An Integrated in silico and in vivo study of nucleic acid vaccine against Nocardia seriolae infection in orange-spotted grouper Epinephelus coioides.

Nocardiosis in aquatic animals caused by Nocardia seriolae is a frequently occurring serious infection that has recently spread to many countries. In this study, DNA vaccines containing potential bacterial antigens predicted using the reverse vaccinology approach were developed and evaluated in orange-spotted groupers. In silico analysis indicated that proteins including cholesterol oxidase, ld-transpeptidase, and glycosyl hydroxylase have high immunogenicity and are potential vaccine candidates. In vitro assays revealed the mature and biological configurations of these proteins. Importantly, when compared to a control PBS injection, N. seriolae DNA-based vaccines showed significantly higher expression of IL1ß, IL17, and IFNγ at 1 or 2 days, in line with higher serum antibody production and expression of other cellular immune-related genes, such as MHCI, CD4, and CD8, at 7 days post-immunization. Remarkably, enhanced immune responses and strong protective efficacy against a highly virulent strain of N. seriolae were recorded in DNA vaccine-cholesterol oxidase (pcD::Cho) injected fish, with a relative survival rate of 73.3%. Our results demonstrate that the reverse vaccinology approach is a valid strategy for screening vaccine candidates and pcD::Cho is a promising candidate that can boost both innate and adaptive immune responses and confer considerable protection against N. seriolae infection.

Vaccine Design by Reverse Vaccinology and Machine Learning.

Reverse vaccinology (RV) is the state-of-the-art vaccine development strategy that starts with predicting vaccine antigens by bioinformatics analysis of the whole genome of a pathogen of interest. Vaxign is the first web-based RV vaccine prediction method based on calculating and filtering different criteria of proteins. Vaxign-ML is a new Vaxign machine learning (ML) method that predicts vaccine antigens based on extreme gradient boosting with the advance of new technologies and cumulation of protective antigen data. Using a benchmark dataset, Vaxign-ML showed superior performance in comparison to existing open-source RV tools. Vaxign-ML is also implemented within the web-based Vaxign platform to support easy and intuitive access. Vaxign-ML is also available as a command-based software package for more advanced and customizable vaccine antigen prediction. Both Vaxign and Vaxign-ML have been applied to predict SARS-CoV-2 (cause of COVID-19) and Brucella vaccine antigens to demonstrate the integrative approach to analyze and select vaccine candidates using the Vaxign platform.

COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning.

To ultimately combat the emerging COVID-19 pandemic, it is desired to develop an effective and safe vaccine against this highly contagious disease caused by the SARS-CoV-2 coronavirus. Our literature and clinical trial survey showed that the whole virus, as well as the spike (S) protein, nucleocapsid (N) protein, and membrane (M) protein, have been tested for vaccine development against SARS and MERS. However, these vaccine candidates might lack the induction of complete protection and have safety concerns. We then applied the Vaxign and the newly developed machine learning-based Vaxign-ML reverse vaccinology tools to predict COVID-19 vaccine candidates. Our Vaxign analysis found that the SARS-CoV-2 N protein sequence is conserved with SARS-CoV and MERS-CoV but not from the other four human coronaviruses causing mild symptoms. By investigating the entire proteome of SARS-CoV-2, six proteins, including the S protein and five non-structural proteins (nsp3, 3CL-pro, and nsp8-10), were predicted to be adhesins, which are crucial to the viral adhering and host invasion. The S, nsp3, and nsp8 proteins were also predicted by Vaxign-ML to induce high protective antigenicity. Besides the commonly used S protein, the nsp3 protein has not been tested in any coronavirus vaccine studies and was selected for further investigation. The nsp3 was found to be more conserved among SARS-CoV-2, SARS-CoV, and MERS-CoV than among 15 coronaviruses infecting human and other animals. The protein was also predicted to contain promiscuous MHC-I and MHC-II T-cell epitopes, and the predicted linear B-cell epitopes were found to be localized on the surface of the protein. Our predicted vaccine targets have the potential for effective and safe COVID-19 vaccine development. We also propose that an "Sp/Nsp cocktail vaccine" containing a structural protein(s) (Sp) and a non-structural protein(s) (Nsp) would stimulate effective complementary immune responses.