zhu2018NC_hela: Zhu et al. 2018 (Nat. Comm.): HeLa titration

In UCLouvain-CBIO/scpdata: Single-Cell Proteomics Data Package

Zhu et al. 2018 (Nat. Comm.): HeLa titration

Description

Near single-cell proteomics data of HeLa samples containing different number of cells. There are three groups of cell concentrations: low (10-14 cells), medium (35-45 cells) and high (137-141 cells). The data also contain measures for blanks, HeLa lysates (50 cell equivalent) and 2 cancer cell line lysates (MCF7 and THP1, 50 cell equivalent).

Usage

zhu2018NC_hela

Format

A QFeatures object with 4 assays, each assay being a SingleCellExperiment object:

• peptides: quantitative information for 37,795 peptides from 21 samples

• proteins_intensity: protein intensities for 3,984 proteins from 21 samples

• proteins_LFQ: LFQ intensities for 3,984 proteins from 21 samples

• proteins_iBAQ: iBAQ values for 3,984 proteins from 21 samples

Sample annotation is stored in colData(zhu2018NC_hela()).

Acquisition protocol

The data were acquired using the following setup. More information can be found in the original article (see References).

• Cell isolation: HeLa cell concentration was adjusted by serial dilution and cell counting was performed manually using an inverted microscope.

• Sample preparation performed using the nanoPOTs device. Protein extraction using RapiGest (+ DTT) + alkylation (IAA) + Lys-C digestion + cleave RapiGest (formic acid).

• Separation: nanoACQUITY UPLC pump (60nL/min) with an Self-Pack PicoFrit 70cm x 30um LC columns.

• Ionization: ESI (1,900V).

• Mass spectrometry: Thermo Fisher Orbitrap Fusion Lumos Tribrid. MS1 settings: accumulation time = 246ms; resolution = 120,000; AGC = 1E6. MS/MS settings, depend on the sample size, excepted for the AGC = 1E5. Blank and approx. 10 cells (time = 502ms; resolution = 240,000), approx. 40 cells (time = 246ms; resolution = 120,000), approx. 140 cells (time = 118ms; resolution = 60,000).

• Data analysis: MaxQuant (v1.5.3.30) + Perseus + OriginLab 2017

Data collection

The data were collected from the PRIDE repository (accession ID: PXD006847). We downloaded the CulturedCells_peptides.txt and the CulturedCells_proteinGroups.txt files containing the combined identification and quantification results. The sample annotations were inferred from the names of columns holding the quantification data and the information in the article. The peptides data were converted to a SingleCellExperiment object. We split the protein table to separate the three types of quantification: protein intensity, label-free quantitification (LFQ) and intensity based absolute quantification (iBAQ). Each table is converted to a SingleCellExperiment object along with the remaining protein annotations. The 4 objects are combined in a single QFeatures object and feature links are created based on the peptide leading razor protein ID and the protein ID.

Source

The PSM data can be downloaded from the PRIDE repository PXD006847. FTP link: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2018/01/PXD006847

References

Zhu, Ying, Paul D. Piehowski, Rui Zhao, Jing Chen, Yufeng Shen, Ronald J. Moore, Anil K. Shukla, et al. 2018. “Nanodroplet Processing Platform for Deep and Quantitative Proteome Profiling of 10-100 Mammalian Cells.” Nature Communications 9 (1): 882 (link to article).

See Also

The same experiment was conducted on HeLa lysates: zhu2018NC_lysates.

Examples

zhu2018NC_hela()

UCLouvain-CBIO/scpdata documentation built on Oct. 29, 2024, 4:22 p.m.