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. Applied to plasma and single-cell proteomics data, IceR enhanced the number of reliably quantified proteins, improved discriminability between single-cell populations, and allowed reconstruction of a developmental trajectory. IceR will be useful to improve performance of large scale global as well as low-input proteomics applications, facilitated by its availability as an easy-to-use R-package.

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. We explored alternative inflammatory mediators that could be used for in vitro differentiation of human monocytes into macrophages. IFN-γ is a potent inflammatory mediator produced by lymphocytes in disease and infections. We used IFN-γ to differentiate human monocytes into macrophages and characterized the cells at a functional and proteomic level. IFN-γ alone was sufficient to generate macrophages (IFN-γ Mϕ) that were phagocytic and responsive to polarization. We demonstrate that IFN-γ Mϕ are potent activators of T lymphocytes that produce IL-17 and IFN-γ. We identified potential markers (GBP-1, IP-10, IL-12p70, and IL-23) of IFN-γ Mϕ and demonstrate that these markers are enriched in the skin of patients with inflamed psoriasis. Collectively, we show that IFN-γ can drive human monocyte to macrophage differentiation, leading to bona fide macrophages with inflammatory characteristics.

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. Strikingly, identified subpopulations differ in proliferative activity and metabolic state. In summary, we here show at single-cell resolution that transcriptional heterogeneity identifies functional states during TIC differentiation. Furthermore, identified expression signatures are linked to patient prognosis. Targeting transcriptional states associated to cancer cell differentiation might unravel novel vulnerabilities in human CRC.

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. We demonstrate drug binding to extracellular receptors and transporters, discover stimulation-dependent remodeling of T cell receptor complexes and describe a competition-based approach to measure target engagement of G-protein-coupled receptor antagonists. Remodeling of the plasma membrane proteome in response to treatment with the TGFB receptor inhibitor SB431542 leads to partial internalization of the monocarboxylate transporters MCT1/3 explaining the antimetastatic effects of the drug.

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. We demonstrate the distinguishing ability of autoSP3 to process low-input samples, reproducibly quantifying 500-1,000 proteins from 100 to 1,000 cells. Furthermore, we applied this approach to a cohort of clinical FFPE pulmonary adenocarcinoma (ADC) samples and recapitulated their separation into known histological growth patterns. Finally, we integrated autoSP3 with AFA ultrasonication for the automated end-to-end sample preparation and LCMS analysis of 96 intact tissue samples. Collectively, this constitutes a generic, scalable, and cost-effective workflow with minimal manual intervention, enabling reproducible tissue proteomics in a broad range of clinical and non-clinical applications.

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. In addition, we devised blood-CETSA and blood-TPP and applied it to measure target and off-target engagement of panobinostat and the BET family inhibitor JQ1 directly in whole blood. Blood-TPP analysis of panobinostat confirmed its binding to known targets and also revealed thermal stabilization of the zinc-finger transcription factor ZNF512. These methods will help to elucidate the mechanisms of drug action in vivo.

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. Precise and multiplexed quantification of relative changes of cell surface protein presentation is enabled by an isobaric labeling strategy.

Monitoring Cell-surface N-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. Here, we combined a chemical glycoprotein-tagging strategy with mass spectrometry to enable comprehensive analysis of the cell-surface glycoproteome. To benchmark this workflow and to provide guidance for cell line selection for functional experiments, we generated an inventory of the N-linked cell-surface glycoproteomes of 15 standard laboratory human cell lines and three primary lymphocytic cell types. On average, about 900 plasma membrane and secreted proteins were identified per experiment, including more than 300 transporters and ion channels. Primary cells displayed distinct expression of surface markers and transporters underpinning the importance of carefully validating model cell lines selected for the study of cell surface-mediated processes. To monitor dynamic changes of the cell-surface proteome in a highly multiplexed experiment, we employed an isobaric mass tag-based chemical labeling strategy. This enabled the time-resolved analysis of plasma membrane protein presentation during differentiation of the monocytic suspension cell line THP-1 into macrophage-like adherent cells. Time-dependent changes observed in membrane protein presentation reflect functional remodeling during the phenotypic transition in three distinct phases: rapid surface presentation and secretion of proteins from intracellular pools concurrent with rapid internalization of no longer needed proteins and finally delayed presentation of newly synthesized macrophage markers. Perturbation of this process using marketed receptor tyrosine kinase inhibitors revealed dasatinib to severely compromise macrophage differentiation due to an off-target activity. This finding suggests that dynamic processes can be highly vulnerable to drug treatment and should be monitored more rigorously to identify adverse drug effects.