Molecular evolution of cytochrome C oxidase-I protein of insects living in Saudi Arabia


Autoři: Jamal S. M. Sabir aff001;  Samar Rabah aff001;  Haitham Yacoub aff002;  Nahid H. Hajrah aff001;  Ahmed Atef aff001;  Mohammed Al-Matary aff001;  Sherif Edris aff001;  Mona G. Alharbi aff001;  Magdah Ganash aff001;  Jazem Mahyoub aff001;  Rashad R. Al-Hindi aff001;  Khalid M. Al-Ghamdi aff001;  Neil Hall aff001;  Ahmed Bahieldin aff001;  Majid R. Kamli aff001;  Irfan A. Rather aff001
Působiště autorů: Department of Biological Sciences, Faculty of Science, King Abdulaziz University (KAU), Jeddah, Saudi Arabia aff001;  Department of Biological Sciences, Faculty of Science, University of Jeddah, Dahaban, Saudi Arabia aff002;  Department of Genetics, Faculty of Agriculture, Ain Shams University, Cairo, Egypt aff003;  Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), Faculty of Medicine, King Abdulaziz University (KAU), Jeddah, Saudi Arabia aff004;  The Genome Analysis Center, Norwich Research Park, Norwich, United Kingdom aff005
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224336

Souhrn

The study underpins barcode characterization of insect species collected from Saudi Arabia and explored functional constraints during evolution at the DNA and protein levels to expect the possible mechanisms of protein evolution in insects. Codon structure designated AT-biased insect barcode of the cytochrome C oxidase I (COI). In addition, the predicted 3D structure of COI protein indicated tyrosine in close proximity with the heme ligand, depicted substitution to phenylalanine in two Hymenopteran species. This change resulted in the loss of chemical bonding with the heme ligand. The estimated nucleotide substitution matrices in insect COI barcode generally showed a higher probability of transversion compared with the transition. Computations of codon-by-codon nonsynonymous substitutions in Hymenopteran and Hemipteran species indicated that almost half of the codons are under positive evolution. Nevertheless, codons of COI barcode of Coleoptera, Lepidoptera and Diptera are mostly under purifying selection. The results reinforce that codons in helices 2, 5 and 6 and those in loops 2–3 and 5–6 are mostly conserved and approach strong purifying selection. The overall results argue the possible evolutionary position of Hymenopteran species among those of other insects.

Klíčová slova:

Animal evolution – Heme – Insects – Protein structure – Protein structure comparison – Protein structure prediction – Sequence alignment – Tyrosine


Zdroje

1. Scheffers BR, Joppa LN, Pimm SL, Laurance WF. What we know and don’t know about Earth's missing biodiversity. Trends Ecol. Evol. 2012;27:501–510. doi: 10.1016/j.tree.2012.05.008 22784409

2. Hebert PDN, Cywinska A, Ball SL, deWaard JR. Biological identifications through DNA barcodes. Proc. Biol. Sci. 2003;270:313–321. doi: 10.1098/rspb.2002.2218 12614582

3. Hebert PDN, Penton EH, Burns JM, Janzen DH, Hallwachs W. Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator. Proc. Natl. Acad. Sci. 2004;101:14812–14817. doi: 10.1073/pnas.0406166101 15465915

4. Ratnasingham S and Hebert PDN. A DNA-based registry for all animal species: The Barcode Index Number (BIN) System. PLoS ONE. 2013;8: e66213. doi: 10.1371/journal.pone.0066213 23861743

5. Hebert PDN, deWaard JR, Zakharov EV, Prosser SWJ, Sones JE, et al. A DNA “Barcode Blitz”: rapid digitization and sequencing of a natural history collection. PLoS ONE. 2013; 8:e68535. doi: 10.1371/journal.pone.0068535 23874660

6. Hebert PDN, Ratnasingham S, Zakharov EV, Telfer AC, Levesque-Beaudin V, Milton MA, et al. Counting species with DNA barcodes: Canadian insects. Phil. Trans. R. Soc. 2016;B371:20150333.

7. Cristescu ME. From barcoding single individuals to metabarcoding biological communities: towards an integrative approach to the study of global biodiversity. Trends Ecol. Evol. 2014;29:566–571. doi: 10.1016/j.tree.2014.08.001 25175416

8. Gwiazdowski RA, Foottit RG, Maw HEL, Hebert PDN. The Hemiptera (Insecta) of Canada: Constructing a reference library of DNA barcodes. PLoS ONE. 2015;10:e0125635. doi: 10.1371/journal.pone.0125635 25923328

9. Mutanen M, Kekkonen M, Prosser SWJ, Hebert PDN, Kaila L. One species in eight: DNA barcodes from type specimens resolve a taxonomic quagmire. Mol. Ecol. Resour. 2015;15:967–984. doi: 10.1111/1755-0998.12361 25524367

10. Borges LMS, Hollatz C, Lobo J, Cunha AM, Vilela AP, Calado G, et al. With a little help from DNA barcoding: investigating the diversity of Gastropoda from the Portuguese coast. Sci. Rep. 2016;6:20226. doi: 10.1038/srep20226 26876495

11. Ashfaq M and Hebert PDN. DNA barcodes for bio-surveillance: regulated and economically important arthropod plant pests. Genome. 2016;59:933–945. doi: 10.1139/gen-2016-0024 27753511

12. Ren JM, Ashfaq M, Hu XN, Ma J, Liang F, Hebert PDN, et al. Barcode index numbers expedite quarantine inspections and aid the interception of nonindigenous mealybugs (Pseudococcidae). Biol. Invasions. 2018;20:449–460.

13. Ashfaq M, Sabir JSM, El-Ansary HO, Perez K, Levesque-Beaudin V, Khan AM, et al. Insect diversity in the Saharo-Arabian region: Revealing a little-studied fauna by DNA barcoding. PLoS ONE. 2018;13:e0199965. doi: 10.1371/journal.pone.0199965 29985924

14. Steinke D, Breton V, Berzitis E, Hebert P D N. The School Malaise Trap Program: Coupling educational outreach with scientific discovery. PLoS Biol. 2017;15:e2001829. doi: 10.1371/journal.pbio.2001829 28437475

15. Moriniere J, de Araujo BC, Lam AW, Hausmann A, Balke M, Schmidt S, et al. Species identification in Malaise trap samples by DNA barcoding based on NGS technologies and a scoring matrix. PLoS ONE. 2016;11:e0155497. doi: 10.1371/journal.pone.0155497 27191722

16. Tsukihara T, Aoyama H, Yamashita E, Tomizaki T, Yamaguchi H, Shinzawa-Itoh K, et al. The whole structure of the 13-subunit oxidized cytochrome c oxidase at 2.8 Å. Science. 1996;272:1136–1144. doi: 10.1126/science.272.5265.1136 8638158

17. Balsa E, Marco R, Perales-Clemente E, Szklarczyk R, Calvo E, Landázuri MO, et al. NDUFA4 is a subunit of Complex IV of the mammalian electron transport chain. Cell Metab. 2012;16:378–386. doi: 10.1016/j.cmet.2012.07.015 22902835

18. Mathews CK, Holde KE. van, Appling DRand Anthony-Cahill SJ, 2013. Biochemistry 4th edition (Pearson).

19. Pesole G, Gissi C, De Chirico A, Saccone C. Nucleotide substitution rate of mammalian mitochondrial genomes. J. Mol. Evol. 1999;48:427–434. doi: 10.1007/pl00006487 10079281

20. Meiklejohn CD, Montooth KL, Rand DM. Positive and negative selection on the mitochondrial genome. Trends Genet. 2007;23:259–263. doi: 10.1016/j.tig.2007.03.008 17418445

21. Castoe TA, Jiang ZJ, Gu W, Wang ZO, Pollock DD. Adaptive evolution and functional redesign of core metabolic proteins in snakes. PLoS ONE. 2008;3:e2201. doi: 10.1371/journal.pone.0002201 18493604

22. Galtier N, Nabholz B, Glémin S, Hurst GD. Mitochondrial DNA as a marker of molecular diversity: A reappraisal. Mol. Ecol. 2009;18:4541–4550. doi: 10.1111/j.1365-294X.2009.04380.x 19821901

23. Hutcheson J and Jones D. Spatial variability of insect communities in a homogenous system: Measuring biodiversity using Malaise trapped beetles in a Pinus radiata plantation in New Zealand. Forest Ecol. Manag. 1999;118:93–105.

24. Hill D, Fasham M, Tucker G, Shewry M, Shaw P. Handbook of biodiversity methods: Survey, evaluation and monitoring. Cambridge University Press. 2005;573p.

25. Evans N, Paulay G. DNA barcoding methods for invertebrates. Meth. Mol. Biol. 2012;858:47–77.

26. Bybee S, Córdoba-Aguilar A, Catherine DM, Futahashi R, Hansson B. Odonata (dragonflies and damselflies) as a bridge between ecology and evolutionary genomics. Front. in Zoology. 2016;13:46.

27. Tsukihara T, Aoyama H, Yamashita E, Tomizaki T, Yamaguchi H, et al. Structures of metal sites of oxidized bovine heart cytochrome c oxidase at 2.8 Å. Science. 1995;269:1069–1074. doi: 10.1126/science.7652554 7652554

28. Yang J, Yan R, Roy A, Xu D, Poisson J. The I-TASSER Suite: Protein structure and function prediction. Nature Methods. 2015;12:7–8. doi: 10.1038/nmeth.3213 25549265

29. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, et al. UCSF Chimera—a visualization system for exploratory research and analysis. J. Comput. Chem. 2004;25:1605–1612. doi: 10.1002/jcc.20084 15264254

30. Muse SV and Gaut BS. A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome. Mol. Biol. Evol. 1994;11:715–724. doi: 10.1093/oxfordjournals.molbev.a040152 7968485

31. Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J. Mol. Evol. 1981;17:368–376. doi: 10.1007/bf01734359 7288891

32. Pentinsaari M, Salmela H, Mutanen M, Roslin T. Molecular evolution of a widely adopted taxonomic marker (COI) across the animal tree of life. Sci. Rep. 2016;6:35275. doi: 10.1038/srep35275 27734964

33. Córdoba-Aguilar A. Dragonflies and damselflies. Model organisms for ecological and evolutionary research. Oxford: Oxford University Press.2008.

34. Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol. Marine Biol. Biotechnol. 1994:3;294–299. 7881515

35. Panchenko AR, Wolf YI, Panchenko LA, Madej T. Evolutionary plasticity of protein families: Coupling between sequence and structure variation. Proteins. 2005;61:535–544. doi: 10.1002/prot.20644 16184609

36. Ortí G, Petry P, Porto JIR, Jégu M, Meyer A. Patterns of nucleotide change in mitochondrial ribosomal RNA genes and the phylogeny of piranhas. J. Mol. Evol. 1996;42:169–182. doi: 10.1007/bf02198843 8919869

37. Tsukihara T, Shimokata K, Katayama Y, Shimada H, Muramoto K, Aoyama H, et al. The low-spin heme of cytochrome c oxidase as the driving element of the proton-pumping process. Proc. Natl. Acad. Sci. 2003;100:15304–15309. doi: 10.1073/pnas.2635097100 14673090

38. Page RDM, Holmes EC. Molecular Evolution: A Phylogenetic Approach (Blackwell Science, 1998. Oxford). doi: 10.1126/science.280.5367.1256

39. Moran NA. The evolutionary maintenance of alternative phenotypes. Am. Nat. 1992;139:971–989.

40. Nijhout HF. Development and evolution of adaptive polyphenisms. Evol. Dev. 2003;5:9–18. 12492404

41. West-Eberhard MJ. Developmental plasticity and evolution. 2003. Oxford Univ Press, New York.

42. Pfennig DW, Wund MA, Snell-Rood EC, Cruickshank T, Schlichting CD, Moczwk AP. Phenotypic plasticity's impacts on diversification and speciation. Trends Ecol. Evol. 2010;25:459–467. doi: 10.1016/j.tree.2010.05.006 20557976

43. Hölldobler B, Wilson EO. The Ants. 1990. Belknap Press of Harvard Univ. Press, Cambridge, MA.

44. Moczek AP and Emlen DJ. Proximate determination of male horn dimorphism in the beetle Onthophagus Taurus (Coleoptera: Scarabaeidae). J. Evol. Biol. 1999;12:27–37.

45. Müller CB, Williams IS, Hardie J. The role of nutrition, crowding and interspecific interactions in the development of winged aphids. Ecol. Entomol. 2001;26:330–340.

46. Ellegren H and Parsch J. The evolution of sex-biased genes and sex-biased gene expression. Nat. Rev. Genet. 2007;8:689–698. doi: 10.1038/nrg2167 17680007

47. Smith CR, Toth AL, Suarez AV, Robinson GE. Genetic and genomic analyses of the division of labour in insect societies. Nat. Rev. Genet. 2008;9:735–748. doi: 10.1038/nrg2429 18802413

48. Ayroles JF, Carbone MA, Stone EA, Jordan KW, Lyman RF, Magwire MM, et al. Systems genetics of complex traits in Drosophila melanogaster. Nat. Genet.2009;41:299–307. doi: 10.1038/ng.332 19234471

49. Connallon T and Clark AG. Association between sex-biased gene expression and mutations with sex-specific phenotypic consequences in Drosophila. Genome Biol. Evol. 2011;3:151–155. doi: 10.1093/gbe/evr004 21292631

50. Graveley BR, Brooks AN, Joseph CW, Duff MO, Jane M, et al. The developmental transcriptome of Drosophila melanogaster. Nature. 2011;471:473–479. doi: 10.1038/nature09715 21179090

51. Ometto L, Shoemaker D, Ross KG, Keller L. Evolution of gene expression in fire ants: The effects of developmental stage, caste, and species. Mol. Biol. Evol. 2011;28:1381–1392. doi: 10.1093/molbev/msq322 21172833

52. Hunt BG, Wyder S, Elango N, Werren JH, Zdobnov EM, et al. Sociality is linked to rates of protein evolution in a highly social insect. Mol. Biol. Evol. 2010;27:497–500. doi: 10.1093/molbev/msp225 20110264

53. Snell-Rood EC, Cash A, Han MV, Kijimoto T, Andrews J, Moczek AP. Developmental decoupling of alternative phenotypes: Insights from the transcriptomes of horn-polyphenic beetles. Evolution. 2011;65:231–245. doi: 10.1111/j.1558-5646.2010.01106.x 20731717

54. Reinhold K. Energetically costly behaviour and the evolution of resting metabolic rate in insects. Funct. Ecol. 1999;13:217–224.


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