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Proteomics Approaches to Assess Sleep and Circadian Rhythms

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Circadian Clocks

Part of the book series: Neuromethods ((NM,volume 186))

Abstract

Mass spectrometry-based quantitative proteomics have greatly benefited from recent technological and computational improvements, allowing quantification of proteomes at continually increasing depth. From a growing number of quantitative proteomic studies in the circadian field in the last years, it has become evident that protein cycles differ significantly from transcript rhythmicity and protein abundance cannot be generally extrapolated from transcriptomic investigations. As proteins are the functional entities of cellular processes, our understanding of rhythmic biology relies thus on the investigation of protein abundance and its post-translational modification state, as proxy of their activity. In this chapter, we present a robust and simple method to prepare and quantitatively measure proteomes and phosphoproteomes in a highly parallelizable manner. We further discuss key factors to be considered when designing time course experiments and during data analysis with the aim to accurately identify circadian and sleep-driven oscillations in proteome and phosphoproteome.

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References

  1. Atger F, Gobet C, Marquis J et al (2015) Circadian and feeding rhythms differentially affect rhythmic mRNA transcription and translation in mouse liver. Proc Natl Acad Sci U S A 112(47):E6579–E6588

    Article  CAS  Google Scholar 

  2. Hughes ME, DiTacchio L, Hayes KR et al (2009) Harmonics of circadian gene transcription in mammals. PLoS Genet 5(4):e1000442

    Article  Google Scholar 

  3. Koike N, Yoo S-H, Huang H-C et al (2012) Transcriptional architecture and chromatin landscape of the core circadian clock in mammals. Science 338(6105):349–354

    Article  CAS  Google Scholar 

  4. Panda S, Antoch MP, Miller BH et al (2002) Coordinated transcription of key pathways in the mouse by the circadian clock. Cell 109(3):307–320

    Article  CAS  Google Scholar 

  5. Storch K-F, Lipan O, Leykin I et al (2002) Extensive and divergent circadian gene expression in liver and heart. Nature 417(6884):78–83

    Article  CAS  Google Scholar 

  6. Ueda HR, Chen W, Adachi A et al (2002) A transcription factor response element for gene expression during circadian night. Nature 418(6897):534–539

    Article  CAS  Google Scholar 

  7. Robles MS, Cox J, Mann M (2014) In-vivo quantitative proteomics reveals a key contribution of post-transcriptional mechanisms to the circadian regulation of liver metabolism. PLoS Genet 10(1):e1004047

    Article  Google Scholar 

  8. Mauvoisin D, Wang J, Jouffe C et al (2014) Circadian clock-dependent and -independent rhythmic proteomes implement distinct diurnal functions in mouse liver. Proc Natl Acad Sci U S A 111(1):167–172

    Article  CAS  Google Scholar 

  9. Ardito F, Giuliani M, Perrone D et al (2017) The crucial role of protein phosphorylation in cell signaling and its use as targeted therapy (Review). Int J Mol Med 40(2):271–280

    Article  CAS  Google Scholar 

  10. Purves D, Augustine GJ, Fitzpatrick D et al (2001) Second messenger targets: protein kinases and phosphatases. 2nd edition. Neuroscience. Sinauer Associates, Sunderland

    Google Scholar 

  11. Funato H, Miyoshi C, Fujiyama T et al (2016) Forward-genetics analysis of sleep in randomly mutagenized mice. Nature 539(7629):378–383

    Article  CAS  Google Scholar 

  12. Tatsuki F, Sunagawa GA, Shi S et al (2016) Involvement of Ca(2+)-dependent hyperpolarization in sleep duration in mammals. Neuron 90(1):70–85

    Article  CAS  Google Scholar 

  13. Mikhail C, Vaucher A, Jimenez S et al (2017) ERK signaling pathway regulates sleep duration through activity-induced gene expression during wakefulness. Sci Signal 10(463):eaai9219

    Article  Google Scholar 

  14. Hein MY, Sharma K, Cox J et al (2013) Proteomic analysis of cellular systems. In: Walhout M, Vidal M, Dekker J (eds) Handbook of systems biology: concepts and insights. Academic Press, New York, pp 3–25

    Chapter  Google Scholar 

  15. Schubert OT, Röst HL, Collins BC et al (2017) Quantitative proteomics: challenges and opportunities in basic and applied research. Nat Protoc 12(7):1289–1294

    Article  CAS  Google Scholar 

  16. Hughes ME, Abruzzi KC, Allada R et al (2017) Guidelines for genome-scale analysis of biological rhythms. J Biol Rhythms 32(5):380–393

    Article  CAS  Google Scholar 

  17. Mauvoisin D, Atger F, Dayon L et al (2017) Circadian and feeding rhythms orchestrate the diurnal liver acetylome. Cell Rep 20(7):1729–1743

    Article  CAS  Google Scholar 

  18. Ray S, Valekunja UK, Stangherlin A et al (2020) Circadian rhythms in the absence of the clock gene Bmal1. Science 367(6479):800–806

    Article  CAS  Google Scholar 

  19. Borbély AA (1982) A two process model of sleep regulation. Hum Neurobiol 1(3):195–204

    PubMed  Google Scholar 

  20. Borbély AA, Daan S, Wirz-Justice A et al (2016) The two-process model of sleep regulation: a reappraisal. J Sleep Res 25(2):131–143

    Article  Google Scholar 

  21. Noya SB, Colameo D, Brüning F et al (2019) The forebrain synaptic transcriptome is organized by clocks but its proteome is driven by sleep. Science 366(6462):eaav2642

    Article  CAS  Google Scholar 

  22. Brüning F, Noya SB, Bange T et al (2019) Sleep-wake cycles drive daily dynamics of synaptic phosphorylation. Science 366(6462):eaav3617

    Article  Google Scholar 

  23. Humphrey SJ, Karayel O, James DE et al (2018) High-throughput and high-sensitivity phosphoproteomics with the EasyPhos platform. Nat Protoc 13(9):1897–1916

    Article  CAS  Google Scholar 

  24. Humphrey SJ, Azimifar SB, Mann M (2015) High-throughput phosphoproteomics reveals in vivo insulin signaling dynamics. Nat Biotechnol 33(9):990–995

    Article  CAS  Google Scholar 

  25. Robles MS, Humphrey SJ, Mann M (2017) Phosphorylation is a central mechanism for circadian control of metabolism and physiology. Cell Metab 25(1):118–127

    Article  CAS  Google Scholar 

  26. Rappsilber J, Mann M, Ishihama Y (2007) Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat Protoc 2(8):1896–1906

    Article  CAS  Google Scholar 

  27. Tyanova S, Temu T, Cox J (2016) The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat Protoc 11(12):2301–2319

    Article  CAS  Google Scholar 

  28. Tyanova S, Temu T, Sinitcyn P et al (2016) The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat Methods 13(9):731–740

    Article  CAS  Google Scholar 

  29. Wiśniewski JR (2013) Proteomic sample preparation from formalin fixed and paraffin embedded tissue. J Vis Exp 79:50589

    Google Scholar 

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Authors and Affiliations

  1. Institute of Medical Psychology and Biomedical Center (BMC), Faculty of Medicine, LMU Munich, Munich, Germany

    Fabian P. Kliem, Franziska Brüning & Maria S. Robles

Authors
  1. Fabian P. Kliem
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  2. Franziska Brüning
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  3. Maria S. Robles
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Corresponding author

Correspondence to Maria S. Robles .

Editor information

Editors and Affiliations

  1. Institute of Transformative Bio-Molecules, Nagoya University, Nagoya, Aichi, Japan

    Tsuyoshi Hirota

  2. Institute of Transformative Bio-Molecules, Nagoya University, Nagoya, Aichi, Japan

    Megumi Hatori

  3. Regulatory Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA

    Satchidananda Panda

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© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Kliem, F.P., Brüning, F., Robles, M.S. (2022). Proteomics Approaches to Assess Sleep and Circadian Rhythms. In: Hirota, T., Hatori, M., Panda, S. (eds) Circadian Clocks. Neuromethods, vol 186. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2577-4_15

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  • DOI: https://doi.org/10.1007/978-1-0716-2577-4_15

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2576-7

  • Online ISBN: 978-1-0716-2577-4

  • eBook Packages: Springer Protocols

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