Development and Evaluation of a Serological Assay for the Diagnosis of Tuberculosis in Alpacas and Llamas

Abstract

South American camelids are susceptible to tuberculosis, caused mainly by Mycobacterium bovis and M. microti. Despite the tuberculin skin test being the official test for tuberculosis, it has a very low sensitivity in these species (14-20%). Serological tests present the advantages of being rapid, easy to perform and facilitate analysis of large numbers of samples in a short period of time. Novel antigen discovery and evaluation would provide enhanced detection of specific antibodies against members of M. tuberculosis complex. Here, we describe the development and evaluation of an ELISA-type immunoassays to use in the diagnosis of tuberculosis in llamas and alpacas based on P22, a multiprotein complex obtained by affinity chromatography from bovine Purified Protein Derivative (bPPD), that showed high sensitivity and specificity in mice, cattle and goats. This work was performed in two stages. First, a preliminary panel of samples collected from tuberculosis-free (n = 396) and M. bovis-infected herds (n = 56) was assayed, obtaining high specificity (100%) and sensitivity ranging from 63 to 96%. Subsequently, the use of the serological assay was tested using samples from two herds suffering from clinical M. bovis (n = 88) and M. microti (n = 25) infection to evaluate the ability of the ELISA to detect infected animals. 11 out of 88 alpacas were positive to the ELISA in a M. bovis outbreak and 7 out of 25 in a M. microti outbreak. The P22 ELISA potentially provides a sensitive and specific platform for improved tuberculosis surveillance in camelids. ; JI-L was supported by an FPU contract-fellowship (Formación de Profesorado Universitario) from the Ministerio de Educación, Cultura y Deporte of the Spanish Government (FPU2013/6000). AR is the recipient of an Industrial Doctorate contract (DI-15-08110) funded by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO) and the European Social Fund. This work was funded by the University of Surrey Innovation Voucher Scheme 2017-18 ; Sí