Sandeep Chenna
The IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2021 provides a leading forum for disseminating the latest research in bioinformatics and health informatics. It brings together academic and industrial scientists from computer science, biology, chemistry, medicine, mathematics and statistics. We solicit high-quality original research papers (including significant work-in-progress) in any aspect of bioinformatics, genomics, and biomedicine.
Mr Sandeep Chenna of the Royal College of Surgeons in Ireland will present a short paper entitled ‘Phenomenological equations for electron transport chain-mediated reactive oxygen species metabolism” at the upcoming IEEE BIBM 2021 – Virtual Conference (9-12 December). This work represents Sandeep’s extension of the PD-MitoQUANT mathematical model and includes ROS production/scavenging.
Why is this study important? Reactive oxygen species (ROS) are a group of small, reactive, chemical molecules. ROS play many important roles in cells when at optimal levels. However, when the levels of ROS increase, they can lead to cellular ‘oxidative’ stress, which is implicated in various disease conditions. We still don’t fully understand the complete ROS lifecycle, and to investigate ROS (such as difficulties distinguishing different ROS types or their site of origin, and varying sensitivity and specificity of different methods). Computational models (mathematical representations of the ROS system) can be used to complement experiments and analyse ROS metabolism in more detail. Aims Computational models can be detailed or minimal, depending on the amount of detail included. Detailed models may be closer representations of the complete biological system, but can be difficult to develop, run, and analyse. Minimal models are simplified representations of the biological system that enable analysis of more general system behaviour in specific contexts. The main advantage of minimal models is that they can be integrated into other models easily. In this paper, to study the production and degradation of ROS in neurodegenerative conditions. There are already detailed models but they are used for different types of studies. What did we do? We had previously developed a computational model of the respiratory chain, theof enzymes responsible for producing adenosine triphosphate (ATP), the primary energy source in our cells. The respiratory chain is one of the main producers of ROS, and is also affected in neurodegenerative disorders like Parkinson’s. Here, we expanded this model to include the production of ROS by the respiratory chain. We first compared the behaviour of our model with known experiments, to ensure the model simulations were representative of the biological system. We then varied some of the parameters in the model to simulate dysfunctional activity observed in neurodegeneration, and monitored how ROS levels were predicted to be altered in these conditions. What did we find? We validated that the model simulations reproduce experimentally observed behaviour in several conditions. We next simulated reduced activity of the enzyme complexes along the respiratory chain, as this has been observed in Parkinson’s disease and other neurodegenerative conditions. The model predicted that reduced activity of the complexes in isolation is not sufficient to cause oxidative stress. In fact, the model predicted that malfunction in the clearance of ROS (ROS ‘scavenging’), rather than in the respiratory chain processes that produce it, are more likely to cause damaging oxidative stress. What does it mean? Our simulations predicted that increased ROS production by the respiratory chain, even in pathological conditions, may not be high enough to directly contribute to neurodegeneration. Nevertheless, the increase in ROS levels may sensitise cells to subsequent stress, or make them particularly vulnerable to failure in any of the mechanisms responsible for clearing ROS.