bioRxivSystems BiologyPreprint
Multimodal analysis of molecular remodeling in aging spleen identified global and cell type specific changes
Katarina VlajiciD, Alison Luciano, Gennifer E. MerrihewiD, Carla Ruiz Sanchez, Michael E. RiffleiD, Kristine A. TsantilasiD, Sahar AttariD, Brian J. BeliveauiD, Mariya T. SweetwyneiD, Michael J. MacCossiD, Gary A. ChurchilliD, Devin K. SchweppeiD
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Abstract
Aging reshapes the cellular and molecular landscape of mammalian tissues. These changes can be progressive, preceding linearly with age, or occur as abrupt transitions of the course of lifespan. To investigate the age-dependent cellular and molecular shifts we profiled matched proteomes and transcriptomes from male and female murine spleens across eight time points, from stable adults through late life. The spleen was chosen to integrate understanding of age-dependent changes associated with immune surveillance, inflammaging, and immune-related proteostasis. Male and female mice follow distinct aging trajectories particularly in protein-RNA correlation in late life, reflecting both compositional shifts and failure of post-transcriptional buffering. To investigate whether these changes could be attributed to specific cell-types within the spleen, we developed Celestial, a machine-learning framework to identify cell-type-specific changes in bulk tissue samples. We found that age-related bulk molecular changes could be attributed in part to compositional remodeling of cell-types--expansion of GZMK+ CD8+ T cells and C1Q+ macrophages alongside naive T cell and global B cell loss. These results demonstrate that cell-type-aware interpretation can inform bulk multi-omic data for accurate mechanistic inference in heterogeneous tissues undergoing complex molecular remodeling.
- organism: mouse
- assay: proteomics
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: benchmarking
- approach: machine learning (classical)
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