Skip to main content
Book cover

AMPK pp 111–142Cite as

Studying AMPK in an Evolutionary Context

Part of the Methods in Molecular Biology book series (MIMB,volume 1732)

Abstract

The AMPK protein kinase forms the heart of a complex network controlling the metabolic activities in a eukaryotic cell. Unraveling the steps by which this pathway evolved from its primordial roots in the last eukaryotic common ancestor to its present status in contemporary species has the potential to shed light on the evolution of eukaryotes. A homolog search for the proteins interacting in this pathway is considerably straightforward. However, interpreting the results, when reconstructing the evolutionary history of the pathway over larger evolutionary distances, bears a number of pitfalls. With this in mind, we present a protocol to trace a metabolic pathway across contemporary species and backward in evolutionary time. Alongside the individual analysis steps, we provide guidelines for data interpretation generalizing beyond the analysis of AMPK.

Key words

  • AMPK evolution
  • Targeted ortholog search
  • Feature architecture
  • Functional equivalence
  • Phylogenetic profiles

This is a preview of subscription content, access via your institution.

Protocol
USD   49.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-1-4939-7598-3_8
  • Chapter length: 32 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   139.00
Price excludes VAT (USA)
  • ISBN: 978-1-4939-7598-3
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   179.00
Price excludes VAT (USA)
Hardcover Book
USD   109.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Springer Nature is developing a new tool to find and evaluate Protocols. Learn more

References

  1. Wetterstrand KA (2016) DNA sequencing costs: data from the NHGRI large-scale genome sequencing program. www.genome.gov/sequencingcostsdata. Accessed 4 Sept. 2016

  2. Vitulo N, Vezzi A, Romualdi C et al (2007) A global gene evolution analysis on Vibrionaceae family using phylogenetic profile. BMC Bioinformatics 8(Suppl 1):S23. https://doi.org/10.1186/1471-2105-8-S1-S23

    CrossRef  PubMed  PubMed Central  Google Scholar 

  3. Sun J, Xu J, Liu Z et al (2005) Refined phylogenetic profiles method for predicting protein-protein interactions. Bioinformatics 21:3409–3415. https://doi.org/10.1093/bioinformatics/bti532

    CrossRef  CAS  PubMed  Google Scholar 

  4. Pellegrini M, Marcotte EM, Thompson MJ et al (1999) Assigning protein functions by comparative genome analysis: protein phylogenetic profiles. Proc Natl Acad Sci U S A 96:4285–4288. https://doi.org/10.1073/pnas.96.8.4285

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  5. Jensen RA (2001) Orthologs and paralogs - we need to get it right. Genome Biol 2(8):interactions1002.1–interactions1002.3. https://doi.org/10.1186/gb-2001-2-8-interactions1002

    CrossRef  Google Scholar 

  6. Baldauf SL (2003) Phylogeny for the faint of heart: a tutorial. Trends Genet 19:345–351. https://doi.org/10.1016/S0168-9525(03)00112-4

    CrossRef  CAS  PubMed  Google Scholar 

  7. Koonin EV (2005) Orthologs, paralogs, and evolutionary genomics. Annu Rev Genet 39:309–338. https://doi.org/10.1146/annurev.genet.39.073003.114725

    CrossRef  CAS  PubMed  Google Scholar 

  8. Dolinski K, Botstein D (2007) Orthology and functional conservation in eukaryotes. Annu Rev Genet 41:465–507. https://doi.org/10.1146/annurev.genet.40.110405.090439

    CrossRef  CAS  PubMed  Google Scholar 

  9. Studer RA, Robinson-Rechavi M (2009) How confident can we be that orthologs are similar, but paralogs differ? Trends Genet 25:210–216. https://doi.org/10.1016/j.tig.2009.03.004

    CrossRef  CAS  PubMed  Google Scholar 

  10. Nehrt NL, Clark WT, Radivojac P, Hahn MW (2011) Testing the ortholog conjecture with comparative functional genomic data from mammals. PLoS Comput Biol 7(6):e1002073. https://doi.org/10.1371/journal.pcbi.1002073

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  11. Gabaldón T, Koonin EV (2013) Functional and evolutionary implications of gene orthology. Nat Rev Genet 14:360–366. https://doi.org/10.1038/nrg3456

    CrossRef  PubMed  Google Scholar 

  12. Roustan V, Jain A, Teige M et al (2016) An evolutionary perspective of AMPK-TOR signaling in the three domains of life. J Exp Bot 67:3897–3907. https://doi.org/10.1093/jxb/erw211

    CrossRef  CAS  PubMed  Google Scholar 

  13. Kanehisa M, Goto S (2000) KEGG: kyoto encyclopaedia of genes and genomes. Nucleic Acids Res 28:27–30. https://doi.org/10.1093/nar/28.1.27

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  14. Nordberg H, Cantor M, Dusheyko S et al (2014) The genome portal of the department of energy joint genome institute: 2014 updates. Nucleic Acids Res 42(Database issue):D26–D31. https://doi.org/10.1093/nar/gkt1069

    CrossRef  CAS  PubMed  Google Scholar 

  15. Bateman A, Martin MJ, O’Donovan C et al (2015) UniProt: a hub for protein information. Nucleic Acids Res 43:D204–D212. https://doi.org/10.1093/nar/gku989

    CrossRef  Google Scholar 

  16. Herrero J, Muffato M, Beal K et al (2016) Ensembl comparative genomics resources. Database 2016:baw053. https://doi.org/10.1093/database/bav096

    CrossRef  PubMed  PubMed Central  Google Scholar 

  17. Sonnhammer ELL, Gabaldon T, Sousa Da Silva AW et al (2014) Big data and other challenges in the quest for orthologs. Bioinformatics 30:2993–2998. https://doi.org/10.1093/bioinformatics/btu492

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kelder T, Van Iersel MP, Hanspers K et al (2012) WikiPathways: building research communities on biological pathways. Nucleic Acids Res 40(Database issue):D1301–D1307. https://doi.org/10.1093/nar/gkr1074

    CrossRef  CAS  PubMed  Google Scholar 

  19. Fabregat A, Sidiropoulos K, Garapati P et al (2016) The reactome pathway knowledgebase. Nucleic Acids Res 44:D481–D487. https://doi.org/10.1093/nar/gkv1351

    CrossRef  CAS  PubMed  Google Scholar 

  20. Cerami EG, Gross BE, Demir E et al (2011) Pathway commons, a web resource for biological pathway data. Nucleic Acids Res 39(Database):D685–D690. https://doi.org/10.1093/nar/gkq1039

    CrossRef  CAS  PubMed  Google Scholar 

  21. Sonnhammer ELL, Östlund G (2015) InParanoid 8: orthology analysis between 273 proteomes, mostly eukaryotic. Nucleic Acids Res 43:D234–D239. https://doi.org/10.1093/nar/gku1203

    CrossRef  CAS  PubMed  Google Scholar 

  22. Altenhoff AM, Boeckmann B, Capella-Gutierrez S et al (2016) Standardized benchmarking in the quest for orthologs. Nat Methods 13:425–430. https://doi.org/10.1038/nmeth.3830

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  23. Altenhoff AM, Šunca N, Glover N et al (2015) The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements. Nucleic Acids Res 43:D240–D249. https://doi.org/10.1093/nar/gku1158

    CrossRef  CAS  PubMed  Google Scholar 

  24. Zdobnov EM, Tegenfeldt F, Kuznetsov D et al (2016) OrthoDB v9.1: cataloging evolutionary and functional annotations for animal, fungal, plant, archaeal, bacterial and viral orthologs. Nucleic Acids Res 45(D1):D744–D749. https://doi.org/10.1093/nar/gkw1119

    CrossRef  PubMed  PubMed Central  Google Scholar 

  25. Ebersberger I, Strauss S, von Haeseler A (2009) HaMStR: profile hidden markov model based search for orthologs in ESTs. BMC Evol Biol 9:157. https://doi.org/10.1186/1471-2148-9-157

    CrossRef  PubMed  PubMed Central  Google Scholar 

  26. Ebersberger I, Simm S, Leisegang MS et al (2014) The evolution of the ribosome biogenesis pathway from a yeast perspective. Nucleic Acids Res 42:1509–1523. https://doi.org/10.1093/nar/gkt1137

    CrossRef  CAS  PubMed  Google Scholar 

  27. Jones P, Binns D, Chang HY et al (2014) InterProScan 5: genome-scale protein function classification. Bioinformatics 30:1236–1240. https://doi.org/10.1093/bioinformatics/btu031

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  28. Finn RD, Mistry J, Tate J et al (2010) The Pfam protein families database. Nucleic Acids Res 38:D211–D222. https://doi.org/10.1093/nar/gkm960

    CrossRef  CAS  PubMed  Google Scholar 

  29. Koestler T, von Haeseler A, Ebersberger I (2010) FACT: functional annotation transfer between proteins with similar feature architectures. BMC Bioinformatics 11:417. https://doi.org/10.1186/1471-2105-11-417

    CrossRef  PubMed  PubMed Central  Google Scholar 

  30. Moore AD, Heldy A, Terrapon N et al (2014) DoMosaics: software for domain arrangement visualization and domain-centric analysis of proteins. Bioinformatics 30:282–283. https://doi.org/10.1093/bioinformatics/btt640

    CrossRef  CAS  PubMed  Google Scholar 

  31. Finn RD, Clements J, Arndt W et al (2015) HMMER web server: 2015 update. Nucleic Acids Res 43:W30–W38. https://doi.org/10.1093/nar/gkv397

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  32. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797. https://doi.org/10.1093/nar/gkh340

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  33. Katoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30:772–780. https://doi.org/10.1093/molbev/mst010

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  34. Darriba D, Taboada GL, Doallo R, Posada D (2011) ProtTest-HPC: fast selection of best-fit models of protein evolution. In: Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics). pp 177–184

    Google Scholar 

  35. Stamatakis A (2014) RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30:1312–1313. https://doi.org/10.1093/bioinformatics/btu033

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  36. Rambaut A (2009) FigTree v1.3.1. 2006–2009. Program package available at http://tree.bio.ed.ac. Accessed 29 Nov. 2012

  37. Pipinellis A (2015) GitHub essentials. Packt Publishing Ltd., Birmingham

    Google Scholar 

  38. Glez-Peña D, Gómez-Blanco D, Reboiro-Jato M et al (2010) ALTER: program-oriented conversion of DNA and protein alignments. Nucleic Acids Res 38(Web Server issue):W14–W18. https://doi.org/10.1093/nar/gkq321

    CrossRef  PubMed  PubMed Central  Google Scholar 

  39. Larkin MA, Blackshields G, Brown NP et al (2007) ClustalW and ClustalX version 2.0. Bioinformatics 23:2947–2948. https://doi.org/10.1093/bioinformatics/btm404

    CrossRef  CAS  PubMed  Google Scholar 

  40. Penn O, Privman E, Ashkenazy H et al (2010) GUIDANCE: a web server for assessing alignment confidence scores. Nucleic Acids Res 38(Web Server issue):W23–W28. https://doi.org/10.1093/nar/gkq443

    CrossRef  CAS  PubMed  PubMed Central  Google Scholar 

  41. Chang JM, Di Tommaso P, Notredame C (2014) TCS: a new multiple sequence alignment reliability measure to estimate alignment accuracy and improve phylogenetic tree reconstruction. Mol Biol Evol 31:1625–1637. https://doi.org/10.1093/molbev/msu117

    CrossRef  CAS  PubMed  Google Scholar 

  42. Le SQ, Gascuel O (2008) An improved general amino acid replacement matrix. Mol Biol Evol 25:1307–1320. https://doi.org/10.1093/molbev/msn067

    CrossRef  CAS  PubMed  Google Scholar 

  43. Goldman N, Anderson JP, Rodrigo a G (2000) Likelihood-based tests of topologies in phylogenetics. Syst Biol 49:652–670. https://doi.org/10.1080/106351500750049752

    CrossRef  CAS  PubMed  Google Scholar 

  44. Shimodaira H, Hasegawa M (1999) Multiple comparisons of log-likelihoods with applications to phylogenetic inference. Mol Biol Evol 16:1114–1116. https://doi.org/10.1177/0148607109348061

    CrossRef  CAS  Google Scholar 

Download references

Acknowledgment

This work was supported by the Marie Curie ITN project CALIPSO (GA ITN-2013 607 607), and by the Deutsche Forschungsgesellschaft (EB 285/2-1).

Author information

Authors and Affiliations

  1. Applied Bioinformatics Group, Institute of Cell Biology and Neuroscience, Goethe University Frankfurt, Frankfurt, Germany

    Arpit Jain & Ingo Ebersberger

  2. Department of Ecogenomics and Systems Biology, University of Vienna, Vienna, Austria

    Valentin Roustan & Wolfram Weckwerth

  3. Vienna Metabolomics Center (VIME), University of Vienna, Vienna, Austria

    Wolfram Weckwerth

  4. Senckenberg Biodiversity and Climate Research Centre (BIK-F), Frankfurt, Germany

    Ingo Ebersberger

Authors
  1. Arpit Jain
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Valentin Roustan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wolfram Weckwerth
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ingo Ebersberger
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ingo Ebersberger .

Editor information

Editors and Affiliations

  1. Department of Pathology CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands

    Dietbert Neumann

  2. Department EMD, Inserm, U1016, Institut Cochin, CNRS, UMR8104, Université Paris Descartes, Paris, France

    Benoit Viollet

Rights and permissions

Reprints and Permissions

Copyright information

© 2018 Springer Science+Business Media, LLC

About this protocol

Verify currency and authenticity via CrossMark

Cite this protocol

Jain, A., Roustan, V., Weckwerth, W., Ebersberger, I. (2018). Studying AMPK in an Evolutionary Context. In: Neumann, D., Viollet, B. (eds) AMPK. Methods in Molecular Biology, vol 1732. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7598-3_8

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-7598-3_8

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7597-6

  • Online ISBN: 978-1-4939-7598-3

  • eBook Packages: Springer Protocols