Single-Cell Proteomics Reveals Novel Cell Phenotypes in Marfan Mouse Aneurysm.
Publication Year:
2026
PubMed ID:
41785993
Funding Grants:
Public Summary:
Researchers used a highly advanced scanning tool to look at the proteins inside individual cells taken from the main blood vessel—the aorta—of both healthy mice and mice with a genetic condition called Marfan syndrome. By zooming in on these proteins, they could easily map out all the different types of cells in the blood vessel, including seven highly specific kinds of muscle cells. The team discovered that the exact mix of cells and their proteins shifted significantly depending on the animal's sex and whether it had the disease. When comparing this new approach to traditional genetic tests, the protein scan proved far better at spotting those subtle, hidden differences between the muscle cells. After double-checking their results with special glowing dyes to confirm their accuracy, the scientists proved that this new method of analyzing single-cell proteins is an incredibly powerful tool for uncovering exactly why blood vessels fail, paving the way for better ways to study complex diseases in the future.
Scientific Abstract:
This report describes single-cell proteomic analyses of cells dissociated from a complex mammalian tissue using direct label-free mass spectrometry (single-cell proteomics by mass spectrometry, SCP-MS). The nanoDTSC approach was applied to profile individual cells from aorta of male and female wild-type and Fbn1(C1041G/+) Marfan mice. Leiden clustering identified all major aortic cell types including seven distinct smooth muscle cell (SMC) subtypes, with informative differences in cell proportions and differentially expressed proteins within cell types observed for both genotype and sex. Comparisons between single-cell RNA and single-cell proteomic profiles showed similarities in detection of major subtypes but not differentiation between SMC subtypes. Integrated multiomics analysis further identified genotype-dependent enrichment of unique SMC subtypes, relative to either protein or RNA datasets. Multiplexed-fluorescence based spatial proteomics validated several of these key genotype markers. Overall, these studies demonstrate the power of SCP-MS to detect novel aneurysm biology and serve as a guide for future development of SCP-MS methodology as it is applied to complex tissue cell mixtures and its integration with other omic modalities.