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Ancestral Sequence Reconstruction as a Tool for the Elucidation of a Stepwise Evolutionary Adaptation

  • Kristina Straub
  • Rainer Merkl
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1851)

Abstract

Ancestral sequence reconstruction (ASR) is a powerful tool to infer primordial sequences from contemporary, i.e., extant ones. An essential element of ASR is the computation of a phylogenetic tree whose leaves are the chosen extant sequences. Most often, the reconstructed sequence related to the root of this tree is of greatest interest: It represents the common ancestor (CA) of the sequences under study. If this sequence encodes a protein, one can “resurrect” the CA by means of gene synthesis technology and study biochemical properties of this extinct predecessor with the help of wet-lab experiments.

However, ASR deduces also sequences for all internal nodes of the tree, and the well-considered analysis of these “intermediates” can help to elucidate evolutionary processes. Moreover, one can identify key mutations that alter proteins or protein complexes and are responsible for the differing properties of extant proteins. As an illustrative example, we describe the protocol for the rapid identification of hotspots determining the binding of the two subunits within the heteromeric complex imidazole glycerol phosphate synthase.

Key words

Ancestral sequence reconstruction Vertical analysis Evolutionary biochemistry In silico mutagenesis Protein–protein interaction 

Notes

Acknowledgement

This work was supported by the Deutsche Forschungsgemeinschaft (ME2259/2-1). Calculations were facilitated by using advanced computational infrastructure provided by the Leibniz Supercomputing Center of the Bavarian Academy of Sciences and Humanities ( www.lrz.de ) under grant pr48fu. We thank Samuel Blanquart for continuous support, many helpful hints, and fruitful discussions.

References

  1. 1.
    Lee D, Redfern O, Orengo C (2007) Predicting protein function from sequence and structure. Nat Rev Mol Cell Biol 8(12):995–1005.  https://doi.org/10.1038/nrm2281CrossRefPubMedGoogle Scholar
  2. 2.
    Schymkowitz J, Borg J, Stricher F et al (2005) The FoldX web server: an online force field. Nucleic Acids Res 33(Web Server issue):W382–W388CrossRefGoogle Scholar
  3. 3.
    Janda JO, Meier A, Merkl R (2013) CLIPS-4D: a classifier that distinguishes structurally and functionally important residue-positions based on sequence and 3D data. Bioinformatics 29(23):3029–3035.  https://doi.org/10.1093/bioinformatics/btt519CrossRefPubMedGoogle Scholar
  4. 4.
    Zellner H, Staudigel M, Trenner T et al (2012) PresCont: predicting protein-protein interfaces utilizing four residue properties. Proteins 80(1):154–168.  https://doi.org/10.1002/prot.23172CrossRefPubMedGoogle Scholar
  5. 5.
    Plach MG, Löffler P, Merkl R, Sterner R (2015) Conversion of anthranilate synthase into isochorismate synthase: implications for the evolution of chorismate-utilizing enzymes. Angew Chem Int Ed 54(38):11270–11274.  https://doi.org/10.1002/anie.201505063CrossRefGoogle Scholar
  6. 6.
    Edgar RC, Batzoglou S (2006) Multiple sequence alignment. Curr Opin Struct Biol 16(3):368–373CrossRefGoogle Scholar
  7. 7.
    Harms MJ, Thornton JW (2010) Analyzing protein structure and function using ancestral gene reconstruction. Curr Opin Struct Biol 20(3):360–366.  https://doi.org/10.1016/j.sbi.2010.03.005CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4(4):406–425PubMedGoogle Scholar
  9. 9.
    Gerlt JA (2017) Genomic enzymology: web tools for leveraging protein family sequence-function space and genome context to discover novel functions. Biochemistry 56(33):4293–4308.  https://doi.org/10.1021/acs.biochem.7b00614CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Merkl R, Sterner R (2016) Ancestral protein reconstruction: techniques and applications. Biol Chem 397(1):1–21.  https://doi.org/10.1515/hsz-2015-0158CrossRefPubMedGoogle Scholar
  11. 11.
    Thornton JW (2004) Resurrecting ancient genes: experimental analysis of extinct molecules. Nat Rev Genet 5(5):366–375.  https://doi.org/10.1038/nrg1324CrossRefPubMedGoogle Scholar
  12. 12.
    Liberles DA (2007) Ancestral sequence reconstruction. Oxford University Press, OxfordCrossRefGoogle Scholar
  13. 13.
    Hochberg GKA, Thornton JW (2017) Reconstructing ancient proteins to understand the causes of structure and function. Annu Rev Biophys 46:247–269.  https://doi.org/10.1146/annurev-biophys-070816-033631CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Bornscheuer UT, Huisman GW, Kazlauskas RJ et al (2012) Engineering the third wave of biocatalysis. Nature 485(7397):185–194.  https://doi.org/10.1038/nature11117CrossRefPubMedGoogle Scholar
  15. 15.
    Romero-Romero ML, Risso VA, Martinez-Rodriguez S et al (2016) Engineering ancestral protein hyperstability. Biochem J 473(20):3611–3620.  https://doi.org/10.1042/BCJ20160532CrossRefPubMedGoogle Scholar
  16. 16.
    Massiere F, Badet-Denisot MA (1998) The mechanism of glutamine-dependent amidotransferases. Cell Mol Life Sci 54(3):205–222CrossRefGoogle Scholar
  17. 17.
    Zalkin H, Smith JL (1998) Enzymes utilizing glutamine as an amide donor. Adv Enzymol Relat Areas Mol Biol 72:87–144PubMedGoogle Scholar
  18. 18.
    Beismann-Driemeyer S, Sterner R (2001) Imidazole glycerol phosphate synthase from Thermotoga maritima. Quaternary structure, steady-state kinetics, and reaction mechanism of the bienzyme complex. J Biol Chem 276(23):20387–20396CrossRefGoogle Scholar
  19. 19.
    List F, Vega MC, Razeto A et al (2012) Catalysis uncoupling in a glutamine amidotransferase bienzyme by unblocking the glutaminase active site. Chem Biol 19(12):1589–1599.  https://doi.org/10.1016/j.chembiol.2012.10.012CrossRefPubMedGoogle Scholar
  20. 20.
    Reisinger B, Sperl J, Holinski A et al (2014) Evidence for the existence of elaborate enzyme complexes in the Paleoarchean era. J Am Chem Soc 136(1):122–129.  https://doi.org/10.1021/ja4115677CrossRefPubMedGoogle Scholar
  21. 21.
    Holinski A, Heyn K, Merkl R, Sterner R (2017) Combining ancestral sequence reconstruction with protein design to identify an interface hotspot in a key metabolic enzyme complex. Proteins 85(2):312–321.  https://doi.org/10.1002/prot.25225CrossRefPubMedGoogle Scholar
  22. 22.
    Bar-Rogovsky H, Stern A, Penn O et al (2015) Assessing the prediction fidelity of ancestral reconstruction by a library approach. Protein Eng Des Sel 28(11):507–518.  https://doi.org/10.1093/protein/gzv038CrossRefPubMedGoogle Scholar
  23. 23.
    Altschul SF, Gish W, Miller W et al (1990) Basic local alignment search tool. J Mol Biol 215(3):403–410CrossRefGoogle Scholar
  24. 24.
    Pruitt KD, Tatusova T, Klimke W, Maglott DR (2009) NCBI Reference Sequences: current status, policy and new initiatives. Nucleic Acids Res 37(Database issue):D32–D36.  https://doi.org/10.1093/nar/gkn721CrossRefPubMedGoogle Scholar
  25. 25.
    Apweiler R, Martin M, O’Donovan C et al (2013) Update on activities at the Universal Protein Resource (UniProt) in 2013. Nucleic Acids Res 41(D 1):D43–D47Google Scholar
  26. 26.
    Hunter S, Jones P, Mitchell A et al (2012) InterPro in 2011: new developments in the family and domain prediction database. Nucleic Acids Res 40(Database issue):D306–D312.  https://doi.org/10.1093/nar/gkr948CrossRefPubMedGoogle Scholar
  27. 27.
    Katoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30(4):772–780.  https://doi.org/10.1093/molbev/mst010CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Waterhouse AM, Procter JB, Martin DMA, Clamp M, Barton GJ, (2009) Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics 25(9):1189–1191.  https://doi.org/10.1093/bioinformatics/btp033CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Castresana J (2000) Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 17(4):540–552CrossRefGoogle Scholar
  30. 30.
    Lartillot N, Lepage T, Blanquart S (2009) PhyloBayes 3: a Bayesian software package for phylogenetic reconstruction and molecular dating. Bioinformatics 25(17):2286–2288.  https://doi.org/10.1093/bioinformatics/btp368CrossRefPubMedGoogle Scholar
  31. 31.
    Ali RH, Bark M, Miro J et al (2017) VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces. BMC Bioinformatics 18(1):97.  https://doi.org/10.1186/s12859-017-1505-3CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Ronquist F, Huelsenbeck JP (2003) MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19(12):1572–1574CrossRefGoogle Scholar
  33. 33.
    Bouckaert R, Heled J, Kuhnert D et al (2014) BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Comput Biol 10(4):e1003537.  https://doi.org/10.1371/journal.pcbi.1003537CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Abascal F, Zardoya R, Posada D (2005) ProtTest: selection of best-fit models of protein evolution. Bioinformatics 21(9):2104–2105.  https://doi.org/10.1093/bioinformatics/bti263CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Perriere G, Gouy M (1996) WWW-query: an on-line retrieval system for biological sequence banks. Biochimie 78(5):364–369CrossRefGoogle Scholar
  36. 36.
    Rambaut A (2012) FigTree v1.4. http://tree.bio.ed.ac.uk/software/figtree/
  37. 37.
    Ciccarelli FD, Doerks T, von Mering C et al (2006) Toward automatic reconstruction of a highly resolved tree of life. Science 311(5765):1283–1287CrossRefGoogle Scholar
  38. 38.
    Puigbo P, Wolf YI, Koonin EV (2009) Search for a ‘Tree of Life’ in the thicket of the phylogenetic forest. J Biol 8(6):59.  https://doi.org/10.1186/jbiol159CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Yang Z (2007) PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24(8):1586–1591.  https://doi.org/10.1093/molbev/msm088CrossRefGoogle Scholar
  40. 40.
    Ashkenazy H, Penn O, Doron-Faigenboim A et al (2012) FastML: a web server for probabilistic reconstruction of ancestral sequences. Nucleic Acids Res 40(Web Server issue):W580–W584.  https://doi.org/10.1093/nar/gks498CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Pürzer A, Grassmann F, Birzer D, Merkl R (2011) Key2Ann: a tool to process sequence sets by replacing database identifiers with a human-readable annotation. J Integr Bioinform 8(1):153.  https://doi.org/10.2390/biecoll-jib-2011-153CrossRefGoogle Scholar
  42. 42.
    Löytynoja A, Goldman N (2008) Phylogeny-aware gap placement prevents errors in sequence alignment and evolutionary analysis. Science 320(5883):1632–1635.  https://doi.org/10.1126/science.1158395CrossRefPubMedGoogle Scholar
  43. 43.
    Holmes IH (2017) Historian: accurate reconstruction of ancestral sequences and evolutionary rates. Bioinformatics 33(8):1227–1229.  https://doi.org/10.1093/bioinformatics/btw791CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Krieger E, Joo K, Lee J et al (2009) Improving physical realism, stereochemistry, and side-chain accuracy in homology modeling: four approaches that performed well in CASP8. Proteins 77 Suppl 9:114–122.  https://doi.org/10.1002/prot.22570CrossRefPubMedGoogle Scholar
  45. 45.
    Zhang Y (2008) I-TASSER server for protein 3D structure prediction. BMC Bioinformatics 9:40.  https://doi.org/10.1186/1471-2105-9-40CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Söding J (2005) Protein homology detection by HMM-HMM comparison. Bioinformatics 21(7):951–960.  https://doi.org/10.1093/bioinformatics/bti125CrossRefPubMedGoogle Scholar
  47. 47.
    Webb B, Sali A (2014) Protein structure modeling with MODELLER. Methods Mol Biol 1137:1–15.  https://doi.org/10.1007/978-1-4939-0366-5_1CrossRefPubMedGoogle Scholar
  48. 48.
    Guerois R, Nielsen JE, Serrano L (2002) Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations. J Mol Biol 320(2):369–387CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Biophysics and Physical BiochemistryUniversity of RegensburgRegensburgGermany

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