Abstract

Background:
Animal tuberculosis caused by Mycobacterium bovis, a member of MTBC, remains endemic in Argentina and poses a zoonotic risk at the wildlife–livestock interface. Surveillance in multi-host wildlife systems is constrained by heterogeneous sampling conditions and limited access to rapid, cost-effective diagnostic tools.

Aim:
To evaluate the performance of an adapted multiplex PCR for post-culture differentiation of MTBC, Mycobacterium avium complex (MAC), and non-tuberculous mycobacteria (NTM) across diverse wildlife sample matrices in Argentina

Methods:
We tested 100 cultures (70 tissue-derived, mainly from culled invasive species, and 30 derived from minimally invasive samples from alive native species). Singleplex PCR (sPCR) was used as a post-culture molecular benchmark. Diagnostic sensitivity, specificity (95% CI), and agreement (Cohen’s κ) were calculated.

Results:
sPCR confirmed mycobacteria in 62/100 cultures and identified 65 strains: 28 MTBC, 7 MAC, and 30 NTM, three cultures showed MTBC+MAC co-isolation. MTBC was predominantly recovered from tissue (lymph nodes of exotic mammals) (23/28, 82.1%), whereas only four MTBC strains (14.3%) were detected in minimally invasive samples from native mammals. The adapted mPCR showed high specificity (MTBC 100%, Mycobacterium genus and MAC 97.8%). Overall sensitivity was 60.7% for MTBC, 57.1% for MAC, and 56.4% for the Mycobacterium genus, with substantial agreement for MTBC (κ=0.69) and moderate agreement for MAC (κ=0.59) and genus-level (κ=0.52) detection. Performance improved in tissue-derived cultures, with MTBC sensitivity reaching 70.8% (specificity 100%). No cross-reactivity was observed with the non-mycobacterial organisms tested.

Conclusion:
This mPCR provides a practical and cost-effective approach for post-culture classification of mycobacteria in wildlife surveillance, especially when tissue sampling is feasible. We recommend expanding the scale of wildlife studies across diverse sample matrices and ecological settings, and explicitly incorporating wildlife–livestock–human interface scenarios, to characterize the epidemiological role of different wildlife hosts and to support integrated, One Health–oriented health surveillance programmes.

Key words: Animal tuberculosis; Molecular diagnosis; Surveillance; Wildlife; Zoonoses.