Project description:Autosomal dominant polycystic kidney disease (ADPKD) is characterized by cyst formation throughout the kidney parenchyma. It is caused by mutations in either of two genes, PKD1 and PKD2. Mice that lack functional Pkd1 (Pkd1?/?), develop rapidly progressive cystic disease during embryogenesis, and serve as a model to study human ADPKD. Genome wide transcriptome reprogramming and the possible roles of micro-RNAs (miRNAs) that affect the initiation and progression of cyst formation in the Pkd1?/? have yet to be studied. miRNAs are small, regulatory non-coding RNAs, implicated in a wide spectrum of biological processes. Their expression levels are altered in several diseases including kidney cancer, diabetic nephropathy and PKD.We examined the molecular pathways that modulate renal cyst formation and growth in the Pkd1?/? model by performing global gene-expression profiling in embryonic kidneys at days 14.5 and 17.5. Gene Ontology and gene set enrichment analysis were used to identify overrepresented signaling pathways in Pkd1?/? kidneys. We found dysregulation of developmental, metabolic, and signaling pathways (e.g. Wnt, calcium, TGF-? and MAPK) in Pkd1?/? kidneys. Using a comparative transcriptomics approach, we determined similarities and differences with human ADPKD: ~50% overlap at the pathway level among the mis-regulated pathways was observed. By using computational approaches (TargetScan, miRanda, microT and miRDB), we then predicted miRNAs that were suggested to target the differentially expressed mRNAs. Differential expressions of 9 candidate miRNAs, miRs-10a, -30a-5p, -96, -126-5p, -182, -200a, -204, -429 and -488, and 16 genes were confirmed by qPCR. In addition, 14 candidate miRNA:mRNA reciprocal interactions were predicted. Several of the highly regulated genes and pathways were predicted as targets of miRNAs.We have described global transcriptional reprogramming during the progression of PKD in the Pkd1?/? model. We propose a model for the cascade of signaling events involved in cyst formation and growth. Our results suggest that several miRNAs may be involved in regulating signaling pathways in ADPKD. We further describe novel putative miRNA:mRNA signatures in ADPKD, which will provide additional insights into the pathogenesis of this common genetic disease in humans.
Project description:Identifying targets is critical for understanding the biological effects of microRNA (miRNA) expression. The challenge lies in characterizing the cohort of targets for a specific miRNA, especially when targets are being actively down-regulated in miRNA- RNA-induced silencing complex (RISC)-messengerRNA (mRNA) complexes. We have developed a robust and versatile strategy called RISCtrap to stabilize and purify targets from this transient interaction. Its utility was demonstrated by determining specific high-confidence target datasets for miR-124, miR-132, and miR-181 that contained known and previously unknown transcripts. Two previously unknown miR-132 targets identified with RISCtrap, adaptor protein CT10 regulator of kinase 1 (CRK1) and tight junction-associated protein 1 (TJAP1), were shown to be endogenously regulated by miR-132 in adult mouse forebrain. The datasets, moreover, differed in the number of targets and in the types and frequency of microRNA recognition element (MRE) motifs, thus revealing a previously underappreciated level of specificity in the target sets regulated by individual miRNAs.
Project description:Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.
Project description:The process of identifying the protein targets and off-targets of a biologically active compound is of great importance in modern drug discovery. Various chemical proteomics approaches have been established for this purpose. To compare the different approaches, and to understand which method would provide the best results, we have chosen the EGFR inhibitor lapatinib as an example molecule. Lapatinib derivatives were designed using linkers with motifs, including amino (amidation), alkyne (click chemistry) and the diazirine group (photo-affinity). These modified lapatinib analogues were validated for their ability to inhibit EGFR activity in vitro and were shown to pull down purified recombinant EGFR protein. In all of the approaches evaluated here, we identified EGFR as the main protein target from the lysate of immortalised cell line expressing EGFR, thus validating its potential use to identify unknown protein targets. Taken together, the results reported here give insight into the cellular activities of lapatinib.
Project description:Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the underlying mechanisms have not yet been comprehensively understood. In this study, a systematic approach was utilized to identify the microRNA signature in DN and to introduce novel drug targets (DTs) in DN. Using microarray profiling followed by qPCR confirmation, 13 and 6 differentially expressed (DE) microRNAs were identified in the kidney cortex and medulla, respectively. The microRNA-target interaction networks for each anatomical compartment were constructed and central nodes were identified. Moreover, enrichment analysis was performed to identify key signaling pathways. To develop a strategy for DT prediction, the human proteome was annotated with 65 biochemical characteristics and 23 network topology parameters. Furthermore, all proteins targeted by at least one FDA-approved drug were identified. Next, mGMDH-AFS, a high-performance machine learning algorithm capable of tolerating massive imbalanced size of the classes, was developed to classify DT and non-DT proteins. The sensitivity, specificity, accuracy, and precision of the proposed method were 90%, 86%, 88%, and 89%, respectively. Moreover, it significantly outperformed the state-of-the-art (P-value ≤ 0.05) and showed very good diagnostic accuracy and high agreement between predicted and observed class labels. The cortex and medulla networks were then analyzed with this validated machine to identify potential DTs. Among the high-rank DT candidates are Egfr, Prkce, clic5, Kit, and Agtr1a which is a current well-known target in DN. In conclusion, a combination of experimental and computational approaches was exploited to provide a holistic insight into the disorder for introducing novel therapeutic targets.
Project description:Autosomal dominant polycystic kidney disease (ADPKD) is characterized by cyst formation throughout the kidney parenchyma. It is caused by mutations in either of two genes, PKD1 and PKD2. Mice that lack functional Pkd1 (Pkd1null/null), develop rapidly progressive cystic disease during embryogenesis, and serve as a model to study human ADPKD. We examined the molecular pathways that modulate renal cyst growth in the Pkd1null/null model by performing global gene-expression profiling in embryonic kidneys at day 14 and 17. Gene Ontology and gene set enrichment analysis were used to identify overrepresented signaling pathways in Pkd1null/null kidneys. We found dysregulation of developmental, metabolic, and signaling pathways (e.g. Wnt, calcium, TGF-b and MAPK) in Pkd1null/null kidneys.
Project description:Protein kinases may function more like variable rheostats rather than two-state switches. However, we lack approaches to properly analyze this aspect of kinase-dependent regulation. To address this, we develop a strategy in which a kinase inhibitor is identified using genetics-based screens, kinase mutations that confer resistance are characterized, and dose-dependent responses of isogenic drug-sensitive and resistant cells to inhibitor treatments are compared. This approach has the advantage that function of wild-type kinase, rather than mutants, is examined. To develop this approach, we focus on Ark1, the fission yeast member of the conserved Aurora kinase family. Applying this approach reveals that proper chromosome compaction in fission yeast needs high Ark1 activity, while other processes depend on significantly lower activity levels. Our strategy is general and can be used to examine the functions of other molecular rheostats.
Project description:The identification of the kinase or kinases targeted by protein kinase inhibitors is a critical challenge in validating their use as therapeutic agents or molecular probes. Here, to address this problem, we describe a chemical genomics strategy that uses a direct comparison between microarray transcriptional signatures elicited by an inhibitor of unknown specificity and those elicited by highly specific pharmacological inhibition of engineered candidate kinase targets. By using this approach, we have identified two cyclin-dependent kinases, Cdk1 and Pho85, as the targets of the inhibitor GW400426 in Saccharomyces cerevisiae. We demonstrate that simultaneous inhibition of Cdk1 and Pho85, and not inhibition of either kinase alone, by GW400426 controls the expression of specific transcripts involved in polarized cell growth, thus revealing a cellular process that is uniquely sensitive to the multiplex inhibition of these two kinases. Our results suggest that the cellular responses induced by multiplex protein kinase inhibitors may be an emergent property that cannot be understood fully by considering only the sum of individual inhibitor-kinase interactions.
Project description:MicroRNAs have been found to play a profound role in embryonic and post-natal development through their regulation of processes such as cell proliferation, differentiation, and morphogenesis. The microRNA-30 (miR-30) family is necessary for vertebrate hepatobiliary development; however, the mechanism through which miR-30 regulates these processes is not fully understood. Here, we identify genes directly regulated by miR-30 that have been characterized as key developmental factors. The targets were confirmed via a luciferase reporter assay, following exogenous over-expression of miR-30a and miR-30c2 in cultured cells. Five novel miR-30ac2 targets were identified using this approach, all of which play crucial roles in hepatobiliary development or are involved in hepatocellular carcinoma and cholangiocarcinoma.
Project description:MicroRNAs (miRNAs) target mRNAs in human cells via complex mechanisms that are still incompletely understood. Using anti-Argonaute (anti-AGO) antibody co-immunoprecipitation, followed by microarray analyses and downstream bioinformatics, 'RIP-Chip' experiments enable direct analyses of miRNA targets. RIP-Chip studies (and parallel assessments of total input mRNA) were performed in cultured H4 cells after transfection with miRNAs corresponding to the miR-15/107 gene group (miR-103, miR-107, miR-16 and miR-195), and five control miRNAs. Three biological replicates were run for each condition with a total of 54 separate human Affymetrix Human Gene 1.0 ST array replicates. Computational analyses queried for determinants of miRNA:mRNA binding. The analyses support four major findings: (i) RIP-Chip studies correlated with total input mRNA profiling provides more comprehensive information than using either RIP-Chip or total mRNA profiling alone after miRNA transfections; (ii) new data confirm that miR-107 paralogs target coding sequence (CDS) of mRNA; (iii) biochemical and computational studies indicate that the 3' portion of miRNAs plays a role in guiding miR-103/7 to the CDS of targets; and (iv) there are major sequence-specific targeting differences between miRNAs in terms of CDS versus 3'-untranslated region targeting, and stable AGO association versus mRNA knockdown. Future studies should take this important miRNA-to-miRNA variability into account.