Evidence map›Paper›PMID 35076627›Full record

ArticleProteomes2022

Comparison of Different Label-Free Techniques for the Semi-Absolute Quantification of Protein Abundance.

Aarón Millán-Oropeza, Mélisande Blein-Nicolas, Véronique Monnet, Michel Zivy, Céline Henry

Abstract read
In one paragraph

Article in Proteomes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
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  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Protein Carrier AAV.bioRxiv : the preprint server for biology · 2024
    Article
  12. Article
  13. Article
  14. Article
  15. Quantitative Aspects of the Human Cell Proteome.International journal of molecular sciences · 2023
    Review
  16. Article
  17. Article
  18. 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.

Aarón Millán-OropezaPAPPSO, Micalis Institute, INRAE, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France.ORCID 0000-0001-9740-8683
Mélisande Blein-NicolasPAPPSO, INRAE, CNRS, AgroParisTech, GQE-Le Moulon, Université Paris-Saclay, 91190 Gif-sur-Yvette, France.
Véronique MonnetPAPPSO, Micalis Institute, INRAE, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France.
Michel ZivyPAPPSO, INRAE, CNRS, AgroParisTech, GQE-Le Moulon, Université Paris-Saclay, 91190 Gif-sur-Yvette, France.
Céline HenryPAPPSO, Micalis Institute, INRAE, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France.

Funding

European Union's Horizon 2020 research programme and the CHASSY innovation program 720824
6 · The paper itself

Abstract

In proteomics, it is essential to quantify proteins in absolute terms if we wish to compare results among studies and integrate high-throughput biological data into genome-scale metabolic models. While labeling target peptides with stable isotopes allow protein abundance to be accurately quantified, the utility of this technique is constrained by the low number of quantifiable proteins that it yields. Recently, label-free shotgun proteomics has become the "gold standard" for carrying out global assessments of biological samples containing thousands of proteins. However, this tool must be further improved if we wish to accurately quantify absolute levels of proteins. Here, we used different label-free quantification techniques to estimate absolute protein abundance in the model yeast Saccharomyces cerevisiae. More specifically, we evaluated the performance of seven different quantification methods, based either on spectral counting (SC) or extracted-ion chromatogram (XIC), which were applied to samples from five different proteome backgrounds. We also compared the accuracy and reproducibility of two strategies for transforming relative abundance into absolute abundance: a UPS2-based strategy and the total protein approach (TPA). This study mentions technical challenges related to UPS2 use and proposes ways of addressing them, including utilizing a smaller, more highly optimized amount of UPS2. Overall, three SC-based methods (PAI, SAF, and NSAF) yielded the best results because they struck a good balance between experimental performance and protein quantification.

Indexed as

label freemetabolic modelsquantitative proteomicsSaccharomycessemi-absolute quantificationTPAUPS2

Identifiers

PMID35076627
PMCPMC8788469

What OpenQuestion holds

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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.