Metabolic Context Species Interaction Networks
The goal of this project is to generate microbial interaction networks using constraint based metabolic modeling. To do this, MetConSIN uses the dynamic FBA system.
For now, clone from github. We plan to add pip install in the future
MetConSIN requires Gurobi and gurobi's python package. Alternatively, MetConSIN can use the open source CyLP, but this is much slower.
Metconsin also requires numba and cobrapy.
Documentation is being written using Sphinx and saved in the docs folder. To compile the docs, install Sphinx, navigate to the docs folder, and run "make html".
Please see the DOCs. There's a usage page and a tutorial page. Quick start is:
from metconsin import metconsin_sim,save_metconsin
metconsin_return = metconsin_sim(community_members,model_info_file,**kwargs)
save_metconsin(metconsin_return,"results")
You must provide a list of community members and a corresponding file indicating paths to metabolic models for those community members. kwargs include initial conditions, simulation length, simulation resolution, etc.
Dynamic FBA can be written:
where each maximizes
For any value of , we can find a basis
for each organism
such that
where is a function of the constraints of the linear program and furthermore
for for some
.
We can then rewrite the system as
for , so that we have an ODE in that time interval.
MetConSIN interprets these ODEs as networks of interactions, which it builds for later analysis.
James D. Brunner and Nicholas Chia. Minimizing the number of optimizations for efficient community dynamic flux balance analysis. PLOS Computational Biology, 16(9):1-20, 09 2020. doi: 10.1371/journal. pcbi.1007786. Link
- pip installation
Eventually, we plan to develop a rigorous species-species approximation of the ODE networks and characterize the error.
An error-free species-species approximation is possible if we can find a conservation law, meaning we seek matrices such that
so that
and is invertible. This would allow us to write rewrite our system as
Finally, we may evaluate the function
to find metabolically contextualized species interactions.
However, such a conservation law is unlikely to exist, so we seek an approximation with desirable error characteristics.
LANL open source approval reference O4634.
© 2023. Triad National Security, LLC. All rights reserved. This program was produced under U.S. Government contract 89233218CNA000001 for Los Alamos National Laboratory (LANL), which is operated by Triad National Security, LLC for the U.S. Department of Energy/National Nuclear Security Administration. All rights in the program are reserved by Triad National Security, LLC, and the U.S. Department of Energy/National Nuclear Security Administration. The Government is granted for itself and others acting on its behalf a nonexclusive, paid-up, irrevocable worldwide license in this material to reproduce, prepare derivative works, distribute copies to the public, perform publicly and display publicly, and to permit others to do so.