Prediction of Bacterial and Archaeal Allergenicity with AllPred Program
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Nowadays, allergic disorders have become one of the most important social problems in the world. This can be related to the advent of new allergenic agents in the environment, as well as an increasing density of human contact with known allergens, including various proteins. Thus, the development of computer programs designed for the prediction of allergenic properties of proteins becomes one of the urgent tasks of modern bioinformatics. Previously we developed a web accessible Allpred Program (http://www-bionet.sscc.ru/ psd/cgi-bin/programs/Allpred/allpred.cgi) that allows users to assess the allergenicity of proteins by taking into account the characteristics of their spatial structure. In this paper, using AllPred, we predicted the allergenicity of proteins from 462 archaea and bacteria species for which a complete genome was available. The segregation of considered proteins on archaea and bacteria has shown that allergens are predicted more often among archaea than among bacteria. The division of these proteins into groups according to their intracellular localization has revealed that the majority of allergenic proteins were among the secreted proteins. The application of methods for predicting the level of gene expression of microorganisms based on DNA sequence analysis showed a statistically significant relationship between the expression level of the proteins and their allergenicity. This analysis has revealed that potentially allergenic proteins were more common among highly expressed proteins. Sorting microorganisms into the pathogenic and nonpathogenic groups has shown that pathogens can potentially be more allergenic because of a statistically significant greater number of allergens predicted among their proteins.
Keywordspathogenic microorganisms allergenicity prediction protein expression
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- 1.Pawankar R., Canonica G.W., Holgate S.T., et al. 2011. WAO White Book on Allergy. Milwaukee, WI: World Allergy Organization.Google Scholar
- 8.Compare D., Nardone G. 2013. The role of gut microbiota in the pathogenesis and management of allergic diseases. Eur. Rev. Med. Pharmacol. 17 (Suppl. 2), 11–17.Google Scholar
- 9.Lynch S.V. 2016. Gut microbiota and allergic disease: New insights. Ann. Am. Thoracic Soc. 13 (Suppl. 1), S51–S54Google Scholar
- 13.Platts-Mills T. A. 2012. Allergy in evolution. In: New Trends in Allergy and Atopic Eczema, vol. 96. Eds. Ring J., Darsow U., Behrendt H. Munich: Karger, pp. 1–6.Google Scholar
- 24.Dimitrov I., Bangov I., Flower D.R., et al. 2014. Aller-TOP v. 2: A server for in silico prediction of allergens. J. Mol. Modeling. 20 (6), 1–6.Google Scholar
- 28.UniProt Consortium. 2014. UniProt: A hub for protein information. Nucleic Acids Res. gku989.Google Scholar
- 36.Bertino J.S., Tirrell P., Greenberg R.N., et al. 1997. A comparative trial of standard or high-dose S subunit recombinant hepatitis B vaccine versus a vaccine containing S subunit, pre-S1, and pre-S2 particles for revaccination of healthy adult nonresponders. J. Infect. Dis. 175 (3), 678–681.CrossRefPubMedGoogle Scholar