A large dataset of protein dynamics in the mammalian heart proteome

Lau, Edward; Cao, Qi; Ng, Dominic C. M.; Bleakley, Brian J.; Dinçer, Tuba; Bot, Brian M.; Wang, Ding; Liem, David A.; Lam, Maggie P. Y.; Ge, Junbo; Ping, Peipei

doi:10.1038/sdata.2016.15

Cited by 72 publications

(144 citation statements)

References 70 publications

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“…Inside the cell, BiP is enriched in the ER, though it may also localize to the mitochondria- associated ER membrane (MAM) and cell surface. The half-life of BiP greatly varies across species and tissue type, ranging from a few hours to 15 days (Figure 1A-B) (Lau et al, 2016). Such a broad range for BiP’s half- life can be attributed to the distinct genetic background and epigenetic, transcriptional, and translational regulation.…”

Section: The Half-life Of Bip In Different Speciesmentioning

confidence: 99%

“…As an example, the half-life of yeast BiP is longer than 85% of all proteins in the proteome (Figure 1A) (Belle et al, 2006). Meanwhile, BiP in other species, such as rodent species, is relatively short-lived, with a consistently longer half-life than only 30% of proteins in each proteome (Figure 1A) (Price et al, 2010; Kim et al, 2012; Lau et al, 2016). Even within the same species and tissue type, BiP’s half-life can fluctuate from 3.6 to 4.6 days (statistically significant by t-test) in different genetic strains, indicating that genetic variation may also regulate half-life length (Figure 1D).…”

Section: The Half-life Of Bip In Different Speciesmentioning

confidence: 99%

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HSPA5 Gene encoding Hsp70 chaperone BiP in the endoplasmic reticulum

Wang

Lee

Liem

et al. 2017

Gene

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The HSPA5 gene (Ensembl ID: ENSG00000044574 (WTSI/EMBL-EBI, 2015)) encodes the binding immunoglobulin protein (BiP), an Hsp70 family chaperone localized in the ER lumen. As a highly conserved molecular chaperone, BiP assists in a wide range of folding processes via its two structural domains, a nucleotide-binding domain (NBD) and substrate-binding domain (SBD). BiP is also an essential component of the translocation machinery for protein import into the ER, a regulator for Ca2+ homeostasis in the ER, as well as a facilitator of ER-associated protein degradation (ERAD) via retrograde transportation of aberrant proteins across the ER membrane. When unfolded/misfolded proteins in the ER overwhelm the capacity of protein folding machinery, BiP can initiate the unfolded protein response (UPR), decrease unfolded/misfolded protein load, induce autophagy, and crosstalk with apoptosis machinery to assist in the cell survival decision. Post- translational modifications (PTMs) of BiP have been shown to regulate BiP’s activity, turnover, and availability upon different extrinsic or intrinsic stimuli. As a master regulator of ER function, BiP is associated with cancer, cardiovascular disease, neurodegenerative disease, and immunological diseases. BiP has been targeted in cancer therapies and shows promise for application in other relevant diseases.

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Section: The Half-life Of Bip In Different Speciesmentioning

confidence: 99%

Section: The Half-life Of Bip In Different Speciesmentioning

confidence: 99%

HSPA5 Gene encoding Hsp70 chaperone BiP in the endoplasmic reticulum

Wang

Lee

Liem

et al. 2017

Gene

Self Cite

193

180

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“…The in vivo experiment used Nitrogen-15 ( 15 N) isotope labeling in the murine brain and liver study[7] and heavy water labeling in the heart[12] study. The cell lines studies used stable isotope labeling with amino acids in cell cultures (SILAC)[14].…”

Section: Datamentioning

confidence: 99%

Predicting the protein half-life in tissue from its cellular properties

Rahman

Sadygov

2017

PLoS ONE

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Protein half-life is an important feature of protein homeostasis (proteostasis). The increasing number of in vivo and in vitro studies using high throughput proteomics provide estimates of the protein half-lives in tissues and cells. However, protein half-lives in cells and tissues are different. Due to the resource requirements for researching tissues, more data is available from cellular studies than tissues. We have designed a multivariate linear model for predicting protein half-life in tissue from its cellular properties. Inputs to the model are cellular half-life, abundance, intrinsically disordered sequences, and transcriptional and translational rates. Before the modeling, we determined substructures in the data using the relative distance from the regression line of the protein half-lives in tissues and cells, identifying three separate clusters. The model was trained on and applied to predict protein half-lives from murine liver, brain and heart tissues. In each tissue type we observed similar prediction patterns of protein half-lives. We found that the model provides the best results when there is a strong correlation between tissue and cell culture protein half-lives. Additionally, we clustered the protein half-lives to determine variations in correlation coefficients between the protein half-lives in the tissue versus in cell culture. The clusters identify strongly and weakly correlated protein half-lives, further improves the overall prediction and identifies sub groupings which exhibit specific characteristics. The model described herein, is generalizable to other data sets and has been implemented in a freely available R code.

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“…With recent advances, proteomics studies can measure turnover dynamics of thousands of proteins in multiple tissues and organisms (67,68). Combining stable isotope labeling, mathematical modeling, and shotgun proteomics, recent investigations into the turnover of ~5,000 cardiac proteins in mouse cardiac hypertrophy (69,70) revealed novel correlations between proteome profiles and phenotypic functional limitations. For example, although the hypertrophic heart is known to switch in fuel preference from fatty acid to glucose, the expression of glycolytic proteins does not change accordingly (71).…”

Section: Multidimensional Protein Parameters In Disease Mechanism Resmentioning

confidence: 99%

Proteomics Research in Cardiovascular Medicine and Biomarker Discovery

Lam

Ping

Murphy

2016

Journal of the American College of Cardiology

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Proteomics is a systems physiology discipline to address the large-scale characterization of protein species within a biological system, be it a cell, a tissue, a body biofluid, an organism, or a cohort population. Building on advances from chemical analytical platforms (e.g., mass spectrometry and other technologies), proteomics approaches have contributed powerful applications in cardiovascular biomedicine, most notably in: 1) the discovery of circulating protein biomarkers of heart diseases from plasma samples; and 2) the identification of disease mechanisms and potential therapeutic targets in cardiovascular tissues, in both preclinical models and translational studies. Contemporary proteomics investigations offer powerful means to simultaneously examine tens of thousands of proteins in various samples, and understand their molecular phenotypes in health and disease. This concise review introduces study design considerations, example applications and use cases, as well as interpretation and analysis of proteomics data in cardiovascular biomedicine.

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A large dataset of protein dynamics in the mammalian heart proteome

Cited by 72 publications

References 70 publications

HSPA5 Gene encoding Hsp70 chaperone BiP in the endoplasmic reticulum

HSPA5 Gene encoding Hsp70 chaperone BiP in the endoplasmic reticulum

Predicting the protein half-life in tissue from its cellular properties

Proteomics Research in Cardiovascular Medicine and Biomarker Discovery

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