Model

Metabolic Network

The study of metabolic networks is a complex and vast task. Modeling of systems biology helps us better understand metabolic mechanisms and provides essential insights for genetic modifications. We decide to take a gradual approach, starting from global metabolic networks to local metabolic networks, and progressing from flux balance analysis to kinetic simulations. By observing changes in key pathways and products, and adjusting pathways that affect β-Glucan production. Combining both approaches is one of our key highlights, as it strengthens our theoretical foundation and offers essential guidance for selecting targets for wet-lab experiments.

We combine the strengths of both methods, maximizing their advantages for modeling.

1. Global metabolic network: by using flux balance analysis , a computational method based on the steady-state assumption, which enforces that the concentration of each metabolite does not change over time. The system's inputs and outputs remain constant over time, and the net production rate of each metabolite in the network is zero. Its key feature is the ability to handle large-scale computations, though it tends to be relatively rough in detail.
2. Local metabolic networks: by using differential equation analysis, where ordinary differential equations (ODEs) are constructed based on biological rules to calculate changes in substances during reactions. Its key feature is that it provides more detailed calculations, but on a smaller scale.

Molecular Modeling

In the molecular modeling system, we evaluate the stability and activity of the bacterial hemoglobin, Vitreoscillahemoglobin (VHb) with the added cell wall anchoring sequence through molecular docking and molecular dynamics simulations. By continuously troubleshooting, we ultimately screen for the optimal conformation, improving oxygen uptake in our chassis organism. This also provides valuable insights and assistance for future teams that wish to utilize modified VHb.