Evidence map›Paper›PMID 37777761›Full record

ReviewCell communication and signaling : CCS2023

The development of proximity labeling technology and its applications in mammals, plants, and microorganisms.

Jieyu Guo, Shuang Guo, Siao Lu, Jun Gong, Long Wang, Liqiong Ding, Qingjie Chen, Wu Liu

Erratum issuedAbstract readVideo-Audio MediaReview
In one paragraph

Review in Cell communication and signaling : CCS, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing 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

51 citing papers in PubMed.

  1. Review
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  3. Identification of a conserved gene family with an essential role inProceedings of the National Academy of Sciences of the United States of America · 2026
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  19. Proteomic Analysis of COVID-19 Infection.Advances in experimental medicine and biology · 2026
    Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Jieyu Guo *School of Basic Medical Sciences, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei, 437000, China.
Shuang Guo *Medicine Research Institute, Hubei Key Laboratory of Diabetes and Angiopathy, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei, 437000, China.
Siao LuSchool of Basic Medical Sciences, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei, 437000, China.
Jun GongSchool of Pharmacy, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei, 437000, China.
Long WangSchool of Basic Medical Sciences, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei, 437000, China.
Liqiong DingSchool of Pharmacy, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei, 437000, China.
Qingjie ChenSchool of Pharmacy, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei, 437000, China. chenqingjie8858@163.com.
Wu LiuSchool of Basic Medical Sciences, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei, 437000, China. lw463684057@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein‒protein, protein‒RNA, and protein‒DNA interaction networks form the basis of cellular regulation and signal transduction, making it crucial to explore these interaction networks to understand complex biological processes. Traditional methods such as affinity purification and yeast two-hybrid assays have been shown to have limitations, as they can only isolate high-affinity molecular interactions under nonphysiological conditions or in vitro. Moreover, these methods have shortcomings for organelle isolation and protein subcellular localization. To address these issues, proximity labeling techniques have been developed. This technology not only overcomes the limitations of traditional methods but also offers unique advantages in studying protein spatial characteristics and molecular interactions within living cells. Currently, this technique not only is indispensable in research on mammalian nucleoprotein interactions but also provides a reliable approach for studying nonmammalian cells, such as plants, parasites and viruses. Given these advantages, this article provides a detailed introduction to the principles of proximity labeling techniques and the development of labeling enzymes. The focus is on summarizing the recent applications of TurboID and miniTurbo in mammals, plants, and microorganisms. Video Abstract.

Indexed as

Protein Interaction MapsProteinsAnimalsMammalsProteinsAPEXBioIDminiTurboProximity labelingTurboID

Identifiers

PMID37777761
PMCPMC10544124

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.