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Related Concept Videos

Phosphorylation01:02

Phosphorylation

54.6K
The addition or removal of phosphate groups from proteins is the most common chemical modification that regulates cellular processes. These modifications can affect the structure, activity, stability, and localization of proteins within cells as well as their interactions with other proteins.
During phosphorylation, protein kinases transfer the terminal phosphate group of ATP to specific amino acid side chains of substrate proteins. Serine, threonine, and tyrosine are the most commonly...
54.6K

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Metabolic Labeling of Leucine Rich Repeat Kinases 1 and 2 with Radioactive Phosphate
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Improved Method for Determining Absolute Phosphorylation Stoichiometry Using Bayesian Statistics and Isobaric

Matthew Y Lim1, Jonathon O'Brien1, Joao A Paulo1

  • 1Department of Cell Biology, Harvard Medical School , Boston, Massachusetts 02115, United States.

Journal of Proteome Research
|October 7, 2017
PubMed
Summary
This summary is machine-generated.

This study enhances phosphoproteomics by improving phosphorylation stoichiometry measurements using TMT labeling and a Bayesian model. The new method provides accurate, absolute stoichiometry for thousands of phosphopeptides, overcoming previous limitations.

Keywords:
Bayesian modelingSPS-MS3TMTerror intervalsglobal proteomehuman cell linesmass spectrometryphosphatasephosphorylationstoichiometry

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Area of Science:

  • Biochemistry
  • Proteomics
  • Molecular Biology

Background:

  • Phosphorylation stoichiometry provides crucial biological context in phosphoproteomics.
  • Previous methods for large-scale stoichiometry assessment suffered from measurement errors leading to inaccurate negative values for low-occupancy phosphopeptides.

Purpose of the Study:

  • To develop an improved method for accurate, large-scale determination of phosphorylation stoichiometry.
  • To overcome limitations of previous methods, particularly for low stoichiometry phosphopeptides.
  • To report absolute stoichiometry measurements with credible intervals for a significant number of phosphopeptides.

Main Methods:

  • Utilized isobaric labeling with 10-plex TMT reagents for simultaneous comparison of phosphatase-treated and untreated samples.
  • Implemented a Bayesian model within an R/Stan script to estimate stoichiometry as a parameter bounded between 0 and 1.
  • Applied the method to HCT116 cells, analyzing five biological replicates without phosphopeptide enrichment.

Main Results:

  • Achieved accurate stoichiometry measurements without missing values, overcoming issues with negative stoichiometry calculations.
  • Reported absolute stoichiometry measurements with credible intervals for 6772 phosphopeptides.
  • Demonstrated consistency between point and interval estimates with plausible stoichiometry values.

Conclusions:

  • The improved method using TMT labeling and Bayesian modeling offers a robust approach for accurate phosphopeptide stoichiometry determination.
  • This advancement enables more reliable quantitative phosphoproteomics and deeper biological insights.
  • The study provides a valuable dataset of absolute phosphorylation stoichiometries for HCT116 cells.