Mass spectrometry-based in vitro kinase screens play an essential role in the discovery of kinase substrates, however, many suffer from biological and technical noise or necessitate genetically-altered enzyme-cofactor systems. We describe a method that combines stable γ-[(18)O2]-ATP with classical in vitro kinase assays within a contemporary quantitative proteomic workflow. Our approach improved detection of known substrates of the non-receptor tyrosine kinase ABL1; and identified potential, new in vitro substrates.

Genomically amplified fibroblast growth factor receptor 1 (FGFR1) is an oncogenic driver in defined lung cancer subgroups and predicts sensibility against FGFR1 inhibitors in this patient cohort. The FGFR inhibitor nintedanib has recently been approved for treatment of lung adenocarcinoma and is currently evaluated for small cell lung cancer (SCLC). However, tumor recurrence due to development of nintedanib resistance might occur. Hence, we aimed at characterizing the molecular mechanisms underlying acquired nintedanib resistance in FGFR1-driven lung cancer. Chronic nintedanib exposure of the FGFR1-driven SCLC cell line DMS114 (DMS114/NIN) but not of two NSCLC cell lines induced massive overexpression of the multidrug-resistance transporter ABCB1. Indeed, we proved nintedanib to be both substrate and modulator of ABCB1-mediated efflux. Importantly, the oncogenic FGFR1 signaling axis remained active in DMS114/NIN cells while bioinformatic analyses suggested hyperactivation of the endothelin-A receptor (ETAR) signaling axis. Indeed, ETAR inhibition resensitized DMS114/NIN cells against nintedanib by downregulation of ABCB1 expression. PKC and downstream NFκB were identified as major downstream players in ETAR-mediated ABCB1 hyperactivation. Summarizing, ABCB1 needs to be considered as a factor underlying nintedanib resistance. Combination approaches with ETAR antagonists or switching to non-ABCB1 substrate FGFR inhibitors represent innovative strategies to manage nintedanib resistance in lung cancer.

The marsupial Tasmanian devil (Sarcophilus harrisii) faces extinction due to transmissible devil facial tumor disease (DFTD). To unveil the molecular underpinnings of this transmissible cancer, we combined pharmacological screens with an integrated systems-biology characterization. Sensitivity to inhibitors of ERBB tyrosine kinases correlated with their overexpression. Proteomic and DNA methylation analyses revealed tumor-specific signatures linked to the evolutionary conserved oncogenic STAT3. ERBB inhibition blocked phosphorylation of STAT3 and arrested cancer cells. Pharmacological blockade of ERBB or STAT3 prevented tumor growth in xenograft models and restored MHC class I expression. This link between the hyperactive ERBB-STAT3 axis and major histocompatibility complex class I-mediated tumor immunosurveillance provides mechanistic insights into horizontal transmissibility and puts forward a dual chemo-immunotherapeutic strategy to save Tasmanian devils from DFTD. VIDEO ABSTRACT.

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.

Signaling from lysosomes controls cellular clearance and energy metabolism. Lysosomal malfunction has been implicated in several pathologies, including neurodegeneration, cancer, infection, immunodeficiency, and obesity. Interestingly, many functions are dependent on the organelle position. Lysosomal motility requires the integration of extracellular and intracellular signals that converge on a competition between motor proteins that ultimately control lysosomal movement on microtubules. Here, we identify a novel upstream control mechanism of Arl8b-dependent lysosomal movement toward the periphery of the cell. We show that the C-terminal domain of lyspersin, a subunit of BLOC-1-related complex (BORC), is essential and sufficient for BORC-dependent recruitment of Arl8b to lysosomes. In addition, we establish lyspersin as the linker between BORC and late endosomal/lysosomal adaptor and mitogen activated protein kinase and mechanistic target of rapamycin activator (LAMTOR) complexes and show that epidermal growth factor stimulation decreases LAMTOR/BORC association, thereby promoting BORC- and Arl8b-dependent lysosomal centrifugal transport.

N-terminal histone tails are subject to many posttranslational modifications that are recognized by and interact with designated reader domains in histone-binding proteins. BROMO domain adjacent to zinc finger 2B (BAZ2B) is a multidomain histone-binding protein that contains two histone reader modules, a plant homeodomain (PHD) and a bromodomain (BRD), linked by a largely disordered linker. Although previous studies have reported specificity of the PHD domain for the unmodified N terminus of histone H3 and of the BRD domain for H3 acetylated at Lys14 (H3K14ac), the exact mode of H3 binding by BAZ2B and its regulation are underexplored. Here, using isothermal titration calorimetry and NMR spectroscopy, we report that acidic residues in the BAZ2B PHD domain are essential for H3 binding and that BAZ2B PHD-BRD establishes a polyvalent interaction with H3K14ac. Furthermore, we provide evidence that the disordered interdomain linker modulates the histone-binding affinity by interacting with the PHD domain. In particular, lysine-rich stretches in the linker, which resemble the positively charged N terminus of histone H3, reduce the binding affinity of the PHD finger toward the histone substrate. Phosphorylation, acetylation, or poly(ADP-ribosyl)ation of the linker residues may therefore act as a cellular mechanism to transiently tune BAZ2B histone-binding affinity. Our findings further support the concept of interdomain linkers serving a dual role in substrate binding by appropriately positioning the adjacent domains and by electrostatically modulating substrate binding. Moreover, inhibition of histone binding by a histone-mimicking interdomain linker represents another example of regulation of protein-protein interactions by intramolecular mimicry.

Affinity purification coupled with mass spectrometry (AP-MS) is a widely used approach for the identification of protein-protein interactions. However, for any given protein of interest, determining which of the identified polypeptides represent bona fide interactors versus those that are background contaminants (for example, proteins that interact with the solid-phase support, affinity reagent or epitope tag) is a challenging task. The standard approach is to identify nonspecific interactions using one or more negative-control purifications, but many small-scale AP-MS studies do not capture a complete, accurate background protein set when available controls are limited. Fortunately, negative controls are largely bait independent. Hence, aggregating negative controls from multiple AP-MS studies can increase coverage and improve the characterization of background associated with a given experimental protocol. Here we present the contaminant repository for affinity purification (the CRAPome) and describe its use for scoring protein-protein interactions. The repository (currently available for Homo sapiens and Saccharomyces cerevisiae) and computational tools are freely accessible at http://www.crapome.org/.

During replicative aging of primary cells morphological transformations occur, the expression pattern is altered and chromatin changes globally. Here we show that chronic damage signals, probably caused by telomere processing, affect expression of histones and lead to their depletion. We investigated the abundance and cell cycle expression of histones and histone chaperones and found defects in histone biosynthesis during replicative aging. Simultaneously, epigenetic marks were redistributed across the phases of the cell cycle and the DNA damage response (DDR) machinery was activated. The age-dependent reprogramming affected telomeric chromatin itself, which was progressively destabilized, leading to a boost of the telomere-associated DDR with each successive cell cycle. We propose a mechanism in which changes in the structural and epigenetic integrity of telomeres affect core histones and their chaperones, enforcing a self-perpetuating pathway of global epigenetic changes that ultimately leads to senescence.

We describe a strategy for comprehending signaling pathways that are active in lung cancer cells and that are targeted by dasatinib using chemical proteomics to identify direct interacting proteins combined with immunoaffinity purification of tyrosine-phosphorylated peptides corresponding to activated tyrosine kinases. We identified nearly 40 different kinase targets of dasatinib. These include SRC-family kinase (SFK) members (LYN, SRC, FYN, LCK and YES), nonreceptor tyrosine kinases (FRK, BRK and ACK) and receptor tyrosine kinases (Ephrin receptors, DDR1 and EGFR). Using quantitative phosphoproteomics, we identified peptides corresponding to autophosphorylation sites of these tyrosine kinases that are inhibited in a concentration-dependent manner by dasatinib. Using drug-resistant gatekeeper mutants, we show that SFKs (particularly SRC and FYN), as well as EGFR, are relevant targets for dasatinib action. The combined mass spectrometry-based approach described here provides a system-level view of dasatinib action in cancer cells and suggests both functional targets and a rationale for combinatorial therapeutic strategies.

Identification of pathways involved in the structural transitions of biomolecular systems is often complicated by the transient nature of the conformations visited across energy barriers and the multiplicity of paths accessible in the multidimensional energy landscape. This task becomes even more challenging in exploring molecular systems on the order of megadaltons. Coarse-grained models that lend themselves to analytical solutions appear to be the only possible means of approaching such cases. Motivated by the utility of elastic network models for describing the collective dynamics of biomolecular systems and by the growing theoretical and experimental evidence in support of the intrinsic accessibility of functional substates, we introduce a new method, adaptive anisotropic network model (aANM), for exploring functional transitions. Application to bacterial chaperonin GroEL and comparisons with experimental data, results from action minimization algorithm, and previous simulations support the utility of aANM as a computationally efficient, yet physically plausible, tool for unraveling potential transition pathways sampled by large complexes/assemblies. An important outcome is the assessment of the critical inter-residue interactions formed/broken near the transition state(s), most of which involve conserved residues.

DNA lesions caused by UV damage are thought to be repaired solely by the nucleotide excision repair (NER) pathway in human cells. Patients carrying mutations within genes functioning in this pathway display a range of pathologies, including an increased susceptibility to cancer, premature aging, and neurological defects. There are currently no curative therapies available. Here we performed a high-throughput chemical screen for agents that could alleviate the cellular sensitivity of NER-deficient cells to UV-induced DNA damage. This led to the identification of the clinically approved anti-diabetic drug acetohexamide, which promoted clearance of UV-induced DNA damage without the accumulation of chromosomal aberrations, hence promoting cellular survival. Acetohexamide exerted this protective function by antagonizing expression of the DNA glycosylase, MUTYH. Together, our data reveal the existence of an NER-independent mechanism to remove UV-induced DNA damage and prevent cell death.

Specific granule deficiency (SGD) is a rare disorder characterized by abnormal neutrophils evidenced by reduced granules, absence of granule proteins, and atypical bilobed nuclei. Mutations in CCAAT/enhancer-binding protein-ε (CEBPE) are one molecular etiology of the disease. Although C/EBPε has been studied extensively, the impact of CEBPE mutations on neutrophil biology remains elusive. Here, we identified two SGD patients bearing a previously described heterozygous mutation (p.Val218Ala) in CEBPE. We took this rare opportunity to characterize SGD neutrophils in terms of granule distribution and protein content. Granules of patient neutrophils were clustered and polarized, suggesting that not only absence of specific granules but also defects affecting other granules contribute to the phenotype. Our analysis showed that remaining granules displayed mixed protein content and lacked several glycoepitopes. To further elucidate the impact of mutant CEBPE, we performed detailed proteomic analysis of SGD neutrophils. Beside an absence of several granule proteins in patient cells, we observed increased expression of members of the linker of nucleoskeleton and cytoskeleton complex (nesprin-2, vimentin, and lamin-B2), which control nuclear shape. This suggests that absence of these proteins in healthy individuals might be responsible for segmented shapes of neutrophilic nuclei. We further show that the heterozygous mutation p.Val218Ala in CEBPE causes SGD through prevention of nuclear localization of the protein product. In conclusion, we uncover that absence of nuclear C/EBPε impacts on spatiotemporal expression and subsequent distribution of several granule proteins and further on expression of proteins controlling nuclear shape.

Small-molecule drugs may complement antibody-based therapies in an immune-oncology setting, yet systematic methods for the identification and characterization of the immunomodulatory properties of these entities are lacking. We surveyed the immumomodulatory potential of 1,402 small chemical molecules, as defined by their ability to alter the cell-cell interactions among peripheral mononuclear leukocytes ex vivo, using automated microscopy and population-wide single-cell image analysis. Unexpectedly, ∼10% of the agents tested affected these cell-cell interactions differentially. The results accurately recapitulated known immunomodulatory drug classes and revealed several clinically approved drugs that unexpectedly harbor the ability to modulate the immune system, which could potentially contribute to their physiological mechanism of action. For instance, the kinase inhibitor crizotinib promoted T cell interactions with monocytes, as well as with cancer cells, through inhibition of the receptor tyrosine kinase MSTR1 and subsequent upregulation of the expression of major histocompatibility complex molecules. The approach offers an attractive platform for the personalized identification and characterization of immunomodulatory therapeutics.

Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool to dissect cell-specific effects of drug treatment in complex tissues. This application requires high levels of precision, robustness, and quantitative accuracy-beyond those achievable with existing methods for mainly qualitative single-cell analysis. Here, we establish the use of standardized reference cells as spike-in controls for accurate and robust dissection of single-cell drug responses.

Recurrent gain-of-function mutations in the transcription factors STAT5A and much more in STAT5B were found in hematopoietic malignancies with the highest proportion in mature T- and natural killer-cell neoplasms (peripheral T-cell lymphoma, PTCL). No targeted therapy exists for these heterogeneous and often aggressive diseases. Given the shortage of models for PTCL, we mimicked graded STAT5A or STAT5B activity by expressing hyperactive Stat5a or STAT5B variants at low or high levels in the hematopoietic system of transgenic mice. Only mice with high activity levels developed a lethal disease resembling human PTCL. Neoplasia displayed massive expansion of CD8+ T cells and destructive organ infiltration. T cells were cytokine-hypersensitive with activated memory CD8+ T-lymphocyte characteristics. Histopathology and mRNA expression profiles revealed close correlation with distinct subtypes of PTCL. Pronounced STAT5 expression and activity in samples from patients with different subsets underline the relevance of JAK/STAT as a therapeutic target. JAK inhibitors or a selective STAT5 SH2 domain inhibitor induced cell death and ruxolitinib blocked T-cell neoplasia in vivo We conclude that enhanced STAT5A or STAT5B action both drive PTCL development, defining both STAT5 molecules as targets for therapeutic intervention.

Cyclin-dependent kinases (CDKs) are frequently deregulated in cancer and represent promising drug targets. We provide evidence that CDK8 has a key role in B-ALL. Loss of CDK8 in leukemia mouse models significantly enhances disease latency and prevents disease maintenance. Loss of CDK8 is associated with pronounced transcriptional changes, whereas inhibiting CDK8 kinase activity has minimal effects. Gene set enrichment analysis suggests that the mTOR signaling pathway is deregulated in CDK8-deficient cells and, accordingly, these cells are highly sensitive to mTOR inhibitors. Analysis of large cohorts of human ALL and AML patients reveals a significant correlation between the level of CDK8 and of mTOR pathway members. We have synthesized a small molecule YKL-06-101 that combines mTOR inhibition and degradation of CDK8, and induces cell death in human leukemic cells. We propose that simultaneous CDK8 degradation and mTOR inhibition might represent a potential therapeutic strategy for the treatment of ALL patients.

Cancer-associated, loss-of-function mutations in genes encoding subunits of the BRG1/BRM-associated factor (BAF) chromatin-remodeling complexes1-8 often cause drastic chromatin accessibility changes, especially in important regulatory regions9-19. However, it remains unknown how these changes are established over time (for example, immediate consequences or long-term adaptations), and whether they are causative for intracomplex synthetic lethalities, abrogating the formation or activity of BAF complexes9,20-24. In the present study, we use the dTAG system to induce acute degradation of BAF subunits and show that chromatin alterations are established faster than the duration of one cell cycle. Using a pharmacological inhibitor and a chemical degrader of the BAF complex ATPase subunits25,26, we show that maintaining genome accessibility requires constant ATP-dependent remodeling. Completely abolishing BAF complex function by acute degradation of a synthetic lethal subunit in a paralog-deficient background results in an almost complete loss of chromatin accessibility at BAF-controlled sites, especially also at superenhancers, providing a mechanism for intracomplex synthetic lethalities.

In acute myeloid leukemia (AML), recurrent DNA methyltransferase 3A (DNMT3A) mutations are associated with chemoresistance and poor prognosis, especially in advanced-age patients. Gene-expression studies in DNMT3A-mutated cells identified signatures implicated in deregulated DNA damage response and replication fork integrity, suggesting sensitivity to replication stress. Here, we tested whether pharmacologically induced replication fork stalling, such as with cytarabine, creates a therapeutic vulnerability in cells with DNMT3A(R882) mutations.

The loss of forkhead box protein O1 (FoxO1) signaling in response to metabolic stress contributes to the etiology of type II diabetes, causing the dedifferentiation of pancreatic beta cells to a cell type reminiscent of endocrine progenitors. Lack of methods to easily model this process in vitro, however, have hindered progress into the identification of key downstream targets and potential inhibitors. We therefore aimed to establish such an in vitro cellular dedifferentiation model and apply it to identify novel agents involved in the maintenance of beta-cell identity.

Antimicrobial resistance prediction from whole genome sequencing data (WGS) is an emerging application of machine learning, promising to improve antimicrobial resistance surveillance and outbreak monitoring. Despite significant reductions in sequencing cost, the availability and sampling diversity of WGS data with matched antimicrobial susceptibility testing (AST) profiles required for training of WGS-AST prediction models remains limited. Best practice machine learning techniques are required to ensure trained models generalize to independent data for optimal predictive performance. Limited data restricts the choice of machine learning training and evaluation methods and can result in overestimation of model performance. We demonstrate that the widely used random k-fold cross-validation method is ill-suited for application to small bacterial genomics datasets and offer an alternative cross-validation method based on genomic distance. We benchmarked three machine learning architectures previously applied to the WGS-AST problem on a set of 8,704 genome assemblies from five clinically relevant pathogens across 77 species-compound combinations collated from public databases. We show that individual models can be effectively ensembled to improve model performance. By combining models via stacked generalization with cross-validation, a model ensembling technique suitable for small datasets, we improved average sensitivity and specificity of individual models by 1.77% and 3.20%, respectively. Furthermore, stacked models exhibited improved robustness and were thus less prone to outlier performance drops than individual component models. In this study, we highlight best practice techniques for antimicrobial resistance prediction from WGS data and introduce the combination of genome distance aware cross-validation and stacked generalization for robust and accurate WGS-AST.