Ubiquitin Ligase COP1 Suppresses Neuroinflammation by Degrading c/EBPß in Microglia.

Dysregulated microglia are intimately involved in neurodegeneration, including Alzheimer's disease (AD) pathogenesis, but the mechanisms controlling pathogenic microglial gene expression remain poorly understood. The transcription factor CCAAT/enhancer binding protein beta (c/EBPß) regulates pro-inflammatory genes in microglia and is upregulated in AD. We show expression of c/EBPß in microglia is regulated post-translationally by the ubiquitin ligase COP1 (also called RFWD2). In the absence of COP1, c/EBPß accumulates rapidly and drives a potent pro-inflammatory and neurodegeneration-related gene program, evidenced by increased neurotoxicity in microglia-neuronal co-cultures. Antibody blocking studies reveal that neurotoxicity is almost entirely attributable to complement. Remarkably, loss of a single allele of Cebpb prevented the pro-inflammatory phenotype. COP1-deficient microglia markedly accelerated tau-mediated neurodegeneration in a mouse model where activated microglia play a deleterious role. Thus, COP1 is an important suppressor of pathogenic c/EBPß-dependent gene expression programs in microglia.

Quantitative Proteomics of the Cancer Cell Line Encyclopedia.

Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.

Dynamic Regulation of Mitochondrial Import by the Ubiquitin System.

Mitochondria import nearly their entire proteome from the cytoplasm by translocating precursor proteins through the translocase of the outer membrane (TOM) complex. Here, we show dynamic regulation of mitochondrial import by the ubiquitin system. Acute pharmacological inhibition or genetic ablation of the mitochondrial deubiquitinase (DUB) USP30 triggers accumulation of Ub-substrates that are normally localized inside the mitochondria. Mitochondrial import of USP30 substrates is impaired in USP30 knockout (KO) cells, suggesting that deubiquitination promotes efficient import. Upstream of USP30, the E3 ligase March5 ubiquitinates mitochondrial proteins whose eventual import depends on USP30. In USP30 KOs, exogenous March5 expression induces accumulation of unimported translocation intermediates that are degraded by the proteasomes. In USP30 KO mice, TOM subunits have reduced abundance across multiple tissues. Together these data highlight how protein import into a subcellular compartment can be regulated by ubiquitination and deubiquitination by E3 ligase and DUB machinery positioned at the gate.

PIKES Analysis Reveals Response to Degraders and Key Regulatory Mechanisms of the CRL4 Network.

Co-opting Cullin4 RING ubiquitin ligases (CRL4s) to inducibly degrade pathogenic proteins is emerging as a promising therapeutic strategy. Despite intense efforts to rationally design degrader molecules that co-opt CRL4s, much about the organization and regulation of these ligases remains elusive. Here, we establish protein interaction kinetics and estimation of stoichiometries (PIKES) analysis, a systematic proteomic profiling platform that integrates cellular engineering, affinity purification, chemical stabilization, and quantitative mass spectrometry to investigate the dynamics of interchangeable multiprotein complexes. Using PIKES, we show that ligase assemblies of Cullin4 with individual substrate receptors differ in abundance by up to 200-fold and that Cand1/2 act as substrate receptor exchange factors. Furthermore, degrader molecules can induce the assembly of their cognate CRL4, and higher expression of the associated substrate receptor enhances degrader potency. Beyond the CRL4 network, we show how PIKES can reveal systems level biochemistry for cellular protein networks important to drug development.

Stress-induced vesicular assemblies of dual leucine zipper kinase are signaling hubs involved in kinase activation and neurodegeneration.

Mitogen-activated protein kinases (MAPKs) drive key signaling cascades during neuronal survival and degeneration. The localization of kinases to specific subcellular compartments is a critical mechanism to locally control signaling activity and specificity upon stimulation. However, how MAPK signaling components tightly control their localization remains largely unknown. Here, we systematically analyzed the phosphorylation and membrane localization of all MAPKs expressed in dorsal root ganglia (DRG) neurons, under control and stress conditions. We found that MAP3K12/dual leucine zipper kinase (DLK) becomes phosphorylated and palmitoylated, and it is recruited to sphingomyelin-rich vesicles upon stress. Stress-induced DLK vesicle recruitment is essential for kinase activation; blocking DLK-membrane interaction inhibits downstream signaling, while DLK recruitment to ectopic subcellular structures is sufficient to induce kinase activation. We show that the localization of DLK to newly formed vesicles is essential for local signaling. Inhibition of membrane internalization blocks DLK activation and protects against neurodegeneration in DRG neurons. These data establish vesicular assemblies as dynamically regulated platforms for DLK signaling during neuronal stress responses.

Single-cell proteomics enabled by next-generation sequencing or mass spectrometry.

In the last decade, single-cell RNA sequencing routinely performed on large numbers of single cells has greatly advanced our understanding of the underlying heterogeneity of complex biological systems. Technological advances have also enabled protein measurements, further contributing to the elucidation of cell types and states present in complex tissues. Recently, there have been independent advances in mass spectrometric techniques bringing us one step closer to characterizing single-cell proteomes. Here we discuss the challenges of detecting proteins in single cells by both mass spectrometry and sequencing-based methods. We review the state of the art for these techniques and propose that there is a space for technological advancements and complementary approaches that maximize the advantages of both classes of technologies.

Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments.

Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories. Here we propose best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics. Resources and discussion forums are available at https://single-cell.net/guidelines .

Graph-pMHC: graph neural network approach to MHC class II peptide presentation and antibody immunogenicity.

Antigen presentation on MHC class II (pMHCII presentation) plays an essential role in the adaptive immune response to extracellular pathogens and cancerous cells. But it can also reduce the efficacy of large-molecule drugs by triggering an anti-drug response. Significant progress has been made in pMHCII presentation modeling due to the collection of large-scale pMHC mass spectrometry datasets (ligandomes) and advances in machine learning. Here, we develop graph-pMHC, a graph neural network approach to predict pMHCII presentation. We derive adjacency matrices for pMHCII using Alphafold2-multimer and address the peptide-MHC binding groove alignment problem with a simple graph enumeration strategy. We demonstrate that graph-pMHC dramatically outperforms methods with suboptimal inductive biases, such as the multilayer-perceptron-based NetMHCIIpan-4.0 (+20.17% absolute average precision). Finally, we create an antibody drug immunogenicity dataset from clinical trial data and develop a method for measuring anti-antibody immunogenicity risk using pMHCII presentation models. Our model increases receiver operating characteristic curve (ROC)-area under the ROC curve (AUC) by 2.57% compared to just filtering peptides by hits in OASis alone for predicting antibody drug immunogenicity.

Context-Specific Stress Causes Compartmentalized SARM1 Activation and Local Degeneration in Cortical Neurons.

Sterile alpha and TIR motif containing 1 (SARM1) is an inducible NADase that localizes to mitochondria throughout neurons and senses metabolic changes that occur after injury. Minimal proteomic changes are observed upon either SARM1 depletion or activation, suggesting that SARM1 does not exert broad effects on neuronal protein homeostasis. However, whether SARM1 activation occurs throughout the neuron in response to injury and cell stress remains largely unknown. Using a semiautomated imaging pipeline and a custom-built deep learning scoring algorithm, we studied degeneration in both mixed-sex mouse primary cortical neurons and male human-induced pluripotent stem cell-derived cortical neurons in response to a number of different stressors. We show that SARM1 activation is differentially restricted to specific neuronal compartments depending on the stressor. Cortical neurons undergo SARM1-dependent axon degeneration after mechanical transection, and SARM1 activation is limited to the axonal compartment distal to the injury site. However, global SARM1 activation following vacor treatment causes both cell body and axon degeneration. Context-specific stressors, such as microtubule dysfunction and mitochondrial stress, induce axonal SARM1 activation leading to SARM1-dependent axon degeneration and SARM1-independent cell body death. Our data reveal that compartment-specific SARM1-mediated death signaling is dependent on the type of injury and cellular stressor.

A Strategy to Combine Sample Multiplexing with Targeted Proteomics Assays for High-Throughput Protein Signature Characterization.

Targeted mass spectrometry assays for protein quantitation monitor peptide surrogates, which are easily multiplexed to target many peptides in a single assay. However, these assays have generally not taken advantage of sample multiplexing, which allows up to ten analyses to occur in parallel. We present a two-dimensional multiplexing workflow that utilizes synthetic peptides for each protein to prompt the simultaneous quantification of >100 peptides from up to ten mixed sample conditions. We demonstrate that targeted analysis of unfractionated lysates (2 hr) accurately reproduces the quantification of fractionated lysates (72 hr analysis) while obviating the need for peptide detection prior to quantification. We targeted 131 peptides corresponding to 69 proteins across all 60 National Cancer Institute cell lines in biological triplicate, analyzing 180 samples in only 48 hr (the equivalent of 16 min/sample). These data further elucidated a correlation between the expression of key proteins and their cellular response to drug treatment.

Increasing the Throughput and Reproducibility of Activity-Based Proteome Profiling Studies with Hyperplexing and Intelligent Data Acquisition.

Intelligent data acquisition (IDA) strategies, such as a real-time database search (RTS), have improved the depth of proteome coverage for experiments that utilize isobaric labels and gas phase purification techniques (i.e., SPS-MS3). In this work, we introduce inSeqAPI, an instrument application programing interface (iAPI) program that enables construction of novel data acquisition algorithms. First, we analyze biotinylated cysteine peptides from ABPP experiments to demonstrate that a real-time search method within inSeqAPI performs similarly to an equivalent vendor method. Then, we describe PairQuant, a method within inSeqAPI designed for the hyperplexing approach that utilizes protein-level isotopic labeling and peptide-level TMT labeling. PairQuant allows for TMT analysis of 36 conditions in a single sample and achieves ∼98% coverage of both peptide pair partners in a hyperplexed experiment as well as a 40% improvement in the number of quantified cysteine sites compared with non-RTS acquisition. We applied this method in the ABPP study of ligandable cysteine sites in the nucleus leading to an identification of additional druggable sites on protein- and DNA-interaction domains of transcription regulators and on nuclear ubiquitin ligases.

Defining the carrier proteome limit for single-cell proteomics.

Single-cell proteomics by mass spectrometry (SCoPE-MS) is a recently introduced method to quantify multiplexed single-cell proteomes. While this technique has generated great excitement, the underlying technologies (isobaric labeling and mass spectrometry (MS)) have technical limitations with the potential to affect data quality and biological interpretation. These limitations are particularly relevant when a carrier proteome, a sample added at 25-500× the amount of a single-cell proteome, is used to enable peptide identifications. Here we perform controlled experiments with increasing carrier proteome amounts and evaluate quantitative accuracy, as it relates to mass analyzer dynamic range, multiplexing level and number of ions sampled. We demonstrate that an increase in carrier proteome level requires a concomitant increase in the number of ions sampled to maintain quantitative accuracy. Lastly, we introduce Single-Cell Proteomics Companion (SCPCompanion), a software tool that enables rapid evaluation of single-cell proteomic data and recommends instrument and data analysis parameters for improved data quality.

Primate cerebrospinal fluid CHI3L1 reflects brain TREM2 agonism.

INTRODUCTION: Triggering receptor expressed on myeloid cells 2 (TREM2) agonists are being clinically evaluated as disease-modifying therapeutics for Alzheimer's disease. Clinically translatable pharmacodynamic (PD) biomarkers are needed to confirm drug activity and select the appropriate therapeutic dose in clinical trials. METHODS: We conducted multi-omic analyses on paired non-human primate brain and cerebrospinal fluid (CSF), and stimulation of human induced pluripotent stem cell-derived microglia cultures after TREM2 agonist treatment, followed by validation of candidate fluid PD biomarkers using immunoassays. We immunostained microglia to characterize proliferation and clustering. RESULTS: We report CSF soluble TREM2 (sTREM2) and CSF chitinase-3-like protein 1 (CHI3L1/YKL-40) as PD biomarkers for the TREM2 agonist hPara.09. The respective reduction of sTREM2 and elevation of CHI3L1 in brain and CSF after TREM2 agonist treatment correlated with transient microglia proliferation and clustering. DISCUSSION: CSF CHI3L1 and sTREM2 reflect microglial TREM2 agonism and can be used as clinical PD biomarkers to monitor TREM2 activity in the brain. HIGHLIGHTS: CSF soluble triggering receptor expressed on myeloid cells 2 (sTREM2) reflects brain target engagement for a novel TREM2 agonist, hPara.09. CSF chitinase-3-like protein 1 reflects microglial TREM2 agonism. Both can be used as clinical fluid biomarkers to monitor TREM2 activity in brain.

AzidoTMT Enables Direct Enrichment and Highly Multiplexed Quantitation of Proteome-Wide Functional Residues.

Recent advances in targeted covalent inhibitors have aroused significant interest for their potential in drug development for difficult therapeutic targets. Proteome-wide profiling of functional residues is an integral step of covalent drug discovery aimed at defining actionable sites and evaluating compound selectivity in cells. A classical workflow for this purpose is called IsoTOP-ABPP, which employs an activity-based probe and two isotopically labeled azide-TEV-biotin tags to mark, enrich, and quantify proteome from two samples. Here we report a novel isobaric 11plex-AzidoTMT reagent and a new workflow, named AT-MAPP, that significantly expands multiplexing power as compared to the original isoTOP-ABPP. We demonstrate its application in identifying cysteine on- and off-targets using a KRAS G12C covalent inhibitor ARS-1620. However, changes in some of these hits can be explained by modulation at the protein and post-translational levels. Thus, it would be crucial to interrogate site-level bona fide changes in concurrence to proteome-level changes for corroboration. In addition, we perform a multiplexed covalent fragment screening using four acrylamide-based compounds as a proof-of-concept. This study identifies a diverse set of liganded cysteine residues in a compound-dependent manner with an average hit rate of 0.07% in intact cell. Lastly, we screened 20 sulfonyl fluoride-based compounds to demonstrate that the AT-MAPP assay is flexible for noncysteine functional residues such as tyrosine and lysine. Overall, we envision that 11plex-AzidoTMT will be a useful addition to the current toolbox for activity-based protein profiling and covalent drug development.

Targeting MCL-1 and BCL-2 with polatuzumab vedotin and venetoclax overcomes treatment resistance in R/R non-Hodgkin lymphoma: Results from preclinical models and a Phase Ib study.

The treatment of patients with relapsed or refractory lymphoid neoplasms represents a significant clinical challenge. Here, we identify the pro-survival BCL-2 protein family member MCL-1 as a resistance factor for the BCL-2 inhibitor venetoclax in non-Hodgkin lymphoma (NHL) cell lines and primary NHL samples. Mechanistically, we show that the antibody-drug conjugate polatuzumab vedotin promotes MCL-1 degradation via the ubiquitin/proteasome system. This targeted MCL-1 antagonism, when combined with venetoclax and the anti-CD20 antibodies obinutuzumab or rituximab, results in tumor regressions in preclinical NHL models, which are sustained even off-treatment. In a Phase Ib clinical trial (NCT02611323) of heavily pre-treated patients with relapsed or refractory NHL, 25/33 (76%) patients with follicular lymphoma and 5/17 (29%) patients with diffuse large B-cell lymphoma achieved complete or partial responses with an acceptable safety profile when treated with the recommended Phase II dose of polatuzumab vedotin in combination with venetoclax and an anti-CD20 antibody.

Prolonged Mek1/2 suppression impairs the developmental potential of embryonic stem cells.

Concomitant activation of the Wnt pathway and suppression of Mapk signalling by two small molecule inhibitors (2i) in the presence of leukaemia inhibitory factor (LIF) (hereafter termed 2i/L) induces a naive state in mouse embryonic stem (ES) cells that resembles the inner cell mass (ICM) of the pre-implantation embryo. Since the ICM exists only transiently in vivo, it remains unclear how sustained propagation of naive ES cells in vitro affects their stability and functionality. Here we show that prolonged culture of male mouse ES cells in 2i/L results in irreversible epigenetic and genomic changes that impair their developmental potential. Furthermore, we find that female ES cells cultured in conventional serum plus LIF medium phenocopy male ES cells cultured in 2i/L. Mechanistically, we demonstrate that the inhibition of Mek1/2 is predominantly responsible for these effects, in part through the downregulation of DNA methyltransferases and their cofactors. Finally, we show that replacement of the Mek1/2 inhibitor with a Src inhibitor preserves the epigenetic and genomic integrity as well as the developmental potential of ES cells. Taken together, our data suggest that, although short-term suppression of Mek1/2 in ES cells helps to maintain an ICM-like epigenetic state, prolonged suppression results in irreversible changes that compromise their developmental potential.

Sensitive and Quantitative Detection of MHC-I Displayed Neoepitopes Using a Semiautomated Workflow and TOMAHAQ Mass Spectrometry.

Advances in several key technologies, including MHC peptidomics, have helped fuel our understanding of basic immune regulatory mechanisms and the identification of T cell receptor targets for the development of immunotherapeutics. Isolating and accurately quantifying MHC-bound peptides from cells and tissues enables characterization of dynamic changes in the ligandome due to cellular perturbations. However, the current multistep analytical process is challenging, and improvements in throughput and reproducibility would enable rapid characterization of multiple conditions in parallel. Here, we describe a robust and quantitative method whereby peptides derived from MHC-I complexes from a variety of cell lines, including challenging adherent lines such as MC38, can be enriched in a semiautomated fashion on reusable, dry-storage, customized antibody cartridges. Using this method, a researcher, with very little hands-on time and in a single day, can perform up to 96 simultaneous enrichments at a similar level of quality as a manual workflow. TOMAHAQ (Triggered by Offset, Multiplexed, Accurate-mass, High-resolution, and Absolute Quantification), a targeted mass spectrometry technique that combines sample multiplexing and high sensitivity, was employed to characterize neoepitopes displayed on MHC-I by tumor cells and to quantitatively assess the influence of neoantigen expression and induced degradation on neoepitope presentation. This unique combination of robust semiautomated MHC-I peptide isolation and high-throughput multiplexed targeted quantitation allows for both the routine analysis of >4000 unique MHC-I peptides from 250 million cells using nontargeted methods, as well as quantitative sensitivity down to the low amol/µl level using TOMAHAQ targeted MS.

Understanding the effect of carrier proteomes in single cell proteomic studies - key lessons.

INTRODUCTION: Mass spectrometry-based single-cell proteomics (scMS) is experiencing rapid evolution due to the increased sensitivity of mass spectrometers as well as advances in multiplexing and sample preparation. To date, researchers have focused on two general approaches to scMS: label-free and isobaric label-based multiplexing. While label-free analysis provides straightforward sample preparation and a clear path to automation, it currently lacks the throughput necessary to practically analyze thousands of single cells. Multiplexed analysis utilizing isobaric labels requires additional sample manipulation but increases throughput such that analyzing thousands of cells is currently achievable. A key feature of multiplexed scMS experiments is a 'carrier proteome' - a sample added at 25x-500x, the single-cell sample that increases the number of proteins that can be identified in an MS analysis. AREAS COVERED: Here, we review early examples of carrier proteomes in quantitative proteomics before summarizing advantages and challenges of using a carrier proteome in scMS experiments. EXPERT OPINION: We conclude that the addition of carrier proteomes improves depth of identification for scMS, but high levels of carrier proteomes can have adverse effects on quantitative accuracy and precision.

Proteomics in the pharmaceutical and biotechnology industry: a look to the next decade.

INTRODUCTION: Pioneering technologies such as proteomics have helped fuel the biotechnology and pharmaceutical industry with the discovery of novel targets and an intricate understanding of the activity of therapeutics and their various activities in vitro and in vivo. The field of proteomics is undergoing an inflection point, where new sensitive technologies are allowing intricate biological pathways to be better understood, and novel biochemical tools are pivoting us into a new era of chemical proteomics and biomarker discovery. In this review, we describe these areas of innovation, and discuss where the fields are headed in terms of fueling biotechnological and pharmacological research and discuss current gaps in the proteomic technology landscape. AREAS COVERED: Single cell sequencing and single molecule sequencing. Chemoproteomics. Biological matrices and clinical samples including biomarkers. Computational tools including instrument control software, data analysis. EXPERT OPINION: Proteomics will likely remain a key technology in the coming decade, but will have to evolve with respect to type and granularity of data, cost and throughput of data generation as well as integration with other technologies to fulfill its promise in drug discovery.

TomahaqCompanion: A Tool for the Creation and Analysis of Isobaric Label Based Multiplexed Targeted Assays.

Triggered by Offset, Multiplexed, Accurate mass, High resolution, and Absolute Quantitation (TOMAHAQ) is a recently introduced targeted proteomics method that combines peptide and sample multiplexing. TOMAHAQ assays enable sensitive and accurate multiplexed quantification by implementing an intricate data collection scheme that comprises multiple MSn scans, mass inclusion lists, and data-driven filters. Consequently, manual creation of TOMAHAQ methods can be time-consuming and error prone, while the resulting TOMAHAQ data may not be compatible with common mass spectrometry analysis pipelines. To address these concerns we introduce TomahaqCompanion, an open-source desktop application that enables rapid creation of TOMAHAQ methods and analysis of TOMAHAQ data. Starting from a list of peptide sequences, a user can perform each step of TOMAHAQ assay development including (1) generation of priming run target list, (2) analysis of priming run data, (3) generation of TOMAHAQ method file, and (4) analysis and export of quantitative TOMAHAQ data. We demonstrate the flexibility of TomahaqCompanion by creating a variety of methods testing TOMAHAQ parameters (e.g., number of SPS notches, run length, etc.). Lastly, we analyze an interference sample comprising heavy yeast peptides, a standard human peptide mixture, TMT11-plex, and super heavy TMT (shTMT) isobaric labels to demonstrate ∼10-200 attomol limit of quantification within a complex background using TOMAHAQ.