Evidence of the efficiency of reverse vaccinology against bovine parasites: A systematic review

Reverse vaccinology is a novel vaccine development technology that uses genome and proteome analyses through bioinformatics to select antigenic epitopes capable of eliciting an immunological and protective response through a quick and cheap methodology. However, data on its use in animal health are scant and further research is advocated. Therefore, this systematic review aimed to evaluate the evidence of the efficiency of reverse vaccinology in the search for antigens against bovine parasites, as well as its perspectives and limitations. One hundred seventy-four studies were found, of which 95 were selected for full reading following the PRISMA guidelines and considering all databases. After the last evaluation and reading of the references, only 19 studies were included and evaluated for methodological quality and biases. The studies applied reverse vaccinology to bacteria, protozoa, and ectoparasites that affect cattle, emphasizing on the tick species Rhipicephalus microplus and the protozoa of the genus Babesia that use it as a vector. Most studies evaluated the acquisition of an immune response through ELISA, WB and IFAT analyses to measure predominantly IgG. In addition, many studies did not examine the complete proteome of the parasites and are carried out only in silico, in vitro, or even with unrelated animals, the reason why they were excluded from our systematic review. Due to lack of studies that met the eligibility criteria, in this systematic review we also included studies carried out with different groups and species of parasites, providing a broad overview of the application of this technique in cattle farming. Conversely, this also resulted in variable methodologies, which makes comparison among studies difficult. Despite that, the application of reverse vaccinology in cattle farming has shown promising results in the development of immunological and protective responses in cattle. However, research methodologies need to be improved to reduce biases and obtain reliable results, in addition to clarity of data and methodologies to enable reproducibility.