Computational modelling of the glycinergic synapse
type: CreativeWork
description: Glycine is the simplest and smallest amino acid present in human proteins. It has many important roles in human as an intermediate of biosynthetic one carbon metabolism pathways, component of structural proteins, and in the brain acting as the second major inhibitory neurotransmitter via the activation of the glycine receptor (GlyR). Glycinergic neurons are present in various brain regions including the forebrain and the retina, although highest densities can be found in the lower brain regions of the central nervous system (CNS) such as the brain stem, where glycine is important in the regulation of muscle contraction, sensory inputs, and others. Given its diverse role, dysregulation in glycine biosynthesis and neurotranmission is implicated in numerous conditions detrimental to human health such as some subtypes of glioma, as well as genetic diseases caused by mutations to the components of the glycinergic synapse, for instance nonketotic hyperglycinemia (NHK) which leads to severe neurological problems. Moreover, the control of glycine concentration time course via the inhibition of glycine reuptake has been suggested as a potential novel treatment for several conditions, including schizophrenia, alcoholism, and others. In order to advance the understanding of glycine regulation in the human CNS, computational modelling of the various aspects of the glycinergic synapse were deployed. A metabolic model of the CNS was constructed with the use of publicly available databases as a derivation of a generic model of human metabolism, Recon2.2. The experimentally determined value of the human oxygen to glucose index (OGI), indicating glucose brain consumption was used to validate the model via the estimation of the background ATP demand which was similar to that reported in the scientic literature. In order to further contextualise the model to represent CNS metabolism, a method for the integration of single cell RNA-sequencing dataset containing the expression values of…
abstract: Glycine is the simplest and smallest amino acid present in human proteins. It has many important roles in human as an intermediate of biosynthetic one carbon metabolism pathways, component of structural proteins, and in the brain acting as the second major inhibitory neurotransmitter via the activation of the glycine receptor (GlyR). Glycinergic neurons are present in various brain regions including the forebrain and the retina, although highest densities can be found in the lower brain regions of the central nervous system (CNS) such as the brain stem, where glycine is important in the regulation of muscle contraction, sensory inputs, and others. Given its diverse role, dysregulation in glycine biosynthesis and neurotranmission is implicated in numerous conditions detrimental to human health such as some subtypes of glioma, as well as genetic diseases caused by mutations to the components of the glycinergic synapse, for instance nonketotic hyperglycinemia (NHK) which leads to severe neurological problems. Moreover, the control of glycine concentration time course via the inhibition of glycine reuptake has been suggested as a potential novel treatment for several conditions, including schizophrenia, alcoholism, and others. In order to advance the understanding of glycine regulation in the human CNS, computational modelling of the various aspects of the glycinergic synapse were deployed. A metabolic model of the CNS was constructed with the use of publicly available databases as a derivation of a generic model of human metabolism, Recon2.2. The experimentally determined value of the human oxygen to glucose index (OGI), indicating glucose brain consumption was used to validate the model via the estimation of the background ATP demand which was similar to that reported in the scientic literature. In order to further contextualise the model to represent CNS metabolism, a method for the integration of single cell RNA-sequencing dataset containing the expression values of…
author: Al-Saidi, Elzbieta
language: en
date published: 2020
date modified: 2026-07-24T03:43:44Z
provider: Oxford Brookes University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Oxford Brookes University

PropertyValue
property ID: DOI
value: 10.24384/9azb-bb36