Endogenous APP-Associated Proteomics in Mouse Brain Defines a Candidate Resource for APP Trafficking and Proteostasis Studies

Background/Objectives: Affinity proteomics of amyloid precursor protein (APP) is complicated by proteolytic processing, dynamic trafficking, and purification background. We generated a C-terminal 3×FLAG knock-in at the endogenous App locus to establish a cortical affinity-proteomic resource and prioritize APP-associated candidates for further study. Methods: Eight-week-old male homozygous APP-3×FLAG mice on a C57BL/6J background and wild-type littermates were characterized by biochemical and behavioral assays (n = 6 and n = 7 per genotype, respectively). Cortical material from three APP-3×FLAG males was pooled for anti-FLAG affinity purification and liquid chromatography–tandem mass spectrometry. Protein accessions were filtered by positive Area, unique-peptide support, and control recovery, with Gene Ontology (GO) analyses conducted under alternative backgrounds. Selected candidates underwent targeted co-immunoprecipitation and immunoblotting. Results: Baseline APP, amyloid-β, and behavioral measurements showed no statistically significant genotype-associated differences. Five shared high-confidence APP regions showed local Cα RMSD values below 0.3 Å in structural-model comparisons. Across APP-IP and control datasets, 1874 accessions were identified. Evidence filtering retained 990 non-bait candidate accessions representing 967 APP-IP protein groups. Two de novo-only spectra supported recovery of the engineered APP–3×FLAG junction peptide. GO analysis identified 21 significant cellular-component terms under the observed-union background, with none under the evidence-eligible background. Targeted anti-FLAG co-immunoprecipitation and immunoblotting supported ANXA2 and RACK1 co-recovery with APP-3×FLAG. Conclusions: The endogenous tagging model, evidence-filtered proteomic dataset, and targeted biochemical findings establish a candidate resource for investigating APP-associated assemblies and prioritizing proteins for studies of trafficking and proteostasis.