Chemical proteomics reveals the target landscape of 1,000 kinase inhibitors

Medicinal chemistry has discovered thousands of potent protein and lipid kinase inhibitors. These may be developed into therapeutic drugs or chemical probes to study kinase biology. Because of polypharmacology, a large part of the human kinome currently lacks selective chemical probes. To discover such probes, we profiled 1,183 compounds from drug discovery projects in lysates of cancer cell lines using Kinobeads. The resulting 500,000 compound-target interactions are available in ProteomicsDB and we exemplify how this molecular resource may be used. For instance, the data revealed several hundred reasonably selective compounds for 72 kinases. Cellular assays validated GSK986310C as a candidate SYK (spleen tyrosine kinase) probe and X-ray crystallography uncovered the structural basis for the observed selectivity of the CK2 inhibitor GW869516X. Compounds targeting PKN3 were discovered and phosphoproteomics identified substrates that indicate target engagement in cells. We anticipate that this molecular resource will aid research in drug discovery and chemical biology.

Inhibiting Hippo pathway kinases releases WWC1 to promote AMPAR-dependent synaptic plasticity and long-term memory in mice

The localization, number, and function of postsynaptic AMPA-type glutamate receptors (AMPARs) are crucial for synaptic plasticity, a cellular correlate for learning and memory. The Hippo pathway member WWC1 is an important component of AMPAR-containing protein complexes. However, the availability of WWC1 is constrained by its interaction with the Hippo pathway kinases LATS1 and LATS2 (LATS1/2). Here, we explored the biochemical regulation of this interaction and found that it is pharmacologically targetable in vivo. In primary hippocampal neurons, phosphorylation of LATS1/2 by the upstream kinases MST1 and MST2 (MST1/2) enhanced the interaction between WWC1 and LATS1/2, which sequestered WWC1. Pharmacologically inhibiting MST1/2 in male mice and in human brain-derived organoids promoted the dissociation of WWC1 from LATS1/2, leading to an increase in WWC1 in AMPAR-containing complexes. MST1/2 inhibition enhanced synaptic transmission in mouse hippocampal brain slices and improved cognition in healthy male mice and in male mouse models of Alzheimer's disease and aging. Thus, compounds that disrupt the interaction between WWC1 and LATS1/2 might be explored for development as cognitive enhancers.

Integrating multi-omics data reveals energy and stress signaling activated by abscisic acid in Arabidopsis

Phytohormones are essential signaling molecules regulating various processes in growth, development, and stress responses. Genetic and molecular studies, especially using Arabidopsis thaliana (Arabidopsis), have discovered many important players involved in hormone perception, signal transduction, transport, and metabolism. Phytohormone signaling pathways are extensively interconnected with other endogenous and environmental stimuli. However, our knowledge of the huge and complex molecular network governed by a hormone remains limited. Here we report a global overview of downstream events of an abscisic acid (ABA) receptor, REGULATORY COMPONENTS OF ABA RECEPTOR (RCAR) 6 (also known as PYRABACTIN RESISTANCE 1 [PYR1]-LIKE [PYL] 12), by integrating phosphoproteomic, proteomic and metabolite profiles. Our data suggest that the RCAR6 overexpression constitutively decreases the protein levels of its coreceptors, namely clade A protein phosphatases of type 2C, and activates sucrose non-fermenting-1 (SNF1)-related protein kinase 1 (SnRK1) and SnRK2, the central regulators of energy and ABA signaling pathways. Furthermore, several enzymes in sugar metabolism were differentially phosphorylated and expressed in the RCAR6 line, and the metabolite profile revealed altered accumulations of several organic acids and amino acids. These results indicate that energy- and water-saving mechanisms mediated by the SnRK1 and SnRK2 kinases, respectively, are under the control of the ABA receptor-coreceptor complexes.

Oktoberfest: Open-source spectral library generation and rescoring pipeline based on Prosit

Machine learning (ML) and deep learning (DL) models for peptide property prediction such as Prosit have enabled the creation of high quality in silico reference libraries. These libraries are used in various applications, ranging from data-independent acquisition (DIA) data analysis to data-driven rescoring of search engine results. Here, we present Oktoberfest, an open source Python package of our spectral library generation and rescoring pipeline originally only available online via ProteomicsDB. Oktoberfest is largely search engine agnostic and provides access to online peptide property predictions, promoting the adoption of state-of-the-art ML/DL models in proteomics analysis pipelines. We demonstrate its ability to reproduce and even improve our results from previously published rescoring analyses on two distinct use cases. Oktoberfest is freely available on GitHub (https://github.com/wilhelm-lab/oktoberfest) and can easily be installed locally through the cross-platform PyPI Python package.

D6PK plasma membrane polarity requires a repeated CXX(X)P motif and PDK1-dependent phosphorylation

D6 PROTEIN KINASE (D6PK) is a polarly localized plasma-membrane-associated kinase from Arabidopsis thaliana that activates polarly distributed PIN-FORMED auxin transporters. D6PK moves rapidly to and from the plasma membrane, independent of its PIN-FORMED targets. The middle D6PK domain, an insertion between kinase subdomains VII and VIII, is required and sufficient for association and polarity of the D6PK plasma membrane. How D6PK polarity is established and maintained remains to be shown. Here we show that cysteines from repeated middle domain CXX(X)P motifs are S-acylated and required for D6PK membrane association. While D6PK S-acylation is not detectably regulated during intracellular transport, phosphorylation of adjacent serine residues, in part in dependence on the upstream 3-PHOSPHOINOSITIDE-DEPENDENT PROTEIN KINASE, promotes D6PK transport, controls D6PK residence time at the plasma membrane and prevents its lateral diffusion. We thus identify new mechanisms for the regulation of D6PK plasma membrane interaction and polarity.

Multicenter Collaborative Study to Optimize Mass Spectrometry Workflows of Clinical Specimens

The foundation for integrating mass spectrometry (MS)-based proteomics into systems medicine is the development of standardized start-to-finish and fit-for-purpose workflows for clinical specimens. An essential step in this pursuit is to highlight the common ground in a diverse landscape of different sample preparation techniques and liquid chromatography-mass spectrometry (LC-MS) setups. With the aim to benchmark and improve the current best practices among the proteomics MS laboratories of the CLINSPECT-M consortium, we performed two consecutive round-robin studies with full freedom to operate in terms of sample preparation and MS measurements. The six study partners were provided with two clinically relevant sample matrices: plasma and cerebrospinal fluid (CSF). In the first round, each laboratory applied their current best practice protocol for the respective matrix. Based on the achieved results and following a transparent exchange of all lab-specific protocols within the consortium, each laboratory could advance their methods before measuring the same samples in the second acquisition round. Both time points are compared with respect to identifications (IDs), data completeness, and precision, as well as reproducibility. As a result, the individual performances of participating study centers were improved in the second measurement, emphasizing the effect and importance of the expert-driven exchange of best practices for direct practical improvements.

Illuminating phenotypic drug responses of sarcoma cells to kinase inhibitors by phosphoproteomics

Kinase inhibitors (KIs) are important cancer drugs but often feature polypharmacology that is molecularly not understood. This disconnect is particularly apparent in cancer entities such as sarcomas for which the oncogenic drivers are often not clear. To investigate more systematically how the cellular proteotypes of sarcoma cells shape their response to molecularly targeted drugs, we profiled the proteomes and phosphoproteomes of 17 sarcoma cell lines and screened the same against 150 cancer drugs. The resulting 2550 phenotypic profiles revealed distinct drug responses and the cellular activity landscapes derived from deep (phospho)proteomes (9-10,000 proteins and 10-27,000 phosphorylation sites per cell line) enabled several lines of analysis. For instance, connecting the (phospho)proteomic data with drug responses revealed known and novel mechanisms of action (MoAs) of KIs and identified markers of drug sensitivity or resistance. All data is publicly accessible via an interactive web application that enables exploration of this rich molecular resource for a better understanding of active signalling pathways in sarcoma cells, identifying treatment response predictors and revealing novel MoA of clinical KIs.

A region-resolved proteomic map of the human brain enabled by high-throughput proteomics

Substantial efforts are underway to deepen our understanding of human brain morphology, structure, and function using high-resolution imaging as well as high-content molecular profiling technologies. The current work adds to these approaches by providing a comprehensive and quantitative protein expression map of 13 anatomically distinct brain regions covering more than 11,000 proteins. This was enabled by the optimization, characterization, and implementation of a high-sensitivity and high-throughput microflow liquid chromatography timsTOF tandem mass spectrometry system (LC-MS/MS) capable of analyzing more than 2,000 consecutive samples prepared from formalin-fixed paraffin embedded (FFPE) material. Analysis of this proteomic resource highlighted brain region-enriched protein expression patterns and functional protein classes, protein localization differences between brain regions and individual markers for specific areas. To facilitate access to and ease further mining of the data by the scientific community, all data can be explored online in a purpose-built R Shiny app (https://brain-region-atlas.proteomics.ls.tum.de).

CurveCurator: a recalibrated F-statistic to assess, classify, and explore significance of dose-response curves

Dose-response curves are key metrics in pharmacology and biology to assess phenotypic or molecular actions of bioactive compounds in a quantitative fashion. Yet, it is often unclear whether or not a measured response significantly differs from a curve without regulation, particularly in high-throughput applications or unstable assays. Treating potency and effect size estimates from random and true curves with the same level of confidence can lead to incorrect hypotheses and issues in training machine learning models. Here, we present CurveCurator, an open-source software that provides reliable dose-response characteristics by computing p-values and false discovery rates based on a recalibrated F-statistic and a target-decoy procedure that considers dataset-specific effect size distributions. The application of CurveCurator to three large-scale datasets enables a systematic drug mode of action analysis and demonstrates its scalable utility across several application areas, facilitated by a performant, interactive dashboard for fast data exploration.

Negative feedback regulation of MAPK signaling is an important driver of chronic lymphocytic leukemia progression

Despite available targeted treatments for the disease, drug-resistant chronic lymphocytic leukemia (CLL) poses a clinical challenge. The objective of this study is to examine whether the dual-specific phosphatases DUSP1 and DUSP6 are required to negatively regulate mitogen-activated protein kinases (MAPKs) and thus counterbalance excessive MAPK activity. We show that high expression of DUSP6 in CLL correlates with poor clinical prognosis. Importantly, genetic deletion of the inhibitory phosphatase DUSP1 or DUSP6 and blocking DUSP1/6 function using a small-molecule inhibitor reduces CLL cell survival in vitro and in vivo. Using global phospho-proteome approaches, we observe acute activation of MAPK signaling by DUSP1/6 inhibition. This promotes accumulation of mitochondrial reactive oxygen species and, thereby, DNA damage and apoptotic cell death in CLL cells. Finally, we observe that DUSP1/6 inhibition is particularly effective against treatment-resistant CLL and therefore suggest transient DUSP1/6 inhibition as a promising treatment concept to eliminate drug-resistant CLL cells.

Structural Basis for Highly Selective Class II Alpha Phosphoinositide-3-Kinase Inhibition

Class II phosphoinositide-3-kinases (PI3Ks) play central roles in cell signaling, division, migration, and survival. Despite evidence that all PI3K class II isoforms serve unique cellular functions, the lack of isoform-selective inhibitors severely hampers the systematic investigation of their potential relevance as pharmacological targets. Here, we report the structural evaluation and molecular determinants for selective PI3K-C2α inhibition by a structure-activity relationship study based on a pteridinone scaffold, leading to the discovery of selective PI3K-C2α inhibitors called PITCOINs. Cocrystal structures and docking experiments supported the rationalization of the structural determinants essential for inhibitor activity and high selectivity. Profiling of PITCOINs in a panel of more than 118 diverse kinases showed no off-target kinase inhibition. Notably, by addressing a selectivity pocket, PITCOIN4 showed nanomolar inhibition of PI3K-C2α and >100-fold selectivity in a general kinase panel. Our study paves the way for the development of novel therapies for diseases related to PI3K-C2α function.

Proteomic meta-study harmonization, mechanotyping and drug repurposing candidate prediction with ProHarMeD

Proteomics technologies, which include a diverse range of approaches such as mass spectrometry-based, array-based, and others, are key technologies for the identification of biomarkers and disease mechanisms, referred to as mechanotyping. Despite over 15,000 published studies in 2022 alone, leveraging publicly available proteomics data for biomarker identification, mechanotyping and drug target identification is not readily possible. Proteomic data addressing similar biological/biomedical questions are made available by multiple research groups in different locations using different model organisms. Furthermore, not only various organisms are employed but different assay systems, such as in vitro and in vivo systems, are used. Finally, even though proteomics data are deposited in public databases, such as ProteomeXchange, they are provided at different levels of detail. Thus, data integration is hampered by non-harmonized usage of identifiers when reviewing the literature or performing meta-analyses to consolidate existing publications into a joint picture. To address this problem, we present ProHarMeD, a tool for harmonizing and comparing proteomics data gathered in multiple studies and for the extraction of disease mechanisms and putative drug repurposing candidates. It is available as a website, Python library and R package. ProHarMeD facilitates ID and name conversions between protein and gene levels, or organisms via ortholog mapping, and provides detailed logs on the loss and gain of IDs after each step. The web tool further determines IDs shared by different studies, proposes potential disease mechanisms as well as drug repurposing candidates automatically, and visualizes these results interactively. We apply ProHarMeD to a set of four studies on bone regeneration. First, we demonstrate the benefit of ID harmonization which increases the number of shared genes between studies by 50%. Second, we identify a potential disease mechanism, with five corresponding drug targets, and the top 20 putative drug repurposing candidates, of which Fondaparinux, the candidate with the highest score, and multiple others are known to have an impact on bone regeneration. Hence, ProHarMeD allows users to harmonize multi-centric proteomics research data in meta-analyses, evaluates the success of the ID conversions and remappings, and finally, it closes the gaps between proteomics, disease mechanism mining and drug repurposing. It is publicly available at https://apps.cosy.bio/proharmed/ .

High-Throughput Screening and Proteomic Characterization of Compounds Targeting Myeloid-Derived Suppressor Cells

Myeloid-derived suppressor cells (MDSC) are a heterogeneous cell population of incompletely differentiated immune cells. They are known to suppress T cell activity and are implicated in multiple chronic diseases, which make them an attractive cell population for drug discovery. Here, we characterized the baseline proteomes and phospho-proteomes of mouse MDSC differentiated from a progenitor cell line to a depth of 7000 proteins and phosphorylation sites. We also validated the cellular system for drug discovery by recapitulating and identifying known and novel molecular responses to the well-studied MDSC drugs entinostat and mocetinostat. We established a high-throughput drug screening platform using a MDSC/T cell coculture system and assessed the effects of ∼21,000 small molecule compounds on T cell proliferation and IFN-γ secretion to identify novel MDSC modulator. The most promising candidates were validated in a human MDSC system, and subsequent proteomic experiments showed significant upregulation of several proteins associated with the reduction of reactive oxygen species (ROS). Proteome-wide solvent-induced protein stability assays identified Acyp1 and Cd74 as potential targets, and the ROS-reducing drug phenotype was validated by measuring ROS levels in cells in response to compound, suggesting a potential mode of action. We anticipate that the data and chemical tools developed in this study will be valuable for further research on MDSC and related drug discovery.

An Introduction to Analytical Challenges, Approaches, and Applications in Mass Spectrometry-Based Secretomics

The active release of proteins into the extracellular space and the proteolytic cleavage of cell surface proteins are key processes that coordinate and fine-tune a multitude of physiological functions. The entirety of proteins that fulfill these extracellular tasks are referred to as the secretome and are of special interest for the investigation of biomarkers of disease states and physiological processes related to cell-cell communication. LC-MS-based proteomics approaches are a valuable tool for the comprehensive and unbiased characterization of this important subproteome. This review discusses procedures, opportunities, and limitations of mass spectrometry-based secretomics to better understand and navigate the complex analytical landscape for studying protein secretion in biomedical science.

Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification

Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types for proteogenomic-based discovery of neoantigens. By using an optimized computational approach, we discover a large number of tumor-specific and tumor-associated antigens. To create a pipeline for the identification of neoantigens in our cohort, we combine DNA and RNA sequencing with MS-based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity and an in-depth validation process. We detect a broad variety of non-canonical HLA-binding peptides in the majority of patients demonstrating partially immunogenicity. Our validation process allows for the selection of 32 potential neoantigen candidates. The majority of neoantigen candidates originates from variants identified in the RNA data set, illustrating the relevance of RNA as a still understudied source of cancer antigens. This study underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates.

Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes

Bacteria are the most abundant and diverse organisms among the kingdoms of life. Due to this excessive variance, finding a unified, comprehensive, and safe workflow for quantitative bacterial proteomics is challenging. In this study, we have systematically evaluated and optimized sample preparation, mass spectrometric data acquisition, and data analysis strategies in bacterial proteomics. We investigated workflow performances on six representative species with highly different physiologic properties to mimic bacterial diversity. The best sample preparation strategy was a cell lysis protocol in 100% trifluoroacetic acid followed by an in-solution digest. Peptides were separated on a 30-min linear microflow liquid chromatography gradient and analyzed in data-independent acquisition mode. Data analysis was performed with DIA-NN using a predicted spectral library. Performance was evaluated according to the number of identified proteins, quantitative precision, throughput, costs, and biological safety. With this rapid workflow, over 40% of all encoded genes were detected per bacterial species. We demonstrated the general applicability of our workflow on a set of 23 taxonomically and physiologically diverse bacterial species. We could confidently identify over 45,000 proteins in the combined dataset, of which 30,000 have not been experimentally validated before. Our work thereby provides a valuable resource for the microbial scientific community. Finally, we grew Escherichia coli and Bacillus cereus in replicates under 12 different cultivation conditions to demonstrate the high-throughput suitability of the workflow. The proteomic workflow we present in this manuscript does not require any specialized equipment or commercial software and can be easily applied by other laboratories to support and accelerate the proteomic exploration of the bacterial kingdom.

Chemoproteomic target deconvolution reveals Histone Deacetylases as targets of (R)-lipoic acid

Lipoic acid is an essential enzyme cofactor in central metabolic pathways. Due to its claimed antioxidant properties, racemic (R/S)-lipoic acid is used as a food supplement but is also investigated as a pharmaceutical in over 180 clinical trials covering a broad range of diseases. Moreover, (R/S)-lipoic acid is an approved drug for the treatment of diabetic neuropathy. However, its mechanism of action remains elusive. Here, we performed chemoproteomics-aided target deconvolution of lipoic acid and its active close analog lipoamide. We find that histone deacetylases HDAC1, HDAC2, HDAC3, HDAC6, HDAC8, and HDAC10 are molecular targets of the reduced form of lipoic acid and lipoamide. Importantly, only the naturally occurring (R)-enantiomer inhibits HDACs at physiologically relevant concentrations and leads to hyperacetylation of HDAC substrates. The inhibition of HDACs by (R)-lipoic acid and lipoamide explain why both compounds prevent stress granule formation in cells and may also provide a molecular rationale for many other phenotypic effects elicited by lipoic acid.

Optimization of the Lead Compound NVP-BHG712 as a Colorectal Cancer Inhibitor

The ephrin type-A receptor 2 (EPHA2) kinase belongs to the largest family of receptor tyrosine kinases. There are several indications of an involvement of EPHA2 in the development of infectious diseases and cancer. Despite pharmacological potential, EPHA2 is an under-examined target protein. In this study, we synthesized a series of derivatives of the inhibitor NVP-BHG712 and triazine-based compounds. These compounds were evaluated to determine their potential as kinase inhibitors of EPHA2, including elucidation of their binding mode (X-ray crystallography), affinity (microscale thermophoresis), and selectivity (Kinobeads assay). Eight inhibitors showed affinities in the low-nanomolar regime (KD <10 nM). Testing in up to seven colon cancer cell lines that express EPHA2 reveals that several derivatives feature promising effects for the control of human colon carcinoma. Thus, we have developed a set of powerful tool compounds for fundamental new research on the interplay of EPH receptors in a cellular context.

Decrypting drug actions and protein modifications by dose- and time-resolved proteomics

Although most cancer drugs modulate the activities of cellular pathways by changing posttranslational modifications (PTMs), little is known regarding the extent and the time- and dose-response characteristics of drug-regulated PTMs. In this work, we introduce a proteomic assay called decryptM that quantifies drug-PTM modulation for thousands of PTMs in cells to shed light on target engagement and drug mechanism of action. Examples range from detecting DNA damage by chemotherapeutics, to identifying drug-specific PTM signatures of kinase inhibitors, to demonstrating that rituximab kills CD20-positive B cells by overactivating B cell receptor signaling. DecryptM profiling of 31 cancer drugs in 13 cell lines demonstrates the broad applicability of the approach. The resulting 1.8 million dose-response curves are provided as an interactive molecular resource in ProteomicsDB.

Discovery of Potent and Exquisitely Selective Inhibitors of Kinase CK1 with Tunable Isoform Selectivity

Casein kinases 1 (CK1) are key signaling molecules that have emerged recently as attractive therapeutic targets in particular for the treatment of hematological malignancies. Herein, we report the identification of a new class of potent and highly selective inhibitors of CK1α, δ and ϵ. Based on their optimal in vitro and in vivo profiles and their exclusive selectivity, MU1250, MU1500 and MU1742 were selected as quality chemical probes for those CK1 isoforms. At proper concentrations, MU1250 and MU1500 allow for specific targeting of CK1δ or dual inhibition of CK1δ/ϵ in cells. The compound MU1742 also efficiently inhibits CK1α and, to our knowledge, represents the first potent and highly selective inhibitor of this enzyme. In addition, we demonstrate that the central 1H-pyrrolo[2,3-b]pyridine-imidazole pharmacophore can be used as the basis of highly selective inhibitors of other therapeutically relevant protein kinases, e.g. p38α, as exemplified by the compound MU1299.

A unified classification approach rating clinical utility of protein biomarkers across neurologic diseases

A major evolution from purely clinical diagnoses to biomarker supported clinical diagnosing has been occurring over the past years in neurology. High-throughput methods, such as next-generation sequencing and mass spectrometry-based proteomics along with improved neuroimaging methods, are accelerating this development. This calls for a consensus framework that is broadly applicable and provides a spot-on overview of the clinical validity of novel biomarkers. We propose a harmonized terminology and a uniform concept that stratifies biomarkers according to clinical context of use and evidence levels, adapted from existing frameworks in oncology with a strong focus on (epi)genetic markers and treatment context. We demonstrate that this framework allows for a consistent assessment of clinical validity across disease entities and that sufficient evidence for many clinical applications of protein biomarkers is lacking. Our framework may help to identify promising biomarker candidates and classify their applications by clinical context, aiming for routine clinical use of (protein) biomarkers in neurology.

UHMK1 is a novel splicing regulatory kinase

The U2AF Homology Motif Kinase 1 (UHMK1) is the only kinase that contains the U2AF homology motif, a common protein interaction domain among splicing factors. Through this motif, UHMK1 interacts with the splicing factors SF1 and SF3B1, known to participate in the 3' splice site recognition during the early steps of spliceosome assembly. Although UHMK1 phosphorylates these splicing factors in vitro, the involvement of UHMK1 in RNA processing has not previously been demonstrated. Here, we identify novel putative substrates of this kinase and evaluate UHMK1 contribution to overall gene expression and splicing, by integrating global phosphoproteomics, RNA-seq, and bioinformatics approaches. Upon UHMK1 modulation, 163 unique phosphosites were differentially phosphorylated in 117 proteins, of which 106 are novel potential substrates of this kinase. Gene Ontology analysis showed enrichment of terms previously associated with UHMK1 function, such as mRNA splicing, cell cycle, cell division, and microtubule organization. The majority of the annotated RNA-related proteins are components of the spliceosome but are also involved in several steps of gene expression. Comprehensive analysis of splicing showed that UHMK1 affected over 270 alternative splicing events. Moreover, splicing reporter assay further supported UHMK1 function on splicing. Overall, RNA-seq data demonstrated that UHMK1 knockdown had a minor impact on transcript expression and pointed to UHMK1 function in epithelial-mesenchymal transition. Functional assays demonstrated that UHMK1 modulation affects proliferation, colony formation, and migration. Taken together, our data implicate UHMK1 as a splicing regulatory kinase, connecting protein regulation through phosphorylation and gene expression in key cellular processes.

Getting Ready for Large-Scale Proteomics in Crop Plants

Plants are an indispensable cornerstone of sustainable global food supply. While immense progress has been made in decoding the genomes of crops in recent decades, the composition of their proteomes, the entirety of all expressed proteins of a species, is virtually unknown. In contrast to the model plant Arabidopsis thaliana, proteomic analyses of crop plants have often been hindered by the presence of extreme concentrations of secondary metabolites such as pigments, phenolic compounds, lipids, carbohydrates or terpenes. As a consequence, crop proteomic experiments have, thus far, required individually optimized protein extraction protocols to obtain samples of acceptable quality for downstream analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). In this article, we present a universal protein extraction protocol originally developed for gel-based experiments and combined it with an automated single-pot solid-phase-enhanced sample preparation (SP3) protocol on a liquid handling robot to prepare high-quality samples for proteomic analysis of crop plants. We also report an automated offline peptide separation protocol and optimized micro-LC-MS/MS conditions that enables the identification and quantification of ~10,000 proteins from plant tissue within 6 h of instrument time. We illustrate the utility of the workflow by analyzing the proteomes of mature tomato fruits to an unprecedented depth. The data demonstrate the robustness of the approach which we propose for use in upcoming large-scale projects that aim to map crop tissue proteomes.

Development of selective inhibitors of phosphatidylinositol 3-kinase C2α

Phosphatidylinositol 3-kinase type 2α (PI3KC2α) and related class II PI3K isoforms are of increasing biomedical interest because of their crucial roles in endocytic membrane dynamics, cell division and signaling, angiogenesis, and platelet morphology and function. Herein we report the development and characterization of PhosphatidylInositol Three-kinase Class twO INhibitors (PITCOINs), potent and highly selective small-molecule inhibitors of PI3KC2α catalytic activity. PITCOIN compounds exhibit strong selectivity toward PI3KC2α due to their unique mode of interaction with the ATP-binding site of the enzyme. We demonstrate that acute inhibition of PI3KC2α-mediated synthesis of phosphatidylinositol 3-phosphates by PITCOINs impairs endocytic membrane dynamics and membrane remodeling during platelet-dependent thrombus formation. PITCOINs are potent and selective cell-permeable inhibitors of PI3KC2α function with potential biomedical applications ranging from thrombosis to diabetes and cancer.

Hippo-released WWC1 facilitates AMPA receptor regulatory complexes for hippocampal learning

Learning and memory rely on changes in postsynaptic glutamergic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-type receptor (AMPAR) number, spatial organization, and function. The Hippo pathway component WW and C2 domain-containing protein 1 (WWC1) regulates AMPAR surface expression and impacts on memory performance. However, synaptic binding partners of WWC1 and its hierarchical position in AMPAR complexes are largely unclear. Using cell-surface proteomics in hippocampal tissue of Wwc1-deficient mice and by generating a hippocampus-specific interactome, we show that WWC1 is a major regulatory platform in AMPAR signaling networks. Under basal conditions, the Hippo pathway members WWC1 and large tumor-suppressor kinase (LATS) are associated, which might prevent WWC1 effects on synaptic proteins. Reduction of WWC1/LATS binding through a point mutation at WWC1 elevates the abundance of WWC1 in AMPAR complexes and improves hippocampal-dependent learning and memory. Thus, uncoupling of WWC1 from the Hippo pathway to AMPAR-regulatory complexes provides an innovative strategy to enhance synaptic transmission.

Merits of Diazirine Photo-Immobilization for Target Profiling of Natural Products and Cofactors

Finding the targets of natural products is of key importance in both chemical biology and drug discovery, and deconvolution of cofactor interactomes contributes to the functional annotation of the proteome. Identifying the proteins that underlie natural compound activity in phenotypic screens helps to validate the respective targets and, potentially, expand the druggable proteome. Here, we present a generally applicable protocol for the photoactivated immobilization of unmodified and microgram quantities of natural products on diazirine-decorated beads and their use for systematic affinity-based proteome profiling. We show that among 31 molecules of very diverse reported activity and biosynthetic origin, 25 could indeed be immobilized. Dose-response competition binding experiments using lysates of human or bacterial cells followed by quantitative mass spectrometry recapitulated targets of 9 molecules with <100 μM affinity. Among them, immobilization of coenzyme A produced a tool to interrogate proteins containing a HotDog domain. Surprisingly, immobilization of the cofactor flavin adenine dinucleotide (FAD) led to the identification of nanomolar interactions with dozens of RNA-binding proteins.

High sensitivity glycomics in biomedicine

Many analytical challenges in biomedicine arise from the generally high heterogeneity and complexity of glycan- and glycoconjugate-containing samples, which are often only available in minute amounts. Therefore, highly sensitive workflows and detection methods are required. In this review mass spectrometric workflows and detection methods are evaluated for glycans and glycoproteins. Furthermore, glycomic methodologies and innovations that are tailored for enzymatic treatments, chemical derivatization, purification, separation, and detection at high sensitivity are highlighted. The discussion is focused on the analysis of mammalian N-linked and GalNAc-type O-linked glycans.

Aza-SAHA Derivatives Are Selective Histone Deacetylase 10 Chemical Probes That Inhibit Polyamine Deacetylation and Phenocopy HDAC10 Knockout

We report the first well-characterized selective chemical probe for histone deacetylase 10 (HDAC10) with unprecedented selectivity over other HDAC isozymes. HDAC10 deacetylates polyamines and has a distinct substrate specificity, making it unique among the 11 zinc-dependent HDAC hydrolases. Taking inspiration from HDAC10 polyamine substrates, we systematically inserted an amino group ("aza-scan") into the hexyl linker moiety of the approved drug Vorinostat (SAHA). This one-atom replacement (C→N) transformed SAHA from an unselective pan-HDAC inhibitor into a specific HDAC10 inhibitor. Optimization of the aza-SAHA structure yielded the HDAC10 chemical probe DKFZ-748, with potency and selectivity demonstrated by cellular and biochemical target engagement, as well as thermal shift assays. Cocrystal structures of our aza-SAHA derivatives with HDAC10 provide a structural rationale for potency, and chemoproteomic profiling confirmed exquisite cellular HDAC10-selectivity of DKFZ-748 across the target landscape of HDAC drugs. Treatment of cells with DKFZ-748, followed by quantification of selected polyamines, validated for the first time the suspected cellular function of HDAC10 as a polyamine deacetylase. Finally, in a polyamine-limiting in vitro tumor model, DKFZ-748 showed dose-dependent growth inhibition of HeLa cells. We expect DKFZ-748 and related probes to enable further studies on the enigmatic biology of HDAC10 and acetylated polyamines in both physiological and pathological settings.

Development and Characterization of Type I, Type II, and Type III LIM-Kinase Chemical Probes

LIMKs are important regulators of actin and microtubule dynamics, and they play essential roles in many cellular processes. Deregulation of LIMKs has been linked to the development of diverse diseases, including cancers and cognitive disabilities, but well-characterized inhibitors known as chemical probes are still lacking. Here, we report the characterization of three highly selective LIMK1/2 inhibitors covering all canonical binding modes (type I/II/III) and the structure-based design of the type II/III inhibitors. Characterization of these chemical probes revealed a low nanomolar affinity for LIMK1/2, and all inhibitors 1 (LIMKi3; type I), 48 (TH470; type II), and 15 (TH257; type III) showed excellent selectivity in a comprehensive scanMAX kinase selectivity panel. Phosphoproteomics revealed remarkable differences between type I and type II inhibitors compared with the allosteric inhibitor 15. In phenotypic assays such as neurite outgrowth models of fragile X-chromosome, 15 showed promising activity, suggesting the potential application of allosteric LIMK inhibitors treating this orphan disease.

The OTUD6B-LIN28B-MYC axis determines the proliferative state in multiple myeloma

Deubiquitylases (DUBs) are therapeutically amenable components of the ubiquitin machinery that stabilize substrate proteins. Their inhibition can destabilize oncoproteins that may otherwise be undruggable. Here, we screened for DUB vulnerabilities in multiple myeloma, an incurable malignancy with dependency on the ubiquitin proteasome system and identified OTUD6B as an oncogene that drives the G1/S‐transition. LIN28B, a suppressor of microRNA biogenesis, is specified as a bona fide cell cycle‐specific substrate of OTUD6B. Stabilization of LIN28B drives MYC expression at G1/S, which in turn allows for rapid S‐phase entry. Silencing OTUD6B or LIN28B inhibits multiple myeloma outgrowth in vivo and high OTUD6B expression evolves in patients that progress to symptomatic multiple myeloma and results in an adverse outcome of the disease. Thus, we link proteolytic ubiquitylation with post‐transcriptional regulation and nominate OTUD6B as a potential mediator of the MGUS‐multiple myeloma transition, a central regulator of MYC, and an actionable vulnerability in multiple myeloma and other tumors with an activated OTUD6B‐LIN28B axis.

Mass spectrometry-based draft of the mouse proteome

The laboratory mouse ranks among the most important experimental systems for biomedical research and molecular reference maps of such models are essential informational tools. Here, we present a quantitative draft of the mouse proteome and phosphoproteome constructed from 41 healthy tissues and several lines of analyses exemplify which insights can be gleaned from the data. For instance, tissue- and cell-type resolved profiles provide protein evidence for the expression of 17,000 genes, thousands of isoforms and 50,000 phosphorylation sites in vivo. Proteogenomic comparison of mouse, human and Arabidopsis reveal common and distinct mechanisms of gene expression regulation and, despite many similarities, numerous differentially abundant orthologs that likely serve species-specific functions. We leverage the mouse proteome by integrating phenotypic drug (n > 400) and radiation response data with the proteomes of 66 pancreatic ductal adenocarcinoma (PDAC) cell lines to reveal molecular markers for sensitivity and resistance. This unique atlas complements other molecular resources for the mouse and can be explored online via ProteomicsDB and PACiFIC.

Epigenetic drug screening defines a PRMT5 inhibitor-sensitive pancreatic cancer subtype

Systemic therapies for pancreatic ductal adenocarcinoma (PDAC) remain unsatisfactory. Clinical prognosis is particularly poor for tumor subtypes with activating aberrations in the MYC pathway, creating an urgent need for novel therapeutic targets. To unbiasedly find MYC-associated epigenetic dependencies, we conducted a drug screen in pancreatic cancer cell lines. Here, we found that protein arginine N-methyltransferase 5 (PRMT5) inhibitors triggered an MYC-associated dependency. In human and murine PDACs, a robust connection of MYC and PRMT5 was detected. By the use of gain- and loss-of-function models, we confirmed the increased efficacy of PRMT5 inhibitors in MYC-deregulated PDACs. Although inhibition of PRMT5 was inducing DNA damage and arresting PDAC cells in the G2/M phase of the cell cycle, apoptotic cell death was executed predominantly in cells with high MYC expression. Experiments in primary patient-derived PDAC models demonstrated the existence of a highly PRMT5 inhibitor-sensitive subtype. Our work suggests developing PRMT5 inhibitor-based therapies for PDAC.

Plant Proteome Dynamics

Proteins are intimately involved in executing and controlling virtually all cellular processes. To understand the molecular mechanisms that underlie plant phenotypes, it is essential to investigate protein expression, interactions, and modifications, to name a few. The proteome is highly dynamic in time and space, and a plethora of protein modifications, protein interactions, and network constellations are at play under specific conditions and developmental stages. Analysis of proteomes aims to characterize the entire protein complement of a particular cell type, tissue, or organism-a challenging task, given the dynamic nature of the proteome. Modern mass spectrometry-based proteomics technology can be used to address this complexity at a system-wide scale by the global identification and quantification of thousands of proteins. In this review, we present current methods and technologies employed in mass spectrometry-based proteomics and provide examples of dynamic changes in the plant proteome elucidated by proteomic approaches.

Prosit-TMT: Deep Learning Boosts Identification of TMT-Labeled Peptides

The prediction of fragment ion intensities and retention time of peptides has gained significant attention over the past few years. However, the progress shown in the accurate prediction of such properties focused primarily on unlabeled peptides. Tandem mass tags (TMT) are chemical peptide labels that are coupled to free amine groups usually after protein digestion to enable the multiplexed analysis of multiple samples in bottom-up mass spectrometry. It is a standard workflow in proteomics ranging from single-cell to high-throughput proteomics. Particularly for TMT, increasing the number of confidently identified spectra is highly desirable as it provides identification and quantification information with every spectrum. Here, we report on the generation of an extensive resource of synthetic TMT-labeled peptides as part of the ProteomeTools project and present the extension of the deep learning model Prosit to accurately predict the retention time and fragment ion intensities of TMT-labeled peptides with high accuracy. Prosit-TMT supports CID and HCD fragmentation and ion trap and Orbitrap mass analyzers in a single model. Reanalysis of published TMT data sets show that this single model extracts substantial additional information. Applying Prosit-TMT, we discovered that the expression of many proteins in human breast milk follows a distinct daily cycle which may prime the newborn for nutritional or environmental cues.

Target deconvolution of HDAC pharmacopoeia reveals MBLAC2 as common off-target

Histone deacetylase (HDAC) targeting drugs have entered the pharmacopoeia in the 2000s. However, some enigmatic phenotypes suggest off-target engagement. Here, we developed a quantitative chemical proteomics assay using immobilized HDAC inhibitors and mass spectrometry that we deployed to establish the target landscape of 53 drugs. The assay covers 9 of the 11 human zinc-dependent HDACs, questions the reported selectivity of some widely-used molecules, notably for HDAC6, and delineates how the composition of HDAC complexes influences drug potency. Unexpectedly, metallo-beta-lactamase domain-containing protein 2 (MBLAC2) featured as a frequent off-target of hydroxamate drugs. This poorly characterized palmitoyl-CoA hydrolase is inhibited by 24 HDAC inhibitors at low nM potency. MBLAC2 enzymatic inhibition and knock down led to the accumulation of extracellular vesicles. Given the importance of extracellular vesicle biology in neurological diseases and cancer, this HDAC-independent drug effect may qualify MBLAC2 as a target for drug discovery.

SIMSI-Transfer: Software-assisted reduction of missing values in phosphoproteomic and proteomic isobaric labeling data using tandem mass spectrum clustering

Isobaric stable isotope labeling techniques such as tandem mass tags (TMTs) have become popular in proteomics because they enable the relative quantification of proteins with high precision from up to 18 samples in a single experiment. While missing values in peptide quantification are rare in a single TMT experiment, they rapidly increase when combining multiple TMT experiments. As the field moves toward analyzing ever higher numbers of samples, tools that reduce missing values also become more important for analyzing TMT datasets. To this end, we developed SIMSI-Transfer (Similarity-based Isobaric Mass Spectra 2 [MS2] Identification Transfer), a software tool that extends our previously developed software MaRaCluster (© Matthew The) by clustering similar tandem MS2 from multiple TMT experiments. SIMSI-Transfer is based on the assumption that similarity-clustered MS2 spectra represent the same peptide. Therefore, peptide identifications made by database searching in one TMT batch can be transferred to another TMT batch in which the same peptide was fragmented but not identified. To assess the validity of this approach, we tested SIMSI-Transfer on masked search engine identification results and recovered >80% of the masked identifications while controlling errors in the transfer procedure to below 1% false discovery rate. Applying SIMSI-Transfer to six published full proteome and phosphoproteome datasets from the Clinical Proteomic Tumor Analysis Consortium led to an increase of 26 to 45% of identified MS2 spectra with TMT quantifications. This significantly decreased the number of missing values across batches and, in turn, increased the number of peptides and proteins identified in all TMT batches by 43 to 56% and 13 to 16%, respectively.

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Spectrum clustering enables peptide identification transfer between LC–MS/MS runs.

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The SIMSI pipeline supports processing full proteome and phosphoproteome data.

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SIMSI increases the number of quantifiable PSMs by 26 to 45%.

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SIMSI reduces missing values in multibatch TMT labeling experiments by up to 21%.

High temporal resolution proteome and phosphoproteome profiling of stem cell-derived hepatocyte development

Primary human hepatocytes are widely used to evaluate liver toxicity of drugs, but they are scarce and demanding to culture. Stem cell-derived hepatocytes are increasingly discussed as alternatives. To obtain a better appreciation of the molecular processes during the differentiation of induced pluripotent stem cells into hepatocytes, we employ a quantitative proteomic approach to follow the expression of 9,000 proteins, 12,000 phosphorylation sites, and 800 acetylation sites over time. The analysis reveals stage-specific markers, a major molecular switch between hepatic endoderm versus immature hepatocyte-like cells impacting, e.g., metabolism, the cell cycle, kinase activity, and the expression of drug transporters. Comparing the proteomes of two- (2D) and three-dimensional (3D)-derived hepatocytes with fetal and adult liver indicates a fetal-like status of the in vitro models and lower expression of important ADME/Tox proteins. The collective data enable constructing a molecular roadmap of hepatocyte development that serves as a valuable resource for future research.

Posttranslational modification of the RHO of plants protein RACB by phosphorylation and cross-kingdom conserved ubiquitination

Small RHO-type G-proteins act as signaling hubs and master regulators of polarity in eukaryotic cells. Their activity is tightly controlled, as defective RHO signaling leads to aberrant growth and developmental defects. Two major processes regulate G-protein activity: canonical shuttling between different nucleotide bound states and posttranslational modification (PTM), of which the latter can support or suppress RHO signaling, depending on the individual PTM. In plants, regulation of Rho of plants (ROPs) signaling activity has been shown to act through nucleotide exchange and GTP hydrolysis, as well as through lipid modification, but there is little data available on phosphorylation or ubiquitination of ROPs. Hence, we applied proteomic analyses to identify PTMs of the barley ROP RACB. We observed in vitro phosphorylation by barley ROP binding kinase 1 and in vivo ubiquitination of RACB. Comparative analyses of the newly identified RACB phosphosites and human RHO protein phosphosites revealed conservation of modified amino acid residues, but no overlap of actual phosphorylation patterns. However, the identified RACB ubiquitination site is conserved in all ROPs from Hordeum vulgare, Arabidopsis thaliana and Oryza sativa and in mammalian Rac1 and Rac3. Point mutation of this ubiquitination site leads to stabilization of RACB. Hence, this highly conserved lysine residue may regulate protein stability across different kingdoms.

On the potential of micro-flow LC-MS/MS in proteomics

INTRODUCTION

Due to its excellent sensitivity, nano-flow liquid chromatography tandem mass spectrometry (LC-MS/MS) is the mainstay in proteome research; however, this comes at the expense of limited throughput and robustness. In contrast, micro-flow LC-MS/MS enables high-throughput, robustness, quantitative reproducibility, and precision while retaining a moderate degree of sensitivity. Such features make it an attractive technology for a wide range of proteomic applications. In particular, large-scale projects involving the analysis of hundreds to thousands of samples.

AREAS COVERED

This review summarizes the history of chromatographic separation in discovery proteomics with a focus on micro-flow LC-MS/MS, discusses the current state-of-the-art, highlights advances in column development and instrumentation, and provides guidance on which LC flow best supports different types of proteomic applications.

EXPERT OPINION

Micro-flow LC-MS/MS will replace nano-flow LC-MS/MS in many proteomic applications, particularly when sample quantities are not limited and sample cohorts are large. Examples include clinical analyses of body fluids, tissues, drug discovery and chemical biology investigations, plus systems biology projects across all kingdoms of life. When combined with rapid and sensitive MS, intelligent data acquisition, and informatics approaches, it will soon become possible to analyze large cohorts of more than 10,000 samples in a comprehensive and fully quantitative fashion.

A novel Cereblon E3 ligase modulator with antitumor activity in gastrointestinal cancer

Targeted protein degradation offers new opportunities to inactivate cancer drivers and has successfully entered the clinic. Ways to induce selective protein degradation include proteolysis targeting chimera (PROTAC) technology and immunomodulatory (IMiDs) / next-generation Cereblon (CRBN) E3 ligase modulating drugs (CELMoDs). Here, we aimed to develop a MYC PROTAC based on the MYC-MAX dimerization inhibitor 10058-F4 derivative 28RH and Thalidomide, called MDEG-541. We show that a subgroup of gastrointestinal cancer cell lines and primary patient-derived organoids are MDEG-541 sensitive. Although MYC expression was regulated in a CRBN-, proteasome- and ubiquitin-dependent manner, we provide evidence that MDEG-541 induced the degradation of CRBN neosubstrates, including G1 to S phase transition 1/2 (GSPT1/2) and the Polo-like kinase 1 (PLK1). In sum, we have established a CRBN-dependent degrader of relevant cancer targets with activity in gastrointestinal cancers.

Proteomic profiling in cerebral amyloid angiopathy reveals an overlap with CADASIL highlighting accumulation of HTRA1 and its substrates

Cerebral amyloid angiopathy (CAA) is an age-related condition and a major cause of intracerebral hemorrhage and cognitive decline that shows close links with Alzheimer's disease (AD). CAA is characterized by the aggregation of amyloid-β (Aβ) peptides and formation of Aβ deposits in the brain vasculature resulting in a disruption of the angioarchitecture. Capillaries are a critical site of Aβ pathology in CAA type 1 and become dysfunctional during disease progression. Here, applying an advanced protocol for the isolation of parenchymal microvessels from post-mortem brain tissue combined with liquid chromatography tandem mass spectrometry (LC-MS/MS), we determined the proteomes of CAA type 1 cases (n = 12) including a patient with hereditary cerebral hemorrhage with amyloidosis-Dutch type (HCHWA-D), and of AD cases without microvascular amyloid pathology (n = 13) in comparison to neurologically healthy controls (n = 12). ELISA measurements revealed microvascular Aβ1-40 levels to be exclusively enriched in CAA samples (mean: > 3000-fold compared to controls). The proteomic profile of CAA type 1 was characterized by massive enrichment of multiple predominantly secreted proteins and showed significant overlap with the recently reported brain microvascular proteome of patients with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a hereditary cerebral small vessel disease (SVD) characterized by the aggregation of the Notch3 extracellular domain. We found this overlap to be largely attributable to the accumulation of high-temperature requirement protein A1 (HTRA1), a serine protease with an established role in the brain vasculature, and several of its substrates. Notably, this signature was not present in AD cases. We further show that HTRA1 co-localizes with Aβ deposits in brain capillaries from CAA type 1 patients indicating a pathologic recruitment process. Together, these findings suggest a central role of HTRA1-dependent protein homeostasis in the CAA microvasculature and a molecular connection between multiple types of brain microvascular disease.

ProteomicsDB: toward a FAIR open-source resource for life-science research

ProteomicsDB (https://www.ProteomicsDB.org) is a multi-omics and multi-organism resource for life science research. In this update, we present our efforts to continuously develop and expand ProteomicsDB. The major focus over the last two years was improving the findability, accessibility, interoperability and reusability (FAIR) of the data as well as its implementation. For this purpose, we release a new application programming interface (API) that provides systematic access to essentially all data in ProteomicsDB. Second, we release a new open-source user interface (UI) and show the advantages the scientific community gains from such software. With the new interface, two new visualizations of protein primary, secondary and tertiary structure as well an updated spectrum viewer were added. Furthermore, we integrated ProteomicsDB with our deep-neural-network Prosit that can predict the fragmentation characteristics and retention time of peptides. The result is an automatic processing pipeline that can be used to reevaluate database search engine results stored in ProteomicsDB. In addition, we extended the data content with experiments investigating different human biology as well as a newly supported organism.

PLK1-dependent phosphorylation restrains EBNA2 activity and lymphomagenesis in EBV-infected mice

While Epstein-Barr virus (EBV) establishes a life-long latent infection in apparently healthy human immunocompetent hosts, immunodeficient individuals are at particular risk to develop lymphoproliferative B-cell malignancies caused by EBV. A key EBV protein is the transcription factor EBV nuclear antigen 2 (EBNA2), which initiates B-cell proliferation. Here, we combine biochemical, cellular, and in vivo experiments demonstrating that the mitotic polo-like kinase 1 (PLK1) binds to EBNA2, phosphorylates its transactivation domain, and thereby inhibits its biological activity. EBNA2 mutants that impair PLK1 binding or prevent EBNA2 phosphorylation are gain-of-function mutants. They exhibit enhanced transactivation capacities, accelerate the proliferation of infected B cells, and promote the development of monoclonal B-cell lymphomas in infected mice. Thus, PLK1 coordinates the activity of EBNA2 to attenuate the risk of tumor incidences in favor of the establishment of latency in the infected but healthy host.

Evaluation of Disposable Trap Column nanoLC-FAIMS-MS/MS for the Proteomic Analysis of FFPE Tissue

Proteomic biomarker discovery using formalin-fixed paraffin-embedded (FFPE) tissue requires robust workflows to support the analysis of large cohorts of patient samples. It also requires finding a reasonable balance between achieving a high proteomic depth and limiting the overall analysis time. To this end, we evaluated the merits of online coupling of single-use disposable trap column nanoflow liquid chromatography, high-field asymmetric-waveform ion-mobility spectrometry (FAIMS), and tandem mass spectrometry (nLC-FAIMS-MS/MS). The data show that ≤600 ng of peptide digest should be loaded onto the chromatographic part of the system. Careful characterization of the FAIMS settings enabled the choice of optimal combinations of compensation voltages (CVs) as a function of the employed LC gradient time. We found nLC-FAIMS-MS/MS to be on par with StageTip-based off-line basic pH reversed-phase fractionation in terms of proteomic depth and reproducibility of protein quantification (coefficient of variation ≤15% for 90% of all proteins) but requiring 50% less sample and substantially reducing sample handling. Using FFPE materials from the lymph node, lung, and prostate tissue as examples, we show that nLC-FAIMS-MS/MS can identify 5000-6000 proteins from the respective tissue within a total of 3 h of analysis time.