CHOOSER: Discovering CRISPR-Cas system with self-processing pre-crRNA capability by foundation models

Introduction

This repository hosts the custom code of CHOOSER (Cas HOmlog Observing and SElf-processing scReening), a novel, effective and unified AI framework for alignment-free discovery of novel CRISPR-Cas systems with self-processing precursor CRISPR RNA (pre-crRNA) capability utilizing protein foundation models.

Model weights & example data

*Note: before running the notebooks on Colab, please ensure that you have to save/add the following folders into your Google Drive ("MyDrive" folder):

• model

• inputs

• data

• ccminer

Environment

CHOOSER is run on Python 3.9 and PyTorch 1.13.1. You can build a conda environment for CHOOSER using this script.

Run CasDiscovery

Note: During the initial data upload to Zenodo, the file models_weights/CasDiscovery/pytorch_model.bin was mistakenly uploaded as models_weights/CasDiscovery/pytorch_model-001.bin. This issue has now been corrected, and the updated version of the model weight files with the correct filename is available here [10.5281/zenodo.14608475].

Alternatively, you can still use the model weight files downloaded from [10.5281/zenodo.13906238]. Simply rename the file models_weights/CasDiscovery/pytorch_model-001.bin to models_weights/CasDiscovery/pytorch_model.bin.

The model weights of CHOOSER and a minimum dataset to run CHOOSER are available in Zenodo (DOI: 10.5281/zenodo.13906238). A small example dataset are also provided:

models_weights.zip

example_data.zip

<pre> #conda activate chooser python CasDiscovery -m models_weights/CasDiscovery -i example_data/suspicious.faa -o suspicious_pred.csv </pre>

Custom code for Colab Notebook

Step.1 Get suspected proteins near CRISPR arrays

Install and run our bioinformatic pipeline CRISPRCasMiner to fetch the suspected proteins around the CRISPR arrays. Custom code is provided here: 01_Get_Suspected_Proteins_near_CRISPR.ipynb, or you can run on Colab notebook: colab_notebook:

Input: Metagenome-assembled genomes/contigs.

Output: Known CRISPR-Cas systems & suspicious proteins adjacent to CRISPR arrays.

Step.2 Cas homolog discovery

Run CHOOSER to discern Cas homologs: 02_CasDiscovery.colab.ipynb, or you can run on Colab notebook: colab_notebook

Input: suspicious proteins in .fasta/.faa format.

Output: predicted tags of the proteins, including cas9, cas12, cas13 and other.

Step.3 Pre-crRNA self-processing functional screening of Cas12 homologs

For the Cas12 candidates, we predicted whether they are able to self-process pre-crRNA or not: 03_Cas12_SelfProcessing.ipynb, or you can run on Colab notebook: colab_notebook

Input: Cas12 proteins in .fasta/.faa format.

Output: predicted wether the Cas12 candidates would self-process their pre-crRNAs.

Datasource

| Source | DataBase | DataSet | Download URL | | - | - | - | - | | Prokaryotic | MGnify | mgnify_human_gut<br>mgnify_human_oral<br>mgnify_cow_rumen<br>mgnify_pig_gut<br>mgnify_fish_gut<br>mgnify_marine | https://www.ebi.ac.uk/metagenomics/browse/genomes | | Prokaryotic | GEM | GEM | https://portal.nersc.gov/GEM | | Prokaryotic | GMBC | GMBC-high<br>GMBC-medium | https://gmgc.embl.de/download.cgi | | Prokaryotic | BGI_human_oral | 4D-SZ cohort | https://db.cngb.org/search/project/CNP0000687 | | Prokaryotic | glacier | Glacier Microbiomes | https://www.biosino.org/node/project/detail/OEP003083 | | Viral | gutPhageDB | gutPhageDB | https://www.sanger.ac.uk/data/gut-phage-database | | Viral | IMGVR | IMG/VR | https://genome.jgi.doe.gov/portal/IMG_VR/IMG_VR.download.html | | Viral | MGV | Metagenomic Gut Virus | https://portal.nersc.gov/MGV | | Viral | GVD | Gut Virome Database | https://bitbucket.org/MAVERICLab/gvd | | Viral | HuVirDB | Human Virome Database | http://opengut.ucsf.edu/HuVirDB-1.0.fasta.gz |

Citation

Li, Wenhui, Xianyue Jiang, Wuke Wang, Liya Hou, Runze Cai, Yongqian Li, Qiuxi Gu et al. "Discovering CRISPR-Cas system with self-processing pre-crRNA capability by foundation models." Nature Communications 15, no. 1 (2024): 10024.

DOI: https://doi.org/10.1038/s41467-024-54365-0

PMCID: PMC11576732

Contacts

qiliu@tongji.edu.cn, liwh@zhejianglab.org, liwh@tongji.edu.cn