Back-to-Africa introductions of Mycobacterium tuberculosis as the main cause of tuberculosis in Dar es Salaam, Tanzania

Abstract

In settings with high tuberculosis (TB) endemicity, various genotypes of the Mycobacterium tuberculosis complex (MTBC) often differ in prevalence. However, the factors leading to these differences remain poorly understood. Here we studied the MTBC population in Dar es Salaam, Tanzania over a six-year period, using 1,082 unique patient-derived MTBC whole-genome sequences (WGS) and associated clinical data. We show that the TB epidemic in Dar es Salaam is dominated by multiple genotypes introduced to Tanzania from different parts of the world during the last 300 years. The most common MTBC genotypes deriving from these introductions exhibited differences in transmission rates and in the duration of the infectious period, but little differences in overall fitness, as measured by the effective reproductive number. Moreover, measures of disease severity and bacterial load indicated no differences in virulence between these genotypes during active TB. Instead, the combination of an early introduction and a high transmission rate accounted for the high prevalence of L3.1.1, the most dominant MTBC genotype in our setting. Yet, a longer co-existence with the host population did not always result in a higher transmission rate, suggesting that distinct life-history traits have evolved in the different MTBC genotypes. Taken together, our results point to bacterial factors as important determinants of the TB epidemic in Dar es Salaam.

HIV co-infection is associated with reducedMycobacterium tuberculosistransmissibility in sub-Saharan Africa

“…However, HIV was most likely introduced only after the establishment of different Mtb lineages, and the majority of branching events informing the epidemiological parameters occur after the introduction of HIV, suggesting minimal impact on the estimates. In support of this notion, current evidence indicates that the main Mtb lineages circulating in these parts of Africa were introduced several centuries ago [35, 38, 53–56]. Moreover, no biases were observed when randomly re-assigning the HIV status of patients.…”

“…We analyzed complete Mtb genomes collected from TB patients in four sub-Saharan African countries: 1,209 sequences from Karonga District, Malawi (1995-2011) [33], 1,133 sequences from Khayelitsha, Cape Town, South Africa (2008-2018) [34], 1,074 sequences from Temeke District, Dar es Salaam, Tanzania (2013-2019) [35], and 185 sequences from Kampala, Uganda (1995-2012) [36, 37] (see Materials and methods for details on the study populations). The sequences from Uganda have been used partially in other studies [38, 39] but are analyzed here together for the first time.…”

“…This could result from an altered TB disease presentation, as supported by the significantly lower chest X-ray scores of HIV-positive compared to HIV-negative TB patients in Uganda (Welch’s two-sample t -test, p = 0.044). Similarly, the HIV-positive patients from Tanzania showed reduced chest X-ray scores (Welch’s two-sample t -test, p < 0.001), less cavity development ( χ 2 -test, p < 0.001), and lower bacterial loads in the sputum (Welch’s two-sample t -test, p = 0.0027) [35], reflecting a distinct lung pathology, consistent with a reduced infectiousness. Furthermore, clinical data from Malawi and South Africa showed that HIV-positive patients were strongly associated with extrapulmonary TB ( χ 2 -test, p < 0.001 for both datasets), which is non-transmissible.…”

“…Tanzania We used previously sequenced isolates from a cohort of sputum smear-positive and GeneXpert-positive adult TB patients prospectively recruited at the Temeke District hospital in Dar es Salaam, Tanzania between 2013 and 2019 (raw reads available in the European Nucleotide Archive under project accession number PRJEB49562) [35]. Only sequences from patients with known HIV status were retained ( n = 1, 074).…”

“…For all datasets, the Illumina reads were processed and analyzed as described in [34, 35]. Lineages and sublineages were identified using the SNP-based classification by Steiner et al [59].…”