Abstract
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.
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References
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. https://doi.org/10.1186/s12915-016-0284-z
Gunn A, Jane Pitt S (2012) Parasitology: an integrated approach. Wiley, London, pp 86–136. https://doi.org/10.1017/S0031182012001412
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. https://doi.org/10.1111/j.1420-9101.2005.00895.x
Antonovics J, Wilson AJ, Forbes MR et al (2017) The evolution of transmission mode. Philos Trans R Soc Lond Ser B Biol Sci. https://doi.org/10.1098/rstb.2016.0083
Walker DM, Oghumu S, Gupta G et al (2014) Mechanisms of cellular invasion by intracellular parasites. Cell Mol Life Sci 71:1245–1263. https://doi.org/10.1007/s00018-013-1491-1
WHO (2015) Investing to overcome the global impact of neglected tropical diseases. Third WHO report on neglected tropical diseases. WHO, Geneva
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. https://doi.org/10.1371/journal.pntd.0002865
Merrifield M, Hotez PJ, Beaumier CM et al (2016) Advancing a vaccine to prevent human schistosomiasis. Vaccine 34:2988–2991. https://doi.org/10.1016/j.vaccine.2016.03.079
Mantelin S, Bellafiore S, Kyndt T (2017) Meloidogyne graminicola: a major threat to rice agriculture. Mol Plant Pathol 18:3–15. https://doi.org/10.1111/mpp.12394
Andrews KT, Fisher G, Skinner-Adams TS (2014) Drug repurposing and human parasitic protozoan diseases. Int J Parasitol Drugs Drug Resist 4:95–111. https://doi.org/10.1016/j.ijpddr.2014.02.002
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. https://doi.org/10.1016/j.zool.2016.06.010
Cuesta-Astroz Y, Scholte LLS, Pais FSM et al (2014) Evolutionary analysis of the cystatin family in three Schistosoma species. Front Genet. https://doi.org/10.3389/fgene.2014.00206
Wakelin D (1996) Helminths: pathogenesis and defenses. University of Texas Medical Branch at Galveston, Galveston
McCall L-I, Zhang W-W, Matlashewski G (2013) Determinants for the development of visceral leishmaniasis disease. PLoS Pathog 9:e1003053. https://doi.org/10.1371/journal.ppat.1003053
Salzet M, Capron A, Stefano GB (2000) Molecular crosstalk in host-parasite relationships: schistosome- and leech-host interactions. Parasitol Today 16:536–540
Cuesta-Astroz Y, Santos A, Oliveira G, Jensen LJ (2017) An integrative method to unravel the host-parasite interactome: an orthology-based approach. bioRxiv. https://doi.org/10.1101/147868
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. https://doi.org/10.1128/MMBR.64.3.515-547.2000
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. https://doi.org/10.1101/gr.207401
Maizels RM, Yazdanbakhsh M (2003) Immune regulation by helminth parasites: cellular and molecular mechanisms. Nat Rev Immunol 3:733–744. https://doi.org/10.1038/nri1183
Cuesta-Astroz Y, Oliveira FS de, Nahum LA, Oliveira G (2017) Helminth secretomes reflect different lifestyles and parasitized hosts. Int J Parasitol doi: https://doi.org/10.1016/j.ijpara.2017.01.007
Nombela C, Gil C, Chaffin WL (2006) Non-conventional protein secretion in yeast. Trends Microbiol 14:15–21. https://doi.org/10.1016/j.tim.2005.11.009
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. https://doi.org/10.1371/journal.pone.0045974
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. https://doi.org/10.1038/srep25885
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. https://doi.org/10.1016/j.ijpara.2015.09.002
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 264:1–74
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. https://doi.org/10.1016/j.ijpara.2015.03.004
Loukas A, Tran M, Pearson MS (2007) Schistosome membrane proteins as vaccines. Int J Parasitol 37:257–263. https://doi.org/10.1016/j.ijpara.2006.12.001
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. https://doi.org/10.3390/ijms17111946
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. https://doi.org/10.1093/nar/gkw937
Fields S, Uetz P, Giot L et al (2000) A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature 403:623–627. https://doi.org/10.1038/35001009
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. https://doi.org/10.1007/s00018-013-1333-1
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). https://doi.org/10.1186/s13071-016-1943-1
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. https://doi.org/10.1074/mcp.M800079-MCP200
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. https://doi.org/10.1038/nprot.2010.83
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. https://doi.org/10.3389/fimmu.2012.00419
Rao VS, Srinivas K, Sujini GN, Kumar GNS (2014) Protein-protein interaction detection: methods and analysis. Int J Proteomics 2014:1–12. https://doi.org/10.1155/2014/147648
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. https://doi.org/10.1007/s00436-015-4666-x
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. https://doi.org/10.1128/JVI.01023-16
Clark DP (1999) New insights into human cryptosporidiosis. Clin Microbiol Rev 12:554–563
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 27:87–88
Miernyk JA, Thelen JJ (2008) Biochemical approaches for discovering protein-protein interactions. Plant J 53:597–609. https://doi.org/10.1111/j.1365-313X.2007.03316.x
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. https://doi.org/10.1038/13732
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. https://doi.org/10.1007/s00436-005-1306-x
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. https://doi.org/10.1007/s00436-016-5327-4
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. https://doi.org/10.1128/IAI.00643-10
Martinez J, Campetella O, Frasch AC, Cazzulo JJ (1991) The major cysteine proteinase (cruzipain) from Trypanosoma cruzi is antigenic in human infections. Infect Immun 59:4275–4277
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 35:191–196
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. https://doi.org/10.1093/intimm/dxm149
Macauley MS, Crocker PR, Paulson JC (2014) Siglec-mediated regulation of immune cell function in disease. Nat Rev Immunol 14:653–666. https://doi.org/10.1038/nri3737
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. https://doi.org/10.1007/s00430-015-0421-2
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. https://doi.org/10.1038/nrm2208
Garcia-del Portillo F, Finlay BB (1995) The varied lifestyles of intracellular pathogens within eukaryotic vacuolar compartments. Trends Microbiol 3:373–380
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. https://doi.org/10.1111/j.1365-2958.2005.04983.x
Melton L (2004) Protein arrays: proteomics in multiplex. Nature 429:101–107. https://doi.org/10.1038/429101a
de Assis RR, Ludolf F, Nakajima R et al (2016) A next-generation proteome array for Schistosoma mansoni. Int J Parasitol 46:411–415. https://doi.org/10.1016/j.ijpara.2016.04.001
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. https://doi.org/10.1371/journal.ppat.1004033
King CH (2010) Parasites and poverty: the case of schistosomiasis. Acta Trop 113:95–104. https://doi.org/10.1016/j.actatropica.2009.11.012
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. https://doi.org/10.1128/IAI.00796-13
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. https://doi.org/10.1371/journal.pntd.0005323
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. https://doi.org/10.1016/j.ymeth.2012.06.011
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. https://doi.org/10.1101/gr.205301
ZHOU H, JIN J, WONG L (2013) Progress in computational studies of host–pathogen interactions. J Bioinforma Comput Biol 11:1230001. https://doi.org/10.1142/S0219720012300018
Nourani E, Khunjush F, DurmuÅŸ S (2015) Computational approaches for prediction of pathogen-host protein-protein interactions. Front Microbiol 6:94. https://doi.org/10.3389/fmicb.2015.00094
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. https://doi.org/10.1186/1471-2105-9-S12-S11
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. https://doi.org/10.1016/j.csbj.2014.08.006
Luo Q, Pagel P, Vilne B, Frishman D (2011) DIMA 3.0: domain interaction map. Nucleic Acids Res 39:D724–D729. https://doi.org/10.1093/nar/gkq1200
Riley R, Lee C, Sabatti C, Eisenberg D (2005) Inferring protein domain interactions from databases of interacting proteins. Genome Biol 6:R89. https://doi.org/10.1186/gb-2005-6-10-r89
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 30:303–305
Kass I, Horovitz A (2002) Mapping pathways of allosteric communication in GroEL by analysis of correlated mutations. Proteins Struct Funct Genet 48:611–617. https://doi.org/10.1002/prot.10180
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. https://doi.org/10.1093/nar/gkt1210
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. https://doi.org/10.1093/nar/gkt887
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. https://doi.org/10.1093/nar/gkv1291
Maier AG, Cooke BM, Cowman AF, Tilley L (2009) Malaria parasite proteins that remodel the host erythrocyte. Nat Rev Microbiol 7:341–354. https://doi.org/10.1038/nrmicro2110
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. https://doi.org/10.1111/j.1365-2141.2012.09044.x
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. https://doi.org/10.1186/s12859-014-0393-z
Chothia C, Lesk AM (1986) The relation between the divergence of sequence and structure in proteins. EMBO J 5:823–826
Fiser A (2010) Template-based protein structure modeling. Methods Mol Biol 673:73–94. https://doi.org/10.1007/978-1-60761-842-3_6
Davis FP, Barkan DT, Eswar N et al (2007) Host-pathogen protein interactions predicted by comparative modeling. Protein Sci 16:2585–2596. https://doi.org/10.1110/ps.073228407
Eswar N, John B, Mirkovic N et al (2003) Tools for comparative protein structure modeling and analysis. Nucleic Acids Res 31:3375–3380
Davis FP, Sali A (2005) PIBASE: a comprehensive database of structurally defined protein interfaces. Bioinformatics 21:1901–1907. https://doi.org/10.1093/bioinformatics/bti277
Jianlin Cheng J, Tegge AN, Baldi P (2008) Machine learning methods for protein structure prediction. IEEE Rev Biomed Eng 1:41–49. https://doi.org/10.1109/RBME.2008.2008239
Baldi P, Brunak S, Chauvin Y et al (2000) Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics 16:412–424
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 2009:516–527
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. https://doi.org/10.1016/j.meegid.2011.02.022
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. https://doi.org/10.1093/bioinformatics/btq394
Kazan H (2016) Modeling gene regulation in liver hepatocellular carcinoma with random forests. Biomed Res Int 2016:1035945. https://doi.org/10.1155/2016/1035945
Wuchty S (2011) Computational prediction of host-parasite protein interactions between P. falciparum and H. sapiens. PLoS One 6:e26960. https://doi.org/10.1371/journal.pone.0026960
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. https://doi.org/10.1038/nmeth.3178
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. https://doi.org/10.1186/1752-0509-4-179
Ge H, Liu Z, Church GM, Vidal M (2001) Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae. Nat Genet 29:482–486. https://doi.org/10.1038/ng776
Reid AJ, Berriman M (2013) Genes involved in host-parasite interactions can be revealed by their correlated expression. Nucleic Acids Res 41:1508–1518. https://doi.org/10.1093/nar/gks1340
Acknowledgments
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.
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Cuesta-Astroz, Y., Oliveira, G. (2018). Computational and Experimental Approaches to Predict Host–Parasite Protein–Protein Interactions. In: von Stechow, L., Santos Delgado, A. (eds) Computational Cell Biology. Methods in Molecular Biology, vol 1819. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8618-7_7
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