Computational and Experimental Approaches to Predict Host–Parasite Protein–Protein Interactions

  • Yesid Cuesta-Astroz
  • Guilherme OliveiraEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1819)


In host–parasite systems, protein–protein interactions are key to allow the pathogen to enter the host and persist within the host. The study of host–parasite molecular communication improves the understanding the mechanisms of infection, evasion of the host immune system and tropism across different tissues. Current trends in parasitology focus on unraveling host–parasite protein–protein interactions to aid the development of new strategies to combat pathogenic parasites with better treatments and prevention mechanisms. Due to the complexity of capturing experimentally these interactions, computational approaches integrating data from different sources (mainly “omics” data) become key to complement or support experimental approaches. Here, we focus on the application of experimental and computational methods in the prediction of host–parasite interactions and highlight the potential of each of these methods in specific contexts.

Key words

Host–parasite interactions Proteomics Computational biology Secretome Parasitology Protein–protein interactions Systems biology 



We would like to thank the editors for the opportunity to contribute to this book. This work was supported by the National Institutes of Health-NIH/Fogarty International Center, USA (TW007012 and 1P50AI098507-01) to G.O., Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-CAPES, Brazil (REDE 21/2015 and 070/13) to G.O., FAPEMIG (RED-00014-14 and PPM-00189-13) to G.O., and Conselho Nacional de Desenvolvimento Científico e Tecnológico-CNPq, Brazil (304138/2014-2) to G.O. G.O. is a CNPq fellow (307479/2016-1), and Y.C.A. a CAPES fellow. An EMBO short-term fellowship (400-2015) to Y.C.A is acknowledged.


  1. 1.
    Xu F, Jerlstrom-Hultqvist J, Kolisko M et al (2016) On the reversibility of parasitism: adaptation to a free-living lifestyle via gene acquisitions in the diplomonad Trepomonas sp. PC1. BMC Biol 14:62.
  2. 2.
    Gunn A, Jane Pitt S (2012) Parasitology: an integrated approach. Wiley, London, pp 86–136. CrossRefGoogle Scholar
  3. 3.
    RAUCH G, KALBE M, TBH REUSCH (2005) How a complex life cycle can improve a parasite’s sex life. J Evol Biol 18:1069–1075. CrossRefGoogle Scholar
  4. 4.
    Antonovics J, Wilson AJ, Forbes MR et al (2017) The evolution of transmission mode. Philos Trans R Soc Lond Ser B Biol Sci. CrossRefGoogle Scholar
  5. 5.
    Walker DM, Oghumu S, Gupta G et al (2014) Mechanisms of cellular invasion by intracellular parasites. Cell Mol Life Sci 71:1245–1263. CrossRefGoogle Scholar
  6. 6.
    WHO (2015) Investing to overcome the global impact of neglected tropical diseases. Third WHO report on neglected tropical diseases. WHO, GenevaGoogle Scholar
  7. 7.
    Hotez PJ, Alvarado M, Basáñez M-G et al (2014) The global burden of disease study 2010: interpretation and implications for the neglected tropical diseases. PLoS Negl Trop Dis 8:e2865. CrossRefGoogle Scholar
  8. 8.
    Merrifield M, Hotez PJ, Beaumier CM et al (2016) Advancing a vaccine to prevent human schistosomiasis. Vaccine 34:2988–2991. CrossRefGoogle Scholar
  9. 11.
    Mantelin S, Bellafiore S, Kyndt T (2017) Meloidogyne graminicola: a major threat to rice agriculture. Mol Plant Pathol 18:3–15. CrossRefGoogle Scholar
  10. 12.
    Andrews KT, Fisher G, Skinner-Adams TS (2014) Drug repurposing and human parasitic protozoan diseases. Int J Parasitol Drugs Drug Resist 4:95–111. PubMedGoogle Scholar
  11. 19.
    Greenwood JM, Ezquerra AL, Behrens S et al (2016) Current analysis of host–parasite interactions with a focus on next generation sequencing data. Zoology 119:298–306. CrossRefGoogle Scholar
  12. 20.
    Cuesta-Astroz Y, Scholte LLS, Pais FSM et al (2014) Evolutionary analysis of the cystatin family in three Schistosoma species. Front Genet.
  13. 21.
    Wakelin D (1996) Helminths: pathogenesis and defenses. University of Texas Medical Branch at Galveston, GalvestonGoogle Scholar
  14. 22.
    McCall L-I, Zhang W-W, Matlashewski G (2013) Determinants for the development of visceral leishmaniasis disease. PLoS Pathog 9:e1003053. CrossRefGoogle Scholar
  15. 23.
    Salzet M, Capron A, Stefano GB (2000) Molecular crosstalk in host-parasite relationships: schistosome- and leech-host interactions. Parasitol Today 16:536–540CrossRefGoogle Scholar
  16. 24.
    Cuesta-Astroz Y, Santos A, Oliveira G, Jensen LJ (2017) An integrative method to unravel the host-parasite interactome: an orthology-based approach. bioRxiv.
  17. 25.
    Tjalsma H, Bolhuis A, Jongbloed JD et al (2000) Signal peptide-dependent protein transport in Bacillus subtilis: a genome-based survey of the secretome. Microbiol Mol Biol Rev 64:515–547. CrossRefGoogle Scholar
  18. 26.
    Greenbaum D, Luscombe NM, Jansen R et al (2001) Interrelating different types of genomic data, from proteome to secretome:‘oming in on function. Genome Res 11:1463–1468. CrossRefGoogle Scholar
  19. 27.
    Maizels RM, Yazdanbakhsh M (2003) Immune regulation by helminth parasites: cellular and molecular mechanisms. Nat Rev Immunol 3:733–744. CrossRefGoogle Scholar
  20. 28.
    Cuesta-Astroz Y, Oliveira FS de, Nahum LA, Oliveira G (2017) Helminth secretomes reflect different lifestyles and parasitized hosts. Int J Parasitol doi: CrossRefGoogle Scholar
  21. 29.
    Nombela C, Gil C, Chaffin WL (2006) Non-conventional protein secretion in yeast. Trends Microbiol 14:15–21. CrossRefGoogle Scholar
  22. 30.
    Marcilla A, Trelis M, Cortés A et al (2012) Extracellular vesicles from parasitic helminths contain specific excretory/secretory proteins and are internalized in intestinal host cells. PLoS One 7:e45974. CrossRefGoogle Scholar
  23. 31.
    Zhu L, Liu J, Dao J et al (2016) Molecular characterization of S. japonicum exosome-like vesicles reveals their regulatory roles in parasite-host interactions. Sci Rep 6:25885.
  24. 32.
    Sotillo J, Pearson M, Potriquet J et al (2016) Extracellular vesicles secreted by Schistosoma mansoni contain protein vaccine candidates. Int J Parasitol 46:1–5. CrossRefGoogle Scholar
  25. 33.
    Anantharaman V, Iyer LM, Balaji S, Aravind L (2007) Adhesion molecules and other secreted host-interaction determinants in Apicomplexa: insights from comparative genomics. Int Rev Cytol 264:1–74Google Scholar
  26. 34.
    Sotillo J, Pearson M, Becker L et al (2015) A quantitative proteomic analysis of the tegumental proteins from Schistosoma mansoni schistosomula reveals novel potential therapeutic targets. Int J Parasitol 45:505–516. CrossRefGoogle Scholar
  27. 35.
    Loukas A, Tran M, Pearson MS (2007) Schistosome membrane proteins as vaccines. Int J Parasitol 37:257–263. CrossRefGoogle Scholar
  28. 36.
    Chang J-W, Zhou Y-Q, Ul Qamar M et al (2016) Prediction of protein–protein interactions by evidence combining methods. Int J Mol Sci 17:1946. CrossRefGoogle Scholar
  29. 37.
    Szklarczyk D, Morris JH, Cook H et al (2017) The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucleic Acids Res 45:D362–D368. CrossRefGoogle Scholar
  30. 38.
    Fields S, Uetz P, Giot L et al (2000) A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature 403:623–627. CrossRefGoogle Scholar
  31. 39.
    Ngounou Wetie AG, Sokolowska I, Woods AG et al (2014) Protein–protein interactions: switch from classical methods to proteomics and bioinformatics-based approaches. Cell Mol Life Sci 71:205–228. CrossRefGoogle Scholar
  32. 40.
    Liu Q, Li F-C, Elsheikha HM et al (2017) Identification of host proteins interacting with Toxoplasma gondii GRA15 (TgGRA15) by yeast two-hybrid system. Parasit Vectors 10(1).
  33. 41.
    Gisler SM, Kittanakom S, Fuster D et al (2008) Monitoring protein-protein interactions between the mammalian integral membrane transporters and PDZ-interacting partners using a modified split-ubiquitin membrane yeast two-hybrid system. Mol Cell Proteomics 7:1362–1377. CrossRefGoogle Scholar
  34. 42.
    Snider J, Kittanakom S, Damjanovic D et al (2010) Detecting interactions with membrane proteins using a membrane two-hybrid assay in yeast. Nat Protoc 5:1281–1293. CrossRefGoogle Scholar
  35. 43.
    Tonelli RR, Colli W, Alves MJM (2012) Selection of binding targets in parasites using phage-display and aptamer libraries in vivo and in vitro. Front Immunol 3:419.
  36. 44.
    Rao VS, Srinivas K, Sujini GN, Kumar GNS (2014) Protein-protein interaction detection: methods and analysis. Int J Proteomics 2014:1–12. CrossRefGoogle Scholar
  37. 45.
    Ruiz A, Pérez D, Muñoz MC et al (2015) Targeting essential Eimeria ninakohlyakimovae sporozoite ligands for caprine host endothelial cell invasion with a phage display peptide library. Parasitol Res 114:4327–4331. CrossRefGoogle Scholar
  38. 46.
    Carmona-Vicente N, Vila-Vicent S, Allen D et al (2016) Characterization of a novel conformational GII.4 norovirus epitope: implications for norovirus-host interactions. J Virol 90:7703–7714. CrossRefGoogle Scholar
  39. 47.
    Clark DP (1999) New insights into human cryptosporidiosis. Clin Microbiol Rev 12:554–563CrossRefGoogle Scholar
  40. 48.
    Guo A, Yin J, Xiang M et al (2009) Screening for relevant proteins involved in adhesion of Cryptosporidium parvum sporozoites to host cells. Zhongguo Ji Sheng Chong Xue Yu Ji Sheng Chong Bing Za Zhi 27:87–88Google Scholar
  41. 49.
    Miernyk JA, Thelen JJ (2008) Biochemical approaches for discovering protein-protein interactions. Plant J 53:597–609. CrossRefGoogle Scholar
  42. 50.
    Rigaut G, Shevchenko A, Rutz B et al (1999) A generic protein purification method for protein complex characterization and proteome exploration. Nat Biotechnol 17:1030–1032. CrossRefGoogle Scholar
  43. 51.
    Zhang W, Moreau E, Peigné F et al (2005) Comparison of modulation of sheep, mouse and buffalo lymphocyte responses by Fasciola hepatica and Fasciola gigantica excretory-secretory products. Parasitol Res 95:333–338.
  44. 52.
    Liu Q, Huang S-Y, Yue D-M et al (2017) Proteomic analysis of Fasciola hepatica excretory and secretory products (FhESPs) involved in interacting with host PBMCs and cytokines by shotgun LC-MS/MS. Parasitol Res 116:627–635. CrossRefGoogle Scholar
  45. 53.
    Manque PA, Probst CM, Probst C et al (2011) Trypanosoma cruzi infection induces a global host cell response in cardiomyocytes. Infect Immun 79:1855–1862. CrossRefGoogle Scholar
  46. 54.
    Martinez J, Campetella O, Frasch AC, Cazzulo JJ (1991) The major cysteine proteinase (cruzipain) from Trypanosoma cruzi is antigenic in human infections. Infect Immun 59:4275–4277Google Scholar
  47. 55.
    Martínez J, Campetella O, Frasch AC, Cazzulo JJ (1993) The reactivity of sera from chagasic patients against different fragments of cruzipain, the major cysteine proteinase from Trypanosoma cruzi, suggests the presence of defined antigenic and catalytic domains. Immunol Lett 35:191–196CrossRefGoogle Scholar
  48. 58.
    Acosta DM, Arnaiz MR, Esteva MI et al (2008) Sulfates are main targets of immune responses to cruzipain and are involved in heart damage in BALB/c immunized mice. Int Immunol 20:461–470. CrossRefGoogle Scholar
  49. 59.
    Macauley MS, Crocker PR, Paulson JC (2014) Siglec-mediated regulation of immune cell function in disease. Nat Rev Immunol 14:653–666. CrossRefGoogle Scholar
  50. 60.
    Ferrero MR, Heins AM, Soprano LL et al (2016) Involvement of sulfates from cruzipain, a major antigen of Trypanosoma cruzi, in the interaction with immunomodulatory molecule Siglec-E. Med Microbiol Immunol 205:21–35. CrossRefGoogle Scholar
  51. 61.
    Gingras A-C, Gstaiger M, Raught B, Aebersold R (2007) Analysis of protein complexes using mass spectrometry. Nat Rev Mol Cell Biol 8:645–654. CrossRefGoogle Scholar
  52. 62.
    Garcia-del Portillo F, Finlay BB (1995) The varied lifestyles of intracellular pathogens within eukaryotic vacuolar compartments. Trends Microbiol 3:373–380CrossRefGoogle Scholar
  53. 63.
    Spielmann T, Gardiner DL, Beck H-P et al (2006) Organization of ETRAMPs and EXP-1 at the parasite-host cell interface of malaria parasites. Mol Microbiol 59:779–794. CrossRefGoogle Scholar
  54. 64.
    Melton L (2004) Protein arrays: proteomics in multiplex. Nature 429:101–107. CrossRefGoogle Scholar
  55. 65.
    de Assis RR, Ludolf F, Nakajima R et al (2016) A next-generation proteome array for Schistosoma mansoni. Int J Parasitol 46:411–415. CrossRefGoogle Scholar
  56. 66.
    Gaze S, Driguez P, Pearson MS et al (2014) An immunomics approach to schistosome antigen discovery: antibody signatures of naturally resistant and chronically infected individuals from endemic areas. PLoS Pathog 10:e1004033. CrossRefGoogle Scholar
  57. 67.
    King CH (2010) Parasites and poverty: the case of schistosomiasis. Acta Trop 113:95–104. CrossRefGoogle Scholar
  58. 68.
    Cannella AP, Arlehamn CSL, Sidney J et al (2014) Brucella melitensis T cell epitope recognition in humans with brucellosis in Peru. Infect Immun 82:124–131. CrossRefGoogle Scholar
  59. 69.
    Uplekar S, Rao PN, Ramanathapuram L et al (2017) Characterizing antibody responses to Plasmodium vivax and Plasmodium falciparum antigens in india using genome-scale protein microarrays. PLoS Negl Trop Dis 11:e0005323. CrossRefGoogle Scholar
  60. 70.
    Arnold R, Boonen K, Sun MGF, Kim PM (2012) Computational analysis of interactomes: current and future perspectives for bioinformatics approaches to model the host–pathogen interaction space. Methods 57:508–518. CrossRefGoogle Scholar
  61. 71.
    Matthews LR, Vaglio P, Reboul J et al (2001) Identification of potential interaction networks using sequence-based searches for conserved protein-protein interactions or “Interologs”. Genome Res 11:2120–2126. CrossRefGoogle Scholar
  62. 72.
    ZHOU H, JIN J, WONG L (2013) Progress in computational studies of host–pathogen interactions. J Bioinforma Comput Biol 11:1230001. CrossRefGoogle Scholar
  63. 73.
    Nourani E, Khunjush F, DurmuÅŸ S (2015) Computational approaches for prediction of pathogen-host protein-protein interactions. Front Microbiol 6:94.
  64. 74.
    Lee S-A, Chan C, Tsai C-H et al (2008) Ortholog-based protein-protein interaction prediction and its application to inter-species interactions. BMC Bioinformatics 9(Suppl 12):S11. CrossRefGoogle Scholar
  65. 75.
    Mulder NJ, Akinola RO, Mazandu GK, Rapanoel H (2014) Using biological networks to improve our understanding of infectious diseases. Comput Struct Biotechnol J 11:1–10. CrossRefGoogle Scholar
  66. 76.
    Luo Q, Pagel P, Vilne B, Frishman D (2011) DIMA 3.0: domain interaction map. Nucleic Acids Res 39:D724–D729. CrossRefGoogle Scholar
  67. 77.
    Riley R, Lee C, Sabatti C, Eisenberg D (2005) Inferring protein domain interactions from databases of interacting proteins. Genome Biol 6:R89. CrossRefGoogle Scholar
  68. 78.
    Xenarios I, Salwínski L, Duan XJ et al (2002) DIP, the database of interacting proteins: a research tool for studying cellular networks of protein interactions. Nucleic Acids Res 30:303–305CrossRefGoogle Scholar
  69. 79.
    Kass I, Horovitz A (2002) Mapping pathways of allosteric communication in GroEL by analysis of correlated mutations. Proteins Struct Funct Genet 48:611–617. CrossRefGoogle Scholar
  70. 80.
    Finn RD, Miller BL, Clements J, Bateman A (2014) iPfam: a database of protein family and domain interactions found in the Protein Data Bank. Nucleic Acids Res 42:D364–D373. CrossRefGoogle Scholar
  71. 81.
    Mosca R, Céol A, Stein A et al (2014) 3did: a catalog of domain-based interactions of known three-dimensional structure. Nucleic Acids Res 42:D374–D379. CrossRefGoogle Scholar
  72. 82.
    Dinkel H, Van Roey K, Michael S et al (2016) ELM 2016—data update and new functionality of the eukaryotic linear motif resource. Nucleic Acids Res 44:D294–D300. CrossRefGoogle Scholar
  73. 83.
    Maier AG, Cooke BM, Cowman AF, Tilley L (2009) Malaria parasite proteins that remodel the host erythrocyte. Nat Rev Microbiol 7:341–354. CrossRefGoogle Scholar
  74. 84.
    Mbengue A, Yam XY, Braun-Breton C (2012) Human erythrocyte remodelling during Plasmodium falciparum malaria parasite growth and egress. Br J Haematol 157:171–179. CrossRefGoogle Scholar
  75. 85.
    Liu X, Huang Y, Liang J et al (2014) Computational prediction of protein interactions related to the invasion of erythrocytes by malarial parasites. BMC Bioinformatics 15:393.
  76. 86.
    Chothia C, Lesk AM (1986) The relation between the divergence of sequence and structure in proteins. EMBO J 5:823–826CrossRefGoogle Scholar
  77. 87.
    Fiser A (2010) Template-based protein structure modeling. Methods Mol Biol 673:73–94. Google Scholar
  78. 88.
    Davis FP, Barkan DT, Eswar N et al (2007) Host-pathogen protein interactions predicted by comparative modeling. Protein Sci 16:2585–2596. CrossRefGoogle Scholar
  79. 89.
    Eswar N, John B, Mirkovic N et al (2003) Tools for comparative protein structure modeling and analysis. Nucleic Acids Res 31:3375–3380CrossRefGoogle Scholar
  80. 90.
    Davis FP, Sali A (2005) PIBASE: a comprehensive database of structurally defined protein interfaces. Bioinformatics 21:1901–1907. CrossRefGoogle Scholar
  81. 91.
    Jianlin Cheng J, Tegge AN, Baldi P (2008) Machine learning methods for protein structure prediction. IEEE Rev Biomed Eng 1:41–49. CrossRefGoogle Scholar
  82. 92.
    Baldi P, Brunak S, Chauvin Y et al (2000) Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics 16:412–424CrossRefGoogle Scholar
  83. 93.
    Tastan O, Qi Y, Carbonell JG, Klein-Seetharaman J (2009) Prediction of interactions between HIV-1 and human proteins by information integration. Pac Symp Biocomput 2009:516–527Google Scholar
  84. 94.
    Dyer MD, Murali TM, Sobral BW (2011) Supervised learning and prediction of physical interactions between human and HIV proteins. Infect Genet Evol 11:917–923. CrossRefGoogle Scholar
  85. 95.
    Qi Y, Tastan O, Carbonell JG et al (2010) Semi-supervised multi-task learning for predicting interactions between HIV-1 and human proteins. Bioinformatics 26:i645–i652. CrossRefGoogle Scholar
  86. 96.
    Kazan H (2016) Modeling gene regulation in liver hepatocellular carcinoma with random forests. Biomed Res Int 2016:1035945. CrossRefGoogle Scholar
  87. 97.
    Wuchty S (2011) Computational prediction of host-parasite protein interactions between P. falciparum and H. sapiens. PLoS One 6:e26960. CrossRefGoogle Scholar
  88. 98.
    Kotlyar M, Pastrello C, Pivetta F et al (2015) In silico prediction of physical protein interactions and characterization of interactome orphans. Nat Methods 12:79–84. CrossRefGoogle Scholar
  89. 99.
    Pang K, Cheng C, Xuan Z et al (2010) Understanding protein evolutionary rate by integrating gene co-expression with protein interactions. BMC Syst Biol 4:179. CrossRefGoogle Scholar
  90. 100.
    Ge H, Liu Z, Church GM, Vidal M (2001) Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae. Nat Genet 29:482–486. CrossRefGoogle Scholar
  91. 101.
    Reid AJ, Berriman M (2013) Genes involved in host-parasite interactions can be revealed by their correlated expression. Nucleic Acids Res 41:1508–1518. CrossRefGoogle Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Instituo René Rachou (CPqRR)Fundação Oswaldo Cruz (FIOCRUZ)Belo HorizonteBrazil
  2. 2.Instituto Tecnológico ValeBelémBrazil

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