Evidence map›Paper›PMID 36603806›Full record

ArticleMolecular & cellular proteomics : MCP2023

Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform.

Yen-Chen Liao, James M Fulcher, David J Degnan, Sarah M Williams, Lisa M Bramer, Dušan Veličković, Kevin J Zemaitis, Marija Veličković, Ryan L Sontag, Ronald J Moore and 3 more

Open access · goldAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 7% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
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  14. Top-down proteomics.Nature reviews. Methods primers · 2024
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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

13 authors at 1 institution in 1 country.

Yen-Chen LiaoEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
James M FulcherEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
David J DegnanBiological Sciences Division, Pacific Northwest National Laboratories, Richland, Washington, USA.
Sarah M WilliamsEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
Lisa M BramerBiological Sciences Division, Pacific Northwest National Laboratories, Richland, Washington, USA.
Dušan VeličkovićEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
Kevin J ZemaitisEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
Marija VeličkovićEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
Ryan L SontagBiological Sciences Division, Pacific Northwest National Laboratories, Richland, Washington, USA.
Ronald J MooreBiological Sciences Division, Pacific Northwest National Laboratories, Richland, Washington, USA.
Ljiljana Paša-TolićEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
Ying ZhuEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA. Electronic address: zhu.ying@gene.com.
Mowei ZhouEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA. Electronic address: mowei.zhou@pnnl.gov.
Pacific Northwest National Laboratory · US

Funding

TR&D 7: Cell Specific ProteomicsP41GM108569 · NIGMS · NORTHWESTERN UNIVERSITY · PI KELLEHER, NEIL L · 2015 to 2024
$13.6M
Spatially resolved characterization of proteoforms for functional proteomicsUH3CA256959 · NCI · BATTELLE PACIFIC NORTHWEST LABORATORIES · PI PASA-TOLIC, LJILJANA · 2022 to 2023
$1.0M
Spatially resolved characterization of proteoforms for functional proteomicsUG3CA256959 · NCI · BATTELLE PACIFIC NORTHWEST LABORATORIES · PI PASA-TOLIC, LJILJANA · 2020 to 2021
$600k
NCI NIH HHS UG3 CA256959NCI NIH HHS UH3 CA256959NIGMS NIH HHS P41 GM108569
6 · The paper itself

Abstract

Conventional proteomic approaches measure the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of signals arising from subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot unambiguously define and quantify proteoforms, which are intact (i.e., functional) forms of proteins capturing genetic variations, alternatively spliced transcripts and posttranslational modifications. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantitation directly from tissue sections. The spatial TDP platform consisted of a nanodroplet processing in one pot for trace samples-based sample preparation system and an laser capture microdissection-based cell isolation system. We improved the nanodroplet processing in one pot for trace samples sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ∼200 cultured cells as test samples, this approach increased total proteoform identifications from 493 to 700; with newly identified proteoforms primarily corresponding to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed laser capture microdissection-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 509 proteoforms within the union of top-down mass spectrometry-based proteoform identification and characterization and TDPortal identifications to match with features from protein mass extractor. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential posttranslational modification-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

Indexed as

ProteomeProteomicsDNA-Binding ProteinsMass SpectrometryMicrofluidicsDNA-Binding ProteinsProteomelaser capture microdissectionnanoPOTSproteoformquantitationspatial proteomicstop-down proteomics

Identifiers

PMID36603806
PMCPMC9944986
OpenAlexW4313479129

What OpenQuestion holds

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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.