Evidence map›Paper›PMID 24974296›Full record

ArticleMethods in enzymology2014

Global analysis of cellular proteolysis by selective enzymatic labeling of protein N-termini.

Arun P Wiita, Julia E Seaman, James A Wells

Abstract read
In one paragraph

Article in Methods in enzymology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
18.2field-weighted citation impact, top 1% of its field
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

17 citing papers in PubMed, 39 citations in OpenAlex.

  1. Caspase-mediated cleavage events hidden by secondary proteolysis during apoptosis.Protein science : a publication of the Protein Society · 2026
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  7. Deep profiling of protease substrate specificity enabled by dual random and scanned human proteome substrate phage libraries.Proceedings of the National Academy of Sciences of the United States of America · 2020
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  17. Circulating proteolytic signatures of chemotherapy-induced cell death in humans discovered by N-terminal labeling.Proceedings of the National Academy of Sciences of the United States of America · 2014
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Arun P WiitaDepartment of Pharmaceutical Chemistry, University of California, San Francisco, California, USA; Department of Laboratory Medicine, University of California, San Francisco, California, USA.
Julia E SeamanDepartment of Pharmaceutical Chemistry, University of California, San Francisco, California, USA.
James A WellsDepartment of Pharmaceutical Chemistry, University of California, San Francisco, California, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California, USA. Electronic address: jim.wells@ucsf.edu.
University of California, San Francisco · US

Funding

YEAST THREONINE &SERINE KINASESP41RR001614 · NCRR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JULIUS, DAVID · 1985 to 2011
$24.1M
PHARMACEUTICAL SCIENCES AND PHARMACOGENOMICST32GM007175 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI AHITUV, NADAV, KROETZ, DEANNA L · 1985 to 2021
$7.1M
Bio-Organic Biomedical Mass Spectromy ResourceP41GM103481 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BURLINGAME, ALMA L · 2012 to 2015
$6.4M
Global Analysis of Proteolysis in ApoptosisR01GM081051 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WELLS, JAMES A · 2007 to 2015
$2.8M
Approaches to discover and quantify apoptotic biomarkers for cancer treatmentR01CA154802 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WELLS, JAMES A · 2011 to 2014
$1.3M
Regulating Proteolysis to Dissect ApoptosisR01GM097316 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WELLS, JAMES A · 2011 to 2014
$1.1M
PURCHASE OF MICRO LC/NANO ESIQQTOF MASS SPECTROMETERS10RR015804 · NCRR · UNIVERSITY OF CALIFORNIA SAN FRANCISCO · PI BURLINGAME, ALMA L · 2001 to 2001
$500k
NCI NIH HHS R01 CA154802NCRR NIH HHS 1S10RR015804NCRR NIH HHS 5P41RR001614NCRR NIH HHS P41 RR001614NCRR NIH HHS S10 RR015804NIGMS NIH HHS 8P41GM103481NIGMS NIH HHS P41 GM103481NIGMS NIH HHS R01 GM081051NIGMS NIH HHS R01 GM097316NIGMS NIH HHS T32 GM007175
6 · The paper itself

Abstract

Proteolysis is a critical modification leading to alteration of protein function with important outcomes in many biological processes. However, for the majority of proteases, we have an incomplete understanding of both cellular substrates and downstream effects. Here, we describe detailed protocols and applications for using the rationally engineered peptide ligase, subtiligase, to specifically label and capture protein N-termini generated by proteases either induced or added to complex biological samples. This method allows identification of the protein targets as well as their precise cleavage locations. This approach has revealed >8000 proteolytic sites in healthy and apoptotic cells including >1700 caspase cleavages. One can further determine substrate preferences through rate analysis with quantitative mass spectrometry, physiological substrate specificities, and even infer the identity of proteases operating in the cell. In this chapter, we also describe how this experimental method can be generalized to investigate proteolysis in any biological sample.

Indexed as

ProteolysisAmino Acid SequenceAnimalsApoptosisHumansMass SpectrometryPeptide HydrolasesPeptide SynthasesProteinsProteomicsRecombinant ProteinsStaining and LabelingSubstrate SpecificitySubtilisinsPeptide HydrolasesPeptide SynthasesProteinsRecombinant ProteinssubtiligaseSubtilisinsApoptosisCaspaseDegradomicsMass spectrometryProteolysisProteomicsSelected reaction monitoringSubtiligase

Identifiers

PMID24974296
PMCPMC4260929
OpenAlexW299538889

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.