A label-free single-cell proteomics workflow has revealed previously unresolved vascular cell states in Marfan syndrome, offering a closer look at how aneurysm-associated changes vary across the aortic wall.
In the study, researchers profiled individual cells isolated from the aortic roots of wild-type and Fbn1C1041G/+ mice, a widely used model of Marfan syndrome. The analysis captured nearly 5,000 cells, with 3,475 retained for downstream analysis, and identified major aortic cell types, including endothelial cells, fibroblasts, macrophages, and multiple smooth muscle cell populations.
To capture those differences, the researchers turned to a direct liquid chromatography–mass spectrometry workflow tailored for single-cell proteomics. By avoiding multiplexed labeling strategies, the method aimed to improve quantitative accuracy and preserve protein-level differences between individual cells.
Clustering of the proteomic data identified 16 cell groups overall, including seven distinct smooth muscle cell subtypes. These ranged from more contractile states to more modified phenotypes, helping the researchers resolve heterogeneity that is difficult to capture with bulk tissue analysis.
Several of the altered smooth muscle cell states were more abundant in Marfan tissue. In particular, the researchers identified disease-enriched subpopulations marked by proteins including LRP1 and PRSS2, suggesting shifts in smooth muscle phenotype during aneurysm development. The analysis also pointed to changes in endothelial cells consistent with endothelial-to-mesenchymal transition, including reduced abundance of adhesion-associated proteins alongside increased expression of smooth muscle-related markers.
To test whether these signals could be confirmed in tissue, the team performed multiplexed spatial proteomics on independent mouse samples. These experiments supported the presence and tissue localization of key Marfan-associated markers, including PRSS2-positive smooth muscle cells and endothelial populations showing transition-like features.
Comparison with published single-cell RNA sequencing datasets showed that transcriptomic and proteomic data agreed well for broad cell classes, but less so for finer smooth muscle subtypes. When the two datasets were analyzed together, the researchers identified additional Marfan-associated cell states, including ACE- and TPM4-linked clusters, suggesting that some phenotypic differences were not fully resolved by RNA data alone.
In their discussion, the authors suggest that these newly defined smooth muscle populations now warrant closer functional study, particularly to determine whether markers such as LRP1 and PRSS2 reflect pathogenic remodeling or compensatory responses in Marfan aneurysm progression.
Newsletters
Receive the latest analytical science news, personalities, education, and career development – weekly to your inbox.
