Objective Prenatal deletion of the type II TGF-β receptor (TBRII) prevents normal vascular morphogenesis and smooth muscle cell (SMC) differentiation, causing embryonic death. The role of TBRII in adult SMC is less well studied. Clarification of this role has important clinical implications because TBRII deletion should ablate TGF-β signaling and blockade of TGF-β signaling is envisioned as a treatment for human aortopathies. We hypothesized that postnatal loss of SMC TBRII would cause aortopathy. Approach and Results We generated mice with either of two tamoxifen-inducible SMC-specific Cre (SMC-CreERT2) alleles and homozygous floxed Tgfbr2 alleles. Mice were injected with tamoxifen, and their aortas examined 4 and 14 weeks later. Both SMC-CreERT2 alleles efficiently and specifically rearranged a floxed reporter gene and efficiently rearranged a floxed Tgfbr2 allele, resulting in loss of aortic medial TBRII protein. Loss of SMC TBRII caused severe aortopathy including hemorrhage, ulceration, dissection, dilation, accumulation of macrophage markers, elastolysis, abnormal proteoglycan accumulation, and aberrant SMC gene expression. All areas of the aorta were affected, with the most severe pathology in the ascending aorta. Cre-mediated loss of SMC TBRII in vitro ablated both canonical and noncanonical TGF-β signaling and reproduced some of the gene expression abnormalities detected in vivo. Conclusions SMC TBRII plays a critical role in maintaining postnatal aortic homeostasis. Loss of SMC TBRII disrupts TGF-β signaling, acutely alters SMC gene expression, and rapidly results in severe and durable aortopathy. These results suggest that pharmacologic blockade of TGF-β signaling in humans could cause aortic disease rather than prevent it.

Objective-Impairment of transforming growth factor (TGF)-␤1 signaling accelerates atherosclerosis in experimental mice. However, it is uncertain whether increased TGF-␤1 expression would retard atherosclerosis. The role of TGF-␤1 in aneurysm formation is also controversial. We tested whether overexpression of active TGF-␤1 in hyperlipidemic mice affects atherogenesis and aortic dilation. Methods and Results-We generated apolipoprotein E-null mice with transgenes that allow regulated overexpression of active TGF-␤1 in their hearts. Compared to littermate controls, these mice had elevated cardiac and plasma TGF-␤1, less aortic root atherosclerosis (PՅ0.002), fewer lesions in the thoracic and abdominal aortae (PՅ0.01), less aortic root dilation (PϽ0.001), and fewer pseudoaneurysms (Pϭ0.02). Mechanistic studies revealed no effect of TGF-␤1 overexpression on plasma lipids or cytokines, or on peripheral lymphoid organ cells. However, aortae of TGF-␤1-overexpressing mice had fewer T-lymphocytes, more collagen, less lipid, lower expression of inflammatory cytokines and matrix metalloproteinase-13, and higher expression of tissue inhibitor of metalloproteinase-2. Conclusions-When overexpressed in the heart and plasma, TGF-␤1 is an antiatherogenic, vasculoprotective cytokine that limits atherosclerosis and prevents aortic dilation. These actions are associated with significant changes in cellularity, collagen and lipid accumulation, and gene expression in the artery wall. Key Words: aneurysm Ⅲ atherosclerosis Ⅲ growth substances Ⅲ inflammation Ⅲ plaque T GF-␤1 is a pleiotropic cytokine that circulates in plasma and is produced by several cardiovascular cell types including smooth muscle and endothelial cells, monocytes, macrophages, and T cells. 1,2 Several studies associate variations in TGF-␤1 expression or signaling with atherosclerosis and aneurysm formation; however, the precise relationships between TGF-␤1, atherosclerosis, and aneurysm formation are incompletely understood.Human studies largely support an antiatherogenic role for TGF-␤1, with most studies revealing a negative correlation between plasma TGF-␤1 concentration and the presence or extent of atherosclerosis. [3][4][5][6] Although some animal studies suggest that TGF-␤1 could accelerate atherosclerosis by increasing vascular extracellular matrix accumulation and lipid retention, 7-10 several studies in hyperlipidemic mice instead portray TGF-␤1 as an antiatherogenic cytokine that limits atherosclerosis largely through immunosuppressive effects. Almost all of these murine studies involve systemic suppression of TGF-␤ activity, for example by injection of antibodies to TGF-␤, infusion of a soluble TGF-␤ receptor, or transgene-mediated abrogation of TGF-␤ signaling in T cells. [11][12][13][14] These studies show that less systemic TGF-␤ activity accelerates atherosclerosis, but they do not address whether enhancement of TGF-␤1 signaling would be antiatherogenic. A recent gene-transfer study suggests that elevated systemic expression of TGF-␤1 might suppress ...

Systematic screens for genetic interactions are a cornerstone of both network and systems biology. However, most screens have been limited to characterizing interaction networks in a single environment. Moving beyond this static view of the cell requires a major technological advance to increase the throughput and ease of replication in these assays. Here, we introduce iSeq—a platform to build large double barcode libraries and rapidly assay genetic interactions across environments. We use iSeq in yeast to measure fitness in three conditions of nearly 400 clonal strains, representing 45 possible single or double gene deletions, including multiple replicate strains per genotype. We show that iSeq fitness and interaction scores are highly reproducible for the same clonal strain across replicate cultures. However, consistent with previous work, we find that replicates with the same putative genotype have highly variable genetic interaction scores. By whole-genome sequencing 102 of our strains, we find that segregating variation and de novo mutations, including aneuploidy, occur frequently during strain construction, and can have large effects on genetic interaction scores. Additionally, we uncover several new environment-dependent genetic interactions, suggesting that barcode-based genetic interaction assays have the potential to significantly expand our knowledge of genetic interaction networks.