• Logo
  • SBMUJournals

Immunoinformatics and Similarity Analysis of House Dust Mite Tropomyosin

Mohammad Mehdi Ranjbar, Sedigheh Nabian, Nayeb Ali Ahmadi, Khodayar Ghorban, Alireza Sazmand, Maryam Dadmanesh, Seyed Hossein Hekmatimoghaddam
1026

Views

PDF

Abstract

Background: Dermatophagoides farinae and Dermatophagoides pteronyssinus are house dust mites (HDM) that they cause severe asthma and allergic symptoms. Tropomyosin protein plays an important role in mentioned immune and allergic reactions to HDMs. Here, tropomyosin protein from Dermatophagoides spp. was comprehensively screened in silico for its allergenicity, antigenicity and similarity/conservation.

Materials and Methods: The amino acid sequences of D. farinae tropomyosin, D. pteronyssinus and other mites were retrieved. We included alignments and evaluated conserved/ variable regions along sequences, constructed their phylogenetic tree and estimated overall mean distances. Then, followed by with prediction of linear B-cell epitope based on different approaches, and besides in-silico evaluation of IgE epitopes allergenicity (by SVMc, IgE epitope, ARPs BLAST, MAST and hybrid method). Finally, comparative analysis of results by different approaches was made.

Results: Alignment results revealed near complete identity between D. farina and D. pteronyssinus members, and also there was close similarity among Dermatophagoides spp. Most of the variations among mites' tropomyosin were approximately located at amino acids 23 to 80, 108 to 120, 142 to 153 and 220 to 230. Topology of tree showed close relationships among mites in tropomyosin protein sequence, although their sequences in D. farina, D. pteronyssinus and Psoroptes ovis are more similar to each other and clustered. Dermanyssus gallinae (AC: Q2WBI0) has less relationship to other mites, being located in a separate branch. Hydrophilicity and flexibility plots revealed that many parts of this protein have potential to be hydrophilic and flexible. Surface accessibility represented 7 different epitopes. Beta-turns in this protein are with high probability in the middle part and its two terminals. Kolaskar and Tongaonkar method analysis represented 11 immunogenic epitopes between amino acids 7-16. From comparative analysis of predicted probable consensus epitope regions by machine learning approaches these epitopes were gained: AA23-48, AA59-80, AA91-110, AA114-143, AA154-168, AA182-200, AA208-225, and AA254-272. Prediction of allergenic proteins by AlgPred server showed 10 matches for IgE epitope, and prediction by hybrid approach showed that IgE epitope is undoubtedly the major allergen.

Conclusion: Immunoinformatic approaches in allergenic protein analysis are now reliable tools for explanation/interpretation of clinically observed complexities. Results of present study, would help in HDM immunotherapy against several species of parasites as a wide range epitopic desensitization or prevention (vaccine) regime.


Keywords

House dust mite, Tropomyosin, Allergenicity, Antigenicity, Similarity

References

Flaum M, Lung CL, Tinkelman D. Take control of high-cost asthma. J Asthma. 1997;34(1):5-14.

Platts-Mills TA, Vervloet D, Thomas WR, Aalberse RC& Chapman MD. Indoor allergens and asthma: report of the Third International Workshop. J Allergy ClinImmunol. 1997;100(6 Pt 1):S2–24.

Downs SH, Marks GB, Sporik R, Belosouva EG, Car NG, Peat JK. Continued increase in the prevalence of asthma and atopy. Arch Dis Child. 2001;84(1):20-3.

Weghofer M, Thomas WR, Pittner G, Horak F, Valenta R,Vrtala S. Comparison of purified Dermatophagoides pteronyssinus allergens and extract by two-dimensional immunoblotting and quantitative immunoglobulin E inhibitions. Clin Exp Allergy. 2005;35(10): 1384-91.

Batard T, Hrabina A, Bi XZ, et al. Production and proteomic characterization of pharmaceutical-grade Dermatophagoides pteronyssinus and Dermatophagoides farinae extracts for allergy vaccines.Int Arch Allergy Immunol. 2006;140(4):295-305.

Weghofer M, Thomas WR, Kronqvist M, et al. Variability of IgE reactivity profiles among European mite allergic patients. Eur J Clin Invest. 2008;38(12):959-65.

Yi FC, Cheong N, Shek PC, Wang DY, Chua KY, Lee BW. Identification of shared and unique immunoglobulin E epitopes of the highly conserved tropomyosins in Blomiatropicalis and Dermatophagoide spteronyssinus. Clin Exp Allergy. 2002;32(8):1203-10.

Nisbet AJ, Huntley JF. Progress and opportunities in the development of vaccines against mites, fleas and myiasis-causing flies of veterinary importance. Parasit Immunol. 2006;28(4):165-72.

Kavitha KV, Saritha R, Vinod Chandra SS. Computational methods in linear B-cell epitope prediction. Int J Comp App. 2013;63(12):28-32.

Aki T, Kodama T, Fujikawa A, et al. Immunochemical characterization of recombinant and native tropomyosins as a new allergen from the house dust mite, Dermatophagoides farina. J Allergy ClinImmunol. 1995;96 (1):74–83.

Jenkins RE, Taylor MJ, Gilvary NJ, Bianco AE. Tropomyosin implicated in host protective responses to microfilariae in onchocerciasis. Proc Natl Acad Sci USA. 1998;95(13):7550–5.

Greenbaum JA, Andersen PH, Blythe M. Towards a consensus on datasets and evaluation metric for developing B-cell epitope prediction tools. J Mol Recognit. 2007;20(2):75–82.

Yang X& Yu X. An introduction to epitope prediction methods and software. Rev Med Virol 2009; 19(2):77–96. [Reviews in Medical Virology]

Thompson JD, Higgins DG & Gilbson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nuleic Acids Res1994; 22(22): 4673–4680.

Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011;28(10):2731-9.

Kimura M. A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. J Mol Evol. 1980;16(2):111–20.

Felsenstein J. Confidence limits on phylogeneies: an approach using the bootstrap. Evolution. 198539(4):783-91.

Zuckerkandl E, Pauling L. Evolutionary divergence and convergence in proteins. In: Bryson V, Vogel HJ. Evolving Genes and Proteins. New York: Academic Press. 1965;97-166.

Parker JM, Guo D, Hodges RS. New hydrophilicity scale derived from high-performance liquid chromatography peptide retention data: correlation of predicted surface residues with antigenicity and X-ray-derived accessible sites. Biochemistry. 1986;25(19):5425–32.

Emini EA, Hughes JV, Perlow DS, Boger J. Induction of hepatitis A virus neutralizing antibody by a virus-specific synthetic peptide. J Virol. 1985;53(3):836-9.

Karplus PA, Schulz GE. Prediction of chain flexibility in proteins: a tool for the selection of peptide antigen. Naturwissenschaften.1985;72(4): 212-3.

Chou PY, Fasman GD. Prediction of beta-turns. Biophys J. 1979;26(3):367-84.

Kolaskar AS, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett. 1990;276(1-2):172-4.

Larson JEP, Lund O, Neilsen M. Improved method for predicting linear B-cell epitopes. Immunome Res. 2006;2:2.

Saha S, Raghava GP. Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins. 2006;65(1):40-48.

EL-Manzalawy Y, Dobbs D, Honavar V. Predicting linear B-cell epitopes using string kernels. J. Mol. Recognit. 2008;21(4):243-55.

Platts-Mills TAE, De Weck AL. Dust mite allergens and asthma – a worldwide problem. J Allergy ClinImmunol. 1989;83:416-27.

Squillace SP, Sporik RB, Rakes G, et.al. Sensitization to dust mites as a dominant risk factor for asthma among adolescents living in central Virginia.Multiple regression analysis of a population-based study. Am J Respir Crit Care Med. 1997;156(6):1760-4.

Boulet LP, Turcotte H, Laprise C, et al. Comparative degree and type of sensitization to common indoor and outdoor allergens in subjects with allergic rhinitis and/or asthma. Clin Exp Allergy. 1997;27(1):52-59.

Breiteneder H, Mills C. Structural bioinformatic approaches to understand cross-reactivity. Mol Nutr Food Res. 2006;50(7):628–32.

Schein CH, Ivanciuc O, Braun W. Bioinformatics approaches to classifying allergens and predicting cross-reactivity. Immunol Allergy Clin North Am. 2007;27(1):1–27.

Reese G, Ayuso R, Lehrer SB. Tropomyosin: An invertebrate pan-allergen. Int Arch Allergy Immunol. 1999;119(14):247-58.

Ayuso R, Reese G, Leong-Kee S, Plante M, Lehrer SB. Molecular basis of arthropod cross-reactivity: IgE-binding cross-reactive epitopes of shrimp, house dust mite and cockroach tropomyosins. Int Arch Allergy Immunol. 2002;129(1):38–48.

Zhang R, Jise Q, Zheng W, et al. Characterization and evaluation of a Sarcoptesscabiei allergen as a candidate vaccine. Parasit Vectors. 2012;5:176.

Galán-Freyle N, Olivero-Verbel J, Díaz-López L. Modeling of allergen proteins found in sea food products. Ciênc Tecnol Aliment. 2012;32(2):393-400.

Acevedo N, Caraballo L. IgE cross-reactivity between Ascaris lumbricoides and mite allergens: possible influences on allergic sensitization and asthma. Parasit Immunol. 2011;33(6):309-21.

Shafique RH, Inam M, et al. Group 10 allergens (tropomyosins) from house-dust mites may cause co-variation of sensitization to allergens from other invertebrates. Allergy Rhinol (Providence). 2012;3(2):74-90.

Pajno GB, La Grutta S, Barberio G, Canonica GW, Passalacqua G. Harmful effect of immunotherapy in children with combined snail and mite allergy. J Allergy ClinImmunol. 2002;109(4):627-9.

Azofra J, Lombardero M. Limpet anaphylaxis: cross-reactivity between limpet and house-dust mite Dermatophagoides pteronyssinus. Allergy. 2003;58(2):146-9.

Xiaohui C, Haiyan H, Xiaoman L. A new measurement of sequence conservation. BMC Genomics. 2009;10:623.




DOI: https://doi.org/10.22037/nbm.v3i4.6964