RTMet: Real-Time Metabolomics using Mass Spectrometry

🏗 [WORK IN PROGRESS] 🏗

⏱ What is RTMet ?

RTMet is a scientific software which aims to facilitate real-time monitoring of metabolites and reaction rates in a bioreactor.

At its core, it is a data pipeline for targeted metabolomics that automatically processes raw data coming from a mass spectrometer, find metabolites, estimate fluxes, and send a feedback command to the bioreactor.

The main goals are:

• Allowing researchers to monitor in real time what is happening in the bioreactor, at the chemical level.
• Better control over the growth of micro-organisms and the bioprocesses at play, by automatically changing the bioreactor parameters.

⭐️ Planned key features

[🔴Todo] [🟠WIP] [🟢Done]

• 🟠 Automatically fetch .raw files produced by the spectrometer,
• 🟠 Process mass spectrometry data to find present metabolites and quantify them,
• 🔴 Estimate extra-cellular and intra-cellular reaction rates and metabolic fluxes,
• 🟢 Upload results to an InfluxDB instance (optional) to allow real-time plotting and easy query,
• 🔴 Send a feedback command to the bioreactor.

📥 Quick Install

RTMet runs on Unix-like systems including Linux and MacOS.

# Install your favorite conda distribution. We'll choose miniforge
curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh"
bash Miniforge3-$(uname)-$(uname -m).sh

# Download the latest release of RTMet (TODO).
curl -L -O "https://github.com/MetaboHUB-MetaToul-FluxoMet/RTMet/releases/latest/download/workflow.tar.gz"
# Or clone this repository default branch.
git clone https://github.com/MetaboHUB-MetaToul-FluxoMet/RTMet.git
cd RTMet

# Create a symbolic link for Cylc to find the workflow
mkdir ~/cylc-src
ln -s cylc-src/bioreactor-workflow ~/cylc-src/bioreactor-workflow 

# Install Cylc and setup the wrapper scripts
cd cylc-src/bioreactor-workflow/environments
conda env create -f cylc.yml
WRAPPER_DIR='/usr/local/bin' # Or somewhere else in your $PATH
conda activate cylc
cylc get-resources cylc ${WRAPPER_DIR}/cylc
conda deactivate
chmod +x ${WRAPPER_DIR}/cylc
ln -s ${WRAPPER_DIR}/cylc ${WRAPPER_DIR}/rose

# Cylc requires `bash`, GNU `coreutils` and `mail` (optional), which are not installed by Conda.
# You may already have them on your system.
# On MacOS, you can install them using brew.
brew install bash coreutils gnu-sed

# Create Conda environments used by workflow tasks
for file in wf-*.yml; do conda env create -n $env_name -f $file; done
conda activate wf-binner
Rscript -e 'remotes::install_github("aberHRML/binneR")'
conda deactivate

If you plan to use InfluxDB to store and visualize the results, you can find the installation instructions [here] (RTMet documentation, TODO).

📝 Configuration

User configuration is located in the config/ directory of the workflow. User-defined variables can be changed in config.ini:

[template variables]
# Necessary parameters
cfg__mol_database='molecules_db.csv'
cfg__spectrometer_id='orbitrap_01'
cfg__tic_threshold=0.50
cfg__ppm_tol=10

# Optional InfluxDB Setup
cfg__toggle_influxdb=False
...

The file (molecules_db.csv) containing metabolites m/z for ions to be matched against should also be edited depending on the metabolome you study.

🕹 How to use

RTMet uses Cylc as a workflow manager. So launching a run of the workflow (e.g. for a fed-batch run of your bioreactor) is simply launching a run of the bioreactor-workflow with Cylc.

# Validate, install, and run the workflow
cylc vip bioreactor-workflow

It will copy most of the files contained in ~/cylc-src/bioreactor-workflow/ (source directory) to ~/cylc-run/bioreactor-workflow/run1/ (run directory).

You can monitor the workflow using the Cylc GUI or TUI (terminal user interface).

# Launch Jupyter Server and open the GUI in your browser
cylc gui bioreactor-workflow

# Or use the TUI
cylc tui bioreactor-workflow

The workflow is awaiting for .raw files. Right now, it simply looks for them in the raws/ folder of the run directory. The raws files you provide should be numbered that way:

• yourexperimentname_1.raw,
• yourexperimentname_2.raw,
• ...
• yourexperimentname_17.raw
• ...

The workflow will automatically detect the files and process them. Results (metabolites, concentrations, etc) are in share/cycle/N/ of the run directory.

🪲 Bugs and feature requests

If you have an idea on how we could improve RTMet please submit a new issue to our GitHub issue tracker.

🚀 Roadmap

• Implement the automatic polling of the spectrometer computer filesystem for new .raw files,
• Continuous integration with GitHub Actions,
• Try building a Docker image for the whole workflow,
• Validate user input when launching the workflow (and assume it is clean in subsequent tasks),
• ...

📧 Contact

Elliot Fontaine, fontain@insa-toulouse.fr