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

ABSTRACT 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 Mycobacterium 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 Mycobacterium communities, including M. tuberculosis, M. canettii, M. bovis, and members of the M. avium 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.