incarceration and/or cavitary disease were predictors of clustering of high-copy-number strains. By identifying local characteristics of tuberculosis clustering through molecular fingerprinting, control programs can distribute their limited resources to impact the transmission of tuberculosis in high-risk populations and evaluate strain distribution across geographical areas.
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