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Meng W, Fenton CG, Johnsen KM, Taman H, Florholmen J, Paulssen RH. DNA methylation fine-tunes pro-and anti-inflammatory signalling pathways in inactive ulcerative colitis tissue biopsies. Sci Rep 2024; 14:6789. [PMID: 38514698 PMCID: PMC10957912 DOI: 10.1038/s41598-024-57440-0] [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: 10/09/2023] [Accepted: 03/18/2024] [Indexed: 03/23/2024] Open
Abstract
DNA methylation has been implied to play a role in the immune dysfunction associated with inflammatory bowel disease (IBD) and the disease development of ulcerative colitis (UC). Changes of the DNA methylation and correlated gene expression in patient samples with inactive UC might reveal possible regulatory features important for further treatment options for UC. Targeted bisulfite sequencing and whole transcriptome sequencing were performed on mucosal biopsies from patients with active UC (UC, n = 14), inactive UC (RM, n = 20), and non-IBD patients which served as controls (NN, n = 11). The differentially methylated regions (DMRs) were identified by DMRseq. Correlation analysis was performed between DMRs and their nearest differentially expressed genes (DEGs). Principal component analysis (PCA) was performed based on correlated DMR regulated genes. DMR regulated genes then were functional annotated. Cell-type deconvolutions were performed based on methylation levels. The comparisons revealed a total of 38 methylation-regulated genes in inactive UC that are potentially regulated by DMRs (correlation p value < 0.1). Several methylation-regulated genes could be identified in inactive UC participating in IL-10 and cytokine signalling pathways such as IL1B and STAT3. DNA methylation events in inactive UC seem to be fine-tuned by the balancing pro- and anti- inflammatory pathways to maintain a prevailed healing process to restore dynamic epithelium homeostasis.
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Affiliation(s)
- Wei Meng
- Clinical Bioinformatics Research Group, Department of Clinical Medicine, Faculty of Health Sciences, UiT- The Arctic University of Norway, Tromsø, Norway
| | - Christopher G Fenton
- Clinical Bioinformatics Research Group, Department of Clinical Medicine, Faculty of Health Sciences, UiT- The Arctic University of Norway, Tromsø, Norway
- Genomics Support Centre Tromsø, Department of Clinical Medicine, Faculty of Health Sciences, UiT- The Arctic University of Norway, Sykehusveien 44, 9037, Tromsø, Norway
| | - Kay-Martin Johnsen
- Gastroenterology and Nutrition Research Group, Faculty of Health Sciences, UiT- The Arctic University of Norway, Tromsø, Norway
- Department of Medical Gastroenterology, University Hospital of North Norway, Tromsø, Norway
| | - Hagar Taman
- Clinical Bioinformatics Research Group, Department of Clinical Medicine, Faculty of Health Sciences, UiT- The Arctic University of Norway, Tromsø, Norway
- Genomics Support Centre Tromsø, Department of Clinical Medicine, Faculty of Health Sciences, UiT- The Arctic University of Norway, Sykehusveien 44, 9037, Tromsø, Norway
| | - Jon Florholmen
- Gastroenterology and Nutrition Research Group, Faculty of Health Sciences, UiT- The Arctic University of Norway, Tromsø, Norway
- Department of Medical Gastroenterology, University Hospital of North Norway, Tromsø, Norway
| | - Ruth H Paulssen
- Clinical Bioinformatics Research Group, Department of Clinical Medicine, Faculty of Health Sciences, UiT- The Arctic University of Norway, Tromsø, Norway.
- Genomics Support Centre Tromsø, Department of Clinical Medicine, Faculty of Health Sciences, UiT- The Arctic University of Norway, Sykehusveien 44, 9037, Tromsø, Norway.
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2
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Varadi M, Velankar S. The impact of AlphaFold Protein Structure Database on the fields of life sciences. Proteomics 2023; 23:e2200128. [PMID: 36382391 DOI: 10.1002/pmic.202200128] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 09/06/2023]
Abstract
Arguably, 2020 was the year of high-accuracy protein structure predictions, with AlphaFold 2.0 achieving previously unseen accuracy in the Critical Assessment of Protein Structure Prediction (CASP). In 2021, DeepMind and EMBL-EBI developed the AlphaFold Protein Structure Database to make an unprecedented number of reliable protein structure predictions easily accessible to the broad scientific community. We provide a brief overview and describe the latest developments in the AlphaFold database. We highlight how the fields of data services, bioinformatics, structural biology, and drug discovery are directly affected by the influx of protein structure data. We also show examples of cutting-edge research that took advantage of the AlphaFold database. It is apparent that connections between various fields through protein structures are now possible, but the amount of data poses new challenges. Finally, we give an outlook regarding the future direction of the database, both in terms of data sets and new functionalities.
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Affiliation(s)
- Mihaly Varadi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Sameer Velankar
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
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3
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Arguinchona LM, Zagona-Prizio C, Joyce ME, Chan ED, Maloney JP. Microvascular significance of TGF-β axis activation in COVID-19. Front Cardiovasc Med 2023; 9:1054690. [PMID: 36684608 PMCID: PMC9852847 DOI: 10.3389/fcvm.2022.1054690] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 12/09/2022] [Indexed: 01/09/2023] Open
Abstract
As 2023 approaches, the COVID-19 pandemic has killed millions. While vaccines have been a crucial intervention, only a few effective medications exist for prevention and treatment of COVID-19 in breakthrough cases or in unvaccinated or immunocompromised patients. SARS-CoV-2 displays early and unusual features of micro-thrombosis and immune dysregulation that target endothelial beds of the lungs, skin, and other organs. Notably, anticoagulation improves outcomes in some COVID-19 patients. The protein transforming growth factor-beta (TGF-β1) has constitutive roles in maintaining a healthy microvasculature through its roles in regulating inflammation, clotting, and wound healing. However, after infection (including viral infection) TGF-β1 activation may augment coagulation, cause immune dysregulation, and direct a path toward tissue fibrosis. Dysregulation of TGF-β signaling in immune cells and its localization in areas of microvascular injury are now well-described in COVID-19, and such events may contribute to the acute respiratory distress syndrome and skin micro-thrombosis outcomes frequently seen in severe COVID-19. The high concentration of TGF-β in platelets and in other cells within microvascular thrombi, its ability to activate the clotting cascade and dysregulate immune pathways, and its pro-fibrotic properties all contribute to a unique milieu in the COVID-19 microvasculature. This unique environment allows for propagation of microvascular clotting and immune dysregulation. In this review we summarize the physiological functions of TGF-β and detail the evidence for its effects on the microvasculature in COVID-19. In addition, we explore the potential role of existing TGF-β inhibitors for the prevention and treatment of COVID-19 associated microvascular thrombosis and immune dysregulation.
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Affiliation(s)
- Lauren M. Arguinchona
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Caterina Zagona-Prizio
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Megan E. Joyce
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Edward D. Chan
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States,Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO, United States,National Jewish Health, Denver, CO, United States
| | - James P. Maloney
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States,*Correspondence: James P. Maloney,
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4
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Varadi M, Nair S, Sillitoe I, Tauriello G, Anyango S, Bienert S, Borges C, Deshpande M, Green T, Hassabis D, Hatos A, Hegedus T, Hekkelman ML, Joosten R, Jumper J, Laydon A, Molodenskiy D, Piovesan D, Salladini E, Salzberg SL, Sommer MJ, Steinegger M, Suhajda E, Svergun D, Tenorio-Ku L, Tosatto S, Tunyasuvunakool K, Waterhouse AM, Žídek A, Schwede T, Orengo C, Velankar S. 3D-Beacons: decreasing the gap between protein sequences and structures through a federated network of protein structure data resources. Gigascience 2022; 11:giac118. [PMID: 36448847 PMCID: PMC9709962 DOI: 10.1093/gigascience/giac118] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 09/20/2022] [Accepted: 11/11/2022] [Indexed: 12/02/2022] Open
Abstract
While scientists can often infer the biological function of proteins from their 3-dimensional quaternary structures, the gap between the number of known protein sequences and their experimentally determined structures keeps increasing. A potential solution to this problem is presented by ever more sophisticated computational protein modeling approaches. While often powerful on their own, most methods have strengths and weaknesses. Therefore, it benefits researchers to examine models from various model providers and perform comparative analysis to identify what models can best address their specific use cases. To make data from a large array of model providers more easily accessible to the broader scientific community, we established 3D-Beacons, a collaborative initiative to create a federated network with unified data access mechanisms. The 3D-Beacons Network allows researchers to collate coordinate files and metadata for experimentally determined and theoretical protein models from state-of-the-art and specialist model providers and also from the Protein Data Bank.
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Affiliation(s)
- Mihaly Varadi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton CB10 1SA, UK
| | - Sreenath Nair
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton CB10 1SA, UK
| | - Ian Sillitoe
- Department of Structural and Molecular Biology, UCL, London WC1E 6BT, UK
| | - Gerardo Tauriello
- Biozentrum, University of Basel, Basel 4056, Switzerland
- Computational Structural Biology, SIB Swiss Institute of Bioinformatics, Basel 4056, Switzerland
| | - Stephen Anyango
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton CB10 1SA, UK
| | - Stefan Bienert
- Biozentrum, University of Basel, Basel 4056, Switzerland
- Computational Structural Biology, SIB Swiss Institute of Bioinformatics, Basel 4056, Switzerland
| | - Clemente Borges
- Computational Structural Biology, SIB Swiss Institute of Bioinformatics, Basel 4056, Switzerland
- European Molecular Biology Laboratory, EMBL Hamburg, Hamburg 69117, Germany
| | - Mandar Deshpande
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton CB10 1SA, UK
| | | | | | - Andras Hatos
- Department of Biomedical Sciences, University of Padova, Padova 35129, Italy
- Department of Oncology, Lausanne University Hospital, Lausanne 1015, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Swiss Cancer Center Leman, Lausanne 1005, Switzerland
| | - Tamas Hegedus
- Department of Biophysics and Radiation Biology, Semmelweis University, Budapest 1094, Hungary
| | | | - Robbie Joosten
- Netherlands Cancer Institute, Amsterdam 1066 CX, The Netherlands
| | | | | | - Dmitry Molodenskiy
- Computational Structural Biology, SIB Swiss Institute of Bioinformatics, Basel 4056, Switzerland
- European Molecular Biology Laboratory, EMBL Hamburg, Hamburg 69117, Germany
| | - Damiano Piovesan
- Department of Biomedical Sciences, University of Padova, Padova 35129, Italy
| | - Edoardo Salladini
- Department of Biomedical Sciences, University of Padova, Padova 35129, Italy
| | - Steven L Salzberg
- Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Markus J Sommer
- Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Martin Steinegger
- School of Biology, Seoul National University, Seoul 82-2-880-6971, 6977, South Korea
| | - Erzsebet Suhajda
- Department of Biophysics and Radiation Biology, Semmelweis University, Budapest 1094, Hungary
| | - Dmitri Svergun
- Computational Structural Biology, SIB Swiss Institute of Bioinformatics, Basel 4056, Switzerland
- European Molecular Biology Laboratory, EMBL Hamburg, Hamburg 69117, Germany
| | - Luiggi Tenorio-Ku
- Department of Biomedical Sciences, University of Padova, Padova 35129, Italy
| | - Silvio Tosatto
- Department of Biomedical Sciences, University of Padova, Padova 35129, Italy
| | | | - Andrew Mark Waterhouse
- Biozentrum, University of Basel, Basel 4056, Switzerland
- Computational Structural Biology, SIB Swiss Institute of Bioinformatics, Basel 4056, Switzerland
| | | | - Torsten Schwede
- Biozentrum, University of Basel, Basel 4056, Switzerland
- Computational Structural Biology, SIB Swiss Institute of Bioinformatics, Basel 4056, Switzerland
| | - Christine Orengo
- Department of Structural and Molecular Biology, UCL, London WC1E 6BT, UK
| | - Sameer Velankar
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton CB10 1SA, UK
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5
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Chang J, Jiang Z, Ma T, Li J, Chen J, Ye P, Feng L. Integrating transcriptomics and network analysis-based multiplexed drug repurposing to screen drug candidates for M2 macrophage-associated castration-resistant prostate cancer bone metastases. Front Immunol 2022; 13:989972. [PMID: 36389722 PMCID: PMC9643318 DOI: 10.3389/fimmu.2022.989972] [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: 07/09/2022] [Accepted: 10/07/2022] [Indexed: 11/24/2022] Open
Abstract
Metastatic castration-resistant prostate cancer (CRPC) has long been considered to be associated with patient mortality. Among metastatic organs, bone is the most common metastatic site, with more than 90% of advanced patients developing bone metastases (BMs) before 24 months of death. Although patients were recommended to use bone-targeted drugs represented by bisphosphonates to treat BMs of CRPC, there was no significant improvement in patient survival. In addition, the use of immunotherapy and androgen deprivation therapy is limited due to the immunosuppressed state and resistance to antiandrogen agents in patients with bone metastases. Therefore, it is still essential to develop a safe and effective therapeutic schedule for CRPC patients with BMs. To this end, we propose a multiplex drug repurposing scheme targeting differences in patient immune cell composition. The identified drug candidates were ranked from the perspective of M2 macrophages by integrating transcriptome and network-based analysis. Meanwhile, computational chemistry and clinical trials were used to generate a comprehensive drug candidate list for the BMs of CRPC by drug redundancy structure filtering. In addition to docetaxel, which has been approved for clinical trials, the list includes norethindrone, testosterone, menthol and foretinib. This study provides a new scheme for BMs of CRPC from the perspective of M2 macrophages. It is undeniable that this multiplex drug repurposing scheme specifically for immune cell-related bone metastases can be used for drug screening of any immune-related disease, helping clinicians find promising therapeutic schedules more quickly, and providing reference information for drug R&D and clinical trials.
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Varadi M, Anyango S, Appasamy SD, Armstrong D, Bage M, Berrisford J, Choudhary P, Bertoni D, Deshpande M, Leines GD, Ellaway J, Evans G, Gaborova R, Gupta D, Gutmanas A, Harrus D, Kleywegt GJ, Bueno WM, Nadzirin N, Nair S, Pravda L, Afonso MQL, Sehnal D, Tanweer A, Tolchard J, Abrams C, Dunlop R, Velankar S. PDBe and PDBe-KB: Providing high-quality, up-to-date and integrated resources of macromolecular structures to support basic and applied research and education. Protein Sci 2022; 31:e4439. [PMID: 36173162 PMCID: PMC9517934 DOI: 10.1002/pro.4439] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/02/2022] [Accepted: 09/05/2022] [Indexed: 11/26/2022]
Abstract
The archiving and dissemination of protein and nucleic acid structures as well as their structural, functional and biophysical annotations is an essential task that enables the broader scientific community to conduct impactful research in multiple fields of the life sciences. The Protein Data Bank in Europe (PDBe; pdbe.org) team develops and maintains several databases and web services to address this fundamental need. From data archiving as a member of the Worldwide PDB consortium (wwPDB; wwpdb.org), to the PDBe Knowledge Base (PDBe-KB; pdbekb.org), we provide data, data-access mechanisms, and visualizations that facilitate basic and applied research and education across the life sciences. Here, we provide an overview of the structural data and annotations that we integrate and make freely available. We describe the web services and data visualization tools we offer, and provide information on how to effectively use or even further develop them. Finally, we discuss the direction of our data services, and how we aim to tackle new challenges that arise from the recent, unprecedented advances in the field of structure determination and protein structure modeling.
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Affiliation(s)
- Mihaly Varadi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Stephen Anyango
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Sri Devan Appasamy
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - David Armstrong
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Marcus Bage
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - John Berrisford
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Preeti Choudhary
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Damian Bertoni
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Mandar Deshpande
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Grisell Diaz Leines
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Joseph Ellaway
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Genevieve Evans
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Romana Gaborova
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Deepti Gupta
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Aleksandras Gutmanas
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Deborah Harrus
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Gerard J Kleywegt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | | | - Nurul Nadzirin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Sreenath Nair
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Lukas Pravda
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | | | - David Sehnal
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
- CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Ahsan Tanweer
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - James Tolchard
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Charlotte Abrams
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Roisin Dunlop
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
| | - Sameer Velankar
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton
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Peng S, Li J, Huo M, Cao Y, Chen Z, Zhang Y, Qiao Y. Identification of the material basis of the medicinal properties in Curcuma Longa L. to enhance targeted clinical application. JOURNAL OF TRADITIONAL CHINESE MEDICAL SCIENCES 2022. [DOI: 10.1016/j.jtcms.2022.07.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
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