Single cell RNA sequencing analysis

The primary data was obtained from ArrayExpress (E-MTAB-9478), followed by annotation and alignment using CellRanger. All samples from spleen were included. Events with 200–5000 genes detected per cell (nFeature) and <5% mitochondrial genes were put through further analysis with the package of Seurat (v4) in R project. Our methodology for analysis was adapted from the original vignette (https://satijalab.org/seurat/articles/integration_introduction.html). In brief, differential expressed genes were found in each dataset using Principal Component Analysis. Shared genes were then identified across different time points as “anchors” to integrate all datasets. Subsequently, clustering was performed based on K-nearest neighbor (KNN) graph constructed. Clusters resembled contaminating cells (i.e., T cells, myeloid cells etc.) were excluded. The data was re-clustered using the workflow described previously.

For cell function evaluation, the “AddModuleScore ()” function was employed. Gene sets displayed in Figure.1h-i included the following: Hallmark mTORC1 signaling (MSigDB, M5924), Hallmark oxidative phosphorylation (MSigDB, M5936), Putative TFEB target genes (described previously⁶¹), KEGG Lysosome (MSigDB, {"type":"entrez-nucleotide","attrs":{"text":"M11266","term_id":"205871","term_text":"M11266"}}M11266), GO lysosome localization (GO:0032418), mitochrondrial complex I (MSigDB, M39781), Reactome mitophagy (MSigDB, {"type":"entrez-nucleotide","attrs":{"text":"M27418","term_id":"335291","term_text":"M27418"}}M27418), and Reactome PINK1-PRKN mediated mitophagy (MSigDB, {"type":"entrez-nucleotide","attrs":{"text":"M27419","term_id":"1220538"}}M27419).