schoof2021: Schoof et al. 2021 (Nat. Comm.): acute myeloid leukemia...
In UCLouvain-CBIO/scpdata: Single-Cell Proteomics Data Package

schoof2021

R Documentation

Schoof et al. 2021 (Nat. Comm.): acute myeloid leukemia differentiation

Description

Single-cell proteomics data from OCI-AML8227 cell culture to reconstruct the cellular hierarchy. The data were acquired using TMTpro multiplexing. The samples contain either no cells, single cells, 10 cells (reference channel) 200 cells (booster channel) or are simply empty wells. Single cells are expected to be one of progenitor cells (PROG), leukaemia stem cells (LSC), CD38- blast cells (⁠BLAST CD38-⁠) or CD38+ blast cells (⁠BLAST CD38+⁠). Booster are either a known 1:1:1 mix of cells (PROG, LSC and BLAST) or are isolated directly from the bulk sample. Samples were isolated and annotated using flow cytometry.

Usage

schoof2021

Format

A QFeatures object with 194 assays, each assay being a SingleCellExperiment object:

⁠F*⁠: 192 assays containing PSM quantification data for 16 TMT channels. The quantification data contain signal to noise ratios as computed by Proteome Discoverer.
proteins: quantitative data for 2898 protein groups in 3072 samples (all runs combined). The quantification data contain signal to noise ratios as computed by Proteome Discoverer.
logNormProteins: quantitative data for 2723 protein groups in 2025 single-cell samples. This assay is the protein datasets that was processed by the authors. Dimension reduction and clustering data are also available in the reducedDims and colData slots, respectively

Sample annotation is stored in colData(schoof2021()). The cell type annotation is stored in the Population column. The flow cytometry data is also available: FSC-A, FSC-H, FSC-W, SSC-A, SSC-H, SSC-W, APC-Cy7-A (= CD34) and PE-A (= CD38).

Acquisition protocol

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

Sample isolation: cultured AML 8227 cells were stained with anti-CD34 and anti-CD38. The sorting was performed by FACSAria instrument and deposited in 384 well plates.
Sample preparation: cells are lysed using freeze-boil and sonication in a lysis buffer (TFE) that also includes reduction and alkylation reagents (TCEP and CAA), followed by trypsin (protein) and benzonase (DNA) digestion, TMT-16 labeling and quenching, desalting using SOLAµ C18 plate, peptide concentration, pooling and peptide concentration again. The booster channel contains 200 cell equivalents.
Liquid chromatography: peptides are separated using a C18 reverse-phase column (50cm x 75 µm i.d., Thermo EasySpray) combined to a Thermo EasyLC 1200 for 160 minute gradient with a flowrate of 100nl/min.
Mass spectrometry: FAIMSPro interface is used. MS1 setup: resolution 60.000, AGC target of 300%, accumulation of 50ms. MS2 setup: resolution 45.000, AGC target of 150, 300 or 500%, accumulation of 150, 300, 500, or 1000ms.
Raw data processing: Proteome Discoverer 2.4 + Sequest spectral search engine and validation with Percolator

Data collection

All data were collected from the PRIDE repository (accession ID: PXD020586). The data and metadata were extracted from the SCeptre_FINAL.zip file.

We performed extensive data wrangling to combine al the metadata available from different files into a single table available using colData(schoof2021).

The PSM data were found in the bulk_PSMs.txt file. Contaminants were defined based on the protein accessions listed in contaminant.txt. The data were converted to a QFeatures object using the scp::readSCP() function.

The protein data were found in the bulk_Proteins.txt file. Contaminants were defined based on the protein accessions listed in contaminant.txt.The column names holding the quantitative data were adapted to match the sample names in the QFeatures object. Unnecessary feature annotations (such as in which assay a protein is found) were removed. Feature names were created following the procedure in SCeptre: features names are the protein symbol (or accession if missing) and if duplicated symbols are present (protein isoforms), they are made unique by appending the protein accession. Contaminants were defined based on the protein accessions listed in contaminant.txt. The data were then converted to a SingleCellExperiment object and inserted in the QFeatures object.

The log-normalized protein data were found in the bulk.h5ad file. This dataset was generated by the authors by running the notebook called bulk.ipynb. The bulk.h5ad was loaded as an AnnData object using the scanpy Python module. The object was then converted to a SingleCellExperiment object using the zellkonverter package. The column names holding the quantitative data were adapted to match the sample names in the QFeatures object. The data were then inserted in the QFeatures object.

The script to reproduce the QFeatures object is available at system.file("scripts", "make-data_schoof2021.R", package = "scpdata")

Source

The PSM and protein data can be downloaded from the PRIDE repository PXD020586 The source link is: https://www.ebi.ac.uk/pride/archive/projects/PXD020586

References

Schoof, Erwin M., Benjamin Furtwängler, Nil Üresin, Nicolas Rapin, Simonas Savickas, Coline Gentil, Eric Lechman, Ulrich auf Dem Keller, John E. Dick, and Bo T. Porse. 2021. “Quantitative Single-Cell Proteomics as a Tool to Characterize Cellular Hierarchies.” Nature Communications 12 (1): 745679. (link to article).