MassIVE MSV000091156

Partial Public PXD039686

Robust and easy-to-use one pot workflow for label free single cell proteomics

Subscribe Comment Reanalyze Spectra Add Reanalysis

Description

The analysis of ultra-low input samples or even individual cells is essential to answering a multitude of biomedical questions, but current proteomic workflows are limited in their sensitivity and reproducibility. Here we report a comprehensive workflow that includes optimized strategies for all steps from cell lysis to data analysis. Thanks to convenient to handle 1 uL sample volume and standardized 384 well plates the workflow is easy for even novice users to implement. At the same time, it can be performed semi-automatized using the CellenONE, which allows for highest reproducibility. To achieve high throughput, ultrashort gradient lengths down to 5 min were tested using advanced u-pillar columns. Data-dependent acquisition (DDA), wide-window acquisition (WWA) and data-independent acquisition (DIA), and commonly used advanced data-analysis algorithms were bench-marked. Using DDA, 1790 proteins covering a dynamic range of four orders of magnitude were identified in a single cell. Using DIA, proteome coverage increased to more than 2200 proteins identified from single cell level input in a 20-min active gradient. The workflow enabled differentiation of two cell lines, demonstrating its suitability to cellular heterogeneity determination. [doi:10.25345/C5XW4858S] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Single Cell Proteomics ; one-pot workflow ; label-free ; WWA ; DIA ; uPAC ; CellenONE

Contact

Principal Investigators:
(in alphabetical order) 		Karl Mechtler, IMP, IMBA, N/A
Manuel Matzinger, IMP, Austria
Submitting User: manuel_matzinger1

Publications

Matzinger M, Müller E, Dürnberger G, Pichler P, Mechtler K.
Robust and Easy-to-Use One-Pot Workflow for Label-Free Single-Cell Proteomics.
Anal Chem. 2023 Mar 7;95(9):4435-4445. Epub 2023 Feb 20.

Number of Files:
Total Size:
Spectra:
Subscribers:
 
Owner Reanalyses
Experimental Design
    Conditions:
    Biological Replicates:
    Technical Replicates:
 
Identification Results
    Proteins (Human, Remapped):
    Proteins (Reported):
    Peptides:
    Variant Peptides:
    PSMs:
 
Quantification Results
    Differential Proteins:
    Quantified Proteins:
 
Browse Dataset Files
 
FTP Download Link (click to copy):

Species

Instrument

Modifications

- Dataset Reanalyses

+ Dataset History

Click here to queue conversion of this dataset's submitted spectrum files to open formats (e.g. mzML). This process may take some time.

When complete, the converted files will be available in the "ccms_peak" subdirectory of the dataset's FTP space (accessible via the "FTP Download" link to the right).
Number of distinct conditions across all analyses (original submission and reanalyses) associated with this dataset.

Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

"N/A" means no results of this type were submitted.
Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

Distinct replicate labels are counted across all files submitted in the "Metadata" category having a "BioReplicate" or "Replicate" column in this dataset.

"N/A" means no results of this type were submitted.
Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

The technical replicate count is defined as the maximum number of times any one distinct combination of condition and biological replicate was analyzed across all files submitted in the "Metadata" category. In the case of fractionated experiments, only the first fraction is considered.

"N/A" means no results of this type were submitted.
Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

"N/A" means no results of this type were submitted.
Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.