Details

Autor(en) / Beteiligte

• Rani, Swati
• Khatoon, Mehnaj
• Hiremath, Jagadish
• Suresh, Kuralayanapalya Puttahonnappa
• Anandakumar, Jayashree
• Barman, Nagendra Nath
• Manjunath, Sheethal
• S, Yamini Sri
• Patil, Sharanagouda S.

Titel

Decoding bovine coronavirus immune targets: an epitope informatics approach

Ist Teil von

• Animal diseases, 2024-12, Vol.4 (1), p.15-16

Ort / Verlag

Singapore: Springer Nature Singapore

Erscheinungsjahr

2024

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Bovine coronavirus (BCoV) poses a significant threat to the global cattle industry, causing both respiratory and gastrointestinal infections in cattle populations. This necessitates the development of efficacious vaccines. While several inactivated and live BCoV vaccines exist, they are predominantly limited to calves. The immunization of adult cattle is imperative for BCoV infection control, as it curtails viral transmission to calves and ameliorates the impact of enteric and respiratory ailments across all age groups within the herd. This study presents an in silico methodology for devising a multiepitope vaccine targeting BCoV. The spike glycoprotein (S) and nucleocapsid (N) proteins, which are integral elements of the BCoV structure, play pivotal roles in the viral infection cycle and immune response. We constructed a remarkably effective multiepitope vaccine candidate specifically designed to combat the BCoV population. Using immunoinformatics technology, B-cell and T-cell epitopes were predicted and linked together using linkers and adjuvants to efficiently trigger both cellular and humoral immune responses in cattle. The in silico construct was characterized, and assessment of its physicochemical properties revealed the formation of a stable vaccine construct. After 3D modeling of the vaccine construct, molecular docking revealed a stable interaction with the bovine receptor bTLR4. Moreover, the viability of the vaccine’s high expression and simple purification was demonstrated by codon optimization and in silico cloning expression into the pET28a (+) vector. By applying immunoinformatics approaches, researchers aim to better understand the immune response to bovine coronavirus, discover potential targets for intervention, and facilitate the development of diagnostic tools and vaccines to mitigate the impact of this virus on cattle health and the livestock industry. We anticipate that the design will be useful as a preventive treatment for BCoV sickness in cattle, opening the door for further laboratory studies.