Fibroblast-Specific β-catenin Signaling Dictates the Outcome of AKI
Dong Zhou, Haiyan Fu, Liangxiang Xiao, Hongyan Mo, Hui Zhuo, Xiaojun Tian, Lin Lin, Jianhua Xing and Youhua Liu
Abstract: AKI is a devastating condition with high morbidity and mortality. The pathologic features of AKI are characterized by tubular injury, inflammation, and vascular impairment. Whether fibroblasts in the renal interstitium have a role in the pathogenesis of AKI is unknown. In this study, we investigated the role of fibroblast-specific β-catenin signaling in dictating the outcome of AKI, using conditional knockout mice in which β-catenin was specifically ablated in fibroblasts (Gli1-β-cat−/−). After ischemia-reperfusion injury (IRI), Gli1-β-cat−/− mice had lower serum creatinine levels and less morphologic injury than Gli1-β-cat+/+ littermate controls. Moreover, we detected fewer apoptotic cells, as well as decreased cytochrome C release; reduced expression of Bax, FasL, and p53; and increased phosphorylation of Akt, in the Gli1-β-cat−/− kidneys. Gli1-β-cat−/− kidneys also exhibited upregulated expression of proliferating cell nuclear antigen and Ki-67, which are markers of cell proliferation. Furthermore, Gli1-β-cat−/− kidneys displayed suppressed NF-κB signaling and cytokine expression and reduced infiltration of inflammatory cells. Notably, loss of β-catenin in fibroblasts induced renal expression of hepatocyte growth factor (HGF) and augmented the tyrosine phosphorylation of c-met receptor after IRI. In vitro, treatment with Wnt ligands or ectopic expression of active β-catenin inhibited HGF mRNA and protein expression and repressed HGF promoter activity. Collectively, these results suggest that fibroblast-specific β-catenin signaling can control tubular injury and repair in AKI by modulating HGF expression. Our studies uncover a previously unrecognized role for interstitial fibroblasts in the pathogenesis of AKI.
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Congratulations to 2017 DiSCoBio alumna Nicole Munne for being selected as a 2018 Regeneron Science Talent Search Scholar for her project, “Developing an in vitro Human Liver Model for Nonalcoholic Fatty Liver Disease,” which was completed with her mentor, Dr. Larry Vernetti.
Each scholar receives a $2,000 award with an additional $2,000 going to their respective school.
For more information, please visit https://student.societyforscience.org/regeneron-sts-2018-scholars.
Congratulations to Jocelyn Sunseri who was selected as one of only 11 recipients of the 2018 Phase-I MolSSI Software Fellowship. She will receive six months of support in this program funded by the National Science Foundation through Virginia Tech. Jocelyn’s adviser is Dr. David Koes.
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Raghavendran Partha, Bharesh K Chauhan, Zelia Ferreira, Joseph D Robinson, Kira Lathrop, Ken K Nischal, Maria Chikina (corresponding author), Nathan L Clark (corresponding author)
Abstract: The underground environment imposes unique demands on life that have led subterranean species to evolve specialized traits, many of which evolved convergently. We studied convergence in evolutionary rate in subterranean mammals in order to associate phenotypic evolution with specific genetic regions. We identified a strong excess of vision- and skin-related genes that changed at accelerated rates in the subterranean environment due to relaxed constraint and adaptive evolution. We also demonstrate that ocular-specific transcriptional enhancers were convergently accelerated, whereas enhancers active outside the eye were not. Furthermore, several uncharacterized genes and regulatory sequences demonstrated convergence and thus constitute novel candidate sequences for congenital ocular disorders. The strong evidence of convergence in these species indicates that evolution in this environment is recurrent and predictable and can be used to gain insights into phenotype–genotype relationships.
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Lee Lab publish in Cell Systems
NF-𝛋B Dynamics Discriminate between TNF Doses in Single Cells
Zhang Q1, Gupta S1, Schipper DL, Kowalczyk GJ, Mancini AE, Faeder JR, Lee REC*
Using an information theory framework and single-cell data, Zhang et al. set out to distinguish between different mechanisms for activation of intracellular signals. They show that heterogeneity between cellular states can lead to underestimates in the capabilities of single cells. In contrast with a switch-like model for pathway activation, they find that single cells can encode multiple levels of response that increase with stimulation strength.
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