Decoding mycobacterial ecology in Sub-Saharan African wastewater: metagenomic and metatranscriptomic insights for tuberculosis surveillance

Tuberculosis (TB) remains a major public health challenge in sub-Saharan Africa, driven by high transmission, delayed diagnosis, and limited surveillance. This study presents one of the first integrated applications of shotgun metagenomic and metatranscriptomic sequencing to investigate <i>Mycobacterium</i> communities in wastewater across six TB-endemic countries: Cameroon, Ghana, Kenya, Nigeria, South Africa, and Uganda. Twelve untreated and treated wastewater samples were analysed to characterise taxonomic composition, strain-level diversity, and transcriptional activity. Metagenomic analyses revealed diverse <i>Mycobacterium</i> communities, including <i>M. tuberculosis</i>, <i>M. canettii</i>, <i>M. bovis</i>, and members of the <i>M. avium</i> complex. Metatranscriptomic data detected MTBC-associated transcripts, indicating transcriptional activity and/or persistence of MTBC RNA signals in wastewater, with higher signal predominance in influent samples, consistent with community-level shedding. Metagenome-assembled genomes (MAGs) recovered from South Africa, Cameroon, and Uganda showed >82% completeness and included zoonotic species. MTBC strains clustered into Lineages 1, 2, 4, and 6, with animal-adapted strains linked to livestock and rodents, highlighting One Health relevance. Overall, this dual-omics approach supports wastewater-based epidemiology as a scalable tool for TB surveillance in high-burden settings.