MetaChat

Brief introduction

MetaChat is a Python package to screen metabolic cell communication (MCC) from spatial multi-omics data of transcriptomics and metabolomics. It contains many intuitive visualization and downstream analysis tools, provides a great practical toolbox for biomedical researchers.

Metabolic cell communication

Metabolic cell-cell communication (MCC) occurs when sensor proteins in the receiver cells detect metabolites in their environment, activating intracellular signaling events. There are three major potential sensors of metabolites: surface receptors, nuclear receptors, and transporters. Metabolites secreted from cells are either transported over short-range distances (a few cells) via diffusion through extracellular space, or over long-range distances via the bloodstream and the cerebrospinal fluid (CSF).

MetaChatDB

MetaChatDB is a literature-supported database for metabolite-sensor interactions for both human and mouse. All the metabolite-sensor interactions are reported based on peer-reviewed publications. Specifically, we manually build MetaChatDB by integrating three high-quality databases (PDB, HMDB, UniProt) that are being continually updated.

Documentation, and Tutorials

For more basic tutorial and real data examples, please see MetaChat documentation that is available through the link https://metachat.readthedocs.io/en/latest/.

Analysis pipeline

Installation

System requirements

Recommended operating systems: macOS or Linux. MetaChat was developed and tested on Linux and macOS.

Python requirements

MetaChat was developed using python 3.9.

Installation using pip

We suggest setting up MetaChat in a separate mamba or conda environment to prevent conflicts with other software dependencies. Create a new Python environment specifically for MetaChat and install the required libraries within it.

mamba create -n metachat_env python=3.9 r-base=4.3.2
mamba activate metachat_env
pip install metachat

if you use conda, r-base=4.3.2 may not included in the channels. Instead, you can r-base=4.3.1 in conda.

Reference

Luo S., Almet A.A., Zhao W., He C., Tsai Y.-C., Ozaki H., Sugita B.K., Du K., Shen X., Cao Y., Yang Q., Watanabe M., Nie Q.* Screening spatial metabolic communication of cells from spatial multi-omics with MetaChat.