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Wolf J, Rasmussen DK, Sun YJ, Vu JT, Wang E, Espinosa C, Bigini F, Chang RT, Montague AA, Tang PH, Mruthyunjaya P, Aghaeepour N, Dufour A, Bassuk AG, Mahajan VB. Liquid-biopsy proteomics combined with AI identifies cellular drivers of eye aging and disease in vivo. Cell 2023; 186:4868-4884.e12. [PMID: 37863056 PMCID: PMC10720485 DOI: 10.1016/j.cell.2023.09.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 07/26/2023] [Accepted: 09/13/2023] [Indexed: 10/22/2023]
Abstract
Single-cell analysis in living humans is essential for understanding disease mechanisms, but it is impractical in non-regenerative organs, such as the eye and brain, because tissue biopsies would cause serious damage. We resolve this problem by integrating proteomics of liquid biopsies with single-cell transcriptomics from all known ocular cell types to trace the cellular origin of 5,953 proteins detected in the aqueous humor. We identified hundreds of cell-specific protein markers, including for individual retinal cell types. Surprisingly, our results reveal that retinal degeneration occurs in Parkinson's disease, and the cells driving diabetic retinopathy switch with disease stage. Finally, we developed artificial intelligence (AI) models to assess individual cellular aging and found that many eye diseases not associated with chronological age undergo accelerated molecular aging of disease-specific cell types. Our approach, which can be applied to other organ systems, has the potential to transform molecular diagnostics and prognostics while uncovering new cellular disease and aging mechanisms.
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Affiliation(s)
- Julian Wolf
- Molecular Surgery Laboratory, Stanford University, Palo Alto, CA 94304, USA; Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA 94304, USA
| | - Ditte K Rasmussen
- Molecular Surgery Laboratory, Stanford University, Palo Alto, CA 94304, USA; Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA 94304, USA; Department of Biomedicine, Aarhus University, 8000 Aarhus C, Denmark
| | - Young Joo Sun
- Molecular Surgery Laboratory, Stanford University, Palo Alto, CA 94304, USA; Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA 94304, USA
| | - Jennifer T Vu
- Molecular Surgery Laboratory, Stanford University, Palo Alto, CA 94304, USA; Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA 94304, USA
| | - Elena Wang
- Molecular Surgery Laboratory, Stanford University, Palo Alto, CA 94304, USA; Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA 94304, USA
| | - Camilo Espinosa
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Fabio Bigini
- Molecular Surgery Laboratory, Stanford University, Palo Alto, CA 94304, USA; Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA 94304, USA
| | - Robert T Chang
- Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA 94304, USA
| | - Artis A Montague
- Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA 94304, USA
| | - Peter H Tang
- Department of Ophthalmology and Visual Neurosciences, University of Minnesota, Minneapolis, MN 55455, USA; Retina Consultants of Minnesota, Edina, MN 55435, USA
| | - Prithvi Mruthyunjaya
- Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA 94304, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Antoine Dufour
- Departments of Physiology and Pharmacology & Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Alexander G Bassuk
- Departments of Pediatrics and Neurology, The Iowa Neuroscience Institute (INI), University of Iowa, Iowa City, IA 52242, USA
| | - Vinit B Mahajan
- Molecular Surgery Laboratory, Stanford University, Palo Alto, CA 94304, USA; Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA 94304, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA.
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2
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Somavarapu AK, Kleijwegt G, Nagaraj M, Alam P, Nielsen J, Otzen DE. Drug repurposing screens identify compounds that inhibit α-synuclein oligomers' membrane disruption and block antibody interactions. Chem Sci 2023; 14:3030-3047. [PMID: 36937574 PMCID: PMC10016340 DOI: 10.1039/d2sc05534a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 02/21/2023] [Indexed: 02/25/2023] Open
Abstract
Small soluble oligomers of the protein α-synuclein (αSO) have been linked to disruptions in neuronal homeostasis, contributing to the development of Parkinson's Disease (PD). While this makes αSO an obvious drug target, the development of effective therapeutics against αSO is challenged by its low abundance and structural and morphological complexity. Here, we employ two different approaches to neutralize toxic interactions made by αSOs with different cellular components. First, we use available data to identify four neuronal proteins as likely candidates for αSO interactions, namely Cfl1, Uchl1, Sirt2 and SerRS. However, despite promising results when immobilized, all 4 proteins only bind weakly to αSO in solution in microfluidic assays, making them inappropriate for screening. In contrast, the formation of stable contacts formed between αSO and vesicles consisting of anionic lipids not only mimics a likely biological role of αSO but also provided a platform to screen two small molecule libraries for disruptors of these contacts. Of the 7 best leads obtained in this way, 2 significantly impaired αSO contacts with other proteins in a sandwich ELISA assay using αSO-binding monoclonal antibodies and nanobodies. In addition, 5 of these leads suppressed α-synuclein amyloid formation. Thus, a repurposing screening that directly targets a key culprit in PD pathogenesis shows therapeutic potential.
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Affiliation(s)
- Arun Kumar Somavarapu
- Interdisciplinary Nanoscience Center (iNANO), Aarhus University Gustav Wieds Vej 14, 8000 Aarhus C Denmark
| | - Giulia Kleijwegt
- Interdisciplinary Nanoscience Center (iNANO), Aarhus University Gustav Wieds Vej 14, 8000 Aarhus C Denmark
| | - Madhu Nagaraj
- Interdisciplinary Nanoscience Center (iNANO), Aarhus University Gustav Wieds Vej 14, 8000 Aarhus C Denmark
| | - Parvez Alam
- Interdisciplinary Nanoscience Center (iNANO), Aarhus University Gustav Wieds Vej 14, 8000 Aarhus C Denmark
| | - Janni Nielsen
- Interdisciplinary Nanoscience Center (iNANO), Aarhus University Gustav Wieds Vej 14, 8000 Aarhus C Denmark
| | - Daniel E Otzen
- Interdisciplinary Nanoscience Center (iNANO), Aarhus University Gustav Wieds Vej 14, 8000 Aarhus C Denmark
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Integrative Proteome Analysis Revels 3-Hydroxybutyrate Exerts Neuroprotective Effect by Influencing Chromatin Bivalency. Int J Mol Sci 2023; 24:ijms24010868. [PMID: 36614311 PMCID: PMC9821512 DOI: 10.3390/ijms24010868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/13/2022] [Accepted: 12/20/2022] [Indexed: 01/05/2023] Open
Abstract
3-hydroxybutyrate (3OHB) has been proved to act as a neuroprotective molecule in multiple neurodegenerative diseases. Here, we employed a quantitative proteomics approach to assess the changes of the global protein expression pattern of neural cells upon 3OHB administration. In combination with a disease-related, protein-protein interaction network we pinpointed a hub marker, histone lysine 27 trimethylation, which is one of the key epigenetic markers in multiple neurodegenerative diseases. Integrative analysis of transcriptomic and epigenomic datasets highlighted the involvement of bivalent transcription factors in 3OHB-mediated disease protection and its alteration of neuronal development processes. Transcriptomic profiling revealed that 3OHB impaired the fate decision process of neural precursor cells by repressing differentiation and promoting proliferation. Our study provides a new mechanism of 3OHB's neuroprotective effect, in which chromatin bivalency is sensitive to 3OHB alteration and drives its neuroprotective function both in neurodegenerative diseases and in neural development processes.
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Cromar GL, Epp JR, Popovic A, Gu Y, Ha V, Walters BJ, St. Pierre J, Xiong X, Howland JG, Josselyn SA, Frankland PW, Parkinson J. Toxoplasma infection in male mice alters dopamine-sensitive behaviors and host gene expression patterns associated with neuropsychiatric disease. PLoS Negl Trop Dis 2022; 16:e0010600. [PMID: 35857765 PMCID: PMC9342775 DOI: 10.1371/journal.pntd.0010600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 08/01/2022] [Accepted: 06/21/2022] [Indexed: 11/18/2022] Open
Abstract
During chronic infection, the single celled parasite, Toxoplasma gondii, can migrate to the brain where it has been associated with altered dopamine function and the capacity to modulate host behavior, increasing risk of neurocognitive disorders. Here we explore alterations in dopamine-related behavior in a new mouse model based on stimulant (cocaine)-induced hyperactivity. In combination with cocaine, infection resulted in heightened sensorimotor deficits and impairment in prepulse inhibition response, which are commonly disrupted in neuropsychiatric conditions. To identify molecular pathways in the brain affected by chronic T. gondii infection, we investigated patterns of gene expression. As expected, infection was associated with an enrichment of genes associated with general immune response pathways, that otherwise limits statistical power to identify more informative pathways. To overcome this limitation and focus on pathways of neurological relevance, we developed a novel context enrichment approach that relies on a customized ontology. Applying this approach, we identified genes that exhibited unexpected patterns of expression arising from the combination of cocaine exposure and infection. These include sets of genes which exhibited dampened response to cocaine in infected mice, suggesting a possible mechanism for some observed behaviors and a neuroprotective effect that may be advantageous to parasite persistence. This model offers a powerful new approach to dissect the molecular pathways by which T. gondii infection contributes to neurocognitive disorders.
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Affiliation(s)
- Graham L. Cromar
- Program in Molecular Medicine, Hospital for Sick Children, Toronto, Canada
| | - Jonathan R. Epp
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
| | - Ana Popovic
- Program in Molecular Medicine, Hospital for Sick Children, Toronto, Canada
- Dept. of Biochemistry, University of Toronto, Toronto, Canada
| | - Yusing Gu
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
| | - Violet Ha
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
| | - Brandon J. Walters
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
| | - James St. Pierre
- Program in Molecular Medicine, Hospital for Sick Children, Toronto, Canada
| | - Xuejian Xiong
- Program in Molecular Medicine, Hospital for Sick Children, Toronto, Canada
| | - John G. Howland
- Dept. of Anatomy, Physiology and Pharmacology, University of Saskatchewan, Saskatoon, Canada
| | - Sheena A. Josselyn
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
- Dept. of Physiology, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
- Dept. of Psychology, University of Toronto, Toronto, Canada
| | - Paul W. Frankland
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
- Dept. of Physiology, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
- Dept. of Psychology, University of Toronto, Toronto, Canada
- * E-mail: (PF); (JP)
| | - John Parkinson
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
- Dept. of Biochemistry, University of Toronto, Toronto, Canada
- Dept. of Molecular Genetics, University of Toronto, Toronto, Canada
- * E-mail: (PF); (JP)
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5
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Identification of Novel Noninvasive Diagnostics Biomarkers in the Parkinson’s Diseases and Improving the Disease Classification Using Support Vector Machine. BIOMED RESEARCH INTERNATIONAL 2022; 2022:5009892. [PMID: 35342758 PMCID: PMC8941533 DOI: 10.1155/2022/5009892] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 02/24/2022] [Indexed: 11/18/2022]
Abstract
Background Parkinson's disease (PD) is a neurological disorder that is marked by the deficit of neurons in the midbrain that changes motor and cognitive function. In the substantia nigra, the selective demise of dopamine-producing neurons was the main cause of this disease. The purpose of this research was to discover genes involved in PD development. Methods In this study, the microarray dataset (GSE22491) provided by GEO was used for further analysis. The Limma package under R software was used to examine and assess gene expression and identify DEGs. The DAVID online tool was used to accomplish GO enrichment analysis and KEGG pathway for DEGs. Furthermore, the PPI network of these DEGs was depicted using the STRING database and analyzed through the Cytoscape to identify hub genes. Support vector machine (SVM) classifier was subsequently employed to predict the accuracy of genes. Result PPI network consisted of 264 nodes as well as 502 edges was generated using the DEGs recognized from the Limma package under the R software. Moreover, three genes were identified as hubs: GNB5, GNG11, and ELANE. By using 3-gene combination, SVM found that prediction accuracy of 88% can be achieved. Conclusion According to the findings of the study, the 3 hub genes GNB5, GNG11, and ELANE may be used as PD detection biomarkers. Moreover, the results obtained from SVM with high accuracy can be considered as PD biomarkers in further investigations.
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Chen GK, Yan Q, Paul KC, Kusters CD, Folle AD, Furlong M, Keener A, Bronstein J, Horvath S, Ritz B. Stochastic Epigenetic Mutations Influence Parkinson's Disease Risk, Progression, and Mortality. JOURNAL OF PARKINSON'S DISEASE 2022; 12:545-556. [PMID: 34842194 PMCID: PMC9076404 DOI: 10.3233/jpd-212834] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Stochastic epigenetic mutations (SEM) reflect a deviation from normal site-specific methylation patterns. Epigenetic mutation load (EML) captures the accumulation of SEMs across an individual's genome and may reflect dysfunction of the epigenetic maintenance system in response to epigenetic challenges. OBJECTIVE We investigate whether EML is associated with PD risk and time to events (i.e., death and motor symptom decline). METHODS We employed logistic regression and Cox proportional hazards regression to assess the association between EML and several outcomes. Our analyses are based on 568 PD patients and 238 controls from the Parkinson's disease, Environment and Genes (PEG) study, for whom blood-based methylation data was available. RESULTS We found an association for PD onset and EML in all genes (OR = 1.90; 95%CI 1.52-2.37) and PD-related genes (OR = 1.87; 95%CI 1.50-2.32). EML was also associated with time to a minimum score of 35 points on the motor UPDRS exam (OR = 1.28; 95%CI 1.06-1.56) and time to death (OR = 1.29, 95%CI 1.11-1.49). An analysis of PD related genes only revealed five intragenic hotspots of high SEM density associated with PD risk. CONCLUSION Our findings suggest an enrichment of methylation dysregulation in PD patients in general and specifically in five PD related genes. EML may also be associated with time to death and motor symptom progression in PD patients.
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Affiliation(s)
| | - Qi Yan
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Kimberly C. Paul
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Cynthia D.J. Kusters
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Aline Duarte Folle
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Melissa Furlong
- Department of Community, Environment and Policy, University of Arizona Mel and Enid Zuckerman College of Public Health, Tucson, AZ, USA
| | - Adrienne Keener
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Jeff Bronstein
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA,Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Beate Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA,Correspondence to: Beate Ritz, UCLA, Epidemiology, Box 951772, Los Angeles, CA 90095, USA.
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7
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Kramarz B, Huntley RP, Rodríguez-López M, Roncaglia P, Saverimuttu SCC, Parkinson H, Bandopadhyay R, Martin MJ, Orchard S, Hooper NM, Brough D, Lovering RC. Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer's Disease Gene Expression Data. J Alzheimers Dis 2021; 75:1417-1435. [PMID: 32417785 PMCID: PMC7369085 DOI: 10.3233/jad-200207] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND Gene Ontology (GO) is a major bioinformatic resource used for analysis of large biomedical datasets, for example from genome-wide association studies, applied universally across biological fields, including Alzheimer's disease (AD) research. OBJECTIVE We aim to demonstrate the applicability of GO for interpretation of AD datasets to improve the understanding of the underlying molecular disease mechanisms, including the involvement of inflammatory pathways and dysregulated microRNAs (miRs). METHODS We have undertaken a systematic full article GO annotation approach focused on microglial proteins implicated in AD and the miRs regulating their expression. PANTHER was used for enrichment analysis of previously published AD data. Cytoscape was used for visualizing and analyzing miR-target interactions captured from published experimental evidence. RESULTS We contributed 3,084 new annotations for 494 entities, i.e., on average six new annotations per entity. This included a total of 1,352 annotations for 40 prioritized microglial proteins implicated in AD and 66 miRs regulating their expression, yielding an average of twelve annotations per prioritized entity. The updated GO resource was then used to re-analyze previously published data. The re-analysis showed novel processes associated with AD-related genes, not identified in the original study, such as 'gliogenesis', 'regulation of neuron projection development', or 'response to cytokine', demonstrating enhanced applicability of GO for neuroscience research. CONCLUSIONS This study highlights ongoing development of the neurobiological aspects of GO and demonstrates the value of biocuration activities in the area, thus helping to delineate the molecular bases of AD to aid the development of diagnostic tools and treatments.
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Affiliation(s)
- Barbara Kramarz
- Functional Gene Annotation, Preclinical and Fundamental Science, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Rachael P Huntley
- Functional Gene Annotation, Preclinical and Fundamental Science, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Milagros Rodríguez-López
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Paola Roncaglia
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Shirin C C Saverimuttu
- Functional Gene Annotation, Preclinical and Fundamental Science, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Helen Parkinson
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Rina Bandopadhyay
- UCL Institute of Neurology and Reta Lila Weston Institute of Neurological Studies, University College London, London, UK
| | - Maria-Jesus Martin
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Sandra Orchard
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Nigel M Hooper
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - David Brough
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Ruth C Lovering
- Functional Gene Annotation, Preclinical and Fundamental Science, UCL Institute of Cardiovascular Science, University College London, London, UK
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Breuza L, Arighi CN, Argoud-Puy G, Casals-Casas C, Estreicher A, Famiglietti ML, Georghiou G, Gos A, Gruaz-Gumowski N, Hinz U, Hyka-Nouspikel N, Kramarz B, Lovering RC, Lussi Y, Magrane M, Masson P, Perfetto L, Poux S, Rodriguez-Lopez M, Stoeckert C, Sundaram S, Wang LS, Wu E, Orchard S. A Coordinated Approach by Public Domain Bioinformatics Resources to Aid the Fight Against Alzheimer's Disease Through Expert Curation of Key Protein Targets. J Alzheimers Dis 2020; 77:257-273. [PMID: 32716361 PMCID: PMC7592670 DOI: 10.3233/jad-200206] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/05/2020] [Indexed: 01/08/2023]
Abstract
BACKGROUND The analysis and interpretation of data generated from patient-derived clinical samples relies on access to high-quality bioinformatics resources. These are maintained and updated by expert curators extracting knowledge from unstructured biological data described in free-text journal articles and converting this into more structured, computationally-accessible forms. This enables analyses such as functional enrichment of sets of genes/proteins using the Gene Ontology, and makes the searching of data more productive by managing issues such as gene/protein name synonyms, identifier mapping, and data quality. OBJECTIVE To undertake a coordinated annotation update of key public-domain resources to better support Alzheimer's disease research. METHODS We have systematically identified target proteins critical to disease process, in part by accessing informed input from the clinical research community. RESULTS Data from 954 papers have been added to the UniProtKB, Gene Ontology, and the International Molecular Exchange Consortium (IMEx) databases, with 299 human proteins and 279 orthologs updated in UniProtKB. 745 binary interactions were added to the IMEx human molecular interaction dataset. CONCLUSION This represents a significant enhancement in the expert curated data pertinent to Alzheimer's disease available in a number of biomedical databases. Relevant protein entries have been updated in UniProtKB and concomitantly in the Gene Ontology. Molecular interaction networks have been significantly extended in the IMEx Consortium dataset and a set of reference protein complexes created. All the resources described are open-source and freely available to the research community and we provide examples of how these data could be exploited by researchers.
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Affiliation(s)
- Lionel Breuza
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Cecilia N. Arighi
- Protein Information Resource, Georgetown University Medical Center, Washington, DC, USA
- Protein Information Resource, University of Delaware, Newark, DE, USA
| | - Ghislaine Argoud-Puy
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Cristina Casals-Casas
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Anne Estreicher
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Maria Livia Famiglietti
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - George Georghiou
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, UK
| | - Arnaud Gos
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Nadine Gruaz-Gumowski
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Ursula Hinz
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Nevila Hyka-Nouspikel
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Barbara Kramarz
- Functional Gene Annotation, Preclinical and Fundamental Science, Institute of Cardiovascular Science, University College London (UCL), London, UK
| | - Ruth C. Lovering
- Functional Gene Annotation, Preclinical and Fundamental Science, Institute of Cardiovascular Science, University College London (UCL), London, UK
| | - Yvonne Lussi
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, UK
| | - Michele Magrane
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, UK
| | - Patrick Masson
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Livia Perfetto
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, UK
| | - Sylvain Poux
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Milagros Rodriguez-Lopez
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, UK
| | - Christian Stoeckert
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Shyamala Sundaram
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
| | - Li-San Wang
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Sandra Orchard
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, UK
| | - IMEx Consortium, UniProt Consortium
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
- Protein Information Resource, Georgetown University Medical Center, Washington, DC, USA
- Protein Information Resource, University of Delaware, Newark, DE, USA
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, UK
- Functional Gene Annotation, Preclinical and Fundamental Science, Institute of Cardiovascular Science, University College London (UCL), London, UK
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Alzforum, Cambridge, MA, USA
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Neubrand VE, Forte-Lago I, Caro M, Delgado M. The atypical RhoGTPase RhoE/Rnd3 is a key molecule to acquire a neuroprotective phenotype in microglia. J Neuroinflammation 2018; 15:343. [PMID: 30553270 PMCID: PMC6295018 DOI: 10.1186/s12974-018-1386-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 11/29/2018] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Over-activated microglia play a central role during neuroinflammation, leading to neuronal cell death and neurodegeneration. Reversion of over-activated to neuroprotective microglia phenotype could regenerate a healthy CNS-supporting microglia environment. Our aim was to identify a dataset of intracellular molecules in primary microglia that play a role in the transition of microglia to a ramified, neuroprotective phenotype. METHODS We exploited the anti-inflammatory and neuroprotective properties of conditioned medium of adipose-derived mesenchymal stem cells (CM) as a tool to generate the neuroprotective phenotype of microglia in vitro, and we set up a microscopy-based siRNA screen to identify its hits by cell morphology. RESULTS We initially assayed an array of 157 siRNAs against genes that codify proteins and factors of cytoskeleton and activation/inflammatory pathways in microglia. From them, 45 siRNAs significantly inhibited the CM-induced transition from a neurotoxic to a neuroprotective phenotype of microglia, and 50 siRNAs had the opposite effect. As a proof-of-concept, ten of these targets were validated with individual siRNAs and by downregulation of protein expression. This validation step resulted essential, because three of the potential targets were false positives. The seven validated targets were assayed in a functional screen that revealed that the atypical RhoGTPase RhoE/Rnd3 is necessary for BDNF expression and plays an essential role in controlling microglial migration. CONCLUSIONS Besides the identification of RhoE/Rnd3 as a novel inducer of a potential neuroprotective phenotype in microglia, we propose a list of potential targets to be further confirmed with selective activators or inhibitors.
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Affiliation(s)
- Veronika E Neubrand
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, Avd. Conocimiento 17, PTS Granada, 18016, Granada, Spain.
| | - Irene Forte-Lago
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, Avd. Conocimiento 17, PTS Granada, 18016, Granada, Spain
| | - Marta Caro
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, Avd. Conocimiento 17, PTS Granada, 18016, Granada, Spain
| | - Mario Delgado
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, Avd. Conocimiento 17, PTS Granada, 18016, Granada, Spain.
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Kramarz B, Roncaglia P, Meldal BHM, Huntley RP, Martin MJ, Orchard S, Parkinson H, Brough D, Bandopadhyay R, Hooper NM, Lovering RC. Improving the Gene Ontology Resource to Facilitate More Informative Analysis and Interpretation of Alzheimer's Disease Data. Genes (Basel) 2018; 9:E593. [PMID: 30501127 PMCID: PMC6315915 DOI: 10.3390/genes9120593] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 11/22/2018] [Accepted: 11/23/2018] [Indexed: 12/28/2022] Open
Abstract
The analysis and interpretation of high-throughput datasets relies on access to high-quality bioinformatics resources, as well as processing pipelines and analysis tools. Gene Ontology (GO, geneontology.org) is a major resource for gene enrichment analysis. The aim of this project, funded by the Alzheimer's Research United Kingdom (ARUK) foundation and led by the University College London (UCL) biocuration team, was to enhance the GO resource by developing new neurological GO terms, and use GO terms to annotate gene products associated with dementia. Specifically, proteins and protein complexes relevant to processes involving amyloid-beta and tau have been annotated and the resulting annotations are denoted in GO databases as 'ARUK-UCL'. Biological knowledge presented in the scientific literature was captured through the association of GO terms with dementia-relevant protein records; GO itself was revised, and new GO terms were added. This literature biocuration increased the number of Alzheimer's-relevant gene products that were being associated with neurological GO terms, such as 'amyloid-beta clearance' or 'learning or memory', as well as neuronal structures and their compartments. Of the total 2055 annotations that we contributed for the prioritised gene products, 526 have associated proteins and complexes with neurological GO terms. To ensure that these descriptive annotations could be provided for Alzheimer's-relevant gene products, over 70 new GO terms were created. Here, we describe how the improvements in ontology development and biocuration resulting from this initiative can benefit the scientific community and enhance the interpretation of dementia data.
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Affiliation(s)
- Barbara Kramarz
- UCL Institute of Cardiovascular Science, University College London, Rayne Building, 5 University Street, London WC1E 6JF, UK.
| | - Paola Roncaglia
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
| | - Birgit H M Meldal
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
| | - Rachael P Huntley
- UCL Institute of Cardiovascular Science, University College London, Rayne Building, 5 University Street, London WC1E 6JF, UK.
| | - Maria J Martin
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
| | - Sandra Orchard
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
| | - Helen Parkinson
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
| | - David Brough
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, AV Hill Building, Oxford Road, Manchester M13 9PT, UK.
| | - Rina Bandopadhyay
- UCL Queen Square Institute of Neurology and Reta Lila Weston Institute of Neurological Studies, 1 Wakefield Street, London WC1N 1PJ, UK.
| | - Nigel M Hooper
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, AV Hill Building, Oxford Road, Manchester M13 9PT, UK.
| | - Ruth C Lovering
- UCL Institute of Cardiovascular Science, University College London, Rayne Building, 5 University Street, London WC1E 6JF, UK.
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11
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A workflow for the integrative transcriptomic description of molecular pathology and the suggestion of normalizing compounds, exemplified by Parkinson's disease. Sci Rep 2018; 8:7937. [PMID: 29784986 PMCID: PMC5962550 DOI: 10.1038/s41598-018-25754-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Accepted: 04/06/2018] [Indexed: 12/13/2022] Open
Abstract
The volume of molecular observations on human diseases in public databases is continuously increasing at accelerating rates. A bottleneck is their computational integration into a coherent description, from which researchers may derive new well-founded hypotheses. Also, the need to integrate data from different technologies (genetics, coding and regulatory RNA, proteomics) emerged in order to identify biomarkers for early diagnosis and prognosis of complex diseases and therefore facilitating the development of novel treatment approaches. We propose here a workflow for the integrative transcriptomic description of the molecular pathology in Parkinsons’s Disease (PD), including suggestions of compounds normalizing disease-induced transcriptional changes as a paradigmatic example. We integrated gene expression profiles, miRNA signatures, and publicly available regulatory databases to specify a partial model of the molecular pathophysiology of PD. Six genetic driver elements (2 genes and 4 miRNAs) and several functional network modules that are associated with PD were identified. Functional modules were assessed for their statistical significance, cellular functional homogeneity, literature evidence, and normalizing small molecules. In summary, our workflow for the joint regulatory analysis of coding and non-coding RNA, has the potential to yield clinically as well as biologically relevant information, as demonstrated here on PD data.
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12
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Denny P, Feuermann M, Hill DP, Lovering RC, Plun-Favreau H, Roncaglia P. Exploring autophagy with Gene Ontology. Autophagy 2018; 14:419-436. [PMID: 29455577 PMCID: PMC5915032 DOI: 10.1080/15548627.2017.1415189] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the strategies that cells use to catabolize substances in a controlled way. Autophagy is used for recycling cellular components, responding to cellular stresses and ridding cells of foreign material. Perturbations in autophagy have been implicated in a number of pathological conditions such as neurodegeneration, cardiac disease and cancer. The growing knowledge about autophagic mechanisms needs to be collected in a computable and shareable format to allow its use in data representation and interpretation. The Gene Ontology (GO) is a freely available resource that describes how and where gene products function in biological systems. It consists of 3 interrelated structured vocabularies that outline what gene products do at the biochemical level, where they act in a cell and the overall biological objectives to which their actions contribute. It also consists of ‘annotations’ that associate gene products with the terms. Here we describe how we represent autophagy in GO, how we create and define terms relevant to autophagy researchers and how we interrelate those terms to generate a coherent view of the process, therefore allowing an interoperable description of its biological aspects. We also describe how annotation of gene products with GO terms improves data analysis and interpretation, hence bringing a significant benefit to this field of study.
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Affiliation(s)
- Paul Denny
- a Functional Gene Annotation , Institute of Cardiovascular Science, University College London , London , UK
| | - Marc Feuermann
- b SIB Swiss Institute of Bioinformatics , Geneva , Switzerland
| | - David P Hill
- c The Jackson Laboratory , Bar Harbor , ME , USA.,f The Gene Ontology Consortium
| | - Ruth C Lovering
- a Functional Gene Annotation , Institute of Cardiovascular Science, University College London , London , UK
| | - Helene Plun-Favreau
- d Department of Molecular Neuroscience , UCL Institute of Neurology , London , UK
| | - Paola Roncaglia
- e European Bioinformatics Institute (EMBL-EBI) , European Molecular Biology Laboratory, Wellcome Genome Campus , Hinxton , Cambridge , UK.,f The Gene Ontology Consortium
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13
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Dysregulation of the causative genes for hereditary parkinsonism in the midbrain in Parkinson's disease. Mov Disord 2017; 32:1211-1220. [DOI: 10.1002/mds.27019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2016] [Revised: 02/26/2017] [Accepted: 03/17/2017] [Indexed: 11/07/2022] Open
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Pierce S, Coetzee GA. Parkinson's disease-associated genetic variation is linked to quantitative expression of inflammatory genes. PLoS One 2017; 12:e0175882. [PMID: 28407015 PMCID: PMC5391096 DOI: 10.1371/journal.pone.0175882] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2016] [Accepted: 03/31/2017] [Indexed: 12/11/2022] Open
Abstract
Genome-wide association studies (GWAS) have linked dozens of single nucleotide polymorphisms (SNPs) with Parkinson’s disease (PD) risk. Ascertaining the functional and eventual causal mechanisms underlying these relationships has proven difficult. The majority of risk SNPs, and nearby SNPs in linkage disequilibrium (LD), are found in intergenic or intronic regions and confer risk through allele-dependent expression of multiple unknown target genes. Combining GWAS results with publicly available GTEx data, generated through eQTL (expression quantitative trait loci) identification studies, enables a direct association of SNPs to gene expression levels and aids in narrowing the large population of potential genetic targets for hypothesis-driven experimental cell biology. Separately, overlapping of SNPs with putative enhancer segmentations can strengthen target filtering. We report here the results of analyzing 7,607 PD risk SNPs along with an additional 23,759 high linkage disequilibrium-associated variants paired with eQTL gene expression. We found that enrichment analysis on the set of genes following target filtering pointed to a single large LD block at 6p21 that contained multiple HLA-MHC-II genes. These MHC-II genes remain associated with PD when the genes were filtered for correlation between GWAS significance and eQTL levels, strongly indicating a direct effect on PD etiology.
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Affiliation(s)
- Steven Pierce
- Center for Neurodegenerative Science, Van Andel Research Institute, Grand Rapids, MI, United States
| | - Gerhard A. Coetzee
- Center for Neurodegenerative Science, Van Andel Research Institute, Grand Rapids, MI, United States
- * E-mail:
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15
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Abstract
Collaborations between the scientific community and members of the Gene Ontology (GO) Consortium have led to an increase in the number and specificity of GO terms, as well as increasing the number of GO annotations. A variety of approaches have been taken to encourage research scientists to contribute to the GO, but the success of these approaches has been variable. This chapter reviews both the successes and failures of engaging the scientific community in GO development and annotation, as well as, providing motivation and advice to encourage individual researchers to contribute to GO.
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Affiliation(s)
- Ruth C Lovering
- Functional Gene Annotation Initiative, Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, 5 University Street, London, WC1E 6JF, UK.
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