Dataset Information

Spatially resolved top-down proteomics of tissue sections based on a microfluidic nanodroplet sample preparation platform

ABSTRACT: We demonstrate spatially resolved top-down proteomics (TDP) for proteoform identification and quantification from small sections of rat brain. We used the nanoPOTS (nanodroplet Processing in One pot for Trace Samples) platform, further improving the sample preparation by adding benzonase in the extraction buffer. We increased identified proteoforms from 493 to 700 in 200 cultured cells, with the largest improvements among nuclear proteins. We then performed nanoPOTS TDP on 100,000 um2 (around 200 cells) laser capture microdissectioned rat brain cortex/hypothalamus tissues. The extracted proteins were directly subjected to top down analysis without enzymatic digestion. Data was searched with TopPIC and TDPortal.

INSTRUMENT(S): Orbitrap Eclipse, Orbitrap Fusion Lumos

ORGANISM(S): Rattus Norvegicus (ncbitaxon:10116) Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Mowei Zhou

PROVIDER: MSV000089163 | MassIVE | Wed Mar 30 09:24:00 BST 2022

REPOSITORIES: MassIVE

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Publications

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

Liao Yen-Chen YC Fulcher James M JM Degnan David J DJ Williams Sarah M SM Bramer Lisa M LM Veličković Dušan D Zemaitis Kevin J KJ Veličković Marija M Sontag Ryan L RL Moore Ronald J RJ Paša-Tolić Ljiljana L Zhu Ying Y Zhou Mowei M

Molecular & cellular proteomics : MCP 20230102 2

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 gen ...[more]

PMID: 36603806

Similar Datasets

Project description: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.