Data-Independent Acquisition Protease-Multiplexing Enables Increased Proteome Sequence Coverage Across Multiple Fragmentation Modes

The use of multiple proteases has been shown to increase protein sequence coverage in proteomics experiments; however, due to the additional analysis time required, it has not been widely adopted in routine data-dependent acquisition (DDA) proteomic workflows. Alternatively, data-independent acquisition (DIA) has the potential to analyze multiplexed samples from different protease digests, but has been primarily optimized for fragmenting tryptic peptides. Here we evaluate a DIA multiplexing approach that combines three proteolytic digests (Trypsin, AspN, and GluC) into a single sample. We first optimize data acquisition conditions for each protease individually with both the canonical DIA fragmentation mode (beam type CID), as well as resonance excitation CID, to determine optimal consensus conditions across proteases. Next, we demonstrate that application of these conditions to a protease-multiplexed sample of human peptides results in similar protein identifications and quantitative performance as compared to trypsin alone, but enables up to a 63% increase in peptide detections, and a 45% increase in nonredundant amino acid detections. Nontryptic peptides enabled noncanonical protein isoform determination and resulted in 100% sequence coverage for numerous proteins, suggesting the utility of this approach in applications where sequence coverage is critical, such as protein isoform analysis.

Impact of SARS-CoV-2 ORF6 and its variant polymorphisms on host responses and viral pathogenesis

We and others have previously shown that the SARS-CoV-2 accessory protein ORF6 is a powerful antagonist of the interferon (IFN) signaling pathway by directly interacting with Nup98-Rae1 at the nuclear pore complex (NPC) and disrupting bidirectional nucleo-cytoplasmic trafficking. In this study, we further assessed the role of ORF6 during infection using recombinant SARS-CoV-2 viruses carrying either a deletion or a well characterized M58R loss-of-function mutation in ORF6. We show that ORF6 plays a key role in the antagonism of IFN signaling and in viral pathogenesis by interfering with karyopherin(importin)-mediated nuclear import during SARS-CoV-2 infection both in vitro , and in the Syrian golden hamster model in vivo . In addition, we found that ORF6-Nup98 interaction also contributes to inhibition of cellular mRNA export during SARS-CoV-2 infection. As a result, ORF6 expression significantly remodels the host cell proteome upon infection. Importantly, we also unravel a previously unrecognized function of ORF6 in the modulation of viral protein expression, which is independent of its function at the nuclear pore. Lastly, we characterized the ORF6 D61L mutation that recently emerged in Omicron BA.2 and BA.4 and demonstrated that it is able to disrupt ORF6 protein functions at the NPC and to impair SARS-CoV-2 innate immune evasion strategies. Importantly, the now more abundant Omicron BA.5 lacks this loss-of-function polymorphism in ORF6. Altogether, our findings not only further highlight the key role of ORF6 in the antagonism of the antiviral innate immune response, but also emphasize the importance of studying the role of non-spike mutations to better understand the mechanisms governing differential pathogenicity and immune evasion strategies of SARS-CoV-2 and its evolving variants.

ONE SENTENCE SUMMARY

SARS-CoV-2 ORF6 subverts bidirectional nucleo-cytoplasmic trafficking to inhibit host gene expression and contribute to viral pathogenesis.

Multi-scale photocatalytic proximity labeling reveals cell surface neighbors on and between cells

The cell membrane proteome is the primary biohub for cell communication, yet we are only beginning to understand the dynamic protein neighborhoods that form on the cell surface and between cells. Proximity labeling proteomics (PLP) strategies using chemically reactive probes are powerful approaches to yield snapshots of protein neighborhoods but are currently limited to one single resolution based on the probe labeling radius. Here, we describe a multi-scale PLP method with tunable resolution using a commercially available histological dye, Eosin Y, which upon visible light illumination, activates three different photo-probes with labeling radii ranging from ∼100 to 3000 Å. We applied this platform to profile neighborhoods of the oncogenic epidermal growth factor receptor (EGFR) and orthogonally validated >20 neighbors using immuno-assays and AlphaFold-Multimer prediction that generated plausible binary interaction models. We further profiled the protein neighborhoods of cell-cell synapses induced by bi-specific T-cell engagers (BiTEs) and chimeric antigen receptor (CAR)T cells at longer length scales. This integrated multi-scale PLP platform maps local and distal protein networks on cell surfaces and between cells. We believe this information will aid in the systematic construction of the cell surface interactome and reveal new opportunities for immunotherapeutics.

Lysosomal proteomics reveals mechanisms of neuronal apoE4associated lysosomal dysfunction

ApoE4 is the primary risk factor for Alzheimer's Disease. While apoE is primarily expressed by astrocytes, AD pathology including endosomal abnormalities and mitochondrial dysfunction first occurs in neurons. Lysosomes are poised at the convergence point between these features. We find that apoE4-expressing cells exhibit lysosomal alkalinization, reduced lysosomal proteolysis, and impaired mitophagy. To identify driving factors for this lysosomal dysfunction, we performed quantitative lysosomal proteome profiling. This revealed that apoE4 expression results in lysosomal depletion of Lgals3bp and accumulation of Tmed5 in both Neuro-2a cells and postmitotic human neurons. Modulating the expression of both proteins affected lysosomal function, with Tmed5 knockdown rescuing lysosomal alkalinization in apoE4 cells, and Lgals3bp knockdown causing lysosomal alkalinization and reduced lysosomal density in apoE3 cells. Taken together, our work reveals that apoE4 exerts gain-of-toxicity by alkalinizing the lysosomal lumen, pinpointing lysosomal Tmed5 accumulation and Lgals3bp depletion as apoE4-associated drivers for this phenotype.

Abstract 6572: Integrative network propagation to uncover potential drug resistance mechanisms in FGFR2 fusion-positive cholangiocarcinoma

Drug resistance emerges in response to most targeted therapies and is a common mechanism of treatment failure in patients with advanced cancer. We have studied resistance in intrahepatic cholangiocarcinoma (ICC) with oncogenic FGFR2 fusions. FGFR2 fusions are seen in 10-15% of ICC patients, and FGFR inhibition (FGFRi) is associated with relatively rapid emergence of resistance. While some FGFRi resistance results from mutations that block drug from binding, previous analysis has revealed polyclonal mechanisms relying on multiple pathways. Given this complexity of treatment-emergent resistance, we have employed computational strategies to integrate the phenotypic response to FGFRi with essential growth mechanisms in FGFR2 fusion-driven ICC. We applied network propagation approaches to the results of multiple -omics platforms to develop an integrated network map of the response of a patient-derived FGFR2 fusion-positive ICC line to the FGFR inhibitor TAS-120. For this analysis, multiple distinct -omics datasets (RNASEQ, global phosphoproteomics) were propagated across the ReactomeFI network, based on experimentally proven physical interactions. We propagated each dataset across the network separately and multiplied the propagation scores for each gene to generate a combined p-value, allowing us to uncover significant pathways in the network that may not have been apparent in the individual datasets. We have identified numerous groups of nodes of functional importance, including a large cluster of proteins involved in Rho family GTPase signaling. To pursue a potentially druggable target, we evaluated the Rho effector Protein Kinase N2 (PKN2). Follow-up biochemical analysis suggests that PKN2 modulates signaling feedback to AKT following FGFRi and results in altered phosphorylation of the apoptotic regulator BAD. Consistent with this, we have found that PKN2 is required for sensitivity to FGFRi in the patient-derived line using a cell viability assay. Furthermore, synergy assays with TAS-120 and the AKT inhibitor MK2206, SGK inhibitor GSK650934, and Bcl-2 inhibitor ABT-263 each resulted in significant synergistic activity, suggesting that AKT is a key effector in PKN2-mediated FGFRi resistance. We are in the process of validating these results in different cell lines and further characterizing the mechanism by which PKN2 is contributing to the FGFR/AKT signaling. In addition to identifying PKN2 as a key mediator of pathway feedback, multiple other candidate resistance mechanisms have emerged, including well established and relatively understudied pathways. These results allow multiple further avenues of investigation, and demonstrate the value of systems approaches in identifying new targets to counter drug resistance.

Citation Format: Yeonjoo Hwang, Danielle L. Swaney, Nabeel Bardeesy, John D. Gordan. Integrative network propagation to uncover potential drug resistance mechanisms in FGFR2 fusion-positive cholangiocarcinoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6572.

The Chlamydia trachomatis Inc Tri1 interacts with TRAF7 to displace native TRAF7 interacting partners

Chlamydia trachomatis is the leading cause of bacterial sexually transmitted infections in the USA and of preventable blindness worldwide. This obligate intracellular pathogen replicates within a membrane-bound inclusion, but how it acquires nutrients from the host while avoiding detection by the innate immune system is incompletely understood. C. trachomatis accomplishes this in part through the translocation of a unique set of effectors into the inclusion membrane, the inclusion membrane proteins (Incs). Incs are ideally positioned at the host-pathogen interface to reprogram host signaling by redirecting proteins or organelles to the inclusion. Using a combination of co-affinity purification, immunofluorescence confocal imaging, and proteomics, we characterize the interaction between an early-expressed Inc of unknown function, Tri1, and tumor necrosis factor receptor-associated factor 7 (TRAF7). TRAF7 is a multi-domain protein with a RING finger ubiquitin ligase domain and a C-terminal WD40 domain. TRAF7 regulates several innate immune signaling pathways associated with C. trachomatis infection and is mutated in a subset of tumors. We demonstrate that Tri1 and TRAF7 specifically interact during infection and that TRAF7 is recruited to the inclusion. We further show that the predicted coiled-coil domain of Tri1 is necessary to interact with the TRAF7 WD40 domain. Finally, we demonstrate that Tri1 displaces the native TRAF7 binding partners, mitogen-activated protein kinase kinase kinase 2 (MEKK2), and MEKK3. Together, our results suggest that by displacing TRAF7 native binding partners, Tri1 has the capacity to alter TRAF7 signaling during C. trachomatis infection.IMPORTANCEChlamydia trachomatis is the leading cause of bacterial sexually transmitted infections in the USA and preventable blindness worldwide. Although easily treated with antibiotics, the vast majority of infections are asymptomatic and therefore go untreated, leading to infertility and blindness. This obligate intracellular pathogen evades the immune response, which contributes to these outcomes. Here, we characterize the interaction between a C. trachomatis-secreted effector, Tri1, and a host protein involved in innate immune signaling, TRAF7. We identified host proteins that bind to TRAF7 and demonstrated that Tri1 can displace these proteins upon binding to TRAF7. Remarkably, the region of TRAF7 to which these host proteins bind is often mutated in a subset of human tumors. Our work suggests a mechanism by which Tri1 may alter TRAF7 signaling and has implications not only in the pathogenesis of C. trachomatis infections but also in understanding the role of TRAF7 in cancer.

Plasma proteomics for novel biomarker discovery in childhood tuberculosis

Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of TB as a leading cause of death in children. Current TB diagnostic assays have poor performance in children, and identifying novel non-sputum-based TB biomarkers to improve pediatric TB diagnosis is a global priority. We sought to develop a plasma biosignature for TB by probing the plasma proteome of 511 children stratified by TB diagnostic classification and HIV status from sites in four low- and middle-income countries, using high-throughput data-independent acquisition mass-spectrometry (DIA-PASEF-MS). We identified 47 proteins differentially regulated (BH adjusted p-values < 1%) between children with microbiologically confirmed TB and children with non-TB respiratory diseases (Unlikely TB). We further employed machine learning to derive three parsimonious biosignatures encompassing 4, 5, or 6 proteins that achieved AUCs of 0.86-0.88 all of which exceeded the minimum WHO target product profile accuracy thresholds for a TB screening test (70% specificity at 90% sensitivity, PPV 0.65-0.74, NPV 0.92-0.95). This work provides insights into the unique host response in pediatric TB disease, as well as a non-sputum biosignature that could reduce delays in TB diagnosis and improve detection and management of TB in children worldwide.

Protocol for mapping differential protein-protein interaction networks using affinity purification-mass spectrometry

Proteins congregate into complexes to perform diverse cellular functions. Protein complexes are remodeled by protein-coding mutations or cellular signaling changes, driving phenotypic outcomes in health and disease. We present an affinity purification-mass spectrometry (AP-MS) proteomics protocol to express affinity-tagged "bait" proteins in mammalian cells, identify and quantify purified protein interactors, and visualize differential protein-protein interaction networks between pairwise conditions. Our protocol possesses general applicability to various cell types and biological areas. For complete details on the use and execution of this protocol, please refer to Bouhaddou et al.1.

Multiscale photocatalytic proximity labeling reveals cell surface neighbors on and between cells

Proximity labeling proteomics (PLP) strategies are powerful approaches to yield snapshots of protein neighborhoods. Here, we describe a multiscale PLP method with adjustable resolution that uses a commercially available photocatalyst, Eosin Y, which upon visible light illumination activates different photo-probes with a range of labeling radii. We applied this platform to profile neighborhoods of the oncogenic epidermal growth factor receptor and orthogonally validated more than 20 neighbors using immunoassays and AlphaFold-Multimer prediction. We further profiled the protein neighborhoods of cell-cell synapses induced by bispecific T cell engagers and chimeric antigen receptor T cells. This integrated multiscale PLP platform maps local and distal protein networks on and between cell surfaces, which will aid in the systematic construction of the cell surface interactome, revealing horizontal signaling partners and reveal new immunotherapeutic opportunities.

Abstract B016: Inhibition of KRASG12C in colon cancer illustrates a link between beta-catenin, WNK, and the GID complex

KRAS is mutated in 35%-45% of colorectal cancers (CRC), and KRAS mutational status determines the prognosis and therapeutic options available to patients with advanced CRC. Direct KRASG12C inhibitors have proven to be highly effective for patients with non-small cell lung cancers, but unfortunately are relatively ineffective in the treatment of CRC. Thus, we have investigated tissue-specific mechanisms of resistance to direct KRAS inhibition. We used multiplex inhibitor bead kinome profiling (MIBs) and global phosphoproteomic analysis to determine the signaling response to the KRASG12C inhibitor ARS-1620 in four human colon cancer cell lines. Analyzing the kinome revealed a profound reprogramming beyond the Ras/MAPK pathway. We used network propagation to integrate analysis across these lines and define essential signaling nodes modified by direct KRAS inhibition, including two distinct signaling nodes containing RAS/MAPK and WNT-regulating kinases. Two additional smaller nodes contained WNK kinases and their effectors, followed by Hippo and a number of cell cycle-related kinases. The WNK kinases have been identified to modulate beta-catenin, a major driver of CRC biology, via the GID E3 ubiquitin ligase complex. Thus, to understand the signaling that links KRAS and beta-catenin, we used small molecule inhibitors of these kinases along with ARS-1620, we tested how they affected the transcription of beta-catenin targets. Additionally, we assessed the correlation between WNK/GID complex, and beta-catenin transcriptional output using western blot and quantitative real time PCR and observe that inhibition of KRASG12C also modulates beta-catenin transcriptional output. Our results identify new families of possible kinase targets in CRCs expressing KRAS mutations and shed light on the relationship of KRAS, beta-catenin, and WNK/GID in CRC maintenance. By dissecting these signaling relationships, we hope to identify potential drug combinations to overcome primary resistance KRASG12C inhibition in CRC.

Citation Format: Kasturi Nayak, Yeonjoo Hwang, LeeAnn Wang, Danielle L. Swaney, Nevan J. Krogan, John D. Gordan. Inhibition of KRASG12C in colon cancer illustrates a link between beta-catenin, WNK, and the GID complex [abstract]. In: Proceedings of the AACR Special Conference on Colorectal Cancer; 2022 Oct 1-4; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_1):Abstract nr B016.

TCO, a Putative Transcriptional Regulator in Arabidopsis, Is a Target of the Protein Kinase CK2

As multicellular organisms grow, spatial and temporal patterns of gene expression are strictly regulated to ensure that developmental programs are invoked at appropriate stages. In this work, we describe a putative transcriptional regulator in Arabidopsis, TACO LEAF (TCO), whose overexpression results in the ectopic activation of reproductive genes during vegetative growth. Isolated as an activation-tagged allele, tco-1D displays gene misexpression and phenotypic abnormalities, such as curled leaves and early flowering, characteristic of chromatin regulatory mutants. A role for TCO in this mode of transcriptional regulation is further supported by the subnuclear accumulation patterns of TCO protein and genetic interactions between tco-1D and chromatin modifier mutants. The endogenous expression pattern of TCO and gene misregulation in tco loss-of-function mutants indicate that this factor is involved in seed development. We also demonstrate that specific serine residues of TCO protein are targeted by the ubiquitous kinase CK2. Collectively, these results identify TCO as a novel regulator of gene expression whose activity is likely influenced by phosphorylation, as is the case with many chromatin regulators.

Cross-family small GTPase ubiquitination by the intracellular pathogen Legionella pneumophila

The intracellular bacterial pathogen Legionella pneumophila (L.p.) manipulates eukaryotic host ubiquitination machinery to form its replicative vacuole. While nearly 10% of L.p.'s arsenal of ~330 secreted effector proteins have been biochemically characterized as ubiquitin ligases or deubiquitinases, a comprehensive measure of temporally resolved changes in the endogenous host ubiquitinome during infection has not been undertaken. To elucidate how L.p hijacks ubiquitin signaling within the host cell, we undertook a proteome-wide analysis of changes in protein ubiquitination during infection. We discover that L.p. infection results in increased ubiquitination of host proteins regulating subcellular trafficking and membrane dynamics, most notably 63 of ~160 mammalian Ras superfamily small GTPases. We determine that these small GTPases predominantly undergo non-degradative monoubiquitination, and link ubiquitination to recruitment to the Legionella-containing vacuole membrane. Finally, we find that the bacterial effectors SidC/SdcA play a central, but likely indirect, role in cross-family small GTPase ubiquitination. This work highlights the extensive reconfiguration of host ubiquitin signaling by bacterial effectors during infection and establishes simultaneous ubiquitination of small GTPases across the Ras superfamily as a novel consequence of L.p. infection. This work positions L.p. as a tool to better understand how small GTPases can be regulated by ubiquitination in uninfected contexts.

Next-generation interaction proteomics for quantitative Jumbophage-bacteria interaction mapping

Host-pathogen interactions (HPIs) are pivotal in regulating establishment, progression, and outcome of an infection. Affinity-purification mass spectrometry has become instrumental for the characterization of HPIs, however the targeted nature of exogenously expressing individual viral proteins has limited its utility to the analysis of relatively small pathogens. Here we present the use of co-fractionation mass spectrometry (SEC-MS) for the high-throughput analysis of HPIs from native viral infections of two jumbophages ( ϕ KZ and ϕ PA3) in Pseudomonas aeruginosa . This enabled the detection > 6000 unique host-pathogen and > 200 pathogen-pathogen interactions for each phage, encompassing > 50% of the phage proteome. Interactome-wide comparison across phages showed similar perturbed protein interactions suggesting fundamentally conserved mechanisms of phage predation within the KZ-like phage family. Prediction of novel ORFs revealed a ϕ PA3 complex showing strong structural and sequence similarity to ϕ KZ nvRNAp, suggesting ϕ PA3 also possesses two RNA polymerases acting at different stages of the infection cycle. We further expanded our understanding on the molecular organization of the virion packaged and injected proteome by identifying 23 novel virion components and 5 novel injected proteins, as well as providing the first evidence for interactions between KZ-like phage proteins and the host ribosome. To enable accessibility to this data, we developed PhageMAP, an online resource for network query, visualization, and interaction prediction ( https://phagemap.ucsf.edu/ ). We anticipate this study will lay the foundation for the application of co-fractionation mass spectrometry for the scalable profiling of hostpathogen interactomes and protein complex dynamics upon infection.

The Mac1 ADP-ribosylhydrolase is a Therapeutic Target for SARS-CoV-2

SARS-CoV-2 continues to pose a threat to public health. Current therapeutics remain limited to direct acting antivirals that lack distinct mechanisms of action and are already showing signs of viral resistance. The virus encodes an ADP-ribosylhydrolase macrodomain (Mac1) that plays an important role in the coronaviral lifecycle by suppressing host innate immune responses. Genetic inactivation of Mac1 abrogates viral replication in vivo by potentiating host innate immune responses. However, it is unknown whether this can be achieved by pharmacologic inhibition and can therefore be exploited therapeutically. Here we report a potent and selective lead small molecule, AVI-4206, that is effective in an in vivo model of SARS-CoV-2 infection. Cellular models indicate that AVI-4206 has high target engagement and can weakly inhibit viral replication in a gamma interferon- and Mac1 catalytic activity-dependent manner; a stronger antiviral effect for AVI-4206 is observed in human airway organoids. In an animal model of severe SARS-CoV-2 infection, AVI-4206 reduces viral replication, potentiates innate immune responses, and leads to a survival benefit. Our results provide pharmacological proof of concept that Mac1 is a valid therapeutic target via a novel immune-restoring mechanism that could potentially synergize with existing therapies targeting distinct, essential aspects of the coronaviral life cycle. This approach could be more widely used to target other viral macrodomains to develop antiviral therapeutics beyond COVID-19.

Epigenetic reprogramming shapes the cellular landscape of schwannoma

Mechanisms specifying cancer cell states and response to therapy are incompletely understood. Here we show epigenetic reprogramming shapes the cellular landscape of schwannomas, the most common tumors of the peripheral nervous system. We find schwannomas are comprised of 2 molecular groups that are distinguished by activation of neural crest or nerve injury pathways that specify tumor cell states and the architecture of the tumor immune microenvironment. Moreover, we find radiotherapy is sufficient for interconversion of neural crest schwannomas to immune-enriched schwannomas through epigenetic and metabolic reprogramming. To define mechanisms underlying schwannoma groups, we develop a technique for simultaneous interrogation of chromatin accessibility and gene expression coupled with genetic and therapeutic perturbations in single-nuclei. Our results elucidate a framework for understanding epigenetic drivers of tumor evolution and establish a paradigm of epigenetic and metabolic reprograming of cancer cells that shapes the immune microenvironment in response to radiotherapy.

Caveolin-1 and Sox-2 are predictive biomarkers of cetuximab response in head and neck cancer

The epidermal growth factor receptor (EGFR) inhibitor cetuximab is the only FDA-approved oncogene-targeting therapy for head and neck squamous cell carcinoma (HNSCC). Despite variable treatment response, no biomarkers exist to stratify patients for cetuximab therapy in HNSCC. Here, we applied unbiased hierarchical clustering to reverse-phase protein array molecular profiles from patient-derived xenograft (PDX) tumors and revealed 2 PDX clusters defined by protein networks associated with EGFR inhibitor resistance. In vivo validation revealed unbiased clustering to classify PDX tumors according to cetuximab response with 88% accuracy. Next, a support vector machine classifier algorithm identified a minimalist biomarker signature consisting of 8 proteins — caveolin-1, Sox-2, AXL, STING, Brd4, claudin-7, connexin-43, and fibronectin — with expression that strongly predicted cetuximab response in PDXs using either protein or mRNA. A combination of caveolin-1 and Sox-2 protein levels was sufficient to maintain high predictive accuracy, which we validated in tumor samples from patients with HNSCC with known clinical response to cetuximab. These results support further investigation into the combined use of caveolin-1 and Sox-2 as predictive biomarkers for cetuximab response in the clinic.

EGFR and EGFRvIII coopt host defense pathways promoting progression in glioblastoma

BACKGROUND

Co-amplification of the epidermal growth factor receptor (EGFR) and EGFRvIII, a tumor-specific truncation mutant of EGFR, represent hallmark genetic lesions in glioblastoma.

METHODS

We used phospho-proteomics, RNA-sequencing, TCGA data, glioblastoma cell culture, and mouse models to study the signal transduction mediated by EGFR and EGFRvIII.

RESULTS

We report that EGFR and EGFRvIII stimulate the innate immune defense receptor Toll-like Receptor 2 (TLR2); and that knockout of TLR2 dramatically improved survival in orthotopic glioblastoma xenografts. EGFR and EGFRvIII activated TLR2 in a ligand-independent manner, promoting tumor growth and immune evasion. We show that EGFR and EGFRvIII cooperate to activate the Rho-associated protein kinase ROCK2, which modulated malignant progression both by activating TLR2 and WNT signaling, and through remodeling the tumor microenvironment.

CONCLUSIONS

Together, our findings show that EGFR and EGFRvIII cooperate to drive tumor progression through ROCK2 and downstream WNT-β-catenin/TLR2 signaling pathways.

Coupled equilibria of dimerization and lipid binding modulate SARS Cov 2 Orf9b interactions and interferon response

Open Reading Frame 9b (Orf9b), an accessory protein of SARS-CoV and -2, is involved in innate immune suppression through its binding to the mitochondrial receptor Translocase of Outer Membrane 70 (Tom70). Previous structural studies of Orf9b in isolation revealed a β-sheet-rich homodimer, however, structures of Orf9b in complex with Tom70 revealed a monomeric helical fold. Here, we developed a biophysical model that quantifies how Orf9b switches between these conformations and binds to Tom70, a requirement for suppressing the type 1 interferon response. We used this model to characterize the effect of lipid binding and mutations in variants of concern to the Orf9b:Tom70 equilibrium. We found that the binding of a lipid to the Orf9b homodimer biases the Orf9b monomer:dimer equilibrium towards the dimer by reducing the dimer dissociation rate ∼100-fold. We also found that mutations in variants of concern can alter different microscopic rate constants without significantly affecting binding to Tom70. Together our results highlight how perturbations to different steps in these coupled equilibria can affect the apparent affinity of Orf9b to Tom70, with potential downstream implications for interferon signaling in coronavirus infection.

Abstract 309: Mapping oncogenic signal transduction in PKA-driven cancers

Protein Kinase A (PKA) is a major effector of cyclic-AMP (cAMP) signaling and has recently been appreciated to play a role in multiple malignancies. Mutations of its catalytic subunit (PRKACA) have been identified in a substantial proportion of adrenocortical tumors, and are also detected in a wide spectrum of tumor types in the TCGA dataset, although at a low frequency. A unique fusion protein of PRKACA and DNAJB1 is seen in the majority of fibrolamellar liver cancers (FLC), a rare malignancy of young adults, where it is suspected to be the primary oncogenic driver. However, the key effectors of oncogenic signaling in FLC and other PRKACA driven cancers remain unknown. To understand PKA's downstream targets, we generated genetic cell models with doxycycline-inducible PRKACA or its dominant negative counterpart, a mutant form of the PRKAR1A regulatory subunit. These cell models were then subjected to mass spectrometry for kinome profiling in order to detect kinases with significant altered activity following PKA modulation. This was integrated with small molecule inhibition and siRNA knockdown to identify PKA-regulated kinases that impact cell proliferation. Our analysis revealed activation of the aurora-family kinase AURKA, with preferential sensitivity to the confirmation-disrupting AURKA inhibitor (CD-AURKAi) CD532 compared to other AURKA inhibitors. CD-AURKAi not only selectively inhibit AURKA's kinase activity, but also disrupt its interaction with MYC-family transcription factors. These key oncogenic mediators are necessary to drive the proliferation of multiple tumor types, although they have not yet been connected with oncogenic PKA signaling. Our follow up quantitative PCR experiments confirm that CD-532 treatment results in reduced expression of MYC family members and their transcriptional targets. We next confirmed that MYC family members support the proliferation of PKA-driven cell models with live cell imaging. Finally, we have begun to investigate other kinases identified in our siRNA screen for potential effects on MYC, and have identified several potential combination partners to augment the activity of CD-532 and other CD-AURKAi. These data suggest that CD-AURKAi, either alone or in combination, have the potential to serve as therapeutic agents for PKA-driven cancers.

Citation Format: Gary Kwan Leung Chan, Samantha M. Maisel, Y. Christina Hwang, Rebecca Wolber, Danielle L. Swaney, Nabeel Bardeesy, John D. Gordan. Mapping oncogenic signal transduction in PKA-driven cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 309.

In vivo protein turnover rates in varying oxygen tensions nominate MYBBP1A as a mediator of the hyperoxia response

Oxygen deprivation and excess are both toxic. Thus, the body's ability to adapt to varying oxygen tensions is critical for survival. While the hypoxia transcriptional response has been well studied, the post-translational effects of oxygen have been underexplored. In this study, we systematically investigate protein turnover rates in mouse heart, lung, and brain under different inhaled oxygen tensions. We find that the lung proteome is the most responsive to varying oxygen tensions. In particular, several extracellular matrix (ECM) proteins are stabilized in the lung under both hypoxia and hyperoxia. Furthermore, we show that complex 1 of the electron transport chain is destabilized in hyperoxia, in accordance with the exacerbation of associated disease models by hyperoxia and rescue by hypoxia. Moreover, we nominate MYBBP1A as a hyperoxia transcriptional regulator, particularly in the context of rRNA homeostasis. Overall, our study highlights the importance of varying oxygen tensions on protein turnover rates and identifies tissue-specific mediators of oxygen-dependent responses.

Molecular determinants of the crosstalk between endosomal microautophagy and chaperone-mediated autophagy

Chaperone-mediated autophagy (CMA) and endosomal microautophagy (eMI) are pathways for selective degradation of cytosolic proteins in lysosomes and late endosomes, respectively. These autophagic processes share as a first step the recognition of the same five-amino-acid motif in substrate proteins by the Hsc70 chaperone, raising the possibility of coordinated activity of both pathways. In this work, we show the existence of a compensatory relationship between CMA and eMI and identify a role for the chaperone protein Bag6 in triage and internalization of eMI substrates into late endosomes. Association and dynamics of Bag6 at the late endosome membrane change during starvation, a stressor that, contrary to other autophagic pathways, causes a decline in eMI activity. Collectively, these results show a coordinated function of eMI with CMA, identify the interchangeable subproteome degraded by these pathways, and start to elucidate the molecular mechanisms that facilitate the switch between them.

Spatial control of sensory adaptation modulates mechanosensing in Pseudomonas aeruginosa

Sensory signaling pathways use adaptation to dynamically respond to changes in their environment. Here, we report the mechanism of sensory adaptation in the Pil-Chp mechanosensory system, which the important human pathogen Pseudomonas aeruginosa uses to sense mechanical stimuli during surface exploration. Using biochemistry, genetics, and cell biology, we discovered that the enzymes responsible for adaptation, a methyltransferase and a methylesterase, are segregated to opposing cell poles as P. aeruginosa explore surfaces. By coordinating the localization of both enzymes, we found that the Pil-Chp response regulators influence local receptor methylation, the molecular basis of bacterial sensory adaptation. We propose a model in which adaptation during mechanosensing spatially resets local receptor methylation, and thus Pil-Chp signaling, to modulate the pathway outputs, which are involved in P. aeruginosa virulence. Despite decades of bacterial sensory adaptation studies, our work has uncovered an unrecognized mechanism that bacteria use to achieve adaptation to sensory stimuli.

Deep learning from harmonized peptide libraries enables retention time prediction of diverse post translational modifications

In proteomics experiments, peptide retention time (RT) is an orthogonal property to fragmentation when assessing detection confidence. Advances in deep learning enable accurate RT prediction for any peptide from sequence alone, including those yet to be experimentally observed. Here we present Chronologer, an open-source software tool for rapid and accurate peptide RT prediction. Using new approaches to harmonize and false-discovery correct across independently collected datasets, Chronologer is built on a massive database with >2.2 million peptides including 10 common post-translational modification (PTM) types. By linking knowledge learned across diverse peptide chemistries, Chronologer predicts RTs with less than two-thirds the error of other deep learning tools. We show how RT for rare PTMs, such as OGlcNAc, can be learned with high accuracy using as few as 10-100 example peptides in newly harmonized datasets. This iteratively updatable workflow enables Chronologer to comprehensively predict RTs for PTM-marked peptides across entire proteomes.

High-throughput chemogenetic drug screening reveals PKC-RhoA/PKN as a targetable signaling vulnerability in GNAQ-driven uveal melanoma

Uveal melanoma (UM) is the most prevalent cancer of the eye in adults, driven by activating mutation of GNAQ/GNA11; however, there are limited therapies against UM and metastatic UM (mUM). Here, we perform a high-throughput chemogenetic drug screen in GNAQ-mutant UM contrasted with BRAF-mutant cutaneous melanoma, defining the druggable landscape of these distinct melanoma subtypes. Across all compounds, darovasertib demonstrates the highest preferential activity against UM. Our investigation reveals that darovasertib potently inhibits PKC as well as PKN/PRK, an AGC kinase family that is part of the "dark kinome." We find that downstream of the Gαq-RhoA signaling axis, PKN converges with ROCK to control FAK, a mediator of non-canonical Gαq-driven signaling. Strikingly, darovasertib synergizes with FAK inhibitors to halt UM growth and promote cytotoxic cell death in vitro and in preclinical metastatic mouse models, thus exposing a signaling vulnerability that can be exploited as a multimodal precision therapy against mUM.