Integrative spatial analysis reveals a multi-layered organization of glioblastoma.

Glioma contains malignant cells in diverse states. Here, we combine spatial transcriptomics, spatial proteomics, and computational approaches to define glioma cellular states and uncover their organization. We find three prominent modes of organization. First, gliomas are composed of small local environments, each typically enriched with one major cellular state. Second, specific pairs of states preferentially reside in proximity across multiple scales. This pairing of states is consistent across tumors. Third, these pairwise interactions collectively define a global architecture composed of five layers. Hypoxia appears to drive the layers, as it is associated with a long-range organization that includes all cancer cell states. Accordingly, tumor regions distant from any hypoxic/necrotic foci and tumors that lack hypoxia such as low-grade IDH-mutant glioma are less organized. In summary, we provide a conceptual framework for the organization of cellular states in glioma, highlighting hypoxia as a long-range tissue organizer.

DrugMap: A quantitative pan-cancer analysis of cysteine ligandability.

Cysteine-focused chemical proteomic platforms have accelerated the clinical development of covalent inhibitors for a wide range of targets in cancer. However, how different oncogenic contexts influence cysteine targeting remains unknown. To address this question, we have developed "DrugMap," an atlas of cysteine ligandability compiled across 416 cancer cell lines. We unexpectedly find that cysteine ligandability varies across cancer cell lines, and we attribute this to differences in cellular redox states, protein conformational changes, and genetic mutations. Leveraging these findings, we identify actionable cysteines in NF-κB1 and SOX10 and develop corresponding covalent ligands that block the activity of these transcription factors. We demonstrate that the NF-κB1 probe blocks DNA binding, whereas the SOX10 ligand increases SOX10-SOX10 interactions and disrupts melanoma transcriptional signaling. Our findings reveal heterogeneity in cysteine ligandability across cancers, pinpoint cell-intrinsic features driving cysteine targeting, and illustrate the use of covalent probes to disrupt oncogenic transcription-factor activity.

Global, site-resolved analysis of ubiquitylation occupancy and turnover rate reveals systems properties.

Ubiquitylation regulates most proteins and biological processes in a eukaryotic cell. However, the site-specific occupancy (stoichiometry) and turnover rate of ubiquitylation have not been quantified. Here we present an integrated picture of the global ubiquitylation site occupancy and half-life. Ubiquitylation site occupancy spans over four orders of magnitude, but the median ubiquitylation site occupancy is three orders of magnitude lower than that of phosphorylation. The occupancy, turnover rate, and regulation of sites by proteasome inhibitors are strongly interrelated, and these attributes distinguish sites involved in proteasomal degradation and cellular signaling. Sites in structured protein regions exhibit longer half-lives and stronger upregulation by proteasome inhibitors than sites in unstructured regions. Importantly, we discovered a surveillance mechanism that rapidly and site-indiscriminately deubiquitylates all ubiquitin-specific E1 and E2 enzymes, protecting them against accumulation of bystander ubiquitylation. The work provides a systems-scale, quantitative view of ubiquitylation properties and reveals general principles of ubiquitylation-dependent governance.

Pan-cancer proteogenomics expands the landscape of therapeutic targets.

Fewer than 200 proteins are targeted by cancer drugs approved by the Food and Drug Administration (FDA). We integrate Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteogenomics data from 1,043 patients across 10 cancer types with additional public datasets to identify potential therapeutic targets. Pan-cancer analysis of 2,863 druggable proteins reveals a wide abundance range and identifies biological factors that affect mRNA-protein correlation. Integration of proteomic data from tumors and genetic screen data from cell lines identifies protein overexpression- or hyperactivation-driven druggable dependencies, enabling accurate predictions of effective drug targets. Proteogenomic identification of synthetic lethality provides a strategy to target tumor suppressor gene loss. Combining proteogenomic analysis and MHC binding prediction prioritizes mutant KRAS peptides as promising public neoantigens. Computational identification of shared tumor-associated antigens followed by experimental confirmation nominates peptides as immunotherapy targets. These analyses, summarized at https://targets.linkedomics.org, form a comprehensive landscape of protein and peptide targets for companion diagnostics, drug repurposing, and therapy development.

CSF proteomics identifies early changes in autosomal dominant Alzheimer's disease.

In this high-throughput proteomic study of autosomal dominant Alzheimer's disease (ADAD), we sought to identify early biomarkers in cerebrospinal fluid (CSF) for disease monitoring and treatment strategies. We examined CSF proteins in 286 mutation carriers (MCs) and 177 non-carriers (NCs). The developed multi-layer regression model distinguished proteins with different pseudo-trajectories between these groups. We validated our findings with independent ADAD as well as sporadic AD datasets and employed machine learning to develop and validate predictive models. Our study identified 137 proteins with distinct trajectories between MCs and NCs, including eight that changed before traditional AD biomarkers. These proteins are grouped into three stages: early stage (stress response, glutamate metabolism, neuron mitochondrial damage), middle stage (neuronal death, apoptosis), and late presymptomatic stage (microglial changes, cell communication). The predictive model revealed a six-protein subset that more effectively differentiated MCs from NCs, compared with conventional biomarkers.

Light-induced targeting enables proteomics on endogenous condensates.

Endogenous condensates with transient constituents are notoriously difficult to study with common biological assays like mass spectrometry and other proteomics profiling. Here, we report a method for light-induced targeting of endogenous condensates (LiTEC) in living cells. LiTEC combines the identification of molecular zip codes that target the endogenous condensates with optogenetics to enable controlled and reversible partitioning of an arbitrary cargo, such as enzymes commonly used in proteomics, into the condensate in a blue light-dependent manner. We demonstrate a proof of concept by combining LiTEC with proximity-based biotinylation (BioID) and uncover putative components of transcriptional condensates in mouse embryonic stem cells. Our approach opens the road to genome-wide functional studies of endogenous condensates.

Spatial proteomics in neurons at single-protein resolution.

To understand biological processes, it is necessary to reveal the molecular heterogeneity of cells by gaining access to the location and interaction of all biomolecules. Significant advances were achieved by super-resolution microscopy, but such methods are still far from reaching the multiplexing capacity of proteomics. Here, we introduce secondary label-based unlimited multiplexed DNA-PAINT (SUM-PAINT), a high-throughput imaging method that is capable of achieving virtually unlimited multiplexing at better than 15 nm resolution. Using SUM-PAINT, we generated 30-plex single-molecule resolved datasets in neurons and adapted omics-inspired analysis for data exploration. This allowed us to reveal the complexity of synaptic heterogeneity, leading to the discovery of a distinct synapse type. We not only provide a resource for researchers, but also an integrated acquisition and analysis workflow for comprehensive spatial proteomics at single-protein resolution.

Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies.

We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified. Overexpression of HMGB3 promoted SCLC cell migration via transcriptional regulation of cell junction-related genes. Immune landscape characterization revealed an association between ZFHX3 mutation and high immune infiltration and underscored a potential immunosuppressive role of elevated DNA damage response activity via inhibition of the cGAS-STING pathway. Multi-omics clustering identified four subtypes with subtype-specific therapeutic vulnerabilities. Cell line and patient-derived xenograft-based drug tests validated the specific therapeutic responses predicted by multi-omics subtyping. This study provides a valuable resource as well as insights to better understand SCLC biology and improve clinical practice.

Proteome-scale movements and compartment connectivity during the eukaryotic cell cycle.

Cell cycle progression relies on coordinated changes in the composition and subcellular localization of the proteome. By applying two distinct convolutional neural networks on images of millions of live yeast cells, we resolved proteome-level dynamics in both concentration and localization during the cell cycle, with resolution of ∼20 subcellular localization classes. We show that a quarter of the proteome displays cell cycle periodicity, with proteins tending to be controlled either at the level of localization or concentration, but not both. Distinct levels of protein regulation are preferentially utilized for different aspects of the cell cycle, with changes in protein concentration being mostly involved in cell cycle control and changes in protein localization in the biophysical implementation of the cell cycle program. We present a resource for exploring global proteome dynamics during the cell cycle, which will aid in understanding a fundamental biological process at a systems level.

The proteomic landscape of genome-wide genetic perturbations.

Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by quantifying protein abundances in a genome-scale knockout library in Saccharomyces cerevisiae, using data-independent acquisition mass spectrometry. We find that global protein expression is driven by a complex interplay of (1) general biological properties, including translation rate, protein turnover, the formation of protein complexes, growth rate, and genome architecture, followed by (2) functional properties, such as the connectivity of a protein in genetic, metabolic, and physical interaction networks. Moreover, we show that functional proteomics complements current gene annotation strategies through the assessment of proteome profile similarity, protein covariation, and reverse proteome profiling. Thus, our study reveals principles that govern protein expression and provides a genome-spanning resource for functional annotation.

The proteomic landscape of synaptic diversity across brain regions and cell types.

Neurons build synaptic contacts using different protein combinations that define the specificity, function, and plasticity potential of synapses; however, the diversity of synaptic proteomes remains largely unexplored. We prepared synaptosomes from 7 different transgenic mouse lines with fluorescently labeled presynaptic terminals. Combining microdissection of 5 different brain regions with fluorescent-activated synaptosome sorting (FASS), we isolated and analyzed the proteomes of 18 different synapse types. We discovered ∼1,800 unique synapse-type-enriched proteins and allocated thousands of proteins to different types of synapses (https://syndive.org/). We identify shared synaptic protein modules and highlight the proteomic hotspots for synapse specialization. We reveal unique and common features of the striatal dopaminergic proteome and discover the proteome signatures that relate to the functional properties of different interneuron classes. This study provides a molecular systems-biology analysis of synapses and a framework to integrate proteomic information for synapse subtypes of interest with cellular or circuit-level experiments.

Systematic identification of anticancer drug targets reveals a nucleus-to-mitochondria ROS-sensing pathway.

Multiple anticancer drugs have been proposed to cause cell death, in part, by increasing the steady-state levels of cellular reactive oxygen species (ROS). However, for most of these drugs, exactly how the resultant ROS function and are sensed is poorly understood. It remains unclear which proteins the ROS modify and their roles in drug sensitivity/resistance. To answer these questions, we examined 11 anticancer drugs with an integrated proteogenomic approach identifying not only many unique targets but also shared ones-including ribosomal components, suggesting common mechanisms by which drugs regulate translation. We focus on CHK1 that we find is a nuclear H2O2 sensor that launches a cellular program to dampen ROS. CHK1 phosphorylates the mitochondrial DNA-binding protein SSBP1 to prevent its mitochondrial localization, which in turn decreases nuclear H2O2. Our results reveal a druggable nucleus-to-mitochondria ROS-sensing pathway-required to resolve nuclear H2O2 accumulation and mediate resistance to platinum-based agents in ovarian cancers.

SARS-CoV-2 variants evolve convergent strategies to remodel the host response.

SARS-CoV-2 variants of concern (VOCs) emerged during the COVID-19 pandemic. Here, we used unbiased systems approaches to study the host-selective forces driving VOC evolution. We discovered that VOCs evolved convergent strategies to remodel the host by modulating viral RNA and protein levels, altering viral and host protein phosphorylation, and rewiring virus-host protein-protein interactions. Integrative computational analyses revealed that although Alpha, Beta, Gamma, and Delta ultimately converged to suppress interferon-stimulated genes (ISGs), Omicron BA.1 did not. ISG suppression correlated with the expression of viral innate immune antagonist proteins, including Orf6, N, and Orf9b, which we mapped to specific mutations. Later Omicron subvariants BA.4 and BA.5 more potently suppressed innate immunity than early subvariant BA.1, which correlated with Orf6 levels, although muted in BA.4 by a mutation that disrupts the Orf6-nuclear pore interaction. Our findings suggest that SARS-CoV-2 convergent evolution overcame human adaptive and innate immune barriers, laying the groundwork to tackle future pandemics.

Pan-cancer proteogenomics connects oncogenic drivers to functional states.

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

Pan-cancer analysis of post-translational modifications reveals shared patterns of protein regulation.

Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable high-throughput, accurate, and sensitive measurement of PTM levels to better understand their role, prevalence, and crosstalk. Here, we analyze the largest collection of proteogenomics data from 1,110 patients with PTM profiles across 11 cancer types (10 from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium [CPTAC]). Our study reveals pan-cancer patterns of changes in protein acetylation and phosphorylation involved in hallmark cancer processes. These patterns revealed subsets of tumors, from different cancer types, including those with dysregulated DNA repair driven by phosphorylation, altered metabolic regulation associated with immune response driven by acetylation, affected kinase specificity by crosstalk between acetylation and phosphorylation, and modified histone regulation. Overall, this resource highlights the rich biology governed by PTMs and exposes potential new therapeutic avenues.

Liquid-biopsy proteomics combined with AI identifies cellular drivers of eye aging and disease in vivo.

Single-cell analysis in living humans is essential for understanding disease mechanisms, but it is impractical in non-regenerative organs, such as the eye and brain, because tissue biopsies would cause serious damage. We resolve this problem by integrating proteomics of liquid biopsies with single-cell transcriptomics from all known ocular cell types to trace the cellular origin of 5,953 proteins detected in the aqueous humor. We identified hundreds of cell-specific protein markers, including for individual retinal cell types. Surprisingly, our results reveal that retinal degeneration occurs in Parkinson's disease, and the cells driving diabetic retinopathy switch with disease stage. Finally, we developed artificial intelligence (AI) models to assess individual cellular aging and found that many eye diseases not associated with chronological age undergo accelerated molecular aging of disease-specific cell types. Our approach, which can be applied to other organ systems, has the potential to transform molecular diagnostics and prognostics while uncovering new cellular disease and aging mechanisms.

De novo protein identification in mammalian sperm using in situ cryoelectron tomography and AlphaFold2 docking.

To understand the molecular mechanisms of cellular pathways, contemporary workflows typically require multiple techniques to identify proteins, track their localization, and determine their structures in vitro. Here, we combined cellular cryoelectron tomography (cryo-ET) and AlphaFold2 modeling to address these questions and understand how mammalian sperm are built in situ. Our cellular cryo-ET and subtomogram averaging provided 6.0-Å reconstructions of axonemal microtubule structures. The well-resolved tertiary structures allowed us to unbiasedly match sperm-specific densities with 21,615 AlphaFold2-predicted protein models of the mouse proteome. We identified Tektin 5, CCDC105, and SPACA9 as novel microtubule-associated proteins. These proteins form an extensive interaction network crosslinking the lumen of axonemal doublet microtubules, suggesting their roles in modulating the mechanical properties of the filaments. Indeed, Tekt5 -/- sperm possess more deformed flagella with 180° bends. Together, our studies presented a cellular visual proteomics workflow and shed light on the in vivo functions of Tektin 5.

SARS-CoV-2 replication in airway epithelia requires motile cilia and microvillar reprogramming.

How SARS-CoV-2 penetrates the airway barrier of mucus and periciliary mucins to infect nasal epithelium remains unclear. Using primary nasal epithelial organoid cultures, we found that the virus attaches to motile cilia via the ACE2 receptor. SARS-CoV-2 traverses the mucus layer, using motile cilia as tracks to access the cell body. Depleting cilia blocks infection for SARS-CoV-2 and other respiratory viruses. SARS-CoV-2 progeny attach to airway microvilli 24 h post-infection and trigger formation of apically extended and highly branched microvilli that organize viral egress from the microvilli back into the mucus layer, supporting a model of virus dispersion throughout airway tissue via mucociliary transport. Phosphoproteomics and kinase inhibition reveal that microvillar remodeling is regulated by p21-activated kinases (PAK). Importantly, Omicron variants bind with higher affinity to motile cilia and show accelerated viral entry. Our work suggests that motile cilia, microvilli, and mucociliary-dependent mucus flow are critical for efficient virus replication in nasal epithelia.

Systemwide disassembly and assembly of SCF ubiquitin ligase complexes.

Cells respond to environmental cues by remodeling their inventories of multiprotein complexes. Cellular repertoires of SCF (SKP1-CUL1-F box protein) ubiquitin ligase complexes, which mediate much protein degradation, require CAND1 to distribute the limiting CUL1 subunit across the family of ∼70 different F box proteins. Yet, how a single factor coordinately assembles numerous distinct multiprotein complexes remains unknown. We obtained cryo-EM structures of CAND1-bound SCF complexes in multiple states and correlated mutational effects on structures, biochemistry, and cellular assays. The data suggest that CAND1 clasps idling catalytic domains of an inactive SCF, rolls around, and allosterically rocks and destabilizes the SCF. New SCF production proceeds in reverse, through SKP1-F box allosterically destabilizing CAND1. The CAND1-SCF conformational ensemble recycles CUL1 from inactive complexes, fueling mixing and matching of SCF parts for E3 activation in response to substrate availability. Our data reveal biogenesis of a predominant family of E3 ligases, and the molecular basis for systemwide multiprotein complex assembly.

Nutrient-regulated control of lysosome function by signaling lipid conversion.

Lysosomes serve dual antagonistic functions in cells by mediating anabolic growth signaling and the catabolic turnover of macromolecules. How these janus-faced activities are regulated in response to cellular nutrient status is poorly understood. We show here that lysosome morphology and function are reversibly controlled by a nutrient-regulated signaling lipid switch that triggers the conversion between peripheral motile mTOR complex 1 (mTORC1) signaling-active and static mTORC1-inactive degradative lysosomes clustered at the cell center. Starvation-triggered relocalization of phosphatidylinositol 4-phosphate (PI(4)P)-metabolizing enzymes reshapes the lysosomal surface proteome to facilitate lysosomal proteolysis and to repress mTORC1 signaling. Concomitantly, lysosomal phosphatidylinositol 3-phosphate (PI(3)P), which marks motile signaling-active lysosomes in the cell periphery, is erased. Interference with this PI(3)P/PI(4)P lipid switch module impairs the adaptive response of cells to altering nutrient supply. Our data unravel a key function for lysosomal phosphoinositide metabolism in rewiring organellar membrane dynamics in response to cellular nutrient status.