Bulk microglia proteomics analysis of mouse brain samples from the Destrooper lab. Data was acquired by DIA mass spectrometry and processed with Spectronaut, then analysed in R.
Study design
Four genotypes, 4 animals each (n=16 total):
| hApp |
GA_1–4 |
Yes |
| hAppNLGF |
GA_5–8 |
Yes |
| hAppNLGF_FIRE |
GA_9–12 |
No (FIRE KO) |
| hApp_FIRE |
GA_13–16 |
No (FIRE KO) |
Analysis
Bulk proteomics
| 1. Initial QC |
Protein counts, MAD outlier detection, PCA, correlation heatmap, contaminant check |
| 2. MSstats |
Differential abundance — pairwise contrasts plus the APP × Microglia interaction contrast |
| 3. DE Plots |
Volcano plots and visualisation of differentially abundant proteins |
| 4. GSEA |
Gene set enrichment analysis using GO, KEGG, and cell-type signatures (C8) |
| 5. Microglia × APP-NLGF |
Microglia-attributable proteins further modulated by APP-NLGF — interaction hits, UpSet, heatmap |
| 6. PPI Networks |
STRINGdb interaction networks and hub proteins per contrast |
| 7. Subcellular Stratification |
UniProt subcellular-location and secretome stratification of significant hits |
| 8. Protein Profile Plots |
Per-protein profile plots across genotypes for selected hits |
Phosphoproteomics
| 1. Phospho QC |
Phosphopeptide / phosphosite counts, MAD outliers, PCA, sample correlation |
| 2. MSstatsPTM |
Phospho DE adjusted for protein-level abundance — 4 pairwise + APP × Microglia interaction |
| 3. Phospho DE Plots |
Volcano plots of adjusted phospho contrasts, plus phospho-vs-protein concordance scatter |
| 4. Kinase Activity |
Inferred kinase activities per contrast via decoupleR + OmniPath kinase–substrate network |
| 5. Phospho GSEA |
Pathway enrichment over GO/KEGG/C8 using gene-level rolled-up phospho ranks |
| 6. Phospho Profile Plots |
Per-phosphosite profile plots across genotypes for selected hits |
| 7. Power Downsampling |
Empirical power curve for the Interaction contrast — subsample N∈{2,3,4} reps per condition, re-run MSstatsPTM + decoupleR per draw in parallel |