Login Register Cart 0
Generic placeholder image

Current Proteomics

Editor-in-Chief

ISSN (Print): 1570-1646
ISSN (Online): 1875-6247

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Bioinformatics-based Identification of Proteins Expressed by Arthropod- borne Viruses Transmitted by Aedes Aegypti Mosquito

Author(s): Carlos Polanco*, Vladimir N. Uversky, Alberto Huberman, Leire Andrés, Thomas Buhse, Jorge Alberto Castañón-González and Alma Fernanda Sánchez-Guerrero

Volume 18, Issue 1, 2021

Published on: 22 April, 2020

Page: [81 - 94] Pages: 14

DOI: 10.2174/1570164617999200422123618

Price: $65

Abstract

Background: The female Aedes aegypti mosquito is a vector of several arthropod-borne viruses, such as Mayaro, Dengue, Chikungunya, Yellow Fever, and Zika. These viruses cause the death of at least 600000 people a year and temporarily disable several million more around the world. Up to date, there are no effective prophylactic measures that would prevent the contact and bite of this arthropod and, therefore, its consequential contagion.

Objective: The objective of the present study was to search for the regularities of the proteins expressed by these five viruses, at residues level, and obtain a “bioinformatic fingerprint” to select them.

Methods: We used two bioinformatic systems, our in-house bioinformatic system named Polarity Index Method® (PIM®) supported at residues level, and the commonly used algorithm for the prediction of intrinsic disorder predisposition, PONDR® FIT. We applied both programs to the 29 proteins that express the five groups of arboviruses studied, and we calculated for each of them their Polarity Index Method® profile and their intrinsic disorder predisposition. This information was then compared with analogous information for other protein groups, such as proteins from bacteria, fungi, viruses, and cell-penetrating peptides from the UniProt database, and a set of intrinsically disordered proteins. Once the “fingerprint” of each group of arboviruses was obtained, these “fingerprints” were searched among the 559228 “reviewed” proteins from the UniProt database.

Results: In total, 1736 proteins were identified from the 559228 “reviewed” proteins from the UniProt database, with similar “PIM® profile” to the 29 mutated proteins that express the five groups of arboviruses.

Conclusion: We propose that the “PIM® profile” of characterization of proteins might be useful for the identification of proteins expressed by arthropod-borne viruses transmitted by Aedes aegypti mosquito.

Keywords: Aedes aegypti mosquito, chikungunya, dengue, mayaro, yellow Fever, zika, intrinsic disorder predisposition, polarity Index Method® profile.

« Previous
Graphical Abstract

[1]
Reynolds, E.S.; Hart, C.E.; Hermance, M.E.; Brining, D.L.; Thangamani, S. An overview of animal models for arthropod-borne Viruses. Comp. Med., 2017, 67(3), 232-241.
[PMID: 28662752]
[2]
Acosta-Ampudia, Y.; Monsalve, D.M.; Rodríguez, Y.; Pacheco, Y.; Anaya, J.M.; Ramírez-Santana, C. Mayaro: an emerging viral threat? Emerg. Microbes Infect., 2018, 7(1), 163.
[http://dx.doi.org/10.1038/s41426-018-0163-5] [PMID: 30254258]
[3]
Patterson, J.; Sammon, M.; Garg, M. Dengue, Zika, and Chikungunya: emerging arboviruses in the new world. West. J. Emerg. Med., 2016, 17(6), 671-679.
[http://dx.doi.org/10.5811/westjem.2016.9.30904] [PMID: 27833670]
[4]
Mehta, R.; Gerardin, P.; de Brito, C.A.A.; Soares, C.N.; Ferreira, M.L.B.; Solomon, T. The neurological complications of chikungunya virus: A systematic review. Rev. Med. Virol., 2018, 28(3), e1978.
[http://dx.doi.org/10.1002/rmv.1978] [PMID: 29671914]
[5]
Weetman, D.; Kamgang, B.; Badolo, A.; Moyes, C.L.; Shearer, F.M.; Coulibaly, M.; Pinto, J.; Lambrechts, L.; McCall, P.J. Aedes Mosquitoes and aedes-borne arboviruses in Africa: current and future threats. Int. J. Environ. Res. Public Health, 2018, 15(2), 220.
[http://dx.doi.org/10.3390/ijerph15020220] [PMID: 29382107]
[6]
Epelboin, Y.; Talaga, S.; Epelboin, L.; Dusfour, I. Zika virus: An updated review of competent or naturally infected mosquitoes. PLoS Negl. Trop. Dis., 2017, 11(11), e0005933.
[http://dx.doi.org/10.1371/journal.pntd.0005933] [PMID: 29145400]
[7]
Braack, L.; Gouveia de Almeida, A.P.; Cornel, A.J.; Swanepoel, R.; de Jager, C. Mosquito-borne arboviruses of African origin: review of key viruses and vectors. Parasit. Vectors, 2018, 11(1), 29.
[http://dx.doi.org/10.1186/s13071-017-2559-9] [PMID: 29316963]
[8]
Mathias, L.; Baraka, V.; Philbert, A.; Innocent, E.; Francis, F.; Nkwengulila, G.; Kweka, E.J. Habitat productivity and pyrethroid susceptibility status of Aedes aegypti mosquitoes in Dar es Salaam, Tanzania. Infect. Dis. Poverty, 2017, 6(1), 102.
[http://dx.doi.org/10.1186/s40249-017-0316-0] [PMID: 28595653]
[9]
Weger-Lucarelli, J.; Auerswald, H.; Vignuzzi, M.; Dussart, P.; Karlsson, E.A. Taking a bite out of nutrition and arbovirus infection. PLoS Negl. Trop. Dis., 2018, 12(3), e0006247.
[http://dx.doi.org/10.1371/journal.pntd.0006247] [PMID: 29596427]
[10]
Zahiri, N.; Rau, M.E. Oviposition attraction and repellency of Aedes aegypti (Diptera: Culicidae) to waters from conspecific larvae subjected to crowding, confinement, starvation, or infection. J. Med. Entomol., 1998, 35(5), 782-787.
[http://dx.doi.org/10.1093/jmedent/35.5.782] [PMID: 9775609]
[11]
Angleró-Rodríguez, Y.I.; MacLeod, H.J.; Kang, S.; Carlson, J.S.; Jupatanakul, N.; Dimopoulos, G. Aedes aegypti Molecular Responses to Zika Virus: Modulation of Infection by the Toll and Jak/Stat Immune Pathways and Virus Host Factors. Front. Microbiol., 2017, 8, 2050.
[http://dx.doi.org/10.3389/fmicb.2017.02050] [PMID: 29109710]
[12]
Hussain, A.; Ali, F.; Latiwesh, O.B.; Hussain, S. A comprehensive review of the manifestations and pathogenesis of Zika virus in neonates and adults. Cureus, 2018, 10(9), e3290.
[http://dx.doi.org/10.7759/cureus.3290] [PMID: 30443460]
[13]
World Health Organization. Dengue and severe dengue. 2019. https://www.who.int/Denguecontrol/mosquito/en/
[14]
Harrington, L.C.; Scott, T.W.; Lerdthusnee, K.; Coleman, R.C.; Costero, A.; Clark, G.G.; Jones, J.J.; Kitthawee, S.; Kittayapong, P.; Sithiprasasna, R.; Edman, J.D. Dispersal of the dengue vector Aedes aegypti within and between rural communities. Am. J. Trop. Med. Hyg., 2005, 72(2), 209-220.
[http://dx.doi.org/10.4269/ajtmh.2005.72.209] [PMID: 15741559]
[15]
Alphey, L.; McKemey, A.; Nimmo, D.; Neira Oviedo, M.; Lacroix, R.; Matzen, K.; Beech, C. Genetic control of Aedes mosquitoes. Pathog. Glob. Health, 2013, 107(4), 170-179.
[http://dx.doi.org/10.1179/2047773213Y.0000000095] [PMID: 23816508]
[16]
Polanco, C.; Samaniego Mendoza, J.L.; Buhse, T.; Uversky, V.N.; Bañuelos Chao, I.P.; Bañuelos Cedano, M.A.; Tavera, F.M.; Tavera, D.M.; Falconi, M.; Ponce de León, A.V. Samaniego- Mendoza, J.L.; Buhse, T.; Uversky, N.V.; Bañuelos Chao, I.P.; Tavera, F.M.; Tavera, D.M.; Falconi, M.; Ponce de León, A.V. On the regularities of the polar profiles of proteins related to ebola virus infection and their functional domains. Cell Biochem. Biophys., 2018, 76(3), 411-431.
[http://dx.doi.org/10.1007/s12013-018-0839-4] [PMID: 29511990]
[17]
He, B.; Wang, K.; Liu, Y.; Xue, B.; Uversky, V.N.; Dunker, A.K. Predicting intrinsic disorder in proteins: an overview. Cell Res., 2009, 19(8), 929-949.
[http://dx.doi.org/10.1038/cr.2009.87] [PMID: 19597536]
[18]
UniProt: a hub for protein information. Nucleic Acids Res., 2015, 43(Database issue), D204-D212.
[PMID: 25348405]
[19]
Xue, B.; Dunbrack, R.L.; Williams, R.W.; Dunker, A.K.; Uversky, V.N. PONDR-FIT: a meta-predictor of intrinsically disordered amino acids. Biochim. Biophys. Acta, 2010, 1804(4), 996-1010.
[http://dx.doi.org/10.1016/j.bbapap.2010.01.011] [PMID: 20100603]
[20]
Agrawal, P.; Bhalla, S.; Usmani, S.S.; Singh, S.; Chaudhary, K.; Raghava, G.P.; Gautam, A. CPPsite 2.0: a repository of experimentally validated cell-penetrating peptides. Nucleic Acids Res., 2016, 44(D1), D1098-D1103.
[http://dx.doi.org/10.1093/nar/gkv1266] [PMID: 26586798]
[21]
Oldfield, C.J.; Cheng, Y.; Cortese, M.S.; Brown, C.J.; Uversky, V.N.; Dunker, A.K. Comparing and combining predictors of mostly disordered proteins. Biochemistry, 2005, 44(6), 1989-2000.
[http://dx.doi.org/10.1021/bi047993o] [PMID: 15697224]
[22]
Siegel, S. Estadística no paramétrica aplicada a las ciencias, 1st ed; Trillas: México, 1985.
[23]
Uversky, V.N.; Gillespie, J.R.; Fink, A.L. Why are “natively unfolded” proteins unstructured under physiologic conditions? Proteins, 2000, 41(3), 415-427.
[http://dx.doi.org/10.1002/1097-0134(20001115)41:3<415::AID-PROT130>3.0.CO;2-7] [PMID: 11025552]
[24]
Dunker, A.K.; Lawson, J.D.; Brown, C.J.; Williams, R.M.; Romero, P.; Oh, J.S.; Oldfield, C.J.; Campen, A.M.; Ratliff, C.M.; Hipps, K.W.; Ausio, J.; Nissen, M.S.; Reeves, R.; Kang, C.; Kissinger, C.R.; Bailey, R.W.; Griswold, M.D.; Chiu, W.; Garner, E.C.; Obradovic, Z. Intrinsically disordered protein. J. Mol. Graph. Model., 2001, 19(1), 26-59.
[http://dx.doi.org/10.1016/S1093-3263(00)00138-8] [PMID: 11381529]
[25]
Romero, P.; Obradovic, Z.; Li, X.; Garner, E.C.; Brown, C.J.; Dunker, A.K. Sequence complexity of disordered protein. Proteins, 2001, 42(1), 38-48.
[http://dx.doi.org/10.1002/1097-0134(20010101)42:1<38::AID-PROT50>3.0.CO;2-3] [PMID: 11093259]
[26]
Radivojac, P.; Iakoucheva, L.M.; Oldfield, C.J.; Obradovic, Z.; Uversky, V.N.; Dunker, A.K. Intrinsic disorder and functional proteomics. Biophys. J., 2007, 92(5), 1439-1456.
[http://dx.doi.org/10.1529/biophysj.106.094045] [PMID: 17158572]
[27]
Vacic, V.; Uversky, V.N.; Dunker, A.K.; Lonardi, S. Composition Profiler: a tool for discovery and visualization of amino acid composition differences. BMC Bioinformatics, 2007, 8, 211.
[http://dx.doi.org/10.1186/1471-2105-8-211] [PMID: 17578581]
[28]
Peng, Z.L.; Kurgan, L. Comprehensive comparative assessment of in-silico predictors of disordered regions. Curr. Protein Pept. Sci., 2012, 13(1), 6-18.
[http://dx.doi.org/10.2174/138920312799277938] [PMID: 22044149]
[29]
Meng, F.; Uversky, V.N.; Kurgan, L. Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions. Cell. Mol. Life Sci., 2017, 74(17), 3069-3090.
[http://dx.doi.org/10.1007/s00018-017-2555-4] [PMID: 28589442]
[30]
Obradovic, Z.; Peng, K.; Vucetic, S.; Radivojac, P.; Dunker, A.K. Exploiting heterogeneous sequence properties improves prediction of protein disorder. Proteins, 2005, 61(Suppl. 7), 176-182.
[http://dx.doi.org/10.1002/prot.20735] [PMID: 16187360]
[31]
Peng, K.; Vucetic, S.; Radivojac, P.; Brown, C.J.; Dunker, A.K.; Obradovic, Z. Optimizing long intrinsic disorder predictors with protein evolutionary information. J. Bioinform. Comput. Biol., 2005, 3(1), 35-60.
[http://dx.doi.org/10.1142/S0219720005000886] [PMID: 15751111]
[32]
Prilusky, J.; Felder, C.E.; Zeev-Ben-Mordehai, T.; Rydberg, E.H.; Man, O.; Beckmann, J.S.; Silman, I.; Sussman, J.L. FoldIndex: a simple tool to predict whether a given protein sequence is intrinsically unfolded. Bioinformatics, 2005, 21(16), 3435-3438.
[http://dx.doi.org/10.1093/bioinformatics/bti537] [PMID: 15955783]
[33]
Dosztányi, Z.; Csizmok, V.; Tompa, P.; Simon, I. IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content. Bioinformatics, 2005, 21(16), 3433-3434.
[http://dx.doi.org/10.1093/bioinformatics/bti541] [PMID: 15955779]
[34]
Campen, A.; Williams, R.M.; Brown, C.J.; Meng, J.; Uversky, V.N.; Dunker, A.K. TOP-IDP-scale: a new amino acid scale measuring propensity for intrinsic disorder. Protein Pept. Lett., 2008, 15(9), 956-963.
[http://dx.doi.org/10.2174/092986608785849164] [PMID: 18991772]
[35]
Walsh, I.; Giollo, M.; Di Domenico, T.; Ferrari, C.; Zimmermann, O.; Tosatto, S.C. Comprehensive large-scale assessment of intrinsic protein disorder. Bioinformatics, 2015, 31(2), 201-208.
[http://dx.doi.org/10.1093/bioinformatics/btu625] [PMID: 25246432]
[36]
Kolmogorov, A.N. Foundations of the Theory of Probability; University of New York, Chelsea Publishing Company New York, 1956.
[37]
Manjasetty, B.A.; Büssow, K.; Panjikar, S.; Turnbull, A.P. Current methods in structural proteomics and its applications in biological sciences. Biotech., 2011, 2, 89-113.
[38]
Eldawlatly, S.; Zhou, Y.; Jin, R.; Oweiss, K.G. On the use of dynamic Bayesian networks in reconstructing functional neuronal networks from spike train ensembles. Neural Comput., 2010, 22(1), 158-189.
[http://dx.doi.org/10.1162/neco.2009.11-08-900] [PMID: 19852619]
[39]
Olivier, M.; Eeles, R.; Hollstein, M.; Khan, M.A.; Harris, C.C.; Hainaut, P. The IARC TP53 database: new online mutation analysis and recommendations to users. Hum. Mutat., 2002, 19(6), 607-614.
[http://dx.doi.org/10.1002/humu.10081] [PMID: 12007217]
[40]
Meng, F.; Badierah, R.A.; Almehdar, H.A.; Redwan, E.M.; Kurgan, L.; Uversky, V.N. Unstructural biology of the Dengue virus proteins. FEBS J., 2015, 282(17), 3368-3394.
[http://dx.doi.org/10.1111/febs.13349] [PMID: 26096987]
[41]
Giri, R.; Kumar, D.; Sharma, N.; Uversky, V.N. Intrinsically Disordered Side of the Zika Virus Proteome. Front. Cell. Infect. Microbiol., 2016, 6, 144.
[http://dx.doi.org/10.3389/fcimb.2016.00144] [PMID: 27867910]
[42]
Mishra, P.M.; Uversky, V.N.; Giri, R. Molecular recognition features in zika virus proteome. J. Mol. Biol., 2018, 430(16), 2372-2388.
[http://dx.doi.org/10.1016/j.jmb.2017.10.018] [PMID: 29080786]
[43]
Singh, A.; Kumar, A.; Yadav, R.; Uversky, V.N.; Giri, R. Deciphering the dark proteome of Chikungunya virus. Sci. Rep., 2018, 8(1), 5822.
[http://dx.doi.org/10.1038/s41598-018-23969-0] [PMID: 29643398]
[44]
Polanco, C. Polarity index in Proteins- A Bioinformatics Tool; Bentham Science Publishers Sharjah: U.A.E, 2016.
[45]
Wright, P.E.; Dyson, H.J. Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm. J. Mol. Biol., 1999, 293(2), 321-331.
[http://dx.doi.org/10.1006/jmbi.1999.3110] [PMID: 10550212]
[46]
Uversky, V.N. Natively unfolded proteins: a point where biology waits for physics. Protein Sci., 2002, 11(4), 739-756.
[http://dx.doi.org/10.1110/ps.4210102] [PMID: 11910019]
[47]
Uversky, V.N.; Dunker, A.K. Understanding protein non-folding. Biochim. Biophys. Acta, 2010, 1804(6), 1231-1264.
[http://dx.doi.org/10.1016/j.bbapap.2010.01.017] [PMID: 20117254]
[48]
Uversky, V.N. A decade and a half of protein intrinsic disorder: biology still waits for physics. Protein Sci., 2013, 22(6), 693-724.
[http://dx.doi.org/10.1002/pro.2261] [PMID: 23553817]
[49]
van der Lee, R.; Buljan, M.; Lang, B.; Weatheritt, R.J.; Daughdrill, G.W.; Dunker, A.K.; Fuxreiter, M.; Gough, J.; Gsponer, J.; Jones, D.T.; Kim, P.M.; Kriwacki, R.W.; Oldfield, C.J.; Pappu, R.V.; Tompa, P.; Uversky, V.N.; Wright, P.E.; Babu, M.M. Classification of intrinsically disordered regions and proteins. Chem. Rev., 2014, 114(13), 6589-6631.
[http://dx.doi.org/10.1021/cr400525m] [PMID: 24773235]
[50]
Dunker, A.K.; Obradovic, Z.; Romero, P.; Garner, E.C.; Brown, C.J. Intrinsic protein disorder in complete genomes. Genome Inform. Ser. Workshop Genome Inform., 2000, 11, 161-171.
[PMID: 11700597]
[51]
Ward, J.J.; Sodhi, J.S.; McGuffin, L.J.; Buxton, B.F.; Jones, D.T. Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. J. Mol. Biol., 2004, 337(3), 635-645.
[http://dx.doi.org/10.1016/j.jmb.2004.02.002] [PMID: 15019783]
[52]
Uversky, V.N. The mysterious unfoldome: structureless, underappreciated, yet vital part of any given proteome. J. Biomed. Biotechnol., 2010, 2010, 568068.
[http://dx.doi.org/10.1155/2010/568068] [PMID: 20011072]
[53]
Xue, B.; Dunker, A.K.; Uversky, V.N. Orderly order in protein intrinsic disorder distribution: disorder in 3500 proteomes from viruses and the three domains of life. J. Biomol. Struct. Dyn., 2012, 30(2), 137-149.
[http://dx.doi.org/10.1080/07391102.2012.675145] [PMID: 22702725]
[54]
Peng, Z.; Yan, J.; Fan, X.; Mizianty, M.J.; Xue, B.; Wang, K.; Hu, G.; Uversky, V.N.; Kurgan, L. Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in all domains of life. Cell. Mol. Life Sci., 2015, 72(1), 137-151.
[http://dx.doi.org/10.1007/s00018-014-1661-9] [PMID: 24939692]
[55]
Xue, B.; Williams, R.W.; Oldfield, C.J.; Goh, G.K-M.; Dunker, A.K.; Uversky, V.N. Viral disorder or disordered viruses: do viral proteins possess unique features? Protein Pept. Lett., 2010, 17(8), 932-951.
[http://dx.doi.org/10.2174/092986610791498984] [PMID: 20450483]
[56]
Xue, B.; Blocquel, D.; Habchi, J.; Uversky, A.V.; Kurgan, L.; Uversky, V.N.; Longhi, S. Structural disorder in viral proteins. Chem. Rev., 2014, 114(13), 6880-6911.
[http://dx.doi.org/10.1021/cr4005692] [PMID: 24823319]
[57]
Rost, B.; Yachdav, G.; Liu, J. The PredictProtein server. Nucleic Acids Res., 2004, 32(Web Server issue), W321-W326.
[http://dx.doi.org/10.1093/nar/gkh377]
[58]
Ramachandran, G.N.; Sasisekharan, V. Conformation of polypeptides and proteins. Adv. Protein Chem., 1968, 23, 283-438.
[http://dx.doi.org/10.1016/S0065-3233(08)60402-7] [PMID: 4882249]
[59]
Cole, C.; Barber, J.D.; Barton, G.J. The Jpred 3 secondary structure prediction server. Nucleic Acids Res., 2008, 36(Web Server issue)W197.
[http://dx.doi.org/10.1093/nar/gkn238]

Rights & Permissions Print Cite
Article Metrics
12
© 2024 Bentham Science Publishers | Privacy Policy