In Silico Annotation and Immunoinformatics Guided Epitope Mapping of Potential Antigenic Proteins of Trichomonas foetus

Abstract

Bovine trichomonosis is one of the neglected tropical diseases of cattle that is resulting in severe reproductive failure. With present knowledge, disease diagnosis and maintaining the infected animals in the quarantine are the only available strategies. Several spillover incidences of Trichomonas foetus had also resulted in zoonotic transmission to humans. In spite of above circumstances, till date there are no point of care diagnostics developed for screening bovine trichomoniasis in cattle. In the light of above circumstances, there exists a demand for cost-effective diagnostic kits to be provided to farming community. This current study highlights evaluation of few surface proteins of Trichomonas foetus for the suitability as sero-diagnostic markers. Few target Proteins such as Adhesin, Immuno-dominant variable surface antigen-like protein, Polymorphic membrane protein - like protein, GP-63-like (Clan MA, family M8) protein and Hypothetical protein (OHS95735.1) were evaluated for suitable pH, Signal Peptide, protein glycosylation pattern using freely available Bioinformatics tools. Mapping of potential epitopes of all the target proteins was done using immunoinformatics tools. Among the above proteins, GP63-like protein, immuno-dominant variable antigenic domain-like protein, and polymorphic membrane protein-like proteins are most suitable as diagnostic targets, owing to their higher levels of glycosylation, large epitope domains, and showing structural similarities with the domains of known toxic proteins. On the other hand, adhesin protein has the potential to be exploited as a vaccine candidate. The above proteins are suitable to be expressed in suitable host system and validated the immunogenic potential by animal inoculation and by testing with the real samples.

Received: 25 November 2023 | Revised: 28 February 2024 | Accepted: 15 March 2024

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.