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Xenopus pp 175-194 | Cite as

Quantitative Proteomics of Xenopus Embryos I, Sample Preparation

  • Meera Gupta
  • Matthew Sonnett
  • Lillia Ryazanova
  • Marc Presler
  • Martin WührEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1865)

Abstract

Xenopus oocytes and embryos are model systems optimally suited for quantitative proteomics. This is due to the availability of large amount of protein material and the ease of physical manipulation. Furthermore, facile in vitro fertilization provides superbly synchronized embryos for cell cycle and developmental stages. Here, we detail protocols developed over the last few years for sample preparation of multiplexed proteomics with TMT-tags followed by quantitative mass spectrometry analysis using the MultiNotch MS3 approach. In this approach, each condition is barcoded with an isobaric tag at the peptide level. After barcoding, samples are combined and the relative abundance of ~100,000 peptides is quantified on a mass spectrometer. High reproducibility of the sample preparation process prior to peptides being tagged and combined is of upmost importance for obtaining unbiased data. Otherwise, differences in sample handling can inadvertently appear as biological changes. We detail and exemplify the application of our sample workflow on an embryonic time-series of ten developmental stages of Xenopus laevis embryos ranging from the egg to stage 35 (just before hatching). Our accompanying paper (Chapter  14) details a bioinformatics pipeline to analyze the quality of the given sample preparation and strategies to convert spectra of X. laevis peptides into biologically interpretable data.

Key words

Proteomics Xenopus laevis Development Sample preparation Multiplexing Mass spectrometry Yolk TMT Protein dynamics 

Notes

Acknowledgments

We thank Thao Nguyen for help collecting the Xenopus embryonic time series and Felix Keber for comments and suggestions on the manuscript. M.P. was supported by NIH grant R01GM103785. M.S. was supported by NIH F31 predoctoral fellowship 5F31GM116451. This work was supported by NIH grant 1R35GM128813 and Princeton University startup funding.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Meera Gupta
    • 1
    • 2
  • Matthew Sonnett
    • 1
  • Lillia Ryazanova
    • 1
  • Marc Presler
    • 3
  • Martin Wühr
    • 1
    Email author
  1. 1.Department of Molecular Biology and Lewis-Sigler Institute for Integrative GenomicsPrinceton UniversityPrincetonUSA
  2. 2.Department of Chemical and Biological EngineeringPrinceton UniversityPrincetonUSA
  3. 3.Department of Systems BiologyHarvard Medical SchoolBostonUSA

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