Periodic Report Summary 1 - REVVAC (Identification of vaccine candidates using reverse vaccinology)
The objectives of this Reverse vaccinology (RevVac) project were: (1) To improve the prediction of vaccine candidates, (2) To understand what makes a bacterial protein a good vaccine candidate, and (3) To create a vaccine resource for bacteriologists. Since the beginning of the project we have identified 64 new bacterial protective antigens (BPAs), implemented 13 new protein annotation tools, constructed new classifiers based on machine learning (support vector machines) to discriminate BPAs from non-antigens, identified different types of vaccine candidate (intra- vs. extracellular), and associated the prominent features used for classification by machine learning methods. The main results achieved so far are a new training data set of 200 BPAs and 200 non-antigens (PAD 200) annotated with 32 protein annotation tools to derive 525 number of features. We have now developed a fully nested cross-validated classifier. Another major finding was a bias in the selection of non-antigens with respect to previously published studies which has now been corrected so that they represent the same bacterial species and subcellular localization as their paired BPA. In addition, we have identified that intra- and extracellular BPAs are fundamentally different based on the annotation derived from protein annotation tools and have developed separate classifiers for these antigen types which are more accurate then when they are combined. Finally, we have initiated a collaboration with Prof. Helen McShane (University of Oxford) and Dr. Ann Rawkins (Public Health England) in order to test the protective efficacy of our BPA predictions against infection with Mycobacterium tuberculosis in a mouse model. The expected final results are trained classifiers capable of identifying intra- or extracellular BPAs that prove protective in animal models of our collaborators whose potential impact will be a new subunit vaccine against tuberculosis. The socio-economic impact of this work is considerable and includes the development of new vaccines which will provide alternatives to antibiotics and thus help to stem the tide of growing antimicrobial resistance. This will have considerable impact on morbidity and mortality in societies throughout the EU and the rest of the globe.
Qiao, Yan (EC Accountant)
Tel.: +44 2380 593907
Tel.: +44 2380 593907
Record Number: 187669 / Last updated on: 2016-08-23