Europe PMC

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Abstract 


Motivation

Using mass spectrometry to measure the concentration and turnover of the individual proteins in a proteome, enables the calculation of individual synthesis and degradation rates for each protein. Software to analyze concentration is readily available, but software to analyze turnover is lacking. Data analysis workflows typically don't access the full breadth of information about instrument precision and accuracy that is present in each peptide isotopic envelope measurement. This method utilizes both isotope distribution and changes in neutromer spacing, which benefits the analysis of both concentration and turnover.

Results

We have developed a data analysis tool, DeuteRater, to measure protein turnover from metabolic D 2 O labeling. DeuteRater uses theoretical predictions for label-dependent change in isotope abundance and inter-peak (neutromer) spacing within the isotope envelope to calculate protein turnover rate. We have also used these metrics to evaluate the accuracy and precision of peptide measurements and thereby determined the optimal data acquisition parameters of different instruments, as well as the effect of data processing steps. We show that these combined measurements can be used to remove noise and increase confidence in the protein turnover measurement for each protein.

Availability and implementation

Source code and ReadMe for Python 2 and 3 versions of DeuteRater are available at https://github.com/JC-Price/DeuteRater . Data is at https://chorusproject.org/pages/index.html project number 1147. Critical Intermediate calculation files provided as Tables S3 and S4. Software has only been tested on Windows machines.

Contact

[email protected].

Supplementary information

Supplementary data are available at Bioinformatics online.

Citations & impact 


Impact metrics

Jump to Citations

Citations of article over time

Alternative metrics

Altmetric item for https://www.altmetric.com/details/15559193
Altmetric
Discover the attention surrounding your research
https://www.altmetric.com/details/15559193

Smart citations by scite.ai
Smart citations by scite.ai include citation statements extracted from the full text of the citing article. The number of the statements may be higher than the number of citations provided by EuropePMC if one paper cites another multiple times or lower if scite has not yet processed some of the citing articles.
Explore citation contexts and check if this article has been supported or disputed.
https://scite.ai/reports/10.1093/bioinformatics/btx009

Supporting
Mentioning
Contrasting
1
70
0

Article citations


Go to all (30) article citations

Funding 


Funders who supported this work.

BN, BYU Undergraduate Research Awards

    JCP, Roland K. Robins Graduate Research Fellowship