Histopathological patterns of bovine tuberculosis in cattle slaughtered in Southern Brazil: correlation with molecular detection of Mycobacterium spp

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Abstract
Bovine tuberculosis (bTB) is a chronic infectious disease caused by Mycobacterium bovis , which has major veterinary, economic, and zoonotic relevance. This study aimed to characterize the histopathological patterns of bTB lesions and their association with molecular detection in cattle slaughtered in Southern Brazil. Thirty-six tissue samples with lesions suggestive of bTB were collected during municipal inspection in Pelotas, Rio Grande do Sul. Polymerase chain reaction (PCR) targeting the 16 S rRNA gene was used to detect Mycobacterium species. DNA in 35/36 samples (97.2%), whereas Ziehl–Neelsen (ZN) staining revealed acid-fast bacilli in 23/36 cases (61.1%), a statistically significant difference (McNemar’s exact test, p = 0.0018). Grossly, the lesions ranged from caseous nodules to purulent and cavitary forms. Histologically, two main morphological patterns were identified: classical granulomatous lesions with complete fibrous encapsulation (19/36, 52.8%) and disorganized granulomatous inflammation lacking complete encapsulation (17/36, 47.2%). Multinucleated giant cells were present in all ZN-positive cases, whereas neutrophilic infiltration was significantly more frequent in disorganized lesions than in classical granulomas (Fisher’s exact test, p = 0.0002), suggesting active inflammation and impaired granuloma containment. PCR showed higher sensitivity than ZN staining, detecting mycobacterial DNA even in lesions with a low bacillary load. As the assay targeted the 16 S rRNA gene, results were reported as Mycobacterium spp., and species-specific methods would be required for the definitive identification of M. bovis . These findings reinforce the diagnostic value of combining histopathology and molecular methods and emphasize the importance of recognizing atypical lesion patterns for the accurate detection of bovine tuberculosis in slaughterhouse surveillance systems.
Funding Information
  • Universidade Federal de Pelotas

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