Metagenomic Analysis of the Bat Microbiome in Bunduki Ecosystem-Morogoro Tanzania - Gift Mang'ita; Jahashi Saidi Nzalawahe; Abdul Selemani Katakweba; Apia Wibaldo Massawe; Jean Nepomuscene Hakizimana (Journal of Applied Veterinary Science And Technology, 2026)
Background: The emergence of a zoonotic disease pathogen in humans commonly reflects their exposure to mammalian wildlife, such as bats. Bats are significant bacteria reservoir responsible for both pathogens’ transmission and environmental contamination. However, despite their potential, few studies in Tanzania have used metagenomic tools to characterize zoonotic bacterial profiles from animals, thus highlighting a critical gap in regional microbial surveillance efforts. Purpose: This study sought to utilize nanopore sequencing platforms in the detection of microbiome in tissue collected from bats within the Bunduki ecosystem. Method: A cross-sectional study was conducted from January to March 2024. Bats were live-trapped using mist-net from undisturbed forests. DNA was extracted directly from pooled tissue samples using DNeasy Blood and Tissue Kit (cat. No. 69506) and the library for nanopore next-generation sequencing was prepared using the Rapid PCR Barcoding Kit 24 V14 (Oxford Nanopore Technologies), we used ONT Guppy v6.4.2 with the 9.4.1 450 bps SUP model for base calling from the MinION sequencing data and the data were run in CZ ID for a metagenomic overview. Results: A total of 30 live bats were captured, a pooled sample uncovered several microbial taxa; those with opportunistic properties include Leclercia adecarboxylata; of environmental properties include Cupriavidus basilensis, Cupriavidus nantongensis, Cupriavidus oxalaticus, Emticicia oligotrophica; that of plants, Ralstonia pseudosolanacearum; and Bacteriophages, Escherichia phage DW-EC. Such findings increase the value of bat microbiota at the human–animal–environment interface. Conclusion:  These results provide baseline data for microbial surveillance in Tanzania. Although there are pooling limitations, this work highlights the importance of the integration of metagenomics into One Health approaches for early detection and control of zoonotic menace, especially in areas with high interaction between wildlife and humans.