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Spreading of Mycobacterium bovis causing animal tuberculosis (TB) at livestock-wildlife-environment interfaces remains a significant problem. Recently, we provided evidence of widespread environmental contamination of an endemic animal TB setting with viable and dormant M. bovis cells able to recover metabolic activity, making indirect transmission via environmental contamination plausible. We now report the first whole genome sequences of M. bovis recovered from the environment. We establish epidemiological links at the environment-animal interface by phylogenomic comparison of these M. bovis genomes with those isolated from livestock and wild ungulates from the same area. Environmental and animal genomes are highly intertwined and distribute similarly into the same M. bovis lineages, supporting several instances of environmental contamination. This study provides compelling evidence of M. bovis excretion into the environment and viability maintenance, supporting the environment as a potential source of new infection. These insights have clear implications for policy formulation, advocating environmental surveillance and an ecosystem perspective in TB control programs. We report the first whole genome sequences of M. bovis from the environment and establish epidemiological links at the environment-animal interface, demonstrating close phylogenomic relatedness of animal and environmental M. bovis. Definitive evidence of M. bovis excretion into the environment with viability maintenance is provided, supporting the environment as a potential source of new infection. Implications of this work include methodological innovations offering a tool to resolve indirect transmission chains and support customized biosecurity measures. Policy formulation aiming at the control of animal tuberculosis and cost mitigation should consider these findings, encouraging environmental surveillance in official eradication programmes. [Display omitted] • M. bovis shed from TB-infected animals may remain viable in the environment. • Whole genome sequencing of environmental M. bovis is reported for the first time. • M. bovis lineages distribute similarly at the animal-environment interface. • Environmental and animal M. bovis genomes are phylogenetically highly intertwined. • The environment is a potential source of new infections in animal TB endemic areas. [ABSTRACT FROM AUTHOR]

Epidemiological surveillance of animal tuberculosis (TB) based on whole genome sequencing (WGS) of Mycobacterium bovis has recently gained track due to its high resolution to identify infection sources, characterize the pathogen population structure, and facilitate contact tracing. However, the workflow from bacterial isolation to sequence data analysis has several technical challenges that may severely impact the power to understand the epidemiological scenario and inform outbreak response. While trying to use archived DNA from cultured samples obtained during routine official surveillance of animal TB in Portugal, we struggled against three major challenges: the low amount of M. bovis DNA obtained from routinely processed animal samples; the lack of purity of M. bovis DNA, i.e., high levels of contamination with DNA from other organisms; and the co-occurrence of more than one M. bovis strain per sample (within-host mixed infection). The loss of isolated genomes generates missed links in transmission chain reconstruction, hampering the biological and epidemiological interpretation of data as a whole. Upon identification of these challenges, we implemented an integrated solution framework based on whole genome amplification and a dedicated computational pipeline to minimize their effects and recover as many genomes as possible. With the approaches described herein, we were able to recover 62 out of 100 samples that would have otherwise been lost. Based on these results, we discuss adjustments that should be made in official and research laboratories to facilitate the sequential implementation of bacteriological culture, PCR, downstream genomics, and computational-based methods. All of this in a time frame supporting data-driven intervention. [ABSTRACT FROM AUTHOR]