851
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Lachmann A, Torre D, Keenan AB, Jagodnik KM, Lee HJ, Wang L, Silverstein MC, Ma'ayan A. Massive mining of publicly available RNA-seq data from human and mouse. Nat Commun 2018; 9:1366. [PMID: 29636450 PMCID: PMC5893633 DOI: 10.1038/s41467-018-03751-6] [Citation(s) in RCA: 389] [Impact Index Per Article: 64.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2018] [Accepted: 03/08/2018] [Indexed: 02/06/2023] Open
Abstract
RNA sequencing (RNA-seq) is the leading technology for genome-wide transcript quantification. However, publicly available RNA-seq data is currently provided mostly in raw form, a significant barrier for global and integrative retrospective analyses. ARCHS4 is a web resource that makes the majority of published RNA-seq data from human and mouse available at the gene and transcript levels. For developing ARCHS4, available FASTQ files from RNA-seq experiments from the Gene Expression Omnibus (GEO) were aligned using a cloud-based infrastructure. In total 187,946 samples are accessible through ARCHS4 with 103,083 mouse and 84,863 human. Additionally, the ARCHS4 web interface provides intuitive exploration of the processed data through querying tools, interactive visualization, and gene pages that provide average expression across cell lines and tissues, top co-expressed genes for each gene, and predicted biological functions and protein-protein interactions for each gene based on prior knowledge combined with co-expression.
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Affiliation(s)
- Alexander Lachmann
- Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG), Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Denis Torre
- Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG), Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Alexandra B Keenan
- Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG), Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Kathleen M Jagodnik
- Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG), Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Hoyjin J Lee
- Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG), Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Lily Wang
- Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG), Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Moshe C Silverstein
- Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG), Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Avi Ma'ayan
- Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG), Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA.
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852
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Fachrul M, Utomo DH, Parikesit AA. lncRNA-based study of epigenetic regulations in diabetic peripheral neuropathy. In Silico Pharmacol 2018; 6:7. [PMID: 30607320 DOI: 10.1007/s40203-018-0042-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Accepted: 03/19/2018] [Indexed: 01/09/2023] Open
Abstract
Diabetes remains one of the most prevalent non-communicable diseases in the world, affecting over 400 million of people worldwide, causing serious complications leading to amputations and even death. Over the years, researchers have found that, in addition to genomic mutations, epigenetic mechanisms also play a role in the development of diabetes-specifically type-2 diabetes. Long noncoding RNAs (lncRNAs) have been linked to mediate epigenetic mechanisms, including those in late-stage diabetes. This study attempts to assess the unexplored topic of how lncRNAs could be used to assess the epigenetic mechanisms present in diabetic peripheral neuropathy (DPN); a serious complication of the disease often leading to amputation. Differential lncRNA expression analysis was done with a dataset containing DPN and healthy patients. Standard and corrected t test, and also LIMMA was applied. Results of this study indicates the usefulness of lncRNAs as an exploratory tool to elucidate the complexity of the epigenetic mechanisms of human DPN.
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Affiliation(s)
- Muhamad Fachrul
- Bioinformatics Department, School of Life Sciences, Indonesia International Institute for Life Sciences, Jakarta, Indonesia
| | - Didik H Utomo
- 2Biology Department, Faculty of Sciences, Brawijaya University, Malang, Indonesia
- Research and Education Center for Bioinformatics, Nusantara Institute for Life Science and Technology, Jakarta, Indonesia
| | - Arli A Parikesit
- Bioinformatics Department, School of Life Sciences, Indonesia International Institute for Life Sciences, Jakarta, Indonesia
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853
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McGrail DJ, Federico L, Li Y, Dai H, Lu Y, Mills GB, Yi S, Lin SY, Sahni N. Multi-omics analysis reveals neoantigen-independent immune cell infiltration in copy-number driven cancers. Nat Commun 2018; 9:1317. [PMID: 29615613 PMCID: PMC5882811 DOI: 10.1038/s41467-018-03730-x] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Accepted: 03/05/2018] [Indexed: 12/20/2022] Open
Abstract
To realize the full potential of immunotherapy, it is critical to understand the drivers of tumor infiltration by immune cells. Previous studies have linked immune infiltration with tumor neoantigen levels, but the broad applicability of this concept remains unknown. Here, we find that while this observation is true across cancers characterized by recurrent mutations, it does not hold for cancers driven by recurrent copy number alterations, such as breast and pancreatic tumors. To understand immune invasion in these cancers, we developed an integrative multi-omics framework, identifying the DNA damage response protein ATM as a driver of cytokine production leading to increased immune infiltration. This prediction was validated in numerous orthogonal datasets, as well as experimentally in vitro and in vivo by cytokine release and immune cell migration. These findings demonstrate diverse drivers of immune cell infiltration across cancer lineages and may facilitate the clinical adaption of immunotherapies across diverse malignancies.
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Affiliation(s)
- Daniel J McGrail
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Lorenzo Federico
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Yongsheng Li
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Hui Dai
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Yiling Lu
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Gordon B Mills
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Song Yi
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
- Department of Oncology, Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX, 78712, USA.
| | - Shiaw-Yih Lin
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - Nidhi Sahni
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
- Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
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854
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Callegaro G, Forcella M, Melchioretto P, Frattini A, Gribaldo L, Fusi P, Fabbri M, Urani C. Toxicogenomics applied to in vitro Cell Transformation Assay reveals mechanisms of early response to cadmium. Toxicol In Vitro 2018; 48:232-243. [DOI: 10.1016/j.tiv.2018.01.025] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 01/26/2018] [Accepted: 01/28/2018] [Indexed: 01/01/2023]
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855
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Ikaros family zinc finger 1 regulates dendritic cell development and function in humans. Nat Commun 2018; 9:1239. [PMID: 29588478 PMCID: PMC5869589 DOI: 10.1038/s41467-018-02977-8] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2017] [Accepted: 01/10/2018] [Indexed: 12/17/2022] Open
Abstract
Ikaros family zinc finger 1 (IKZF1) is a haematopoietic transcription factor required for mammalian B-cell development. IKZF1 deficiency also reduces plasmacytoid dendritic cell (pDC) numbers in mice, but its effects on human DC development are unknown. Here we show that heterozygous mutation of IKZF1 in human decreases pDC numbers and expands conventional DC1 (cDC1). Lenalidomide, a drug that induces proteosomal degradation of IKZF1, also decreases pDC numbers in vivo, and reduces the ratio of pDC/cDC1 differentiated from progenitor cells in vitro in a dose-dependent manner. In addition, non-classical monocytes are reduced by IKZF1 deficiency in vivo. DC and monocytes from patients with IKZF1 deficiency or lenalidomide-treated cultures secrete less IFN-α, TNF and IL-12. These results indicate that human DC development and function are regulated by IKZF1, providing further insights into the consequences of IKZF1 mutation on immune function and the mechanism of immunomodulation by lenalidomide. IKZF1 is a transcription factor known to regulate mammalian B-cell development. Here the authors show that IKZF1 is required for human pDC development and regulation of DC cytokine production in patients with IKZF1 haploinsufficiency, findings which are recapitulated in lenalidomide-induced IKZF1 deficiency.
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856
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Hydrophilic Auristatin Glycoside Payload Enables Improved Antibody-Drug Conjugate Efficacy and Biocompatibility. Antibodies (Basel) 2018; 7:antib7020015. [PMID: 31544867 PMCID: PMC6698876 DOI: 10.3390/antib7020015] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 03/01/2018] [Accepted: 03/05/2018] [Indexed: 11/17/2022] Open
Abstract
Antibody-drug conjugates (ADCs) offer a combination of antibody therapy and specific delivery of potent small-molecule payloads to target cells. The properties of the ADC molecule are determined by the balance of its components. The efficacy of the payload component increases with higher drug-to-antibody ratio (DAR), while homogeneous DAR = 8 ADCs are easily prepared by conjugation to the four accessible antibody hinge cystines. However, use of hydrophobic payloads has permitted only DAR = 2-4, due to poor pharmacokinetics and aggregation problems. Here, we describe generation and characterization of homogeneous DAR = 8 ADCs carrying a novel auristatin β-D-glucuronide, MMAU. The glycoside payload contributed to overall hydrophilicity of the ADC reducing aggregation. Compared to standard DAR = 2-4 ADCs, cytotoxicity of the homogeneous DAR = 8 ADCs was improved to low-picomolar IC50 values against cancer cells in vitro. Bystander efficacy was restored after ADC internalization and subsequent cleavage of the glycoside, although unconjugated MMAU was relatively non-toxic to cells. DAR = 8 MMAU ADCs were effective against target antigen-expressing xenograft tumors. The ADCs were also studied in 3D in vitro patient-derived xenograft (PDX) assays where they outperformed clinically used ADC. In conclusion, increased hydrophilicity of the payload contributed to the ADC's hydrophilicity, stability and safety to non-target cells, while significantly improving cytotoxicity and enabling bystander efficacy.
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857
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Mutations in THAP1/DYT6 reveal that diverse dystonia genes disrupt similar neuronal pathways and functions. PLoS Genet 2018; 14:e1007169. [PMID: 29364887 PMCID: PMC5798844 DOI: 10.1371/journal.pgen.1007169] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2017] [Revised: 02/05/2018] [Accepted: 12/25/2017] [Indexed: 12/14/2022] Open
Abstract
Dystonia is characterized by involuntary muscle contractions. Its many forms are genetically, phenotypically and etiologically diverse and it is unknown whether their pathogenesis converges on shared pathways. Mutations in THAP1 [THAP (Thanatos-associated protein) domain containing, apoptosis associated protein 1], a ubiquitously expressed transcription factor with DNA binding and protein-interaction domains, cause dystonia, DYT6. There is a unique, neuronal 50-kDa Thap1-like immunoreactive species, and Thap1 levels are auto-regulated on the mRNA level. However, THAP1 downstream targets in neurons, and the mechanism via which it causes dystonia are largely unknown. We used RNA-Seq to assay the in vivo effect of a heterozygote Thap1 C54Y or ΔExon2 allele on the gene transcription signatures in neonatal mouse striatum and cerebellum. Enriched pathways and gene ontology terms include eIF2α Signaling, Mitochondrial Dysfunction, Neuron Projection Development, Axonal Guidance Signaling, and Synaptic LongTerm Depression, which are dysregulated in a genotype and tissue-dependent manner. Electrophysiological and neurite outgrowth assays were consistent with those enrichments, and the plasticity defects were partially corrected by salubrinal. Notably, several of these pathways were recently implicated in other forms of inherited dystonia, including DYT1. We conclude that dysfunction of these pathways may represent a point of convergence in the pathophysiology of several forms of inherited dystonia. Dystonia is a brain disorder that causes disabling involuntary muscle contractions and abnormal postures. Mutations in THAP1, a zinc-finger transcription factor, cause DYT6, but its neuronal targets and functions are unknown. In this study, we sought to determine the effects of Thap1C54Y and ΔExon2 alleles on the gene transcription signatures at postnatal day 1 (P1) in the mouse striatum and cerebellum in order to correlate function with specific genes or pathways. Our unbiased transcriptomics approach showed that Thap1 mutants revealed multiple signaling pathways involved in neuronal plasticity, axonal guidance, and oxidative stress response, which are also present in other forms of dystonia, particularly DYT1. We conclude that dysfunction of these pathways may represent a point of convergence on the pathogenesis of unrelated forms of inherited dystonia.
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858
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Keenan AB, Jenkins SL, Jagodnik KM, Koplev S, He E, Torre D, Wang Z, Dohlman AB, Silverstein MC, Lachmann A, Kuleshov MV, Ma'ayan A, Stathias V, Terryn R, Cooper D, Forlin M, Koleti A, Vidovic D, Chung C, Schürer SC, Vasiliauskas J, Pilarczyk M, Shamsaei B, Fazel M, Ren Y, Niu W, Clark NA, White S, Mahi N, Zhang L, Kouril M, Reichard JF, Sivaganesan S, Medvedovic M, Meller J, Koch RJ, Birtwistle MR, Iyengar R, Sobie EA, Azeloglu EU, Kaye J, Osterloh J, Haston K, Kalra J, Finkbiener S, Li J, Milani P, Adam M, Escalante-Chong R, Sachs K, Lenail A, Ramamoorthy D, Fraenkel E, Daigle G, Hussain U, Coye A, Rothstein J, Sareen D, Ornelas L, Banuelos M, Mandefro B, Ho R, Svendsen CN, Lim RG, Stocksdale J, Casale MS, Thompson TG, Wu J, Thompson LM, Dardov V, Venkatraman V, Matlock A, Van Eyk JE, Jaffe JD, Papanastasiou M, Subramanian A, Golub TR, Erickson SD, Fallahi-Sichani M, Hafner M, Gray NS, Lin JR, Mills CE, Muhlich JL, Niepel M, Shamu CE, Williams EH, Wrobel D, Sorger PK, Heiser LM, Gray JW, Korkola JE, Mills GB, LaBarge M, Feiler HS, Dane MA, Bucher E, Nederlof M, Sudar D, Gross S, Kilburn DF, Smith R, Devlin K, Margolis R, Derr L, Lee A, Pillai A. The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations. Cell Syst 2018; 6:13-24. [PMID: 29199020 PMCID: PMC5799026 DOI: 10.1016/j.cels.2017.11.001] [Citation(s) in RCA: 241] [Impact Index Per Article: 40.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Revised: 09/13/2017] [Accepted: 11/01/2017] [Indexed: 12/19/2022]
Abstract
The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.
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Affiliation(s)
- Alexandra B Keenan
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sherry L Jenkins
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kathleen M Jagodnik
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Simon Koplev
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Edward He
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Denis Torre
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Zichen Wang
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Anders B Dohlman
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Moshe C Silverstein
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Alexander Lachmann
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Maxim V Kuleshov
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Avi Ma'ayan
- BD2K-LINCS DCIC, Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Vasileios Stathias
- BD2K-LINCS DCIC, Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL 33146, USA
| | - Raymond Terryn
- BD2K-LINCS DCIC, Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL 33146, USA
| | - Daniel Cooper
- BD2K-LINCS DCIC, Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL 33146, USA
| | - Michele Forlin
- BD2K-LINCS DCIC, Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL 33146, USA
| | - Amar Koleti
- BD2K-LINCS DCIC, Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL 33146, USA
| | - Dusica Vidovic
- BD2K-LINCS DCIC, Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL 33146, USA
| | - Caty Chung
- BD2K-LINCS DCIC, Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL 33146, USA
| | - Stephan C Schürer
- BD2K-LINCS DCIC, Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL 33146, USA
| | - Jouzas Vasiliauskas
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Marcin Pilarczyk
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Behrouz Shamsaei
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Mehdi Fazel
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Yan Ren
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Wen Niu
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Nicholas A Clark
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Shana White
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Naim Mahi
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Lixia Zhang
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Michal Kouril
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - John F Reichard
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Siva Sivaganesan
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Mario Medvedovic
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Jaroslaw Meller
- BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA
| | - Rick J Koch
- DToxS, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Marc R Birtwistle
- DToxS, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ravi Iyengar
- DToxS, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Eric A Sobie
- DToxS, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Evren U Azeloglu
- DToxS, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Julia Kaye
- NeuroLINCS, Gladstone Institute of Neurological Disease and the Departments of Neurology and Physiology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jeannette Osterloh
- NeuroLINCS, Gladstone Institute of Neurological Disease and the Departments of Neurology and Physiology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Kelly Haston
- NeuroLINCS, Gladstone Institute of Neurological Disease and the Departments of Neurology and Physiology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jaslin Kalra
- NeuroLINCS, Gladstone Institute of Neurological Disease and the Departments of Neurology and Physiology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Steve Finkbiener
- NeuroLINCS, Gladstone Institute of Neurological Disease and the Departments of Neurology and Physiology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jonathan Li
- NeuroLINCS, Department of Biological Engineering, MIT, Cambridge, MA 02142, USA
| | - Pamela Milani
- NeuroLINCS, Department of Biological Engineering, MIT, Cambridge, MA 02142, USA
| | - Miriam Adam
- NeuroLINCS, Department of Biological Engineering, MIT, Cambridge, MA 02142, USA
| | | | - Karen Sachs
- NeuroLINCS, Department of Biological Engineering, MIT, Cambridge, MA 02142, USA
| | - Alex Lenail
- NeuroLINCS, Department of Biological Engineering, MIT, Cambridge, MA 02142, USA
| | - Divya Ramamoorthy
- NeuroLINCS, Department of Biological Engineering, MIT, Cambridge, MA 02142, USA
| | - Ernest Fraenkel
- NeuroLINCS, Department of Biological Engineering, MIT, Cambridge, MA 02142, USA
| | - Gavin Daigle
- NeuroLINCS, Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Uzma Hussain
- NeuroLINCS, Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Alyssa Coye
- NeuroLINCS, Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Jeffrey Rothstein
- NeuroLINCS, Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Dhruv Sareen
- NeuroLINCS, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Loren Ornelas
- NeuroLINCS, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Maria Banuelos
- NeuroLINCS, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Berhan Mandefro
- NeuroLINCS, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Ritchie Ho
- NeuroLINCS, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Clive N Svendsen
- NeuroLINCS, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Ryan G Lim
- NeuroLINCS, Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine, CA 92697, USA
| | - Jennifer Stocksdale
- NeuroLINCS, Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine, CA 92697, USA
| | - Malcolm S Casale
- NeuroLINCS, Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine, CA 92697, USA
| | - Terri G Thompson
- NeuroLINCS, Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine, CA 92697, USA
| | - Jie Wu
- NeuroLINCS, Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine, CA 92697, USA
| | - Leslie M Thompson
- NeuroLINCS, Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine, CA 92697, USA
| | - Victoria Dardov
- NeuroLINCS, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | | | - Andrea Matlock
- NeuroLINCS, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | | | - Jacob D Jaffe
- LINCS PCCSE, The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | | | - Aravind Subramanian
- LINCS Center for Transcriptomics, The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Todd R Golub
- LINCS Center for Transcriptomics, The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Dana-Farber Cancer Institute, Boston, MA 02215, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Sean D Erickson
- HMS LINCS Center, Harvard Medical School, Boston, MA 02115, USA
| | | | - Marc Hafner
- HMS LINCS Center, Harvard Medical School, Boston, MA 02115, USA
| | | | - Jia-Ren Lin
- HMS LINCS Center, Harvard Medical School, Boston, MA 02115, USA
| | - Caitlin E Mills
- HMS LINCS Center, Harvard Medical School, Boston, MA 02115, USA
| | | | - Mario Niepel
- HMS LINCS Center, Harvard Medical School, Boston, MA 02115, USA
| | | | | | - David Wrobel
- HMS LINCS Center, Harvard Medical School, Boston, MA 02115, USA
| | - Peter K Sorger
- HMS LINCS Center, Harvard Medical School, Boston, MA 02115, USA
| | - Laura M Heiser
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Joe W Gray
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - James E Korkola
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Gordon B Mills
- MEP-LINCS Center, Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Mark LaBarge
- MEP-LINCS Center, Department of Population Sciences, Beckman Research Institute at City of Hope, Duarte, CA 91011, USA; MEP-LINCS Center, Center for Cancer Biomarkers Research, University of Bergen, Bergen 5009, Norway
| | - Heidi S Feiler
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Mark A Dane
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Elmar Bucher
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Michel Nederlof
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA; MEP-LINCS Center, Quantitative Imaging Systems LLC, Portland, OR 97239, USA
| | - Damir Sudar
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA; MEP-LINCS Center, Quantitative Imaging Systems LLC, Portland, OR 97239, USA
| | - Sean Gross
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - David F Kilburn
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Rebecca Smith
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Kaylyn Devlin
- MEP-LINCS Center, Oregon Health & Science University, Portland, OR 97239, USA
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859
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Li C, Cao F, Li S, Huang S, Li W, Abumaria N. Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus. Front Mol Neurosci 2018; 10:454. [PMID: 29375311 PMCID: PMC5768633 DOI: 10.3389/fnmol.2017.00454] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 12/26/2017] [Indexed: 12/28/2022] Open
Abstract
Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA) has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice). Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to stress-induced pathologies; in particular, to inescapable stress-induced synaptic modifications.
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Affiliation(s)
- Chaoqun Li
- Institutes of Brain Science, Collaborative Innovation Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Feifei Cao
- Institutes of Brain Science, Collaborative Innovation Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shengli Li
- Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shenglin Huang
- Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei Li
- Institutes of Brain Science, Collaborative Innovation Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Nashat Abumaria
- Institutes of Brain Science, Collaborative Innovation Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Laboratory Animal Science, Shanghai Medical College, Fudan University, Shanghai, China
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860
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Ren L, Sun Y, Lu H, Ye D, Han L, Wang N, Daugherty A, Li F, Wang M, Su F, Tao W, Sun J, Zelcer N, Mullick AE, Danser AHJ, Jiang Y, He Y, Ruan X, Lu X. (Pro)renin Receptor Inhibition Reprograms Hepatic Lipid Metabolism and Protects Mice From Diet-Induced Obesity and Hepatosteatosis. Circ Res 2018; 122:730-741. [PMID: 29301853 DOI: 10.1161/circresaha.117.312422] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2017] [Revised: 11/18/2017] [Accepted: 12/29/2017] [Indexed: 01/12/2023]
Abstract
RATIONALE An elevated level of plasma LDL (low-density lipoprotein) is an established risk factor for cardiovascular disease. Recently, we reported that the (pro)renin receptor ([P]RR) regulates LDL metabolism in vitro via the LDLR (LDL receptor) and SORT1 (sortilin-1), independently of the renin-angiotensin system. OBJECTIVES To investigate the physiological role of (P)RR in lipid metabolism in vivo. METHODS AND RESULTS We used N-acetylgalactosamine modified antisense oligonucleotides to specifically inhibit hepatic (P)RR expression in C57BL/6 mice and studied the consequences this has on lipid metabolism. In line with our earlier report, hepatic (P)RR silencing increased plasma LDL-C (LDL cholesterol). Unexpectedly, this also resulted in markedly reduced plasma triglycerides in a SORT1-independent manner in C57BL/6 mice fed a normal- or high-fat diet. In LDLR-deficient mice, hepatic (P)RR inhibition reduced both plasma cholesterol and triglycerides, in a diet-independent manner. Mechanistically, we found that (P)RR inhibition decreased protein abundance of ACC (acetyl-CoA carboxylase) and PDH (pyruvate dehydrogenase). This alteration reprograms hepatic metabolism, leading to reduced lipid synthesis and increased fatty acid oxidation. As a result, hepatic (P)RR inhibition attenuated diet-induced obesity and hepatosteatosis. CONCLUSIONS Collectively, our study suggests that (P)RR plays a key role in energy homeostasis and regulation of plasma lipids by integrating hepatic glucose and lipid metabolism.
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Affiliation(s)
- Liwei Ren
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Yuan Sun
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Hong Lu
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Dien Ye
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Lijuan Han
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Na Wang
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Alan Daugherty
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Furong Li
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Miaomiao Wang
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Fengting Su
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Wenjun Tao
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Jie Sun
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Noam Zelcer
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Adam E Mullick
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - A H Jan Danser
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Yizhou Jiang
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Yongcheng He
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.)
| | - Xiongzhong Ruan
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.).
| | - Xifeng Lu
- From the AstraZeneca-Shenzhen University Joint Institute of Nephrology, Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, China (L.R., Y.S., D.Y., L.H., N.W., M.W., F.S., W.T., J.S., X.R., X.L.); Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China (L.R., Y.S., F.L., X.L.); Division of Pharmacology and Vascular Medicine, Department of Internal Medicine, Erasmus Medical Center, Rotterdam University, The Netherlands (L.R., Y.S., A.H.J.D.); Saha Cardiovascular Research Center and Department of Physiology, University of Kentucky, Lexington (H.L., A.D.); Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, The Netherlands (N.Z.); Ionis Pharmaceuticals, Inc, Carlsbad, CA (A.E.M.); Institute for Advanced Study, Shenzhen University, China (Y.J.); The First Affiliated Hospital of Shenzhen University, China (Y.H.); and John Moorhead Laboratory, Center for Nephrology, University College London, United Kingdom (X.R.).
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861
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Lakiotaki K, Vorniotakis N, Tsagris M, Georgakopoulos G, Tsamardinos I. BioDataome: a collection of uniformly preprocessed and automatically annotated datasets for data-driven biology. Database (Oxford) 2018; 2018:4917852. [PMID: 29688366 PMCID: PMC5836265 DOI: 10.1093/database/bay011] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Revised: 01/12/2018] [Accepted: 01/15/2018] [Indexed: 01/12/2023]
Abstract
Biotechnology revolution generates a plethora of omics data with an exponential growth pace. Therefore, biological data mining demands automatic, 'high quality' curation efforts to organize biomedical knowledge into online databases. BioDataome is a database of uniformly preprocessed and disease-annotated omics data with the aim to promote and accelerate the reuse of public data. We followed the same preprocessing pipeline for each biological mart (microarray gene expression, RNA-Seq gene expression and DNA methylation) to produce ready for downstream analysis datasets and automatically annotated them with disease-ontology terms. We also designate datasets that share common samples and automatically discover control samples in case-control studies. Currently, BioDataome includes ∼5600 datasets, ∼260 000 samples spanning ∼500 diseases and can be easily used in large-scale massive experiments and meta-analysis. All datasets are publicly available for querying and downloading via BioDataome web application. We demonstrate BioDataome's utility by presenting exploratory data analysis examples. We have also developed BioDataome R package found in: https://github.com/mensxmachina/BioDataome/.Database URL: http://dataome.mensxmachina.org/.
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Affiliation(s)
- Kleanthi Lakiotaki
- Computer Science Department, University of Crete, Voutes Campus, 70013 Heraklion, Crete, Greece
| | - Nikolaos Vorniotakis
- Computer Science Department, University of Crete, Voutes Campus, 70013 Heraklion, Crete, Greece
| | - Michail Tsagris
- Computer Science Department, University of Crete, Voutes Campus, 70013 Heraklion, Crete, Greece
| | - Georgios Georgakopoulos
- Computer Science Department, University of Crete, Voutes Campus, 70013 Heraklion, Crete, Greece
| | - Ioannis Tsamardinos
- Computer Science Department, University of Crete, Voutes Campus, 70013 Heraklion, Crete, Greece
- Gnosis Data Analysis PC, Palaiokapa 64, 71305 Heraklion, Crete, Greece
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862
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Rusan M, Li K, Li Y, Christensen CL, Abraham BJ, Kwiatkowski N, Buczkowski KA, Bockorny B, Chen T, Li S, Rhee K, Zhang H, Chen W, Terai H, Tavares T, Leggett AL, Li T, Wang Y, Zhang T, Kim TJ, Hong SH, Poudel-Neupane N, Silkes M, Mudianto T, Tan L, Shimamura T, Meyerson M, Bass AJ, Watanabe H, Gray NS, Young RA, Wong KK, Hammerman PS. Suppression of Adaptive Responses to Targeted Cancer Therapy by Transcriptional Repression. Cancer Discov 2018; 8:59-73. [PMID: 29054992 PMCID: PMC5819998 DOI: 10.1158/2159-8290.cd-17-0461] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Revised: 10/02/2017] [Accepted: 10/17/2017] [Indexed: 12/15/2022]
Abstract
Acquired drug resistance is a major factor limiting the effectiveness of targeted cancer therapies. Targeting tumors with kinase inhibitors induces complex adaptive programs that promote the persistence of a fraction of the original cell population, facilitating the eventual outgrowth of inhibitor-resistant tumor clones. We show that the addition of a newly identified CDK7/12 inhibitor, THZ1, to targeted therapy enhances cell killing and impedes the emergence of drug-resistant cell populations in diverse cellular and in vivo cancer models. We propose that targeted therapy induces a state of transcriptional dependency in a subpopulation of cells poised to become drug tolerant, which THZ1 can exploit by blocking dynamic transcriptional responses, promoting remodeling of enhancers and key signaling outputs required for tumor cell survival in the setting of targeted therapy. These findings suggest that the addition of THZ1 to targeted therapies is a promising broad-based strategy to hinder the emergence of drug-resistant cancer cell populations.Significance: CDK7/12 inhibition prevents active enhancer formation at genes, promoting resistance emergence in response to targeted therapy, and impedes the engagement of transcriptional programs required for tumor cell survival. CDK7/12 inhibition in combination with targeted cancer therapies may serve as a therapeutic paradigm for enhancing the effectiveness of targeted therapies. Cancer Discov; 8(1); 59-73. ©2017 AACR.See related commentary by Carugo and Draetta, p. 17This article is highlighted in the In This Issue feature, p. 1.
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Affiliation(s)
- Maria Rusan
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Department of Clinical Medicine, Aarhus University, Aarhus, 8000, Denmark
- Cancer Program, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Kapsok Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Department of Dermatology, Chung-Ang University College of Medicine, Seoul, Korea
| | - Yvonne Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Cancer Program, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | | | - Brian J Abraham
- Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, USA
| | - Nicholas Kwiatkowski
- Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Kevin A Buczkowski
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Bruno Bockorny
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Cancer Program, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
- Division of Hematology and Oncology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Ting Chen
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Shuai Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Kevin Rhee
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Haikuo Zhang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Wankun Chen
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Department of Anesthesiology, Fudan University Shanghai Cancer Center, Shanghai 200032 China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Hideki Terai
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Tiffany Tavares
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Alan L Leggett
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Tianxia Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Yichen Wang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Tinghu Zhang
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Tae-Jung Kim
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Sook-Hee Hong
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | | | - Michael Silkes
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Tenny Mudianto
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Li Tan
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Takeshi Shimamura
- Molecular Pharmacology and Therapeutics, Oncology Research Institute, Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153 USA
| | - Matthew Meyerson
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Cancer Program, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Adam J Bass
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Cancer Program, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
- Departments of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Hideo Watanabe
- Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine and Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Nathanael S Gray
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Richard A Young
- Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kwok-Kin Wong
- Laura & Isaac Perlmutter Cancer Center, NYU Langone Medical Center, New York, NY, 10016, USA
| | - Peter S Hammerman
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Cancer Program, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
- Novartis Institutes of Biomedical Research, Cambridge, MA, 02139
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863
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Gonzalez-Gonzalez FJ, Chandel NS, Jain M, Budinger GRS. Reactive oxygen species as signaling molecules in the development of lung fibrosis. Transl Res 2017; 190:61-68. [PMID: 29080401 PMCID: PMC5730357 DOI: 10.1016/j.trsl.2017.09.005] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Revised: 09/10/2017] [Accepted: 09/28/2017] [Indexed: 12/15/2022]
Abstract
Pulmonary fibrosis is a relatively rare but devastating disease characterized by the excessive deposition of extracellular matrix. The increased matrix results in reduced lung compliance and increased work of breathing, while the obliteration of alveolar-capillary structures can result in hypoxemia and pulmonary hypertension, which manifests clinically as worsening shortness of breath, respiratory failure, and death. Unbiased genome-wide association studies combined with animal models suggest that damage to the alveolar epithelium is the initiating factor in pulmonary fibrosis. This epithelial injury leads to the activation and proliferation of myofibroblasts that secrete extracellular matrix proteins characteristic of fibrosis. The best described molecular link between alveolar epithelial dysfunction and myofibroblast activation and proliferation is the profibrotic cytokine transforming growth factor-β (TGF-β). We and others have found that mitochondrial and NAD(P)H oxidase-generated reactive oxygen species (ROS) play a signaling role to enhance TGF-β signaling and promote fibrosis. The purpose of this article is to review how ROS signaling leads to the activation of TGF-β. We suggest that an improved understanding of these pathways might explain the failure of nonselective antioxidants to improve outcomes in patients with pulmonary fibrosis and might identify novel targets for therapy.
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Affiliation(s)
- Francisco J Gonzalez-Gonzalez
- Division of Pulmonary and Critical Care Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Ill
| | - Navdeep S Chandel
- Division of Pulmonary and Critical Care Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Ill
| | - Manu Jain
- Division of Pulmonary and Critical Care Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Ill
| | - G R Scott Budinger
- Division of Pulmonary and Critical Care Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Ill.
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864
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Okuno H, Renault Mihara F, Ohta S, Fukuda K, Kurosawa K, Akamatsu W, Sanosaka T, Kohyama J, Hayashi K, Nakajima K, Takahashi T, Wysocka J, Kosaki K, Okano H. CHARGE syndrome modeling using patient-iPSCs reveals defective migration of neural crest cells harboring CHD7 mutations. eLife 2017; 6. [PMID: 29179815 PMCID: PMC5705211 DOI: 10.7554/elife.21114] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Accepted: 10/22/2017] [Indexed: 12/11/2022] Open
Abstract
CHARGE syndrome is caused by heterozygous mutations in the chromatin remodeler, CHD7, and is characterized by a set of malformations that, on clinical grounds, were historically postulated to arise from defects in neural crest formation during embryogenesis. To better delineate neural crest defects in CHARGE syndrome, we generated induced pluripotent stem cells (iPSCs) from two patients with typical syndrome manifestations, and characterized neural crest cells differentiated in vitro from these iPSCs (iPSC-NCCs). We found that expression of genes associated with cell migration was altered in CHARGE iPSC-NCCs compared to control iPSC-NCCs. Consistently, CHARGE iPSC-NCCs showed defective delamination, migration and motility in vitro, and their transplantation in ovo revealed overall defective migratory activity in the chick embryo. These results support the historical inference that CHARGE syndrome patients exhibit defects in neural crest migration, and provide the first successful application of patient-derived iPSCs in modeling craniofacial disorders. CHARGE syndrome is a disease in which organs including the heart, eyes and ears may not develop properly. The cells that form the tissues affected by CHARGE syndrome develop in embryos from precursor cells called neural crest cells. Individuals with CHARGE syndrome also have mutations in a gene called CHD7. However, it is difficult to examine how CHD7 mutations affect neural crest cells in embryos. In recent years, cell reprogramming techniques have made it possible to create induced pluripotent stem cells (iPSCs) from the specialized somatic cells found in the human body. These iPSCs can be developed into many different cell types, including neural crest cells. Okuno et al. created iPSCs from the skin cells of people with CHARGE syndrome, developed these cells into neural crest cells, and compared them with neural crest cells that were developed from the skin cells of people without CHARGE syndrome. The neural crest cells developed from people with CHARGE syndrome showed multiple abnormalities. For example, they were not able to move around correctly. This is an important observation because neural crest cells must move through tissues to form the various organs affected by CHARGE syndrome. Okuno et al. also observed changes in the activity of many genes other than CHD7 in the neural crest cells developed from CHARGE patients. Further research is now needed to find out which genes are the most important for restoring the normal activity of neural crest cells.
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Affiliation(s)
- Hironobu Okuno
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | | | - Shigeki Ohta
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Kimiko Fukuda
- Department of Biological Science, Tokyo Metropolitan University, Tokyo, Japan
| | - Kenji Kurosawa
- Division of Medical Genetics, Kanagawa Children's Medical Center, Yokohama, Japan
| | - Wado Akamatsu
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan.,Center for Genomic and Regenerative Medicine, Juntendo University School of Medicine, Tokyo, Japan
| | - Tsukasa Sanosaka
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Jun Kohyama
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Kanehiro Hayashi
- Department of Anatomy, Keio University School of Medicine, Tokyo, Japan
| | - Kazunori Nakajima
- Department of Anatomy, Keio University School of Medicine, Tokyo, Japan
| | - Takao Takahashi
- Department of Pediatrics, Keio University School of Medicine, Tokyo, Japan
| | - Joanna Wysocka
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, United States.,Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, United States.,Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, United States.,Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, United States
| | - Kenjiro Kosaki
- Center for Medical Genetics, Keio University School of Medicine, Tokyo, Japan
| | - Hideyuki Okano
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
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865
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Klaips CL, Jayaraj GG, Hartl FU. Pathways of cellular proteostasis in aging and disease. J Cell Biol 2017; 217:51-63. [PMID: 29127110 PMCID: PMC5748993 DOI: 10.1083/jcb.201709072] [Citation(s) in RCA: 480] [Impact Index Per Article: 68.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Revised: 10/17/2017] [Accepted: 10/18/2017] [Indexed: 12/19/2022] Open
Abstract
Ensuring cellular protein homeostasis, or proteostasis, requires precise control of protein synthesis, folding, conformational maintenance, and degradation. A complex and adaptive proteostasis network coordinates these processes with molecular chaperones of different classes and their regulators functioning as major players. This network serves to ensure that cells have the proteins they need while minimizing misfolding or aggregation events that are hallmarks of age-associated proteinopathies, including neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. It is now clear that the capacity of cells to maintain proteostasis undergoes a decline during aging, rendering the organism susceptible to these pathologies. Here we discuss the major proteostasis pathways in light of recent research suggesting that their age-dependent failure can both contribute to and result from disease. We consider different strategies to modulate proteostasis capacity, which may help develop urgently needed therapies for neurodegeneration and other age-dependent pathologies.
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Affiliation(s)
- Courtney L Klaips
- Department of Cellular Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany
| | | | - F Ulrich Hartl
- Department of Cellular Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany
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866
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Limbeck E, Vanselow JT, Hofmann J, Schlosser A, Mally A. Linking site-specific loss of histone acetylation to repression of gene expression by the mycotoxin ochratoxin A. Arch Toxicol 2017; 92:995-1014. [PMID: 29098329 DOI: 10.1007/s00204-017-2107-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Accepted: 10/26/2017] [Indexed: 11/30/2022]
Abstract
Ochratoxin A (OTA) is a potent renal carcinogen but its mechanism has not been fully resolved. In vitro and in vivo gene expression studies consistently revealed down-regulation of gene expression as the predominant transcriptional response to OTA. Based on the importance of specific histone acetylation marks in regulating gene transcription and our recent finding that OTA inhibits histone acetyltransferases (HATs), leading to loss of acetylation of histones and non-histone proteins, we hypothesized that OTA-mediated repression of gene expression may be causally linked to HAT inhibition and loss of histone acetylation. In this study, we used a novel mass spectrometry approach employing chemical 13C-acetylation of unmodified lysine residues for quantification of post-translational acetylation sites to identify site-specific alterations in histone acetylation in human kidney epithelial cells (HK-2) exposed to OTA. These results showed OTA-mediated hypoacetylation at almost all lysine residues of core histones, including loss of acetylation at H3K9 and H3K14, which are hallmarks of gene activation. ChIP-qPCR used to establish a possible link between H3K9 or H3K14 hypoacetylation and OTA-mediated down-regulation of selected genes (AMIGO2, CLASP2, CTNND1) confirmed OTA-mediated H3K9 hypoacetylation at promoter regions of these genes. Integrated analysis of OTA-mediated genome-wide changes in H3K9 acetylation identified by ChIP-Seq with published gene expression data further demonstrated that among OTA-responsive genes almost 80% of hypoacetylated genes were down-regulated, thus confirming an association between H3K9 acetylation status and gene expression of these genes. However, only 7% of OTA repressed genes showed loss of H3K9 acetylation within promoter regions. Interestingly, however, GO analysis and functional enrichment of down-regulated genes showing loss of H3K9 acetylation at their respective promoter regions revealed enrichment of genes involved in the regulation of transcription, including a number of transcription factors that are predicted to directly or indirectly regulate the expression of 98% of OTA repressed genes. Thus, it is possible that histone acetylation changes in a fairly small set of genes but with key function in transcriptional regulation may trigger a cascade of events that may lead to overall repression of gene expression. Taken together, our data provide evidence for a mechanistic link between loss of H3K9 acetylation as a consequence of OTA-mediated inhibition of HATs and repression of gene expression by OTA, thereby affecting cellular processes critical to tumorigenesis.
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Affiliation(s)
- Elisabeth Limbeck
- Department of Toxicology, University of Würzburg, Versbacher Str. 9, 97078, Würzburg, Germany
| | - Jens T Vanselow
- Rudolf Virchow Center for Experimental Biomedicine, University of Würzburg, 97078, Würzburg, Germany
| | - Julian Hofmann
- Department of Toxicology, University of Würzburg, Versbacher Str. 9, 97078, Würzburg, Germany
| | - Andreas Schlosser
- Rudolf Virchow Center for Experimental Biomedicine, University of Würzburg, 97078, Würzburg, Germany
| | - Angela Mally
- Department of Toxicology, University of Würzburg, Versbacher Str. 9, 97078, Würzburg, Germany.
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867
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Jagannath V, Brotzakis ZF, Parrinello M, Walitza S, Grünblatt E. Controversial Effects of D-Amino Acid Oxidase Activator (DAOA)/G72 on D-Amino Acid Oxidase (DAO) Activity in Human Neuronal, Astrocyte and Kidney Cell Lines: The N-methyl D-aspartate (NMDA) Receptor Hypofunction Point of View. Front Mol Neurosci 2017; 10:342. [PMID: 29114206 PMCID: PMC5660716 DOI: 10.3389/fnmol.2017.00342] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Accepted: 10/10/2017] [Indexed: 12/23/2022] Open
Abstract
Dysfunction of D-amino acid oxidase (DAO) and DAO activator (DAOA)/G72 genes have been linked to neuropsychiatric disorders. The glutamate hypothesis of schizophrenia has proposed that increased DAO activity leads to decreased D-serine, which subsequently may lead to N-methyl-D-aspartate (NMDA) receptor hypofunction. It has been shown that DAOA binds to DAO and increases its activity. However, there are also studies showing DAOA decreases DAO activity. Thus, the effect of DAOA on DAO is controversial. We aimed to understand the effect of DAOA on DAO activity in neuron-like (SH-SY5Y), astrocyte-like (1321N1) and kidney-like (HEK293) human cell lines. DAO activity was measured based on the release of hydrogen peroxide and its interaction with Amplex Red reagent. We found that DAOA increases DAO activity only in HEK293 cells, but has no effect on DAO activity in SH-SY5Y and 1321N1 cells. This might be because of different signaling pathways, or due to lower DAO and DAOA expression in SH-SY5Y and 1321N1 cells compared to HEK293 cells, but also due to different compartmentalization of the proteins. The lower DAO and DAOA expression in neuron-like SH-SY5Y and astrocyte-like 1321N1 cells might be due to tightly regulated expression, as previously reported in the human post-mortem brain. Our simulation experiments to demonstrate the interaction between DAOA and human DAO (hDAO) showed that hDAO holoenzyme [hDAO with flavine adenine dinucleotide (FAD)] becomes more flexible and misfolded in the presence of DAOA, whereas DAOA had no effect on hDAO apoprotein (hDAO without FAD), which indicate that DAOA inactivates hDAO holoenzyme. Furthermore, patch-clamp analysis demonstrated no effect of DAOA on NMDA receptor activity in NR1/NR2A HEK293 cells. In summary, the interaction between DAO and DAOA seems to be cell type and its biochemical characteristics dependent which still needs to be elucidated.
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Affiliation(s)
- Vinita Jagannath
- Molecular and Neurobiochemistry Laboratory, Centre for Child and Adolescent Psychiatry Research, Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, Switzerland
| | - Zacharias Faidon Brotzakis
- Department of Chemistry and Applied Biosciences, Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland.,Faculty of Informatics, Institute of Computational Science, Università della Svizzera Italiana (USI), Lugano, Switzerland
| | - Michele Parrinello
- Department of Chemistry and Applied Biosciences, Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland.,Faculty of Informatics, Institute of Computational Science, Università della Svizzera Italiana (USI), Lugano, Switzerland
| | - Susanne Walitza
- Molecular and Neurobiochemistry Laboratory, Centre for Child and Adolescent Psychiatry Research, Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, Switzerland.,Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.,Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Edna Grünblatt
- Molecular and Neurobiochemistry Laboratory, Centre for Child and Adolescent Psychiatry Research, Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, Switzerland.,Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.,Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
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868
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Wolski D, Foote PK, Chen DY, Lewis-Ximenez LL, Fauvelle C, Aneja J, Walker A, Tonnerre P, Torres-Cornejo A, Kvistad D, Imam S, Waring MT, Tully DC, Allen TM, Chung RT, Timm J, Haining WN, Kim AY, Baumert TF, Lauer GM. Early Transcriptional Divergence Marks Virus-Specific Primary Human CD8 + T Cells in Chronic versus Acute Infection. Immunity 2017; 47:648-663.e8. [PMID: 29045899 PMCID: PMC5708133 DOI: 10.1016/j.immuni.2017.09.006] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Revised: 06/13/2017] [Accepted: 09/13/2017] [Indexed: 01/11/2023]
Abstract
Distinct molecular pathways govern the differentiation of CD8+ effector T cells into memory or exhausted T cells during acute and chronic viral infection, but these are not well studied in humans. Here, we employed an integrative systems immunology approach to identify transcriptional commonalities and differences between virus-specific CD8+ T cells from patients with persistent and spontaneously resolving hepatitis C virus (HCV) infection during the acute phase. We observed dysregulation of metabolic processes during early persistent infection that was linked to changes in expression of genes related to nucleosomal regulation of transcription, T cell differentiation, and the inflammatory response and correlated with subject age, sex, and the presence of HCV-specific CD4+ T cell populations. These early changes in HCV-specific CD8+ T cell transcription preceded the overt establishment of T cell exhaustion, making this signature a prime target in the search for the regulatory origins of T cell dysfunction in chronic viral infection.
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Affiliation(s)
- David Wolski
- Gastrointestinal Unit and Liver Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA; Inserm, U1110, Institut de Recherche sur les Maladies Virales et Hépatiques, Strasbourg 67000, France; Université de Strasbourg, Strasbourg 67081, France
| | - Peter K Foote
- Gastrointestinal Unit and Liver Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Diana Y Chen
- Gastrointestinal Unit and Liver Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Lia L Lewis-Ximenez
- Laboratory of Viral Hepatitis, Oswaldo Cruz Institute, FIOCRUZ, Rio de Janeiro 21040, Brazil
| | - Catherine Fauvelle
- Inserm, U1110, Institut de Recherche sur les Maladies Virales et Hépatiques, Strasbourg 67000, France; Université de Strasbourg, Strasbourg 67081, France
| | - Jasneet Aneja
- Gastrointestinal Unit and Liver Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Andreas Walker
- Institute for Virology, University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Pierre Tonnerre
- Gastrointestinal Unit and Liver Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Almudena Torres-Cornejo
- Gastrointestinal Unit and Liver Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Daniel Kvistad
- Gastrointestinal Unit and Liver Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Sabrina Imam
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Michael T Waring
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Damien C Tully
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
| | - Todd M Allen
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
| | - Raymond T Chung
- Gastrointestinal Unit and Liver Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Jörg Timm
- Institute for Virology, University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf 40225, Germany
| | - W Nicholas Haining
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Arthur Y Kim
- Division of Infectious Disease, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Thomas F Baumert
- Inserm, U1110, Institut de Recherche sur les Maladies Virales et Hépatiques, Strasbourg 67000, France; Université de Strasbourg, Strasbourg 67081, France; Institut Hospitalo-Universitaire, Pôle Hépato-digestif, Nouvel Hôpital Civil, Strasbourg 67000, France
| | - Georg M Lauer
- Gastrointestinal Unit and Liver Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
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869
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Structural basis for regulation of the nucleo-cytoplasmic distribution of Bag6 by TRC35. Proc Natl Acad Sci U S A 2017; 114:11679-11684. [PMID: 29042515 DOI: 10.1073/pnas.1702940114] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
The metazoan protein BCL2-associated athanogene cochaperone 6 (Bag6) forms a hetero-trimeric complex with ubiquitin-like 4A and transmembrane domain recognition complex 35 (TRC35). This Bag6 complex is involved in tail-anchored protein targeting and various protein quality-control pathways in the cytosol as well as regulating transcription and histone methylation in the nucleus. Here we present a crystal structure of Bag6 and its cytoplasmic retention factor TRC35, revealing that TRC35 is remarkably conserved throughout the opisthokont lineage except at the C-terminal Bag6-binding groove, which evolved to accommodate Bag6, a unique metazoan factor. While TRC35 and its fungal homolog, guided entry of tail-anchored protein 4 (Get4), utilize a conserved hydrophobic patch to bind their respective partners, Bag6 wraps around TRC35 on the opposite face relative to the Get4-5 interface. We further demonstrate that TRC35 binding is critical not only for occluding the Bag6 nuclear localization sequence from karyopherin α to retain Bag6 in the cytosol but also for preventing TRC35 from succumbing to RNF126-mediated ubiquitylation and degradation. The results provide a mechanism for regulation of Bag6 nuclear localization and the functional integrity of the Bag6 complex in the cytosol.
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870
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Fernandez NF, Gundersen GW, Rahman A, Grimes ML, Rikova K, Hornbeck P, Ma’ayan A. Clustergrammer, a web-based heatmap visualization and analysis tool for high-dimensional biological data. Sci Data 2017; 4:170151. [PMID: 28994825 PMCID: PMC5634325 DOI: 10.1038/sdata.2017.151] [Citation(s) in RCA: 125] [Impact Index Per Article: 17.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 09/06/2017] [Indexed: 01/11/2023] Open
Abstract
Most tools developed to visualize hierarchically clustered heatmaps generate static images. Clustergrammer is a web-based visualization tool with interactive features such as: zooming, panning, filtering, reordering, sharing, performing enrichment analysis, and providing dynamic gene annotations. Clustergrammer can be used to generate shareable interactive visualizations by uploading a data table to a web-site, or by embedding Clustergrammer in Jupyter Notebooks. The Clustergrammer core libraries can also be used as a toolkit by developers to generate visualizations within their own applications. Clustergrammer is demonstrated using gene expression data from the cancer cell line encyclopedia (CCLE), original post-translational modification data collected from lung cancer cells lines by a mass spectrometry approach, and original cytometry by time of flight (CyTOF) single-cell proteomics data from blood. Clustergrammer enables producing interactive web based visualizations for the analysis of diverse biological data.
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Affiliation(s)
- Nicolas F. Fernandez
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, BD2K-LINCS Data Coordination and Integration Center (DCIC), Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Gregory W. Gundersen
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, BD2K-LINCS Data Coordination and Integration Center (DCIC), Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Adeeb Rahman
- Human Immune Monitoring Core, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Mark L. Grimes
- Center for Structural and Functional Neuroscience, University of Montana, Missoula, Montana 59812, USA
| | - Klarisa Rikova
- Cell Signaling Technology Inc., Danvers, Massachusetts 01923, USA
| | - Peter Hornbeck
- Cell Signaling Technology Inc., Danvers, Massachusetts 01923, USA
| | - Avi Ma’ayan
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, BD2K-LINCS Data Coordination and Integration Center (DCIC), Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
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871
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Carter CJ. Genetic, Transcriptome, Proteomic, and Epidemiological Evidence for Blood-Brain Barrier Disruption and Polymicrobial Brain Invasion as Determinant Factors in Alzheimer's Disease. J Alzheimers Dis Rep 2017; 1:125-157. [PMID: 30480234 PMCID: PMC6159731 DOI: 10.3233/adr-170017] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Diverse pathogens are detected in Alzheimer's disease (AD) brains. A bioinformatics survey showed that AD genome-wide association study (GWAS) genes (localized in bone marrow, immune locations and microglia) relate to multiple host/pathogen interactomes (Candida albicans, Cryptococcus neoformans, Bornavirus, Borrelia burgdorferri, cytomegalovirus, Ebola virus, HSV-1, HERV-W, HIV-1, Epstein-Barr, hepatitis C, influenza, Chlamydia pneumoniae, Porphyrymonas gingivalis, Helicobacter pylori, Toxoplasma gondii, Trypanosoma cruzi). These interactomes also relate to the AD hippocampal transcriptome and to plaque or tangle proteins. Upregulated AD hippocampal genes match those upregulated by multiple bacteria, viruses, fungi, or protozoa in immunocompetent cells. AD genes are enriched in GWAS datasets reflecting pathogen diversity, suggesting selection for pathogen resistance, as supported by the old age of AD patients, implying resistance to earlier infections. APOE4 is concentrated in regions of high parasitic burden and protects against childhood tropical infections and hepatitis C. Immune/inflammatory gain of function applies to APOE4, CR1, and TREM2 variants. AD genes are also expressed in the blood-brain barrier (BBB), which is disrupted by AD risk factors (age, alcohol, aluminum, concussion, cerebral hypoperfusion, diabetes, homocysteine, hypercholesterolemia, hypertension, obesity, pesticides, pollution, physical inactivity, sleep disruption, smoking) and by pathogens, directly or via olfactory routes to basal-forebrain BBB control centers. The BBB benefits from statins, NSAIDs, estrogen, melatonin, memantine, and the Mediterranean diet. Polymicrobial involvement is supported by upregulation of bacterial, viral, and fungal sensors/defenders in the AD brain, blood, or cerebrospinal fluid. AD serum amyloid-β autoantibodies may attenuate its antimicrobial effects favoring microbial survival and cerebral invasion leading to activation of neurodestructive immune/inflammatory processes, which may also be augmented by age-related immunosenescence. AD may thus respond to antibiotic, antifungal, or antiviral therapy.
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872
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Rapid Discovery of De Novo Deleterious Mutations in Cattle Enhances the Value of Livestock as Model Species. Sci Rep 2017; 7:11466. [PMID: 28904385 PMCID: PMC5597596 DOI: 10.1038/s41598-017-11523-3] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 08/23/2017] [Indexed: 01/17/2023] Open
Abstract
In humans, the clinical and molecular characterization of sporadic syndromes is often hindered by the small number of patients and the difficulty in developing animal models for severe dominant conditions. Here we show that the availability of large data sets of whole-genome sequences, high-density SNP chip genotypes and extensive recording of phenotype offers an unprecedented opportunity to quickly dissect the genetic architecture of severe dominant conditions in livestock. We report on the identification of seven dominant de novo mutations in CHD7, COL1A1, COL2A1, COPA, and MITF and exploit the structure of cattle populations to describe their clinical consequences and map modifier loci. Moreover, we demonstrate that the emergence of recessive genetic defects can be monitored by detecting de novo deleterious mutations in the genome of bulls used for artificial insemination. These results demonstrate the attractiveness of cattle as a model species in the post genomic era, particularly to confirm the genetic aetiology of isolated clinical case reports in humans.
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873
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Li YE, Xiao M, Shi B, Yang YCT, Wang D, Wang F, Marcia M, Lu ZJ. Identification of high-confidence RNA regulatory elements by combinatorial classification of RNA-protein binding sites. Genome Biol 2017; 18:169. [PMID: 28886744 PMCID: PMC5591525 DOI: 10.1186/s13059-017-1298-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 08/14/2017] [Indexed: 12/20/2022] Open
Abstract
Crosslinking immunoprecipitation sequencing (CLIP-seq) technologies have enabled researchers to characterize transcriptome-wide binding sites of RNA-binding protein (RBP) with high resolution. We apply a soft-clustering method, RBPgroup, to various CLIP-seq datasets to group together RBPs that specifically bind the same RNA sites. Such combinatorial clustering of RBPs helps interpret CLIP-seq data and suggests functional RNA regulatory elements. Furthermore, we validate two RBP–RBP interactions in cell lines. Our approach links proteins and RNA motifs known to possess similar biochemical and cellular properties and can, when used in conjunction with additional experimental data, identify high-confidence RBP groups and their associated RNA regulatory elements.
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Affiliation(s)
- Yang Eric Li
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Mu Xiao
- Life Sciences Institute, Innovation Center for Cell Signaling Network, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Binbin Shi
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Yu-Cheng T Yang
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Dong Wang
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Fei Wang
- Life Sciences Institute, Innovation Center for Cell Signaling Network, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Marco Marcia
- European Molecular Biology Laboratory, Grenoble Outstation, 71 Avenue des Martyrs, Grenoble, 38042, France
| | - Zhi John Lu
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
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874
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Cellular responses to human cytomegalovirus infection: Induction of a mesenchymal-to-epithelial transition (MET) phenotype. Proc Natl Acad Sci U S A 2017; 114:E8244-E8253. [PMID: 28874566 DOI: 10.1073/pnas.1710799114] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Human cytomegalovirus (HCMV) is the prototypical human β-herpes virus. Here we perform a systems analysis of the HCMV host-cell transcriptome, using gene set enrichment analysis (GSEA) as an engine to globally map the host-pathogen interaction across two cell types. Our analysis identified several previously unknown signatures of infection, such as induction of potassium channels and amino acid transporters, derepression of genes marked with histone H3 lysine 27 trimethylation (H3K27me3), and inhibition of genes related to epithelial-to-mesenchymal transition (EMT). The repression of EMT genes was dependent on early viral gene expression and correlated with induction E-cadherin (CDH1) and mesenchymal-to-epithelial transition (MET) genes. Infection of transformed breast carcinoma and glioma stem cells similarly inhibited EMT and induced MET, arguing that HCMV induces an epithelium-like cellular environment during infection.
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875
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Size-based detection of sarcoma circulating tumor cells and cell clusters. Oncotarget 2017; 8:78965-78977. [PMID: 29108279 PMCID: PMC5668012 DOI: 10.18632/oncotarget.20697] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Accepted: 05/29/2017] [Indexed: 01/30/2023] Open
Abstract
Metastatic disease is the most important factor in determining the survival of sarcoma patients. Since sarcoma metastasis is predominantly hematogenous, we hypothesized that detection and quantification of circulating tumor cells (CTCs) could reflect response to therapy and risk of metastatic relapse. We evaluated the presence of CTCs using a novel animal model and in the blood of patients with high grade sarcomas utilizing the CellSieve™ size-based low pressure microfiltration system. Sarcoma CTCs were identified based on antibody staining patterns and nuclear morphology. Additionally, RNA was extracted from the CTCs for molecular analysis including demonstration of an EWS-FLI1 translocation, identification of a previously unrecognized p53 mutation in a patient with Ewing sarcoma, and single cell RNA sequencing of CTC from a child with alveolar rhabdomyosarcoma. In mouse xenograft models, the presence of CTC correlates with disease burden and with clinically silent metastases. In human patients, CTCs were readily detected at diagnosis, decreased with successful treatment, and were detectable in the blood of patients with no radiographic evidence of disease prior to the development of overt metastasis. Although evaluation of CTC is established in the care of patients with carcinomas, this technology has yet to be effectively applied to the evaluation and treatment of sarcoma patients. Our work demonstrates that the CellSieve™ microfiltration system can be used to study the biology of CTC in both mouse models and human sarcoma patients, with the potential for application to the monitoring of disease response and prediction of metastatic relapse.
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876
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Naidoo P, Naidoo RN, Ramkaran P, Asharam K, Chuturgoon AA. The Tyr113His T/C rs1051740 and 'very slow' phenotype of the EPHX1 gene alters miR-26b-5p and miR-1207-5p expression in pregnancy. Gene 2017; 633:71-81. [PMID: 28789952 DOI: 10.1016/j.gene.2017.07.080] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Revised: 06/29/2017] [Accepted: 07/31/2017] [Indexed: 12/11/2022]
Abstract
BACKGROUND Environmental insults and microsomal epoxide hydrolase 1 (EPHX1) single nucleotide polymorphisms (SNPs), Tyr113His T/C rs1051740 and His139Arg A/G rs2234922, aberrantly alters microRNA (miR) expression and are linked to low birthweights (LBW). OBJECTIVES To investigate the interplay between pollution, EPHX1 SNPs and miRs during pregnancy and associated LBW outcomes. METHODS South African pregnant women (n=241) were recruited in the MACE birth cohort study in Durban, a city with high levels of industry and traffic related pollutants. EPHX1 SNPs were genotyped using PCR-RFLP and grouped into their respective phenotypes, i.e. normal (N), slow (S), very slow (VS) and fast (F). EPHX1, miR-26b-5p, miR-193b-3p and miR-1207-5p expression were determined using quantitative PCR. RESULTS Mothers with the Tyr113His SNP had low iron levels [TT vs. TC+CC: mean difference (MD)=0.67g/dl; p=0.0167], LBW [TT vs. TC+CC: MD=189.30g; p=0.0067], and low EPHX1 expression; p<0.0001. miR-26b-5p and miR-1207-5p expression were significantly higher in the CC genotypes compared to TT+TC groups; p<0.0001. The opposite trend occurred for miR-193b-3p; p=0.0045. Mothers with the VS phenotype had low iron levels [N vs. VS and VS vs. F: MD=2.03 and -1.96g/dl; p=0.0021, respectively], decreased gestational age [VS vs. F: MD=-2.14weeks; p=0.0051, respectively], and LBW [N vs. VS, VS vs. F and S vs. VS: MD=1000, -940.30 and 968.80g; p<0.0001, respectively]; F phenotype had the highest EPHX1 expression [N vs. F, VS vs. F and S vs. F: MD=-1.067, -1.854 and -1.379; p=0.0002, respectively]; and N phenotype had low miR-26b-5p [N vs. VS: MD=-0.6100; p=0.0159] and miR-1207-5p [N vs. VS and VS vs. F: MD=-0.834 and 1.103; p=0.0007, respectively] expression. miR-193b-3p expression between phenotypes remained unchanged. CONCLUSION The Tyr113His T/C variant of rs1051740 and VS phenotype alters EPHX1, miR-26b-5p and miR-1207-5p expression, and contributes towards low blood iron levels and LBW.
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Affiliation(s)
- Pragalathan Naidoo
- Discipline of Medical Biochemistry and Chemical Pathology, Howard College Campus, University of KwaZulu-Natal, Durban, South Africa
| | - Rajen N Naidoo
- Discipline of Occupational and Environmental Health, University of KwaZulu-Natal, Durban, South Africa
| | - Prithiksha Ramkaran
- Discipline of Medical Biochemistry and Chemical Pathology, Howard College Campus, University of KwaZulu-Natal, Durban, South Africa
| | - Kareshma Asharam
- Discipline of Occupational and Environmental Health, University of KwaZulu-Natal, Durban, South Africa
| | - Anil A Chuturgoon
- Discipline of Medical Biochemistry and Chemical Pathology, Howard College Campus, University of KwaZulu-Natal, Durban, South Africa.
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877
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Necroptosis activation in Alzheimer's disease. Nat Neurosci 2017; 20:1236-1246. [PMID: 28758999 DOI: 10.1038/nn.4608] [Citation(s) in RCA: 278] [Impact Index Per Article: 39.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Accepted: 06/21/2017] [Indexed: 12/16/2022]
Abstract
Alzheimer's disease (AD) is characterized by severe neuronal loss; however, the mechanisms by which neurons die remain elusive. Necroptosis, a programmed form of necrosis, is executed by the mixed lineage kinase domain-like (MLKL) protein, which is triggered by receptor-interactive protein kinases (RIPK) 1 and 3. We found that necroptosis was activated in postmortem human AD brains, positively correlated with Braak stage, and inversely correlated with brain weight and cognitive scores. In addition, we found that the set of genes regulated by RIPK1 overlapped significantly with multiple independent AD transcriptomic signatures, indicating that RIPK1 activity could explain a substantial portion of transcriptomic changes in AD. Furthermore, we observed that lowering necroptosis activation reduced cell loss in a mouse model of AD. We anticipate that our findings will spur a new area of research in the AD field focused on developing new therapeutic strategies aimed at blocking its activation.
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878
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Ma T, Zhang A. Reconstructing context-specific gene regulatory network and identifying modules and network rewiring through data integration. Methods 2017; 124:36-45. [PMID: 28529066 DOI: 10.1016/j.ymeth.2017.05.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2017] [Accepted: 05/05/2017] [Indexed: 12/01/2022] Open
Abstract
Reconstructing context-specific transcriptional regulatory network is crucial for deciphering principles of regulatory mechanisms underlying various conditions. Recently studies that reconstructed transcriptional networks have focused on individual organisms or cell types and relied on data repositories of context-free regulatory relationships. Here we present a comprehensive framework to systematically derive putative regulator-target pairs in any given context by integrating context-specific transcriptional profiling and public data repositories of gene regulatory networks. Moreover, our framework can identify core regulatory modules and signature genes underlying global regulatory circuitry, and detect network rewiring and core rewired modules in different contexts by considering gene modules and edge (gene interaction) modules collaboratively. We applied our methods to analyzing Autism RNA-seq experiment data and produced biologically meaningful results. In particular, all 11 hub genes in a predicted rewired autistic regulatory subnetwork have been linked to autism based on literature review. The predicted rewired autistic regulatory network may shed some new insight into disease mechanism.
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Affiliation(s)
- Tianle Ma
- Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY 14260-2500, United States.
| | - Aidong Zhang
- Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY 14260-2500, United States.
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879
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Lee BJ, Marchionni L, Andrews CE, Norris AL, Nucifora LG, Wu YC, Wright RA, Pevsner J, Ross CA, Margolis RL, Sawa A, Nucifora FC. Analysis of differential gene expression mediated by clozapine in human postmortem brains. Schizophr Res 2017; 185:58-66. [PMID: 28038920 PMCID: PMC6541388 DOI: 10.1016/j.schres.2016.12.017] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Revised: 12/12/2016] [Accepted: 12/15/2016] [Indexed: 12/11/2022]
Abstract
Clozapine is the only medication indicated for treating refractory schizophrenia, due to its superior efficacy among all antipsychotic agents, but its mechanism of action is poorly understood. To date, no studies of human postmortem brain have characterized the gene expression response to clozapine. Therefore, we addressed this question by analyzing expression data extracted from published microarray studies involving brains of patients on antipsychotic therapy. We first performed a systematic review and identified four microarray studies of postmortem brains from antipsychotic-treated patients, then extracted the expression data. We then performed generalized linear model analysis on each study separately, and identified the genes differentially expressed in response to clozapine compared to other atypical antipsychotic medications, as well as their associated canonical pathways. We also found a number of genes common to all four studies that we analyzed: GCLM, ZNF652, and GYPC. In addition, pathway analysis highlighted the following processes in all four studies: clathrin-mediated endocytosis, SAPK/JNK signaling, 3-phosphoinositide synthesis, and paxillin signaling. Our analysis yielded the first comprehensive compendium of genes and pathways differentially expressed upon clozapine treatment in the human brain, which may provide insight into the mechanism and unique efficacy of clozapine, as well as the pathophysiology of schizophrenia.
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Affiliation(s)
- Brian J Lee
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 N. Wolfe St., Baltimore, MD 21287, USA; Cellular and Molecular Medicine Program, Johns Hopkins University School of Medicine, 1830 E. Monument St., Baltimore, MD 21205, USA
| | - Luigi Marchionni
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, 401 N. Broadway, Baltimore, MD 21287, USA
| | - Carrie E Andrews
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 N. Wolfe St., Baltimore, MD 21287, USA
| | - Alexis L Norris
- Department of Neuroscience, Johns Hopkins University School of Medicine, 725 N. Wolfe St., Baltimore, MD 21205, USA; Department of Neurology, Kennedy Krieger Institute, Johns Hopkins University School of Medicine, 707 N. Broadway, Baltimore, MD 21205, USA
| | - Leslie G Nucifora
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 N. Wolfe St., Baltimore, MD 21287, USA
| | - Yeewen Candace Wu
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 N. Wolfe St., Baltimore, MD 21287, USA
| | - Robert A Wright
- William H. Welch Medical Library, Johns Hopkins University, 1900 E. Monument St., Baltimore, MD 21205, USA
| | - Jonathan Pevsner
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 N. Wolfe St., Baltimore, MD 21287, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, 725 N. Wolfe St., Baltimore, MD 21205, USA; Department of Neurology, Kennedy Krieger Institute, Johns Hopkins University School of Medicine, 707 N. Broadway, Baltimore, MD 21205, USA
| | - Christopher A Ross
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 N. Wolfe St., Baltimore, MD 21287, USA; Cellular and Molecular Medicine Program, Johns Hopkins University School of Medicine, 1830 E. Monument St., Baltimore, MD 21205, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, 725 N. Wolfe St., Baltimore, MD 21205, USA
| | - Russell L Margolis
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 N. Wolfe St., Baltimore, MD 21287, USA; Cellular and Molecular Medicine Program, Johns Hopkins University School of Medicine, 1830 E. Monument St., Baltimore, MD 21205, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, 725 N. Wolfe St., Baltimore, MD 21205, USA
| | - Akira Sawa
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 N. Wolfe St., Baltimore, MD 21287, USA; Cellular and Molecular Medicine Program, Johns Hopkins University School of Medicine, 1830 E. Monument St., Baltimore, MD 21205, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, 725 N. Wolfe St., Baltimore, MD 21205, USA
| | - Frederick C Nucifora
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 N. Wolfe St., Baltimore, MD 21287, USA.
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880
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Jagodnik KM, Koplev S, Jenkins SL, Ohno-Machado L, Paten B, Schurer SC, Dumontier M, Verborgh R, Bui A, Ping P, McKenna NJ, Madduri R, Pillai A, Ma'ayan A. Developing a framework for digital objects in the Big Data to Knowledge (BD2K) commons: Report from the Commons Framework Pilots workshop. J Biomed Inform 2017; 71:49-57. [PMID: 28501646 DOI: 10.1016/j.jbi.2017.05.006] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Revised: 05/01/2017] [Accepted: 05/08/2017] [Indexed: 12/11/2022]
Abstract
The volume and diversity of data in biomedical research have been rapidly increasing in recent years. While such data hold significant promise for accelerating discovery, their use entails many challenges including: the need for adequate computational infrastructure, secure processes for data sharing and access, tools that allow researchers to find and integrate diverse datasets, and standardized methods of analysis. These are just some elements of a complex ecosystem that needs to be built to support the rapid accumulation of these data. The NIH Big Data to Knowledge (BD2K) initiative aims to facilitate digitally enabled biomedical research. Within the BD2K framework, the Commons initiative is intended to establish a virtual environment that will facilitate the use, interoperability, and discoverability of shared digital objects used for research. The BD2K Commons Framework Pilots Working Group (CFPWG) was established to clarify goals and work on pilot projects that address existing gaps toward realizing the vision of the BD2K Commons. This report reviews highlights from a two-day meeting involving the BD2K CFPWG to provide insights on trends and considerations in advancing Big Data science for biomedical research in the United States.
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Affiliation(s)
- Kathleen M Jagodnik
- Department of Pharmacological Sciences, BD2K-LINCS Data Coordination and Integration Center, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1215, New York, NY 10029, USA
| | - Simon Koplev
- Department of Pharmacological Sciences, BD2K-LINCS Data Coordination and Integration Center, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1215, New York, NY 10029, USA
| | - Sherry L Jenkins
- Department of Pharmacological Sciences, BD2K-LINCS Data Coordination and Integration Center, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1215, New York, NY 10029, USA
| | - Lucila Ohno-Machado
- Health System Department of Biomedical Informatics, University of California San Diego, 9500 Gilman Dr., La Jolla, CA 92083, USA; Health Services Research, San Diego Veterans Administration Health System, San Diego, CA 92083, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95060, USA
| | - Stephan C Schurer
- Department of Molecular and Cellular Pharmacology, University of Miami, 331461120 NW 14th Street, CRB 650 (M-857), Miami, FL 33136, USA
| | - Michel Dumontier
- Institute for Data Science, Universiteit Maastricht, Minderbroedersberg 4-6, 6211 LK Maastricht, Netherlands
| | - Ruben Verborgh
- Ghent University - iMinds Research Foundation Flanders, St. Pietersnieuwstraat 33, 9000 Gent, Belgium
| | - Alex Bui
- Department of Radiological Sciences, UCLA School of Medicine, Los Angeles, CA 90095, USA; Department of Bioengineering, UCLA Henri Samueli School of Engineering, Los Angeles, CA 90095, USA
| | - Peipei Ping
- Departments of Physiology, Medicine, and Bioinformatics, UCLA School of Medicine, Los Angeles, CA 90095, USA
| | - Neil J McKenna
- Department of Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Ravi Madduri
- Department of Mathematics and Computer Science, Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439, USA
| | - Ajay Pillai
- Division of Genome Sciences, National Human Genome Research Institute, National Institutes of Health, 31 Center Drive, MSC 2152, 9000 Rockville Pike, Bethesda, MD 20892, USA
| | - Avi Ma'ayan
- Department of Pharmacological Sciences, BD2K-LINCS Data Coordination and Integration Center, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1215, New York, NY 10029, USA.
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881
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Bui AAT, Van Horn JD. Envisioning the future of 'big data' biomedicine. J Biomed Inform 2017; 69:115-117. [PMID: 28366789 PMCID: PMC5613673 DOI: 10.1016/j.jbi.2017.03.017] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Revised: 03/17/2017] [Accepted: 03/29/2017] [Indexed: 01/23/2023]
Abstract
Through the increasing availability of more efficient data collection procedures, biomedical scientists are now confronting ever larger sets of data, often finding themselves struggling to process and interpret what they have gathered. This, while still more data continues to accumulate. This torrent of biomedical information necessitates creative thinking about how the data are being generated, how they might be best managed, analyzed, and eventually how they can be transformed into further scientific understanding for improving patient care. Recognizing this as a major challenge, the National Institutes of Health (NIH) has spearheaded the "Big Data to Knowledge" (BD2K) program - the agency's most ambitious biomedical informatics effort ever undertaken to date. In this commentary, we describe how the NIH has taken on "big data" science head-on, how a consortium of leading research centers are developing the means for handling large-scale data, and how such activities are being marshalled for the training of a new generation of biomedical data scientists. All in all, the NIH BD2K program seeks to position data science at the heart of 21st Century biomedical research.
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Affiliation(s)
- Alex A T Bui
- BD2K Centers Coordinating Center (BD2K CCC), University of California, Los Angeles, Los Angeles, CA, USA. http://www.bd2kccc.org
| | - John Darrell Van Horn
- BD2K Training Coordinating Center (BD2K TCC), University of Southern California, Los Angeles, CA, USA. http://www.bigdatau.org
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882
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Wright C, Shin JH, Rajpurohit A, Deep-Soboslay A, Collado-Torres L, Brandon NJ, Hyde TM, Kleinman JE, Jaffe AE, Cross AJ, Weinberger DR. Altered expression of histamine signaling genes in autism spectrum disorder. Transl Psychiatry 2017; 7:e1126. [PMID: 28485729 PMCID: PMC5534955 DOI: 10.1038/tp.2017.87] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Revised: 03/17/2017] [Accepted: 03/21/2017] [Indexed: 12/18/2022] Open
Abstract
The histaminergic system (HS) has a critical role in cognition, sleep and other behaviors. Although not well studied in autism spectrum disorder (ASD), the HS is implicated in many neurological disorders, some of which share comorbidity with ASD, including Tourette syndrome (TS). Preliminary studies suggest that antagonism of histamine receptors 1-3 reduces symptoms and specific behaviors in ASD patients and relevant animal models. In addition, the HS mediates neuroinflammation, which may be heightened in ASD. Together, this suggests that the HS may also be altered in ASD. Using RNA sequencing (RNA-seq), we investigated genome-wide expression, as well as a focused gene set analysis of key HS genes (HDC, HNMT, HRH1, HRH2, HRH3 and HRH4) in postmortem dorsolateral prefrontal cortex (DLPFC) initially in 13 subjects with ASD and 39 matched controls. At the genome level, eight transcripts were differentially expressed (false discovery rate <0.05), six of which were small nucleolar RNAs (snoRNAs). There was no significant diagnosis effect on any of the individual HS genes but expression of the gene set of HNMT, HRH1, HRH2 and HRH3 was significantly altered. Curated HS gene sets were also significantly differentially expressed. Differential expression analysis of these gene sets in an independent RNA-seq ASD data set from DLPFC of 47 additional subjects confirmed these findings. Understanding the physiological relevance of an altered HS may suggest new therapeutic options for the treatment of ASD.
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Affiliation(s)
- C Wright
- Lieber Institute for Brain Development, Clinical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA,AstraZeneca Postdoc Program, Innovative Medicines and Early Development, Waltham, MA, USA
| | - J H Shin
- Lieber Institute for Brain Development, Clinical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - A Rajpurohit
- Lieber Institute for Brain Development, Clinical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - A Deep-Soboslay
- Lieber Institute for Brain Development, Clinical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - L Collado-Torres
- Lieber Institute for Brain Development, Clinical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - N J Brandon
- AstraZeneca Neuroscience, Innovative Medicines and Early Development, Waltham, MA, USA
| | - T M Hyde
- Lieber Institute for Brain Development, Clinical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA,Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA,Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - J E Kleinman
- Lieber Institute for Brain Development, Clinical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA,Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - A E Jaffe
- Lieber Institute for Brain Development, Clinical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA,Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA,Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - A J Cross
- AstraZeneca Neuroscience, Innovative Medicines and Early Development, Waltham, MA, USA
| | - D R Weinberger
- Lieber Institute for Brain Development, Clinical Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA,Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA,Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA,The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA,McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA,Lieber Institute for Brain Development, Clinical Sciences, Johns Hopkins School of Medicine, Johns Hopkins Medical Campus, 855 North Wolfe Street, Suite 300, 3rd Floor, Baltimore, MD 21205, USA. E-mail:
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883
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Lee HS, Jang HJ, Shah R, Yoon D, Hamaji M, Wald O, Lee JS, Sugarbaker DJ, Burt BM. Genomic Analysis of Thymic Epithelial Tumors Identifies Novel Subtypes Associated with Distinct Clinical Features. Clin Cancer Res 2017; 23:4855-4864. [PMID: 28400429 DOI: 10.1158/1078-0432.ccr-17-0066] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Revised: 01/09/2017] [Accepted: 04/06/2017] [Indexed: 12/11/2022]
Abstract
Purpose: To reconcile the heterogeneity of thymic epithelial tumors (TET) and gain deeper understanding of the molecular determinants of TETs, we set out to establish a clinically relevant molecular classification system for these tumors.Experimental Design: Molecular subgrouping of TETs was performed in 120 patients from The Cancer Genome Atlas using a multidimensional approach incorporating analyses of DNA mutations, mRNA expression, and somatic copy number alterations (SCNA), and validated in two independent cohorts.Results: Four distinct molecular subtypes of TETs were identified. The most commonly identified gene mutation was a missense mutation in General Transcription Factor II-I (GTF2I group), which was present in 38% of patients. The next group was identified by unsupervised mRNA clustering of GTF2I wild-type tumors and represented TETs enriched in expression of genes associated with T-cell signaling (TS group; 33%). The remaining two groups were distinguished by their degree of chromosomal stability (CS group; 8%) or instability (CIN group; 21%) based upon SCNA analyses. Disease-free survival and overall survival were favorable in the GTF2I group and unfavorable in the CIN group. These molecular subgroups were associated with TET histology and clinical features including disease-free survival. Finally, we demonstrate high expression of PD1 mRNA and correlation of PD1 and CD8A in the TS subgroup.Conclusions: Molecular subtyping of TETs is associated with disease-free and overall survival. Classification of TETs by a molecular framework could aid in the refinement of staging and in the discovery and development of rational treatment options for patients with TETs. Clin Cancer Res; 23(16); 4855-64. ©2017 AACR.
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Affiliation(s)
- Hyun-Sung Lee
- Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Hee-Jin Jang
- Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Rohan Shah
- Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - David Yoon
- Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Masatsugu Hamaji
- Department of Thoracic Surgery, Kyoto University Hospital, Kyoto, Japan
| | - Ori Wald
- Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Ju-Seog Lee
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - David J Sugarbaker
- Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Bryan M Burt
- Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.
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884
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Malhotra AG, Jha M, Singh S, Pandey KM. Construction of a Comprehensive Protein-Protein Interaction Map for Vitiligo Disease to Identify Key Regulatory Elements: A Systemic Approach. Interdiscip Sci 2017; 10:500-514. [PMID: 28290051 DOI: 10.1007/s12539-017-0213-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 12/09/2016] [Accepted: 12/29/2016] [Indexed: 12/14/2022]
Abstract
Vitiligo is an idiopathic disorder characterized by depigmented patches on the skin due to progressive loss of melanocytes. Several genetic, immunological, and pathophysiological investigations have established vitiligo as a polygenetic disorder with multifactorial etiology. However, no definite model explaining the interplay between these causative factors has been established hitherto. Therefore, we studied the disorder at the system level to identify the key proteins involved by exploring their molecular connectivity in terms of topological parameters. The existing research data helped us in collating 215 proteins involved in vitiligo onset or progression. Interaction study of these proteins leads to a comprehensive vitiligo map with 4845 protein nodes linked with 107,416 edges. Based on centrality measures, a backbone network with 500 nodes has been derived. This has presented a clear overview of the proteins and processes involved and the crosstalk between them. Clustering backbone proteins revealed densely connected regions inferring major molecular interaction modules essential for vitiligo. Finally, a list of top order proteins that play a key role in the disease pathomechanism has been formulated. This includes SUMO2, ESR1, COPS5, MYC, SMAD3, and Cullin proteins. While this list is in fair agreement with the available literature, it also introduces new candidate proteins that can be further explored. A subnetwork of 64 vitiligo core proteins was built by analyzing the backbone and seed protein networks. Our finding suggests that the topology, along with functional clustering, provides a deep insight into the behavior of proteins. This in turn aids in the illustration of disease condition and discovery of significant proteins involved in vitiligo.
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Affiliation(s)
- Anvita Gupta Malhotra
- Department of Biological Science and Engineering, Maulana Azad National Institute of Technology (MANIT), Bhopal, 462003, India
| | - Mohit Jha
- Department of Biological Science and Engineering, Maulana Azad National Institute of Technology (MANIT), Bhopal, 462003, India
| | - Sudha Singh
- Department of Biological Science and Engineering, Maulana Azad National Institute of Technology (MANIT), Bhopal, 462003, India
| | - Khushhali M Pandey
- Department of Biological Science and Engineering, Maulana Azad National Institute of Technology (MANIT), Bhopal, 462003, India.
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885
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MAP7 Regulates Axon Collateral Branch Development in Dorsal Root Ganglion Neurons. J Neurosci 2017; 37:1648-1661. [PMID: 28069923 DOI: 10.1523/jneurosci.3260-16.2017] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 12/27/2016] [Accepted: 01/04/2017] [Indexed: 01/26/2023] Open
Abstract
Collateral branches from axons are key components of functional neural circuits that allow neurons to connect with multiple synaptic targets. Like axon growth and guidance, formation of collateral branches depends on the regulation of microtubules, but how such regulation is coordinated to ensure proper circuit development is not known. Based on microarray analysis, we have identified a role for microtubule-associated protein 7 (MAP7) during collateral branch development of dorsal root ganglion (DRG) sensory neurons. We show that MAP7 is expressed at the onset of collateral branch formation. Perturbation of its expression by overexpression or shRNA knockdown alters axon branching in cultured DRG neurons. Localization and time-lapse imaging analysis reveals that MAP7 is enriched at branch points and colocalizes with stable microtubules, but enters the new branch with a delay, suggesting a role in branch maturation. We have also investigated a spontaneous mutant mouse that expresses a truncated MAP7 and found a gain-of-function phenotype both in vitro and in vivo Further domain analysis suggests that the amino half of MAP7 is responsible for branch formation, suggesting a mechanism that is independent of its known interaction with kinesin. Moreover, this mouse exhibits increased pain sensitivity, a phenotype that is consistent with increased collateral branch formation. Therefore, our study not only uncovers the first neuronal function of MAP7, but also demonstrates the importance of proper microtubule regulation in neural circuit development. Furthermore, our data provide new insights into microtubule regulation during axonal morphogenesis and may shed light on MAP7 function in neurological disorders.SIGNIFICANCE STATEMENT Neurons communicate with multiple targets by forming axonal branches. In search of intrinsic factors that control collateral branch development, we identified a role for microtubule-associated protein 7 (MAP7) in dorsal root ganglion sensory neurons. We show that MAP7 expression is developmentally regulated and perturbation of this expression alters branch formation. Cell biological analysis indicates that MAP7 promotes branch maturation. Analysis of a spontaneous mouse mutant suggests a molecular mechanism for branch regulation and the potential influence of collateral branches on pain sensitivity. Our studies thus establish the first neuronal function of MAP7 and demonstrate its role in branch morphogenesis and neural circuit function. These findings may help in our understanding of the contribution of MAP7 to neurological disorders and nerve regeneration.
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886
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Dev A, Asch R, Jachimowicz E, Rainville N, Johnson A, Greenfest-Allen E, Wojchowski DM. Governing roles for Trib3 pseudokinase during stress erythropoiesis. Exp Hematol 2017; 49:48-55.e5. [PMID: 28062363 DOI: 10.1016/j.exphem.2016.12.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Revised: 12/21/2016] [Accepted: 12/27/2016] [Indexed: 01/19/2023]
Abstract
In response to anemia, the heightened production of erythropoietin (EPO) can sharply promote erythroid progenitor cell (EPC) formation. Specific mediators of such EPO- accelerated erythropoiesis, however, are not well understood. Presently, we first report that the expression of Trib3 in adult bone marrow EPCs in vivo is nominal at steady state, but strongly activated on EPO challenge. In a knockout mouse model, Trib3 disruption modestly increased steady-state erythrocyte numbers and decreased mean corpuscular volume. Following 5-fluorouracil myeloablation, however, rebound red blood cell production and hemoglobin levels were substantially (and selectively) compromised in Trib3-/- mice versus Trib3+/+ congenic controls. Erythrocytes from 5-fluorouracil-treated Trib3-/- mice additionally were more prone to lysis and exhibited elevated peroxide-induced reactive oxygen species. Ex vivo, the development of CD71posTer119pos erythroblasts from Trib3-/- bone marrow progenitors was attenuated, and this was associated with heightened EPO-dependent Erk1/2 activation and moderately increased Akt activation. For developmentally staged EPCs, gene profiling provided further initial insight into candidate mediators of EPO-induced Trib3 gene expression, including Cebp-beta, Atf4, Egr-1, and Nab1. Overall, Trib3 is indicated to act as a novel EPC-intrinsic governor of stress erythropoiesis.
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Affiliation(s)
- Arvind Dev
- Molecular Medicine Division, Maine Medical Center Research Institute, 81 Research Drive, Scarborough, ME
| | - Ruth Asch
- Molecular Medicine Division, Maine Medical Center Research Institute, 81 Research Drive, Scarborough, ME
| | - Edward Jachimowicz
- Molecular Medicine Division, Maine Medical Center Research Institute, 81 Research Drive, Scarborough, ME
| | - Nicole Rainville
- Molecular Medicine Division, Maine Medical Center Research Institute, 81 Research Drive, Scarborough, ME
| | - Ashley Johnson
- Molecular Medicine Division, Maine Medical Center Research Institute, 81 Research Drive, Scarborough, ME
| | - Emily Greenfest-Allen
- Computational Biology and Informatics Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Don M Wojchowski
- Molecular Medicine Division, Maine Medical Center Research Institute, 81 Research Drive, Scarborough, ME; Department of Medicine, Tufts University Medical Center, Boston, MA.
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887
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Nguyen DT, Mathias S, Bologa C, Brunak S, Fernandez N, Gaulton A, Hersey A, Holmes J, Jensen LJ, Karlsson A, Liu G, Ma'ayan A, Mandava G, Mani S, Mehta S, Overington J, Patel J, Rouillard AD, Schürer S, Sheils T, Simeonov A, Sklar LA, Southall N, Ursu O, Vidovic D, Waller A, Yang J, Jadhav A, Oprea TI, Guha R. Pharos: Collating protein information to shed light on the druggable genome. Nucleic Acids Res 2017; 45:D995-D1002. [PMID: 27903890 PMCID: PMC5210555 DOI: 10.1093/nar/gkw1072] [Citation(s) in RCA: 181] [Impact Index Per Article: 25.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Revised: 10/17/2016] [Accepted: 10/24/2016] [Indexed: 01/12/2023] Open
Abstract
The 'druggable genome' encompasses several protein families, but only a subset of targets within them have attracted significant research attention and thus have information about them publicly available. The Illuminating the Druggable Genome (IDG) program was initiated in 2014, has the goal of developing experimental techniques and a Knowledge Management Center (KMC) that would collect and organize information about protein targets from four families, representing the most common druggable targets with an emphasis on understudied proteins. Here, we describe two resources developed by the KMC: the Target Central Resource Database (TCRD) which collates many heterogeneous gene/protein datasets and Pharos (https://pharos.nih.gov), a multimodal web interface that presents the data from TCRD. We briefly describe the types and sources of data considered by the KMC and then highlight features of the Pharos interface designed to enable intuitive access to the IDG knowledgebase. The aim of Pharos is to encourage 'serendipitous browsing', whereby related, relevant information is made easily discoverable. We conclude by describing two use cases that highlight the utility of Pharos and TCRD.
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Affiliation(s)
- Dac-Trung Nguyen
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Stephen Mathias
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
| | - Cristian Bologa
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
| | - Soren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Nicolas Fernandez
- Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Anna Gaulton
- European Molecular Biology Laboratory - European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Anne Hersey
- European Molecular Biology Laboratory - European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Jayme Holmes
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
| | - Lars Juhl Jensen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | | | - Guixia Liu
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
- East China University of Science and Technology, Dept. Pharmaceutical Sciences, Shanghai, China
| | - Avi Ma'ayan
- Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Geetha Mandava
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Subramani Mani
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
| | - Saurabh Mehta
- Center for Computational Science, University of Miami, Coral Gables, FL 33146, USA
- Department of Applied Chemistry, Delhi Technological University, Delhi 110042, India
| | | | - Juhee Patel
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
- BA/MD Program, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
| | - Andrew D Rouillard
- Mount Sinai Center for Bioinformatics, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA
| | - Stephan Schürer
- Center for Computational Science, University of Miami, Coral Gables, FL 33146, USA
- Department of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Timothy Sheils
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Anton Simeonov
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Larry A Sklar
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
- Center for Molecular Discovery, University of New Mexico Cancer Center, University of New Mexico, Albuquerque, NM 87131, USA
| | - Noel Southall
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Oleg Ursu
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
| | - Dusica Vidovic
- Center for Computational Science, University of Miami, Coral Gables, FL 33146, USA
- Department of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Anna Waller
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
- Center for Molecular Discovery, University of New Mexico Cancer Center, University of New Mexico, Albuquerque, NM 87131, USA
| | - Jeremy Yang
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
| | - Ajit Jadhav
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Tudor I Oprea
- Translational Informatics Division, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
| | - Rajarshi Guha
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
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888
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Mittermayr S, Lê GN, Clarke C, Millán Martín S, Larkin AM, O’Gorman P, Bones J. Polyclonal Immunoglobulin G N-Glycosylation in the Pathogenesis of Plasma Cell Disorders. J Proteome Res 2016; 16:748-762. [DOI: 10.1021/acs.jproteome.6b00768] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Stefan Mittermayr
- NIBRT−The
National Institute for Bioprocessing Research and Training, Foster Avenue, Mount Merrion, Blackrock Co., Dublin A94 X099, Ireland
| | - Giao N. Lê
- NIBRT−The
National Institute for Bioprocessing Research and Training, Foster Avenue, Mount Merrion, Blackrock Co., Dublin A94 X099, Ireland
- Department
of Haematology, Mater Misericordiae University Hospital, Dublin D07 R2WY, Ireland
- National
Institute for Cellular Biotechnology, Dublin City University, Dublin D09 NR58, Ireland
| | - Colin Clarke
- NIBRT−The
National Institute for Bioprocessing Research and Training, Foster Avenue, Mount Merrion, Blackrock Co., Dublin A94 X099, Ireland
| | - Silvia Millán Martín
- NIBRT−The
National Institute for Bioprocessing Research and Training, Foster Avenue, Mount Merrion, Blackrock Co., Dublin A94 X099, Ireland
| | - Anne-Marie Larkin
- National
Institute for Cellular Biotechnology, Dublin City University, Dublin D09 NR58, Ireland
| | - Peter O’Gorman
- Department
of Haematology, Mater Misericordiae University Hospital, Dublin D07 R2WY, Ireland
| | - Jonathan Bones
- NIBRT−The
National Institute for Bioprocessing Research and Training, Foster Avenue, Mount Merrion, Blackrock Co., Dublin A94 X099, Ireland
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889
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Koscielny G, An P, Carvalho-Silva D, Cham JA, Fumis L, Gasparyan R, Hasan S, Karamanis N, Maguire M, Papa E, Pierleoni A, Pignatelli M, Platt T, Rowland F, Wankar P, Bento AP, Burdett T, Fabregat A, Forbes S, Gaulton A, Gonzalez CY, Hermjakob H, Hersey A, Jupe S, Kafkas Ş, Keays M, Leroy C, Lopez FJ, Magarinos MP, Malone J, McEntyre J, Munoz-Pomer Fuentes A, O'Donovan C, Papatheodorou I, Parkinson H, Palka B, Paschall J, Petryszak R, Pratanwanich N, Sarntivijal S, Saunders G, Sidiropoulos K, Smith T, Sondka Z, Stegle O, Tang YA, Turner E, Vaughan B, Vrousgou O, Watkins X, Martin MJ, Sanseau P, Vamathevan J, Birney E, Barrett J, Dunham I. Open Targets: a platform for therapeutic target identification and validation. Nucleic Acids Res 2016; 45:D985-D994. [PMID: 27899665 PMCID: PMC5210543 DOI: 10.1093/nar/gkw1055] [Citation(s) in RCA: 281] [Impact Index Per Article: 35.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2016] [Revised: 10/19/2016] [Accepted: 11/03/2016] [Indexed: 01/16/2023] Open
Abstract
We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.
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Affiliation(s)
- Gautier Koscielny
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK .,GSK, Medicines Research Center, Gunnels Wood Road, Stevenage, SG1 2NY, UK
| | - Peter An
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,Biogen, Cambridge, MA 02142, USA
| | - Denise Carvalho-Silva
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Jennifer A Cham
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Luca Fumis
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Rippa Gasparyan
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,Biogen, Cambridge, MA 02142, USA
| | - Samiul Hasan
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,GSK, Medicines Research Center, Gunnels Wood Road, Stevenage, SG1 2NY, UK
| | - Nikiforos Karamanis
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Michael Maguire
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Eliseo Papa
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,Biogen, Cambridge, MA 02142, USA
| | - Andrea Pierleoni
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Miguel Pignatelli
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Theo Platt
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,Biogen, Cambridge, MA 02142, USA
| | - Francis Rowland
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Priyanka Wankar
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,Biogen, Cambridge, MA 02142, USA
| | - A Patrícia Bento
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Tony Burdett
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Antonio Fabregat
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Simon Forbes
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Anna Gaulton
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Cristina Yenyxe Gonzalez
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Henning Hermjakob
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,National Center for Protein Research, No. 38, Life Science Park Road, Changping District, 102206 Beijing, China
| | - Anne Hersey
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Steven Jupe
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Şenay Kafkas
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Maria Keays
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Catherine Leroy
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Francisco-Javier Lopez
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Maria Paula Magarinos
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - James Malone
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Johanna McEntyre
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Alfonso Munoz-Pomer Fuentes
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Claire O'Donovan
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Irene Papatheodorou
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Helen Parkinson
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Barbara Palka
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Justin Paschall
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Robert Petryszak
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Naruemon Pratanwanich
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Sirarat Sarntivijal
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Gary Saunders
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Konstantinos Sidiropoulos
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Thomas Smith
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Zbyslaw Sondka
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Oliver Stegle
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Y Amy Tang
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Edward Turner
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Brendan Vaughan
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Olga Vrousgou
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Xavier Watkins
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Maria-Jesus Martin
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Philippe Sanseau
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,GSK, Medicines Research Center, Gunnels Wood Road, Stevenage, SG1 2NY, UK
| | - Jessica Vamathevan
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Ewan Birney
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Jeffrey Barrett
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.,Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Ian Dunham
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK .,European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
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