APOSTL: An Interactive Galaxy Pipeline for Reproducible Analysis of Affinity Proteomics Data

Regulation of Enhancers by SUMOylation Through TFAP2C Binding and Recruitment of HDAC Complex to the Chromatin

Enhancers are fundamental to gene regulation. Post-translational modifications by the small ubiquitin-like modifiers (SUMO) modify chromatin regulation enzymes, including histone acetylases and deacetylases. However, it remains unclear whether SUMOylation regulates enhancer marks, acetylation at the 27th lysine residue of the histone H3 protein (H3K27Ac). To investigate whether SUMOylation regulates H3K27Ac, we performed genome-wide ChIP-seq analyses and discovered that knockdown (KD) of the SUMO activating enzyme catalytic subunit UBA2 reduced H3K27Ac at most enhancers. Bioinformatic analysis revealed that TFAP2C-binding sites are enriched in enhancers whose H3K27Ac was reduced by UBA2 KD. ChIP-seq analysis in combination with molecular biological methods showed that TFAP2C binding to enhancers increased upon UBA2 KD or inhibition of SUMOylation by a small molecule SUMOylation inhibitor. However, this is not due to the SUMOylation of TFAP2C itself. Proteomics analysis of TFAP2C interactome on the chromatin identified histone deacetylation (HDAC) and RNA splicing machineries that contain many SUMOylation targets. TFAP2C KD reduced HDAC1 binding to chromatin and increased H3K27Ac marks at enhancer regions, suggesting that TFAP2C is important in recruiting HDAC machinery. Taken together, our findings provide insights into the regulation of enhancer marks by SUMOylation and TFAP2C and suggest that SUMOylation of proteins in the HDAC machinery regulates their recruitments to enhancers.

Extracellular Proximity Labeling Reveals an Expanded Interactome for the Matrisome Protein TIMP2

Classical methods of investigating protein-protein interactions (PPIs) are generally performed in non-living systems, yet in recent years new technologies utilizing proximity labeling (PL) have given researchers the tools to explore proximal PPIs in living systems. PL has distinct advantages over traditional protein interactome studies, such as the ability to identify weak and transient interactions in vitro and in vivo. Most PL studies are performed on targets within the cell or on the cell membrane. We have adapted the original PL method to investigate PPIs within the extracellular compartment, using both BioID2 and TurboID, that we term extracellular PL (ePL). To demonstrate the utility of this modified technique, we investigate the interactome of the widely expressed matrisome protein tissue inhibitor of metalloproteinases 2 (TIMP2). Tissue inhibitors of metalloproteinases (TIMPs) are a family of multi-functional proteins that were initially defined by their ability to inhibit the enzymatic activity of metalloproteinases (MPs), the major mediators of extracellular matrix (ECM) breakdown and turnover. TIMP2 exhibits a broad expression profile and is often abundant in both normal and diseased tissues. Understanding the functional transformation of matrisome regulators, like TIMP2, during the evolution of tissue microenvironments associated with disease progression is essential for the development of ECM-targeted therapeutics. Using carboxyl- and amino-terminal fusion proteins of TIMP2 with BioID2 and TurboID, we describe the TIMP2 proximal interactome. We also illustrate how the TIMP2 interactome changes in the presence of different stimuli, in different cell types, in unique culture conditions (2D vs 3D), and with different reaction kinetics (BioID2 vs. TurboID); demonstrating the power of this technique versus classical PPI methods. We propose that the screening of matrisome targets in disease models using ePL will reveal new therapeutic targets for further comprehensive studies.

Integrated Proteomics-Based Physical and Functional Mapping of AXL Kinase Signaling Pathways and Inhibitors Define Its Role in Cell Migration

To better understand the signaling complexity of AXL, a member of the tumor-associated macrophage (TAM) receptor tyrosine kinase family, we created a physical and functional map of AXL signaling interactions, phosphorylation events, and target-engagement of three AXL tyrosine kinase inhibitors (TKI). We assessed AXL protein complexes using proximity-dependent biotinylation (BioID), effects of AXL TKI on global phosphoproteins using mass spectrometry, and target engagement of AXL TKI using activity-based protein profiling. BioID identifies AXL-interacting proteins that are mostly involved in cell adhesion/migration. Global phosphoproteomics show that AXL inhibition decreases phosphorylation of peptides involved in phosphatidylinositol-mediated signaling and cell adhesion/migration. Comparison of three AXL inhibitors reveals that TKI RXDX-106 inhibits pAXL, pAKT, and migration/invasion of these cells without reducing their viability, while bemcentinib exerts AXL-independent phenotypic effects on viability. Proteomic characterization of these TKIs demonstrates that they inhibit diverse targets in addition to AXL, with bemcentinib having the most off-targets. AXL and EGFR TKI cotreatment did not reverse resistance in cell line models of erlotinib resistance. However, a unique vulnerability was identified in one resistant clone, wherein combination of bemcentinib and erlotinib inhibited cell viability and signaling. We also show that AXL is overexpressed in approximately 30% to 40% of nonsmall but rarely in small cell lung cancer. Cell lines have a wide range of AXL expression, with basal activation detected rarely.

IMPLICATIONS

Our study defines mechanisms of action of AXL in lung cancers which can be used to establish assays to measure drug targetable active AXL complexes in patient tissues and inform the strategy for targeting it's signaling as an anticancer therapy.

CANVS: an easy-to-use application for the analysis and visualization of mass spectrometry-based protein-protein interaction/association data

The elucidation of a protein’s interaction/association network is important for defining its biological function. Mass spectrometry–based proteomic approaches have emerged as powerful tools for identifying protein–protein interactions (PPIs) and protein–protein associations (PPAs). However, interactome/association experiments are difficult to interpret, considering the complexity and abundance of data that are generated. Although tools have been developed to identify protein interactions/associations quantitatively, there is still a pressing need for easy-to-use tools that allow users to contextualize their results. To address this, we developed CANVS, a computational pipeline that cleans, analyzes, and visualizes mass spectrometry–based interactome/association data. CANVS is wrapped as an interactive Shiny dashboard with simple requirements, allowing users to interface easily with the pipeline, analyze complex experimental data, and create PPI/A networks. The application integrates systems biology databases such as BioGRID and CORUM to contextualize the results. Furthermore, CANVS features a Gene Ontology tool that allows users to identify relevant GO terms in their results and create visual networks with proteins associated with relevant GO terms. Overall, CANVS is an easy-to-use application that benefits all researchers, especially those who lack an established bioinformatic pipeline and are interested in studying interactome/association data.

Hemeprotein Tpx1 interacts with cell-surface heme transporter Str3 in Schizosaccharomyces pombe

Str3 is a transmembrane protein that mediates low-affinity heme uptake in Schizosaccharomyces pombe. Under iron-limiting conditions, Str3 remains at the cell surface in the presence of increasing hemin concentrations. Using a proximity-dependent biotinylation approach coupled to mass spectrometry and coimmunoprecipitation assays, we report that the peroxiredoxin Tpx1 is a binding partner of Str3. Under microaerobic conditions, cells deficient in heme biosynthesis and lacking the heme receptor Shu1 exhibit poor hemin-dependent growth in the absence of Tpx1. Analysis of membrane protein preparations from iron-starved hem1Δ shu1Δ str3Δ tpx1Δ cells coexpressing Str3-GFP and TAP-Tpx1 showed that TAP-Tpx1 is enriched in membrane protein fractions in response to hemin. Bimolecular fluorescence complementation assays brought additional evidence that an interaction between Tpx1 and Str3 occurs at the plasma membrane. Results showed that Tpx1 exhibits an equilibrium constant value of 0.26 μM for hemin. The association of Tpx1 with hemin protects hemin from degradation by H₂ O₂ . The peroxidase activity of hemin is lowered when it is bound to Tpx1. Taken together, these results revealed that Tpx1 is a novel interacting partner of Str3. Our data are the first example of an interaction between a cytoplasmic heme-binding protein and a cell-surface heme transporter.

Network of Interactions between ZIKA Virus Non-Structural Proteins and Human Host Proteins

The Zika virus (ZIKV) is a mosquito-borne Flavivirus and can be transmitted through an infected mosquito bite or through human-to-human interaction by sexual activity, blood transfusion, breastfeeding, or perinatal exposure. After the 2015-2016 outbreak in Brazil, a strong link between ZIKV infection and microcephaly emerged. ZIKV specifically targets human neural progenitor cells, suggesting that proteins encoded by ZIKV bind and inactivate host cell proteins, leading to microcephaly. Here, we present a systematic annotation of interactions between human proteins and the seven non-structural ZIKV proteins corresponding to a Brazilian isolate. The interaction network was generated by combining tandem-affinity purification followed by mass spectrometry with yeast two-hybrid screens. We identified 150 human proteins, involved in distinct biological processes, as interactors to ZIKV non-structural proteins. Our interacting network is composed of proteins that have been previously associated with microcephaly in human genetic disorders and/or animal models. Further, we show that the protein inhibitor of activated STAT1 (PIAS1) interacts with NS5 and modulates its stability. This study builds on previously published interacting networks of ZIKV and genes related to autosomal recessive primary microcephaly to generate a catalog of human cellular targets of ZIKV proteins implicated in processes related to microcephaly in humans. Collectively, these data can be used as a resource for future characterization of ZIKV infection biology and help create a basis for the discovery of drugs that may disrupt the interaction and reduce the health damage to the fetus.

Proximity labeling reveals novel interactomes in live Drosophila tissue

Gametogenesis is dependent on intercellular communication facilitated by stable intercellular bridges connecting developing germ cells. During Drosophila oogenesis, intercellular bridges (referred to as ring canals; RCs) have a dynamic actin cytoskeleton that drives their expansion to a diameter of 10 μm. Although multiple proteins have been identified as components of RCs, we lack a basic understanding of how RC proteins interact together to form and regulate the RC cytoskeleton. Thus, here, we optimized a procedure for proximity-dependent biotinylation in live tissue using the APEX enzyme to interrogate the RC interactome. APEX was fused to four different RC components (RC-APEX baits) and 55 unique high-confidence prey were identified. The RC-APEX baits produced almost entirely distinct interactomes that included both known RC proteins and uncharacterized proteins. A proximity ligation assay was used to validate close-proximity interactions between the RC-APEX baits and their respective prey. Furthermore, an RNA interference screen revealed functional roles for several high-confidence prey genes in RC biology. These findings highlight the utility of enzyme-catalyzed proximity labeling for protein interactome analysis in live tissue and expand our understanding of RC biology.

An immunoproteomic approach to characterize the CAR interactome and signalosome

Adoptive transfer of T cells that express a chimeric antigen receptor (CAR) is an approved immunotherapy that may be curative for some hematological cancers. To better understand the therapeutic mechanism of action, we systematically analyzed CAR signaling in human primary T cells by mass spectrometry. When we compared the interactomes and the signaling pathways activated by distinct CAR-T cells that shared the same antigen-binding domain but differed in their intracellular domains and their in vivo antitumor efficacy, we found that only second-generation CARs induced the expression of a constitutively phosphorylated form of CD3ζ that resembled the endogenous species. This phenomenon was independent of the choice of costimulatory domains, or the hinge/transmembrane region. Rather, it was dependent on the size of the intracellular domains. Moreover, the second-generation design was also associated with stronger phosphorylation of downstream secondary messengers, as evidenced by global phosphoproteome analysis. These results suggest that second-generation CARs can activate additional sources of CD3ζ signaling, and this may contribute to more intense signaling and superior antitumor efficacy that they display compared to third-generation CARs. Moreover, our results provide a deeper understanding of how CARs interact physically and/or functionally with endogenous T cell molecules, which will inform the development of novel optimized immune receptors.

Off-target based drug repurposing opportunities for tivantinib in acute myeloid leukemia

GSK3α has been identified as a new target in the treatment of acute myeloid leukemia (AML). However, most GSK3 inhibitors lack specificity for GSK3α over GSK3β and other kinases. We have previously shown in lung cancer cells that GSK3α and to a lesser extent GSK3β are inhibited by the advanced clinical candidate tivantinib (ARQ197), which was designed as a MET inhibitor. Thus, we hypothesized that tivantinib would be an effective therapy for the treatment of AML. Here, we show that tivantinib has potent anticancer activity across several AML cell lines and primary patient cells. Tivantinib strongly induced apoptosis, differentiation and G2/M cell cycle arrest and caused less undesirable stabilization of β-catenin compared to the pan-GSK3 inhibitor LiCl. Subsequent drug combination studies identified the BCL-2 inhibitor ABT-199 to synergize with tivantinib while cytarabine combination with tivantinib was antagonistic. Interestingly, the addition of ABT-199 to tivantinib completely abrogated tivantinib induced β-catenin stabilization. Tivantinib alone, or in combination with ABT-199, downregulated anti-apoptotic MCL-1 and BCL-XL levels, which likely contribute to the observed synergy. Importantly, tivantinib as single agent or in combination with ABT-199 significantly inhibited the colony forming capacity of primary patient AML bone marrow mononuclear cells. In summary, tivantinib is a novel GSK3α/β inhibitor that potently kills AML cells and tivantinib single agent or combination therapy with ABT-199 may represent attractive new therapeutic opportunities for AML.

The Galaxy Platform for Reproducible Affinity Proteomic Mass Spectrometry Data Analysis

Affinity proteomics (AP-MS) is growing in importance for characterizing protein-protein interactions (PPIs) in the form of protein complexes and signaling networks. The AP-MS approach necessitates several different software tools, integrated into reproducible and accessible workflows. However, if the scientist (e.g., a bench biologist) lacks a computational background, then managing large AP-MS datasets can be challenging, manually formatting AP-MS data for input into analysis software can be error-prone, and data visualization involving dozens of variables can be laborious. One solution to address these issues is Galaxy, an open source and web-based platform for developing and deploying user-friendly computational pipelines or workflows. Here, we describe a Galaxy-based platform enabling AP-MS analysis. This platform enables researchers with no prior computational experience to begin with data from a mass spectrometer (e.g., peaklists in mzML format) and perform peak processing, database searching, assignment of interaction confidence scores, and data visualization with a few clicks of a mouse. We provide sample data and a sample workflow with step-by-step instructions to quickly acquaint users with the process.

Targeting the BRD4-HOXB13 Coregulated Transcriptional Networks with Bromodomain-Kinase Inhibitors to Suppress Metastatic Castration-Resistant Prostate Cancer

Resistance to androgen receptor (AR) antagonists is a significant problem in the treatment of castration-resistant prostate cancers (CRPC). Identification of the mechanisms by which CRPCs evade androgen deprivation therapies (ADT) is critical to develop novel therapeutics. We uncovered that CRPCs rely on BRD4-HOXB13 epigenetic reprogramming for androgen-independent cell proliferation. Mechanistically, BRD4, a member of the BET bromodomain family, epigenetically promotes HOXB13 expression. Consistently, genetic disruption of HOXB13 or pharmacological suppression of its mRNA and protein expression by the novel dual-activity BET bromodomain-kinase inhibitors directly correlates with rapid induction of apoptosis, potent inhibition of tumor cell proliferation and cell migration, and suppression of CRPC growth. Integrative analysis revealed that the BRD4-HOXB13 transcriptome comprises a proliferative gene network implicated in cell-cycle progression, nucleotide metabolism, and chromatin assembly. Notably, although the core HOXB13 target genes responsive to BET inhibitors (HOTBIN10) are overexpressed in metastatic cases, in ADT-treated CRPC cell lines and patient-derived circulating tumor cells (CTC) they are insensitive to AR depletion or blockade. Among the HOTBIN10 genes, AURKB and MELK expression correlates with HOXB13 expression in CTCs of mCRPC patients who did not respond to abiraterone (ABR), suggesting that AURKB inhibitors could be used additionally against high-risk HOXB13-positive metastatic prostate cancers. Combined, our study demonstrates that BRD4-HOXB13-HOTBIN10 regulatory circuit maintains the malignant state of CRPCs and identifies a core proproliferative network driving ADT resistance that is targetable with potent dual-activity bromodomain-kinase inhibitors.

An architecture for genomics analysis in a clinical setting using Galaxy and Docker

Next-generation sequencing is used on a daily basis to perform molecular analysis to determine subtypes of disease (e.g., in cancer) and to assist in the selection of the optimal treatment. Clinical bioinformatics handles the manipulation of the data generated by the sequencer, from the generation to the analysis and interpretation. Reproducibility and traceability are crucial issues in a clinical setting. We have designed an approach based on Docker container technology and Galaxy, the popular bioinformatics analysis support open-source software. Our solution simplifies the deployment of a small-size analytical platform and simplifies the process for the clinician. From the technical point of view, the tools embedded in the platform are isolated and versioned through Docker images. Along the Galaxy platform, we also introduce the AnalysisManager, a solution that allows single-click analysis for biologists and leverages standardized bioinformatics application programming interfaces. We added a Shiny/R interactive environment to ease the visualization of the outputs. The platform relies on containers and ensures the data traceability by recording analytical actions and by associating inputs and outputs of the tools to EDAM ontology through ReGaTe. The source code is freely available on Github at https://github.com/CARPEM/GalaxyDocker.

Updates on resources, software tools, and databases for plant proteomics in 2016-2017

Proteomics data processing, annotation, and analysis can often lead to major hurdles in large-scale high-throughput bottom-up proteomics experiments. Given the recent rise in protein-based big datasets being generated, efforts in in silico tool development occurrences have had an unprecedented increase; so much so, that it has become increasingly difficult to keep track of all the advances in a particular academic year. However, these tools benefit the plant proteomics community in circumventing critical issues in data analysis and visualization, as these continually developing open-source and community-developed tools hold potential in future research efforts. This review will aim to introduce and summarize more than 50 software tools, databases, and resources developed and published during 2016-2017 under the following categories: tools for data pre-processing and analysis, statistical analysis tools, peptide identification tools, databases and spectral libraries, and data visualization and interpretation tools. Intended for a well-informed proteomics community, finally, efforts in data archiving and validation datasets for the community will be discussed as well. Additionally, the author delineates the current and most commonly used proteomics tools in order to introduce novice readers to this -omics discovery platform.

Sustained activation of the AKT/mTOR and MAP kinase pathways mediate resistance to the Src inhibitor, dasatinib, in thyroid cancer

New targeted therapies are needed for advanced thyroid cancer. Our lab has shown that Src is a key mediator of tumorigenic processes in thyroid cancer. However, single-agent Src inhibitors have had limited efficacy in solid tumors. In order to more effectively target Src in the clinic, our lab has previously generated four thyroid cancer cell lines that are resistant to dasatinib through gradual dose escalation. We further tested two additional Src inhibitors and shown the dasatinib-resistant (DasRes) cells exhibit cross-resistance to saracatinib, but are sensitive to bosutinib, suggesting that unique off-targets of bosutinib play an important role in mediating sensitivity to bosutinib. To identify the kinases targeted by dasatinib and bosutinib, we utilized an unbiased compound centric chemical proteomics screen. We identified 33 kinases that were enriched in the bosutinib pull down. Using the STRING database to map protein-protein interactions of the unique bosutinib targets, we identified a signaling axis which included mTOR, FAK, and MEK. Inhibition of the mTOR, MEK, and Src/FAK nodes simultaneously was the most effective at reducing cell growth and survival. Overall, these studies have identified key mediators of Src inhibitor resistance, and show that targeting these signaling nodes are necessary for anti-tumor efficacy.

Polypharmacology-based ceritinib repurposing using integrated functional proteomics

Targeted drugs are effective when they directly inhibit strong disease drivers, but only a small fraction of diseases feature defined actionable drivers. Alternatively, network-based approaches can uncover new therapeutic opportunities. Applying an integrated phenotypic screening, chemical and phosphoproteomics strategy, here we describe the anaplastic lymphoma kinase (ALK) inhibitor ceritinib as having activity across several ALK-negative lung cancer cell lines and identify new targets and network-wide signaling effects. Combining pharmacological inhibitors and RNA interference revealed a polypharmacology mechanism involving the noncanonical targets IGF1R, FAK1, RSK1 and RSK2. Mutating the downstream signaling hub YB1 protected cells from ceritinib. Consistent with YB1 signaling being known to cause taxol resistance, combination of ceritinib with paclitaxel displayed strong synergy, particularly in cells expressing high FAK autophosphorylation, which we show to be prevalent in lung cancer. Together, we present a systems chemical biology platform for elucidating multikinase inhibitor polypharmacology mechanisms, subsequent design of synergistic drug combinations, and identification of mechanistic biomarker candidates.

Dual Targeting of WEE1 and PLK1 by AZD1775 Elicits Single Agent Cellular Anticancer Activity

Inhibition of the WEE1 tyrosine kinase enhances anticancer chemotherapy efficacy. Accordingly, the WEE1 inhibitor AZD1775 (previously MK-1775) is currently under evaluation in clinical trials for cancer in combination with chemotherapy. AZD1775 has been reported to display high selectivity and is therefore used in many studies as a probe to interrogate WEE1 biology. However, AZD1775 also exhibits anticancer activity as a single agent although the underlying mechanism is not fully understood. Using a chemical proteomics approach, we here describe a proteome-wide survey of AZD1775 targets in lung cancer cells and identify several previously unknown targets in addition to WEE1. In particular, we observed polo-like kinase 1 (PLK1) as a new target of AZD1775. Importantly, in vitro kinase assays showed PLK1 and WEE1 to be inhibited by AZD1775 with similar potency. Subsequent loss-of-function experiments using RNAi for WEE1 and PLK1 suggested that targeting PLK1 enhances the pro-apoptotic and antiproliferative effects observed with WEE1 knockdown. Combination of RNAi with AZD1775 treatment suggested WEE1 and PLK1 to be the most relevant targets for mediating AZD1775's anticancer effects. Furthermore, disruption of WEE1 by CRISPR-Cas9 sensitized H322 lung cancer cells to AZD1775 to a similar extent as the potent PLK1 inhibitor BI-2536 suggesting a complex crosstalk between PLK1 and WEE1. In summary, we show that AZD1775 is a potent dual WEE1 and PLK1 inhibitor, which limits its use as a specific molecular probe for WEE1. However, PLK1 inhibition makes important contributions to the single agent mechanism of action of AZD1775 and enhances its anticancer effects.