Complete Computational Workflow for Integrated PTM and Total Proteome Analysis: Distinguishing Expression from Usage Changes

# PTM Analysis Example: Complete Computational Workflow **Version:** 1.0 **Date:** July 2025 **DOI:** [Add Zenodo DOI here] ## Overview This repository contains a complete, executable example of the computational workflow for integrated post-translational modification (PTM) and total proteome analysis described in our manuscript "Integrated Analysis of Post-Translational Modifications and Total Proteome: Methods for Distinguishing Expression from Usage Changes". The analysis demonstrates how to distinguish between **Differential PTM Expression (DPE)** - changes in PTM abundance due to protein expression changes - and **Differential PTM Usage (DPU)** - true changes in modification stoichiometry independent of protein abundance. ## Dataset Description The example uses the Atg16l1 macrophage dataset from Maculins et al. (eLife 2021), investigating autophagy responses to bacterial infection: - **Experimental Design**: 2×3 factorial (Genotype: WT/KO × Timepoint: Uninfected/Early/Late infection) - **Technology**: TMT 11-plex quantitative proteomics - **Sample Type**: Mouse bone marrow-derived macrophages - **Conditions**: Wild-type vs Atg16l1-knockout cells infected with Shigella ## Repository Contents ### 📁 Core Analysis Scripts - `prolfqua_dataset.sh` - Dataset annotation creation - `prolfqua_dea.sh` - Differential expression analysis wrapper - `prolfqua_qc.sh` - Quality control analysis wrapper - `prolfqua_yaml.sh` - Configuration setup - `config.yaml` - Analysis configuration parameters ### 📊 Quality Control Reports - `QCReport.html` - Comprehensive QC analysis of TMT data including: - Database composition analysis - TMT labeling efficiency assessment - Missed cleavage analysis - Quantitative channel balance evaluation ### 📈 Differential Expression Analysis Results #### Total Proteome Analysis (`DEA_20250715_WUtotal_proteome_vsn/`) - `index.html` - Analysis overview - `Results_WU_total_proteome/` - `DE_WUtotal_proteome.html` - Interactive differential expression report - `DE_WUtotal_proteome.xlsx` - Complete statistical results - `QC_WUtotal_proteome.html` - Quality control metrics - `GSEA_*.rnk` - Gene set enrichment analysis input files - `ORA_*.txt` - Over-representation analysis results #### Single-site PTM Analysis (`DEA_20250715_WUsinglesite_PTM_vsn/`) - Individual phosphorylation site-level analysis - Site-specific statistical testing and visualization #### Multi-site PTM Analysis (`DEA_20250715_WUmultisite_PTM_vsn/`) - Peptide-level PTM pattern analysis - Multi-site modification coordination assessment ### 🔬 Integrated PTM Analysis Results (`PTM_analysis_20250715_singlesite_CustomPhosphoAnalysis/`) #### Key Output Files: - **`Result_phosphoAndTotalIntegration.html`** - Interactive integrated analysis report with: - DPE vs DPU comparison tables - N-to-C sequence visualization plots - Statistical summaries and quality metrics - **`Result_phosphoAndTotalIntegration.xlsx`** - Complete statistical results including: - Combined PTM and protein statistics - DPU calculations with p-values and FDR correction - Site-level annotations and sequence windows - **`Site_differential_Expression.pdf`** - N-to-C plots showing PTM sites along protein sequences with expression changes - **`Site_differential_UsageChange.pdf`** - N-to-C plots showing protein-normalized PTM usage changes ### 📖 Documentation and Source Code - `Supplementary_Material_v2.html` - Complete analysis walkthrough - `Supplementary_Material_v2.pdf` - PDF version of the analysis guide - `dataset_with_contrasts.tsv` - Experimental design annotation ## Software Requirements ### R Environment - **R version**: ≥ 4.0.0 - **System requirements**: 8GB+ RAM (16GB+ recommended), 5GB+ storage ### Required R Packages - `prolfqua` (doi:10.1021/acs.jproteome.2c00441) - Statistical framework - `prolfquapp` (doi:10.1021/acs.jproteome.4c00911) - Differential expression pipeline - `prolfquappPTMreaders` (doi:10.5281/zenodo.15845243) - PTM data readers - `prophosqua` (doi:10.5281/zenodo.15845272) - PTM integration and visualization - `tidyverse`, `ggseqlogo`, `writexl`, `rmarkdown` - Data manipulation and reporting ## How to Use This Example ### 1. **Explore the Results** Start by opening the main results files: - `QCReport.html` - Understand data quality - `DEA_*/Results_*/DE_*.html` - Review differential expression results - `Supplementary_Material_v2.html` - Understand the analysis methodology - `Result_phosphoAndTotalIntegration.html` - Examine integrated analysis ### 2. **Reproduce the Analysis** For details see https://github.com/prolfqua/prophosqua/ ### 3. **Adapt to Your Data** Modify the analysis parameters in: - `config.yaml` - Analysis settings - `dataset_with_contrasts.tsv` - Experimental design - Script parameters for your file paths and conditions ### 4. **Understand the Methodology** The `Supplementary_Material_v2.html` provides a complete step-by-step walkthrough including: - Data preprocessing and quality control - Statistical analysis frameworks - Integration methodology for PTM and protein data - Biological interpretation guidelines ## Key Analysis Concepts ### Differential PTM Expression (DPE) Tests raw PTM-feature changes between conditions without protein normalization. Identifies any modification whose abundance changes, including those driven by protein expression changes. ### Differential PTM Usage (DPU) Tests protein-normalized PTM changes, revealing modification sites where stoichiometry genuinely changes independent of protein abundance. This analysis identifies true signaling changes. ### N-to-C Plots Visualizations showing PTM sites along protein sequences in their biological context, facilitating interpretation by displaying modifications relative to known domains and functional regions. ## File Size Information - **Total size**: ~700 MB (compressed) - **Largest files**: - Excel results files: 50-65 MB each - HTML reports: 15-36 MB each - PDF visualizations: 100-130 KB each ## Citation If you use this example in your research, please cite: [10.5281/zenodo.15830989](https://doi.org/10.5281/zenodo.15830989) ## Support and Contact For questions about this analysis example: - **Issues with DEA example**: [GitHub repository](https://github.com/prolfqua/prolfquapp/issues) - **Issues with PTM analysis example**: [GitHub repository](https://github.com/prophosqua/issues) ## License This example analysis is provided under [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) license. The underlying R packages have their own licenses as specified in their respective repositories. ## Acknowledgments This example is based on the dataset from Maculins et al. (eLife 2021) doi:10.7554/elife.62320. We thank the authors for making their data publicly available for method development and validation. --- **Keywords**: proteomics, post-translational modifications, phosphoproteomics, TMT, differential expression, R, bioinformatics, mass spectrometry