Evidence map›Paper›PMID 39699734›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

DNA-Assisted Assays for Studying Lipid Transfer Between Membranes.

Yunyun Wang, Qian Shi, Qiulan Yang, Yang Yang, Xin Bian

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Yunyun Wang *State Key Laboratory of Medicinal Chemical Biology, College of Life Sciences, Frontiers Science Center for Cell Responses, Nankai University, Tianjin, China.
Qian Shi *Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Qiulan YangInstitute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yang YangInstitute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xin BianState Key Laboratory of Medicinal Chemical Biology, College of Life Sciences, Frontiers Science Center for Cell Responses, Nankai University, Tianjin, China. xin.bian@nankai.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extended-synaptotagmins (E-Syts) are proteins located on the endoplasmic reticulum (ER) that tether the ER to the plasma membrane (PM) and regulate their lipid homeostasis via its lipid transfer module, the synaptotagmin-like mitochondrial lipid-binding protein (SMP) domain. Here, we describe in vitro DNA nanostructure-assisted lipid transfer assays investigating how the SMP domain transports lipids between membranes and associates with the membranes to extract and release lipids. The lipid transfer signal was detected through fluorescence resonance energy transfer (FRET). This method overcomes the limitations of commonly used lipid transfer assays in accurately controlling inter-liposome distance and liposome size, enabling us to further understand the details involved in the process of SMP domain-mediated lipid transfer. Similar platforms can be extended to studying the lipid transfer distance and membrane curvature sensitivity of other lipid transfer proteins.

Indexed as

DNAFluorescence Resonance Energy TransferLiposomesCarrier ProteinsCell MembraneEndoplasmic ReticulumHumansLipid MetabolismLipidsSynaptotagminsCarrier ProteinsDNALipidslipid transfer proteinLiposomesSynaptotagminsDNA nanostructureE-SytsMembrane contact sitesSMP domain

Identifiers

PMID39699734

What OpenQuestion holds

Textmetadata
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.