Novel RNA-binding protein YebC enhances translation of proline-rich amino acid stretches in bacteria

This repository contains the R scripts and source data necessary to reproduce the main results presented in the manuscript by Ignatov et al. (2024). However, since the alignment data and genome information is serveral GB large, it is archived here: https://doi.org/10.17617/3.8PZNYF.

Description of files and structure

We structured the analysis, R scripts, and source data based on the different high-throughput approaches applied in our study. Each analysis folder contains a README.md file with explanatory text about the input files and R scripts that were used to perform the analyses.

Installation

Follow these steps to reproduce the analysis:

Download repository

1. Clone or download this repository.
2. Navigate to the main project folder; it should contain the subfolder analysis.

git clone https://github.com/MPUSP/ignatov_et_al_2025.git
cd ignatov_et_al_2025

Download genome and alignment data

1. Download data data.zip from EDMOND.
2. Unzip the downloaded data and move the data folder into the project's main folder.
3. Confirm that your project's folder now contains the subfolders analysis and data.
4. Inside the data folder, you should find three subfolders: genome, iclip, and riboseq.

Your project folder should look like this now:

ignatov_et_al_2025/
├── .gitignore
├── LICENSE
├── README.md
├── analysis/
│   └── 01_analysis_of_OOPS_and_RBS-ID
│   └── 02_analysis_of_RNAseq_for_yebC_mutant
│   └── 03_analysis_of_iCLIP_for_yebC
│   └── 04_analysis_of_riboseq_for_yebC_mutant
│   └── 05_analysis_of_proteomics_for_yebC_mutant
└── data/
    └── genome/
    └── iclip/
    └── riboseq/

Setup R environment

In order to execute the R scripts, you will need the following R libraries:

• R (4.3.1)
• stringr (1.5.0)
• tidyverse (2.0.0)
• VennDiagram (1.7.3)
• beeswarm (0.4.0)
• ggpubr (0.6.0)
• ggrepel (0.9.4)
• plotROC (2.3.1)
• UniProt.ws (2.40.1)
• janitor (2.2.1)
• drawProteins (1.20.0)
• ggvenn (0.1.10)
• GenomicAlignments (1.36.0)
• edgeR (3.42.4)
• heatmaply (1.5.0)
• Biostrings (2.68.1)
• ggseqlogo (0.2.0)

Authors

• Dr. Dmitriy Ignatov
  • Affiliation: Max-Planck-Unit for the Science of Pathogens (MPUSP), Berlin, Germany
  • ORCID profile: https://orcid.org/0000-0002-2237-974X
• Dr. Rina Ahmed-Begrich
  • Affiliation: Max-Planck-Unit for the Science of Pathogens (MPUSP), Berlin, Germany
  • ORCID profile: https://orcid.org/0000-0002-0656-1795

Visit the MPUSP github page at https://github.com/MPUSP for more information on other projects.

References

• Essential R libraries required are listed in the R setup section of this document.

If you use the source code or data provided in this repository, please cite our manuscript: Ignatov et al. (2024).