Evidence map›Paper›PMID 25919452›Full record

ArticlePloS one2015

Proteomic Analysis of Copper-Binding Proteins in Excess Copper-Stressed Roots of Two Rice (Oryza sativa L.) Varieties with Different Cu Tolerances.

Chen Chen, Yufeng Song, Kai Zhuang, Lu Li, Yan Xia, Zhenguo Shen

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

20 citing papers in PubMed, 59 citations in OpenAlex.

  1. Family Identification and Functional Study of Copper Transporter Genes inInternational journal of molecular sciences · 2024
    Article
  2. Review
  3. Removal of Copper Ions from Wastewater: A Review.International journal of environmental research and public health · 2023
    Review
  4. Review
  5. Article
  6. Recent advances in physiological and molecular mechanisms of heavy metal accumulation in plants.Environmental science and pollution research international · 2021
    Review
  7. Article
  8. Article
  9. Article
  10. Morpho-Physiological and Proteomic Analyses ofPlants (Basel, Switzerland) · 2019
    Article
  11. Search for Partner Proteins ofMolecules (Basel, Switzerland) · 2018
    Article
  12. Article
  13. Frontiers in microbiology · 2018
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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

6 authors at 1 institution in 1 country.

Chen ChenCollege of Life Sciences, Nanjing Agricultural University, Nanjing, People's Republic of China.
Yufeng SongCollege of Life Sciences, Nanjing Agricultural University, Nanjing, People's Republic of China.
Kai ZhuangCollege of Life Sciences, Nanjing Agricultural University, Nanjing, People's Republic of China.
Lu LiCollege of Life Sciences, Nanjing Agricultural University, Nanjing, People's Republic of China.
Yan XiaCollege of Life Sciences, Nanjing Agricultural University, Nanjing, People's Republic of China.
Zhenguo ShenCollege of Life Sciences, Nanjing Agricultural University, Nanjing, People's Republic of China.
Nanjing Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To better understand the mechanisms involved in the heavy metal stress response and tolerance in plants, a proteomic approach was used to investigate the differences in Cu-binding protein expression in Cu-tolerant and Cu-sensitive rice varieties. Cu-binding proteins from Cu-treated rice roots were separated using a new IMAC method in which an IDA-sepharose column was applied prior to the Cu-IMAC column to remove metal ions from protein samples. More than 300 protein spots were reproducibly detected in the 2D gel. Thirty-five protein spots exhibited changes greater than 1.5-fold in intensity compared to the control. Twenty-four proteins contained one or more of nine putative metal-binding motifs reported by Smith et al., and 19 proteins (spots) contained one to three of the top six motifs reported by Kung et al. The intensities of seven protein spots were increased in the Cu-tolerant variety B1139 compared to the Cu-sensitive variety B1195 (p<0.05) and six protein spots were markedly up-regulated in B1139, but not detectable in B1195. Four protein spots were significantly up-regulated in B1139, but unchanged in B1195 under Cu stress. In contrast, two protein spots were significantly down-regulated in B1195, but unchanged in B1139. These Cu-responsive proteins included those involved in antioxidant defense and detoxification (spots 5, 16, 21, 22, 28, 29 and 33), pathogenesis (spots 5, 16, 21, 22, 28, 29 and 33), regulation of gene transcription (spots 8 and 34), amino acid synthesis (spots 8 and 34), protein synthesis, modification, transport and degradation (spots 1, 2, 4, 10, 15, 19, 30, 31, 32 and 35), cell wall synthesis (spot 14), molecular signaling (spot 3), and salt stress (spots 7, 9 and 27); together with other proteins, such as a putative glyoxylate induced protein, proteins containing dimeric alpha-beta barrel domains, and adenosine kinase-like proteins. Our results suggest that these proteins, together with related physiological processes, play an important role in the detoxification of excess Cu and in maintaining cellular homeostasis.

Indexed as

Adaptation, PhysiologicalAmino Acid MotifsCarrier ProteinsChromatography, AffinityCopperElectrophoresis, Gel, Two-DimensionalOryzaPlant ProteinsPlant RootsProteomicsStress, PhysiologicalTandem Mass SpectrometryCarrier ProteinsCoppercopper-binding proteinPlant Proteins

Identifiers

PMID25919452
PMCPMC4412397
OpenAlexW2028751119

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.