Evidence map›Paper›PMID 25745177›Full record

ArticleScience (New York, N.Y.)2015

Immunogenetics. Dynamic profiling of the protein life cycle in response to pathogens.

Marko Jovanovic, Michael S Rooney, Philipp Mertins, Dariusz Przybylski, Nicolas Chevrier, Rahul Satija, Edwin H Rodriguez, Alexander P Fields, Schraga Schwartz, Raktima Raychowdhury and 10 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Science (New York, N.Y.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 300 papers.

0numbers the graph read from it
0cells of the map it votes in
300citing papers in PubMed
28.9field-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

300 citing papers in PubMed, 473 citations in OpenAlex.

  1. Estimating protein isoform abundances with [Formula: see text].Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Bacterial stress responses lower mRNA-protein level correlations.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Mass spectrometry proteomics for studying mitostasis.Protein science : a publication of the Protein Society · 2026
    Review
  8. Article
  9. Article
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  11. Age-based approach to characterize the dynamics of cellular processes.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  12. Article
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  19. Review
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240 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors at 4 institutions in 1 country.

Marko JovanovicThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Michael S RooneyThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Philipp MertinsThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Dariusz PrzybylskiThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Nicolas ChevrierThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Harvard Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Cambridge, MA 02138, USA.
Rahul SatijaThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Edwin H RodriguezDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, CA 94158, USA.
Alexander P FieldsDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, CA 94158, USA.
Schraga SchwartzThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Raktima RaychowdhuryThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Maxwell R MumbachThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Thomas EisenhaureThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA 02114, USA.
Michal RabaniThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Dave GennertThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Diana LuThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Toni DeloreyThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Jonathan S WeissmanDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, CA 94158, USA. Howard Hughes Medical Institute (HHMI), University of California, San Francisco, San Francisco, CA 94158, USA.
Steven A CarrThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Nir HacohenThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA 02114, USA. Harvard Medical School, Boston, MA 02115, USA. aregev@broad.mit.edu nhacohen@mgh.harvard.edu.
Aviv RegevThe Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02140, USA. HHMI, Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02140, USA. aregev@broad.mit.edu nhacohen@mgh.harvard.edu.
Broad Institute · USQB3 · USMassachusetts General Hospital · USMassachusetts Institute of Technology · US

Funding

Training Program in Bioinformatics and Integrative GenomicsT32HG002295 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Peter J Park · 2001 to 2026
$15.8M
Center for Cell CircuitsP50HG006193 · NHGRI · BROAD INSTITUTE, INC. · PI REGEV, AVIV · 2011 to 2015
$15.6M
STRUCTURAL BIOLOGY TRAINING PROGRAMT32GM008284 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KORTEMME, TANJA · 1988 to 2022
$10.1M
The chromatin regulatory circuitry of bivalent domainsF32HD075541 · NICHD · BROAD INSTITUTE, INC. · PI SATIJA, RAHUL · 2013 to 2014
$99k
Howard Hughes Medical InstituteNHGRI NIH HHS P50 HG006193NHGRI NIH HHS T32 HG002295NICHD NIH HHS F32 HD075541NIGMS NIH HHS T32 GM008284
6 · The paper itself

Abstract

Protein expression is regulated by the production and degradation of messenger RNAs (mRNAs) and proteins, but their specific relationships remain unknown. We combine measurements of protein production and degradation and mRNA dynamics so as to build a quantitative genomic model of the differential regulation of gene expression in lipopolysaccharide-stimulated mouse dendritic cells. Changes in mRNA abundance play a dominant role in determining most dynamic fold changes in protein levels. Conversely, the preexisting proteome of proteins performing basic cellular functions is remodeled primarily through changes in protein production or degradation, accounting for more than half of the absolute change in protein molecules in the cell. Thus, the proteome is regulated by transcriptional induction for newly activated cellular functions and by protein life-cycle changes for remodeling of preexisting functions.

Indexed as

Molecular Dynamics SimulationProtein BiosynthesisProteolysisAmino AcidsAnimalsBone Marrow CellsCell Culture TechniquesDendritic CellsHost-Pathogen InteractionsIsotope LabelingLipopolysaccharidesMiceMitochondrial ProteinsRNA, MessengerSequence Analysis, RNAAmino AcidsLipopolysaccharidesMitochondrial ProteinsRNA, Messenger

Identifiers

PMID25745177
PMCPMC4506746
OpenAlexW2079279399

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.