Signaling mechanisms in renal compensatory hypertrophy revealed by multi-omics

被引:14
|
作者
Kikuchi, Hiroaki [1 ]
Chou, Chung-Lin [1 ]
Yang, Chin-Rang [1 ]
Chen, Lihe [1 ]
Jung, Hyun Jun [2 ]
Park, Euijung [1 ]
Limbutara, Kavee [3 ]
Carter, Benjamin [4 ]
Yang, Zhi-Hong [5 ]
Kun, Julia F. [5 ]
Remaley, Alan T. [5 ]
Knepper, Mark A. [1 ]
机构
[1] NHLBI, Epithelial Syst Biol Lab, Syst Biol Ctr, Bethesda, MD 20824 USA
[2] Johns Hopkins Univ, Dept Med, Div Nephrol, Sch Med, Baltimore, MD USA
[3] Chulalongkorn Univ, Fac Med, Ctr Excellence Syst Biol, Bangkok, Thailand
[4] NHLBI, Syst Biol Ctr, Lab Epigenome Biol, Bethesda, MD USA
[5] NHLBI, Lipoprotein Metab Sect, Translat Vasc Med Branch, NIH, Bethesda, MD USA
关键词
PROLIFERATOR-ACTIVATED RECEPTORS; METABOLIC-RESPONSE; MAMMALIAN TARGET; FATTY-ACIDS; GENE; NEPHRON; ALPHA; EICOSANOIDS; ADAPTATION; EXPRESSION;
D O I
10.1038/s41467-023-38958-9
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Loss of a kidney results in compensatory growth of the remaining kidney, a phenomenon of considerable clinical importance. However, the mechanisms involved are largely unknown. Here, we use a multi-omic approach in a unilateral nephrectomy model in male mice to identify signaling processes associated with renal compensatory hypertrophy, demonstrating that the lipid-activated transcription factor peroxisome proliferator-activated receptor alpha (PPAR & alpha;) is an important determinant of proximal tubule cell size and is a likely mediator of compensatory proximal tubule hypertrophy. The authors used a multi-omic approach in a mouse unilateral nephrectomy model to identify signaling processes associated with compensatory hypertrophy of the renal proximal tubule. The results indicate that PPAR & alpha; is an important determinant of proximal tubule cell size and is a likely mediator of compensatory proximal tubule hypertrophy.
引用
收藏
页数:22
相关论文
共 50 条
  • [31] Multi-Omics Integration Analysis Revealed the Seed Germination Mechanism of Pecan
    Xue, T.
    Qiu, S.
    Yang, C.
    Tang, X.
    Liu, J.
    Yuan, Y.
    RUSSIAN JOURNAL OF PLANT PHYSIOLOGY, 2024, 71 (04)
  • [32] Integrating adipocyte insulin signaling and metabolism in the multi-omics era
    Calejman, C. Martinez
    Doxsey, W. G.
    Fazakerley, D. J.
    Guertin, D. A.
    TRENDS IN BIOCHEMICAL SCIENCES, 2022, 47 (06) : 531 - 546
  • [33] Multi-omics joint analysis revealed the metabolic profile of retroperitoneal liposarcoma
    Xie, Fu'an
    Niu, Yujia
    Lian, Lanlan
    Wang, Yue
    Zhuang, Aobo
    Yan, Guangting
    Ren, Yantao
    Chen, Xiaobing
    Xiao, Mengmeng
    Li, Xi
    Xi, Zhe
    Zhang, Gen
    Qin, Dongmei
    Yang, Kunrong
    Zheng, Zhigang
    Zhang, Quan
    Xia, Xiaogang
    Li, Peng
    Gu, Lingwei
    Wu, Ting
    Luo, Chenghua
    Lin, Shu-Hai
    Li, Wengang
    FRONTIERS OF MEDICINE, 2024, 18 (02) : 375 - 393
  • [34] Multi-Omics Revealed the Protective Effects of Rhamnolipids in Lipopolysaccharide Challenged Broilers
    Zhang, Ruiqiang
    Shi, Xueyan
    Chen, Yuqi
    Liu, Jinsong
    Wu, Yanping
    Xu, Yinglei
    FRONTIERS IN IMMUNOLOGY, 2022, 13
  • [35] Are multi-omics enough?
    Cristina Vilanova
    Manuel Porcar
    Nature Microbiology, 1 (8)
  • [36] Are multi-omics enough?
    Vilanova, Cristina
    Porcar, Manuel
    NATURE MICROBIOLOGY, 2016, 1 (08)
  • [37] CLINICAL MULTI-OMICS
    Radstake, Timothy R.
    ANNALS OF THE RHEUMATIC DISEASES, 2019, 78 : 16 - 16
  • [38] Multi-Omics Approaches to Study Molecular Mechanisms in Cannabis sativa
    Sirangelo, Tiziana M.
    Ludlow, Richard A.
    Spadafora, Natasha D.
    PLANTS-BASEL, 2022, 11 (16):
  • [39] Multi-Omics Approaches to Discover Novel Mechanisms in Pulmonary Hypertension
    O'Connor, Ellen
    Ruffenach, Gregoire
    Lertpanit, Long
    Grijalva, Victor
    Wilson, Jennifer
    Eghbali, Mansoureh
    Reddy, Srinivasa
    JOURNAL OF BIOLOGICAL CHEMISTRY, 2024, 300 (03) : S509 - S509
  • [40] Editorial: Multi-omics approaches in the study of human disease mechanisms
    Wang, Dapeng
    Agapito, Giuseppe
    FRONTIERS IN BIOINFORMATICS, 2025, 4