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Environmental decontamination and water disinfection practices are hallmarks of disease prevention and control in agricultural and public health settings. Informed fit-to-purpose biocontainment is thus dependent on methodologies accurately assessing microbial burden and viability. Also, rigorous evaluation of the efficacy of biocontrol measures implies monitoring microbial inactivation after decontamination/disinfection procedures. In this study, we used flow cytometry coupled with a resuscitation protocol to monitor the metabolic inactivation of bacteria capable of entering non-cultivable states, after the application of a chlorine-based water disinfectant. For this purpose, we used Mycobacterium bovis BCG as a model of slow-growing bacteria able to enter dormancy and representing a multi-host pathogen in a zoonotic disease system—animal tuberculosis—thriving both across temperate and semi-arid regions and involving environmental contamination. The biocide activity of a commercial sodium dichloroisocyanurate (NaDCC) disinfectant against M. bovis BCG was evaluated through mock environmental matrix tests. Using the manufacturer-recommended dosage of NaDCC, BCG cells were apparently inactivated after 24 h upon exposure. However, we show via flow cytometry that, upon exposure to optimal growth conditions, mycobacterial cells were able to regain metabolic activity shortly after, highlighting a sublethal effect of NaDCC at the recommended commercial dosage due to reversible BCG cell damage. In contrast, increasing twice the disinfectant dosage completely inactivated BCG cells after 24 h of exposure, with full irreversible loss of metabolic activity. Methodological workflows based on conventional culture or PCR would have missed the detection of these dormant subpopulations that were in fact able to resume growth when following the recommendations of a commercial disinfectant. This study highlights the superior, high-resolution value of single-cell approaches, such as flow cytometry, to accurately assess the activity of biocides against metabolically heterogeneous and dormant pathogenic bacteria with environmental cycles, supporting data-driven prioritization of environmental management and disinfection options in contaminated vulnerable settings. [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]

Tuberculosis (TB) is a widespread disease that crosses the human and animal health boundaries, with infection being reported in wildlife, from temperate and subtropical to arctic regions. Often, TB in wild species is closely associated with disease occurrence in livestock but the TB burden in wildlife remains poorly quantified on a global level. Through meta‐regression and systematic review, this study aimed to summarize global information on TB prevalence in commonly infected wildlife species and to draw a global picture of the scientific knowledge accumulated in wildlife TB. For these purposes, a literature search was conducted through the Web of Science and Google Scholar. The 223 articles retrieved, concerning a 39‐year period, were submitted to bibliometric analysis and 54 publications regarding three wildlife hosts fulfilled the criteria for meta‐regression. Using a random‐effects model, the worldwide pooled TB prevalence in wild boar is higher than for any other species and estimated as 21.98%, peaking in Spain (31.68%), Italy (23.84%) and Hungary (18.12%). The pooled prevalence of TB in red deer is estimated at 13.71%, with Austria (31.58%), Portugal (27.75%), New Zealand (19.26%) and Spain (12.08%) positioning on the top, while for European badger it was computed 11.75%, peaking in the UK (16.43%) and Ireland (22.87%). Despite these hard numbers, a declining trend in wildlife TB prevalence is apparent over the last decades. The overall heterogeneity calculated by multivariable regression ranged from 28.61% (wild boar) to 60.92% (red deer), indicating that other unexplored moderators could explain disease burden. The systematic review shows that the most prolific countries contributing to knowledge related with wildlife TB are settled in Europe and Mycobacterium bovis is the most reported pathogen (89.5%). This study provides insight into the global epidemiology of wildlife TB, ascertaining research gaps that need to be explored and informing how should surveillance be refined. [ABSTRACT FROM AUTHOR]