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Sebastiano MR, Hadano S, Cesca F, Ermondi G. Preclinical alternative drug discovery programs for monogenic rare diseases. Should small molecules or gene therapy be used? The case of hereditary spastic paraplegias. Drug Discov Today 2024; 29:104138. [PMID: 39154774 DOI: 10.1016/j.drudis.2024.104138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 06/28/2024] [Accepted: 08/13/2024] [Indexed: 08/20/2024]
Abstract
Patients diagnosed with rare diseases and their and families search desperately to organize drug discovery campaigns. Alternative models that differ from default paradigms offer real opportunities. There are, however, no clear guidelines for the development of such models, which reduces success rates and raises costs. We address the main challenges in making the discovery of new preclinical treatments more accessible, using rare hereditary paraplegia as a paradigmatic case. First, we discuss the necessary expertise, and the patients' clinical and genetic data. Then, we revisit gene therapy, de novo drug development, and drug repurposing, discussing their applicability. Moreover, we explore a pool of recommended in silico tools for pathogenic variant and protein structure prediction, virtual screening, and experimental validation methods, discussing their strengths and weaknesses. Finally, we focus on successful case applications.
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Affiliation(s)
- Matteo Rossi Sebastiano
- University of Torino, Molecular Biotechnology and Health Sciences Department, CASSMedChem, Piazza Nizza, 10138 Torino, Italy
| | - Shinji Hadano
- Molecular Neuropathobiology Laboratory, Department of Physiology, Tokai University School of Medicine, Isehara, Japan
| | - Fabrizia Cesca
- Department of Life Sciences, University of Trieste, 34127 Trieste, Italy
| | - Giuseppe Ermondi
- University of Torino, Molecular Biotechnology and Health Sciences Department, CASSMedChem, Piazza Nizza, 10138 Torino, Italy.
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2
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Pavelescu LA, Profir M, Enache RM, Roşu OA, Creţoiu SM, Gaspar BS. A Proteogenomic Approach to Unveiling the Complex Biology of the Microbiome. Int J Mol Sci 2024; 25:10467. [PMID: 39408795 PMCID: PMC11476728 DOI: 10.3390/ijms251910467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2024] [Revised: 09/26/2024] [Accepted: 09/26/2024] [Indexed: 10/20/2024] Open
Abstract
The complex biology of the microbiome was elucidated once the genomics era began. The proteogenomic approach analyzes and integrates genetic makeup (genomics) and microbial communities' expressed proteins (proteomics). Therefore, researchers gained insights into gene expression, protein functions, and metabolic pathways, understanding microbial dynamics and behavior, interactions with host cells, and responses to environmental stimuli. In this context, our work aims to bring together data regarding the application of genomics, proteomics, and bioinformatics in microbiome research and to provide new perspectives for applying microbiota modulation in clinical practice with maximum efficiency. This review also synthesizes data from the literature, shedding light on the potential biomarkers and therapeutic targets for various diseases influenced by the microbiome.
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Affiliation(s)
- Luciana Alexandra Pavelescu
- Department of Morphological Sciences, Cell and Molecular Biology and Histology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania; (L.A.P.); (M.P.); (O.A.R.)
| | - Monica Profir
- Department of Morphological Sciences, Cell and Molecular Biology and Histology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania; (L.A.P.); (M.P.); (O.A.R.)
- Department of Oncology, Elias University Emergency Hospital, 011461 Bucharest, Romania
| | - Robert Mihai Enache
- Department of Radiology and Medical Imaging, Fundeni Clinical Institute, 022328 Bucharest, Romania;
| | - Oana Alexandra Roşu
- Department of Morphological Sciences, Cell and Molecular Biology and Histology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania; (L.A.P.); (M.P.); (O.A.R.)
- Department of Oncology, Elias University Emergency Hospital, 011461 Bucharest, Romania
| | - Sanda Maria Creţoiu
- Department of Morphological Sciences, Cell and Molecular Biology and Histology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania; (L.A.P.); (M.P.); (O.A.R.)
| | - Bogdan Severus Gaspar
- Department of Surgery, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania;
- Surgery Clinic, Bucharest Emergency Clinical Hospital, 014461 Bucharest, Romania
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3
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Kahn RA, Virk H, Laflamme C, Houston DW, Polinski NK, Meijers R, Levey AI, Saper CB, Errington TM, Turn RE, Bandrowski A, Trimmer JS, Rego M, Freedman LP, Ferrara F, Bradbury ARM, Cable H, Longworth S. Antibody characterization is critical to enhance reproducibility in biomedical research. eLife 2024; 13:e100211. [PMID: 39140332 PMCID: PMC11324233 DOI: 10.7554/elife.100211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Accepted: 08/06/2024] [Indexed: 08/15/2024] Open
Abstract
Antibodies are used in many areas of biomedical and clinical research, but many of these antibodies have not been adequately characterized, which casts doubt on the results reported in many scientific papers. This problem is compounded by a lack of suitable control experiments in many studies. In this article we review the history of the 'antibody characterization crisis', and we document efforts and initiatives to address the problem, notably for antibodies that target human proteins. We also present recommendations for a range of stakeholders - researchers, universities, journals, antibody vendors and repositories, scientific societies and funders - to increase the reproducibility of studies that rely on antibodies.
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Affiliation(s)
- Richard A Kahn
- Department of Biochemistry, Emory University School of MedicineAtlantaUnited States
| | - Harvinder Virk
- Department of Respiratory Sciences, University of LeicesterLeicesterUnited Kingdom
| | - Carl Laflamme
- Department of Neurology and Neurosurgery, Structural Genomics Consortium, The Montreal Neurological Institute, McGill UniversityMontrealCanada
| | - Douglas W Houston
- The Development Studies Hybridoma Databank, University of IowaIowa CityUnited States
| | - Nicole K Polinski
- The Michael J Fox Foundation for Parkinson’s ResearchNew YorkUnited States
| | - Rob Meijers
- Institute for Protein InnovationBostonUnited States
| | - Allan I Levey
- Department of Neurology, Emory University School of MedicineAtlantaUnited States
| | - Clifford B Saper
- Department of Neurology and Program in Neuroscience, Harvard Medical School and Beth Israel Deaconess Medical CenterBostonUnited States
| | | | - Rachel E Turn
- Department of Microbiology and Immunology, Stanford University School of MedicineStanfordUnited States
| | - Anita Bandrowski
- Department of Neuroscience, University of California, San DiegoLa JollaUnited States
| | - James S Trimmer
- Department of Physiology and Membrane Biology, University of California, Davis School of MedicineDavisUnited States
| | | | | | | | | | - Hannah Cable
- Department of Research and Development, AbcamCambridgeUnited Kingdom
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4
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Sharma KR, Colvis CM, Rodgers GP, Sheeley DM. Illuminating the druggable genome: Pathways to progress. Drug Discov Today 2024; 29:103805. [PMID: 37890715 PMCID: PMC10939933 DOI: 10.1016/j.drudis.2023.103805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/12/2023] [Accepted: 10/19/2023] [Indexed: 10/29/2023]
Abstract
There are ∼4500 genes within the 'druggable genome', the subset of the human genome that expresses proteins able to bind drug-like molecules, yet existing drugs only target a few hundred. A substantial subset of druggable proteins are largely uncharacterized or understudied, with many falling within G protein-coupled receptor (GPCR), ion channel, and kinase protein families. To improve scientific understanding of these three understudied protein families, the US National Institutes of Health launched the Illuminating the Druggable Genome Program. Now, as the program draws to a close, this review will lay out resources developed by the program that are intended to equip the scientific community with the tools necessary to explore previously understudied biology with the potential to rapidly impact human health.
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Affiliation(s)
- Karlie R Sharma
- National Center for Advancing Translational Sciences, National Institutes of Health, 6701 Democracy Blvd, Bethesda, MD 20892, USA.
| | - Christine M Colvis
- National Center for Advancing Translational Sciences, National Institutes of Health, 6701 Democracy Blvd, Bethesda, MD 20892, USA
| | - Griffin P Rodgers
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA
| | - Douglas M Sheeley
- Office of Strategic Coordination, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA
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5
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Biddle M, Stylianou P, Rekas M, Wright A, Sousa J, Ruddy D, Stefana MI, Kmiecik K, Bandrowski A, Kahn R, Laflamme C, Krockow EM, Virk H. Improving the integrity and reproducibility of research that uses antibodies: a technical, data sharing, behavioral and policy challenge. MAbs 2024; 16:2323706. [PMID: 38444344 PMCID: PMC10936606 DOI: 10.1080/19420862.2024.2323706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 02/22/2024] [Indexed: 03/07/2024] Open
Abstract
Antibodies are one of the most important reagents used in biomedical and fundamental research, used to identify, and quantify proteins, contribute to knowledge of disease mechanisms, and validate drug targets. Yet many antibodies used in research do not recognize their intended target, or recognize additional molecules, compromising the integrity of research findings and leading to waste of resources, lack of reproducibility, failure of research projects, and delays in drug development. Researchers frequently use antibodies without confirming that they perform as intended in their application of interest. Here we argue that the determinants of end-user antibody choice and use are critical, and under-addressed, behavioral drivers of this problem. This interacts with the batch-to-batch variability of these biological reagents, and the paucity of available characterization data for most antibodies, making it more difficult for researchers to choose high quality reagents and perform necessary validation experiments. The open-science company YCharOS works with major antibody manufacturers and knockout cell line producers to characterize antibodies, identifying high-performing renewable antibodies for many targets in neuroscience. This shows the progress that can be made by stakeholders working together. However, their work so far applies to only a tiny fraction of available antibodies. Where characterization data exists, end-users need help to find and use it appropriately. While progress has been made in the context of technical solutions and antibody characterization, we argue that initiatives to make best practice behaviors by researchers more feasible, easy, and rewarding are needed. Global cooperation and coordination between multiple partners and stakeholders will be crucial to address the technical, policy, behavioral, and open data sharing challenges. We offer potential solutions by describing our Only Good Antibodies initiative, a community of researchers and partner organizations working toward the necessary change. We conclude with an open invitation for stakeholders, including researchers, to join our cause.
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Affiliation(s)
- M. Biddle
- NIHR Respiratory BRC, Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - P. Stylianou
- NIHR Respiratory BRC, Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - M. Rekas
- NIHR Respiratory BRC, Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - A. Wright
- NIHR Respiratory BRC, Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - J. Sousa
- NIHR Respiratory BRC, Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - D. Ruddy
- NIHR Respiratory BRC, Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - M. I. Stefana
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - K. Kmiecik
- NIHR Respiratory BRC, Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - A. Bandrowski
- Department of Neuroscience, UC San Diego, La Jolla, CA, USA
| | - R.A. Kahn
- Department of Biochemistry, Emory University School of Medicine, Atlanta, USA
| | - C. Laflamme
- Department of Neurology and Neurosurgery, Structural Genomics Consortium, The Montreal Neurological Institute, McGill University, Canada
| | - E. M. Krockow
- School of Psychology and Vision Sciences, University of Leicester, Leicester, UK
| | - H.S. Virk
- NIHR Respiratory BRC, Department of Respiratory Sciences, University of Leicester, Leicester, UK
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Zhang J, Kanoatov M, Jarvi K, Gauthier-Fisher A, Moskovtsev SI, Librach C, Drabovich AP. Germ cell-specific proteins AKAP4 and ASPX facilitate identification of rare spermatozoa in non-obstructive azoospermia. Mol Cell Proteomics 2023; 22:100556. [PMID: 37087050 DOI: 10.1016/j.mcpro.2023.100556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 04/06/2023] [Accepted: 04/16/2023] [Indexed: 04/24/2023] Open
Abstract
Non-obstructive azoospermia (NOA), the most severe form of male infertility, could be treated with intra-cytoplasmic sperm injection, providing spermatozoa were retrieved with the microdissection testicular sperm extraction (mTESE). We hypothesized that testis- and germ cell-specific proteins would facilitate flow cytometry-assisted identification of rare spermatozoa in semen cell pellets of NOA patients, thus enabling non-invasive diagnostics prior to mTESE. Data mining, targeted proteomics, and immunofluorescent microscopy identified and verified a panel of highly testis-specific proteins expressed at the continuum of germ cell differentiation. Late germ cell-specific proteins AKAP4_HUMAN and ASPX_HUMAN (ACRV1 gene) revealed exclusive localization in spermatozoa tails and acrosomes, respectively. A multiplex imaging flow cytometry assay facilitated fast and unambiguous identification of rare but morphologically intact AKAP4+/ASPX+/Hoechst+ spermatozoa within debris-laden semen pellets of NOA patients. While the previously suggested markers for spermatozoa retrieval suffered from low diagnostic specificity, the multi-step gating strategy and visualization of AKAP4+/ASPX+/Hoechst+ cells with elongated tails and acrosome-capped nuclei facilitated fast and unambiguous identification of the mature intact spermatozoa. AKAP4+/ASPX+/Hoechst+ assay may emerge as a non-invasive test to predict retrieval of morphologically intact spermatozoa by mTESE, thus improving diagnostics and treatment of severe forms of male infertility.
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Affiliation(s)
| | - Mirzo Kanoatov
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Keith Jarvi
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada; Department of Surgery, Division of Urology, Mount Sinai Hospital, Toronto, ON, Canada
| | | | - Sergey I Moskovtsev
- CReATe Fertility Centre, Toronto, ON, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Clifford Librach
- CReATe Fertility Centre, Toronto, ON, Canada; Department of Obstetrics and Gynecology, University of Toronto, Toronto, ON, Canada; Department of Physiology, University of Toronto, Toronto, ON, Canada; Sunnybrook Research Institute, Toronto, ON, Canada
| | - Andrei P Drabovich
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada.
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7
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Kelleher KJ, Sheils TK, Mathias SL, Yang JJ, Metzger V, Siramshetty V, Nguyen DT, Jensen LJ, Vidović D, Schürer S, Holmes J, Sharma K, Pillai A, Bologa C, Edwards J, Mathé E, Oprea T. Pharos 2023: an integrated resource for the understudied human proteome. Nucleic Acids Res 2023; 51:D1405-D1416. [PMID: 36624666 PMCID: PMC9825581 DOI: 10.1093/nar/gkac1033] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/12/2022] [Accepted: 11/28/2022] [Indexed: 11/30/2022] Open
Abstract
The Illuminating the Druggable Genome (IDG) project aims to improve our understanding of understudied proteins and our ability to study them in the context of disease biology by perturbing them with small molecules, biologics, or other therapeutic modalities. Two main products from the IDG effort are the Target Central Resource Database (TCRD) (http://juniper.health.unm.edu/tcrd/), which curates and aggregates information, and Pharos (https://pharos.nih.gov/), a web interface for fusers to extract and visualize data from TCRD. Since the 2021 release, TCRD/Pharos has focused on developing visualization and analysis tools that help reveal higher-level patterns in the underlying data. The current iterations of TCRD and Pharos enable users to perform enrichment calculations based on subsets of targets, diseases, or ligands and to create interactive heat maps and UpSet charts of many types of annotations. Using several examples, we show how to address disease biology and drug discovery questions through enrichment calculations and UpSet charts.
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Affiliation(s)
- Keith J Kelleher
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Timothy K Sheils
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Stephen L Mathias
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Jeremy J Yang
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Vincent T Metzger
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Vishal B Siramshetty
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Dac-Trung Nguyen
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Lars Juhl Jensen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen 2200, Copenhagen, Denmark
| | - Dušica Vidović
- Institute for Data Science and Computing, 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
| | - Stephan C Schürer
- Institute for Data Science and Computing, 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
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Jayme Holmes
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Karlie R Sharma
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Ajay Pillai
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Cristian G Bologa
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Jeremy S Edwards
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, NM 87131, USA
| | - Ewy A Mathé
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Tudor I Oprea
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
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8
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Avram S, Wilson TB, Curpan R, Halip L, Borota A, Bora A, Bologa C, Holmes J, Knockel J, Yang J, Oprea T. DrugCentral 2023 extends human clinical data and integrates veterinary drugs. Nucleic Acids Res 2022; 51:D1276-D1287. [PMID: 36484092 PMCID: PMC9825566 DOI: 10.1093/nar/gkac1085] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/20/2022] [Accepted: 12/02/2022] [Indexed: 12/14/2022] Open
Abstract
DrugCentral monitors new drug approvals and standardizes drug information. The current update contains 285 drugs (131 for human use). New additions include: (i) the integration of veterinary drugs (154 for animal use only), (ii) the addition of 66 documented off-label uses and iii) the identification of adverse drug events from pharmacovigilance data for pediatric and geriatric patients. Additional enhancements include chemical substructure searching using SMILES and 'Target Cards' based on UniProt accession codes. Statistics of interests include the following: (i) 60% of the covered drugs are on-market drugs with expired patent and exclusivity coverage, 17% are off-market, and 23% are on-market drugs with active patents and exclusivity coverage; (ii) 59% of the drugs are oral, 33% are parenteral and 18% topical, at the level of the active ingredients; (iii) only 3% of all drugs are for animal use only; however, 61% of the veterinary drugs are also approved for human use; (iv) dogs, cats and horses are by far the most represented target species for veterinary drugs; (v) the physicochemical property profile of animal drugs is very similar to that of human drugs. Use cases include azaperone, the only sedative approved for swine, and ruxolitinib, a Janus kinase inhibitor.
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Affiliation(s)
| | | | - Ramona Curpan
- Department of Computational Chemistry, “Coriolan Dragulescu” Institute of Chemistry, 24 Mihai Viteazu Blvd, Timişoara, Timiş 300223, Romania
| | - Liliana Halip
- Department of Computational Chemistry, “Coriolan Dragulescu” Institute of Chemistry, 24 Mihai Viteazu Blvd, Timişoara, Timiş 300223, Romania
| | - Ana Borota
- Department of Computational Chemistry, “Coriolan Dragulescu” Institute of Chemistry, 24 Mihai Viteazu Blvd, Timişoara, Timiş 300223, Romania
| | - Alina Bora
- Department of Computational Chemistry, “Coriolan Dragulescu” Institute of Chemistry, 24 Mihai Viteazu Blvd, Timişoara, Timiş 300223, Romania
| | - Cristian G Bologa
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, 700 Camino de Salud NE, Albuquerque, NM 87106, USA
| | - Jayme Holmes
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, 700 Camino de Salud NE, Albuquerque, NM 87106, USA
| | - Jeffrey Knockel
- Department of Computer Science, University of New Mexico, 1901 Redondo S Dr, Albuquerque, NM 87106, USA
| | - Jeremy J Yang
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, 700 Camino de Salud NE, Albuquerque, NM 87106, USA
| | - Tudor I Oprea
- To whom correspondence should be addressed. Tel: +1 505 925 7529; Fax: +1 505 925 7625;
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9
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Waury K, Willemse EAJ, Vanmechelen E, Zetterberg H, Teunissen CE, Abeln S. Bioinformatics tools and data resources for assay development of fluid protein biomarkers. Biomark Res 2022; 10:83. [DOI: 10.1186/s40364-022-00425-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 10/25/2022] [Indexed: 11/16/2022] Open
Abstract
AbstractFluid protein biomarkers are important tools in clinical research and health care to support diagnosis and to monitor patients. Especially within the field of dementia, novel biomarkers could address the current challenges of providing an early diagnosis and of selecting trial participants. While the great potential of fluid biomarkers is recognized, their implementation in routine clinical use has been slow. One major obstacle is the often unsuccessful translation of biomarker candidates from explorative high-throughput techniques to sensitive antibody-based immunoassays. In this review, we propose the incorporation of bioinformatics into the workflow of novel immunoassay development to overcome this bottleneck and thus facilitate the development of novel biomarkers towards clinical laboratory practice. Due to the rapid progress within the field of bioinformatics many freely available and easy-to-use tools and data resources exist which can aid the researcher at various stages. Current prediction methods and databases can support the selection of suitable biomarker candidates, as well as the choice of appropriate commercial affinity reagents. Additionally, we examine methods that can determine or predict the epitope - an antibody’s binding region on its antigen - and can help to make an informed choice on the immunogenic peptide used for novel antibody production. Selected use cases for biomarker candidates help illustrate the application and interpretation of the introduced tools.
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10
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Choi Y. Artificial intelligence for antibody reading comprehension: AntiBERTa. PATTERNS (NEW YORK, N.Y.) 2022; 3:100535. [PMID: 35845838 PMCID: PMC9278504 DOI: 10.1016/j.patter.2022.100535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Utilizing publicly available antibody big data resources, Leem et al. (2022) developed an antibody-specific language model, AntiBERTa, to understand the "language" of antibodies. Case studies reveal that AntiBERTa can be an extremely useful tool for antibody engineering.
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Affiliation(s)
- Yoonjoo Choi
- Combinatorial Tumor Immunotherapy MRC, Chonnam National University Medical School, Hwasun-gun, Jeollanam-do 58128, South Korea
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11
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Understanding metabolic alterations and heterogeneity in cancer progression through validated immunodetection of key molecular components: a case of carbonic anhydrase IX. Cancer Metastasis Rev 2022; 40:1035-1053. [PMID: 35080763 PMCID: PMC8825433 DOI: 10.1007/s10555-021-10011-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 12/08/2021] [Indexed: 12/22/2022]
Abstract
Cancer metabolic heterogeneity develops in response to both intrinsic factors (mutations leading to activation of oncogenic pathways) and extrinsic factors (physiological and molecular signals from the extracellular milieu). Here we review causes and consequences of metabolic alterations in cancer cells with focus on hypoxia and acidosis, and with particular attention to carbonic anhydrase IX (CA IX). CA IX is a cancer-associated enzyme induced and activated by hypoxia in a broad range of tumor types, where it participates in pH regulation as well as in molecular mechanisms supporting cancer cells’ invasion and metastasis. CA IX catalyzes reversible conversion of carbon dioxide to bicarbonate ion plus proton and cooperates with a spectrum of molecules transporting ions or metabolites across the plasma membrane. Thereby CA IX contributes to extracellular acidosis as well as to buffering intracellular pH, which is essential for cell survival, metabolic performance, and proliferation of cancer cells. Since CA IX expression pattern reflects gradients of oxygen, pH, and other intratumoral factors, we use it as a paradigm to discuss an impact of antibody quality and research material on investigating metabolic reprogramming of tumor tissue. Based on the validation, we propose the most reliable CA IX-specific antibodies and suggest conditions for faithful immunohistochemical analysis of molecules contributing to heterogeneity in cancer progression.
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12
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Yang JJ, Grissa D, Lambert CG, Bologa CG, Mathias SL, Waller A, Wild DJ, Jensen LJ, Oprea TI. TIGA: target illumination GWAS analytics. Bioinformatics 2021; 37:3865-3873. [PMID: 34086846 PMCID: PMC11025677 DOI: 10.1093/bioinformatics/btab427] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 05/12/2021] [Accepted: 06/03/2021] [Indexed: 12/31/2022] Open
Abstract
MOTIVATION Genome-wide association studies can reveal important genotype-phenotype associations; however, data quality and interpretability issues must be addressed. For drug discovery scientists seeking to prioritize targets based on the available evidence, these issues go beyond the single study. RESULTS Here, we describe rational ranking, filtering and interpretation of inferred gene-trait associations and data aggregation across studies by leveraging existing curation and harmonization efforts. Each gene-trait association is evaluated for confidence, with scores derived solely from aggregated statistics, linking a protein-coding gene and phenotype. We propose a method for assessing confidence in gene-trait associations from evidence aggregated across studies, including a bibliometric assessment of scientific consensus based on the iCite relative citation ratio, and meanRank scores, to aggregate multivariate evidence.This method, intended for drug target hypothesis generation, scoring and ranking, has been implemented as an analytical pipeline, available as open source, with public datasets of results, and a web application designed for usability by drug discovery scientists. AVAILABILITY AND IMPLEMENTATION Web application, datasets and source code via https://unmtid-shinyapps.net/tiga/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jeremy J Yang
- Division of Translational Informatics, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
- Integrative Data Science Laboratory, School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN 47408, USA
| | - Dhouha Grissa
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Christophe G Lambert
- Division of Translational Informatics, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Cristian G Bologa
- Division of Translational Informatics, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Stephen L Mathias
- Division of Translational Informatics, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Anna Waller
- Department of Pathology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - David J Wild
- Integrative Data Science Laboratory, School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN 47408, USA
| | - Lars Juhl Jensen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Tudor I Oprea
- Division of Translational Informatics, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
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13
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Svobodova Z, Novotny J, Ospalkova B, Slovakova M, Bilkova Z, Foret F. Affiblot: a dot blot-based screening device for selection of reliable antibodies. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2021; 13:3874-3884. [PMID: 34528947 DOI: 10.1039/d1ay00955a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The key factor in the development of antibody-based assays is to find an antibody that has an appropriate affinity, high specificity, and low cross-reactivity. However, this task is not easy to carry out since the research antibodies on the market may suffer from low specificity and reproducibility. Here, we report on a palm-sized dot blot-based device, called the affiblot, that has a specially designed lid that allows simultaneous semi-quantitative comparison of up to five antibodies from different suppliers regarding their affinity/avidity, cross-reactivity, and batch-to-batch reliability. The only required peripheral equipment is a vacuum pump, a camera, and densitometry software. The affiblot device was tested for its functionality and its measurements were compared against those obtained by standard dot blot and ELISA. The benefit over these methods, when various antibodies are evaluated, is in its simplicity. It allows easy antigen deposition, fast application and the discarding of the solutions, a compact undivided membrane, and therefore significant decrease of labor. The device was tested with specific anti-ApoE, anti-EpCAM, anti-Salmonella, anti-E. coli, and anti-Listeria antibodies from different suppliers. Their properties were compared for their ability to interact specifically with antigen and/or non-target structures and the best-suited antibody for the intended application was identified.
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Affiliation(s)
- Zuzana Svobodova
- Department of Biological and Biochemical Sciences, Faculty of Chemical Technology, University of Pardubice, Studentska 573, Pardubice, Czech Republic.
- Department of Biological and Medical Sciences, Faculty of Pharmacy in Hradec Kralove, Charles University, Zborovska 2089, Czech Republic
| | - Jakub Novotny
- Department of Biological and Biochemical Sciences, Faculty of Chemical Technology, University of Pardubice, Studentska 573, Pardubice, Czech Republic.
- Institute of Analytical Chemistry of the CAS, v. v. i., Veveri 967/97, Brno, Czech Republic
| | - Barbora Ospalkova
- Department of Biological and Biochemical Sciences, Faculty of Chemical Technology, University of Pardubice, Studentska 573, Pardubice, Czech Republic.
| | - Marcela Slovakova
- Department of Biological and Biochemical Sciences, Faculty of Chemical Technology, University of Pardubice, Studentska 573, Pardubice, Czech Republic.
| | - Zuzana Bilkova
- Department of Biological and Biochemical Sciences, Faculty of Chemical Technology, University of Pardubice, Studentska 573, Pardubice, Czech Republic.
| | - Frantisek Foret
- Institute of Analytical Chemistry of the CAS, v. v. i., Veveri 967/97, Brno, Czech Republic
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14
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Su M, Zhang Z, Zhou L, Han C, Huang C, Nice EC. Proteomics, Personalized Medicine and Cancer. Cancers (Basel) 2021; 13:2512. [PMID: 34063807 PMCID: PMC8196570 DOI: 10.3390/cancers13112512] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 05/12/2021] [Accepted: 05/17/2021] [Indexed: 02/05/2023] Open
Abstract
As of 2020 the human genome and proteome are both at >90% completion based on high stringency analyses. This has been largely achieved by major technological advances over the last 20 years and has enlarged our understanding of human health and disease, including cancer, and is supporting the current trend towards personalized/precision medicine. This is due to improved screening, novel therapeutic approaches and an increased understanding of underlying cancer biology. However, cancer is a complex, heterogeneous disease modulated by genetic, molecular, cellular, tissue, population, environmental and socioeconomic factors, which evolve with time. In spite of recent advances in treatment that have resulted in improved patient outcomes, prognosis is still poor for many patients with certain cancers (e.g., mesothelioma, pancreatic and brain cancer) with a high death rate associated with late diagnosis. In this review we overview key hallmarks of cancer (e.g., autophagy, the role of redox signaling), current unmet clinical needs, the requirement for sensitive and specific biomarkers for early detection, surveillance, prognosis and drug monitoring, the role of the microbiome and the goals of personalized/precision medicine, discussing how emerging omics technologies can further inform on these areas. Exemplars from recent onco-proteogenomic-related publications will be given. Finally, we will address future perspectives, not only from the standpoint of perceived advances in treatment, but also from the hurdles that have to be overcome.
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Affiliation(s)
- Miao Su
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, and West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu 610041, China; (M.S.); (Z.Z.); (L.Z.); (C.H.)
| | - Zhe Zhang
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, and West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu 610041, China; (M.S.); (Z.Z.); (L.Z.); (C.H.)
| | - Li Zhou
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, and West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu 610041, China; (M.S.); (Z.Z.); (L.Z.); (C.H.)
| | - Chao Han
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, and West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu 610041, China; (M.S.); (Z.Z.); (L.Z.); (C.H.)
| | - Canhua Huang
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, and West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu 610041, China; (M.S.); (Z.Z.); (L.Z.); (C.H.)
| | - Edouard C. Nice
- Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia
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15
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Al-Shaheri FN, Alhamdani MSS, Bauer AS, Giese N, Büchler MW, Hackert T, Hoheisel JD. Blood biomarkers for differential diagnosis and early detection of pancreatic cancer. Cancer Treat Rev 2021; 96:102193. [PMID: 33865174 DOI: 10.1016/j.ctrv.2021.102193] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 03/17/2021] [Accepted: 03/19/2021] [Indexed: 12/12/2022]
Abstract
Pancreatic cancer is currently the most lethal tumor entity and case numbers are rising. It will soon be the second most frequent cause of cancer-related death in the Western world. Mortality is close to incidence and patient survival after diagnosis stands at about five months. Blood-based diagnostics could be one crucial factor for improving this dismal situation and is at a stage that could make this possible. Here, we are reviewing the current state of affairs with its problems and promises, looking at various molecule types. Reported results are evaluated in the overall context. Also, we are proposing steps toward clinical utility that should advance the development toward clinical application by improving biomarker quality but also by defining distinct clinical objectives and the respective diagnostic accuracies required to achieve them. Many of the discussed points and conclusions are highly relevant to other solid tumors, too.
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Affiliation(s)
- Fawaz N Al-Shaheri
- Division of Functional Genome Analysis, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany; Medical Faculty Heidelberg, Heidelberg University, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany.
| | - Mohamed S S Alhamdani
- Division of Functional Genome Analysis, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Andrea S Bauer
- Division of Functional Genome Analysis, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Nathalia Giese
- Department of General Surgery, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
| | - Markus W Büchler
- Department of General Surgery, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
| | - Thilo Hackert
- Department of General Surgery, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
| | - Jörg D Hoheisel
- Division of Functional Genome Analysis, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
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16
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O’Garro C, Igbineweka L, Ali Z, Mezei M, Mujtaba S. The Biological Significance of Targeting Acetylation-Mediated Gene Regulation for Designing New Mechanistic Tools and Potential Therapeutics. Biomolecules 2021; 11:biom11030455. [PMID: 33803759 PMCID: PMC8003229 DOI: 10.3390/biom11030455] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 03/15/2021] [Accepted: 03/16/2021] [Indexed: 01/13/2023] Open
Abstract
The molecular interplay between nucleosomal packaging and the chromatin landscape regulates the transcriptional programming and biological outcomes of downstream genes. An array of epigenetic modifications plays a pivotal role in shaping the chromatin architecture, which controls DNA access to the transcriptional machinery. Acetylation of the amino acid lysine is a widespread epigenetic modification that serves as a marker for gene activation, which intertwines the maintenance of cellular homeostasis and the regulation of signaling during stress. The biochemical horizon of acetylation ranges from orchestrating the stability and cellular localization of proteins that engage in the cell cycle to DNA repair and metabolism. Furthermore, lysine acetyltransferases (KATs) modulate the functions of transcription factors that govern cellular response to microbial infections, genotoxic stress, and inflammation. Due to their central role in many biological processes, mutations in KATs cause developmental and intellectual challenges and metabolic disorders. Despite the availability of tools for detecting acetylation, the mechanistic knowledge of acetylation-mediated cellular processes remains limited. This review aims to integrate molecular and structural bases of KAT functions, which would help design highly selective tools for understanding the biology of KATs toward developing new disease treatments.
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Affiliation(s)
- Chenise O’Garro
- Department of Biology, Medgar Evers College, City University of New York, Brooklyn, NY 11225, USA; (C.O.); (L.I.); (Z.A.)
| | - Loveth Igbineweka
- Department of Biology, Medgar Evers College, City University of New York, Brooklyn, NY 11225, USA; (C.O.); (L.I.); (Z.A.)
| | - Zonaira Ali
- Department of Biology, Medgar Evers College, City University of New York, Brooklyn, NY 11225, USA; (C.O.); (L.I.); (Z.A.)
| | - Mihaly Mezei
- Department of Pharmaceutical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Shiraz Mujtaba
- Department of Biology, Medgar Evers College, City University of New York, Brooklyn, NY 11225, USA; (C.O.); (L.I.); (Z.A.)
- Correspondence:
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17
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Avram S, Bologa CG, Holmes J, Bocci G, Wilson TB, Nguyen DT, Curpan R, Halip L, Bora A, Yang JJ, Knockel J, Sirimulla S, Ursu O, Oprea TI. DrugCentral 2021 supports drug discovery and repositioning. Nucleic Acids Res 2021; 49:D1160-D1169. [PMID: 33151287 PMCID: PMC7779058 DOI: 10.1093/nar/gkaa997] [Citation(s) in RCA: 98] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 10/09/2020] [Accepted: 10/14/2020] [Indexed: 12/18/2022] Open
Abstract
DrugCentral is a public resource (http://drugcentral.org) that serves the scientific community by providing up-to-date drug information, as described in previous papers. The current release includes 109 newly approved (October 2018 through March 2020) active pharmaceutical ingredients in the US, Europe, Japan and other countries; and two molecular entities (e.g. mefuparib) of interest for COVID19. New additions include a set of pharmacokinetic properties for ∼1000 drugs, and a sex-based separation of side effects, processed from FAERS (FDA Adverse Event Reporting System); as well as a drug repositioning prioritization scheme based on the market availability and intellectual property rights forFDA approved drugs. In the context of the COVID19 pandemic, we also incorporated REDIAL-2020, a machine learning platform that estimates anti-SARS-CoV-2 activities, as well as the 'drugs in news' feature offers a brief enumeration of the most interesting drugs at the present moment. The full database dump and data files are available for download from the DrugCentral web portal.
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Affiliation(s)
- Sorin Avram
- Department of Computational Chemistry, “Coriolan Dragulescu’’ Institute of Chemistry, 24 Mihai Viteazu Blvd, Timişoara, Timiş, 300223, România
| | - Cristian G Bologa
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
- UNM Comprehensive Cancer Center, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Jayme Holmes
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Giovanni Bocci
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Thomas B Wilson
- College of Pharmacy, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Dac-Trung Nguyen
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Ramona Curpan
- Department of Computational Chemistry, “Coriolan Dragulescu’’ Institute of Chemistry, 24 Mihai Viteazu Blvd, Timişoara, Timiş, 300223, România
| | - Liliana Halip
- Department of Computational Chemistry, “Coriolan Dragulescu’’ Institute of Chemistry, 24 Mihai Viteazu Blvd, Timişoara, Timiş, 300223, România
| | - Alina Bora
- Department of Computational Chemistry, “Coriolan Dragulescu’’ Institute of Chemistry, 24 Mihai Viteazu Blvd, Timişoara, Timiş, 300223, România
| | - Jeremy J Yang
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Jeffrey Knockel
- Department of Computer Science, University of New Mexico, Albuquerque, NM 87131, USA
| | - Suman Sirimulla
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Texas at El Paso, TX 79902, USA
| | - Oleg Ursu
- Computational and Structural Chemistry, Merck & Co., Inc., 2000 Galloping Hill Road, Kenilworth, NJ 07033, USA
| | - Tudor I Oprea
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
- Computational and Structural Chemistry, Merck & Co., Inc., 2000 Galloping Hill Road, Kenilworth, NJ 07033, USA
- Department of Rheumatology and Inflammation Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, 40530 Gothenburg, Sweden
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
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18
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Sheils TK, Mathias SL, Kelleher KJ, Siramshetty VB, Nguyen DT, Bologa CG, Jensen LJ, Vidović D, Koleti A, Schürer SC, Waller A, Yang JJ, Holmes J, Bocci G, Southall N, Dharkar P, Mathé E, Simeonov A, Oprea TI. TCRD and Pharos 2021: mining the human proteome for disease biology. Nucleic Acids Res 2021; 49:D1334-D1346. [PMID: 33156327 PMCID: PMC7778974 DOI: 10.1093/nar/gkaa993] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/09/2020] [Accepted: 10/14/2020] [Indexed: 12/13/2022] Open
Abstract
In 2014, the National Institutes of Health (NIH) initiated the Illuminating the Druggable Genome (IDG) program to identify and improve our understanding of poorly characterized proteins that can potentially be modulated using small molecules or biologics. Two resources produced from these efforts are: The Target Central Resource Database (TCRD) (http://juniper.health.unm.edu/tcrd/) and Pharos (https://pharos.nih.gov/), a web interface to browse the TCRD. The ultimate goal of these resources is to highlight and facilitate research into currently understudied proteins, by aggregating a multitude of data sources, and ranking targets based on the amount of data available, and presenting data in machine learning ready format. Since the 2017 release, both TCRD and Pharos have produced two major releases, which have incorporated or expanded an additional 25 data sources. Recently incorporated data types include human and viral-human protein-protein interactions, protein-disease and protein-phenotype associations, and drug-induced gene signatures, among others. These aggregated data have enabled us to generate new visualizations and content sections in Pharos, in order to empower users to find new areas of study in the druggable genome.
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Affiliation(s)
- Timothy K Sheils
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Stephen L Mathias
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Keith J Kelleher
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Vishal B Siramshetty
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Dac-Trung Nguyen
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Cristian G Bologa
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, 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
| | - Dušica Vidović
- Institute for Data Science and Computing, 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
| | - Amar Koleti
- Institute for Data Science and Computing, University of Miami, Coral Gables, FL 33146, USA
| | - Stephan C Schürer
- Institute for Data Science and Computing, 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
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Anna Waller
- UNM Center for Molecular Discovery, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Jeremy J Yang
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Jayme Holmes
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Giovanni Bocci
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
| | - Noel Southall
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Poorva Dharkar
- National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
| | - Ewy Mathé
- 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
| | - Tudor I Oprea
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
- UNM Comprehensive Cancer Center, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
- Department of Rheumatology and Inflammation Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, 40530 Gothenburg, Sweden
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19
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Sivertsson Å, Lindström E, Oksvold P, Katona B, Hikmet F, Vuu J, Gustavsson J, Sjöstedt E, von Feilitzen K, Kampf C, Schwenk JM, Uhlén M, Lindskog C. Enhanced Validation of Antibodies Enables the Discovery of Missing Proteins. J Proteome Res 2020; 19:4766-4781. [PMID: 33170010 PMCID: PMC7723238 DOI: 10.1021/acs.jproteome.0c00486] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
![]()
The localization of proteins at a
tissue- or cell-type-specific
level is tightly linked to the protein function. To better understand
each
protein’s role in cellular systems, spatial information constitutes
an important complement to quantitative data. The standard methods
for determining the spatial distribution of proteins in single cells
of complex tissue samples make use of antibodies. For a stringent
analysis of the human proteome, we used orthogonal methods and independent
antibodies to validate 5981 antibodies that show the expression of
3775 human proteins across all major human tissues. This enhanced
validation uncovered 56 proteins corresponding to the group of “missing
proteins” and 171 proteins of unknown function. The presented
strategy will facilitate further discussions around criteria for evidence
of protein existence based on immunohistochemistry and serves as a
useful guide to identify candidate proteins for integrative studies
with quantitative proteomics methods.
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Affiliation(s)
- Åsa Sivertsson
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, 17121 Stockholm, Sweden
| | - Emil Lindström
- Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, 75185 Uppsala, Sweden
| | - Per Oksvold
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, 17121 Stockholm, Sweden
| | - Borbala Katona
- Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, 75185 Uppsala, Sweden
| | - Feria Hikmet
- Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, 75185 Uppsala, Sweden
| | - Jimmy Vuu
- Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, 75185 Uppsala, Sweden
| | - Jonas Gustavsson
- Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, 75185 Uppsala, Sweden
| | - Evelina Sjöstedt
- Department of Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
| | - Kalle von Feilitzen
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, 17121 Stockholm, Sweden
| | - Caroline Kampf
- Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, 75185 Uppsala, Sweden.,Atlas Antibodies AB, 16869 Bromma, Sweden
| | - Jochen M Schwenk
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, 17121 Stockholm, Sweden
| | - Mathias Uhlén
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, 17121 Stockholm, Sweden.,Department of Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
| | - Cecilia Lindskog
- Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, 75185 Uppsala, Sweden
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20
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Adhikari S, Nice EC, Deutsch EW, Lane L, Omenn GS, Pennington SR, Paik YK, Overall CM, Corrales FJ, Cristea IM, Van Eyk JE, Uhlén M, Lindskog C, Chan DW, Bairoch A, Waddington JC, Justice JL, LaBaer J, Rodriguez H, He F, Kostrzewa M, Ping P, Gundry RL, Stewart P, Srivastava S, Srivastava S, Nogueira FCS, Domont GB, Vandenbrouck Y, Lam MPY, Wennersten S, Vizcaino JA, Wilkins M, Schwenk JM, Lundberg E, Bandeira N, Marko-Varga G, Weintraub ST, Pineau C, Kusebauch U, Moritz RL, Ahn SB, Palmblad M, Snyder MP, Aebersold R, Baker MS. A high-stringency blueprint of the human proteome. Nat Commun 2020; 11:5301. [PMID: 33067450 PMCID: PMC7568584 DOI: 10.1038/s41467-020-19045-9] [Citation(s) in RCA: 134] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 09/25/2020] [Indexed: 02/07/2023] Open
Abstract
The Human Proteome Organization (HUPO) launched the Human Proteome Project (HPP) in 2010, creating an international framework for global collaboration, data sharing, quality assurance and enhancing accurate annotation of the genome-encoded proteome. During the subsequent decade, the HPP established collaborations, developed guidelines and metrics, and undertook reanalysis of previously deposited community data, continuously increasing the coverage of the human proteome. On the occasion of the HPP's tenth anniversary, we here report a 90.4% complete high-stringency human proteome blueprint. This knowledge is essential for discerning molecular processes in health and disease, as we demonstrate by highlighting potential roles the human proteome plays in our understanding, diagnosis and treatment of cancers, cardiovascular and infectious diseases.
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Affiliation(s)
- Subash Adhikari
- Faculty of Medicine, Health and Human Sciences, Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, 2109, Australia
| | - Edouard C Nice
- Faculty of Medicine, Health and Human Sciences, Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, 2109, Australia
- Faculty of Medicine, Nursing and Health Sciences, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, 3800, Australia
| | - Eric W Deutsch
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA, 98109, USA
| | - Lydie Lane
- Faculty of Medicine, SIB-Swiss Institute of Bioinformatics and Department of Microbiology and Molecular Medicine, University of Geneva, CMU, Michel-Servet 1, 1211, Geneva, Switzerland
| | - Gilbert S Omenn
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109-2218, USA
| | - Stephen R Pennington
- UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Dublin, Ireland
| | - Young-Ki Paik
- Yonsei Proteome Research Center, 50 Yonsei-ro, Sudaemoon-ku, Seoul, 120-749, South Korea
| | | | - Fernando J Corrales
- Functional Proteomics Laboratory, Centro Nacional de Biotecnología-CSIC, Proteored-ISCIII, 28049, Madrid, Spain
| | - Ileana M Cristea
- Department of Molecular Biology, Princeton University, Princeton, NJ, 08544, USA
| | - Jennifer E Van Eyk
- Cedars Sinai Medical Center, Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Los Angeles, CA, 90048, USA
| | - Mathias Uhlén
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 17121, Solna, Sweden
| | - Cecilia Lindskog
- Rudbeck Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 75185, Uppsala, Sweden
| | - Daniel W Chan
- Department of Pathology and Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21224, USA
| | - Amos Bairoch
- Faculty of Medicine, SIB-Swiss Institute of Bioinformatics and Department of Microbiology and Molecular Medicine, University of Geneva, CMU, Michel-Servet 1, 1211, Geneva, Switzerland
| | - James C Waddington
- UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Dublin, Ireland
| | - Joshua L Justice
- Department of Molecular Biology, Princeton University, Princeton, NJ, 08544, USA
| | - Joshua LaBaer
- Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Henry Rodriguez
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA
| | - Fuchu He
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Markus Kostrzewa
- Bruker Daltonik GmbH, Microbiology and Diagnostics, Fahrenheitstrasse, 428359, Bremen, Germany
| | - Peipei Ping
- Cardiac Proteomics and Signaling Laboratory, Department of Physiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Rebekah L Gundry
- CardiOmics Program, Center for Heart and Vascular Research, Division of Cardiovascular Medicine and Department of Cellular and Integrative Physiology, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Peter Stewart
- Department of Chemical Pathology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | | | - Sudhir Srivastava
- Cancer Biomarkers Research Branch, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Suite 5E136, Rockville, MD, 20852, USA
| | - Fabio C S Nogueira
- Proteomics Unit and Laboratory of Proteomics, Institute of Chemistry, Federal University of Rio de Janeiro, Av Athos da Silveria Ramos, 149, 21941-909, Rio de Janeiro, RJ, Brazil
| | - Gilberto B Domont
- Proteomics Unit and Laboratory of Proteomics, Institute of Chemistry, Federal University of Rio de Janeiro, Av Athos da Silveria Ramos, 149, 21941-909, Rio de Janeiro, RJ, Brazil
| | - Yves Vandenbrouck
- University of Grenoble Alpes, Inserm, CEA, IRIG-BGE, U1038, 38000, Grenoble, France
| | - Maggie P Y Lam
- Departments of Medicine-Cardiology and Biochemistry and Molecular Genetics, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
- Consortium for Fibrosis Research and Translation, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Sara Wennersten
- Division of Cardiology, Department of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Juan Antonio Vizcaino
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Marc Wilkins
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Jochen M Schwenk
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 17121, Solna, Sweden
| | - Emma Lundberg
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 17121, Solna, Sweden
| | - Nuno Bandeira
- Department of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, Mail Code 0404, La Jolla, CA, 92093-0404, USA
| | | | - Susan T Weintraub
- Department of Biochemistry and Structural Biology, University of Texas Health Science Center San Antonio, UT Health, 7703 Floyd Curl Drive, San Antonio, TX, 78229-3900, USA
| | - Charles Pineau
- University of Rennes, Inserm, EHESP, IREST, UMR_S 1085, F-35042, Rennes, France
| | - Ulrike Kusebauch
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA, 98109, USA
| | - Robert L Moritz
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA, 98109, USA
| | - Seong Beom Ahn
- Faculty of Medicine, Health and Human Sciences, Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, 2109, Australia
| | - Magnus Palmblad
- Leiden University Medical Center, Leiden, 2333, The Netherlands
| | - Michael P Snyder
- Department of Genetics, Stanford School of Medicine, Stanford, CA, 94305, USA
| | - Ruedi Aebersold
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA, 98109, USA
- Faculty of Science, University of Zurich, Zurich, Switzerland
| | - Mark S Baker
- Faculty of Medicine, Health and Human Sciences, Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, 2109, Australia.
- Department of Genetics, Stanford School of Medicine, Stanford, CA, 94305, USA.
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21
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Johnson A, Gnyliukh N, Kaufmann WA, Narasimhan M, Vert G, Bednarek SY, Friml J. Experimental toolbox for quantitative evaluation of clathrin-mediated endocytosis in the plant model Arabidopsis. J Cell Sci 2020; 133:jcs248062. [PMID: 32616560 DOI: 10.1242/jcs.248062] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 06/22/2020] [Indexed: 12/29/2022] Open
Abstract
Clathrin-mediated endocytosis (CME) is a crucial cellular process implicated in many aspects of plant growth, development, intra- and intercellular signaling, nutrient uptake and pathogen defense. Despite these significant roles, little is known about the precise molecular details of how CME functions in planta To facilitate the direct quantitative study of plant CME, we review current routinely used methods and present refined, standardized quantitative imaging protocols that allow the detailed characterization of CME at multiple scales in plant tissues. These protocols include: (1) an efficient electron microscopy protocol for the imaging of Arabidopsis CME vesicles in situ, thus providing a method for the detailed characterization of the ultrastructure of clathrin-coated vesicles; (2) a detailed protocol and analysis for quantitative live-cell fluorescence microscopy to precisely examine the temporal interplay of endocytosis components during single CME events; (3) a semi-automated analysis to allow the quantitative characterization of global internalization of cargos in whole plant tissues; and (4) an overview and validation of useful genetic and pharmacological tools to interrogate the molecular mechanisms and function of CME in intact plant samples.This article has an associated First Person interview with the first author of the paper.
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Affiliation(s)
- Alexander Johnson
- Institute of Science and Technology Austria, 3400 Klosterneuburg, Austria
| | - Nataliia Gnyliukh
- Institute of Science and Technology Austria, 3400 Klosterneuburg, Austria
| | - Walter A Kaufmann
- Institute of Science and Technology Austria, 3400 Klosterneuburg, Austria
| | | | - Grégory Vert
- Plant Science Research Laboratory (LRSV), UMR5546 CNRS/Université Toulouse 3, 24 chemin de Borde Rouge, 31320 Auzeville Tolosane, France
| | | | - Jiří Friml
- Institute of Science and Technology Austria, 3400 Klosterneuburg, Austria
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22
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Lima WC, Gasteiger E, Marcatili P, Duek P, Bairoch A, Cosson P. The ABCD database: a repository for chemically defined antibodies. Nucleic Acids Res 2020; 48:D261-D264. [PMID: 31410491 PMCID: PMC6943046 DOI: 10.1093/nar/gkz714] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 08/01/2019] [Accepted: 08/05/2019] [Indexed: 12/11/2022] Open
Abstract
The ABCD (for AntiBodies Chemically Defined) database is a repository of sequenced antibodies, integrating curated information about the antibody and its antigen with cross-links to standardized databases of chemical and protein entities. It is freely available to the academic community, accessible through the ExPASy server (https://web.expasy.org/abcd/). The ABCD database aims at helping to improve reproducibility in academic research by providing a unique, unambiguous identifier associated to each antibody sequence. It also allows to determine rapidly if a sequenced antibody is available for a given antigen.
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Affiliation(s)
- Wanessa C Lima
- Geneva Antibody Facility, Faculty of Medicine, University of Geneva, CH-1211 Geneva, Switzerland
| | - Elisabeth Gasteiger
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
| | - Paolo Marcatili
- Department of Bio and Health Informatics, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark
| | - Paula Duek
- CALIPHO Group, Faculty of Medicine, University of Geneva and SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
| | - Amos Bairoch
- CALIPHO Group, Faculty of Medicine, University of Geneva and SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
| | - Pierre Cosson
- Geneva Antibody Facility, Faculty of Medicine, University of Geneva, CH-1211 Geneva, Switzerland
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23
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FibroAtlas: A Database for the Exploration of Fibrotic Diseases and Their Genes. Cardiol Res Pract 2019; 2019:4237285. [PMID: 32082621 PMCID: PMC7012261 DOI: 10.1155/2019/4237285] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Accepted: 12/06/2019] [Indexed: 12/21/2022] Open
Abstract
Background Fibrosis is a highly dynamic process caused by prolonged injury, deregulation of the normal processes of wound healing, and extensive deposition of extracellular matrix (ECM) proteins. During fibrosis process, multiple genes interact with environmental factors. Over recent decades, tons of fibrosis-related genes have been identified to shed light on the particular clinical manifestations of this complex process. However, the genetics information about fibrosis is dispersed in lots of extensive literature. Methods We extracted data from literature abstracts in PubMed by text mining, and manually curated the literature and identified the evidence sentences. Results We presented FibroAtlas, which included 1,439 well-annotated fibrosis-associated genes. FibroAtlas 1.0 is the first attempt to build a nonredundant and comprehensive catalog of fibrosis-related genes with supporting evidence derived from curated published literature and allows us to have an overview of human fibrosis-related genes.
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24
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Danquah BD, Yefremova Y, Opuni KFM, Röwer C, Koy C, Glocker MO. Intact Transition Epitope Mapping - Thermodynamic Weak-force Order (ITEM - TWO). J Proteomics 2019; 212:103572. [PMID: 31683061 DOI: 10.1016/j.jprot.2019.103572] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 10/25/2019] [Accepted: 10/27/2019] [Indexed: 01/17/2023]
Abstract
We have developed an electrospray mass spectrometry method which is capable to determine antibody affinity in a gas phase experiment. A solution with the immune complex is electrosprayed and multiply charged ions are translated into the gas phase. Then, the intact immune-complex ions are separated from unbound peptide ions. Increasing the voltage difference in a collision cell results in collision induced dissociation of the immune-complex by which bound peptide ions are released. When analyzing a peptide mixture, measuring the mass of the complex-released peptide ions identifies which of the peptides contains the epitope. A step-wise increase in the collision cell voltage difference changes the intensity ratios of the surviving immune complex ions, the released peptide ions, and the antibody ions. From all the ions´ normalized intensity ratios are deduced the thermodynamic quasi equilibrium dissociation constants (KDm0g#) from which are calculated the apparent gas phase Gibbs energies of activation over temperature (ΔGm0g#T). The order of the apparent gas phase dissociation constants of four antibody - epitope peptide pairs matched well with those obtained from in-solution measurements. The determined gas phase values for antibody affinities are independent from the source of the investigated peptides and from the applied instrument. Data are available via ProteomeXchange with identifier PXD016024. SIGNIFICANCE: ITEM - TWO enables rapid epitope mapping and determination of apparent dissociation energies of immune complexes with minimal in-solution handling. Mixing of antibody and antigen peptide solutions initiates immune complex formation in solution. Epitope binding strengths are determined in the gas phase after electrospraying the antibody / antigen peptide mixtures and mass spectrometric analysis of immune complexes under different collision induced dissociation conditions. Since the order of binding strengths in the gas phase is the same as that in solution, ITEM - TWO characterizes two most important antibody properties, specificity and affinity.
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Affiliation(s)
- Bright D Danquah
- Proteome Center Rostock, University Medicine Rostock, Rostock, Germany
| | - Yelena Yefremova
- Proteome Center Rostock, University Medicine Rostock, Rostock, Germany
| | | | - Claudia Röwer
- Proteome Center Rostock, University Medicine Rostock, Rostock, Germany
| | - Cornelia Koy
- Proteome Center Rostock, University Medicine Rostock, Rostock, Germany
| | - Michael O Glocker
- Proteome Center Rostock, University Medicine Rostock, Rostock, Germany.
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25
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Kalina T, Lundsten K, Engel P. Relevance of Antibody Validation for Flow Cytometry. Cytometry A 2019; 97:126-136. [DOI: 10.1002/cyto.a.23895] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2019] [Revised: 07/10/2019] [Accepted: 08/22/2019] [Indexed: 01/01/2023]
Affiliation(s)
- Tomas Kalina
- CLIP‐Childhood Leukemia Investigation Prague, Department of Pediatric Hematology and Oncology, 2nd Medical SchoolCharles University and University Hospital Motol Prague Czech Republic
| | | | - Pablo Engel
- Department of Biomedical SciencesFaculty of Medicine and Health Sciences, University of Barcelona Barcelona Spain
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26
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Steentoft C, Yang Z, Wang S, Ju T, Vester-Christensen MB, Festari MF, King SL, Moremen K, Larsen ISB, Goth CK, Schjoldager KT, Hansen L, Bennett EP, Mandel U, Narimatsu Y. A validated collection of mouse monoclonal antibodies to human glycosyltransferases functioning in mucin-type O-glycosylation. Glycobiology 2019; 29:645-656. [PMID: 31172184 PMCID: PMC6704369 DOI: 10.1093/glycob/cwz041] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 05/16/2019] [Accepted: 05/29/2019] [Indexed: 01/09/2023] Open
Abstract
Complex carbohydrates serve a wide range of biological functions in cells and tissues, and their biosynthesis involves more than 200 distinct glycosyltransferases (GTfs) in human cells. The kinetic properties, cellular expression patterns and subcellular topology of the GTfs direct the glycosylation capacity of a cell. Most GTfs are ER or Golgi resident enzymes, and their specific subcellular localization is believed to be distributed in the secretory pathway according to their sequential role in the glycosylation process, although detailed knowledge for individual enzymes is still highly fragmented. Progress in quantitative transcriptome and proteome analyses has greatly advanced our understanding of the cellular expression of this class of enzymes, but availability of appropriate antibodies for in situ monitoring of expression and subcellular topology have generally been limited. We have previously used catalytically active GTfs produced as recombinant truncated secreted proteins in insect cells for generation of mouse monoclonal antibodies (mAbs) to human enzymes primarily involved in mucin-type O-glycosylation. These mAbs can be used to probe subcellular topology of active GTfs in cells and tissues as well as their presence in body fluids. Here, we present several new mAbs to human GTfs and provide a summary of our entire collection of mAbs, available to the community. Moreover, we present validation of specificity for many of our mAbs using human cell lines with CRISPR/Cas9 or zinc finger nuclease (ZFN) knockout and knockin of relevant GTfs.
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Affiliation(s)
- Catharina Steentoft
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
| | - Zhang Yang
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
| | - Shengjun Wang
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
- School of Pharmaceutical Sciences, Sun Yat-Sen University, 132 East Circle at University City, Guangzhou 510006, China
| | - Tongzhong Ju
- Department of Biochemistry, Emory University School of Medicine, 201 Dowman Drive, Atlanta, GA 30322, USA
- Office of Biotechnology Products, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA
| | - Malene B Vester-Christensen
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
- Mammalian Expression, Novo Nordisk A/S, Novo Nordisk Park 1, DK-2760 Måløv, Denmark
| | - María F Festari
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
- Departamento de Inmunobiología, Facultad de Medicina, Universidad de la República, Avenida Gral. Flores 2125, Montevideo 11800, Uruguay
| | - Sarah L King
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
| | - Kelley Moremen
- Department of Biochemistry and Molecular Biology, University of Georgia, B122 Life Sciences Bldg., Athens, GA, 30602, USA
| | - Ida S B Larsen
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
| | - Christoffer K Goth
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
| | - Katrine T Schjoldager
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
| | - Lars Hansen
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
| | - Eric P Bennett
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
| | - Ulla Mandel
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
| | - Yoshiki Narimatsu
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and Odontology, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark
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27
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Wang X, Diao L, Sun D, Wang D, Zhu J, He Y, Liu Y, Xu H, Zhang Y, Liu J, Wang Y, He F, Li Y, Li D. OsteoporosAtlas: a human osteoporosis-related gene database. PeerJ 2019; 7:e6778. [PMID: 31086734 PMCID: PMC6487800 DOI: 10.7717/peerj.6778] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Accepted: 03/13/2019] [Indexed: 01/12/2023] Open
Abstract
Background Osteoporosis is a common, complex disease of bone with a strong heritable component, characterized by low bone mineral density, microarchitectural deterioration of bone tissue and an increased risk of fracture. Due to limited drug selection for osteoporosis and increasing morbidity, mortality of osteoporotic fractures, osteoporosis has become a major health burden in aging societies. Current researches for identifying specific loci or genes involved in osteoporosis contribute to a greater understanding of the pathogenesis of osteoporosis and the development of better diagnosis, prevention and treatment strategies. However, little is known about how most causal genes work and interact to influence osteoporosis. Therefore, it is greatly significant to collect and analyze the studies involved in osteoporosis-related genes. Unfortunately, the information about all these osteoporosis-related genes is scattered in a large amount of extensive literature. Currently, there is no specialized database for easily accessing relevant information about osteoporosis-related genes and miRNAs. Methods We extracted data from literature abstracts in PubMed by text-mining and manual curation. Moreover, a local MySQL database containing all the data was developed with PHP on a Windows server. Results OsteoporosAtlas (http://biokb.ncpsb.org/osteoporosis/), the first specialized database for easily accessing relevant information such as osteoporosis-related genes and miRNAs, was constructed and served for researchers. OsteoporosAtlas enables users to retrieve, browse and download osteoporosis-related genes and miRNAs. Gene ontology and pathway analyses were integrated into OsteoporosAtlas. It currently includes 617 human encoding genes, 131 human non-coding miRNAs, and 128 functional roles. We think that OsteoporosAtlas will be an important bioinformatics resource to facilitate a better understanding of the pathogenesis of osteoporosis and developing better diagnosis, prevention and treatment strategies.
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Affiliation(s)
- Xun Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Lihong Diao
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Dezhi Sun
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Dan Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Jiarun Zhu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China.,College of life Sciences, Hebei University, Baoding, China
| | - Yangzhige He
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China.,Central Research Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuan Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Hao Xu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Yi Zhang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China.,College of life Sciences, Hebei University, Baoding, China
| | - Jinying Liu
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Yan Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Fuchu He
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Yang Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
| | - Dong Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing, China
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28
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Gabdank I, Chan ET, Davidson JM, Hilton JA, Davis CA, Baymuradov UK, Narayanan A, Onate KC, Graham K, Miyasato SR, Dreszer TR, Strattan JS, Jolanki O, Tanaka FY, Hitz BC, Sloan CA, Cherry JM. Prevention of data duplication for high throughput sequencing repositories. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2018; 2018:4913687. [PMID: 29688363 PMCID: PMC5829560 DOI: 10.1093/database/bay008] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Accepted: 01/10/2018] [Indexed: 01/01/2023]
Abstract
Database URL https://www.encodeproject.org/.
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Affiliation(s)
- Idan Gabdank
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Esther T Chan
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Jean M Davidson
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Jason A Hilton
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Carrie A Davis
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | | | - Aditi Narayanan
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Kathrina C Onate
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Keenan Graham
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Stuart R Miyasato
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Timothy R Dreszer
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - J Seth Strattan
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Otto Jolanki
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Forrest Y Tanaka
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Benjamin C Hitz
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - Cricket A Sloan
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
| | - J Michael Cherry
- Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA
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Liu J, Liu Y, Wang D, He M, Diao L, Liu Z, Li Y, Tang L, He F, Li D, Guo S. AllerGAtlas 1.0: a human allergy-related genes database. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2018; 2018:4904120. [PMID: 29688358 PMCID: PMC5824776 DOI: 10.1093/database/bay010] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Accepted: 01/15/2018] [Indexed: 12/25/2022]
Abstract
Allergy is a detrimental hypersensitive response to innocuous environmental antigen, which is caused by the effect of interaction between environmental factors and multiple genetic pre-disposition. In the past decades, hundreds of allergy-related genes have been identified to illustrate the epidemiology and pathogenesis of allergic diseases, which are associated with better endophenotype, novel biomarkers, early-life risk factors and individual differences in treatment responses. However, the information of all these allergy-related genes is dispersed in thousands of publications. Here, we present a manually curated human allergy-related gene database of AllerGAtlas, which contained 1195 well-annotated human allergy-related genes, determined by text-mining and manual curation. AllerGAtlas will be a valuable bioinformatics resource to search human allergy-related genes and explore their functions in allergy for experimental research. Database URL: http://biokb.ncpsb.org/AlleRGatlas/
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Affiliation(s)
- Jinying Liu
- School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Yuan Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing, China
| | - Dan Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing, China
| | - Mengqi He
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing, China
| | - Lihong Diao
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing, China
| | - Zhongyang Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing, China
| | - Yang Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing, China
| | - Li Tang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing, China
| | - Fuchu He
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing, China
| | - Dong Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing, China
| | - Shuzhen Guo
- School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
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30
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Enhanced validation of antibodies for research applications. Nat Commun 2018; 9:4130. [PMID: 30297845 PMCID: PMC6175901 DOI: 10.1038/s41467-018-06642-y] [Citation(s) in RCA: 69] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Accepted: 09/04/2018] [Indexed: 01/24/2023] Open
Abstract
There is a need for standardized validation methods for antibody specificity and selectivity. Recently, five alternative validation pillars were proposed to explore the specificity of research antibodies using methods with no need for prior knowledge about the protein target. Here, we show that these principles can be used in a streamlined manner for enhanced validation of research antibodies in Western blot applications. More than 6,000 antibodies were validated with at least one of these strategies involving orthogonal methods, genetic knockdown, recombinant expression, independent antibodies, and capture mass spectrometry analysis. The results show a path forward for efforts to validate antibodies in an application-specific manner suitable for both providers and users.
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31
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Hannigan MM, Zagore LL, Licatalosi DD. Mapping transcriptome-wide protein-RNA interactions to elucidate RNA regulatory programs. QUANTITATIVE BIOLOGY 2018; 6:228-238. [PMID: 31098334 PMCID: PMC6516777 DOI: 10.1007/s40484-018-0145-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2018] [Revised: 03/27/2018] [Accepted: 04/03/2018] [Indexed: 12/12/2022]
Abstract
BACKGROUND Our understanding of post-transcriptional gene regulation has increased exponentially with the development of robust methods to define protein-RNA interactions across the transcriptome. In this review, we highlight the evolution and successful applications of crosslinking and immunoprecipitation (CLIP) methods to interrogate protein-RNA interactions in a transcriptome-wide manner. RESULTS Here, we survey the vast array of in vitro and in vivo approaches used to identify protein-RNA interactions, including but not limited to electrophoretic mobility shift assays, systematic evolution of ligands by exponential enrichment (SELEX), and RIP-seq. We particularly emphasize the advancement of CLIP technologies, and detail protocol improvements and computational tools used to analyze the output data. Importantly, we discuss how profiling protein-RNA interactions can delineate biological functions including splicing regulation, alternative polyadenylation, cytoplasmic decay substrates, and miRNA targets. CONCLUSIONS In summary, this review summarizes the benefits of characterizing RNA-protein networks to further understand the regulation of gene expression and disease pathogenesis. Our review comments on how future CLIP technologies can be adapted to address outstanding questions related to many aspects of RNA metabolism and further advance our understanding of RNA biology.
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Affiliation(s)
- Molly M Hannigan
- Center for RNA Science and Therapeutics, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Leah L Zagore
- Center for RNA Science and Therapeutics, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Donny D Licatalosi
- Center for RNA Science and Therapeutics, Case Western Reserve University, Cleveland, OH 44106, USA
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32
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Alexander SPH, Roberts RE, Broughton BRS, Sobey CG, George CH, Stanford SC, Cirino G, Docherty JR, Giembycz MA, Hoyer D, Insel PA, Izzo AA, Ji Y, MacEwan DJ, Mangum J, Wonnacott S, Ahluwalia A. Goals and practicalities of immunoblotting and immunohistochemistry: A guide for submission to the British Journal of Pharmacology. Br J Pharmacol 2018; 175:407-411. [PMID: 29350411 DOI: 10.1111/bph.14112] [Citation(s) in RCA: 595] [Impact Index Per Article: 99.2] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Yong Ji
- British Journal of Pharmacology, London, UK
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33
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Goodman SL. The path to VICTORy - a beginner's guide to success using commercial research antibodies. J Cell Sci 2018; 131:131/10/jcs216416. [PMID: 29764917 DOI: 10.1242/jcs.216416] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Commercial research antibodies are crucial tools in modern cell biology and biochemistry. In the USA some $2 billion a year are spent on them, but many are apparently not fit-for-purpose, and this may contribute to the 'reproducibility crisis' in biological sciences. Inadequate antibody validation and characterization, lack of user awareness, and occasional incompetence amongst suppliers have had immense scientific and personal costs. In this Opinion, I suggest some paths to make the use of these vital tools more successful. I have attempted to summarize and extend expert views from the literature to suggest that sustained routine efforts should made in: (1) the validation of antibodies, (2) their identification, (3) communication and controls, (4) the training of potential users, (5) the transparency of original equipment manufacturer (OEM) marketing agreements, and (5) in a more widespread use of recombinant antibodies (together denoted the 'VICTOR' approach).
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34
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Poetz O, Dieze T, Hammer H, Weiß F, Sommersdorf C, Templin MF, Esdar C, Zimmermann A, Stevanovic S, Bedke J, Stenzl A, Joos TO. Peptide-Based Sandwich Immunoassay for the Quantification of the Membrane Transporter Multidrug Resistance Protein 1. Anal Chem 2018; 90:5788-5794. [DOI: 10.1021/acs.analchem.8b00152] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Affiliation(s)
- Oliver Poetz
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Markwiesenstrasse 55, 72770 Reutlingen, Germany
- SIGNATOPE GmbH Markwiesenstrasse 55, 72770 Reutlingen, Germany
| | - Theresa Dieze
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Markwiesenstrasse 55, 72770 Reutlingen, Germany
| | - Helen Hammer
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Markwiesenstrasse 55, 72770 Reutlingen, Germany
- SIGNATOPE GmbH Markwiesenstrasse 55, 72770 Reutlingen, Germany
| | - Frederik Weiß
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Markwiesenstrasse 55, 72770 Reutlingen, Germany
- SIGNATOPE GmbH Markwiesenstrasse 55, 72770 Reutlingen, Germany
| | - Cornelia Sommersdorf
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Markwiesenstrasse 55, 72770 Reutlingen, Germany
- SIGNATOPE GmbH Markwiesenstrasse 55, 72770 Reutlingen, Germany
| | - Markus F. Templin
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Markwiesenstrasse 55, 72770 Reutlingen, Germany
| | - Christina Esdar
- Merck KGaA, Frankfurter Strasse 250, 64293 Darmstadt, Germany
| | | | - Stefan Stevanovic
- Eberhard Karls University, Department of Immunology, 72076 Tübingen, Germany
| | - Jens Bedke
- Eberhard Karls University, Department of Urology, 72076 Tübingen, Germany
| | - Arnulf Stenzl
- Eberhard Karls University, Department of Urology, 72076 Tübingen, Germany
| | - Thomas O. Joos
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Markwiesenstrasse 55, 72770 Reutlingen, Germany
- SIGNATOPE GmbH Markwiesenstrasse 55, 72770 Reutlingen, Germany
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35
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Opuni KFM, Al-Majdoub M, Yefremova Y, El-Kased RF, Koy C, Glocker MO. Mass spectrometric epitope mapping. MASS SPECTROMETRY REVIEWS 2018; 37:229-241. [PMID: 27403762 DOI: 10.1002/mas.21516] [Citation(s) in RCA: 70] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Accepted: 06/23/2016] [Indexed: 06/06/2023]
Abstract
Mass spectrometric epitope mapping has become a versatile method to precisely determine a soluble antigen's partial structure that directly interacts with an antibody in solution. Typical lengths of investigated antigens have increased up to several 100 amino acids while experimentally determined epitope peptides have decreased in length to on average 10-15 amino acids. Since the early 1990s more and more sophisticated methods have been developed and have forwarded a bouquet of suitable approaches for epitope mapping with immobilized, temporarily immobilized, and free-floating antibodies. While up to now monoclonal antibodies have been mostly used in epitope mapping experiments, the applicability of polyclonal antibodies has been proven. The antibody's resistance towards enzymatic proteolysis has been of key importance for the two mostly applied methods: epitope excision and epitope extraction. Sample consumption has dropped to low pmol amounts on both, the antigen and the antibody. While adequate in-solution sample handling has been most important for successful epitope mapping, mass spectrometric analysis has been found the most suitable read-out method from early on. The rapidity by which mass spectrometric epitope mapping nowadays is executed outperforms all alternative methods. Thus, it can be asserted that mass spectrometric epitope mapping has reached a state of maturity, which allows it to be used in any mass spectrometry laboratory. After 25 years of constant and steady improvements, its application to clinical samples, for example, for patient characterization and stratification, is anticipated in the near future. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:229-241, 2018.
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Affiliation(s)
- Kwabena F M Opuni
- Proteome Center Rostock, University Medicine and Natural Science Faculty, University of Rostock, Rostock, Germany
| | - Mahmoud Al-Majdoub
- Proteome Center Rostock, University Medicine and Natural Science Faculty, University of Rostock, Rostock, Germany
| | - Yelena Yefremova
- Proteome Center Rostock, University Medicine and Natural Science Faculty, University of Rostock, Rostock, Germany
| | - Reham F El-Kased
- Microbiology and Immunology Faculty of Pharmacy, The British University in Egypt, Cairo, Egypt
| | - Cornelia Koy
- Proteome Center Rostock, University Medicine and Natural Science Faculty, University of Rostock, Rostock, Germany
| | - Michael O Glocker
- Proteome Center Rostock, University Medicine and Natural Science Faculty, University of Rostock, Rostock, Germany
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36
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Webster RP, Cohen CF, Saeed FO, Wetzel HN, Ball WJ, Kirley TL, Norman AB. Evaluation of methods to reduce background using the Python-based ELISA_QC program. J Immunol Methods 2018; 456:61-66. [PMID: 29470976 DOI: 10.1016/j.jim.2018.02.013] [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: 12/04/2017] [Revised: 02/07/2018] [Accepted: 02/16/2018] [Indexed: 11/27/2022]
Abstract
Almost all immunological approaches [immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), Western blot], that are used to quantitate specific proteins have had to address high backgrounds due to non-specific reactivity. We report here for the first time a quantitative comparison of methods for reduction of the background of commercial biotinylated antibodies using the Python-based ELISA_QC program. This is demonstrated using a recombinant humanized anti-cocaine monoclonal antibody. Several approaches, such as adjustment of the incubation time and the concentration of blocking agent, as well as the dilution of secondary antibodies, have been explored to address this issue. In this report, systematic comparisons of two different methods, contrasted with other more traditional methods to address this problem are provided. Addition of heparin (HP) at 1 μg/ml to the wash buffer prior to addition of the secondary biotinylated antibody reduced the elevated background absorbance values (from a mean of 0.313 ± 0.015 to 0.137 ± 0.002). A novel immunodepletion (ID) method also reduced the background (from a mean of 0.331 ± 0.010 to 0.146 ± 0.013). Overall, the ID method generated more similar results at each concentration of the ELISA standard curve to that using the standard lot 1 than the HP method, as analyzed by the Python-based ELISA_QC program. We conclude that the ID method, while more laborious, provides the best solution to resolve the high background seen with specific lots of biotinylated secondary antibody.
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Affiliation(s)
- Rose P Webster
- Department of Pharmacology and Systems Physiology, University of Cincinnati, College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, United States.
| | - Cinder F Cohen
- Department of Pharmacology and Systems Physiology, University of Cincinnati, College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, United States
| | - Fatima O Saeed
- Department of Pharmacology and Systems Physiology, University of Cincinnati, College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, United States
| | - Hanna N Wetzel
- Department of Pharmacology and Systems Physiology, University of Cincinnati, College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, United States
| | - William J Ball
- Department of Pharmacology and Systems Physiology, University of Cincinnati, College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, United States
| | - Terence L Kirley
- Department of Pharmacology and Systems Physiology, University of Cincinnati, College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, United States
| | - Andrew B Norman
- Department of Pharmacology and Systems Physiology, University of Cincinnati, College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, United States
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37
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Brooks HL, Lindsey ML. Guidelines for authors and reviewers on antibody use in physiology studies. Am J Physiol Heart Circ Physiol 2018; 314:H724-H732. [PMID: 29351459 PMCID: PMC6048465 DOI: 10.1152/ajpheart.00512.2017] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Antibody use is a critical component of cardiovascular physiology research, and antibodies are used to monitor protein abundance (immunoblot analysis) and protein expression and localization (in tissue by immunohistochemistry and in cells by immunocytochemistry). With ongoing discussions on how to improve reproducibility and rigor, the goal of this review is to provide best practice guidelines regarding how to optimize antibody use for increased rigor and reproducibility in both immunoblot analysis and immunohistochemistry approaches. Listen to this article’s corresponding podcast at http://ajpheart.podbean.com/e/guidelines-on-antibody-use-in-physiology-studies/.
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Affiliation(s)
- Heddwen L Brooks
- Department of Physiology, Pharmacology and Medicine, Sarver Heart Center, College of Medicine, University of Arizona , Tucson, Arizona
| | - Merry L Lindsey
- Mississippi Center for Heart Research, Department of Physiology and Biophysics, University of Mississippi Medical Center , Jackson, Mississippi.,Research Service, G.V. (Sonny) Montgomery Veterans Affairs Medical Center , Jackson, Mississippi
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38
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Schwenk JM, Omenn GS, Sun Z, Campbell DS, Baker MS, Overall CM, Aebersold R, Moritz RL, Deutsch EW. The Human Plasma Proteome Draft of 2017: Building on the Human Plasma PeptideAtlas from Mass Spectrometry and Complementary Assays. J Proteome Res 2017; 16:4299-4310. [PMID: 28938075 PMCID: PMC5864247 DOI: 10.1021/acs.jproteome.7b00467] [Citation(s) in RCA: 150] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Human blood plasma provides a highly accessible window to the proteome of any individual in health and disease. Since its inception in 2002, the Human Proteome Organization's Human Plasma Proteome Project (HPPP) has been promoting advances in the study and understanding of the full protein complement of human plasma and on determining the abundance and modifications of its components. In 2017, we review the history of the HPPP and the advances of human plasma proteomics in general, including several recent achievements. We then present the latest 2017-04 build of Human Plasma PeptideAtlas, which yields ∼43 million peptide-spectrum matches and 122,730 distinct peptide sequences from 178 individual experiments at a 1% protein-level FDR globally across all experiments. Applying the latest Human Proteome Project Data Interpretation Guidelines, we catalog 3509 proteins that have at least two non-nested uniquely mapping peptides of nine amino acids or more and >1300 additional proteins with ambiguous evidence. We apply the same two-peptide guideline to historical PeptideAtlas builds going back to 2006 and examine the progress made in the past ten years in plasma proteome coverage. We also compare the distribution of proteins in historical PeptideAtlas builds in various RNA abundance and cellular localization categories. We then discuss advances in plasma proteomics based on targeted mass spectrometry as well as affinity assays, which during early 2017 target ∼2000 proteins. Finally, we describe considerations about sample handling and study design, concluding with an outlook for future advances in deciphering the human plasma proteome.
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Affiliation(s)
- Jochen M. Schwenk
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH Royal Institute of Technology, Tomtebodavägen 23, SE-171 65 Solna, Sweden
| | - Gilbert S. Omenn
- Departments of Computational Medicine & Bioinformatics, Internal Medicine, and Human Genetics and School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2218, USA
- Institute for Systems Biology, Seattle, WA, USA
| | - Zhi Sun
- Institute for Systems Biology, Seattle, WA, USA
| | | | - Mark S. Baker
- Department of Biomedical Sciences, Faculty of Medicine and Health Science, Macquarie University, NSW, 2109. Australia
| | - Christopher M. Overall
- Centre for Blood Research, Departments of Oral Biological & Medical Sciences, and Biochemistry & Molecular Biology, Faculty of Dentistry, University of British Columbia, Vancouver, Canada
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
- Faculty of Science, University of Zurich, 8006 Zurich, Switzerland
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39
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Wheeler EC, Van Nostrand EL, Yeo GW. Advances and challenges in the detection of transcriptome-wide protein-RNA interactions. WILEY INTERDISCIPLINARY REVIEWS-RNA 2017; 9. [PMID: 28853213 PMCID: PMC5739989 DOI: 10.1002/wrna.1436] [Citation(s) in RCA: 124] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 06/28/2017] [Accepted: 07/03/2017] [Indexed: 12/14/2022]
Abstract
RNA binding proteins (RBPs) play key roles in determining cellular behavior by manipulating the processing of target RNAs. Robust methods are required to detect the numerous binding sites of RBPs across the transcriptome. RNA‐immunoprecipitation followed by sequencing (RIP‐seq) and crosslinking followed by immunoprecipitation and sequencing (CLIP‐seq) are state‐of‐the‐art methods used to identify the RNA targets and specific binding sites of RBPs. Historically, CLIP methods have been confounded with challenges such as the requirement for tens of millions of cells per experiment, low RNA yields resulting in libraries that contain a high number of polymerase chain reaction duplicated reads, and technical inconveniences such as radioactive labeling of RNAs. However, recent improvements in the recovery of bound RNAs and the efficiency of converting isolated RNAs into a library for sequencing have enhanced our ability to perform the experiment at scale, from less starting material than has previously been possible, and resulting in high quality datasets for the confident identification of protein binding sites. These, along with additional improvements to protein capture, removal of nonspecific signals, and methods to isolate noncanonical RBP targets have revolutionized the study of RNA processing regulation, and reveal a promising future for mapping the human protein‐RNA regulatory network. WIREs RNA 2018, 9:e1436. doi: 10.1002/wrna.1436 This article is categorized under:
RNA Interactions with Proteins and Other Molecules > Protein–RNA Recognition RNA Interactions with Proteins and Other Molecules > Protein–RNA Interactions: Functional Implications RNA Methods > RNA Analyses in Cells
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Affiliation(s)
- Emily C Wheeler
- Department of Cellular and Molecular Medicine, University of California at San Diego, La Jolla, CA, USA.,Stem Cell Program, University of California at San Diego, La Jolla, CA, USA.,Institute for Genomic Medicine, University of California at San Diego, La Jolla, CA, USA
| | - Eric L Van Nostrand
- Department of Cellular and Molecular Medicine, University of California at San Diego, La Jolla, CA, USA.,Stem Cell Program, University of California at San Diego, La Jolla, CA, USA.,Institute for Genomic Medicine, University of California at San Diego, La Jolla, CA, USA
| | - Gene W Yeo
- Department of Cellular and Molecular Medicine, University of California at San Diego, La Jolla, CA, USA.,Stem Cell Program, University of California at San Diego, La Jolla, CA, USA.,Institute for Genomic Medicine, University of California at San Diego, La Jolla, CA, USA.,Molecular Engineering Laboratory, A*STAR, Singapore.,Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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40
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Yefremova Y, Opuni KFM, Danquah BD, Thiesen HJ, Glocker MO. Intact Transition Epitope Mapping (ITEM). JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2017; 28:1612-1622. [PMID: 28616748 DOI: 10.1007/s13361-017-1654-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Revised: 03/06/2017] [Accepted: 03/07/2017] [Indexed: 06/07/2023]
Abstract
Intact transition epitope mapping (ITEM) enables rapid and accurate determination of protein antigen-derived epitopes by either epitope extraction or epitope excision. Upon formation of the antigen peptide-containing immune complex in solution, the entire mixture is electrosprayed to translate all constituents as protonated ions into the gas phase. There, ions from antibody-peptide complexes are separated from unbound peptide ions according to their masses, charges, and shapes either by ion mobility drift or by quadrupole ion filtering. Subsequently, immune complexes are dissociated by collision induced fragmentation and the ion signals of the "complex-released peptides," which in effect are the epitope peptides, are recorded in the time-of-flight analyzer of the mass spectrometer. Mixing of an antibody solution with a solution in which antigens or antigen-derived peptides are dissolved is, together with antigen proteolysis, the only required in-solution handling step. Simplicity of sample handling and speed of analysis together with very low sample consumption makes ITEM faster and easier to perform than other experimental epitope mapping methods. Graphical Abstract ᅟ.
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Affiliation(s)
- Yelena Yefremova
- Proteome Center Rostock, University Medicine Rostock, Schillingallee 69, 18057, Rostock, Germany
| | - Kwabena F M Opuni
- Proteome Center Rostock, University Medicine Rostock, Schillingallee 69, 18057, Rostock, Germany
| | - Bright D Danquah
- Proteome Center Rostock, University Medicine Rostock, Schillingallee 69, 18057, Rostock, Germany
| | - Hans-Juergen Thiesen
- Institute of Immunology, University Medicine Rostock, Schillingallee 70, 18057, Rostock, Germany
| | - Michael O Glocker
- Proteome Center Rostock, University Medicine Rostock, Schillingallee 69, 18057, Rostock, Germany.
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41
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Development of Novel Monoclonal Antibodies for Evaluation of Transmembrane Prostate Androgen-Induced Protein 1 (TMEPAI) Expression Patterns in Gastric Cancer. Pathol Oncol Res 2017; 24:427-438. [DOI: 10.1007/s12253-017-0247-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2017] [Accepted: 04/27/2017] [Indexed: 12/11/2022]
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42
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Reisdorf WC, Chhugani N, Sanseau P, Agarwal P. Harnessing public domain data to discover and validate therapeutic targets. Expert Opin Drug Discov 2017; 12:687-693. [DOI: 10.1080/17460441.2017.1329296] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- William C. Reisdorf
- Computational Biology, Target Sciences, GlaxoSmithKline R&D, King of Prussia, PA, USA
| | - Neha Chhugani
- Jacobs School of Engineering, University of California San Diego, Belle Mead, NJ, USA
| | - Philippe Sanseau
- Computational Biology, Target Sciences, GlaxoSmithKline R&D, Hertfordshire, UK
| | - Pankaj Agarwal
- Computational Biology, Target Sciences, GlaxoSmithKline R&D, King of Prussia, PA, USA
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43
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Abstract
Validation of antibodies is an integral part of translational research, particularly for biomarker discovery. Assaying the specificity of the reagent (antibody) and confirming the identity of the protein biomarker is of critical importance prior to implementing any biomarker in clinical studies, and the lack of such quality control tests may result in unexpected and/or misleading results.Antibody validation is the procedure in which a single antibody is thoroughly assayed for sensitivity and specificity. Although a plethora of commercial antibodies exist, antibody specificity must be extensively demonstrated using diverse complex biological samples, rather than purified recombinant proteins, prior to use in clinical translational research. In the simplest iteration, antibody specificity is determined by the presence of a single band in a complex biological sample, at the expected molecular weight, on a Western blot.To date, numerous Western blotting procedures are available, based on either manual or automated systems and spanning the spectrum of single blots to multiplex blots. X-ray film is still employed in many research laboratories, but digital imaging has become a gold standard in immunoblotting. The basic principles of Western blotting are (a) separation of protein mixtures by gel electrophoresis, (b) transfer of the proteins to a blot, (c) probing the blot for a protein or proteins of interest, and (d) subsequent detection of the protein by chemiluminescent, fluorescent, or colorimetric methods. This chapter focuses on the chemiluminescent detection of proteins using a manual Western blotting system and a vacuum-enhanced detection system (SNAP i.d.™, Millipore).
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Vehus T, Roberg-Larsen H, Waaler J, Aslaksen S, Krauss S, Wilson SR, Lundanes E. Versatile, sensitive liquid chromatography mass spectrometry - Implementation of 10 μm OT columns suitable for small molecules, peptides and proteins. Sci Rep 2016; 6:37507. [PMID: 27897190 PMCID: PMC5126632 DOI: 10.1038/srep37507] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 10/28/2016] [Indexed: 12/14/2022] Open
Abstract
We have designed a versatile and sensitive liquid chromatographic (LC) system, featuring a monolithic trap column and a very narrow (10 μm ID) fused silica open tubular liquid chromatography (OTLC) separation column functionalized with C18-groups, for separating a wide range of molecules (from small metabolites to intact proteins). Compared to today's capillary/nanoLC approaches, our system provides significantly enhanced sensitivity (up to several orders) with matching or improved separation efficiency, and highly repeatable chromatographic performance. The chemical properties of the trap column and the analytical column were fine-tuned to obtain practical sample loading capacities (above 2 μg), an earlier bottleneck of OTLC. Using the OTLC system (combined with Orbitrap mass spectrometry), we could perform targeted metabolomics of sub-μg amounts of exosomes with 25 attogram detection limit of a breast cancer-related hydroxylated cholesterol. With the same set-up, sensitive bottom-up proteomics (targeted and untargeted) was possible, and high-resolving intact protein analysis. In contrast to state-of-the-art packed columns, our platform performs chromatography with very little dilution and is "fit-for-all", well suited for comprehensive analysis of limited samples, and has potential as a tool for challenges in diagnostics.
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Affiliation(s)
- T. Vehus
- Department of Chemistry, University of Oslo, Post Box 1033 Blindern, NO-0315 Oslo, Norway
- Department of Engineering Sciences, University of Agder, Jon Lilletunsvei 9, NO-4891 Grimstad, Norway
| | - H. Roberg-Larsen
- Department of Chemistry, University of Oslo, Post Box 1033 Blindern, NO-0315 Oslo, Norway
| | - J. Waaler
- Unit for Cell Signaling, SFI-CAST Biomedical Innovation Center, Oslo University Hospital, Rikshospitalet, NO-0027 Oslo, Norway
| | - S. Aslaksen
- Unit for Cell Signaling, SFI-CAST Biomedical Innovation Center, Oslo University Hospital, Rikshospitalet, NO-0027 Oslo, Norway
| | - S. Krauss
- Unit for Cell Signaling, SFI-CAST Biomedical Innovation Center, Oslo University Hospital, Rikshospitalet, NO-0027 Oslo, Norway
| | - S. R. Wilson
- Department of Chemistry, University of Oslo, Post Box 1033 Blindern, NO-0315 Oslo, Norway
| | - E. Lundanes
- Department of Chemistry, University of Oslo, Post Box 1033 Blindern, NO-0315 Oslo, Norway
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Treindl F, Ruprecht B, Beiter Y, Schultz S, Döttinger A, Staebler A, Joos TO, Kling S, Poetz O, Fehm T, Neubauer H, Kuster B, Templin MF. A bead-based western for high-throughput cellular signal transduction analyses. Nat Commun 2016; 7:12852. [PMID: 27659302 PMCID: PMC5036152 DOI: 10.1038/ncomms12852] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Accepted: 08/08/2016] [Indexed: 12/28/2022] Open
Abstract
Dissecting cellular signalling requires the analysis of large number of proteins. The DigiWest approach we describe here transfers the western blot to a bead-based microarray platform. By combining gel-based protein separation with immobilization on microspheres, hundreds of replicas of the initial blot are created, thus enabling the comprehensive analysis of limited material, such as cells collected by laser capture microdissection, and extending traditional western blotting to reach proteomic scales. The combination of molecular weight resolution, sensitivity and signal linearity on an automated platform enables the rapid quantification of hundreds of specific proteins and protein modifications in complex samples. This high-throughput western blot approach allowed us to identify and characterize alterations in cellular signal transduction that occur during the development of resistance to the kinase inhibitor Lapatinib, revealing major changes in the activation state of Ephrin-mediated signalling and a central role for p53-controlled processes. Dissecting cellular signalling requires the analysis of large numbers of proteins. Here the authors describe DigiWest, a high-throughput protein detection method that combines the concept of western and widely-used bead array systems that allows rapid quantification of hundreds of specific proteins.
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Affiliation(s)
- Fridolin Treindl
- NMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany.,Pharmaceutical Biotechnology, Eberhard-Karls-Universität Tübingen, Tübingen, 72770 Reutlingen, Germany
| | - Benjamin Ruprecht
- Chair for Proteomics and Bioanalytics, Center of Life and Food Sciences Weihenstephan, Technische Universität München, 85354 Freising, Germany.,Center for Integrated Protein Science Munich, 85354 Freising, Germany
| | - Yvonne Beiter
- NMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany.,Pharmaceutical Biotechnology, Eberhard-Karls-Universität Tübingen, Tübingen, 72770 Reutlingen, Germany
| | - Silke Schultz
- Department of Obstetrics and Gynecology, Medical Faculty and University Hospital of the Heinrich-Heine University Duesseldorf, 40225 Düsseldorf, Germany
| | - Anette Döttinger
- NMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany
| | - Annette Staebler
- Department of Pathology, University Hospital Tübingen, 72076 Tübingen, Germany
| | - Thomas O Joos
- NMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany
| | - Simon Kling
- NMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany
| | - Oliver Poetz
- NMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany
| | - Tanja Fehm
- Department of Obstetrics and Gynecology, Medical Faculty and University Hospital of the Heinrich-Heine University Duesseldorf, 40225 Düsseldorf, Germany
| | - Hans Neubauer
- Department of Obstetrics and Gynecology, Medical Faculty and University Hospital of the Heinrich-Heine University Duesseldorf, 40225 Düsseldorf, Germany
| | - Bernhard Kuster
- Chair for Proteomics and Bioanalytics, Center of Life and Food Sciences Weihenstephan, Technische Universität München, 85354 Freising, Germany.,Center for Integrated Protein Science Munich, 85354 Freising, Germany.,Bavarian Biomolecular Mass Spectrometry Center (BayBioMS), Technische Universität München, 85354 Freising, Germany
| | - Markus F Templin
- NMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany.,Pharmaceutical Biotechnology, Eberhard-Karls-Universität Tübingen, Tübingen, 72770 Reutlingen, Germany
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[Letter to the Editor] The need for improved education and training in research antibody usage and validation practices. Biotechniques 2016; 61:16-8. [PMID: 27401669 DOI: 10.2144/000114431] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Accepted: 04/08/2016] [Indexed: 11/23/2022] Open
Abstract
Address correspondence to Leonard P. Freedman, Global Biological Standards Institute, 1020 19th Street, NW, Suite 550, Washington, DC, 20036. E-mail: lfreedman@gbsi.org.
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Catena R, Özcan A, Jacobs A, Chevrier S, Bodenmiller B. AirLab: a cloud-based platform to manage and share antibody-based single-cell research. Genome Biol 2016; 17:142. [PMID: 27356760 PMCID: PMC4928244 DOI: 10.1186/s13059-016-1006-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2016] [Accepted: 06/10/2016] [Indexed: 11/10/2022] Open
Abstract
Single-cell analysis technologies are essential tools in research and clinical diagnostics. These methods include flow cytometry, mass cytometry, and other microfluidics-based technologies. Most laboratories that employ these methods maintain large repositories of antibodies. These ever-growing collections of antibodies, their multiple conjugates, and the large amounts of data generated in assays using specific antibodies and conditions makes a dedicated software solution necessary. We have developed AirLab, a cloud-based tool with web and mobile interfaces, for the organization of these data. AirLab streamlines the processes of antibody purchase, organization, and storage, antibody panel creation, results logging, and antibody validation data sharing and distribution. Furthermore, AirLab enables inventory of other laboratory stocks, such as primers or clinical samples, through user-controlled customization. Thus, AirLab is a mobile-powered and flexible tool that harnesses the capabilities of mobile tools and cloud-based technology to facilitate inventory and sharing of antibody and sample collections and associated validation data.
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Affiliation(s)
- Raúl Catena
- Institute of Molecular Life Sciences, University of Zürich, Winterthurerstrasse 190, Building/Room: Y11-J-82, CH-8057, Zurich, Switzerland
| | - Alaz Özcan
- Institute of Molecular Life Sciences, University of Zürich, Winterthurerstrasse 190, Building/Room: Y11-J-82, CH-8057, Zurich, Switzerland.,Department of Biology, Biology Master's Program, ETH, Zürich, Switzerland
| | - Andrea Jacobs
- Institute of Molecular Life Sciences, University of Zürich, Winterthurerstrasse 190, Building/Room: Y11-J-82, CH-8057, Zurich, Switzerland
| | - Stephane Chevrier
- Institute of Molecular Life Sciences, University of Zürich, Winterthurerstrasse 190, Building/Room: Y11-J-82, CH-8057, Zurich, Switzerland
| | - Bernd Bodenmiller
- Institute of Molecular Life Sciences, University of Zürich, Winterthurerstrasse 190, Building/Room: Y11-J-82, CH-8057, Zurich, Switzerland.
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Park YN, Glover RA, Daniels KJ, Soll DR. Generation and Validation of Monoclonal Antibodies Against the Maltose Binding Protein. Monoclon Antib Immunodiagn Immunother 2016; 35:104-8. [PMID: 26982821 DOI: 10.1089/mab.2015.0072] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The maltose binding protein (MBP) is a commonly used protein tag. Two monoclonal antibodies (mAbs) were generated against the MBP by immunizing mice with purified 6xHis-tagged MBP (6xHis-MBP). A nontoxic adjuvant cocktail of poly(I:C) and anti-CD40 mAb was used. The two mAbs, 3D7 and 2A1, are demonstrated to be effective in immunoprecipitation, immunoblotting, western blot hybridization, and the ELISA assay. These two mAbs are available individually or in combination at cost through the Developmental Studies Hybridoma Bank, a nonprofit National Resource created by the National Institutes of Health.
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Affiliation(s)
- Yang-Nim Park
- Developmental Studies Hybridoma Bank, The University of Iowa , Iowa City, Iowa
| | - Rebecca A Glover
- Developmental Studies Hybridoma Bank, The University of Iowa , Iowa City, Iowa
| | - Karla J Daniels
- Developmental Studies Hybridoma Bank, The University of Iowa , Iowa City, Iowa
| | - David R Soll
- Developmental Studies Hybridoma Bank, The University of Iowa , Iowa City, Iowa
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Akopyan K, Lindqvist A, Müllers E. Cell Cycle Dynamics of Proteins and Post-translational Modifications Using Quantitative Immunofluorescence. Methods Mol Biol 2016; 1342:173-83. [PMID: 26254923 DOI: 10.1007/978-1-4939-2957-3_9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Immunofluorescence can be a powerful tool to detect protein levels, intracellular localization, and post-translational modifications. However, standard immunofluorescence provides only a still picture and thus lacks temporal information. Here, we describe a method to extract temporal information from immunofluorescence images of fixed cells. In addition, we provide an optional protocol that uses micropatterns, which increases the accuracy of the method. These methods allow assessing how protein levels, intracellular localization, and post-translational modifications change through the cell cycle.
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Affiliation(s)
- Karen Akopyan
- Department of Cell and Molecular Biology, Karolinska Institutet, 285, 171 77, Stockholm, Sweden
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50
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Gibson TJ, Dinkel H, Van Roey K, Diella F. Experimental detection of short regulatory motifs in eukaryotic proteins: tips for good practice as well as for bad. Cell Commun Signal 2015; 13:42. [PMID: 26581338 PMCID: PMC4652402 DOI: 10.1186/s12964-015-0121-y] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Accepted: 11/13/2015] [Indexed: 12/17/2022] Open
Abstract
It has become clear in outline though not yet in detail how cellular regulatory and signalling systems are constructed. The essential machines are protein complexes that effect regulatory decisions by undergoing internal changes of state. Subcomponents of these cellular complexes are assembled into molecular switches. Many of these switches employ one or more short peptide motifs as toggles that can move between one or more sites within the switch system, the simplest being on-off switches. Paradoxically, these motif modules (termed short linear motifs or SLiMs) are both hugely abundant but difficult to research. So despite the many successes in identifying short regulatory protein motifs, it is thought that only the “tip of the iceberg” has been exposed. Experimental and bioinformatic motif discovery remain challenging and error prone. The advice presented in this article is aimed at helping researchers to uncover genuine protein motifs, whilst avoiding the pitfalls that lead to reports of false discovery.
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Affiliation(s)
- Toby J Gibson
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, D69117, Heidelberg, Germany.
| | - Holger Dinkel
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, D69117, Heidelberg, Germany.
| | - Kim Van Roey
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, D69117, Heidelberg, Germany. .,Health Services Research Unit, Operational Direction Public Health and Surveillance, Scientific Institute of Public Health (WIV-ISP), 1050, Brussels, Belgium.
| | - Francesca Diella
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, D69117, Heidelberg, Germany.
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