Evidence map›Paper›PMID 23935119›Full record

ArticleNucleic acids research2013

Genome-wide single-cell-level screen for protein abundance and localization changes in response to DNA damage in S. cerevisiae.

Aprotim Mazumder, Laia Quiros Pesudo, Siobhan McRee, Mark Bathe, Leona D Samson

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

23 citing papers in PubMed, 45 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Incorporation of a unified protein abundance dataset into the Saccharomyces genome database.Database : the journal of biological databases and curation · 2020
    Article
  6. Article
  7. Review
  8. Spatial proteomics: a powerful discovery tool for cell biology.Nature reviews. Molecular cell biology · 2019
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.Integrative biology : quantitative biosciences from nano to macro · 2016
    Article
  20. 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

5 authors at 3 institutions in 1 country.

Aprotim MazumderDepartment of Biological Engineering, Center for Environmental Health Sciences, Laboratory for Computational Biology and Biophysics, Department of Biology and The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Laia Quiros Pesudo
Siobhan McRee
Mark Bathe
Leona D Samson
Center for Environmental Health · USMassachusetts Institute of Technology · USCenter for Cancer Research · US

Funding

VIRUS PRODUCTION COREP30CA014051 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI MATTHEW G. VANDER HEIDEN · 1985 to 2026
$93.9M
Tumor Cell Networks CenterU54CA112967 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LAUFFENBURGER, DOUGLAS A · 2004 to 2015
$26.2M
TOXICOLOGY CORE UNITP30ES002109 · NIEHS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LEVINE, STUART S · 1985 to 2020
$25.6M
EUKARYTIC DNA ALKYLATION REPAIRR01CA055042 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI SAMSON, LEONA D. · 1991 to 2010
$4.8M
Eukaryotic DNA Alkylation RepairR01ES022872 · NIEHS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI SAMSON, LEONA D. · 2013 to 2017
$1.7M
NCI NIH HHS P30 CA014051NCI NIH HHS P30-CA14051NCI NIH HHS R01 CA055042NCI NIH HHS R01-CA055042NCI NIH HHS U54 CA112967NCI NIH HHS U54-CA112967NIEHS NIH HHS P30 ES002109NIEHS NIH HHS P30-ES002109NIEHS NIH HHS R01 ES022872NIEHS NIH HHS R01-ES022872
6 · The paper itself

Abstract

An effective response to DNA damaging agents involves modulating numerous facets of cellular homeostasis in addition to DNA repair and cell-cycle checkpoint pathways. Fluorescence microscopy-based imaging offers the opportunity to simultaneously interrogate changes in both protein level and subcellular localization in response to DNA damaging agents at the single-cell level. We report here results from screening the yeast Green Fluorescent Protein (GFP)-fusion library to investigate global cellular protein reorganization on exposure to the alkylating agent methyl methanesulfonate (MMS). Broad groups of induced, repressed, nucleus- and cytoplasm-enriched proteins were identified. Gene Ontology and interactome analyses revealed the underlying cellular processes. Transcription factor (TF) analysis identified principal regulators of the response, and targets of all major stress-responsive TFs were enriched amongst the induced proteins. An unexpected partitioning of biological function according to the number of TFs targeting individual genes was revealed. Finally, differential modulation of ribosomal proteins depending on methyl methanesulfonate dose was shown to correlate with cell growth and with the translocation of the Sfp1 TF. We conclude that cellular responses can navigate different routes according to the extent of damage, relying on both expression and localization changes of specific proteins.

Indexed as

DNA DamageDNA RepairChromatin Assembly and DisassemblyCytoplasmGene Expression Regulation, FungalGene Regulatory NetworksGenome, FungalLipidsMethyl MethanesulfonateNuclear ProteinsProtein BiosynthesisProteolysisRibosomal ProteinsRibosomesSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsLipidsMethyl MethanesulfonateNuclear ProteinsRibosomal ProteinsSaccharomyces cerevisiae ProteinsTranscription Factors

Identifiers

PMID23935119
PMCPMC3814357
OpenAlexW2102105090

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.