Deep mutational scanning of ZIKV NS3 protein

Experiments by Blake Richardson and Matt Evans. Analysis by Caroline Kikawa, adapting a pipeline by Jesse Bloom and David Bacsik.

Analysis pipeline overview

This Snakemake takes input deep sequencing reads and processes them using the dms_tools2 package written by the Bloom lab. For this project, a deep mutational scanning library was created in discrete 'tiles' across the NS2B/NS3 protein from Zika virus. A pool of virus particles expressing these variants was selected by passaging on cells. The pre-selection counts of each variant (e.g., their frequency in the plasmid library) were compared to their counts in the cell-passaging selected libraries. The amino acid preferences or prefs are the result of this comparison. We then calculate mutational effects or muteffects for each variant by taking the log ratio of the variant mutation versus wild-type.

Results

For a summary of the results, see results/summary/, which has Markdown summaries for the analysis of each tile (e.g., results/summary/dms_tile_1_analysis.md, etc).

Other results are placed in ./results/, although not all files are tracked in the GitHub repo. Again, these files are sub-divided by tile and analysis (e.g., results/tile_1/prefs, results/tile_1/muteffects, etc).

Running analysis

First activate the ZIKV_DMS_NS5_EvansLab conda environment for the analysis. If you have not already created this environment, build it from environment.yml with:

conda env create -f environment.yml

Then activate the environment with:

conda activate ZIKV_DMS_NS3_EvansLab

The analysis is run by the snakemake pipeline in Snakefile. Essentially, this pipeline runs the Jupyter notebook dms_tile_analysis.ipynb for each deep mutational scanning tile, with the tile information specified in config.yml. To run the pipeline using 36 jobs, use the command:

snakemake -j 36

Add the --keep-incomplete flag if you don't want to delete results on an error. To run on the Hutch cluster using slurm, do:

sbatch -c 36 run_Snakemake.bash

Input data

The input data are in ./data/:

• ./data/tile_*_amplicon.fasta: amplicons for each tile of the barcoded-subamplicon sequencing.

• ./data/tile_*_subamplicon_alignspecs.txt: the alignment specs for the barcoded subamplicon sequencing for each amplicon.

• ./data/tile_*_samplelist.csv: all the samples that we sequenced and the locations of the associated deep-sequencing data for each amplicon.