Decrypting lysine deacetylase inhibitor action and protein modifications by dose-resolved proteomics.

Lysine deacetylase inhibitors (KDACis) are approved drugs for cutaneous T cell lymphoma (CTCL), peripheral T cell lymphoma (PTCL), and multiple myeloma, but many aspects of their cellular mechanism of action (MoA) and substantial toxicity are not well understood. To shed more light on how KDACis elicit cellular responses, we systematically measured dose-dependent changes in acetylation, phosphorylation, and protein expression in response to 21 clinical and pre-clinical KDACis. The resulting 862,000 dose-response curves revealed, for instance, limited cellular specificity of histone deacetylase (HDAC) 1, 2, 3, and 6 inhibitors; strong cross-talk between acetylation and phosphorylation pathways; localization of most drug-responsive acetylation sites to intrinsically disordered regions (IDRs); an underappreciated role of acetylation in protein structure; and a shift in EP300 protein abundance between the cytoplasm and the nucleus. This comprehensive dataset serves as a resource for the investigation of the molecular mechanisms underlying KDACi action in cells and can be interactively explored online in ProteomicsDB.

Multiomics Characterization of a Less Invasive Microfluidic-Based Cell Sorting Technique.

Fluorescence-activated cell sorting (FACS) is a specialized technique to isolate specific cell subpopulations with a high level of recovery and accuracy. However, the cell sorting procedure can impact the viability and metabolic state of cells. Here, we performed a comparative study and evaluated the impact of traditional high-pressure charged droplet-based and microfluidic chip-based sorting on the metabolic and phosphoproteomic profile of different cell types. While microfluidic chip-based sorted cells more closely resembled the unsorted control group for most cell types tested, the droplet-based sorted cells showed significant metabolic and phosphoproteomic alterations. In particular, greater changes in redox and energy status were present in cells sorted with the droplet-based cell sorter along with larger shifts in proteostasis. 13C-isotope tracing analysis on cells recovering postsorting revealed that the sorter-induced suppression of mitochondrial TCA cycle activity recovered faster in the microfluidic chip-based sorted group. Apart from this, amino acid and lipid biosynthesis pathways were suppressed in sorted cells, with minimum impact and faster recovery in the microfluidic chip-based sorted group. These results indicate microfluidic chip-based sorting has a minimum impact on metabolism and is less disruptive compared to droplet-based sorting.

A systems immunology study comparing innate and adaptive immune responses in adults to COVID-19 mRNA and adenovirus vectored vaccines.

Identifying the molecular mechanisms that promote optimal immune responses to coronavirus disease 2019 (COVID-19) vaccination is critical for future rational vaccine design. Here, we longitudinally profile innate and adaptive immune responses in 102 adults after the first, second, and third doses of mRNA or adenovirus-vectored COVID-19 vaccines. Using a multi-omics approach, we identify key differences in the immune responses induced by ChAdOx1-S and BNT162b2 that correlate with antigen-specific antibody and T cell responses or vaccine reactogenicity. Unexpectedly, we observe that vaccination with ChAdOx1-S, but not BNT162b2, induces an adenoviral vector-specific memory response after the first dose, which correlates with the expression of proteins with roles in thrombosis with potential implications for thrombosis with thrombocytopenia syndrome (TTS), a rare but serious adverse event linked to adenovirus-vectored vaccines. The COVID-19 Vaccine Immune Responses Study thus represents a major resource that can be used to understand the immunogenicity and reactogenicity of these COVID-19 vaccines.

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.

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.

Linking post-translational modifications and protein turnover by site-resolved protein turnover profiling.

Proteome-wide measurements of protein turnover have largely ignored the impact of post-translational modifications (PTMs). To address this gap, we employ stable isotope labeling and mass spectrometry to measure the turnover of >120,000 peptidoforms including >33,000 phosphorylated, acetylated, and ubiquitinated peptides for >9,000 native proteins. This site-resolved protein turnover (SPOT) profiling discloses global and site-specific differences in turnover associated with the presence or absence of PTMs. While causal relationships may not always be immediately apparent, we speculate that PTMs with diverging turnover may distinguish states of differential protein stability, structure, localization, enzymatic activity, or protein-protein interactions. We show examples of how the turnover data may give insights into unknown functions of PTMs and provide a freely accessible online tool that allows interrogation and visualisation of all turnover data. The SPOT methodology is applicable to many cell types and modifications, offering the potential to prioritize PTMs for future functional investigations.

The IMiD target CRBN determines HSP90 activity toward transmembrane proteins essential in multiple myeloma.

The complex architecture of transmembrane proteins requires quality control (QC) of folding, membrane positioning, and trafficking as prerequisites for cellular homeostasis and intercellular communication. However, it has remained unclear whether transmembrane protein-specific QC hubs exist. Here we identify cereblon (CRBN), the target of immunomodulatory drugs (IMiDs), as a co-chaperone that specifically determines chaperone activity of HSP90 toward transmembrane proteins by means of counteracting AHA1. This function is abrogated by IMiDs, which disrupt the interaction of CRBN with HSP90. Among the multiple transmembrane protein clients of CRBN-AHA1-HSP90 revealed by cell surface proteomics, we identify the amino acid transporter LAT1/CD98hc as a determinant of IMiD activity in multiple myeloma (MM) and present an Anticalin-based CD98hc radiopharmaceutical for MM radio-theranostics. These data establish the CRBN-AHA1-HSP90 axis in the biogenesis of transmembrane proteins, link IMiD activity to tumor metabolism, and nominate CD98hc and LAT1 as attractive diagnostic and therapeutic targets in MM.

PTPN2 Deficiency Enhances Programmed T Cell Expansion and Survival Capacity of Activated T Cells.

Manipulating molecules that impact T cell receptor (TCR) or cytokine signaling, such as the protein tyrosine phosphatase non-receptor type 2 (PTPN2), has significant potential for advancing T cell-based immunotherapies. Nonetheless, it remains unclear how PTPN2 impacts the activation, survival, and memory formation of T cells. We find that PTPN2 deficiency renders cells in vivo and in vitro less dependent on survival-promoting cytokines, such as interleukin (IL)-2 and IL-15. Remarkably, briefly ex vivo-activated PTPN2-deficient T cells accumulate in 3- to 11-fold higher numbers following transfer into unmanipulated, antigen-free mice. Moreover, the absence of PTPN2 augments the survival of short-lived effector T cells and allows them to robustly re-expand upon secondary challenge. Importantly, we find no evidence for impaired effector function or memory formation. Mechanistically, PTPN2 deficiency causes broad changes in the expression and phosphorylation of T cell expansion and survival-associated proteins. Altogether, our data underline the therapeutic potential of targeting PTPN2 in T cell-based therapies to augment the number and survival capacity of antigen-specific T cells.

Proteome activity landscapes of tumor cell lines determine drug responses.

Integrated analysis of genomes, transcriptomes, proteomes and drug responses of cancer cell lines (CCLs) is an emerging approach to uncover molecular mechanisms of drug action. We extend this paradigm to measuring proteome activity landscapes by acquiring and integrating quantitative data for 10,000 proteins and 55,000 phosphorylation sites (p-sites) from 125 CCLs. These data are used to contextualize proteins and p-sites and predict drug sensitivity. For example, we find that Progesterone Receptor (PGR) phosphorylation is associated with sensitivity to drugs modulating estrogen signaling such as Raloxifene. We also demonstrate that Adenylate kinase isoenzyme 1 (AK1) inactivates antimetabolites like Cytarabine. Consequently, high AK1 levels correlate with poor survival of Cytarabine-treated acute myeloid leukemia patients, qualifying AK1 as a patient stratification marker and possibly as a drug target. We provide an interactive web application termed ATLANTiC (http://atlantic.proteomics.wzw.tum.de), which enables the community to explore the thousands of novel functional associations generated by this work.

Data, Reagents, Assays and Merits of Proteomics for SARS-CoV-2 Research and Testing.

As the COVID-19 pandemic continues to spread, thousands of scientists around the globe have changed research direction to understand better how the virus works and to find out how it may be tackled. The number of manuscripts on preprint servers is soaring and peer-reviewed publications using MS-based proteomics are beginning to emerge. To facilitate proteomic research on SARS-CoV-2, the virus that causes COVID-19, this report presents deep-scale proteomes (10,000 proteins; >130,000 peptides) of common cell line models, notably Vero E6, Calu-3, Caco-2, and ACE2-A549 that characterize their protein expression profiles including viral entry factors such as ACE2 or TMPRSS2. Using the 9 kDa protein SRP9 and the breast cancer oncogene BRCA1 as examples, we show how the proteome expression data can be used to refine the annotation of protein-coding regions of the African green monkey and the Vero cell line genomes. Monitoring changes of the proteome on viral infection revealed widespread expression changes including transcriptional regulators, protease inhibitors, and proteins involved in innate immunity. Based on a library of 98 stable-isotope labeled synthetic peptides representing 11 SARS-CoV-2 proteins, we developed PRM (parallel reaction monitoring) assays for nano-flow and micro-flow LC-MS/MS. We assessed the merits of these PRM assays using supernatants of virus-infected Vero E6 cells and challenged the assays by analyzing two diagnostic cohorts of 24 (+30) SARS-CoV-2 positive and 28 (+9) negative cases. In light of the results obtained and including recent publications or manuscripts on preprint servers, we critically discuss the merits of MS-based proteomics for SARS-CoV-2 research and testing.

Meltome atlas-thermal proteome stability across the tree of life.

We have used a mass spectrometry-based proteomic approach to compile an atlas of the thermal stability of 48,000 proteins across 13 species ranging from archaea to humans and covering melting temperatures of 30-90 °C. Protein sequence, composition and size affect thermal stability in prokaryotes and eukaryotic proteins show a nonlinear relationship between the degree of disordered protein structure and thermal stability. The data indicate that evolutionary conservation of protein complexes is reflected by similar thermal stability of their proteins, and we show examples in which genomic alterations can affect thermal stability. Proteins of the respiratory chain were found to be very stable in many organisms, and human mitochondria showed close to normal respiration at 46 °C. We also noted cell-type-specific effects that can affect protein stability or the efficacy of drugs. This meltome atlas broadly defines the proteome amenable to thermal profiling in biology and drug discovery and can be explored online at http://meltomeatlas.proteomics.wzw.tum.de:5003/ and http://www.proteomicsdb.org.

Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC-MS/MS.

Nano-flow liquid chromatography tandem mass spectrometry (nano-flow LC-MS/MS) is the mainstay in proteome research because of its excellent sensitivity but often comes at the expense of robustness. Here we show that micro-flow LC-MS/MS using a 1 × 150 mm column shows excellent reproducibility of chromatographic retention time (<0.3% coefficient of variation, CV) and protein quantification (<7.5% CV) using data from >2000 samples of human cell lines, tissues and body fluids. Deep proteome analysis identifies >9000 proteins and >120,000 peptides in 16 h and sample multiplexing using tandem mass tags increases throughput to 11 proteomes in 16 h. The system identifies >30,000 phosphopeptides in 12 h and protein-protein or protein-drug interaction experiments can be analyzed in 20 min per sample. We show that the same column can be used to analyze >7500 samples without apparent loss of performance. This study demonstrates that micro-flow LC-MS/MS is suitable for a broad range of proteomic applications.

ProteomicsDB: a multi-omics and multi-organism resource for life science research.

ProteomicsDB (https://www.ProteomicsDB.org) started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data. In this manuscript, we summarize new developments since the previous update that was published in Nucleic Acids Research in 2017. Over the past two years, we have enriched the data content by additional datasets and extended the platform to support protein turnover data. Another important new addition is that ProteomicsDB now supports the storage and visualization of data collected from other organisms, exemplified by Arabidopsis thaliana. Due to the generic design of ProteomicsDB, all analytical features available for the original human resource seamlessly transfer to other organisms. Furthermore, we introduce a new service in ProteomicsDB which allows users to upload their own expression datasets and analyze them alongside with data stored in ProteomicsDB. Initially, users will be able to make use of this feature in the interactive heat map functionality as well as the drug sensitivity prediction, but ultimately will be able to use all analytical features of ProteomicsDB in this way.

Functional expression of electrogenic sodium bicarbonate cotransporter 1 (NBCe1) in mouse cortical astrocytes is dependent on S255-257 and regulated by mTOR.

The electrogenic sodium bicarbonate cotransporter 1, NBCe1 (SLC4A4), is the major bicarbonate transporter expressed in astrocytes. It is highly sensitive for bicarbonate and the main regulator of intracellular, extracellular, and synaptic pH, thereby modulating neuronal excitability. However, despite these essential functions, the molecular mechanisms underlying NBCe1-mediated astrocytic response to extracellular pH changes are mostly unknown. Using primary mouse cortical astrocyte cultures, we investigated the effect of long-term extracellular metabolic alkalosis on regulation of NBCe1 and elucidated the underlying molecular mechanisms by immunoblotting, biotinylation of surface proteins, intracellular H+ recording using the H+ -sensitive dye 2',7'-bis-(carboxyethyl)-5-(and-6)-carboxyfluorescein, and phosphoproteomic analysis. The results showed significant downregulation of NBCe1 activity following metabolic alkalosis without influencing protein abundance or surface expression of NBCe1. During alkalosis, the rate of intracellular H+ changes upon challenging NBCe1 was decreased in wild-type astrocytes, but not in cortical astrocytes from NBCe1-deficient mice. Alkalosis-induced decrease of NBCe1 activity was rescued after activation of mTOR signaling. Moreover, mass spectrometry revealed constitutively phosphorylated S255-257 and mutational analysis uncovered these residues being crucial for NBCe1 transport activity. Our results demonstrate a novel mTOR-regulated mechanism by which NBCe1 functional expression is regulated. Such mechanism likely applies not only for NBCe1 in astrocytes, but in epithelial cells as well.

TMT Labeling for the Masses: A Robust and Cost-efficient, In-solution Labeling Approach.

Isobaric stable isotope labeling using, for example, tandem mass tags (TMTs) is increasingly being applied for large-scale proteomic studies. Experiments focusing on proteoform analysis in drug time course or perturbation studies or in large patient cohorts greatly benefit from the reproducible quantification of single peptides across samples. However, such studies often require labeling of hundreds of micrograms of peptides such that the cost for labeling reagents represents a major contribution to the overall cost of an experiment. Here, we describe and evaluate a robust and cost-effective protocol for TMT labeling that reduces the quantity of required labeling reagent by a factor of eight and achieves complete labeling. Under- and overlabeling of peptides derived from complex digests of tissues and cell lines were systematically evaluated using peptide quantities of between 12.5 and 800 µg and TMT-to-peptide ratios (wt/wt) ranging from 8:1 to 1:2 at different TMT and peptide concentrations. When reaction volumes were reduced to maintain TMT and peptide concentrations of at least 10 mm and 2 g/l, respectively, TMT-to-peptide ratios as low as 1:1 (wt/wt) resulted in labeling efficiencies of > 99% and excellent intra- and interlaboratory reproducibility. The utility of the optimized protocol was further demonstrated in a deep-scale proteome and phosphoproteome analysis of patient-derived xenograft tumor tissue benchmarked against the labeling procedure recommended by the TMT vendor. Finally, we discuss the impact of labeling reaction parameters for N-hydroxysuccinimide ester-based chemistry and provide guidance on adopting efficient labeling protocols for different peptide quantities.

A deep proteome and transcriptome abundance atlas of 29 healthy human tissues.

Genome-, transcriptome- and proteome-wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we generated a quantitative proteome and transcriptome abundance atlas of 29 paired healthy human tissues from the Human Protein Atlas project representing human genes by 18,072 transcripts and 13,640 proteins including 37 without prior protein-level evidence. The analysis revealed that hundreds of proteins, particularly in testis, could not be detected even for highly expressed mRNAs, that few proteins show tissue-specific expression, that strong differences between mRNA and protein quantities within and across tissues exist and that protein expression is often more stable across tissues than that of transcripts. Only 238 of 9,848 amino acid variants found by exome sequencing could be confidently detected at the protein level showing that proteogenomics remains challenging, needs better computational methods and requires rigorous validation. Many uses of this resource can be envisaged including the study of gene/protein expression regulation and biomarker specificity evaluation.

Peptide Level Turnover Measurements Enable the Study of Proteoform Dynamics.

The coordination of protein synthesis and degradation regulating protein abundance is a fundamental process in cellular homeostasis. Today, mass spectrometry-based technologies allow determination of endogenous protein turnover on a proteome-wide scale. However, standard dynamic SILAC (Stable Isotope Labeling in Cell Culture) approaches can suffer from missing data across pulse time-points limiting the accuracy of such analysis. This issue is of particular relevance when studying protein stability at the level of proteoforms because often only single peptides distinguish between different protein products of the same gene. To address this shortcoming, we evaluated the merits of combining dynamic SILAC and tandem mass tag (TMT)-labeling of ten pulse time-points in a single experiment. Although the comparison to the standard dynamic SILAC method showed a high concordance of protein turnover rates, the pulsed SILAC-TMT approach yielded more comprehensive data (6000 proteins on average) without missing values. Replicate analysis further established that the same reproducibility of turnover rate determination can be obtained for peptides and proteins facilitating proteoform resolved investigation of protein stability. We provide several examples of differentially turned over splice variants and show that post-translational modifications can affect cellular protein half-lives. For example, N-terminally processed peptides exhibited both faster and slower turnover behavior compared with other peptides of the same protein. In addition, the suspected proteolytic processing of the fusion protein FAU was substantiated by measuring vastly different stabilities of the cleavage products. Furthermore, differential peptide turnover suggested a previously unknown mechanism of activity regulation by post-translational destabilization of cathepsin D as well as the DNA helicase BLM. Finally, our comprehensive data set facilitated a detailed evaluation of the impact of protein properties and functions on protein stability in steady-state cells and uncovered that the high turnover of respiratory chain complex I proteins might be explained by oxidative stress.

The target landscape of clinical kinase drugs.

Kinase inhibitors are important cancer therapeutics. Polypharmacology is commonly observed, requiring thorough target deconvolution to understand drug mechanism of action. Using chemical proteomics, we analyzed the target spectrum of 243 clinically evaluated kinase drugs. The data revealed previously unknown targets for established drugs, offered a perspective on the "druggable" kinome, highlighted (non)kinase off-targets, and suggested potential therapeutic applications. Integration of phosphoproteomic data refined drug-affected pathways, identified response markers, and strengthened rationale for combination treatments. We exemplify translational value by discovering SIK2 (salt-inducible kinase 2) inhibitors that modulate cytokine production in primary cells, by identifying drugs against the lung cancer survival marker MELK (maternal embryonic leucine zipper kinase), and by repurposing cabozantinib to treat FLT3-ITD-positive acute myeloid leukemia. This resource, available via the ProteomicsDB database, should facilitate basic, clinical, and drug discovery research and aid clinical decision-making.

Lapatinib Resistance in Breast Cancer Cells Is Accompanied by Phosphorylation-Mediated Reprogramming of Glycolysis.

HER2/ERBB2-overexpressing breast cancers targeted effectively by the small-molecule kinase inhibitor lapatinib frequently acquire resistance to this drug. In this study, we employed explorative mass spectrometry to profile proteome, kinome, and phosphoproteome changes in an established model of lapatinib resistance to systematically investigate initial inhibitor response and subsequent reprogramming in resistance. The resulting dataset, which collectively contains quantitative data for >7,800 proteins, >300 protein kinases, and >15,000 phosphopeptides, enabled deep insight into signaling recovery and molecular reprogramming upon resistance. Our data-driven approach confirmed previously described mechanisms of resistance (e.g., AXL overexpression and PIK3 reactivation), revealed novel pharmacologically actionable targets, and confirmed the expectation of significant heterogeneity in molecular resistance drivers inducing distinct phenotypic changes. Furthermore, our approach identified an extensive and exclusively phosphorylation-mediated reprogramming of glycolytic activity, supported additionally by widespread changes of corresponding metabolites and an increased sensitivity towards glycolysis inhibition. Collectively, our multi-omic analysis offers deeper perspectives on cancer drug resistance and suggests new biomarkers and treatment options for lapatinib-resistant cancers. Cancer Res; 77(8); 1842-53. ©2017 AACR.

High pH Reversed-Phase Micro-Columns for Simple, Sensitive, and Efficient Fractionation of Proteome and (TMT labeled) Phosphoproteome Digests.

Despite recent advances in mass spectrometric sequencing speed and improved sensitivity, the in-depth analysis of proteomes still widely relies on off-line peptide separation and fractionation to deal with the enormous molecular complexity of shotgun digested proteomes. While a multitude of methods has been established for off-line peptide separation using HPLC columns, their use can be limited particularly when sample quantities are scarce. In this protocol, we describe an approach which combines high pH reversed-phase peptide separation into few fractions in StageTip micro-columns. This miniaturized sample preparation method enhances peptide recovery and hence improves sensitivity. This is particularly useful when working with limited sample amounts obtained from e.g., phosphopeptide enrichments or tissue biopsies. Essentially the same approach can also be applied for multiplexed analysis using tandem mass tags (TMT) and can be parallelized in order to deliver the required throughput. Here, we provide a step-by-step protocol for TMT6plex labeling of peptides, the construction of StageTips, sample fractionation and pooling schemes adjusted to different types of analytes, mass spectrometric sample measurement, and downstream data processing using MaxQuant. To illustrate the expected results using this protocol, we provide results from an unlabeled and a TMT6plex labeled phosphopeptide sample leading to the identification of >17,000 phosphopeptides in 8 h (Q Exactive HF) and >23,000 TMT6plex labeled phosphopeptides (Q Exactive Plus) in 12 h of measurement time. Importantly, this protocol is equally applicable to the fractionation of full proteome digests.