Evidence map›Paper›PMID 26552604›Full record

ArticleProteomics2016

Micro-proteomics with iterative data analysis: Proteome analysis in C. elegans at the single worm level.

Dalila Bensaddek, Vikram Narayan, Armel Nicolas, Alejandro Brenes Murillo, Anton Gartner, Cynthia J Kenyon, Angus I Lamond

Open access · hybridAbstract read
In one paragraph

Article in Proteomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

24 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Single-tissue proteomics inProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Exposome, Molecular Pathways and One Health: The InvertebrateInternational journal of molecular sciences · 2022
    Review
  11. Article
  12. Article
  13. Article
  14. Quo VadisMetabolites · 2021
    Review
  15. Article
  16. Article
  17. Article
  18. Measuring and modeling interventions in aging.Current opinion in cell biology · 2018
    Review
  19. Review
  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

7 authors at 2 institutions in 2 countries.

Dalila BensaddekCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow Street, Dundee, United Kingdom.
Vikram NarayanCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow Street, Dundee, United Kingdom.
Armel NicolasCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow Street, Dundee, United Kingdom.
Alejandro Brenes MurilloCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow Street, Dundee, United Kingdom.
Anton GartnerCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow Street, Dundee, United Kingdom.
Cynthia J KenyonDepartment of Biochemistry and Biophysics, Genentech Hall, University of California, San Francisco, CA, USA.
Angus I LamondCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow Street, Dundee, United Kingdom.
University of Dundee · GBUniversity of California, San Francisco · US

Funding

Biotechnology and Biological Sciences Research Council BB/K003801/1Wellcome Trust 073980Wellcome Trust 073980/Z/03/BWellcome Trust 090944Wellcome Trust 0909444/Z/09/ZWellcome Trust 097945Wellcome Trust 097945/B/11/Z
6 · The paper itself

Abstract

Proteomics studies typically analyze proteins at a population level, using extracts prepared from tens of thousands to millions of cells. The resulting measurements correspond to average values across the cell population and can mask considerable variation in protein expression and function between individual cells or organisms. Here, we report the development of micro-proteomics for the analysis of Caenorhabditis elegans, a eukaryote composed of 959 somatic cells and ∼1500 germ cells, measuring the worm proteome at a single organism level to a depth of ∼3000 proteins. This includes detection of proteins across a wide dynamic range of expression levels (>6 orders of magnitude), including many chromatin-associated factors involved in chromosome structure and gene regulation. We apply the micro-proteomics workflow to measure the global proteome response to heat-shock in individual nematodes. This shows variation between individual animals in the magnitude of proteome response following heat-shock, including variable induction of heat-shock proteins. The micro-proteomics pipeline thus facilitates the investigation of stochastic variation in protein expression between individuals within an isogenic population of C. elegans. All data described in this study are available online via the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd), an open access, searchable database resource.

Indexed as

AnimalsCaenorhabditis elegansCaenorhabditis elegans ProteinsChromatinChromatography, Reverse-PhaseGene Expression ProfilingGene Expression RegulationHeat-Shock ProteinsMass SpectrometryProteomeProteomicsCaenorhabditis elegans ProteinsChromatinHeat-Shock ProteinsProteomeCaenorhabditis elegansHeat-shockMicro-proteomicsNematodeSingle worm proteomicsTechnology

Identifiers

PMID26552604
PMCPMC4819713
OpenAlexW2122910113

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.