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Manna S, Ruano CSM, Hegenbarth JC, Vaiman D, Gupta S, McCarthy FP, Méhats C, McCarthy C, Apicella C, Scheel J. Computational Models on Pathological Redox Signalling Driven by Pregnancy: A Review. Antioxidants (Basel) 2022; 11:585. [PMID: 35326235 PMCID: PMC8945226 DOI: 10.3390/antiox11030585] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/15/2022] [Accepted: 03/16/2022] [Indexed: 02/04/2023] Open
Abstract
Oxidative stress is associated with a myriad of diseases including pregnancy pathologies with long-term cardiovascular repercussions for both the mother and baby. Aberrant redox signalling coupled with deficient antioxidant defence leads to chronic molecular impairment. Abnormal placentation has been considered the primary source for reactive species; however, placental dysfunction has been deemed secondary to maternal cardiovascular maladaptation in pregnancy. While various therapeutic interventions, aimed at combating deregulated oxidative stress during pregnancy have shown promise in experimental models, they often result as inconclusive or detrimental in clinical trials, warranting the need for further research to identify candidates. The strengths and limitations of current experimental methods in redox research are discussed. Assessment of redox status and oxidative stress in experimental models and in clinical practice remains challenging; the state-of-the-art of computational models in this field is presented in this review, comparing static and dynamic models which provide functional information such as protein-protein interactions, as well as the impact of changes in molecular species on the redox-status of the system, respectively. Enhanced knowledge of redox biology in during pregnancy through computational modelling such as generation of Systems Biology Markup Language model which integrates existing models to a larger network in the context of placenta physiology.
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Affiliation(s)
- Samprikta Manna
- Department of Obstetrics and Gynaecology, Cork University Maternity Hospital, University College Cork, T12 YE02 Cork, Ireland;
| | - Camino S. M. Ruano
- Institut Cochin, Inserm U1016, UMR8104 CNRS, Université de Paris, 75014 Paris, France; (C.S.M.R.); (D.V.); (C.M.); (C.A.)
| | - Jana-Charlotte Hegenbarth
- Department of Molecular Genetics, Faculty of Science and Engineering, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6211 KH Maastricht, The Netherlands;
- Department of Cardiology, CARIM School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Daniel Vaiman
- Institut Cochin, Inserm U1016, UMR8104 CNRS, Université de Paris, 75014 Paris, France; (C.S.M.R.); (D.V.); (C.M.); (C.A.)
| | - Shailendra Gupta
- Department of Systems Biology and Bioinformatics, Rostock University, 18051 Rostock, Germany; (S.G.); (J.S.)
| | - Fergus P. McCarthy
- Department of Obstetrics and Gynaecology, Cork University Maternity Hospital, University College Cork, T12 YE02 Cork, Ireland;
| | - Céline Méhats
- Institut Cochin, Inserm U1016, UMR8104 CNRS, Université de Paris, 75014 Paris, France; (C.S.M.R.); (D.V.); (C.M.); (C.A.)
| | - Cathal McCarthy
- Department of Pharmacology and Therapeutics, Western Gateway Building, University College Cork, T12 K8AF Cork, Ireland;
| | - Clara Apicella
- Institut Cochin, Inserm U1016, UMR8104 CNRS, Université de Paris, 75014 Paris, France; (C.S.M.R.); (D.V.); (C.M.); (C.A.)
| | - Julia Scheel
- Department of Systems Biology and Bioinformatics, Rostock University, 18051 Rostock, Germany; (S.G.); (J.S.)
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Zobolas J, Touré V, Kuiper M, Vercruysse S. UniBioDicts: Unified access to biological dictionaries. Bioinformatics 2020; 37:143-144. [PMID: 33367853 PMCID: PMC8034525 DOI: 10.1093/bioinformatics/btaa1065] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 11/20/2020] [Accepted: 12/11/2020] [Indexed: 12/03/2022] Open
Abstract
Summary We present a set of software packages that provide uniform access to diverse biological vocabulary resources that are instrumental for current biocuration efforts and tools. The Unified Biological Dictionaries (UniBioDicts or UBDs) provide a single query-interface for accessing the online API services of leading biological data providers. Given a search string, UBDs return a list of matching term, identifier and metadata units from databases (e.g. UniProt), controlled vocabularies (e.g. PSI-MI) and ontologies (e.g. GO, via BioPortal). This functionality can be connected to input fields (user-interface components) that offer autocomplete lookup for these dictionaries. UBDs create a unified gateway for accessing life science concepts, helping curators find annotation terms across resources (based on descriptive metadata and unambiguous identifiers), and helping data users search and retrieve the right query terms. Availability and implementation The UBDs are available through npm and the code is available in the GitHub organisation UniBioDicts (https://github.com/UniBioDicts) under the Affero GPL license. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- John Zobolas
- Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim, NO-7491, Norway
| | - Vasundra Touré
- Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim, NO-7491, Norway
| | - Martin Kuiper
- Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim, NO-7491, Norway
| | - Steven Vercruysse
- Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim, NO-7491, Norway
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