Astron

A biophysical model for studying Ca²⁺-signaling and gliotransmission from astrocytes

This code implements a detailed biophysical model of a single astrocytic compartment/microdomain. The model incorporates multiple molecular components to reproduce mGluR-mediated calcium signaling and calcium-mediated gliotransmitter release from astrocytic microdomains, as observed experimentally.

Calcium signaling components in the model includes:

1. Cytosolic Ca²⁺ buffer
2. PMCA pump
3. ER leak
4. ER Ca²⁺ buffer
5. SERCA
6. IP₃ receptor cluster (using Langevin approx. of Li-Rinzel model)
7. mGluR

Additionally, the model has components involved in the production and degradation of IP₃, and a very detailed framework for Ca²⁺-mediated gliotransmission that includes

1. Synaptotagmins (Syt4 & Syt7)
2. Vesicles (docked & mobile)
3. Vesicle release and recycling

Using the above model of an astrocytic microdomain, we investigated some of the functional consequences of Alzheimer's pathology on astrocytic Ca²⁺ signaling and gliotransmission. The study has been submitted to PloS Computational biology for publication and will be linked here once accepted.

The steps to install the model, run the simulations, analyze data and plot figures in the manuscript are below.

Installation

Linux

Ubuntu 20.04.2.0 LTS

Install project dependencies:

$ sudo apt-get install build-essential
$ sudo apt-get install python3.6

Clone the source locally:

$ git clone https://github.com/anupgp/astron
$ cd astron
$ git submodule update --init --recursive
$ make                                                  

Code organization

The following folders are in the root folder (astron)

• analysis: has all the Python codes for data analysis and visualization
• bin: has the main executable (astron_main) and utility folder.
  • utility: contains executable files for creating various parameter files for stimulating the astrocytic compartments and other accessory. operations
• build: contains all object files.
• doc: extra documentation and/or notes
• include: currently has nothing
• input: parameter files for each molecular component in the model
• lib: Includes all the libraries. - run: has codes to run the simulation in a Linux machine or an HPC managed through PBSPro software.
• src: source codes.
• stimparams: stimulation (DHPG or glutamate release) files.
• validation_data: data for model validation

Usage

Below are the steps to recreate calcium signaling and gliotransmitter release data for validating the model with previous experimental data from astrocytic microdomains (Figures 1 & 3). This is accomplished by stimulating the astrocytic compartment with a single pulse of DHPG (100 μM, 2s). The model is typically run for some time (~200s) until Ca²⁺ and IP₃ levels stabilize.

Step 1: run simulation

Edit the launch script (run/generate_data_dhpg100000nM2s.sh) to specify paths to the root (astron) folder, folder for data storage and path to main executable (astron_main). Leave the rest of the lines unchanged Run the script as below

$ bash run/generate_data_dhpg100000nM2s.sh

The above command will start independent processes, starting from trialstart to trialstop in multiples of 7 (#CPUs/threads available). The later can be changed through jobmax variable in file: run/insilico_single_processor_multiple_runs.sh. The stimulus parameter file (stimparams_dhpg100000nM2s.isfdp) is copied to the data folder before the simulation launch. Visualization of Figures 1 & 3 requires 2400 trials (400 x 6) in total. The data is later split into 6 batches when generating plots with mean and standard error. Each simulation trial is for 300s with DHPG (100 μM, 2s) stimulation applied at time 200s. The integration step is set at 50μs and data is written at every 200 steps. However, each release event will also trigger a data write at that specific simulation time. Data write frequency can be changed through the function: newinsilico::set_observe_step_interval in file: src/astron_main.cpp. Two variables, tstart and tstop in astron_main.cpp file specify the start and end of the simulation times, respectively. A typical trial lasting 300s takes about 15 minutes to complete in a desktop computer.

Step2: analyze data

All the analysis codes are in the analysis folder. Data obtained from the above simulation is analyzed using file: dhpg100000nM2s_analyze_save_cacyt_rel.py. The paths to the raw data and the folder for saving the processed data set need to be correctly specified. The analyzed data is saved in a compressed (HDF5) format and requires several python modules that can be installed with the command below.

$ python3.6 -m pip install numpy pandas matplotlib h5py scipy 

The code needs to be adjusted for the number of trials, batches, simulation start and stop times etc. Finally, the analysis code can be run as below.

$ python3.6 astron/analysis/dhpg100000nM2s_analyze_save_cacyt_rel.py

Step3: visualization

Once the analysis is completed, the data is visualized by running the below python code

$ python3.6 astron/analysis/dhpg100000nM2s_plot_cacyt_rel.py

The above visualization code is organized in sections that correspond to specific figure panels of figures 1 & 3 in the manuscript.

License

This work is licensed under the MIT License.

Written by Dr. Anup Pillai
and Prof. Suhita Nadkarni