Journal of Molecular Evolution

, Volume 85, Issue 5–6, pp 172–187 | Cite as

Evolution of Single-Domain Globins in Hydrothermal Vent Scale-Worms

  • J. Projecto-Garcia
  • A.-S. Le Port
  • T. Govindji
  • D. Jollivet
  • S. W. Schaeffer
  • S. Hourdez
Original Article


Hypoxia at deep-sea hydrothermal vents represents one of the most basic challenges for metazoans, which then requires specific adaptations to acquire oxygen to meet their metabolic needs. Hydrothermal vent scale-worms (Polychaeta; Polynoidae) express large amounts of extracellular single- and multi-domain hemoglobins, in contrast with their shallow-water relatives that only possess intracellular globins in their nervous system (neuroglobins). We sequenced the gene encoding the single-domain (SD) globin from nine species of polynoids found in various vent and deep-sea reduced microhabitats (and associated constraints) to determine if the Polynoidae SD globins have been the targets of diversifying selection. Although extracellular, all the SD globins (and multi-domain ones) form a monophyletic clade that clusters within the intracellular globin group of other annelids, indicating that these hemoglobins have evolved from an intracellular myoglobin-like form. Positive selection could not be detected at the major ecological changes that the colonization of the deep-sea and hydrothermal vents represents. This suggests that no major structural modification was necessary to allow the globins to function under these conditions. The mere expression of these globins extracellularly may have been sufficiently advantageous for the polynoids living in hypoxic hydrothermal vents. Among hydrothermal vent species, positively selected amino acids were only detected in the phylogenetic lineage leading to the two mussel-commensal species (Branchipolynoe). In this lineage, the multiplicity of hemoglobins could have lessened the selective pressure on the SD hemoglobin, allowing the acquisition of novel functions by positive Darwinian selection. Conversely, the colonization of hotter environments (species of Branchinotogluma) does not seem to have required additional modifications.


Extracellular globin Single-domain Positive selection Heme Oxygen affinity Polynoidae 



The authors would like to thank the crews of the ships and submersibles, as well as the chief scientists, of the cruises ATOS 2001 (project funded by Ifremer and INSU), Lau basin (projects funded by two NSF grants to C.R. Fisher (NSF OCE 0240985 and NSF OCE 0732333)), and EPR 2001 (project funded by a NSF Grant to C.R. Fisher (NSF OCE-0002729)). We would also like to thank Isabelle Boutet-Tanguy and Arnaud Tanguy for technical advice in lab, and Matthieu Bruneaux, Anis Bessadok, and Mirjam Czjzek for protein modeling advice. This work is part of the project HYPOXEVO (Région Bretagne), Deep-Sea Annelid Biodiversity and Evolution (Fondation Total), and was supported by the ESTeam research Marie Curie grant under the 6th framework program from the European Commission.

Supplementary material

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Supplementary material 1 (DOCX 35 KB)
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Supplementary material 2 (PDF 268 KB)
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Supplementary material 3 (PDF 122 KB)
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Supplementary material 4 (PDF 103 KB)


  1. Anisimova M (2003) Detecting positive selection in the protein coding genes. Dissertation, University College LondonGoogle Scholar
  2. Anisimova M, Bielawski JP, Yang Z (2001) Accuracy and power of the likelihood ratio test in detecting adaptive molecular evolution. Mol Biol Evol 18:1585–1592CrossRefPubMedGoogle Scholar
  3. Arnold K, Bordoli L, Kopp J, Schwede T (2006) The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling. Bioinformatics 22:195–201CrossRefPubMedGoogle Scholar
  4. Arp AJ, Childress JJ (1983) Sulfide binding by the blood of the hydrothermal vent tube worm Riftia pachyptila. Science 219:295–297CrossRefPubMedGoogle Scholar
  5. Bailly X, Jollivet D, Vanin S, Deutsch J, Zal F, Lallier F, Toulmond A (2002) Evolution of the sulfide-binding function within the globin multigenic family of the deep-sea hydrothermal vent tubeworm Riftia pachyptila. Mol Biol Evol 19:1421–1433CrossRefPubMedGoogle Scholar
  6. Bailly X, Leroy R, Carney S, Collin O, Zal F, Toulmond A, Jollivet D (2003) The loss of the hemoglobin H2S-binding function in annelids from sulfide-free habitats reveals molecular adaptation driven by Darwinian positive selection. PNAS 100:5885–5890CrossRefPubMedPubMedCentralGoogle Scholar
  7. Biasini M, Bienert S, Waterhouse A, Arnold K, Studer G, Schmidt T, Kiefer F, Cassarino TG, Bertoni M, Bordoli L, Schwede T (2014) SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Res 42(W1):W252-W258CrossRefPubMedCentralGoogle Scholar
  8. Bordoli L, Kiefer F, Arnold K, Benkert P, Battey J, Schwede T (2009) Protein structure homology modelling using SWISS-MODEL Workspace. Nat Protoc 4:1CrossRefPubMedGoogle Scholar
  9. Carrico RJ, Blumberg WE, Peisach J (1978) The reversible binding of oxygen to sulfhemoglobin. J Biol Chem 253:7212–7215PubMedGoogle Scholar
  10. Childress JJ, Fisher CR (1992) The biology of hydrothermal vent animals: physiology, biochemistry, and autotrophic symbioses. Oceanogr Mar Biol - An Annual Review 30:337–441Google Scholar
  11. Darriba D, Taboada GL, Doallo R, Posada D (2011) ProtTest 3: fast selection of best-fit models of protein evolution. Bioinformatics 27:1164CrossRefPubMedPubMedCentralGoogle Scholar
  12. Darriba D, Taboada GL, Doallo R, Posada D (2012) jModelTest 2: more models, new heuristics and parallel computing. Nat Methods 9:772CrossRefPubMedPubMedCentralGoogle Scholar
  13. Davenport HE (1949) Ascaris Haemoglobin as an indicator of the oxygen produced by isolated chloroplasts. P R Soc London B 136:281–290CrossRefGoogle Scholar
  14. De Baere I, Perutz MF, Kiger L, Marden MC, Poyart C (1994) Formation of two hydrogen bonds from the globin to the heme-linked oxygen molecule in Ascaris hemoglobin. P Natl Acad Sci USA 91:1594–1597CrossRefGoogle Scholar
  15. DeLano WL (2008) The PyMOL Molecular Graphics System. DeLano Scientific LLC, Palo Alto, CAGoogle Scholar
  16. Dewilde S, Blaxter M, Hauwaert M-L, Vanfleteren J, Esmans EL, Marden M, Griffon N, Moens L (1996) Globin and Globin Structure of the Nerve Myoglobin of Aphrodite aculeata. J Biol Chem 271:19865–19870CrossRefPubMedGoogle Scholar
  17. Doyle JJ, Doyle JL (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull 19:11–15Google Scholar
  18. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797CrossRefPubMedPubMedCentralGoogle Scholar
  19. Gibson QH, Smith MH (1965) Rates of Reaction of Ascaris Haemoglobins with Ligands. P Roy Soc Lond B Bio163:206–214CrossRefGoogle Scholar
  20. Goodman M, Pedwaydon J, Czelusniak J, Suzuki T, Gotoh T, Moens L, Shishikura F, Walz D, Vinogradov SN (1988) An evolutionary tree for invertebrate globin sequences. J Mol Evol 27:236–249CrossRefPubMedGoogle Scholar
  21. Guidon S, Gascuel O (2003) A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol 52:696–704CrossRefGoogle Scholar
  22. Hourdez S, Lallier F (2007) Adaptations to hypoxia in hydrothermal-vent and cold-seep invertebrates. Rev Environ Sci Biotechnol 6:143–159CrossRefGoogle Scholar
  23. Hourdez S, Weber RE (2005) Molecular and functional adaptations in deep-sea hemoglobins. J Inorg Biochem 99:130–141CrossRefPubMedGoogle Scholar
  24. Hourdez S, Lallier FH, Green BN, Toulmond A (1999a) Hemoglobins from deep-sea hydrothermal vent scale-worms of the genus Branchipolynoe: A new type of quaternary structure. Proteins 34:427–434CrossRefPubMedGoogle Scholar
  25. Hourdez S, Lallier FH, Martin-Jézéquel V, Weber RE, Toulmond A (1999b) Characterization and functional properties of the extracellular coelomic hemoglobins from the deep-sea, hydrothermal vent scale-worm Branchipolynoe symmytilida. Proteins 34:435–442CrossRefPubMedGoogle Scholar
  26. Huelsenbeck JP, Ronquist F (2001) MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17:754–755CrossRefPubMedGoogle Scholar
  27. Jollivet D, Empis A, Baker MC, Hourdez S, Comtet T, Jouin-Toulmond C, Desbruyères D, Tyler PA (2000) Reproductive Biology, Sexual Dimorphism, and Population Structure of the Deep Sea Hydrothermal Vent Scale-Worm, Branchipolynoe Seepensis (Polychaeta: Polynoidae). J Mar Biol 80:55–68CrossRefGoogle Scholar
  28. Koshi JM, Goldstein RA (1996) Probabilistic Reconstruction of Ancestral Protein Sequences. J Mol Evol 42:313–320CrossRefPubMedGoogle Scholar
  29. Mozhaev VV, Heremans K, Frank J, Masson P, Balny C (1996) High Pressure Effects on Protein Structure and Function. Proteins: Structure, Function Genetics 24:84–91Google Scholar
  30. Nielsen R, Yang Z (1998) Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene. Genetics 148:929–936PubMedPubMedCentralGoogle Scholar
  31. Norlinder E, Nygren A, Wiklund H, Pleijel F (2012) Phylogeny of scale-worms (Aphroditiformia, Annelida), assessed from 18SrRNA, 28SrRNA, 16SrRNA, mitochondrial cytochrome c oxidase subunit I (COI), and morphology. Mol Phylogenet Evol 65(2):490–500CrossRefPubMedGoogle Scholar
  32. Okazaki T, Wittenberg JB (1965) The Hemoglobin of Ascaris Perienteric Fluid. BBA-Gen Subjects 111:485–495CrossRefGoogle Scholar
  33. Pascual-García A, Abia D, Méndez R, Nido GS, Bastolla U (2010) Quantifying the evolutionary divergence of protein structures: the role of function change and function conservation. Proteins 78:181–196CrossRefPubMedGoogle Scholar
  34. Penn O, Privman E, Ashkenazy H, Landan G, Graur D, Pupko T (2010) GUIDANCE; a web server for assessing alignment confidence scores. Nucleic Acids Res 38:W23-W28CrossRefPubMedCentralGoogle Scholar
  35. Peterson ES, Huang S, Wang J, Miller LM, Vidugiris G, Kloek AP, Goldberg DE, Chance MR, Wittenberg JB, Friedman JM (1997) A comparison of functional and structural consequences of the tyrosine B10 and glutamine E7 motifs in two invertebrate hemoglobins (Ascaris suum and Lucina pectinata). BioChemistry 36:13110–13121CrossRefPubMedGoogle Scholar
  36. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) UCSF Chimera - A visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612CrossRefPubMedGoogle Scholar
  37. Projecto-Garcia J, Zorn N, Didier J, Shaeffer SW, Lallier FH, Hourdez S (2010) Origin and evolution of the unique tetra-domain hemoglobin from the hydrothermal vent scale-worm Branchipolynoe. Mol Biol Evol 27:143–152CrossRefPubMedGoogle Scholar
  38. Projecto-Garcia J, Jollivet D, Mary J, Lallier FH, Schaeffer SW, Hourdez H (2015) Selective forces acting during multidomain protein evolution: the case of multi-domain globins. SpringerPlus 4:354CrossRefPubMedPubMedCentralGoogle Scholar
  39. Ronquist F, Huelsenbeck JP (2003) Mr Bayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19:1572–1574CrossRefPubMedGoogle Scholar
  40. Royer WE Jr, Strand K, van Heel M, Hendrickson WA (2000) Structural hierarchy in erythrocruorin, the giant respiratory assemblage of annelids. P Natl Acad Sci USA 97:7107–7111CrossRefGoogle Scholar
  41. Royer WE Jr, Knapp JE, Strand K, Heaslet HA (2001) Cooperative Hemoglobins: Conserved Fold, Diverse Quaternary Assemblies and Allosteric Mechanisms. Trends Biochem Sci 26:297–304CrossRefPubMedGoogle Scholar
  42. Royer WE Jr, Zhu H, Gorr TA, Flores JF, Knapp JE (2005) Allosteric hemoglobin assembly: Diversity and similarity. J Biol Chem 280:27477–27480CrossRefPubMedGoogle Scholar
  43. Sambrook J, Fritsch EF, Maniatis T (1989) Molecular Cloning: A Laboratory Manual, vol I. 2nd edn. Cold Spring Harbor Laboratory PressGoogle Scholar
  44. Schlitzer R (2015) Ocean Data View 4.
  45. Sick H, Gersonde K (1969) Method of continuous registration of O2 binding curves of hemoproteins by means of a diffusion chamber. Ana Biochem 32:362–376CrossRefGoogle Scholar
  46. Tunnicliffe V (1991) The Biology of Hydrothermal Vents: Ecology and Evolution. Oceanogr Mar Biol Ann Rev 29:319–407Google Scholar
  47. Van Dover CL, Trask J, Gross J, Knowlton A (1999) Reproductive biology of free-living and commensal polynoid polychaetes at the Lucky Strike hydrothermal vent field (Mid-Atlantic Ridge). Mar Ecol Prog Ser 181:201–214CrossRefGoogle Scholar
  48. Weber RE (1978) Respiratory pigments. Physiology of annelids. Academic Press Inc, LondonGoogle Scholar
  49. Weber RE (2000) Adaptations for oxygen transport: Lessons from fish hemoglobins. In: Di Prisco G, Giardina B, Weber RE (eds) Hemoglobin function in vertebrates, molecular adaptation in extreme and temperate environments. Springer, Milan, pp 23–37CrossRefGoogle Scholar
  50. Weber RE, Vinogradov SN (2001) Nonvertebrate hemoglobins: functions and molecular adaptations. Physiol Rev 81:569–628PubMedGoogle Scholar
  51. Weber RE, Lykkeboe G, Johansen K (1976) Physiological properties of eel haemoglobin: hypoxic acclimation, phosphate effects and multiplicity. J Exp Bio 64:75–88Google Scholar
  52. Weigert A, Bleidorn C (2016) Current status of annelid phylogeny. Org Div Evol 16(2):345–362CrossRefGoogle Scholar
  53. Wong WSW, Yang Z, Goldman N, Nielsen R (2004) Accuracy and power of statistical methods for detecting adaptive evolution in protein coding sequences and for identifying positively selected sites. Genetics 168:1041–1051CrossRefPubMedPubMedCentralGoogle Scholar
  54. Yang Z (1998) Likelihood ratio tests for detecting positive selection and application to primate lysozyme evolution. Mol Biol Evol 15:568–573CrossRefPubMedGoogle Scholar
  55. Yang Z (2008) Computational molecular evolution. Oxford, New YorkGoogle Scholar
  56. Yang Z, Nielsen R (2002) Codon-substitution models for detecting molecular adaptations at individual sites along specific lineages. Mol Biol Evol 19:908–917CrossRefPubMedGoogle Scholar
  57. Yang Z, Wong WSW, Nielsen R (2005) Bayes empirical bayes inference of Amino acid sites under positive selection. Mol Biol Evol 22:1107–1118CrossRefPubMedGoogle Scholar
  58. Zhang Y, Sun J, Chen C, Watanabe HK, Feng D, Zhang Y, Chiu JMY, Qian P-Y, Qiu J-W (2017) Adaptation and evolution of deep-sea scale worms (Annelida: Polynoidae): insights from transcriptome comparison with a shallow-water species. Sci Rep 7:46205CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.CNRS UMR 7144Station Biologique de RoscoffRoscoffFrance
  2. 2.Laboratoire Adaptation et Diversité en Milieu MarinSorbonne Universités, UPMC Univ. Paris 06Roscoff CedexFrance
  3. 3.Department of Biology and Institute of Molecular Evolutionary GeneticsPennsylvania State UniversityUniversity ParkUSA
  4. 4.Ragsdale Lab, Myers Hall 100Indiana UniversityBloomingtonUSA

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