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Published on: July 11, 2015
Competitive enzyme-linked immunosorbent assay based on a rhoptry-associated protein 1 epitope specifically identifies
Will L Goff1, Terry F McElwain, Carlos E Suarez
1Animal Disease Research Unit, Agricultural Research Service, U.S. Department of Agriculture, Pullman, Washington 99164-6630, USA. wgoff@vetmed.wsu.edu
Insights
A new competitive enzyme-linked immunosorbent assay (cELISA) effectively detects Babesia bovis infections in cattle. This reliable method shows high specificity and concordance, making it valuable for disease surveillance.
Area of Science:
- Veterinary Immunology
- Parasitology
- Biotechnology
Background:
- Hemoparasite infections, particularly Babesia bovis, pose significant threats to cattle health and productivity.
- Accurate and high-throughput diagnostic methods are crucial for managing and controlling these diseases.
- Existing diagnostic tools may lack specificity or scalability for widespread epidemiological surveillance.
Purpose of the Study:
- To develop and validate a species-specific competitive enzyme-linked immunosorbent assay (cELISA) for detecting Babesia bovis antibodies.
- To utilize a conserved B-cell epitope from the rhoptry-associated protein 1 of Babesia bovis as a target antigen.
- To assess the diagnostic accuracy, specificity, and geographical applicability of the developed cELISA.
Main Methods:
- Cloning and expression of a histidine-tagged thioredoxin fusion peptide containing a conserved B-cell epitope from Babesia bovis rhoptry-associated protein 1.
- Optimization of the cELISA using defined positive and negative bovine sera.
- Testing the cELISA with sera from experimentally and naturally infected cattle, as well as sera from animals infected with other hemoparasites.
- Validation of the assay's performance against indirect immunofluorescence and assessment of epitope conservation across different geographical regions.
Main Results:
- The cELISA demonstrated high specificity (98.7%) in differentiating Babesia bovis-infected animals from uninfected and cross-reacting animals.
- The assay successfully detected Babesia bovis antibodies in sera from various geographical locations, confirming epitope conservation.
- Early detection of experimental infections was achieved between 13 and 17 days post-infection.
- Concordance with indirect immunofluorescence for naturally infected carrier cattle was high (98.3%).
Conclusions:
- The developed cELISA is an accurate, reliable, and standardized method for detecting Babesia bovis infections.
- The assay exhibits broad applicability due to conserved epitope recognition across different regions.
- The cELISA possesses the necessary characteristics to serve as a valuable tool for epidemiological studies and disease surveillance in cattle.
Abstract:
The competitive enzyme-linked immunosorbent assay (cELISA) format has proven to be an accurate, reliable, easily standardized, and high-throughput method for detecting hemoparasite infections. In the present study, a species-specific, broadly conserved, and tandemly repeated B-cell epitope within the C terminus of the rhoptry-associated protein 1 of the hemoparasite Babesia bovis was cloned and expressed as a histidine-tagged thioredoxin fusion peptide and used as antigen in a cELISA. The assay was optimized with defined negative and positive bovine sera, where positive sera inhibited the binding of the epitope-specific monoclonal antibody BABB75A4. The cELISA accurately differentiated animals with B. bovis-specific antibodies from uninfected animals and from animals with antibodies against other tick-borne hemoparasites (98.7% specificity). In addition, B. bovis-specific sera from Australia, Argentina, Bolivia, Puerto Rico, and Morocco inhibited the binding of BABB75A4, confirming conservation of the epitope. The assay first detected experimentally infected animals between 13 and 17 days postinfection, and with sera from naturally infected carrier cattle, was comparable to indirect immunofluorescence (98.3% concordance). The assay appears to have the characteristics necessary for an epidemiologic and disease surveillance tool.
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