Determining and interpreting protein lifetimes in mammalian tissues

Fornasiero, Eugenio F.; Savas, Jeffrey N.

doi:10.1016/j.tibs.2022.08.011

Cited by 21 publications

(13 citation statements)

References 67 publications

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“…To calculate the half-life the median amplitude values from each cell were normalized between 0 and 1 to standardize the values and allow analysis of all cells together. Nonlinear Least Squares (NLS) function was used to fit all the representative values according to equation 1 for protein degradation, in exponential decay model, and equation 2 for protein synthesis, in 1 minus exponential decay model 44 . …”

Section: Methodsmentioning

confidence: 99%

Imaging of existing and newly translated proteins elucidates mechanisms of sarcomere turnover

Douvdevany,

Erlich,

Haimovich-Caspi

et al. 2023

Preprint

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How the sarcomeric complex is continuously turned-over in long-living cardiomyocytes is unclear. Here, we imaged the exchange of old and new Halo-tagged sarcomeric proteins. We disprove the prevailing ‘protein pool’ model and instead show an ordered mechanism in which only newly translated proteins enter the sarcomeric complex while older ones are removed and degraded. We also show that degradation is independent of protein age, and that proteolytic extraction is a rate limiting step in the turnover. We imaged and quantified the turnover of expressed and endogenous sarcomeric proteins, including the giant protein titin, in cardiomyocytes in culture and in vivo, at the single cell and at the single sarcomere level. We show that replacement occurs at a similar rate within cells and across the heart and is markedly slower in adult cells. Our findings imply a new model of sarcomere turnover and sarcomeric subunit replacement.

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Section: Methodsmentioning

confidence: 99%

Imaging of existing and newly translated proteins elucidates mechanisms of sarcomere turnover

Douvdevany,

Erlich,

Haimovich-Caspi

et al. 2023

Preprint

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“…The equilibria are tissue-specific, and they shift during organismal development, aging, and diseases. Metabolic stable isotope labeling followed by liquid chromatography and mass spectrometry (LC-MS) has been a powerful tool to study in vivo protein turnover on a large scale and high throughput [ 1 , 2 ]. As a labeling agent, heavy water (drinking water enriched in D 2 O) is easy to use, cost-efficient, and does not require adaptation period [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Software Tool for Visualization and Validation of Protein Turnover Rates Using Heavy Water Metabolic Labeling and LC-MS

Deberneh

Sadygov

2022

IJMS

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Metabolic stable isotope labeling followed by liquid chromatography coupled with mass spectrometry (LC-MS) is a powerful tool for in vivo protein turnover studies of individual proteins on a large scale and with high throughput. Turnover rates of thousands of proteins from dozens of time course experiments are determined by data processing tools, which are essential components of the workflows for automated extraction of turnover rates. The development of sophisticated algorithms for estimating protein turnover has been emphasized. However, the visualization and annotation of the time series data are no less important. The visualization tools help to validate the quality of the model fits, their goodness-of-fit characteristics, mass spectral features of peptides, and consistency of peptide identifications, among others. Here, we describe a graphical user interface (GUI) to visualize the results from the protein turnover analysis tool, d2ome, which determines protein turnover rates from metabolic D2O labeling followed by LC-MS. We emphasize the specific features of the time series data and their visualization in the GUI. The time series data visualized by the GUI can be saved in JPEG format for storage and further dissemination.

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“…The dependence on antibody-based quantification limits the throughput of the method. A comprehensive review of the techniques used for protein turnover studies can be found elsewhere [25][26][27] .…”

mentioning

confidence: 99%

Quantifying label enrichment from two mass isotopomers increases proteome coverage for in vivo protein turnover using heavy water metabolic labeling

et al. 2023

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Heavy water metabolic labeling followed by liquid chromatography coupled with mass spectrometry is a powerful high throughput technique for measuring the turnover rates of individual proteins in vivo. The turnover rate is obtained from the exponential decay modeling of the depletion of the monoisotopic relative isotope abundance. We provide theoretical formulas for the time course dynamics of six mass isotopomers and use the formulas to introduce a method that utilizes partial isotope profiles, only two mass isotopomers, to compute protein turnover rate. The use of partial isotope profiles alleviates the interferences from co-eluting contaminants in complex proteome mixtures and improves the accuracy of the estimation of label enrichment. In five different datasets, the technique consistently doubles the number of peptides with high goodness-of-fit characteristics of the turnover rate model. We also introduce a software tool, d2ome+, which automates the protein turnover estimation from partial isotope profiles.

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Determining and interpreting protein lifetimes in mammalian tissues

Cited by 21 publications

References 67 publications

Imaging of existing and newly translated proteins elucidates mechanisms of sarcomere turnover

Imaging of existing and newly translated proteins elucidates mechanisms of sarcomere turnover

Software Tool for Visualization and Validation of Protein Turnover Rates Using Heavy Water Metabolic Labeling and LC-MS

Quantifying label enrichment from two mass isotopomers increases proteome coverage for in vivo protein turnover using heavy water metabolic labeling

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