Implementation Of Ribosomal Tagging Strategies To Analyze Smooth Muscle Specific Rna Expression In Mouse Models Of Atherosclerosis

Background: Atherosclerotic cardiovascular disease (CVD) is the leading cause of mortality worldwide. Smooth muscle cells (SMCs) make up the bulk of the healthy arterial wall and atherosclerotic lesions. During atherosclerosis progression, we and others have reported on the emergence of multiple harmful and protective types of SMC-derived cell types (SDCs) in lesions, and the use of fluorescence lineage-tracing animal models have made it possible to isolate and analyze cell-type specific transcriptomes by flow cytometry and scRNA-seq. However, these manipulations are known to carry risk for artifacts, alter transcription, and introduce cell type bias. Therefore, alternative approaches that circumvent the need for single cell isolation may be beneficial. Hypothesis: Introduction of an isolation-free method for SMC translatome retrieval may be beneficial in confirming the presence of SDCs correlating with disease. Methods: SMC-specific translatomes were isolated by immunoprecipitation (IP) of epitope-tagged ribosomes from the aortic arch following the “RiboTag approach” developed by McKnight et al. and sequenced to test against libraries created by flow isolation of SMCs and bulk RNA-sequencing. Results: Here we report the creation of SMC-specific atherosclerotic RiboTag mouse model and initial efforts made to assess the SMC/SDC translatome during atherosclerosis. Side-by-side comparison of translatomes isolated by IP from the aortic arch and transcriptomes from sorted SDCs will be used to identify advantages and disadvantages of the respective approaches. Conclusions: This work will determine if and how the use of cell isolation may impact the transcriptome of SMCs and SDCs from mouse atherosclerotic models and establish if translatome analysis of these cell types can be used to complement standard sort-based profiling strategies in the study of atherosclerosis.