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Bioinformatics. 2017 Oct 1;33(19):3065-3071. doi: 10.1093/bioinformatics/btx341.

Computational modeling of immune system of the fish for a more effective vaccination in aquaculture.

Author information

Department of Ecological and Biological Sciences, Tuscia University, 01100, Viterbo, Italy.
Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), Section of Animal and Veterinary Sciences, University of Udine, 33100, Italy.
Faculty of Veterinary Medicine, University of Teramo, Italy.
Institute of Applied Computing "M.Picone", CNR, 00185, Rome, Italy.



A computational model equipped with the main immunological features of the sea bass (Dicentrarchus labrax L.) immune system was used to predict more effective vaccination in fish. The performance of the model was evaluated by using the results of two in vivo vaccinations trials against L. anguillarum and P. damselae.


Tests were performed to select the appropriate doses of vaccine and infectious bacteria to set up the model. Simulation outputs were compared with the specific antibody production and the expression of BcR and TcR gene transcripts in spleen. The model has shown a good ability to be used in sea bass and could be implemented for different routes of vaccine administration even with more than two pathogens. The model confirms the suitability of in silico methods to optimize vaccine doses and the immune response to them. This model could be applied to other species to optimize the design of new vaccination treatments of fish in aquaculture.

Availability and implementation:

The method is available at∼filippo/c-immsim/.


Supplementary information:

Supplementary data are available at Bioinformatics online.

[Indexed for MEDLINE]

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