Cargando…

Modelling steroidogenesis: a framework model to support hypothesis generation and testing across endocrine studies

OBJECTIVE: Steroid hormones are responsible for the control of a wide range of physiological processes such as development, growth, reproduction, metabolism, and aging. Because of the variety of enzymes, substrates and products that take part in steroidogenesis and the compartmentalisation of its co...

Descripción completa

Detalles Bibliográficos
Autores principales: O’Hara, Laura, O’Shaughnessy, Peter J., Freeman, Tom C., Smith, Lee B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937803/
https://www.ncbi.nlm.nih.gov/pubmed/29690918
http://dx.doi.org/10.1186/s13104-018-3365-y
_version_ 1783320685157810176
author O’Hara, Laura
O’Shaughnessy, Peter J.
Freeman, Tom C.
Smith, Lee B.
author_facet O’Hara, Laura
O’Shaughnessy, Peter J.
Freeman, Tom C.
Smith, Lee B.
author_sort O’Hara, Laura
collection PubMed
description OBJECTIVE: Steroid hormones are responsible for the control of a wide range of physiological processes such as development, growth, reproduction, metabolism, and aging. Because of the variety of enzymes, substrates and products that take part in steroidogenesis and the compartmentalisation of its constituent reactions, it is a complex process to visualise and document. One of the goals of systems biology is to quantitatively describe the behaviour of complex biological systems that involve the interaction of many components. This can be done by representing these interactions visually in a pathway model and then optionally constructing a mathematical model of the interactions. RESULTS: We have used the modified Edinburgh Pathway Notation to construct a framework diagram describing human steroidogenic pathways, which will be of use to endocrinologists. To demonstrate further utility, we show how such models can be parameterised with empirical data within the software Graphia Professional, to recapitulate specific examples of steroid hormone production, and also to mimic gene knockout. These framework models support in silico hypothesis generation and testing with utility across endocrine endpoints, with significant potential to reduce costs, time and animal numbers, whilst informing the design of planned studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-018-3365-y) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5937803
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-59378032018-05-14 Modelling steroidogenesis: a framework model to support hypothesis generation and testing across endocrine studies O’Hara, Laura O’Shaughnessy, Peter J. Freeman, Tom C. Smith, Lee B. BMC Res Notes Research Note OBJECTIVE: Steroid hormones are responsible for the control of a wide range of physiological processes such as development, growth, reproduction, metabolism, and aging. Because of the variety of enzymes, substrates and products that take part in steroidogenesis and the compartmentalisation of its constituent reactions, it is a complex process to visualise and document. One of the goals of systems biology is to quantitatively describe the behaviour of complex biological systems that involve the interaction of many components. This can be done by representing these interactions visually in a pathway model and then optionally constructing a mathematical model of the interactions. RESULTS: We have used the modified Edinburgh Pathway Notation to construct a framework diagram describing human steroidogenic pathways, which will be of use to endocrinologists. To demonstrate further utility, we show how such models can be parameterised with empirical data within the software Graphia Professional, to recapitulate specific examples of steroid hormone production, and also to mimic gene knockout. These framework models support in silico hypothesis generation and testing with utility across endocrine endpoints, with significant potential to reduce costs, time and animal numbers, whilst informing the design of planned studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-018-3365-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-24 /pmc/articles/PMC5937803/ /pubmed/29690918 http://dx.doi.org/10.1186/s13104-018-3365-y Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Note
O’Hara, Laura
O’Shaughnessy, Peter J.
Freeman, Tom C.
Smith, Lee B.
Modelling steroidogenesis: a framework model to support hypothesis generation and testing across endocrine studies
title Modelling steroidogenesis: a framework model to support hypothesis generation and testing across endocrine studies
title_full Modelling steroidogenesis: a framework model to support hypothesis generation and testing across endocrine studies
title_fullStr Modelling steroidogenesis: a framework model to support hypothesis generation and testing across endocrine studies
title_full_unstemmed Modelling steroidogenesis: a framework model to support hypothesis generation and testing across endocrine studies
title_short Modelling steroidogenesis: a framework model to support hypothesis generation and testing across endocrine studies
title_sort modelling steroidogenesis: a framework model to support hypothesis generation and testing across endocrine studies
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937803/
https://www.ncbi.nlm.nih.gov/pubmed/29690918
http://dx.doi.org/10.1186/s13104-018-3365-y
work_keys_str_mv AT oharalaura modellingsteroidogenesisaframeworkmodeltosupporthypothesisgenerationandtestingacrossendocrinestudies
AT oshaughnessypeterj modellingsteroidogenesisaframeworkmodeltosupporthypothesisgenerationandtestingacrossendocrinestudies
AT freemantomc modellingsteroidogenesisaframeworkmodeltosupporthypothesisgenerationandtestingacrossendocrinestudies
AT smithleeb modellingsteroidogenesisaframeworkmodeltosupporthypothesisgenerationandtestingacrossendocrinestudies