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Wang X, Huang R, Zhang L, Li S, Luo J, Gu Y, Chen Z, Zheng Q, Chao T, Zheng W, Qi X, Wang L, Wen Y, Liang Y, Lu L. A severe atherosclerosis mouse model on the resistant NOD background. Dis Model Mech 2018; 11:11/10/dmm033852. [PMID: 30305306 PMCID: PMC6215432 DOI: 10.1242/dmm.033852] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Accepted: 08/16/2018] [Indexed: 12/24/2022] Open
Abstract
Atherosclerosis is a complex disease affecting arterial blood vessels and blood flow that could result in a variety of life-threatening consequences. Disease models with diverged genomes are necessary for understanding the genetic architecture of this complex disease. Non-obese diabetic (NOD) mice are highly polymorphic and widely used for studies of type 1 diabetes and autoimmunity. Understanding atherosclerosis development in the NOD strain is of particular interest as human atherosclerosis on the diabetic and autoimmune background has not been successfully modeled. In this study, we used CRISPR/Cas9 genome editing to genetically disrupt apolipoprotein E (ApoE) and low-density lipoprotein receptor (LDLR) expression on the pure NOD background, and compared phenotype between single-gene-deleted mice and double-knockout mutants with reference to ApoE-deficient C57BL/6 mice. We found that genetic ablation of Ldlr or Apoe in NOD mice was not sufficient to establish an atherosclerosis model, in contrast to ApoE-deficient C57BL/6 mice fed a high-fat diet (HFD) for over 12 weeks. We further obtained NOD mice deficient in both LDLR and ApoE, and assessed the severity of atherosclerosis and immune response to hyperlipidemia in comparison to ApoE-deficient C57BL/6 mice. Strikingly, the double-knockout NOD mice treated with a HFD developed severe atherosclerosis with aorta narrowed by over 60% by plaques, accompanied by destruction of pancreatic islets and an inflammatory response to hyperlipidemia. Therefore, we succeeded in obtaining a genetic model with severe atherosclerosis on the NOD background, which is highly resistant to the disease. This model is useful for the study of atherosclerosis in the setting of autoimmunity.
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Affiliation(s)
- Xugang Wang
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Rong Huang
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Lichen Zhang
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Saichao Li
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Jing Luo
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Yanrong Gu
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Zhijun Chen
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Qianqian Zheng
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Tianzhu Chao
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Laboratory of Mouse Genetics, Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Henan Province 453003, China
| | - Wenping Zheng
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Xinhui Qi
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Li Wang
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Yinhang Wen
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China
| | - Yinming Liang
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China .,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Laboratory of Mouse Genetics, Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Henan Province 453003, China
| | - Liaoxun Lu
- Laboratory of Genetic Regulators in the Immune System, Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China .,Henan Key Laboratory of Immunology and Targeted Therapy, School of Laboratory Medicine, Xinxiang Medical University, Henan Province 453003, China.,Laboratory of Mouse Genetics, Institute of Psychiatry and Neuroscience, Xinxiang Medical University, Henan Province 453003, China
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3
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Tang G, Yao J, Shen R, Ji A, Ma K, Cong B, Wang F, Zhu L, Wang X, Ding Y, Zhang B. Reduced inflammatory factor expression facilitates recovery after sciatic nerve injury in TLR4 mutant mice. Int Immunopharmacol 2018; 55:77-85. [PMID: 29227824 DOI: 10.1016/j.intimp.2017.12.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Revised: 12/05/2017] [Accepted: 12/06/2017] [Indexed: 12/11/2022]
Abstract
Toll-like receptors (TLRs) are extremely significant pattern recognition receptors. When nerve injury occurs, a variety of inflammatory factors are generated, leading to an exceedingly complex micro-environment. TLRs recognize damage-associated molecular patterns. To investigate the correlation between TLR4 and recovery after sciatic nerve injury, the model of sciatic nerve injury was conducted using TLR4-mutated mice (C3H/HeJ) and wild mice (C3H/HeN). Our goal was to identify short-stage and long-stage changes after sciatic nerve injury, mainly by checking the expression changes of inflammation factors in the short-stage and the differences in the recovery of the injured sciatic nerve in the long-stage. The results show that the increase of changes in the HeN group of IL-1β, IL-6, TNF-α and MCP-1 are more obvious than in the HeJ group, with caspase1 expression higher and Nlrp3 expression lower in the former group. Further results reveal intense inflammation occurred in the HeN group showing more neutrophils and macrophages. Nlrp3 and caspase1 showed little difference by Immunohistochemistry, with Nlrp6 expression differing between the HeJ group and the HeN group. The results led us to conclude that better recovery of the injured sciatic nerve occurred in the HeJ group because the expression of GAP-43 and p75NTR was higher and had a better SFI figure. TLR4 mutation can decrease the expression of inflammatory factors and enhance the speed of recovery after sciatic nerve injury. The changes in the expression of Nlrp6, which are related to the TLR4 mutation, may influence recovery of the injured sciatic nerve. Further studies will be conducted to confirm these results.
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Affiliation(s)
- Guoqing Tang
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, PR China
| | - Jia Yao
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, PR China
| | - Ruowu Shen
- Department of Anatomy, Medical College of Qingdao University, Qingdao, Shandong 266071, PR China
| | - Aiyu Ji
- Department of Traumatic Surgery, The Affiliated Hospital, Medical College of Qingdao University, Qingdao, Shandong 266003, PR China
| | - Kai Ma
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, PR China
| | - Beibei Cong
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, PR China
| | - Fang Wang
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, PR China
| | - Lingyu Zhu
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, PR China
| | - Xuan Wang
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, PR China
| | - Yingqiao Ding
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, PR China
| | - Bei Zhang
- Department of Immunology, Medical College of Qingdao University, Qingdao, Shandong 266071, PR China.
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6
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Kim SK, Avila JJ, Massett MP. Strain survey and genetic analysis of vasoreactivity in mouse aorta. Physiol Genomics 2016; 48:861-873. [PMID: 27764765 DOI: 10.1152/physiolgenomics.00054.2016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Accepted: 09/25/2016] [Indexed: 11/22/2022] Open
Abstract
Understanding the genetic influence on vascular reactivity is important for identifying genes underlying impaired vascular function. The purpose of this study was to characterize the genetic contribution to intrinsic vascular function and to identify loci associated with phenotypic variation in vascular reactivity in mice. Concentration response curves to phenylephrine (PE), potassium chloride (KCl), acetylcholine (ACh), and sodium nitroprusside (SNP) were generated in aortic rings from male mice (12 wk old) from 27 inbred mouse strains. Significant strain-dependent differences were found for both maximal responses and sensitivity for each agent, except for SNP Max (%). Strain differences for maximal responses to ACh, PE, and KCl varied by two- to fivefold. On the basis of these large strain differences, we performed genome-wide association mapping (GWAS) to identify loci associated with variation in responses to these agents. GWAS for responses to ACh identified four significant and 19 suggestive loci. Several suggestive loci for responses to SNP, PE, and KCl (including one significant locus for KCl EC50) were also identified. These results demonstrate that intrinsic endothelial function, and more generally vascular function, is genetically determined and associated with multiple genomic loci. Furthermore, these results are supported by the finding that several genes residing in significant and suggestive loci for responses to ACh were previously identified in rat and/or human quantitative trait loci/GWAS for cardiovascular disease. This study represents the first step toward the unbiased comprehensive discovery of genetic determinants that regulate intrinsic vascular function, particularly endothelial function.
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Affiliation(s)
- Seung Kyum Kim
- Department of Health and Kinesiology, Texas A&M University, College Station, Texas
| | - Joshua J Avila
- Department of Health and Kinesiology, Texas A&M University, College Station, Texas
| | - Michael P Massett
- Department of Health and Kinesiology, Texas A&M University, College Station, Texas
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7
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Kayashima Y, Tomita H, Zhilicheva S, Kim S, Kim HS, Bennett BJ, Maeda N. Quantitative trait loci affecting atherosclerosis at the aortic root identified in an intercross between DBA2J and 129S6 apolipoprotein E-null mice. PLoS One 2014; 9:e88274. [PMID: 24586312 PMCID: PMC3930552 DOI: 10.1371/journal.pone.0088274] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2013] [Accepted: 01/09/2014] [Indexed: 12/23/2022] Open
Abstract
Apolipoprotein E-null mice on a DBA/2J genetic background (DBA-apoE) are highly susceptible to atherosclerosis in the aortic root area compared with those on a 129S6 background (129-apoE). To explore atherosclerosis-responsible genetic regions, we performed a quantitative trait locus (QTL) analysis using 172 male and 137 female F2 derived from an intercross between DBA-apoE and 129-apoE mice. A genome-wide scan identified two significant QTL for the size of lesions at the root: one is Ath44 on Chromosome (Chr) 1 at 158 Mb, and the other Ath45 on Chr 2 at 162 Mb. Ath44 co-localizes with but appears to be independent of a previously reported QTL, Ath1, while Ath45 is a novel QTL. DBA alleles of both Ath44 and Ath45 confer atherosclerosis-susceptibility. In addition, a QTL on Chr 14 at 73 Mb was found significant only in males, and 129 allele conferring susceptibility. Further analysis detected female-specific interactions between a second QTL on Chr 1 at 73 Mb and a QTL on Chr 3 at 21 Mb, and between Chr 7 at 84 Mb and Chr 12 at 77 Mb. These loci for the root atherosclerosis were independent of QTLs for plasma total cholesterol and QTLs for triglycerides, but a QTL for HDL (Chr 1 at 126 Mb) overlapped with the Ath44. Notably, haplotype analysis among 129S6, DBA/2J and C57BL/6 genomes and their gene expression data narrowed the candidate regions for Ath44 and Ath45 to less than 5 Mb intervals where multiple genome wide associations with cardiovascular phenotypes have also been reported in humans. SNPs in or near Fmo3, Sele and Selp for Ath44, and Lbp and Pkig for Ath45 were suggested for further investigation as potential candidates underlying the atherosclerosis susceptibility.
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Affiliation(s)
- Yukako Kayashima
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Hirofumi Tomita
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Svetlana Zhilicheva
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Shinja Kim
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Hyung-Suk Kim
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Brian J. Bennett
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Nobuyo Maeda
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- * E-mail:
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