Mycobacterium bovis in Wildlife: Reservoir Dynamics and Spillover Risk

Introduction

Bovine tuberculosis, caused by Mycobacterium bovis, remains a persistent challenge to livestock health and wildlife conservation globally. Unlike host-restricted members of the Mycobacterium tuberculosis complex, M. bovis exhibits a remarkably broad host range, infecting domestic cattle, farmed cervids, and a wide spectrum of free-ranging wildlife species. The establishment of sustained transmission cycles within wildlife populations complicates eradication efforts in livestock and introduces perpetual spillover risk at the livestock-wildlife interface. This review examines the biophysical and ecological mechanisms governing M. bovis maintenance in wildlife reservoirs, the molecular and immunological factors influencing transmission, and the diagnostic and management strategies required for effective One Health interventions.

Pathogen Biology and Host Adaptation

Mycobacterium bovis is an acid-fast, facultative intracellular bacillus adapted to survive within host macrophages. The pathogen's success across diverse mammalian hosts is mediated by a suite of secreted virulence factors, including the ESAT-6 and CFP-10 proteins, which are encoded within the region of difference 1 (RD1) genomic locus. Strain-dependent differences in ESAT-6 and CFP-10 activity influence inflammasome activation in bovine macrophages, as demonstrated by Blanco et al. [1]. These proteins interact with host innate immune sensors, modulating the NLRP3 inflammasome and altering the balance between pyroptosis and bacterial survival. The specific allelic variants present in circulating wildlife strains can therefore influence within-host replication rates and the probability of onward transmission.

Whole-genome sequencing studies have revealed substantial genetic diversity within M. bovis populations circulating in wildlife. Okunola et al. [2] characterized M. bovis strains from multiple wildlife species in South Africa, demonstrating that transmission networks often involve multiple host species sharing closely related genotypes. The presence of geographically structured clonal complexes suggests that wildlife reservoirs can sustain independent transmission chains even in the absence of livestock spillover.

Wildlife Reservoir Dynamics

The term wildlife reservoir describes a population in which a pathogen is maintained endemically and from which it can be transmitted to target populations of interest. For M. bovis, the most well-characterized wildlife reservoir systems include the European badger (Meles meles) in the United Kingdom and Ireland, the brushtail possum (Trichosurus vulpecula) in New Zealand, and wild boar (Sus scrofa) and white-tailed deer (Odocoileus virginianus) in various regions. However, the list of species capable of maintaining infection continues to expand.

European Badger

The European badger is a primary maintenance host for M. bovis in the British Isles. Infection in badgers is often chronic and subclinical, although severe tuberculosis lesions can occur in the lungs, kidneys, and lymph nodes. Excretion of M. bovis occurs via sputum, urine, feces, and discharging fistulous tracts, creating multiple routes of environmental contamination and interspecies transmission.

Meadows et al. [3] investigated the fecal microbiome of badgers in relation to bovine tuberculosis infection status, social group, and age. They found that infection with M. bovis was associated with alterations in gut microbial community structure, independent of social group effects. Dysbiosis of the respiratory or gastrointestinal microbiome may influence host susceptibility, disease progression, and shedding dynamics. These findings underscore the complexity of host-pathogen interactions in wild populations and suggest that microbiome-based biomarkers could augment diagnostic screening.

Diagnostic detection of M. bovis in badgers is challenging due to the limitations of traditional tuberculin skin testing in non-domestic species. Serological approaches have advanced substantially, with proteome microarray-guided antigen discovery enabling the identification of novel immunodominant peptides. Williams et al. [4] used a proteome microarray to screen badger sera for antibody reactivity against a panel of mycobacterial antigens, followed by peptide mapping to optimize an enzyme-linked immunosorbent assay (ELISA) format. This approach improved diagnostic sensitivity for subclinical infections and is now being integrated into surveillance programmes.

Wild Deer

Cervids represent an important reservoir for M. bovis in many regions, including North America, Europe, and parts of Asia. In southwest England, seroprevalence surveys of wild deer populations have demonstrated that infection persists in areas where badger culling and cattle testing have reduced prevalence. Jinks et al. [5] estimated the seroprevalence of M. bovis infection in a wild deer population, finding evidence of exposure in multiple deer species including fallow deer and roe deer. Deer can excrete M. bovis in nasal secretions and saliva, and congregation at supplemental feeding sites facilitates direct contact and aerosol transmission.

The role of deer as true maintenance hosts versus spillover hosts from badgers or cattle remains debated. Longitudinal serosurveillance combined with molecular typing is essential to quantify the directionality of transmission. The integration of serological and molecular diagnostic data allows for more accurate parameterization of transmission models.

Wild Boar and Feral Swine

Wild boar and feral swine are highly competent reservoirs for M. bovis across Europe, Asia, and the Americas. In the Republic of Korea, Moon et al. [6] conducted a nationwide seroprevalence study of M. bovis and Mycobacterium avium in domestic sows and wild boar under a One Health framework. Seropositivity in wild boar was reported across multiple provinces, confirming that free-ranging suids sustain endemic infection in the absence of domestic livestock contact. The high fecundity, social behavior, and omnivorous foraging habits of wild boar facilitate both direct and indirect transmission. Wild boar commonly frequent cattle pastures and water sources, creating spatiotemporal overlap with livestock.

Other Wildlife Species

The host range of M. bovis extends to many other species, including carnivores (foxes, coyotes, wolves), non-human primates, and even pachyderms. Kader et al. [7] reported molecular detection of the M. tuberculosis complex in a wild Asian elephant (Elephas maximus) from Assam, India, representing one of the few confirmed cases of MTBC infection in a free-ranging elephant. The source of infection was suspected to be contaminated water or shared forage with infected livestock, highlighting the risk of spillover even to species not traditionally considered reservoirs.

Okunola et al. [2] sequenced M. bovis isolates from multiple South African wildlife species, including African buffalo, kudu, and rhinoceros, revealing extensive cross-species transmission. These findings parallel the transmission dynamics seen in European systems and suggest that wildlife reservoirs operate on a continuum from spillover hosts to true maintenance populations depending on ecological and management contexts.

Transmission Mechanisms at the Livestock-Wildlife Interface

Transmission of M. bovis between livestock and wildlife occurs via multiple routes, each with distinct biophysical parameters.

Direct aerosol transmission requires close proximity, typically within a few meters. This route predominates when cattle and wildlife share housing, feeding areas, or watering points. In pasture-based systems, cattle and deer or badgers may graze the same fields, particularly at night when wildlife activity peaks.

Indirect transmission via contaminated environments is particularly important for M. bovis, which can remain viable in soil, water, and manure for extended periods. Badgers latently infected may excrete bacteria in urine at badger latrines, which are often located on pasture. Grazing cattle may ingest contaminated herbage or soil, leading to oral infection. The role of fomites such as shared water troughs and feed bunks is increasingly recognized.

Rodríguez-Martínez et al. [8] described the epidemiological challenges of bovine tuberculosis in Mexico and Latin America, where extensive livestock management and limited biosecurity create opportunities for wildlife contact. In these systems, the movement of infected cattle and the lack of diagnostic testing at slaughter amplify the risk of spillover to wildlife, which then act as secondary reservoirs.

The prevalence of M. bovis infection in cattle directly influences the force of infection to wildlife. Wang et al. [9] performed a systematic review and meta-analysis of bovine tuberculosis prevalence in dairy cattle from 2020 to 2025, identifying a pooled prevalence of subclinical infection that was significantly higher in regions with endemic wildlife reservoirs. This bidirectional enhancement effect creates a self-sustaining cycle: wildlife maintain infection in the absence of cattle, and cattle amplify infection pressure to wildlife.

Diagnostic Challenges in Wild Species

Accurate diagnosis of M. bovis in wildlife is constrained by species-specific immune responses, the absence of validated tests for many species, and the logistical difficulties of sample collection in free-ranging populations.

Ante-mortem diagnostics rely heavily on serological assays, as tuberculin skin testing and interferon-gamma release assays are impractical for most wildlife. Commercial ELISA kits and species-specific indirect ELISAs have been developed for badgers, wild boar, and deer. Williams et al. [4] improved serological detection in badgers using a multi-antigen peptide ELISA, while Moyano et al. [10] evaluated a polyprotein-based ELISA for paratuberculosis detection across multiple species, noting that cross-reactivity with M. bovis is a persistent issue requiring careful antigen selection.

Molecular diagnostics using real-time PCR (qPCR) targeting insertion sequences such as IS6110 and IS1081 offer high sensitivity and specificity for M. bovis detection in tissues, swabs, and environmental samples. Basak et al. [11] used a combination of PCR and ELISA to estimate herd-level prevalence of bovine tuberculosis in raw milk from Bangladesh, demonstrating that molecular detection from milk samples can be applied to wildlife through similar non-invasive approaches using fecal or respiratory samples.

Whole-genome sequencing represents the gold standard for epidemiological tracing. The first report of a complete M. bovis genome from India by Verma et al. [12] provided a reference sequence for genotype comparison in Asian livestock and wildlife. Okunola et al. [2] used whole-genome sequencing to reconstruct transmission networks among South African wildlife, revealing multiple spillover events from a common reservoir population.

Post-mortem diagnosis remains critical for surveillance in wildlife. Detection of gross tuberculosis lesions at necropsy, followed by histopathology and culture or PCR confirmation, provides definitive evidence of infection. However, reliance on post-mortem detection limits the ability to track live, shedding animals and to implement real-time control measures.

One Health Control Strategies

Control of M. bovis at the livestock-wildlife interface requires integrated strategies that address the ecological, immunological, and management factors perpetuating infection.

Vaccination

Bacille Calmette-Guerin (BCG) vaccination has been evaluated as a tool to reduce infection and shedding in wildlife reservoirs. Palphramand et al. [13] studied the immune response to co-administration of BCG and a contraceptive vaccine in badgers, demonstrating that combined vaccination was immunogenic and did not induce adverse effects. Field trials of BCG-baited vaccines for badgers and wild boar are ongoing, with the goal of reducing population-level susceptibility. In cattle, BCG vaccination confers partial protection but is not sufficient to eliminate transmission, and its use in wildlife is seen as a complementary measure rather than a standalone solution.

Test and Cull Strategies

Selective removal of infected wildlife has been implemented in several regions, most prominently in the UK through badger culling. While culling can reduce local prevalence, it may also disrupt social structure, causing increased ranging behavior and greater contact rates between surviving badgers and cattle. This perturbation effect underscores the importance of understanding the behavioral ecology of reservoir hosts. Targeted removal of seropositive animals combined with fertility control may offer a more sustainable approach.

Biosecurity Measures

Reducing contact between cattle and wildlife is the most direct method of spillover prevention. Fencing of feed stores, installation of badger-proof gates, and removal of wildlife attractants from farmyards reduce opportunities for indirect transmission. Avoidance of shared water sources and pasture rotation to minimize grazing on contaminated fields are recommended management practices.

Surveillance and Early Detection

Continuous surveillance at the livestock-wildlife interface is essential for early detection of spillover events. Integration of serological, molecular, and genomic data enables real-time risk assessment. The development of serological assays with high sensitivity across multiple species, as described by Moon et al. [6] and Williams et al. [4], facilitates large-scale screening. Computational modeling using diagnostic data can identify high-risk areas and predict outbreak trajectories. A conceptual workflow integrating these components is presented in the framework below.

graph TD
    A[Wildlife Sampling], > B{Ante-mortem Diagnostics}
    B, > C[Serological ELISA]
    B, > D[Molecular qPCR]
    C, > E[Seropositive Animals]
    D, > F[Molecular Positive]
    E, > G[Post-mortem Confirmation]
    F, > G
    G, > H[Culture and Whole-Genome Sequencing]
    H, > I[Genotype Comparison]
    I, > J[Transmission Network Reconstruction]
    J, > K[Identify Spillover Events]
    K, > L[Risk Mapping]
    L, > M[Targeted Intervention]
    M, > N[Vaccination / Biosecurity / Culling]
    N, > A

Future Directions

Advances in computational biology and diagnostic technology promise to refine our understanding of M. bovis reservoir dynamics. The application of biological foundation models to predict host tropism from genomic sequences may identify wildlife species at elevated risk of maintenance. Machine learning algorithms trained on landscape-level data can predict contact risk between cattle and wildlife. The integration of these tools into veterinary surveillance systems will enhance the precision and timeliness of interventions.

The continued development of species-specific serological tests and portable molecular platforms will enable field-deployable diagnostics, reducing reliance on centralized laboratory infrastructure. The use of environmental DNA (eDNA) sampling to detect M. bovis in water, soil, and air samples offers a complementary surveillance strategy that does not require animal capture or handling.

References

[1] Blanco FC, Vazquez CL, Bigi MM, et al. Mycobacterium bovis strain-dependent effects of ESAT-6 and CFP-10 on inflammasome activation in bovine macrophages. Int J Mol Sci. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42123677/

[2] Okunola A, Loubser J, Ghielmetti G, et al. Whole-genome sequencing reveals genetic diversity and transmission dynamics of Mycobacterium bovis in South African wildlife. Microb Genom. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41665621/

[3] Meadows NML, Delahay RJ, McDonald RA, et al. Fecal microbiome varies with social group, age and bovine tuberculosis infection in the European badger (Meles meles). Mol Ecol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42175702/

[4] Williams GA, Rahou S, Bateman O, et al. Proteome microarray-guided identification of mycobacterial antigens and ELISA-based peptide mapping for improved serological detection of Mycobacterium bovis infection in European badgers. J Clin Microbiol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41589841/

[5] Jinks R, Hollingdale A, Avigad R, et al. Estimating the seroprevalence of Mycobacterium bovis infection in a wild deer population in southwest England. Vet Rec. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41995129/

[6] Moon SJ, Bae DY, Cho YC, et al. Nationwide seroprevalence of Mycobacterium bovis and Mycobacterium avium in domestic sows and wild boars in Korea under a one health framework. Front Microbiol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41834877/

[7] Kader NA, Barman NN, Changmai K, et al. Molecular detection of Mycobacterium tuberculosis complex (MTBC) in a wild Asian elephant (Elephas maximus) from Assam, India. Vet Res Commun. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42183932/

[8] Rodríguez-Martínez LM, Chavelas-Reyes JL, Medina-Ramírez CF, et al. Bovine tuberculosis as a neglected zoonotic disease in Mexico and Latin America: Epidemiological challenges, diagnostic insights, and public health implications in emerging economies. Vet Sci. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41893676/

[9] Wang Q, Wang XN, Liu XQ, et al. Prevalence and risk factors of bovine tuberculosis in dairy cattle, 2020-2025: A systematic review and meta-analysis of available literature. Prev Vet Med. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42176585/

[10] Moyano RD, Colombatti Olivieri MA, Basconez González M, et al. Specificity evaluation of a polyprotein-based ELISA designed for the detection of paratuberculosis in multiple species. Vet Med Int. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41567710/

[11] Basak LR, Islam MT, Mazumder SK, et al. Bovine tuberculosis in raw milk: A herd-level prevalence study by PCR and ELISA testing in Sylhet region of Bangladesh. Vet Med Sci. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41910171/

[12] Verma R, Gandham RK, Mathesh K, et al. First report of whole genome sequence of a Mycobacterium bovis (3/86Rv) strain isolated from a cow in India. Braz J Microbiol. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/41456234/

[13] Palphramand KL, Anderson P, Bellamy F, et al. Immune response to co-administration of Bacillus Calmette-Guerin (BCG) and contraceptive vaccines in badgers (Meles meles). Vaccine. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41371097/

[14] N G K, S J N, T R. Continental prevalence of tuberculosis infection and associated risk factors from African cattle: Systematic review and meta-analysis. Vet Med Sci. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42030422/

[15] Xu Y, Gong Z, Yu J, et al. FcRn alleviates mycobacterium-induced lung injury by triggering YBX1-mediated autophagy. Int Immunopharmacol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41633016/