IceR improves proteome coverage and data completeness in global and single-cell proteomics.

Label-free proteomics by data-dependent acquisition enables the unbiased quantification of thousands of proteins, however it notoriously suffers from high rates of missing values, thus prohibiting consistent protein quantification across large sample cohorts. To solve this, we here present IceR (Ion current extraction Re-quantification), an efficient and user-friendly quantification workflow that combines high identification rates of data-dependent acquisition with low missing value rates similar to data-independent acquisition. Specifically, IceR uses ion current information for a hybrid peptide identification propagation approach with superior quantification precision, accuracy, reliability and data completeness compared to other quantitative workflows.

IFN-γ Drives Human Monocyte Differentiation into Highly Proinflammatory Macrophages That Resemble a Phenotype Relevant to Psoriasis.

As key cells of the immune system, macrophages coordinate the activation and regulation of the immune response. Macrophages present a complex phenotype that can vary from homeostatic, proinflammatory, and profibrotic to anti-inflammatory phenotypes. The factors that drive the differentiation from monocyte to macrophage largely define the resultant phenotype, as has been shown by the differences found in M-CSF- and GM-CSF-derived macrophages.

Functional States in Tumor-Initiating Cell Differentiation in Human Colorectal Cancer.

Intra-tumor heterogeneity of tumor-initiating cell (TIC) activity drives colorectal cancer (CRC) progression and therapy resistance. Here, we used single-cell RNA-sequencing of patient-derived CRC models to decipher distinct cell subpopulations based on their transcriptional profiles. Cell type-specific expression modules of stem-like, transit amplifying-like, and differentiated CRC cells resemble differentiation states of normal intestinal epithelial cells.

Cell surface thermal proteome profiling tracks perturbations and drug targets on the plasma membrane.

Numerous drugs and endogenous ligands bind to cell surface receptors leading to modulation of downstream signaling cascades and frequently to adaptation of the plasma membrane proteome. In-depth analysis of dynamic processes at the cell surface is challenging due to biochemical properties and low abundances of plasma membrane proteins. Here we introduce cell surface thermal proteome profiling for the comprehensive characterization of ligand-induced changes in protein abundances and thermal stabilities at the plasma membrane.

Protease-resistant streptavidin for interaction proteomics.

Streptavidin-mediated enrichment is a powerful strategy to identify biotinylated biomolecules and their interaction partners; however, intense streptavidin-derived peptides impede protein identification by mass spectrometry. Here, we present an approach to chemically modify streptavidin, thus rendering it resistant to proteolysis by trypsin and LysC. This modification results in over 100-fold reduction of streptavidin contamination and in better coverage of proteins interacting with various biotinylated bait molecules (DNA, protein, and lipid) in an overall simplified workflow.

Automated sample preparation with SP3 for low-input clinical proteomics.

High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phase-enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format. AutoSP3 performs unbiased protein purification and digestion, and delivers peptides that can be directly analyzed by LCMS, thereby significantly reducing hands-on time, reducing variability in protein quantification, and improving longitudinal reproducibility.

Identifying drug targets in tissues and whole blood with thermal-shift profiling.

Monitoring drug-target interactions with methods such as the cellular thermal-shift assay (CETSA) is well established for simple cell systems but remains challenging in vivo. Here we introduce tissue thermal proteome profiling (tissue-TPP), which measures binding of small-molecule drugs to proteins in tissue samples from drug-treated animals by detecting changes in protein thermal stability using quantitative mass spectrometry. We report organ-specific, proteome-wide thermal stability maps and derive target profiles of the non-covalent histone deacetylase inhibitor panobinostat in rat liver, lung, kidney and spleen and of the B-Raf inhibitor vemurafenib in mouse testis.

Monitoring Dynamic Changes of the Cell Surface Glycoproteome by Quantitative Proteomics.

The analysis of the cell surface accessible proteome provides invaluable information about cellular identity, cellular functions, and interactions. Cell surface labeling in combination with quantitative proteomics enables the unbiased identification and quantification of cell surface proteins. We describe a fast, efficient, and robust protocol for the enrichment of the N-linked plasma membrane glycoproteome and subsequent analysis by mass spectrometry.

Monitoring Cell-surface -Glycoproteome Dynamics by Quantitative Proteomics Reveals Mechanistic Insights into Macrophage Differentiation.

The plasma membrane proteome plays a crucial role in inter- and intracellular signaling, cell survival, and cell identity. As such, it is a prominent target for pharmacological intervention. The relatively low abundance of this subproteome in conjunction with challenging extractability and solubility still hampers its comprehensive analysis.