NUSAP1 Binds ILF2 to Modulate R-Loop Accumulation and DNA Damage in Prostate Cancer.

Increased expression of NUSAP1 has been identified as a robust prognostic biomarker in prostate cancer and other malignancies. We have previously shown that NUSAP1 is positively regulated by E2F1 and promotes cancer invasion and metastasis. To further understand the biological function of NUSAP1, we used affinity purification and mass spectrometry proteomic analysis to identify NUSAP1 interactors. We identified 85 unique proteins in the NUSAP1 interactome, including ILF2, DHX9, and other RNA-binding proteins. Using proteomic approaches, we uncovered a function for NUSAP1 in maintaining R-loops and in DNA damage response through its interaction with ILF2. Co-immunoprecipitation and colocalization using confocal microscopy verified the interactions of NUSAP1 with ILF2 and DHX9, and RNA/DNA hybrids. We showed that the microtubule and charged helical domains of NUSAP1 were necessary for the protein-protein interactions. Depletion of ILF2 alone further increased camptothecin-induced R-loop accumulation and DNA damage, and NUSAP1 depletion abolished this effect. In human prostate adenocarcinoma, NUSAP1 and ILF2 mRNA expression levels are positively correlated, elevated, and associated with poor clinical outcomes. Our study identifies a novel role for NUSAP1 in regulating R-loop formation and accumulation in response to DNA damage through its interactions with ILF2 and hence provides a potential therapeutic target.

TEAD Proteins Associate With DNA Repair Proteins to Facilitate Cellular Recovery From DNA Damage.

Transcriptional enhanced associate domain family members 1 to 4 (TEADs) are a family of four transcription factors and the major transcriptional effectors of the Hippo pathway. In order to activate transcription, TEADs rely on interactions with other proteins, such as the transcriptional effectors Yes-associated protein and transcriptional co-activator with PDZ-binding motif. Nuclear protein interactions involving TEADs influence the transcriptional regulation of genes involved in cell growth, tissue homeostasis, and tumorigenesis. Clearly, protein interactions for TEADs are functionally important, but the full repertoire of TEAD interaction partners remains unknown. Here, we employed an affinity purification mass spectrometry approach to identify nuclear interacting partners of TEADs. We performed affinity purification mass spectrometry experiment in parallel in two different cell types and compared a wildtype TEAD bait protein to a nuclear localization sequence mutant that does not localize to the nucleus. We quantified the results using SAINT analysis and found a significant enrichment of proteins linked to DNA damage including X-ray repair cross-complementing protein 5 (XRCC5), X-ray repair cross-complementing protein 6 (XRCC6), poly(ADP-ribose) polymerase 1 (PARP1), and Rap1-interacting factor 1 (RIF1). In cellular assays, we found that TEADs co-localize with DNA damage-induced nuclear foci marked by histone H2AX phosphorylated on S139 (γH2AX) and Rap1-interacting factor 1. We also found that depletion of TEAD proteins makes cells more susceptible to DNA damage by various agents and that depletion of TEADs promotes genomic instability. Additionally, depleting TEADs dampens the efficiency of DNA double-stranded break repair in reporter assays. Our results connect TEADs to DNA damage response processes, positioning DNA damage as an important avenue for further research of TEAD proteins.

MSstatsPTM: Statistical Relative Quantification of Posttranslational Modifications in Bottom-Up Mass Spectrometry-Based Proteomics.

Liquid chromatography coupled with bottom-up mass spectrometry (LC-MS/MS)-based proteomics is increasingly used to detect changes in posttranslational modifications (PTMs) in samples from different conditions. Analysis of data from such experiments faces numerous statistical challenges. These include the low abundance of modified proteoforms, the small number of observed peptides that span modification sites, and confounding between changes in the abundance of PTM and the overall changes in the protein abundance. Therefore, statistical approaches for detecting differential PTM abundance must integrate all the available information pertaining to a PTM site and consider all the relevant sources of confounding and variation. In this manuscript, we propose such a statistical framework, which is versatile, accurate, and leads to reproducible results. The framework requires an experimental design, which quantifies, for each sample, both peptides with PTMs and peptides from the same proteins with no modification sites. The proposed framework supports both label-free and tandem mass tag-based LC-MS/MS acquisitions. The statistical methodology separately summarizes the abundances of peptides with and without the modification sites, by fitting separate linear mixed effects models appropriate for the experimental design. Next, model-based inferences regarding the PTM and the protein-level abundances are combined to account for the confounding between these two sources. Evaluations on computer simulations, a spike-in experiment with known ground truth, and three biological experiments with different organisms, modification types, and data acquisition types demonstrate the improved fold change estimation and detection of differential PTM abundance, as compared to currently used approaches. The proposed framework is implemented in the free and open-source R/Bioconductor package MSstatsPTM.

CRAF dimerization with ARAF regulates KRAS-driven tumor growth.

KRAS, which is mutated in ∼30% of all cancers, activates the RAF-MEK-ERK signaling cascade. CRAF is required for growth of KRAS mutant lung tumors, but the requirement for CRAF kinase activity is unknown. Here, we show that subsets of KRAS mutant tumors are dependent on CRAF for growth. Kinase-dead but not dimer-defective CRAF rescues growth inhibition, suggesting that dimerization but not kinase activity is required. Quantitative proteomics demonstrates increased levels of CRAF:ARAF dimers in KRAS mutant cells, and depletion of both CRAF and ARAF rescues the CRAF-loss phenotype. Mechanistically, CRAF depletion causes sustained ERK activation and induction of cell-cycle arrest, while treatment with low-dose MEK or ERK inhibitor rescues the CRAF-loss phenotype. Our studies highlight the role of CRAF in regulating MAPK signal intensity to promote tumorigenesis downstream of mutant KRAS and suggest that disrupting CRAF dimerization or degrading CRAF may have therapeutic benefit.

The neutrophil protein CD177 is a novel PDPN receptor that regulates human cancer-associated fibroblast physiology.

The cancer-associated fibroblast (CAF) marker podoplanin (PDPN) is generally correlated with poor clinical outcomes in cancer patients and thus represents a promising therapeutic target. Despite its biomedical relevance, basic aspects of PDPN biology such as its cellular functions and cell surface ligands remain poorly uncharacterized, thus challenging drug development. Here, we utilize a high throughput platform to elucidate the PDPN cell surface interactome, and uncover the neutrophil protein CD177 as a new binding partner. Quantitative proteomics analysis of the CAF phosphoproteome reveals a role for PDPN in cell signaling, growth and actomyosin contractility, among other processes. Moreover, cellular assays demonstrate that CD177 is a functional antagonist, recapitulating the phenotype observed in PDPN-deficient CAFs. In sum, starting from the unbiased elucidation of the PDPN co-receptome, our work provides insights into PDPN functions and reveals the PDPN/CD177 axis as a possible modulator of fibroblast physiology in the tumor microenvironment.

Homeostatic functions of monocytes and interstitial lung macrophages are regulated via collagen domain-binding receptor LAIR1.

Myeloid cells encounter stromal cells and their matrix determinants on a continual basis during their residence in any given organ. Here, we examined the impact of the collagen receptor LAIR1 on myeloid cell homeostasis and function. LAIR1 was highly expressed in the myeloid lineage and enriched in non-classical monocytes. Proteomic definition of the LAIR1 interactome identified stromal factor Colec12 as a high-affinity LAIR1 ligand. Proteomic profiling of LAIR1 signaling triggered by Collagen1 and Colec12 highlighted pathways associated with survival, proliferation, and differentiation. Lair1-/- mice had reduced frequencies of Ly6C- monocytes, which were associated with altered proliferation and apoptosis of non-classical monocytes from bone marrow and altered heterogeneity of interstitial macrophages in lung. Myeloid-specific LAIR1 deficiency promoted metastatic growth in a melanoma model and LAIR1 expression associated with improved clinical outcomes in human metastatic melanoma. Thus, monocytes and macrophages rely on LAIR1 sensing of stromal determinants for fitness and function, with relevance in homeostasis and disease.

Multiplexed proteomics of autophagy-deficient murine macrophages reveals enhanced antimicrobial immunity via the oxidative stress response.

Defective autophagy is strongly associated with chronic inflammation. Loss-of-function of the core autophagy gene Atg16l1 increases risk for Crohn's disease in part by enhancing innate immunity through myeloid cells such as macrophages. However, autophagy is also recognized as a mechanism for clearance of certain intracellular pathogens. These divergent observations prompted a re-evaluation of ATG16L1 in innate antimicrobial immunity. In this study, we found that loss of Atg16l1 in myeloid cells enhanced the killing of virulent Shigella flexneri (S.flexneri), a clinically relevant enteric bacterium that resides within the cytosol by escaping from membrane-bound compartments. Quantitative multiplexed proteomics of murine bone marrow-derived macrophages revealed that ATG16L1 deficiency significantly upregulated proteins involved in the glutathione-mediated antioxidant response to compensate for elevated oxidative stress, which simultaneously promoted S.flexneri killing. Consistent with this, myeloid-specific deletion of Atg16l1 in mice accelerated bacterial clearance in vitro and in vivo. Pharmacological induction of oxidative stress through suppression of cysteine import enhanced microbial clearance by macrophages. Conversely, antioxidant treatment of macrophages permitted S.flexneri proliferation. These findings demonstrate that control of oxidative stress by ATG16L1 and autophagy regulates antimicrobial immunity against intracellular pathogens.

The Immunoglobulin Superfamily Receptome Defines Cancer-Relevant Networks Associated with Clinical Outcome.

Cell surface receptors and their interactions play a central role in physiological and pathological signaling. Despite its clinical relevance, the immunoglobulin superfamily (IgSF) remains uncharacterized and underrepresented in databases. Here, we present a systematic extracellular protein map, the IgSF interactome. Using a high-throughput technology to interrogate most single transmembrane receptors for binding to 445 IgSF proteins, we identify over 500 interactions, 82% previously undocumented, and confirm more than 60 receptor-ligand pairs using orthogonal assays. Our study reveals a map of cell-type-specific interactions and the landscape of dysregulated receptor-ligand crosstalk in cancer, including selective loss of function for tumor-associated mutations. Furthermore, investigation of the IgSF interactome in a large cohort of cancer patients identifies interacting protein signatures associated with clinical outcome. The IgSF interactome represents an important resource to fuel biological discoveries and a framework for understanding the functional organization of the surfaceome during homeostasis and disease, ultimately informing therapeutic development.

Synthetic Essentiality of Metabolic Regulator PDHK1 in PTEN-Deficient Cells and Cancers.

Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) is a tumor suppressor and bi-functional lipid and protein phosphatase. We report that the metabolic regulator pyruvate dehydrogenase kinase1 (PDHK1) is a synthetic-essential gene in PTEN-deficient cancer and normal cells. The PTEN protein phosphatase dephosphorylates nuclear factor κB (NF-κB)-activating protein (NKAP) and limits NFκB activation to suppress expression of PDHK1, a NF-κB target gene. Loss of the PTEN protein phosphatase upregulates PDHK1 to induce aerobic glycolysis and PDHK1 cellular dependence. PTEN-deficient human tumors harbor increased PDHK1, a biomarker of decreased patient survival. This study uncovers a PTEN-regulated signaling pathway and reveals PDHK1 as a potential target in PTEN-deficient cancers.

The Gag protein PEG10 binds to RNA and regulates trophoblast stem cell lineage specification.

Peg10 (paternally expressed gene 10) is an imprinted gene that is essential for placental development. It is thought to derive from a Ty3-gyspy LTR (long terminal repeat) retrotransposon and retains Gag and Pol-like domains. Here we show that the Gag domain of PEG10 can promote vesicle budding similar to the HIV p24 Gag protein. Expressed in a subset of mouse endocrine organs in addition to the placenta, PEG10 was identified as a substrate of the deubiquitinating enzyme USP9X. Consistent with PEG10 having a critical role in placental development, PEG10-deficient trophoblast stem cells (TSCs) exhibited impaired differentiation into placental lineages. PEG10 expressed in wild-type, differentiating TSCs was bound to many cellular RNAs including Hbegf (Heparin-binding EGF-like growth factor), which is known to play an important role in placentation. Expression of Hbegf was reduced in PEG10-deficient TSCs suggesting that PEG10 might bind to and stabilize RNAs that are critical for normal placental development.

PTCD1 Is Required for Mitochondrial Oxidative-Phosphorylation: Possible Genetic Association with Alzheimer's Disease.

In addition to amyloid-ß plaques and tau tangles, mitochondrial dysfunction is implicated in the pathology of Alzheimer's disease (AD). Neurons heavily rely on mitochondrial function, and deficits in brain energy metabolism are detected early in AD; however, direct human genetic evidence for mitochondrial involvement in AD pathogenesis is limited. We analyzed whole-exome sequencing data of 4549 AD cases and 3332 age-matched controls and discovered that rare protein altering variants in the gene pentatricopeptide repeat-containing protein 1 (PTCD1) show a trend for enrichment in cases compared with controls. We show here that PTCD1 is required for normal mitochondrial rRNA levels, proper assembly of the mitochondrial ribosome and hence for mitochondrial translation and assembly of the electron transport chain. Loss of PTCD1 function impairs oxidative phosphorylation and forces cells to rely on glycolysis for energy production. Cells expressing the AD-linked variant of PTCD1 fail to sustain energy production under increased metabolic stress. In neurons, reduced PTCD1 expression leads to lower ATP levels and impacts spontaneous synaptic activity. Thus, our study uncovers a possible link between a protein required for mitochondrial function and energy metabolism and AD risk.SIGNIFICANCE STATEMENT Mitochondria are the main source of cellular energy and mitochondrial dysfunction is implicated in the pathology of Alzheimer's disease (AD) and other neurodegenerative disorders. Here, we identify a variant in the gene PTCD1 that is enriched in AD patients and demonstrate that PTCD1 is required for ATP generation through oxidative phosphorylation. PTCD1 regulates the level of 16S rRNA, the backbone of the mitoribosome, and is essential for mitochondrial translation and assembly of the electron transport chain. Cells expressing the AD-associated variant fail to maintain adequate ATP production during metabolic stress, and reduced PTCD1 activity disrupts neuronal energy homeostasis and dampens spontaneous transmission. Our work provides a mechanistic link between a protein required for mitochondrial function and genetic AD risk.

OTULIN limits cell death and inflammation by deubiquitinating LUBAC.

OTULIN (OTU deubiquitinase with linear linkage specificity) removes linear polyubiquitin from proteins that have been modified by LUBAC (linear ubiquitin chain assembly complex) and is critical for preventing auto-inflammatory disease1,2 and embryonic lethality during mouse development3. Here we show that OTULIN promotes rather than counteracts LUBAC activity by preventing its auto-ubiquitination with linear polyubiquitin. Thus, knock-in mice that express catalytically inactive OTULIN, either constitutively or selectively in endothelial cells, resembled LUBAC-deficient mice4 and died midgestation as a result of cell death mediated by TNFR1 (tumour necrosis factor receptor 1) and the kinase activity of RIPK1 (receptor-interacting protein kinase 1). Inactivation of OTULIN in adult mice also caused pro-inflammatory cell death. Accordingly, embryonic lethality and adult auto-inflammation were prevented by the combined loss of cell death mediators: caspase 8 for apoptosis and RIPK3 for necroptosis. Unexpectedly, OTULIN mutant mice that lacked caspase 8 and RIPK3 died in the perinatal period, exhibiting enhanced production of type I interferon that was dependent on RIPK1. Collectively, our results indicate that OTULIN and LUBAC function in a linear pathway, and highlight a previously unrecognized interaction between linear ubiquitination, regulators of cell death, and induction of type I interferon.

Selective autophagy of the adaptor TRIF regulates innate inflammatory signaling.

Defective autophagy is linked to diseases such as rheumatoid arthritis, lupus and inflammatory bowel disease (IBD). However, the mechanisms by which autophagy limits inflammation remain poorly understood. Here we found that loss of the autophagy-related gene Atg16l1 promoted accumulation of the adaptor TRIF and downstream signaling in macrophages. Multiplex proteomic profiling identified SQSTM1 and Tax1BP1 as selective autophagy-related receptors that mediated the turnover of TRIF. Knockdown of Tax1bp1 increased production of the cytokines IFN-ß and IL-1ß. Mice lacking Atg16l1 in myeloid cells succumbed to lipopolysaccharide-mediated sepsis but enhanced their clearance of intestinal Salmonella typhimurium in an interferon receptor-dependent manner. Human macrophages with the Crohn's disease-associated Atg16l1 variant T300A exhibited more production of IFN-ß and IL-1ß. An elevated interferon-response gene signature was observed in patients with IBD who were resistant to treatment with an antibody to the cytokine TNF. These findings identify selective autophagy as a key regulator of signaling via the innate immune system.

The mTOR Complex Controls HIV Latency.

A population of CD4 T lymphocytes harboring latent HIV genomes can persist in patients on antiretroviral therapy, posing a barrier to HIV eradication. To examine cellular complexes controlling HIV latency, we conducted a genome-wide screen with a pooled ultracomplex shRNA library and in vitro system modeling HIV latency and identified the mTOR complex as a modulator of HIV latency. Knockdown of mTOR complex subunits or pharmacological inhibition of mTOR activity suppresses reversal of latency in various HIV-1 latency models and HIV-infected patient cells. mTOR inhibitors suppress HIV transcription both through the viral transactivator Tat and via Tat-independent mechanisms. This inhibition occurs at least in part via blocking the phosphorylation of CDK9, a p-TEFb complex member that serves as a cofactor for Tat-mediated transcription. The control of HIV latency by mTOR signaling identifies a pathway that may have significant therapeutic opportunities.

A combined proteomics/genomics approach links hepatitis C virus infection with nonsense-mediated mRNA decay.

Hepatitis C virus (HCV) is a leading cause of liver disease, but insight into virus-host interactions remains limited. We systematically used affinity purification/mass spectrometry to define the host interactions of all ten HCV proteins in hepatoma cells. We combined these studies with RNAi knockdown of corresponding genes using a two-step scoring approach to generate a map of 139 high-confidence HCV-host protein-protein interactions. We found mitochondrial proteins highly involved in HCV infection and characterized an interaction between the viral core protein and host protein within bgcn homolog (WIBG). Expression of core prevents WIBG from binding its regular interaction partners Y14 and Magoh, two known mediators of the nonsense-mediated mRNA decay pathway. We discovered that this surveillance pathway is disrupted in HCV-infected cells, causing potentially harmful transcripts to accumulate. Our study provides a comprehensive view of HCV-host interactions and uncovers mechanisms for how HCV perturbs host functions during infection.

Global mapping of herpesvirus-host protein complexes reveals a transcription strategy for late genes.

Mapping host-pathogen interactions has proven instrumental for understanding how viruses manipulate host machinery and how numerous cellular processes are regulated. DNA viruses such as herpesviruses have relatively large coding capacity and thus can target an extensive network of cellular proteins. To identify the host proteins hijacked by this pathogen, we systematically affinity tagged and purified all 89 proteins of Kaposi's sarcoma-associated herpesvirus (KSHV) from human cells. Mass spectrometry of this material identified over 500 virus-host interactions. KSHV causes AIDS-associated cancers, and its interaction network is enriched for proteins linked to cancer and overlaps with proteins that are also targeted by HIV-1. We found that the conserved KSHV protein ORF24 binds to RNA polymerase II and brings it to viral late promoters by mimicking and replacing cellular TATA-box-binding protein (TBP). This is required for herpesviral late gene expression, a complex and poorly understood phase of the viral lifecycle.

Affinity purification-mass spectrometry and network analysis to understand protein-protein interactions.

By determining protein-protein interactions in normal, diseased and infected cells, we can improve our understanding of cellular systems and their reaction to various perturbations. In this protocol, we discuss how to use data obtained in affinity purification-mass spectrometry (AP-MS) experiments to generate meaningful interaction networks and effective figures. We begin with an overview of common epitope tagging, expression and AP practices, followed by liquid chromatography-MS (LC-MS) data collection. We then provide a detailed procedure covering a pipeline approach to (i) pre-processing the data by filtering against contaminant lists such as the Contaminant Repository for Affinity Purification (CRAPome) and normalization using the spectral index (SIN) or normalized spectral abundance factor (NSAF); (ii) scoring via methods such as MiST, SAInt and CompPASS; and (iii) testing the resulting scores. Data formats familiar to MS practitioners are then transformed to those most useful for network-based analyses. The protocol also explores methods available in Cytoscape to visualize and analyze these types of interaction data. The scoring pipeline can take anywhere from 1 d to 1 week, depending on one's familiarity with the tools and data peculiarities. Similarly, the network analysis and visualization protocol in Cytoscape takes 2-4 h to complete with the provided sample data, but we recommend taking days or even weeks to explore one's data and find the right questions.

Integration of protein abundance and structure data reveals competition in the ErbB signaling network.

The mechanisms of context-specific differences in signal transduction, such as those that occur among different cell types, are not fully understood. One possibility is that differences in the abundance of proteins change signaling outputs because these proteins compete for binding to hub proteins at critical network branch points. Focusing on the ErbB signaling, we created a protein interaction network that included information about protein domains and analyzed the role of competing protein interactions. By leveraging three-dimensional protein structures to infer steric interactions among binding partners for a common binding domain or linear motif (node) and including information about protein abundance and interaction affinities, we identified a large number of competitive, mutually exclusive (XOR) protein interactions. Modeling changes in protein abundance with different patterns of partner proteins and XOR nodes (XOR motifs) revealed that each motif conferred a different response. We experimentally investigated the XOR motif containing the hub protein Ras and its binding partners RIN1 (Ras and Rab interactor 1) and CRAF (v-raf-leukemia viral oncogene 1). Consistent with the computational prediction, overexpression of RIN1 in cultured cells decreased the phosphorylation of CRAF and its downstream targets. Thus, our analyses provide evidence that variation in the abundance of proteins that compete for binding to XOR nodes could contribute to context-specific signaling plasticity.

Protein-peptide complex prediction through fragment interaction patterns.

The number of protein-peptide interactions in a cell is so large that experimental determination of all these complex structures would be a daunting task. Although homology modeling and refinement protocols have vastly improved the number and quality of predicted structural models, ab initio methods are still challenged by both the large number of possible docking sites and the conformational space accessible to flexible peptides. We present a method that addresses these challenges by sampling the entire accessible surface of a protein with a reduced conformational space of interacting backbone fragment pairs from unrelated structures. We demonstrate its potential by predicting ab initio the bound structure for a variety of protein-peptide complexes. In addition, we show the potential of our method for the discovery of domain interaction sites and domain-domain docking.

The multiple-specificity landscape of modular peptide recognition domains.

Modular protein interaction domains form the building blocks of eukaryotic signaling pathways. Many of them, known as peptide recognition domains, mediate protein interactions by recognizing short, linear amino acid stretches on the surface of their cognate partners with high specificity. Residues in these stretches are usually assumed to contribute independently to binding, which has led to a simplified understanding of protein interactions. Conversely, we observe in large binding peptide data sets that different residue positions display highly significant correlations for many domains in three distinct families (PDZ, SH3 and WW). These correlation patterns reveal a widespread occurrence of multiple binding specificities and give novel structural insights into protein interactions. For example, we predict a new binding mode of PDZ domains and structurally rationalize it for DLG1 PDZ1. We show that multiple specificity more accurately predicts protein interactions and experimentally validate some of the predictions for the human proteins DLG1 and SCRIB. Overall, our results reveal a rich specificity landscape in peptide recognition domains, suggesting new ways of encoding specificity in protein interaction networks.