Alexey Stukalov

Although the genes essential for life have been identified in less complex model organisms, their elucidation in human cells has been hindered by technical barriers. We used extensive mutagenesis in haploid human cells to identify approximately 2000 genes required for optimal fitness under culture conditions. To study the principles of genetic interactions in human cells, we created a synthetic lethality network focused on the secretory pathway based exclusively on mutations. This revealed a genetic cross-talk governing Golgi homeostasis, an additional subunit of the human oligosaccharyltransferase complex, and a phosphatidylinositol 4-kinase β adaptor hijacked by viruses. The synthetic lethality map parallels observations made in yeast and projects a route forward to reveal genetic networks in diverse aspects of human cell biology.

The emergence and global spread of SARS-CoV-2 has resulted in the urgent need for an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Several individual omics studies have extended our knowledge of COVID-19 pathophysiology1-10. Integration of such datasets to obtain a holistic view of virus-host interactions and to define the pathogenic properties of SARS-CoV-2 is limited by the heterogeneity of the experimental systems. Here we report a concurrent multi-omics study of SARS-CoV-2 and SARS-CoV. Using state-of-the-art proteomics, we profiled the interactomes of both viruses, as well as their influence on the transcriptome, proteome, ubiquitinome and phosphoproteome of a lung-derived human cell line. Projecting these data onto the global network of cellular interactions revealed crosstalk between the perturbations taking place upon infection with SARS-CoV-2 and SARS-CoV at different levels and enabled identification of distinct and common molecular mechanisms of these closely related coronaviruses. The TGF-β pathway, known for its involvement in tissue fibrosis, was specifically dysregulated by SARS-CoV-2 ORF8 and autophagy was specifically dysregulated by SARS-CoV-2 ORF3. The extensive dataset (available at https://covinet.innatelab.org ) highlights many hotspots that could be targeted by existing drugs and may be used to guide rational design of virus- and host-directed therapies, which we exemplify by identifying inhibitors of kinases and matrix metalloproteases with potent antiviral effects against SARS-CoV-2.

Activated RAS GTPase signalling is a critical driver of oncogenic transformation and malignant disease. Cellular models of RAS-dependent cancers have been used to identify experimental small molecules, such as SCH51344, but their molecular mechanism of action remains generally unknown. Here, using a chemical proteomic approach, we identify the target of SCH51344 as the human mutT homologue MTH1 (also known as NUDT1), a nucleotide pool sanitizing enzyme. Loss-of-function of MTH1 impaired growth of KRAS tumour cells, whereas MTH1 overexpression mitigated sensitivity towards SCH51344. Searching for more drug-like inhibitors, we identified the kinase inhibitor crizotinib as a nanomolar suppressor of MTH1 activity. Surprisingly, the clinically used (R)-enantiomer of the drug was inactive, whereas the (S)-enantiomer selectively inhibited MTH1 catalytic activity. Enzymatic assays, chemical proteomic profiling, kinome-wide activity surveys and MTH1 co-crystal structures of both enantiomers provide a rationale for this remarkable stereospecificity. Disruption of nucleotide pool homeostasis via MTH1 inhibition by (S)-crizotinib induced an increase in DNA single-strand breaks, activated DNA repair in human colon carcinoma cells, and effectively suppressed tumour growth in animal models. Our results propose (S)-crizotinib as an attractive chemical entity for further pre-clinical evaluation, and small-molecule inhibitors of MTH1 in general as a promising novel class of anticancer agents. A chemoproteomic screen is used here to identify MTH1 as the target of SCH51344, an experimental RAS-dependent cancer drug; a further search for inhibitors revealed (S)-crizotinib as a potent MTH1 antagonist, which suppresses tumour growth in animal models of colon cancer, and could be part of a new class of anticancer drugs. Mutations in the Ras oncogene are associated with poor prognosis. It was known that overexpression of MTH1, a protein involved in preventing the incorporation of damaged bases into DNA, prevents Ras-induced senescence. In seeking to understand how damaged deoxynucleotides (dNTPs) promote cancer, Thomas Helleday and colleagues found that MTH1 activity is essential for the survival of transformed cells, and isolated two small-molecule MTH1 inhibitors, TH287 and TH588. In the presence of these hydrolase inhibitors, damaged nucleotides are incorporated into DNA only in cancer cells, causing cytotoxicity and eliciting a beneficial response in mouse xenograft cancer models. In a second study, Giulio Superti-Furga and colleagues sought to identify the target of a small molecule, SCH51344, that had been developed for use against Ras-dependent cancers and found that it inactivates MTH1. This allowed them to identify a new potent inhibitor of MTH1 that is enantiomer-selective, (S)-crizotinib. In the presence of this drug, tumour growth is suppressed in animal models of colon cancer.

Type 1 diabetes is characterized by the destruction of pancreatic β cells, and generating new insulin-producing cells from other cell types is a major aim of regenerative medicine. One promising approach is transdifferentiation of developmentally related pancreatic cell types, including glucagon-producing α cells. In a genetic model, loss of the master regulatory transcription factor Arx is sufficient to induce the conversion of α cells to functional β-like cells. Here, we identify artemisinins as small molecules that functionally repress Arx by causing its translocation to the cytoplasm. We show that the protein gephyrin is the mammalian target of these antimalarial drugs and that the mechanism of action of these molecules depends on the enhancement of GABAA receptor signaling. Our results in zebrafish, rodents, and primary human pancreatic islets identify gephyrin as a druggable target for the regeneration of pancreatic β cell mass from α cells.

The CEBPA gene is mutated in 9% of patients with acute myeloid leukemia (AML). Selective expression of a short (30-kDa) CCAAT-enhancer binding protein-α (C/EBPα) translational isoform, termed p30, represents the most common type of CEBPA mutation in AML. The molecular mechanisms underlying p30-mediated transformation remain incompletely understood. We show that C/EBPα p30, but not the normal p42 isoform, preferentially interacts with Wdr5, a key component of SET/MLL (SET-domain/mixed-lineage leukemia) histone-methyltransferase complexes. Accordingly, p30-bound genomic regions were enriched for MLL-dependent H3K4me3 marks. The p30-dependent increase in self-renewal and inhibition of myeloid differentiation required Wdr5, as downregulation of the latter inhibited proliferation and restored differentiation in p30-dependent AML models. OICR-9429 is a new small-molecule antagonist of the Wdr5-MLL interaction. This compound selectively inhibited proliferation and induced differentiation in p30-expressing human AML cells. Our data reveal the mechanism of p30-dependent transformation and establish the essential p30 cofactor Wdr5 as a therapeutic target in CEBPA-mutant AML.

Necroptosis is a form of regulated necrotic cell death mediated by receptor-interacting serine/threonine-protein kinase 1 (RIPK1) and RIPK3. Necroptotic cell death contributes to the pathophysiology of several disorders involving tissue damage, including myocardial infarction, stroke and ischemia-reperfusion injury. However, no inhibitors of necroptosis are currently in clinical use. Here we performed a phenotypic screen for small-molecule inhibitors of tumor necrosis factor-alpha (TNF-α)-induced necroptosis in Fas-associated protein with death domain (FADD)-deficient Jurkat cells using a representative panel of Food and Drug Administration (FDA)-approved drugs. We identified two anti-cancer agents, ponatinib and pazopanib, as submicromolar inhibitors of necroptosis. Both compounds inhibited necroptotic cell death induced by various cell death receptor ligands in human cells, while not protecting from apoptosis. Ponatinib and pazopanib abrogated phosphorylation of mixed lineage kinase domain-like protein (MLKL) upon TNF-α-induced necroptosis, indicating that both agents target a component upstream of MLKL. An unbiased chemical proteomic approach determined the cellular target spectrum of ponatinib, revealing key members of the necroptosis signaling pathway. We validated RIPK1, RIPK3 and transforming growth factor-β-activated kinase 1 (TAK1) as novel, direct targets of ponatinib by using competitive binding, cellular thermal shift and recombinant kinase assays. Ponatinib inhibited both RIPK1 and RIPK3, while pazopanib preferentially targeted RIPK1. The identification of the FDA-approved drugs ponatinib and pazopanib as cellular inhibitors of necroptosis highlights them as potentially interesting for the treatment of pathologies caused or aggravated by necroptotic cell death.

Coronavirus Disease-2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. It was first identified in Wuhan, China, and has since spread causing a global pandemic. Various studies have been performed to understand the molecular mechanisms of viral infection for predicting drug repurposing candidates. However, such information is spread across many publications and it is very time-consuming to access, integrate, explore, and exploit. We developed CoVex, the first interactive online platform for SARS-CoV-2 and SARS-CoV-1 host interactome exploration and drug (target) identification. CoVex integrates 1) experimentally validated virus-human protein interactions, 2) human protein-protein interactions and 3) drug-target interactions. The web interface allows user-friendly visual exploration of the virus-host interactome and implements systems medicine algorithms for network-based prediction of drugs. Thus, CoVex is an important resource, not only to understand the molecular mechanisms involved in SARS-CoV-2 and SARS-CoV-1 pathogenicity, but also in clinical research for the identification and prioritization of candidate therapeutics. We apply CoVex to investigate recent hypotheses on a systems biology level and to systematically explore the molecular mechanisms driving the virus life cycle. Furthermore, we extract and discuss drug repurposing candidates involved in these mechanisms. CoVex renders COVID-19 drug research systems-medicine-ready by giving the scientific community direct access to network medicine algorithms integrating virus-host-drug interactions. It is available at https://exbio.wzw.tum.de/covex/.

Zika virus (ZIKV) has recently emerged as a global health concern owing to its widespread diffusion and its association with severe neurological symptoms and microcephaly in newborns1. However, the molecular mechanisms that are responsible for the pathogenicity of ZIKV remain largely unknown. Here we use human neural progenitor cells and the neuronal cell line SK-N-BE2 in an integrated proteomics approach to characterize the cellular responses to viral infection at the proteome and phosphoproteome level, and use affinity proteomics to identify cellular targets of ZIKV proteins. Using this approach, we identify 386 ZIKV-interacting proteins, ZIKV-specific and pan-flaviviral activities as well as host factors with known functions in neuronal development, retinal defects and infertility. Moreover, our analysis identified 1,216 phosphorylation sites that are specifically up- or downregulated after ZIKV infection, indicating profound modulation of fundamental signalling pathways such as AKT, MAPK–ERK and ATM–ATR and thereby providing mechanistic insights into the proliferation arrest elicited by ZIKV infection. Functionally, our integrative study identifies ZIKV host-dependency factors and provides a comprehensive framework for a system-level understanding of ZIKV-induced perturbations at the levels of proteins and cellular pathways. Integrative analyses identify host proteins that are modulated by Zika virus at multiple levels and provide a comprehensive framework for the understanding of Zika virus-induced changes to cellular pathways.

Summary The global emergence of SARS-CoV-2 urgently requires an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Several individual omics studies have extended our knowledge of COVID-19 pathophysiology 1–10 . Integration of such datasets to obtain a holistic view of virus-host interactions and to define the pathogenic properties of SARS-CoV-2 is limited by the heterogeneity of the experimental systems. We therefore conducted a concurrent multi-omics study of SARS-CoV-2 and SARS-CoV. Using state-of-the-art proteomics, we profiled the interactome of both viruses, as well as their influence on transcriptome, proteome, ubiquitinome and phosphoproteome in a lung-derived human cell line. Projecting these data onto the global network of cellular interactions revealed crosstalk between the perturbations taking place upon SARS-CoV-2 and SARS-CoV infections at different layers and identified unique and common molecular mechanisms of these closely related coronaviruses. The TGF-β pathway, known for its involvement in tissue fibrosis, was specifically dysregulated by SARS-CoV-2 ORF8 and autophagy by SARS-CoV-2 ORF3. The extensive dataset (available at https://covinet.innatelab.org ) highlights many hotspots that can be targeted by existing drugs and it can guide rational design of virus- and host-directed therapies, which we exemplify by identifying kinase and MMPs inhibitors with potent antiviral effects against SARS-CoV-2.

The RAPTA pharmacophore was linked to beads to identify its biomolecular targets in cancer cells.

TANK-binding kinase 1 (TBK1) and inducible IκB-kinase (IKK-i) are central regulators of type-I interferon induction. They are associated with three adaptor proteins called TANK, Sintbad (or TBKBP1) and NAP1 (or TBKBP2, AZI2) whose functional relationship to TBK1 and IKK-i is poorly understood. We performed a systematic affinity purification–mass spectrometry approach to derive a comprehensive TBK1/IKK-i molecular network. The most salient feature of the network is the mutual exclusive interaction of the adaptors with the kinases, suggesting distinct alternative complexes. Immunofluorescence data indicated that the individual adaptors reside in different subcellular locations. TANK, Sintbad and NAP1 competed for binding of TBK1. The binding site for all three adaptors was mapped to the C-terminal coiled-coil 2 region of TBK1. Point mutants that affect binding of individual adaptors were used to reconstitute TBK1/IKK-i-deficient cells and dissect the functional relevance of the individual kinase-adaptor edges within the network. Using a microarray-derived gene expression signature of TBK1 in response virus infection or poly(I∶C) stimulation, we found that TBK1 activation was strictly dependent on the integrity of the TBK1/TANK interaction.

Nat. Chem. Biol. 11, 571–578 (2015); published online 13 July 2015; corrected online 20 August 2015 In the author list, affiliation and correspondence information for Cheryl Arrowsmith was missing. Her name should be accompanied by affiliation number 3 (signifying the Structural Genomics Consortium,University of Toronto, Toronto, Ontario, Canada) and by an asterisk indicating her status as a corresponding author.

The imprinted Airn macro long non-coding (lnc) RNA is an established example of a cis-silencing lncRNA. Airn expression is necessary to initiate paternal-specific silencing of the Igf2r gene, which is followed by gain of a somatic DNA methylation imprint on the silent Igf2r promoter. However, the developmental requirements for Airn initiation of Igf2r silencing and the role of Airn or DNA methylation in maintaining stable Igf2r repression have not been investigated. Here, we use inducible systems to control Airn expression during mouse embryonic stem cell (ESC) differentiation. By turning Airn expression off during ESC differentiation, we show that continuous Airn expression is needed to maintain Igf2r silencing, but only until the paternal Igf2r promoter is methylated. By conditionally turning Airn expression on, we show that Airn initiation of Igf2r silencing is not limited to one developmental 'window of opportunity' and can be maintained in the absence of DNA methylation. Together, this study shows that Airn expression is both necessary and sufficient to silence Igf2r throughout ESC differentiation and that the somatic methylation imprint, although not required to initiate or maintain silencing, adds a secondary layer of repressive epigenetic information.

The study aimed to identify genetic lesions associated with secondary acute myeloid leukemia (sAML) in comparison with AML arising de novo (dnAML) and assess their impact on patients' overall survival (OS). High-resolution genotyping and loss of heterozygosity mapping was performed on DNA samples from 86 sAML and 117 dnAML patients, using Affymetrix Genome-Wide Human SNP 6.0 arrays. Genes TP53, RUNX1, CBL, IDH1/2, NRAS, NPM1, and FLT3 were analyzed for mutations in all patients. We identified 36 recurrent cytogenetic aberrations (more than five events). Mutations in TP53, 9pUPD, and del7q (targeting CUX1 locus) were significantly associated with sAML, while NPM1 and FLT3 mutations associated with dnAML. Patients with sAML carrying TP53 mutations demonstrated lower 1-year OS rate than those with wild-type TP53 (14.3% ± 9.4% vs. 35.4% ± 7.2%; P = 0.002), while complex karyotype, del7q (CUX1) and del7p (IKZF1) showed no significant effect on OS. Multivariate analysis confirmed that mutant TP53 was the only independent adverse prognostic factor for OS in sAML (hazard ratio 2.67; 95% CI: 1.33-5.37; P = 0.006). Patients with dnAML and complex karyotype carried sAML-associated defects (TP53 defects in 54.5%, deletions targeting FOXP1 and ETV6 loci in 45.4% of the cases). We identified several co-occurring lesions associated with either sAML or dnAML diagnosis. Our data suggest that distinct genetic lesions drive leukemogenesis in sAML. High karyotype complexity of sAML patients does not influence OS. Somatic mutations in TP53 are the only independent adverse prognostic factor in sAML. Patients with dnAML and complex karyotype show genetic features associated with sAML and myeloproliferative neoplasms.

Introducing engineered nanoparticles (NPs) into a biofluid such as blood plasma leads to the formation of a selective and reproducible protein corona at the particle-protein interface, driven by the relationship between protein-NP affinity and protein abundance. This enables scalable systems that leverage protein-nano interactions to overcome current limitations of deep plasma proteomics in large cohorts. Here the importance of the protein to NP-surface ratio (P/NP) is demonstrated and protein corona formation dynamics are modeled, which determine the competition between proteins for binding. Tuning the P/NP ratio significantly modulates the protein corona composition, enhancing depth and precision of a fully automated NP-based deep proteomic workflow (Proteograph). By increasing the binding competition on engineered NPs, 1.2-1.7× more proteins with 1% false discovery rate are identified on the surface of each NP, and up to 3× more proteins compared to a standard plasma proteomics workflow. Moreover, the data suggest P/NP plays a significant role in determining the in vivo fate of nanomaterials in biomedical applications. Together, the study showcases the importance of P/NP as a key design element for biomaterials and nanomedicine in vivo and as a powerful tuning strategy for accurate, large-scale NP-based deep proteomic studies.

Constant exposure of the airways to inhaled pathogens requires efficient early immune responses protecting against infections. How bacteria on the epithelial surface are detected and first-line protective mechanisms are initiated are not well understood. We have recently shown that tracheal brush cells (BCs) express functional taste receptors. Here we report that bitter taste signaling in murine BCs induces neurogenic inflammation. We demonstrate that BC signaling stimulates adjacent sensory nerve endings in the trachea to release the neuropeptides CGRP and substance P that mediate plasma extravasation, neutrophil recruitment, and diapedesis. Moreover, we show that bitter tasting quorum-sensing molecules from Pseudomonas aeruginosa activate tracheal BCs. BC signaling depends on the key taste transduction gene Trpm5, triggers secretion of immune mediators, among them the most abundant member of the complement system, and is needed to combat P. aeruginosa infections. Our data provide functional insight into first-line defense mechanisms against bacterial infections of the lung.

The SARS-CoV-2 infection cycle is a multistage process that relies on functional interactions between the host and the pathogen. Here, we repurposed antiviral drugs against both viral and host enzymes to pharmaceutically block methylation of the viral RNA 2'-O-ribose cap needed for viral immune escape. We find that the host cap 2'-O-ribose methyltransferase MTr1 can compensate for loss of viral NSP16 methyltransferase in facilitating virus replication. Concomitant inhibition of MTr1 and NSP16 efficiently suppresses SARS-CoV-2 replication. Using in silico target-based drug screening, we identify a bispecific MTr1/NSP16 inhibitor with anti-SARS-CoV-2 activity in vitro and in vivo but with unfavorable side effects. We further show antiviral activity of inhibitors that target independent stages of the host SAM cycle providing the methyltransferase co-substrate. In particular, the adenosylhomocysteinase (AHCY) inhibitor DZNep is antiviral in in vitro, in ex vivo, and in a mouse infection model and synergizes with existing COVID-19 treatments. Moreover, DZNep exhibits a strong immunomodulatory effect curbing infection-induced hyperinflammation and reduces lung fibrosis markers ex vivo. Thus, multispecific and metabolic MTase inhibitors constitute yet unexplored treatment options against COVID-19.

Alzheimer's disease (AD) and related dementias (ADRD) is a complex disease with multiple pathophysiological drivers that determine clinical symptomology and disease progression. These diseases develop insidiously over time, through many pathways and disease mechanisms and continue to have a huge societal impact for affected individuals and their families. While emerging blood-based biomarkers, such as plasma p-tau181 and p-tau217, accurately detect Alzheimer neuropthology and are associated with faster cognitive decline, the full extension of plasma proteomic changes in ADRD remains unknown. Earlier detection and better classification of the different subtypes may provide opportunities for earlier, more targeted interventions, and perhaps a higher likelihood of successful therapeutic development. In this study, we aim to leverage unbiased mass spectrometry proteomics to identify novel, blood-based biomarkers associated with cognitive decline. 1,786 plasma samples from 1,005 patients were collected over 12 years from partcipants in the Massachusetts Alzheimer's Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, and clinical dementia rating (CDR) scores taken concurrently. The Proteograph™ Product Suite (Seer, Inc.) and liquid-chromatography mass-spectrometry (LC-MS) analysis were used to process the plasma samples in this cohort and generate unbiased proteomics data. Data-independent acquisition (DIA) mass spectrometry results yielded 36,259 peptides and 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD and healthy controls. Machine learning classification models for AD diagnosis identified potential candidate biomarkers including MBP, BGLAP, and APoD. Cox regression models were created to determine the association of proteins with disease progression and suggest CLNS1A, CRISPLD2, and GOLPH3 as targets of further investigation as potential biomarkers. The Proteograph workflow provided deep, unbiased coverage of the plasma proteome at a speed that enabled a cohort study of almost 1,800 samples, which is the largest, deep, unbiased proteomics study of ADRD conducted to date.

Secretion of type I interferon (IFN) is the first cellular reaction to invading pathogens. Despite the protective function of these cytokines, an excessive response to their action can contribute to serious pathologies, such as autoimmune diseases. Transcripts of most cytokines contain adenylate‐uridylate (A/U)‐rich elements (AREs) that make them highly unstable. RNA‐binding proteins (RBPs) are mediators of the regulatory mechanisms that determine the fate of mRNAs containing AREs. Here, we applied an affinity proteomic approach and identified lethal, abnormal vision, drosophila‐like 1 (ELAVL1)/Hu antigen R (HuR) as the predominant RBP of the IFN‐β mRNA ARE. Reduced expression or chemical inhibition of HuR severely hampered the type I IFN response in various cell lines and fibroblast‐like synoviocytes isolated from joints of rheumatoid arthritis patients. These results define a role for HuR as a potent modulator of the type I IFN response. Taken together, HuR could be used as therapeutic target for diseases where type I IFN production is exaggerated.

To the editor: Myeloproliferative neoplasms (MPNs) comprise a heterogeneous group of hematologic disorders characterized by clonal overproduction of differentiated myeloid cells, propensity to thrombosis, hemorrhage, and increased risk of leukemia. Three MPN subtypes, polycythemia vera (PV),

Abstract MLL-fusions represent a large group of leukemia drivers, whose diversity originates from the vast molecular heterogeneity of C-terminal fusion partners of MLL. While studies of selected MLL-fusions have revealed critical molecular pathways, unifying mechanisms across all MLL-fusions remain poorly understood. We present the first comprehensive survey of protein–protein interactions of seven distantly related MLL-fusion proteins. Functional investigation of 128 conserved MLL-fusion-interactors identifies a specific role for the lysine methyltransferase SETD2 in MLL-leukemia. SETD2 loss causes growth arrest and differentiation of AML cells, and leads to increased DNA damage. In addition to its role in H3K36 tri-methylation, SETD2 is required to maintain high H3K79 di-methylation and MLL-AF9-binding to critical target genes, such as Hoxa9 . SETD2 loss synergizes with pharmacologic inhibition of the H3K79 methyltransferase DOT1L to induce DNA damage, growth arrest, differentiation, and apoptosis. These results uncover a dependency for SETD2 during MLL-leukemogenesis, revealing a novel actionable vulnerability in this disease.

The cell intrinsic antiviral response of multicellular organisms developed over millions of years and critically relies on the ability to sense and eliminate viral nucleic acids. Here we use an affinity proteomics approach in evolutionary distant species (human, mouse and fly) to identify proteins that are conserved in their ability to associate with diverse viral nucleic acids. This approach shows a core of orthologous proteins targeting viral genetic material and species-specific interactions. Functional characterization of the influence of 181 candidates on replication of 6 distinct viruses in human cells and flies identifies 128 nucleic acid binding proteins with an impact on virus growth. We identify the family of TAO kinases (TAOK1, -2 and -3) as dsRNA-interacting antiviral proteins and show their requirement for type-I interferon induction. Depletion of TAO kinases in mammals or flies leads to an impaired response to virus infection characterized by a reduced induction of interferon stimulated genes in mammals and impaired expression of srg1 and diedel in flies. Overall, our study shows a larger set of proteins able to mediate the interaction between viral genetic material and host factors than anticipated so far, attesting to the ancestral roots of innate immunity and to the lineage-specific pressures exerted by viruses.

We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein-protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems-level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14-protein core network critical to the viability of multiple EGFR-mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR-mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance.

Plasma membrane (PM) proteins contribute to the identity of a cell, mediate contact and communication, and account for more than two-thirds of known drug targets.1−8 In the past years, several protocols for the proteomic profiling of PM proteins have been described. Nevertheless, comparative analyses have mainly focused on different variations of one approach.9−11 We compared sulfo-NHS-SS-biotinylation, aminooxy-biotinylation, and surface coating with silica beads to isolate PM proteins for subsequent analysis by one-dimensional gel-free liquid chromatography mass spectrometry. Absolute and relative numbers of PM proteins and reproducibility parameters on a qualitative and quantitative level were assessed. Sulfo-NHS-SS-biotinylation outperformed aminooxy-biotinylation and surface coating using silica beads for most of the monitored criteria. We further simplified this procedure by a competitive biotin elution strategy achieving an average PM annotated protein fraction of 54% (347 proteins). Computational analysis using additional databases and prediction tools revealed that in total over 90% of the purified proteins were associated with the PM, mostly as interactors. The modified sulfo-NHS-SS-biotinylation protocol was validated by tracking changes in the plasma membrane proteome composition induced by genetic alteration and drug treatment. Glycosylphosphatidylinositol (GPI)-anchored proteins were depleted in PM purifications from cells deficient in the GPI transamidase component PIGS, and treatment of cells with tunicamycin significantly reduced the abundance of N-glycoproteins in surface purifications.

Ewing's sarcoma is a pediatric cancer of the bone that is characterized by the expression of the chimeric transcription factor EWS-FLI1 that confers a highly malignant phenotype and results from the chromosomal translocation t(11;22)(q24;q12). Poor overall survival and pronounced long-term side effects associated with traditional chemotherapy necessitate the development of novel, targeted, therapeutic strategies. We therefore conducted a focused viability screen with 200 small molecule kinase inhibitors in 2 different Ewing's sarcoma cell lines. This resulted in the identification of several potential molecular intervention points. Most notably, tozasertib (VX-680, MK-0457) displayed unique nanomolar efficacy, which extended to other cell lines, but was specific for Ewing's sarcoma. Furthermore, tozasertib showed strong synergies with the chemotherapeutic drugs etoposide and doxorubicin, the current standard agents for Ewing's sarcoma. To identify the relevant targets underlying the specific vulnerability toward tozasertib, we determined its cellular target profile by chemical proteomics. We identified 20 known and unknown serine/threonine and tyrosine protein kinase targets. Additional target deconvolution and functional validation by RNAi showed simultaneous inhibition of Aurora kinases A and B to be responsible for the observed tozasertib sensitivity, thereby revealing a new mechanism for targeting Ewing's sarcoma. We further corroborated our cellular observations with xenograft mouse models. In summary, the multilayered chemical biology approach presented here identified a specific vulnerability of Ewing's sarcoma to concomitant inhibition of Aurora kinases A and B by tozasertib and danusertib, which has the potential to become a new therapeutic option.

The cellular response to replication stress requires the DNA-damage-responsive kinase ATM and its cofactor ATMIN; however, the roles of this signaling pathway following replication stress are unclear. To identify the functions of ATM and ATMIN in response to replication stress, we utilized both transcriptomics and quantitative mass-spectrometry-based phosphoproteomics. We found that replication stress induced by aphidicolin triggered widespread changes in both gene expression and protein phosphorylation patterns. These changes gave rise to distinct early and late replication stress responses. Furthermore, our analysis revealed previously unknown targets of ATM and ATMIN downstream of replication stress. We demonstrate ATMIN-dependent phosphorylation of H2AX and of CRMP2, a protein previously implicated in Alzheimer’s disease but not in the DNA damage response. Overall, our dataset provides a comprehensive resource for discovering the cellular responses to replication stress and, potentially, associated pathologies.

Cellular response to environmental challenges requires immediate and precise regulation of transcriptional programs. During viral infections, this includes the expression of antiviral genes that are essential to combat the pathogen. Transcribed mRNAs are bound and escorted to the cytoplasm by the cap-binding complex (CBC). We recently identified a protein complex consisting of NCBP1 and NCBP3 that, under physiological conditions, has redundant function to the canonical CBC, consisting of NCBP1 and NCBP2. Here, we provide evidence that NCBP3 is essential to mount a precise and appropriate antiviral response. Ncbp3-deficient cells allow higher virus growth and elicit a reduced antiviral response, a defect happening on post-transcriptional level. Ncbp3-deficient mice suffered from severe lung pathology and increased morbidity after influenza A virus challenge. While NCBP3 appeared to be particularly important during viral infections, it may be more broadly involved to ensure proper protein expression.

Hepatitis C virus (HCV) is a considerable global health and economic burden. The HCV nonstructural protein (NS) 5A is essential for the viral life cycle. The ability of NS5A to interact with different host and viral proteins allow it to manipulate cellular pathways and regulate viral processes, including RNA replication and virus particle assembly. As part of a proteomic screen, we identified several NS5A-binding proteins, including the lysine methyltransferase SET and MYND domain containing protein 3 (SMYD3). We confirmed the interaction in the context of viral replication by co-immunoprecipitation and co-localization studies. Mutational analyses revealed that the MYND-domain of SMYD3 and domain III of NS5A are required for the interaction. Overexpression of SMYD3 resulted in decreased intracellular and extracellular virus titers, whilst viral RNA replication remained unchanged, suggesting that SMYD3 negatively affects HCV particle production in a NS5A-dependent manner.

Affinity purification (AP) coupled to mass spectrometry (MS) has been successful in elucidating protein molecular networks of mammalian cells. These approaches have dramatically increased the knowledge of the interconnectivity present among proteins and highlighted biological functions within different protein complexes. Despite significant technical improvements reached in the past years, it is still challenging to identify the interaction networks and the subsequent associated functions of nuclear proteins such as transcription factors (TFs). A straightforward and robust methodology is therefore required to obtain unbiased and reproducible interaction data. Here we present a new approach for TF AP-MS, exemplified with the CCAAT/enhancer binding protein alpha (C/EBPalpha). Utilizing the advantages of a double tag and three different MS strategies, we conducted a total of six independent AP-MS strategies to analyze the protein-protein interactions of C/EBPalpha. The resultant data were combined to produce a cohesive C/EBPalpha interactome. Our study describes a new methodology that robustly identifies specific molecular complexes associated with transcription factors. Moreover, it emphasizes the existence of TFs as protein complexes essential for cellular biological functions and not as single, static entities.

RNA-dependent RNA polymerases (RdRps) play a key role in the life cycle of RNA viruses and impact their immunobiology. The arenavirus lymphocytic choriomeningitis virus (LCMV) strain Clone 13 provides a benchmark model for studying chronic infection. A major genetic determinant for its ability to persist maps to a single amino acid exchange in the viral L protein, which exhibits RdRp activity, yet its functional consequences remain elusive. To unravel the L protein interactions with the host proteome, we engineered infectious L protein-tagged LCMV virions by reverse genetics. A subsequent mass-spectrometric analysis of L protein pulldowns from infected human cells revealed a comprehensive network of interacting host proteins. The obtained LCMV L protein interactome was bioinformatically integrated with known host protein interactors of RdRps from other RNA viruses, emphasizing interconnected modules of human proteins. Functional characterization of selected interactors highlighted proviral (DDX3X) as well as antiviral (NKRF, TRIM21) host factors. To corroborate these findings, we infected Trim21-/- mice with LCMV and found impaired virus control in chronic infection. These results provide insights into the complex interactions of the arenavirus LCMV and other viral RdRps with the host proteome and contribute to a better molecular understanding of how chronic viruses interact with their host.

The wide dynamic range of circulating proteins coupled with the diversity of proteoforms present in plasma has historically impeded comprehensive and quantitative characterization of the plasma proteome at scale. Automated nanoparticle (NP) protein corona-based proteomics workflows can efficiently compress the dynamic range of protein abundances into a mass spectrometry (MS)-accessible detection range. This enhances the depth and scalability of quantitative MS-based methods, which can elucidate the molecular mechanisms of biological processes, discover new protein biomarkers, and improve comprehensiveness of MS-based diagnostics.Investigating multi-species spike-in experiments and a cohort, we investigated fold-change accuracy, linearity, precision, and statistical power for the using the Proteograph™ Product Suite, a deep plasma proteomics workflow, in conjunction with multiple MS instruments.We show that NP-based workflows enable accurate identification (false discovery rate of 1%) of more than 6,000 proteins from plasma (Orbitrap Astral) and, compared to a gold standard neat plasma workflow that is limited to the detection of hundreds of plasma proteins, facilitate quantification of more proteins with accurate fold-changes, high linearity, and precision. Furthermore, we demonstrate high statistical power for the discovery of biomarkers in small- and large-scale cohorts.The automated NP workflow enables high-throughput, deep, and quantitative plasma proteomics investigation with sufficient power to discover new biomarker signatures with a peptide level resolution.

Abstract Zika virus (ZIKV) has emerged as a global health issue, yet neither antiviral therapy nor a vaccine are available. ZIKV is an enveloped RNA virus, replicating in the cytoplasm in close association with ER membranes. Here, we isolate ER membranes from ZIKV-infected cells and determine their proteome. Forty-six host cell factors are enriched in ZIKV remodeled membranes, several of these having a role in redox and methylation pathways. Four proteins are characterized in detail: thioredoxin reductase 1 (TXNRD1) contributing to folding of disulfide bond containing proteins and modulating ZIKV secretion; aldo-keto reductase family 1 member C3 (AKR1C3), regulating capsid protein abundance and thus, ZIKV assembly; biliverdin reductase B (BLVRB) involved in ZIKV induced lipid peroxidation and increasing stability of viral transmembrane proteins; adenosylhomocysteinase (AHCY) indirectly promoting m 6 A methylation of ZIKV RNA by decreasing the level of S- adenosyl homocysteine and thus, immune evasion. These results highlight the involvement of redox and methylation enzymes in the ZIKV life cycle and their accumulation at virally remodeled ER membranes.

Global campaign against COVID-19 have vaccinated a significant portion of the world population in recent years. Combating the COVID-19 pandemic with mRNA vaccines played a pivotal role in the global immunization effort. However, individual responses to a vaccine are diverse and lead to varying vaccination efficacy. Despite significant progress, a complete understanding of the molecular mechanisms driving the individual immune response to the COVID-19 vaccine remains elusive. To address this gap, we combined a novel nanoparticle-based proteomic workflow with tandem mass tag (TMT) labeling, to quantitatively assess the proteomic changes in a cohort of 12 volunteers following two doses of the Pfizer-BioNTech mRNA COVID-19 vaccine. This optimized protocol seamlessly integrates comprehensive proteome analysis with enhanced throughput by leveraging the enrichment of low-abundant plasma proteins by engineered nanoparticles. Our data demonstrate the ability of this nanoparticle-based workflow to quantify over 3,000 proteins from 48 human plasma samples, providing the deepest view into COVID-19 vaccine-related plasma proteome study. We identified 69 proteins exhibiting a boosted response to the vaccine after the second dose. Additionally, 74 proteins were differentially regulated between seven volunteers, who contracted COVID-19 despite receiving two doses of the vaccine, and the ones who did not contract COVID-19. These findings offer valuable insights into individual variability in response to vaccination, demonstrating the potential of personalized medicine approaches in vaccine development.

While targeted therapy based on the idea of attenuating the activity of a preselected, therapeutically relevant protein has become one of the major trends in modern cancer therapy, no truly specific targeted drug has been developed and most clinical agents have displayed a degree of polypharmacology. Therefore, the specificity of anticancer therapeutics has emerged as a highly important but severely underestimated issue. Chemical proteomics is a powerful technique combining postgenomic drug-affinity chromatography with high-end mass spectrometry analysis and bioinformatic data processing to assemble a target profile of a desired therapeutic molecule. Due to high demands on the starting material, however, chemical proteomic studies have been mostly limited to cancer cell lines. Herein, we report a down-scaling of the technique to enable the analysis of very low abundance samples, as those obtained from needle biopsies. By a systematic investigation of several important parameters in pull-downs with the multikinase inhibitor bosutinib, the standard experimental protocol was optimized to 100 μg protein input. At this level, more than 30 well-known targets were detected per single pull-down replicate with high reproducibility. Moreover, as presented by the comprehensive target profile obtained from miniaturized pull-downs with another clinical drug, dasatinib, the optimized protocol seems to be extendable to other drugs of interest. Sixty distinct human and murine targets were finally identified for bosutinib and dasatinib in chemical proteomic experiments utilizing core needle biopsy samples from xenotransplants derived from patient tumor tissue. Altogether, the developed methodology proves robust and generic and holds many promises for the field of personalized health care.

Sequence logos have been widely used as graphical representations of conserved nucleic acid and protein motifs. Due to the complexity of the amino acid (AA) alphabet, rich post-translational modification, and diverse subcellular localization of proteins, few versatile tools are available for effective identification and visualization of protein motifs. In addition, various reduced AA alphabets based on physicochemical, structural, or functional properties have been valuable in the study of protein alignment, folding, structure prediction, and evolution. However, there is lack of tools for applying reduced AA alphabets to the identification and visualization of statistically significant motifs. To fill this gap, we developed an R/Bioconductor package dagLogo, which has several advantages over existing tools. First, dagLogo allows various formats for input sets and provides comprehensive options to build optimal background models. It implements different reduced AA alphabets to group AAs of similar properties. Furthermore, dagLogo provides statistical and visual solutions for differential AA (or AA group) usage analysis of both large and small data sets. Case studies showed that dagLogo can better identify and visualize conserved protein sequence patterns from different types of inputs and can potentially reveal the biological patterns that could be missed by other logo generators.

Current proteomic techniques allow researchers to analyze chosen biological pathways or an ensemble of related protein complexes at a global level via the measure of physical protein–protein interactions by affinity purification mass spectrometry (AP-MS). Such experiments yield information-rich but complex interaction maps whose unbiased interpretation is challenging. Guided by current knowledge on the modular structure of protein complexes, we propose a novel statistical approach, named BI-MAP, complemented by software tools and a visual grammar to present the inferred modules. We show that the BI-MAP tools can be applied from small and very detailed maps to large, sparse, and much noisier data sets. The BI-MAP tool implementation and test data are made freely available.

Proteomics In article number 2206008, Omid C. Farokhzad, Daniel Hornburg, and co-workers show how the Vroman effect can be leveraged to capture the complexity of human proteomes using engineered nanoparticles. Protein corona formation dynamics demonstrate how nanoparticle functionalization and nano–bio binding competition enable deep and quantitative interrogation of biosamples. This facilitates increased capture of low-abundance proteins, including cytokines and chemokines, enabling new strategies for biomarker discovery and personalized nanomedicine.

The pathogenesis of myeloproliferative neoplasms (MPN) is determined by the acquisition of somatic mutations in several genes, such as JAK2 , MPL , and TET2 . Familial clustering of MPN is observed in 5-10% of cases following predominantly autosomal dominant inheritance with incomplete penetrance. Familial MPN patients carry somatically acquired mutations in JAK2 , MPL and other genes similar to sporadic cases. It is thought that the germline mutations in familial cases of MPN predispose to acquisition of somatic mutations which in turn drive the disease. No gene has been implicated in familial MPN predisposition so far. The JAK2 haplotype predisposing to MPN at population level does not explain familial MPN cases. We studied a family with five MPN cases in four generations displaying an autosomal dominant pattern of inheritance with reduced penetrance. DNA was available from three MPN cases in the family. One of the patients carried a JAK2-V617F mutation and a deletion on chromosome 22q, while an MPL-W515L mutation was detected in another affected member of the family. The third patient did not have JAK2 or MPL mutations, but carried three chromosomal aberrations on chromosomes 2p, 7q and 15q. Chromosomal aberrations were detected using Affymetrix SNP 6.0 microarrays. The genotypic data from SNP 6.0 arrays was used to perform high-resolution nonparametric linkage analysis. In order to identify the germline mutation predisposing to MPN in the family we performed whole exome sequencing of the three affected members using Illumina next-generation sequencing technology. The mutations identified from exome sequencing were combined with the linkage analysis data. We identified a germline mutation in the RBBP6 gene that segregates with the MPN phenotype in the studied pedigree. Further screening in familial and sporadic MPN cases identified several other germline RBBP6 mutations in 5% of the familial and 0.6% of the sporadic MPN cases. Familial MPN cases mostly had the diagnosis of primary myelofibrosis. All the detected mutations cluster in putative p53-binding region of the protein, suggesting a possible link of the mutations and p53 function. The functional effect of the mutations was assessed in a doxycycline-inducible HEK-flp-in cell line system. Upon doxycyline induction, the wild-type and mutant RBBP6 constructs were over-expressed and the consequent functional effect of mutation was assessed using RNA sequencing and global proteomic analyses. The combination of the two datasets yielded 109 genes/proteins that were significantly changed in both the RNA sequencing and the global proteomic results when comparing wild-type to mutant RBBP6 , 87 of which were downregulated by the mutation, while 22 were upregulated. Several important cell cycle and apoptosis regulators were found among the deregulated genes, including TP53 , BAX , BID and USP7 (downregulated) and CDK6 (upregulated). KEGG pathway analysis of the downregulated genes showed significant enrichment for the p53 and the apoptosis pathways. We have identified germline mutations in RBBP6 that predispose to the development of MPN and are enriched in the families. Functional studies have shown that the mutations likely affect the p53 pathway and apoptosis and thus increase the risk of acquiring somatic mutations that lead to MPN. Our study implicates RBBP6 in MPN susceptibility and suggests that RBBP6 is an important cancer-associated gene. Disclosures: No relevant conflicts of interest to declare.

<div>Abstract<p>Ewing's sarcoma is a pediatric cancer of the bone that is characterized by the expression of the chimeric transcription factor EWS-FLI1 that confers a highly malignant phenotype and results from the chromosomal translocation t(11;22)(q24;q12). Poor overall survival and pronounced long-term side effects associated with traditional chemotherapy necessitate the development of novel, targeted, therapeutic strategies. We therefore conducted a focused viability screen with 200 small molecule kinase inhibitors in 2 different Ewing's sarcoma cell lines. This resulted in the identification of several potential molecular intervention points. Most notably, tozasertib (VX-680, MK-0457) displayed unique nanomolar efficacy, which extended to other cell lines, but was specific for Ewing's sarcoma. Furthermore, tozasertib showed strong synergies with the chemotherapeutic drugs etoposide and doxorubicin, the current standard agents for Ewing's sarcoma. To identify the relevant targets underlying the specific vulnerability toward tozasertib, we determined its cellular target profile by chemical proteomics. We identified 20 known and unknown serine/threonine and tyrosine protein kinase targets. Additional target deconvolution and functional validation by RNAi showed simultaneous inhibition of Aurora kinases A and B to be responsible for the observed tozasertib sensitivity, thereby revealing a new mechanism for targeting Ewing's sarcoma. We further corroborated our cellular observations with xenograft mouse models. In summary, the multilayered chemical biology approach presented here identified a specific vulnerability of Ewing's sarcoma to concomitant inhibition of Aurora kinases A and B by tozasertib and danusertib, which has the potential to become a new therapeutic option. <i>Mol Cancer Ther; 10(10); 1846–56. ©2011 AACR</i>.</p></div>

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ABSTRACT Cap0-mRNA is characterized by a 5’-5’triphosphate-linked N7-methylated guanosine(m7G). In higher eukaryotes, the methyltransferase CMTR1 additionally methylates the 2’O-position of the penultimate mRNA nucleotide(N1) ribose (cap1-mRNA). While the m7G cap is essential for mRNA export and translation initiation by the eIF4F complex, the N1-2’O-methylation prevents recognition of cap1-mRNA by the antiviral RNA receptors RIG-I and IFIT1, but a function beyond immunotolerance remained elusive. Here, we generated CMTR1 -knockout( CMTR1 -/- ) cells and found that type-I-interferon(IFN-I) treatment resulted in IFIT1-mediated reduction of cell viability and broad mRNA translation. Consequently, stimulation of the antiviral receptor RIG-I in CMTR1 -/- cells revealed an IFIT1 dependent dramatic reduction of IFN-I and chemokine protein induction, demonstrating the importance of N1-2’O-methylation for antiviral responses. Additionally, IFN-I- and IFIT1-independent effects were observed: CMTR1 -/- cells were smaller, divided slower, and exhibited a reduced transcription of mRNAs coding ribosomal proteins (RP), 5’TOP-RNA and snoRNA host genes(SNHG). Additionally, proteome and transcriptome analysis revealed that expression of NVL2, an essential factor in ribosome biogenesis, is strongly suppressed by an alternative-splicing event of NVL2 mRNA in CMTR1 -/- cells. This reduction could only be rescued by catalytically active CMTR1. Altogether, besides antiviral immunity N1-2’O-methylation by CMTR1 has broad effects on cellular physiology and controls splicing of NVL2.

<div>Abstract<p>Ewing's sarcoma is a pediatric cancer of the bone that is characterized by the expression of the chimeric transcription factor EWS-FLI1 that confers a highly malignant phenotype and results from the chromosomal translocation t(11;22)(q24;q12). Poor overall survival and pronounced long-term side effects associated with traditional chemotherapy necessitate the development of novel, targeted, therapeutic strategies. We therefore conducted a focused viability screen with 200 small molecule kinase inhibitors in 2 different Ewing's sarcoma cell lines. This resulted in the identification of several potential molecular intervention points. Most notably, tozasertib (VX-680, MK-0457) displayed unique nanomolar efficacy, which extended to other cell lines, but was specific for Ewing's sarcoma. Furthermore, tozasertib showed strong synergies with the chemotherapeutic drugs etoposide and doxorubicin, the current standard agents for Ewing's sarcoma. To identify the relevant targets underlying the specific vulnerability toward tozasertib, we determined its cellular target profile by chemical proteomics. We identified 20 known and unknown serine/threonine and tyrosine protein kinase targets. Additional target deconvolution and functional validation by RNAi showed simultaneous inhibition of Aurora kinases A and B to be responsible for the observed tozasertib sensitivity, thereby revealing a new mechanism for targeting Ewing's sarcoma. We further corroborated our cellular observations with xenograft mouse models. In summary, the multilayered chemical biology approach presented here identified a specific vulnerability of Ewing's sarcoma to concomitant inhibition of Aurora kinases A and B by tozasertib and danusertib, which has the potential to become a new therapeutic option. <i>Mol Cancer Ther; 10(10); 1846–56. ©2011 AACR</i>.</p></div>

Gel-free liquid chromatography mass spectrometry coupled to chemical proteomics is a powerful approach for characterizing cellular target profiles of small molecules. We have previously described a fast and efficient elution protocol; however, altered target profiles were observed. We hypothesised that elution conditions critically impact the effectiveness of disrupting drug-protein interactions. Thus, a number of elution conditions were systematically assessed with the aim of improving the recovery of all classes of proteins whilst maintaining compatibility with immunoblotting procedures. A double elution with formic acid combined with urea emerged as the most efficient and generically applicable elution method for chemical proteomics

Nat. Chem. Biol. 11, 571–578 (2015); published online 13 July 2015; corrected online 20 August 2015 In the author list, affiliation and correspondence information for Cheryl Arrowsmith was missing. Her name should be accompanied by affiliation number 3 (signifying the Structural Genomics Consortium,University of Toronto, Toronto, Ontario, Canada) and by an asterisk indicating her status as a corresponding author.

Abstract Sequence logos have been widely used as graphical representations of conserved nucleic acid and protein motifs. Due to the complexity of the amino acid (AA) alphabet, rich post-translational modification, and diverse subcellular localization of proteins, few versatile tools are available for effective identification and visualization of protein motifs. In addition, various reduced AA alphabets based on physicochemical, structural, or functional properties have been valuable in the study of protein alignment, folding, structure prediction, and evolution. However, there is lack of tools for applying reduced AA alphabets to the identification and visualization of statistically significant motifs. To fill this gap, we developed an R/Bioconductor package dagLogo, which has several advantages over existing tools. First, dagLogo allows various formats for input sets and provides comprehensive options to build optimal background models. It implements different reduced AA alphabets to group AAs of similar properties. Furthermore, dagLogo provides statistical and visual solutions for differential AA (or AA group) usage analysis of both large and small data sets. Case studies showed that dagLogo can better identify and visualize conserved protein sequence patterns from different types of inputs and can potentially reveal the biological patterns that could be missed by other logo generators.

The Mixed Lineage Leukemia gene (MLL) is a frequent target of chromosomal rearrangements in human malignancies. Balanced translocations result in the fusion of the MLL gene to over 65 partner genes. Even though critical effectors of distinct MLL fusion proteins have been identified, it is not clear if these effectors are conserved among all MLL fusion proteins or if different molecular mechanisms of transformation exist. We aim to delineate common critical effectors of MLL fusion proteins that are presumed to employ different mechanisms of oncogenic transformation. Stable cell lines allowing for inducible expression of 7 selected, affinity-tagged MLL fusion proteins were prepared and the expression of transgenes was verified by qRT-PCR and Western Blotting. Affinity purification coupled to mass spectrometry (AP-MS) identified known and novel interaction partners of 7 MLL fusions. Advanced statistical filtering using a novel algorithm developed by us yielded a densely connected protein-protein interaction network of >950 proteins. 128 proteins were found to interact with ≥5 of the 7 MLL-fusions. This list of conserved MLL-interactors is enriched for proteins with functions in chromatin metabolism and transcriptional control. To functionally dissect the conserved MLL-interactome, we employed a pooled RNAi screening approach. MLL-AF9-positive AML cells were transduced with pools of viral vectors allowing for the expression of 6 shRNA targeting the same candidate gene. Through a screening methodology that allows for simultaneous positive and negative selection readouts, we identified novel interactors of MLL fusion proteins that were selected for further validation experiments. In conclusion, we developed an experimental pipeline for the functional characterization of cellular effects of MLL fusion proteins in a comprehensive manner, allowing further insight into the molecular mechanisms of MLL-fusion dependent leukemogenesis.

In this issue of Cell Host & Microbe, Tripathi et al., 2015Tripathi S. Pohl M.O. Zhou Y. Rodriguez-Frandsen A. Wang G. Stein D.A. Moulton H.M. DeJesus P. Che J. Mulder L.C.F. et al.Cell Host Microbe. 2015; 18 (this issue): 723-735Abstract Full Text Full Text PDF PubMed Scopus (628) Google Scholar report an in-depth meta-analysis of eight influenza virus siRNA screens combined with viral-host protein interactome data. The integration of the different omics datasets highlights candidate genes and pathways for further investigation and potential therapeutic targeting in the future. In this issue of Cell Host & Microbe, Tripathi et al., 2015Tripathi S. Pohl M.O. Zhou Y. Rodriguez-Frandsen A. Wang G. Stein D.A. Moulton H.M. DeJesus P. Che J. Mulder L.C.F. et al.Cell Host Microbe. 2015; 18 (this issue): 723-735Abstract Full Text Full Text PDF PubMed Scopus (628) Google Scholar report an in-depth meta-analysis of eight influenza virus siRNA screens combined with viral-host protein interactome data. The integration of the different omics datasets highlights candidate genes and pathways for further investigation and potential therapeutic targeting in the future. Viruses have an inherent ability to mutate and thereby escape direct targeting by antiviral drugs. At the same time they heavily rely on multiple cellular pathways to facilitate viral replication and spread. Besides pathways that are directly targeted by viruses, many host factors either promote or inhibit infection indirectly. A main perspective for future therapeutic intervention is to identify cellular pathways and proteins that can serve as targets for broadly active antiviral drugs. Targeting host proteins required for virus replication is an elegant way to circumvent the viruses’ ability to generate drug-escape mutants (Manns and von Hahn, 2013Manns M.P. von Hahn T. Nat. Rev. Drug Discov. 2013; 12: 595-610Crossref PubMed Scopus (169) Google Scholar). Our general understanding of cellular proteins and pathways involved in viral disease progression is steadily increasing, particularly due to recent technological developments that allow unbiased genome-wide assessment of the viral-host interface. In this regard, genome-wide siRNA knockdown studies have emerged as a powerful tool for unbiased assessment of the impact of host genes on virus growth. A main issue of such studies, however, is the apparent marginal overlap of the genes identified in individual screens (Bushman et al., 2009Bushman F.D. Malani N. Fernandes J. D’Orso I. Cagney G. Diamond T.L. Zhou H. Hazuda D.J. Espeseth A.S. König R. et al.PLoS Pathog. 2009; 5: e1000437Crossref PubMed Scopus (371) Google Scholar). This raises skepticism regarding their real benefit, particularly since raw data for some studies are not publically available, thereby complicating comparisons and interpretations between different studies. However, differences between siRNA screens are not surprising, given broad variations in experimental design (e.g., studying early versus late events during virus infection), variations in treatments and cell lines, different transfection efficiencies, as well as individualized data analysis and interpretation. Clearly, every single siRNA screen contains individual characteristics and thus only covers a portion of the overall variability landscape, which is a known problem in systems biology. Meta-analysis is a statistical technique to consolidate multiple datasets, systematically assess this variability, and reveal common signatures (Evangelou and Ioannidis, 2013Evangelou E. Ioannidis J.P. Nat. Rev. Genet. 2013; 14: 379-389Crossref PubMed Scopus (386) Google Scholar, Liberali et al., 2015Liberali P. Snijder B. Pelkmans L. Nat. Rev. Genet. 2015; 16: 18-32Crossref PubMed Scopus (62) Google Scholar). Such analysis can be applied to different data types (e.g., microarrays, disease-associated gene polymorphisms, etc.) and to questions ranging from bee behavior to key factors of diabetes susceptibility (Mahajan et al., 2014Mahajan A. Go M.J. Zhang W. Below J.E. Gaulton K.J. Ferreira T. Horikoshi M. Johnson A.D. Ng M.C. Prokopenko I. et al.DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) ConsortiumAsian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) ConsortiumSouth Asian Type 2 Diabetes (SAT2D) ConsortiumMexican American Type 2 Diabetes (MAT2D) ConsortiumType 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) ConsortiumNat. Genet. 2014; 46: 234-244Crossref PubMed Scopus (760) Google Scholar). In this issue of Cell Host & Microbe, Tripathi et al., 2015Tripathi S. Pohl M.O. Zhou Y. Rodriguez-Frandsen A. Wang G. Stein D.A. Moulton H.M. DeJesus P. Che J. Mulder L.C.F. et al.Cell Host Microbe. 2015; 18 (this issue): 723-735Abstract Full Text Full Text PDF PubMed Scopus (628) Google Scholar analyzed the data from eight large-scale siRNA knockdown studies that tested the impact of cellular genes on influenza A virus (IAV) replication and combined these data with 3 human-IAV protein interaction datasets (Figure 1). This work represents the first reported meta-analysis of genome-wide siRNA knockdown screens for influenza A virus. Importantly, the authors did not simply merge the hits of individual siRNA screens but re-analyzed raw data. This allowed them to re-score each candidate gene based on its signature in multiple screens, thereby improving both sensitivity and confidence of hit detection and allowing for identification of new genes that had lower, yet reproducible, scores in individual screens. The results are available online at http://www.metascape.org/IAV. The authors also demonstrated that considering the proper hierarchical level of the cellular machinery improves consolidation of datasets. To disrupt a pathway or protein complex, one can target its different components. Due to individual biases, each screen may reveal an individual subset of such components as hits. However, when affected pathways or complexes are considered, all screens reveal more homogenous patterns. In sum, after re-evaluating scores for all genes identified in the eight screens, the authors observed that almost 50% of hits could be identified in more than one screen or showed shared pathway contribution. This by itself is a remarkable result, clearly demonstrating the power of meta-analysis to identify shared signatures between large-scale datasets. Also, this analysis should mitigate skepticism against apparently diverse results obtained in individual large-scale siRNA screens. Integrating orthogonal datasets helps to dissect the functional role of candidate genes. Tripathi et al., 2015Tripathi S. Pohl M.O. Zhou Y. Rodriguez-Frandsen A. Wang G. Stein D.A. Moulton H.M. DeJesus P. Che J. Mulder L.C.F. et al.Cell Host Microbe. 2015; 18 (this issue): 723-735Abstract Full Text Full Text PDF PubMed Scopus (628) Google Scholar combine the siRNA data with virus-host protein interactomes obtained through yeast two-hybrid screens and affinity purification of expressed viral proteins followed by mass spectrometry. The overlap between the host interactors of viral proteins and the siRNA hits highlighted some candidates and provided them with topological information. For instance, this approach allowed the authors to identify the ubiquitin protein ligase E3 component n-recognin 4 (UBR4) both as a cellular protein required for influenza A virus growth and as interaction partner of the viral M2 protein. UBR4, a 570 kDA protein, is known for its involvement in the N-end rule proteolytic system, where it mediates proteasomal and autophagosomal degradation of target proteins (Tasaki et al., 2012Tasaki T. Sriram S.M. Park K.S. Kwon Y.T. Annu. Rev. Biochem. 2012; 81: 261-289Crossref PubMed Scopus (272) Google Scholar). Moreover, UBR4 has been shown to be a critical host factor for efficient Dengue virus replication (Morrison et al., 2013Morrison J. Laurent-Rolle M. Maestre A.M. Rajsbaum R. Pisanelli G. Simon V. Mulder L.C. Fernandez-Sesma A. García-Sastre A. PLoS Pathog. 2013; 9: e1003265Crossref PubMed Scopus (157) Google Scholar). Depletion of UBR4 led to reduced IAV growth, presumably due to mis-localization and subsequent degradation of viral proteins. The mechanistic basis for this effect on virus growth is not yet clear. However, a virus-specific component appears to be involved since avian influenza viruses seem less dependent on UBR4 than human isolates. IAV-infected Ubr4-depleted mice show mitigated virus growth and pathology scores, clearly indicating its role in viral propagation. However, it is unlikely that UBR4 itself will be a suitable candidate for antiviral therapy since genetic depletion of Ubr4 in mice is detrimental and transient depletion of Ubr4 in vivo appears to have some side effects (Tripathi et al., 2015Tripathi S. Pohl M.O. Zhou Y. Rodriguez-Frandsen A. Wang G. Stein D.A. Moulton H.M. DeJesus P. Che J. Mulder L.C.F. et al.Cell Host Microbe. 2015; 18 (this issue): 723-735Abstract Full Text Full Text PDF PubMed Scopus (628) Google Scholar). Nevertheless, this discovery clearly exemplifies the power of meta-analysis to identify host candidates for therapeutic targeting. The meta-analysis done by Tripathi et al., 2015Tripathi S. Pohl M.O. Zhou Y. Rodriguez-Frandsen A. Wang G. Stein D.A. Moulton H.M. DeJesus P. Che J. Mulder L.C.F. et al.Cell Host Microbe. 2015; 18 (this issue): 723-735Abstract Full Text Full Text PDF PubMed Scopus (628) Google Scholar is very encouraging and constitutes a valuable resource for research on influenza viruses. This approach can now be further extended with additional datasets, which will help to dissect the role of individual host factors. Of particular interest are datasets studying the dynamics of viral infection such as changes of the cellular metabolome, proteome expression, protein-protein interactions, as well as chemical interference screens (Figure 1). The increased complexity of meta-analysis will require more rigorous assessment of false positive hits, e.g., by randomly permuting input data to derive the background distribution of the meta-analysis scores. Besides focusing on influenza virus, integrating data from siRNA screens of other viruses should be particularly rewarding since this could highlight a core set of genes that are generally important to promote or restrict growth of diverse viruses (Amberkar and Kaderali, 2015Amberkar S.S. Kaderali L. Algorithms Mol. Biol. 2015; 10: 6Crossref PubMed Scopus (6) Google Scholar). Indeed, a number of hits that were identified and validated by Tripathi et al., 2015Tripathi S. Pohl M.O. Zhou Y. Rodriguez-Frandsen A. Wang G. Stein D.A. Moulton H.M. DeJesus P. Che J. Mulder L.C.F. et al.Cell Host Microbe. 2015; 18 (this issue): 723-735Abstract Full Text Full Text PDF PubMed Scopus (628) Google Scholar have previously been shown to be important for other viruses as well (e.g., UBR4, IFITMs, COP9 signalosome, etc.). This supports the notion that diverse viruses evolved in parallel to utilize or target conserved cellular networks (Pichlmair et al., 2012Pichlmair A. Kandasamy K. Alvisi G. Mulhern O. Sacco R. Habjan M. Binder M. Stefanovic A. Eberle C.A. Goncalves A. et al.Nature. 2012; 487: 486-490Crossref PubMed Scopus (189) Google Scholar). Modulating the activity of such candidate genes and pathways could be particularly fruitful to generate pan-viral therapies in the future. The work in the authors’ laboratory is funded by the Max-Planck Free Floater program, an ERC starting grant (311339; iVIP), InfectERA (ERASE), and the German research foundation (P1084/2). Meta- and Orthogonal Integration of Influenza “OMICs” Data Defines a Role for UBR4 in Virus BuddingTripathi et al.Cell Host & MicrobeDecember 09, 2015In BriefTripathi et al. have reconciled and integrated divergent influenza “OMICs” studies to reveal a functionally validated virus-host interaction network of high-confidence human proteins essential for influenza A virus replication. The authors leverage this approach to identify UBR4 as a host protein essential for virus budding and pathogenesis. Full-Text PDF Open Archive

The Mixed Lineage Leukemia gene (MLL) is a frequent target of chromosomal rearrangements in human malignancies. MLL-rearrangements are primarily associated with pediatric leukemias with poor prognosis. Balanced translocations result in the fusion of the MLL gene to over 60 fusion partner genes, leading to the production of novel chimeric proteins. Even though critical effectors of distinct MLL fusion proteins have been identified, it is not clear if these effectors are conserved among all MLL fusion proteins or if different molecular mechanisms of transformation exist. We aimed to delineate critical common effectors of 7 selected MLL fusion proteins that are presumed to differ in their oncogenic mechanisms. Stable cell lines allowing for inducible expression of 7 selected, affinity-tagged MLL fusion proteins were prepared and expression of transgenes was verified by qRT-PCR and Western Blotting. Affinity purification coupled to mass spectrometry (AP-MS) identified novel interactors of 7 MLL fusions protein complexes. Advanced statistical filtering using a novel, improved algorithm we developed yielded a densely connected interaction network of 900 proteins, including many known MLL-interactors. 128 proteins were found to interact with 5 of the 7 MLL-fusions. This list of conserved MLL-interactors is highly enriched for proteins with a function in chromatin metabolism and transcriptional control. To assign functional information to the candidate genes we employ a NGS-based multiplexed RNAi screening approach. We have established a novel screening methodology that is suitable for positive and negative selection readouts. This dual read-out will cross-validate itself, thereby highly increasing the significance of true hits. In conclusion, we developed a robust experimental pipeline allowing for the functional characterization of cellular effects of MLL fusion proteins in a comprehensive and comparative manner, which will contribute further insights into the molecular mechanisms of MLL-fusion dependent leukemogenesis. The Mixed Lineage Leukemia gene (MLL) is a frequent target of chromosomal rearrangements in human malignancies. MLL-rearrangements are primarily associated with pediatric leukemias with poor prognosis. Balanced translocations result in the fusion of the MLL gene to over 60 fusion partner genes, leading to the production of novel chimeric proteins. Even though critical effectors of distinct MLL fusion proteins have been identified, it is not clear if these effectors are conserved among all MLL fusion proteins or if different molecular mechanisms of transformation exist. We aimed to delineate critical common effectors of 7 selected MLL fusion proteins that are presumed to differ in their oncogenic mechanisms. Stable cell lines allowing for inducible expression of 7 selected, affinity-tagged MLL fusion proteins were prepared and expression of transgenes was verified by qRT-PCR and Western Blotting. Affinity purification coupled to mass spectrometry (AP-MS) identified novel interactors of 7 MLL fusions protein complexes. Advanced statistical filtering using a novel, improved algorithm we developed yielded a densely connected interaction network of 900 proteins, including many known MLL-interactors. 128 proteins were found to interact with 5 of the 7 MLL-fusions. This list of conserved MLL-interactors is highly enriched for proteins with a function in chromatin metabolism and transcriptional control. To assign functional information to the candidate genes we employ a NGS-based multiplexed RNAi screening approach. We have established a novel screening methodology that is suitable for positive and negative selection readouts. This dual read-out will cross-validate itself, thereby highly increasing the significance of true hits. In conclusion, we developed a robust experimental pipeline allowing for the functional characterization of cellular effects of MLL fusion proteins in a comprehensive and comparative manner, which will contribute further insights into the molecular mechanisms of MLL-fusion dependent leukemogenesis.

Abstract Lung cancer is a devastating worldwide disease yet enthusiasm exists for treatment of subsets of the disease with molecularly targeted agents. Mutations in the epidermal growth factor receptor (EGFR) or translocation of echinoderm microtubule associated protein like 4 – anaplastic lymphoma kinase (EML4-ALK) define two unique subsets of lung cancer characterized by sensitivity to tyrosine kinase inhibitors (TKI). Despite striking results with TKI, not all patients respond, the drugs are non-curative, and resistance is universal. Mutations in KRAS also define a group of patients awaiting therapeutic opportunities. We are characterizing signaling networks using tandem affinity purification (TAP) and liquid chromatography-mass spectrometry (LC-MS/MS) to map protein-protein interactions (PPI) and anti-phosphotyrosine immunoprecipitation coupled with LC-MS/MS to map tyrosine phosphorylation. In PC9 cells with mutated EGFR, we characterized a physical EGFR network consisting of 266 proteins by integrating both TAP and pTyr MS data. In H3122 cells harboring EML4-ALK, we identified a PPI network consisting of 113 proteins and using pTyr MS identified changes in tyrosine phosphorylation in 120 proteins (58 decreased, 62 increased) following exposure to ALK tyrosine kinase inhibitor. Functional proteins are being discovered from these networks using siRNA and inhibitor screens. In parallel studies, we have exploited the use of chemical proteomics to discern targets of promiscuous kinase inhibitors and enable optimal combination approaches. In this way, we view network mapping linked to chemical proteomics as one approach to discern novel drug combination studies for in vivo validation and ultimately translation to early phase clinical trials. To translate PPI based mass spectrometry studies to clinic, we are developing in situ assays that identify and quantify PPI using proximal ligation assays (PLA). Pilot studies identify EGFR:Grb2 interactions in formalin fixed human lung cancers. These approaches have the potential to enable ‘network medicine’ by identifying novel combination approaches as well as through identifying subtypes of cancers through network views of cancer.

In a pandemic, such as the one caused by the coronavirus in 2020, fast action is required to provide insights into the disease mechanisms and to find potential drug targets to slow the progress of the disease and lower mortality.We developed CoVex, an interactive online platform for the exploration of the SARS-CoV-2 host interactome and the identification of drug candidates.CoVex integrates the virus-human protein interactions, human protein-protein interactions, and drug-target interactions, and allows for visual exploration of the data.The exploration is guided by network-based systems medicine algorithms that enable the assembly of ranked lists of candidates for already approved drugs.Unlike novel drugs, approved drugs have the advantage that most of their side effects and contraindications are known.Additionally, they are already available and can be distributed quickly, which makes them promising candidates to stop the uncontrolled spread of the disease early.CoVex is an example of how this could be achieved in future pandemics and provides valuable lessons on what is required in such a situation to maximize the potential of computational approaches that can significantly speed up drug discovery.