FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / Int J Mol Sci / Secrets behind Protein Sequences: Unveiling the Potential Re...
International journal of molecular sciences2023; 24(3); 2481; doi: 10.3390/ijms24032481

Secrets behind Protein Sequences: Unveiling the Potential Reasons for Varying Allergenicity Caused by Caseins from Cows, Goats, Camels, and Mares Based on Bioinformatics Analyses.

Abstract: This study systematically investigated the differences in allergenicity of casein in cow milk (CM), goat milk (GM), camel milk (CAM), and mare milk (MM) from protein structures using bioinformatics. Primary structure sequence analysis reveals high sequence similarity between the -casein of CM and GM, while all allergenic subtypes are likely to have good hydrophilicity and thermal stability. By analyzing linear B-cell epitope, T-cell epitope, and allergenic peptides, the strongest casein allergenicity is observed for CM, followed by GM, and the casein of MM has the weakest allergenicity. Meanwhile, 7, 9, and 16 similar or identical amino acid fragments in linear B-cell epitopes, T-cell epitopes, and allergenic peptides, respectively, were observed in different milks. Among these, the same T-cell epitope FLGAEVQNQ was shared by κ-CN in all four different species' milk. Epitope results may provide targets of allergenic fragments for reducing milk allergenicity through physical or/and chemical methods. This study explained the underlying secrets for the high allergenicity of CM to some extent from the perspective of casein and provided new insights for the dairy industry to reduce milk allergy. Furthermore, it provides a new idea and method for comparing the allergenicity of homologous proteins from different species.
Get Full Text
Publication Date: 2023-01-27 PubMed ID: 36768806PubMed Central: PMC9916876DOI: 10.3390/ijms24032481Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research focuses on investigating the varying degrees of allergenicity in casein—a protein found in milk—of different animal species, namely cows, goats, camels, and mares. The study employs bioinformatics to establish a relation between the protein structures and allergenicity.

Protein Structure and Allergenicity

  • The research points out a noticeable similarity in the sequence of the proteins present in cow milk (CM) casein and goat milk (GM) casein at a primary structure level.
  • All the allergenic casein subtypes observed were found to possess good hydrophilicity and excellent thermal stability.
  • The allergenicity of casein differs in various types of milk; cow’s milk casein shows the highest allergenicity, while that found in mare’s milk (MM) has the weakest. Goat’s milk casein an intermediate allergenicity, superior to mare’s milk but inferior to cow’s milk.

Allergenic Peptides and Epitopes

  • Analysis of linear B-cell epitopes, T-cell epitopes, and allergenic peptides was carried out, revealing several similar or identical amino acid fragments.
  • Specifically, 7, 9, and 16 similar or identical amino acid fragments were found in linear B-cell epitopes, T-cell epitopes, and allergenic peptides, respectively, in different types of milk.
  • A unique T-cell epitope, FLGAEVQNQ, was found in κ-CN, a type of casein, in all four types of milk.

Implications and Future Directions

  • The results from the epitope analysis may be useful in identifying targets for reducing milk allergenicity. The possible methods of reducing allergenicity might include physical or chemical alterations.
  • The research partially sheds light on the reasons behind the high allergenicity of cow’s milk casein.
  • These findings offer new insights that could be valuable for the dairy industry in mitigating milk allergy incidence.
  • This study also proposes a novel approach to comparing the allergenicity of homologous proteins across different species.

Cite This Article

APA
Zhao S, Pan F, Cai S, Yi J, Zhou L, Liu Z. (2023). Secrets behind Protein Sequences: Unveiling the Potential Reasons for Varying Allergenicity Caused by Caseins from Cows, Goats, Camels, and Mares Based on Bioinformatics Analyses. Int J Mol Sci, 24(3), 2481. https://doi.org/10.3390/ijms24032481

Publication

International journal of molecular sciences
ISSN: 1422-0067
NlmUniqueID: 101092791
Country: Switzerland
Language: English
Volume: 24
Issue: 3
PII: 2481

Researcher Affiliations

Zhao, Shuai
  • Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China.
  • Yunnan Engineering Research Center for Fruit & Vegetable Products, Kunming 650500, China.
  • International Green Food Processing Research and Development Center of Kunming City, Kunming 650500, China.
Pan, Fei
  • Beijing Engineering and Technology Research Center of Food Additives, Beijing Technology and Business University, Beijing 100048, China.
Cai, Shengbao
  • Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China.
  • Yunnan Engineering Research Center for Fruit & Vegetable Products, Kunming 650500, China.
  • International Green Food Processing Research and Development Center of Kunming City, Kunming 650500, China.
Yi, Junjie
  • Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China.
  • Yunnan Engineering Research Center for Fruit & Vegetable Products, Kunming 650500, China.
  • International Green Food Processing Research and Development Center of Kunming City, Kunming 650500, China.
Zhou, Linyan
  • Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China.
  • Yunnan Engineering Research Center for Fruit & Vegetable Products, Kunming 650500, China.
  • International Green Food Processing Research and Development Center of Kunming City, Kunming 650500, China.
Liu, Zhijia
  • Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China.
  • Yunnan Engineering Research Center for Fruit & Vegetable Products, Kunming 650500, China.
  • International Green Food Processing Research and Development Center of Kunming City, Kunming 650500, China.

MeSH Terms

  • Animals
  • Female
  • Horses
  • Cattle
  • Caseins / chemistry
  • Camelus
  • Allergens / metabolism
  • Goats / metabolism
  • Epitopes, T-Lymphocyte
  • Immunoglobulin E
  • Peptides
  • Epitopes, B-Lymphocyte
  • Milk Proteins

Grant Funding

  • 202102AE099950 / Yunnan Major Science and Technology Project
  • 202202AG050009 / Yunnan Major Science and Technology Project

Conflict of Interest Statement

The authors declare that they have no known competing financial interest or personal relationships that could have appeared to influence the work reported in this paper.

References

This article includes 46 references
  1. Pu P, Zheng X, Jiao L, Chen L, Yang H, Zhang Y, Liang G. Six flavonoids inhibit the antigenicity of β-lactoglobulin by noncovalent interactions: A spectroscopic and molecular docking study.. Food Chem 2021 Mar 1;339:128106.
    doi: 10.1016/j.foodchem.2020.128106pubmed: 33152886google scholar: lookup
  2. Villa C, Costa J, Oliveira MBPP, Mafra I. Bovine Milk Allergens: A Comprehensive Review.. Compr Rev Food Sci Food Saf 2018 Jan;17(1):137-164.
    doi: 10.1111/1541-4337.12318pubmed: 33350061google scholar: lookup
  3. Kurpiewska K, Biela A, Loch JI, Lipowska J, Siuda M, Lewiński K. Towards understanding the effect of high pressure on food protein allergenicity: β-lactoglobulin structural studies.. Food Chem 2019 Jan 1;270:315-321.
    pubmed: 30174052doi: 10.1016/j.foodchem.2018.07.104google scholar: lookup
  4. Monaci L, Tregoat V, Hengel A.J.V, Anklam E. Milk allergens, their characteristics and their detection in food: A review.. Eur. Food Res. Technol. 2006;223:149–179.
    doi: 10.1007/s00217-005-0178-8google scholar: lookup
  5. Ehlayel M, Bener A, Abu Hazeima K, Al-Mesaifri F. Camel milk is a safer choice than goat milk for feeding children with cow milk allergy.. ISRN Allergy 2011;2011:391641.
    doi: 10.5402/2011/391641pmc: PMC3658853pubmed: 23724227google scholar: lookup
  6. Uniacke-Lowe T, Huppertz T, Fox P.F. Equine milk proteins: Chemistry, structure and nutritional significance.. Int. Dairy J. 2010;20:609–629.
    doi: 10.1016/j.idairyj.2010.02.007google scholar: lookup
  7. Ng SW, Lu P, Rulikowska A, Boehm D, O'Neill G, Bourke P. The effect of atmospheric cold plasma treatment on the antigenic properties of bovine milk casein and whey proteins.. Food Chem 2021 Apr 16;342:128283.
    doi: 10.1016/j.foodchem.2020.128283pubmed: 33067041google scholar: lookup
  8. Selvaggi M, Laudadio V, Dario C, Tufarelli V. Major proteins in goat milk: an updated overview on genetic variability.. Mol Biol Rep 2014 Feb;41(2):1035-48.
    doi: 10.1007/s11033-013-2949-9pubmed: 24381104google scholar: lookup
  9. Brezovečki A, Čagalj M, Filipović Dermit Z, Mikulec N, Bendelja Ljoljić D, Antunac N. Camel milk and milk products.. Mljekarstvo 2015;65:81–90.
  10. Natale M, Bisson C, Monti G, Peltran A, Garoffo LP, Valentini S, Fabris C, Bertino E, Coscia A, Conti A. Cow's milk allergens identification by two-dimensional immunoblotting and mass spectrometry.. Mol Nutr Food Res 2004 Oct;48(5):363-9.
    doi: 10.1002/mnfr.200400011pubmed: 15672476google scholar: lookup
  11. Mackie A. The Digestive Tract: A Complex System.. Interdiscip. Approaches Food Dig. 2019:11–27.
  12. Han R, Maycock J, Murray BS, Boesch C. Identification of angiotensin converting enzyme and dipeptidyl peptidase-IV inhibitory peptides derived from oilseed proteins using two integrated bioinformatic approaches.. Food Res Int 2019 Jan;115:283-291.
    doi: 10.1016/j.foodres.2018.12.015pubmed: 30599943google scholar: lookup
  13. Bokka CS, Veeramachaneni GK, Thunuguntla VBSC, Manda NK, Bondili JS. Specific panallergen peptide of Sorghum Polcalcin showing IgE response identified based on in silico and in vivo peptide mapping.. Biosci Rep 2019 Nov 29;39(11).
    doi: 10.1042/BSR20191835pmc: PMC6859114pubmed: 31694050google scholar: lookup
  14. da S Vieira D, Polveiro RC, Butler TJ, Hackett TA, Braga CP, Puniya BL, Teixeira WFP, de M Padilha P, Adamec J, Feitosa FLF. An in silico, structural, and biological analysis of lactoferrin of different mammals.. Int J Biol Macromol 2021 Sep 30;187:119-126.
    doi: 10.1016/j.ijbiomac.2021.07.102pubmed: 34302867google scholar: lookup
  15. Yu C, Huang L. Cross-Linking Mass Spectrometry: An Emerging Technology for Interactomics and Structural Biology.. Anal Chem 2018 Jan 2;90(1):144-165.
    doi: 10.1021/acs.analchem.7b04431pmc: PMC6022837pubmed: 29160693google scholar: lookup
  16. Roy A, Kucukural A, Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction.. Nat Protoc 2010 Apr;5(4):725-38.
    doi: 10.1038/nprot.2010.5pmc: PMC2849174pubmed: 20360767google scholar: lookup
  17. Zhang C, Freddolino PL, Zhang Y. COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction information.. Nucleic Acids Res 2017 Jul 3;45(W1):W291-W299.
    doi: 10.1093/nar/gkx366pmc: PMC5793808pubmed: 28472402google scholar: lookup
  18. Nongonierma A.B, Fitzgerald R.J. Strategies for the discovery and identification of food protein-derived biologically active peptides.. Trends Food Sci. Technol. 2017;69:289–305.
    doi: 10.1016/j.tifs.2017.03.003google scholar: lookup
  19. Dimitrov I, Bangov I, Flower DR, Doytchinova I. AllerTOP v.2--a server for in silico prediction of allergens.. J Mol Model 2014 Jun;20(6):2278.
    doi: 10.1007/s00894-014-2278-5pubmed: 24878803google scholar: lookup
  20. Gupta S, Kapoor P, Chaudhary K, Gautam A, Kumar R, Raghava GP. In silico approach for predicting toxicity of peptides and proteins.. PLoS One 2013;8(9):e73957.
    pmc: PMC3772798pubmed: 24058508doi: 10.1371/journal.pone.0073957google scholar: lookup
  21. Miranda G, Mahé MF, Leroux C, Martin P. Proteomic tools to characterize the protein fraction of Equidae milk.. Proteomics 2004 Aug;4(8):2496-509.
    doi: 10.1002/pmic.200300765pubmed: 15274143google scholar: lookup
  22. Lönnerdal B. Nutritional and physiologic significance of human milk proteins.. Am J Clin Nutr 2003 Jun;77(6):1537S-1543S.
    doi: 10.1093/ajcn/77.6.1537Spubmed: 12812151google scholar: lookup
  23. Jaiswal L, Worku M. Recent perspective on cow's milk allergy and dairy nutrition.. Crit Rev Food Sci Nutr 2022;62(27):7503-7517.
    doi: 10.1080/10408398.2021.1915241pubmed: 33983082google scholar: lookup
  24. Thompson JD, Gibson TJ, Higgins DG. Multiple sequence alignment using ClustalW and ClustalX.. Curr Protoc Bioinformatics 2002 Aug;Chapter 2:Unit 2.3.
    doi: 10.1002/0471250953.bi0203s00pubmed: 18792934google scholar: lookup
  25. Restani P, Ballabio C, Di Lorenzo C, Tripodi S, Fiocchi A. Molecular aspects of milk allergens and their role in clinical events.. Anal Bioanal Chem 2009 Sep;395(1):47-56.
    doi: 10.1007/s00216-009-2909-3pubmed: 19578836google scholar: lookup
  26. Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins M.R, Appel R.D, Bairoch A. The proteomics protocols handbook, Protein identification and analysis tools on the ExPASy server.. Proteom. Protoc. Handbook. 2005:571–607.
  27. Kyte J, Doolittle RF. A simple method for displaying the hydropathic character of a protein.. J Mol Biol 1982 May 5;157(1):105-32.
    doi: 10.1016/0022-2836(82)90515-0pubmed: 7108955google scholar: lookup
  28. Ikai A. Thermostability and aliphatic index of globular proteins.. J Biochem 1980 Dec;88(6):1895-8.
    pubmed: 7462208
  29. Rehman SU, Nadeem A, Javed M, Hassan FU, Luo X, Khalid RB, Liu Q. Genomic Identification, Evolution and Sequence Analysis of the Heat-Shock Protein Gene Family in Buffalo.. Genes (Basel) 2020 Nov 23;11(11).
    doi: 10.3390/genes11111388pmc: PMC7700627pubmed: 33238553google scholar: lookup
  30. Gomaa A, Boye J.I. Impact of thermal processing time and cookie size on the detection of casein, egg, gluten and soy allergens in food.. Food Res. Int. 2013;52:483–489.
    doi: 10.1016/j.foodres.2013.01.019google scholar: lookup
  31. Zhou F.L, He S.D, Sun H.J, Wang Y.F, Zhang Y. Advances in epitope mapping technologies for food protein allergens: A review.. Trends Food Sci. Technol. 2020;107:226–239.
    doi: 10.1016/j.tifs.2020.10.035google scholar: lookup
  32. Jespersen MC, Peters B, Nielsen M, Marcatili P. BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes.. Nucleic Acids Res 2017 Jul 3;45(W1):W24-W29.
    doi: 10.1093/nar/gkx346pmc: PMC5570230pubmed: 28472356google scholar: lookup
  33. Dhanda SK, Mahajan S, Paul S, Yan Z, Kim H, Jespersen MC, Jurtz V, Andreatta M, Greenbaum JA, Marcatili P, Sette A, Nielsen M, Peters B. IEDB-AR: immune epitope database-analysis resource in 2019.. Nucleic Acids Res 2019 Jul 2;47(W1):W502-W506.
    doi: 10.1093/nar/gkz452pmc: PMC6602498pubmed: 31114900google scholar: lookup
  34. Chatchatee P, Järvinen KM, Bardina L, Beyer K, Sampson HA. Identification of IgE- and IgG-binding epitopes on alpha(s1)-casein: differences in patients with persistent and transient cow's milk allergy.. J Allergy Clin Immunol 2001 Feb;107(2):379-83.
    doi: 10.1067/mai.2001.112372pubmed: 11174208google scholar: lookup
  35. Busse PJ, Järvinen KM, Vila L, Beyer K, Sampson HA. Identification of sequential IgE-binding epitopes on bovine alpha(s2)-casein in cow's milk allergic patients.. Int Arch Allergy Immunol 2002 Sep;129(1):93-6.
    doi: 10.1159/000065178pubmed: 12373003google scholar: lookup
  36. Chatchatee P, Järvinen KM, Bardina L, Vila L, Beyer K, Sampson HA. Identification of IgE and IgG binding epitopes on beta- and kappa-casein in cow's milk allergic patients.. Clin Exp Allergy 2001 Aug;31(8):1256-62.
    doi: 10.1046/j.1365-2222.2001.01167.xpubmed: 11529896google scholar: lookup
  37. Kapila R, Kavadi P.K, Kapila S. Comparative evaluation of allergic sensitization to milk proteins of cow, buffalo and goat.. Small Rumin. Res. 2013;112:191–198.
    doi: 10.1016/j.smallrumres.2012.11.028google scholar: lookup
  38. El-Agamy E.I. The challenge of cow milk protein allergy.. Small Rumin. Res. 2007;68:64–72.
    doi: 10.1016/j.smallrumres.2006.09.016google scholar: lookup
  39. Lafarga T, O'Connor P, Hayes M. Identification of novel dipeptidyl peptidase-IV and angiotensin-I-converting enzyme inhibitory peptides from meat proteins using in silico analysis.. Peptides 2014 Sep;59:53-62.
    doi: 10.1016/j.peptides.2014.07.005pubmed: 25020248google scholar: lookup
  40. Bush RK, Hefle SL. Food allergens.. Crit Rev Food Sci Nutr 1996;36 Suppl:S119-63.
    doi: 10.1080/10408399609527762pubmed: 8959381google scholar: lookup
  41. Gallego M, Toldrá F, Mora L. Quantification and in silico analysis of taste dipeptides generated during dry-cured ham processing.. Food Chem 2022 Feb 15;370:130977.
    doi: 10.1016/j.foodchem.2021.130977pubmed: 34509941google scholar: lookup
  42. Bohle B. T-cell epitopes of food allergens.. Clin Rev Allergy Immunol 2006 Apr;30(2):97-108.
    doi: 10.1385/CRIAI:30:2:97pubmed: 16645222google scholar: lookup
  43. Jensen KK, Andreatta M, Marcatili P, Buus S, Greenbaum JA, Yan Z, Sette A, Peters B, Nielsen M. Improved methods for predicting peptide binding affinity to MHC class II molecules.. Immunology 2018 Jul;154(3):394-406.
    doi: 10.1111/imm.12889pmc: PMC6002223pubmed: 29315598google scholar: lookup
  44. Luo F, Fu Y, Ma L, Dai H, Wang H, Chen H, Zhu H, Yu Y, Hou Y, Zhang Y. Exploration of Dipeptidyl Peptidase-IV (DPP-IV) Inhibitory Peptides from Silkworm Pupae (Bombyx mori) Proteins Based on In Silico and In Vitro Assessments.. J Agric Food Chem 2022 Mar 30;70(12):3862-3871.
    doi: 10.1021/acs.jafc.1c08225pubmed: 35230117google scholar: lookup
  45. Buchan DW, Minneci F, Nugent TC, Bryson K, Jones DT. Scalable web services for the PSIPRED Protein Analysis Workbench.. Nucleic Acids Res 2013 Jul;41(Web Server issue):W349-57.
    doi: 10.1093/nar/gkt381pmc: PMC3692098pubmed: 23748958google scholar: lookup
  46. Combet C, Blanchet C, Geourjon C, Deléage G. NPS@: network protein sequence analysis.. Trends Biochem Sci 2000 Mar;25(3):147-50.
    doi: 10.1016/S0968-0004(99)01540-6pubmed: 10694887google scholar: lookup

Citations

This article has been cited 0 times.
Subscribe to our newsletter
Join 99,344 horse owners like you who receive our email updates on horse health and nutrition.