Evidence map›Paper›PMID 37090610›Full record

ArticlebioRxiv : the preprint server for biology2024

A proximity proteomics pipeline with improved reproducibility and throughput.

Xiaofang Zhong, Qiongyu Li, Benjamin J Polacco, Trupti Patil, Aaron Marley, Helene Foussard, Prachi Khare, Rasika Vartak, Jiewei Xu, Jeffrey F DiBerto and 5 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 12 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 3 institutions in 1 country.

Xiaofang ZhongQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.
Qiongyu LiQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.
Benjamin J PolaccoQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.
Trupti PatilQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.
Aaron MarleyDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94158, USA.
Helene FoussardQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.
Prachi KhareQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.
Rasika VartakQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.
Jiewei XuQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.
Jeffrey F DiBertoDepartment of Pharmacology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Bryan L RothDepartment of Pharmacology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.ORCID 0000-0002-0561-6520
Manon EckhardtQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0001-8143-6129
Mark Von ZastrowQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0003-1375-6926
Nevan J KroganQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0003-4902-337X
Ruth HüttenhainQuantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0002-0896-5910
Gladstone Institutes · USUniversity of California, San Francisco · USUniversity of North Carolina at Chapel Hill · US

Funding

Project 3: Control of cardiac transcription by MEF2 and myocardinP01HL146366 · NHLBI · J. DAVID GLADSTONE INSTITUTES · PI BLACK, BRIAN L · 2019 to 2023
$13.7M
PROTEINS REGULATING ENDOCYTOSIS OF OPIOID RECEPTORSR01DA012864 · NIDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Mark E Von Zastrow · 2000 to 2026
$7.9M
Mechanistic insights into LSD actions at 5-HT2A serotonin receptorsR37DA045657 · NIDA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Bryan L. Roth · 2018 to 2026
$5.8M
Membrane Trafficking of Opioid and Adrenergic ReceptorsR01DA010711 · NIDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI VONZASTROW, MARK E · 2014 to 2023
$4.6M
Spatiotemporal signaling and trafficking of the mu-opioid receptorR01DA056354 · NIDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Ruth Huttenhain · 2022 to 2026
$2.9M
NHLBI NIH HHS P01 HL146366NIDA NIH HHS R01 DA010711NIDA NIH HHS R01 DA012864NIDA NIH HHS R01 DA056354NIDA NIH HHS R37 DA045657
6 · The paper itself

Abstract

Proximity labeling (PL) through biotinylation coupled with mass spectrometry (MS) has emerged as a powerful technique for capturing spatial proteomes within living cells. Large-scale sample processing for proximity proteomics requires a workflow that minimizes hands-on time while enhancing quantitative reproducibility. Here, we present a scalable PL pipeline integrating automated enrichment of biotinylated proteins in a 96-well plate format. By combining this pipeline with an optimized quantitative MS acquisition method based on data-independent acquisition (DIA), we not only significantly increased sample throughput but also improved the reproducibility of protein identification and quantification. We applied this pipeline to delineate subcellular proteomes across various cellular compartments, including endosomes, late endosomes/lysosomes, the Golgi apparatus, and the plasma membrane. Moreover, employing 5HT

Identifiers

PMID37090610
PMCPMC10120663
OpenAlexW4365144750

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
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.