Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis

Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. Leveraging progress in proteomic technologies and network-based methodologies, we introduce Virtual Enrichment-based Signaling Protein-activity Analysis (VESPA)-an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations-and use it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogating tumor-specific enzyme/substrate interactions accurately infers kinase and phosphatase activity, based on their substrate phosphorylation state, effectively accounting for signal crosstalk and sparse phosphoproteome coverage. The analysis elucidates time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring, experimentally confirmed by CRISPR knock-out assays, suggesting broad applicability to cancer and other diseases.

Elucidating Compound Mechanism of Action and Polypharmacology with a Large-scale Perturbational Profile Compendium

The Mechanism of Action (MoA) of a drug is generally represented as a small, non-tissue-specific repertoire of high-affinity binding targets. Yet, drug activity and polypharmacology are increasingly associated with a broad range of off-target and tissue-specific effector proteins. To address this challenge, we have implemented an efficient integrative experimental and computational framework leveraging the systematic generation and analysis of drug perturbational profiles representing >700 FDA-approved and experimental oncology drugs, in cell lines selected as high-fidelity models of 23 aggressive tumor subtypes. Protein activity-based analyses revealed highly reproducible, drug-mediated modulation of tissue-specific targets, leading to generation of a proteome-wide polypharmacology map, characterization of MoA-related drug clusters and off-target effects, and identification and experimental validation of novel, tissue-specific inhibitors of undruggable oncoproteins. The proposed framework, which is easily extended to elucidating the MoA of novel small-molecule libraries, could help support more systematic and quantitative approaches to precision oncology.

Network-based elucidation of colon cancer drug resistance by phosphoproteomic time-series analysis

Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. By leveraging progress in proteomic technologies and network-based methodologies, over the past decade, we developed VESPA-an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations-and used it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogation of tumor-specific enzyme/substrate interactions accurately inferred kinase and phosphatase activity, based on their inferred substrate phosphorylation state, effectively accounting for signal cross-talk and sparse phosphoproteome coverage. The analysis elucidated time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring that was experimentally confirmed by CRISPRko assays, suggesting broad applicability to cancer and other diseases.

OncoLoop: A Network-Based Precision Cancer Medicine Framework

Prioritizing treatments for individual patients with cancer remains challenging, and performing coclinical studies using patient-derived models in real time is often unfeasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework that predicts drug sensitivity in human tumors and their preexisting high-fidelity (cognate) model(s) by leveraging drug perturbation profiles. As a proof of concept, we applied OncoLoop to prostate cancer using genetically engineered mouse models (GEMM) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of human prostate cancer cohorts by Master Regulator (MR) conservation analysis revealed that most patients with advanced prostate cancer were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated in allograft, syngeneic, and patient-derived xenograft (PDX) models of tumors and metastasis. Furthermore, OncoLoop-predicted drugs enhanced the efficacy of clinically relevant drugs, namely, the PD-1 inhibitor nivolumab and the AR inhibitor enzalutamide.

SIGNIFICANCE

OncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround coclinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available. This article is highlighted in the In This Issue feature, p. 247.

Validation of a High-Throughput Dicentric Chromosome Assay Using Complex Radiation Exposures

Validation of biodosimetry assays is routinely performed using primarily orthovoltage irradiators at a conventional dose rate of approximately 1 Gy/min. However, incidental/ accidental exposures caused by nuclear weapons can be more complex. The aim of this work was to simulate the DNA damage effects mimicking those caused by the detonation of a several kilotons improvised nuclear device (IND). For this, we modeled complex exposures to: 1. a mixed (photons + IND-neutrons) field and 2. different dose rates that may come from the blast, nuclear fallout, or ground deposition of radionuclides (ground shine). Additionally, we assessed whether myeloid cytokines affect the precision of radiation dose estimation by modulating the frequency of dicentric chromosomes. To mimic different exposure scenarios, several irradiation systems were used. In a mixed field study, human blood samples were exposed to a photon field enriched with neutrons (ranging from 10% to 37%) from a source that mimics Hiroshima's A-bomb's energy spectrum (0.2-9 MeV). Using statistical analysis, we assessed whether photons and neutrons act in an additive or synergistic way to form dicentrics. For the dose rates study, human blood was exposed to photons or electrons at dose rates ranging from low (where the dose was spread over 32 h) to extremely high (where the dose was delivered in a fraction of a microsecond). Potential effects of cytokine treatment on biodosimetry dose predictions were analyzed in irradiated blood subjected to Neupogen or Neulasta for 24 or 48 h at the concentration recommended to forestall manifestation of an acute radiation syndrome in bomb survivors. All measurements were performed using a robotic station, the Rapid Automated Biodosimetry Tool II, programmed to culture lymphocytes and score dicentrics in multiwell plates (the RABiT-II DCA). In agreement with classical concepts of radiation biology, the RABiT-II DCA calibration curves suggested that the frequency of dicentrics depends on the type of radiation and is modulated by changes in the dose rate. The resulting dose-response curves suggested an intermediate dicentric yields and additive effects of photons and IND-neutrons in the mixed field. At ultra-high dose rate (600 Gy/s), affected lymphocytes exhibited significantly fewer dicentrics (P < 0.004, t test). In contrast, we did not find the dose-response modification effects of radiomitigators on the yields of dicentrics (Bonferroni corrected P > 0.006, ANOVA test). This result suggests no bias in the dose predictions should be expected after emergency cytokine treatment initiated up to 48 h prior to blood collection for dicentric analysis.

A Model for Network-Based Identification and Pharmacological Targeting of Aberrant, Replication-Permissive Transcriptional Programs Induced by Viral Infection.. [PMID: 35132404 PMCID: PMC8820669 DOI: 10.21203/rs.3.rs-1287631/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Precise characterization and targeting of host cell transcriptional machinery hijacked by viral infection remains challenging. Here, we show that SARS-CoV-2 hijacks the host cell transcriptional machinery to induce a phenotypic state amenable to its replication. Specifically, analysis of Master Regulator (MR) proteins representing mechanistic determinants of the gene expression signature induced by SARS-CoV-2 in infected cells revealed coordinated inactivation of MRs enriched in physical interactions with SARS-CoV-2 proteins, suggesting their mechanistic role in maintaining a host cell state refractory to virus replication. To test their functional relevance, we measured SARS-CoV-2 replication in epithelial cells treated with drugs predicted to activate the entire repertoire of repressed MRs, based on their experimentally elucidated, context-specific mechanism of action. Overall, >80% of drugs predicted to be effective by this methodology induced significant reduction of SARS-CoV-2 replication, without affecting cell viability. This model for host-directed pharmacological therapy is fully generalizable and can be deployed to identify drugs targeting host cell-based MR signatures induced by virtually any pathogen.

The RABiT-II DCA in the Rhesus Macaque Model

An automated platform for cytogenetic biodosimetry, the "Rapid Automated Biodosimetry Tool II (RABiT-II)," adapts the dicentric chromosome assay (DCA) for high-throughput mass-screening of the population after a large-scale radiological event. To validate this test, the U.S. Federal Drug Administration (FDA) recommends demonstrating that the high-throughput biodosimetric assay in question correctly reports the dose in an in vivo model. Here we describe the use of rhesus macaques (Macaca mulatta) to augment human studies and validate the accuracy of the high-throughput version of the DCA. To perform analysis, we developed the 17/22-mer peptide nucleic acid (PNA) probes that bind to the rhesus macaque's centromeres. To our knowledge, these are the first custom PNA probes with high specificity that can be used for chromosome analysis in M. mulatta. The accuracy of fully-automated chromosome analysis was improved by optimizing a low-temperature telomere PNA FISH staining in multiwell plates and adding the telomere detection feature to our custom chromosome detection software, FluorQuantDic V4. The dicentric frequencies estimated from in vitro irradiated rhesus macaque samples were compared to human blood samples of individuals subjected to the same ex vivo irradiation conditions. The results of the RABiT-II DCA analysis suggest that, in the lymphocyte system, the dose responses to gamma radiation in the rhesus macaques were similar to those in humans, with small but statistically significant differences between these two model systems.

The Host Cell ViroCheckpoint: Identification and Pharmacologic Targeting of Novel Mechanistic Determinants of Coronavirus-Mediated Hijacked Cell States

Most antiviral agents are designed to target virus-specific proteins and mechanisms rather than the host cell proteins that are critically dysregulated following virus-mediated reprogramming of the host cell transcriptional state. To overcome these limitations, we propose that elucidation and pharmacologic targeting of host cell Master Regulator proteins-whose aberrant activities govern the reprogramed state of coronavirus-infected cells-presents unique opportunities to develop novel mechanism-based therapeutic approaches to antiviral therapy, either as monotherapy or as a complement to established treatments. Specifically, we propose that a small module of host cell Master Regulator proteins (ViroCheckpoint) is hijacked by the virus to support its efficient replication and release. Conventional methodologies are not well suited to elucidate these potentially targetable proteins. By using the VIPER network-based algorithm, we successfully interrogated 12h, 24h, and 48h signatures from Calu-3 lung adenocarcinoma cells infected with SARS-CoV, to elucidate the time-dependent reprogramming of host cells and associated Master Regulator proteins. We used the NYS CLIA-certified Darwin OncoTreat algorithm, with an existing database of RNASeq profiles following cell perturbation with 133 FDA-approved and 195 late-stage experimental compounds, to identify drugs capable of virtually abrogating the virus-induced Master Regulator signature. This approach to drug prioritization and repurposing can be trivially extended to other viral pathogens, including SARS-CoV-2, as soon as the relevant infection signature becomes available.

The use of a centrifuge-free RABiT-II system for high-throughput micronucleus analysis

The cytokinesis-block micronucleus (CBMN) assay is considered to be the most suitable biodosimetry method for automation. Previously, we automated this assay on a commercial robotic biotech high-throughput system (RABiT-II) adopting both a traditional and an accelerated micronucleus protocol, using centrifugation steps for both lymphocyte harvesting and washing, after whole blood culturing. Here we describe further development of our accelerated CBMN assay protocol for use on high-throughput/high content screening (HTS/HCS) robotic systems without a centrifuge. This opens the way for implementation of the CBMN assay on a wider range of commercial automated HTS/HCS systems and thus increases the potential capacity for dose estimates following a mass-casualty radiological event.

RABiT-II-DCA: A Fully-automated Dicentric Chromosome Assay in Multiwell Plates

We developed a fully-automated dicentric chromosome assay (DCA) in multiwell plates. All operations, from sample loading to chromosome scoring, are performed, without human intervention, by the second-generation Rapid Automated Biodosimetry Tool II (RABiT-II) robotic system, a plate imager and custom software, FluorQuantDic. The system requires small volumes of blood (30 µl per individual) to determine radiation dose received as a result of a radiation accident or terrorist attack. To visualize dicentrics in multiwell plates, we implemented a non-classical protocol for centromere FISH staining at 37°C. The RABiT-II performs rapid analysis of chromosomes after extracting them from metaphase cells. With the use of multiwell plates, many samples can be screened at the same time. Thus, the RABiT-II DCA provides an advantage during triage when risk-based stratification and medical management are required for a large population exposed to unknown levels of ionizing radiation.

Automated Triage Radiation Biodosimetry: Integrating Imaging Flow Cytometry with High-Throughput Robotics to Perform the Cytokinesis-Block Micronucleus Assay

The cytokinesis-block micronucleus (CBMN) assay has become a fully-validated and standardized method for radiation biodosimetry. The assay is typically performed using microscopy, which is labor intensive, time consuming and impractical after a large-scale radiological/nuclear event. Imaging flow cytometry (IFC), which combines the statistical power of traditional flow cytometry with the sensitivity and specificity of microscopy, has been recently used to perform the CBMN assay. Since this technology is capable of automated sample acquisition and multi-file analysis, we have integrated IFC into our Rapid Automated Biodosimetry Technology (RABiT-II). Assay development and optimization studies were designed to increase the yield of binucleated cells (BNCs), and improve data acquisition and analysis templates to increase the speed and accuracy of image analysis. Human peripheral blood samples were exposed ex vivo with up to 4 Gy of c rays at a dose rate of 0.73 Gy/min. After irradiation, samples were transferred to microtubes (total volume of 1 ml including blood and media) and organized into a standard 8 × 12 plate format. Sample processing methods were modified by increasing the blood-to-media ratio, adding hypotonic solution prior to cell fixation and optimizing nuclear DRAQ5 staining, leading to an increase of 81% in BNC yield. Modification of the imaging processing algorithms within IFC software also improved BNC and MN identification, and reduced the average time of image analysis by 78%. Finally, 50 ll of irradiated whole blood was cultured with 200 ll of media in 96-well plates. All sample processing steps were performed automatically using the RABiT-II cell: :explorer robotic system adopting the optimized IFC-CBMN assay protocol. The results presented here detail a novel, high-throughput RABiT-IFC CBMN assay that possesses the potential to increase capacity for triage biodosimetry during a large-scale radiological/nuclear event.

RABiT-II: A Fully-Automated Micronucleus Assay System with Shortened Time to Result

In this work, we describe a fully automated cytokinesis-block micronucleus (CBMN) assay with a significantly shortened time to result, motivated by the need for rapid high-throughput biodosimetric estimation of radiation doses from small-volume human blood samples. The Rapid Automated Biodosimetry Tool (RABiT-II) currently consists of two commercial automated systems: a PerkinElmer cell::explorer Workstation and a GE Healthcare IN Cell Analyzer 2000 Imager. Blood samples (30 μl) from eight healthy volunteers were gamma-ray irradiated ex vivo with 0 (control), 0.5, 1.5, 2.5, 3.5 or 4.5 Gy and processed with full automation in 96-well plates on the RABiT-II system. The total cell culture time was 54 h and total assay time was 3 days. DAPI-stained fixed samples were imaged on an IN Cell Analyzer 2000 with fully-automated image analysis using the GE Healthcare IN Cell Developer Toolbox version 1.9. A CBMN dose-response calibration curve was established, after which the capability of the system to predict known doses was assessed. Various radiation doses for irradiated samples from two donors were estimated within 20% of the true dose (±0.5 Gy below 2 Gy) in 97% of the samples, with the doses in some 5 Gy irradiated samples being underestimated by up to 25%. In summary, the findings from this work demonstrate that the accelerated CBMN assay can be automated in a high-throughput format, using commercial biotech robotic systems, in 96-well plates, providing a rapid and reliable bioassay for radiation exposure.

Guaiacol as a drug candidate for treating adult polyglucosan body disease

Adult polyglucosan body disease (APBD) is a late-onset disease caused by intracellular accumulation of polyglucosan bodies, formed due to glycogen-branching enzyme (GBE) deficiency. To find a treatment for APBD, we screened 1,700 FDA-approved compounds in fibroblasts derived from APBD-modeling GBE1-knockin mice. Capitalizing on fluorescent periodic acid-Schiff reagent, which interacts with polyglucosans in the cell, this screen discovered that the flavoring agent guaiacol can lower polyglucosans, a result also confirmed in APBD patient fibroblasts. Biochemical assays showed that guaiacol lowers basal and glucose 6-phosphate-stimulated glycogen synthase (GYS) activity. Guaiacol also increased inactivating GYS1 phosphorylation and phosphorylation of the master activator of catabolism, AMP-dependent protein kinase. Guaiacol treatment in the APBD mouse model rescued grip strength and shorter lifespan. These treatments had no adverse effects except making the mice slightly hyperglycemic, possibly due to the reduced liver glycogen levels. In addition, treatment corrected penile prolapse in aged GBE1-knockin mice. Guaiacol's curative effects can be explained by its reduction of polyglucosans in peripheral nerve, liver, and heart, despite a short half-life of up to 60 minutes in most tissues. Our results form the basis to use guaiacol as a treatment and prepare for the clinical trials in APBD.

Abstract 5103: Notch is a master regulator of mesenchymal transformation and therapeutic resistance in glioma

Introduction: Gliomas are highly infiltrative tumors rendering complete resection impossible. As such, prognosis remains dismal. Recent studies have identified both proneural and mesenchymal cell populations. Crucially, recurring gliomas bear a mesenchymal phenotype. Understanding mechanisms driving mesenchymal transformation is important in developing tailored, more efficient therapeutic approaches.

Methods: Using targeted biopsies from a mouse glioma model and human glioma databases, we applied bioinformatics and identified Notch as an additional master regulator (MR) protein driving mesenchymal transformation. To better understand the role of Notch, we overexpressed active forms of Notch1 (N1IC) or Notch3 (N3IC) in primary cells, orthotopic xenotransplants, and transgenic mouse models. We performed mouse survival studies and examined Notch-induced phenotypic alterations in tumor cells and the microenvironment using molecular and immunohistochemical approaches. Finally, we performed high-throughput drug and radiation screening studies to assess responses to treatment.

Results: In silico analyses on RNAseq of biopsies from spatially distinct tumor regions in a mouse glioma model identified Notch as a highly active pathway in the cores of tumors undergoing mesenchymal transformation. Importantly, MR analysis of TCGA samples and single cell transcriptomic data identified the Notch pathway as a driver of proneural to mesenchymal transformation. Immunophenotyping and RNAseq profiling of human GBMs identified Notch receptors on tumor cells and Notch ligands on astrocytes and microglia suggesting potential microenvironment-mediated plasticity since Notch proteins are not frequently mutated in GBM. Overexpression of N1IC or N3IC in proneural cells induced mesenchymal transformation with slow proliferation and a highly invasive phenotype. Orthotransplantation of N3IC-expressing cells in mice led to slower growing tumors, perivascular invasion, increased recruitment of reactive phagocytes and slightly prolonged survival. A novel transgenic mouse model in which N1IC was overexpressed also led to prolonged survival compared to a control population. Importantly, high-throughput screening studies showed that N1IC and N3IC rendered tumor cells significantly more resistant to standard and targeted therapies, including irradiation and etoposide.

Conclusions: Our study identifies Notch signaling as an important, likely microenvironment-driven pathway driving proneural to mesenchymal transformation in glioma. While Notch was shown to slow tumor growth and prolong survival, cells were more invasive and less sensitive to treatment. These findings suggest that Notch plays a role in the mesenchymal transformation and therapeutic resistance seen in post-treatment recurrence. Targeting Notch may therefore be important in improving therapeutic responses against glioma.

Citation Format: Matei A. Banu, Athanassios Dovas, Henar Cuervo, Brianna Pereira, Aayushi Mahajan, Hongxu Ding, Mukesh Bansal, Sergey Pampou, Charles Karan, Andrea Califano, Peter A. Sims, Jan Kitajewski, Jeffrey N. Bruce, Peter Canoll. Notch is a master regulator of mesenchymal transformation and therapeutic resistance in glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5103.

Identification of Fluorescent Small Molecule Compounds for Synaptic Labeling by Image-Based, High-Content Screening

Few tools are available for noninvasive imaging of synapses in the living mammalian brain. Current paradigms require the use of genetically modified mice or viral delivery of genetic material to the brain. To develop an alternative chemical approach, utilizing the recognition of synaptic components by organic small molecules, we designed an imaging-based, high-content screen in cultured cortical neurons to identify molecules based on their colocalization with fluorescently tagged synaptic proteins. We used this approach to screen a library of ∼7000 novel fluorescent dyes, and identified a series of compounds in the xanthone family that exhibited consistent synaptic labeling. Follow-up studies with one of these compounds, CX-G3, demonstrated its ability to label acidic organelles and in particular synaptic vesicles at glutamatergic synapses in cultured neurons and murine brain tissue, indicating the potential of this screening approach to identify promising lead compounds for use as synaptic markers, sensors, and targeting devices.

Systematic, network-based characterization of therapeutic target inhibitors

A large fraction of the proteins that are being identified as key tumor dependencies represent poor pharmacological targets or lack clinically-relevant small-molecule inhibitors. Availability of fully generalizable approaches for the systematic and efficient prioritization of tumor-context specific protein activity inhibitors would thus have significant translational value. Unfortunately, inhibitor effects on protein activity cannot be directly measured in systematic and proteome-wide fashion by conventional biochemical assays. We introduce OncoLead, a novel network based approach for the systematic prioritization of candidate inhibitors for arbitrary targets of therapeutic interest. In vitro and in vivo validation confirmed that OncoLead analysis can recapitulate known inhibitors as well as prioritize novel, context-specific inhibitors of difficult targets, such as MYC and STAT3. We used OncoLead to generate the first unbiased drug/regulator interaction map, representing compounds modulating the activity of cancer-relevant transcription factors, with potential in precision medicine.

RABiT-II: Implementation of a High-Throughput Micronucleus Biodosimetry Assay on Commercial Biotech Robotic Systems

We demonstrate the use of high-throughput biodosimetry platforms based on commercial high-throughput/high-content screening robotic systems. The cytokinesis-block micronucleus (CBMN) assay, using only 20 μl whole blood from a fingerstick, was implemented on a PerkinElmer cell::explorer and General Electric IN Cell Analyzer 2000. On average 500 binucleated cells per sample were detected by our FluorQuantMN software. A calibration curve was generated in the radiation dose range up to 5.0 Gy using the data from 8 donors and 48,083 binucleated cells in total. The study described here demonstrates that high-throughput radiation biodosimetry is practical using current commercial high-throughput/high-content screening robotic systems, which can be readily programmed to perform and analyze robotics-optimized cytogenetic assays. Application to other commercial high-throughput/high-content screening systems beyond the ones used in this study is clearly practical. This approach will allow much wider access to high-throughput biodosimetric screening for large-scale radiological incidents than is currently available.

Abstract A35: Predicting drugs effect on transcription factor activity by regulatory network analysis of drug perturbed cellular states

Phenotypic changes during pathophysiological processes can be efficiently captured by genome-wide gene expression signatures or molecular phenotypes. Transcription factors (TFs) are the key components of the transcriptional regulatory network that integrates intracellular and extracellular stimuli and generates a response in the form of specific gene expression signatures.

We have shown the existence and dissected the components of this integrative logic layer in several pathologic and physiologic processes.

Moreover, perturbation of key components of this machinery can be efficiently used to induce desired phenotypic changes. However, TFs have been rather elusive targets for pharmacological intervention.

Here, by using a cell-context specific network-based approach, we generated a comprehensive map between small compounds and TF activity. We leveraged the large collection of expression profiles in response to small molecule perturbagens from CMAP to first reverse-engineer transcriptionally regulatory networks in 3 different cellular context (Breast: MCF7, Prostate:PC3 and Myeloma:HL60) by the ARACNe algorithm, and then interrogate these networks with the MARINa algorithm to identify TFs whose activity is affected by the profiled compounds.

We show two different evidences that validate our method. First, we correctly identified ESR1 as the very top TF whose activity is affected by the estrogen antagonists tamoxifen, raloxifen and clomifene. Second, we selected 10 compounds from the 1,400 represented in the MCF7 CMAP dataset that our method predict as STAT3 perturbagens. From these, 4 showed a significant inhibition of STAT3 activity in a cell-based STAT3 reported assay.

Citation Format: Yao Shen, Mariano Alvarez, Sergey Pampou, Jorida Coku, Andrea Califano. Predicting drugs effect on transcription factor activity by regulatory network analysis of drug perturbed cellular states [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr A36.

Evidence for acquisition of Legionella type IV secretion substrates via interdomain horizontal gene transfer

Intracellular pathogens exploit host cell functions to create a replication niche inside eukaryotic cells. The causative agent of Legionnaires' disease, the gamma-proteobacterium Legionella pneumophila, resides and replicates within a modified vacuole of protozoan and mammalian cells. L. pneumophila translocates effector proteins into host cells through the Icm-Dot complex, a specialized type IVB secretion system that is required for intracellular growth. To find out if some effector proteins may have been acquired through interdomain horizontal gene transfer (HGT), we performed a bioinformatic screen that searched for eukaryotic motifs in all open reading frames of the L. pneumophila Philadelphia-1 genome. We found 44 uncharacterized genes with many distinct eukaryotic motifs. Most of these genes contain G+C biases compared to other L. pneumophila genes, supporting the theory that they were acquired through HGT. Furthermore, we found that several of them are expressed and up-regulated in stationary phase in an RpoS-dependent manner. In addition, at least seven of these gene products are translocated into host cells via the Icm-Dot complex, confirming their role in the intracellular environment. Reminiscent of the case with most Icm-Dot substrates, most of the strains containing mutations in these genes grew comparably to the parent strain intracellularly. Our findings suggest that in L. pneumophila, interdomain HGT may have been a major mechanism for the acquisition of determinants of infection.

The genomic sequence of the accidental pathogen Legionella pneumophila

We present the genomic sequence of Legionella pneumophila, the bacterial agent of Legionnaires' disease, a potentially fatal pneumonia acquired from aerosolized contaminated fresh water. The genome includes a 45-kilobase pair element that can exist in chromosomal and episomal forms, selective expansions of important gene families, genes for unexpected metabolic pathways, and previously unknown candidate virulence determinants. We highlight the genes that may account for Legionella's ability to survive in protozoa, mammalian macrophages, and inhospitable environmental niches and that may define new therapeutic targets.

Opposing effect of angiopoietin-1 on VEGF-mediated disruption of endothelial cell-cell interactions requires activation of PKC beta

Angiopoietin-1 (Ang1) and vascular endothelial growth factor (VEGF) cooperate in migration and survival of endothelial cells by activation of phosphatidylinositol-3 (PI-3) kinase and mitogen activating protein (MAP) kinase pathways. However, Ang1 opposes the effect of VEGF on vascular permeability. We found that Ang1 also blocks VEGF-mediated diffusion of fluoresin isothiocyanate (FITC)-labeled albumin across an endothelial cell monolayer. VEGF-mediated vascular permeability has been attributed, in part, to activation of phospholipase A(2) and subsequent formation of platelet activating factor. However, Ang1 had no effect on VEGF-induced activation of phospholipase A(2) or the release of arachidonic acid. VEGF-mediated permeability was associated with disruption of endothelial cell junctional complexes, dissociation of beta-catenin from VE-cadherin, and accumulation of beta-catenin in the cytosol. In contrast, Ang1 enhanced the interaction of beta-catenin with VE-cadherin and impaired VEGF-mediated dissociation of this complex. Ang1 also blocked VEGF-induced translocation of protein kinase C (PKC) and beta2 to the membrane, but had no effect on activation of PKC alpha. In addition, staurosporine and a PKC beta inhibitor, LY379196, blocked VEGF-mediated dissociation of beta-catenin from VE-cadherin, diffusion of albumin across the endothelial cell monolayer, and translocation of PKC beta isoforms. These data indicate that VEGF-mediated disruption of endothelial cell-cell interactions requires activation of PKC beta isoforms and that this pathway is blocked by Ang1.