Evidence map›Paper›PMID 28578850›Full record

ArticleCell systems2017

Time-Resolved Proteomics Extends Ribosome Profiling-Based Measurements of Protein Synthesis Dynamics.

Tzu-Yu Liu, Hector H Huang, Diamond Wheeler, Yichen Xu, James A Wells, Yun S Song, Arun P Wiita

Abstract read
In one paragraph

Article in Cell systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Advances in ribosome profiling technologies.Biochemical Society transactions · 2025
    Review
  6. Article
  7. Landscape and regulation of mRNA translation in the earlybioRxiv : the preprint server for biology · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
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  17. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Tzu-Yu LiuComputer Science Division, University of California, Berkeley, Berkeley, CA 94720, USA; Departments of Mathematics and Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Hector H HuangDepartment of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94107, USA.
Diamond WheelerDepartment of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94107, USA; Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA.
Yichen XuDepartment of Urology, University of California, San Francisco, San Francisco, CA 94158, USA.
James A WellsDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA.
Yun S SongComputer Science Division, University of California, Berkeley, Berkeley, CA 94720, USA; Departments of Mathematics and Biology, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Statistics, University of California, Berkeley, Berkeley, CA 94720, USA. Electronic address: yss@berkeley.edu.
Arun P WiitaDepartment of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94107, USA. Electronic address: arun.wiita@ucsf.edu.

Funding

YEAST THREONINE &SERINE KINASESP41RR001614 · NCRR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ORTIZ DE MONTELLANO, PAUL R · 1985 to 2011
$24.1M
Global Assessment of Myeloma Response to ChemotherapyK08CA184116 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WIITA, ARUN P. · 2014 to 2018
$684k
Purchase of Applied Biosystems QTRAP 5500 Mass SpectrometerS10RR026662 · NCRR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BURLINGAME, ALMA L · 2010 to 2010
$500k
NCI NIH HHS K08 CA184116NCRR NIH HHS P41 RR001614NCRR NIH HHS S10 RR026662
6 · The paper itself

Abstract

Ribosome profiling is a widespread tool for studying translational dynamics in human cells. Its central assumption is that ribosome footprint density on a transcript quantitatively reflects protein synthesis. Here, we test this assumption using pulsed-SILAC (pSILAC) high-accuracy targeted proteomics. We focus on multiple myeloma cells exposed to bortezomib, a first-line chemotherapy and proteasome inhibitor. In the absence of drug effects, we found that direct measurement of protein synthesis by pSILAC correlated well with indirect measurement of synthesis from ribosome footprint density. This correlation, however, broke down under bortezomib-induced stress. By developing a statistical model integrating longitudinal proteomic and mRNA-sequencing measurements, we found that proteomics could directly detect global alterations in translational rate caused by bortezomib; these changes are not detectable by ribosomal profiling alone. Further, by incorporating pSILAC data into a gene expression model, we predict cell-stress specific proteome remodeling events. These results demonstrate that pSILAC provides an important complement to ribosome profiling in measuring proteome dynamics.

Indexed as

BortezomibCell Line, TumorGene ExpressionHumansMultiple MyelomaProteasome InhibitorsProtein BiosynthesisProteomeProteomicsRibosomesRNA, MessengerBortezomibProteasome InhibitorsProteomeRNA, Messengermultiple myelomaprotein synthesisproteomicspSILACquantitative modelribosome profilingtranslational efficiencytranslational regulation

Identifiers

PMID28578850
PMCPMC5546878

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.