Mixed Strain Infections and Microevolution of Mycobacterium tuberculosis: Genetic Diversity in a High-Burden Setting of Northeastern Brazil.

BACKGROUND

Tuberculosis (TB) control in high-burden settings is complicated by the genetic diversity of Mycobacterium tuberculosis (Mtb), which influences transmission. This study assessed the prevalence of mixed strain infections (MSIs) and microevolutionary events, analyzing their association with biosocial and clinical variables in Fortaleza, northeastern Brazil.

METHODS

This prospective study included 168 patients with pulmonary TB from two referral hospitals serving socioeconomically vulnerable populations. Mtb isolates were subjected to drug resistance testing using Xpert MTB/RIF, MGIT 960, SIRE kit, and 24-locus mycobacterial interspersed repetitive unit-variable number tandem repeat typing. Genetic diversity was classified as MSI when multiple alleles were detected at two or more loci, or as a microevolutionary event when multiple alleles were detected at a single locus. Clinical and socioeconomic data were correlated with the genotypic profiles of the patients.

RESULTS

Genetic diversity was observed in 10 isolates (6%), comprising three (1.75%) MSIs and seven microevolutionary events. Among the 10 patients with genetic diversity, the median age was 46 years, and illicit drug use was reported in this subgroup. All MSIs were rifampicin-sensitive; four of the seven cases with microevolution showed rifampicin resistance. Half of the patients with genetic diversity showed poor treatment outcomes in the form of death, failure, and loss of follow-up; comorbid conditions such as diabetes, syphilis, and previous TB were common in this subgroup.

CONCLUSIONS

The patterns of Mtb genetic diversity in this high-burden setting coexist with conditions of social vulnerability and complex disease presentations. These findings highlight the coexistence of Mtb genetic diversity with social and clinical vulnerability in this setting and support further investigation using larger cohorts and higher-resolution genomic approaches.