Temporal Transcriptome Analysis Reveals Dynamic Gene Expression Patterns Driving β-Cell Maturation

被引:7
|
作者
Sanavia, Tiziana [1 ]
Huang, Chen [2 ,3 ]
Manduchi, Elisabetta [4 ,5 ]
Xu, Yanwen [2 ]
Dadi, Prasanna K. [6 ]
Potter, Leah A. [2 ]
Jacobson, David A. [6 ]
Di Camillo, Barbara [7 ]
Magnuson, Mark A. [2 ,6 ]
Stoeckert, Christian J., Jr. [8 ]
Gu, Guoqiang [2 ]
机构
[1] Univ Torino, Dept Med Sci, Turin, Italy
[2] Vanderbilt Univ, Sch Med, Ctr Stem Cell Biol, Vanderbilt Program Dev Biol,Dept Cell & Dev Biol, Nashville, TN 37212 USA
[3] Baylor Coll Med, Lester & Sue Smith Breast Ctr, Houston, TX 77030 USA
[4] Childrens Hosp Philadelphia, Div Human Genet, Philadelphia, PA 19104 USA
[5] Univ Penn, Inst Biomed Informat, Perelman Sch Med, Philadelphia, PA 19104 USA
[6] Vanderbilt Univ, Sch Med, Dept Mol Physiol & Biophys, Nashville, TN 37212 USA
[7] Univ Padua, Dept Informat Engn, Padua, Italy
[8] Univ Penn, Dept Genet, Perelman Sch Med, Philadelphia, PA 19104 USA
关键词
β -cell maturation; glucose-induced insulin secretion; vesicle release; calcium influx; time-series gene expression; RNA sequencing; INSULIN-SECRETION; STEM-CELLS; FUNCTIONAL MATURATION; GLUCOSE; FETAL; PATHWAYS; HETEROGENEITY; COMMUNICATION; METABOLISM; GENERATION;
D O I
10.3389/fcell.2021.648791
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Newly differentiated pancreatic beta cells lack proper insulin secretion profiles of mature functional beta cells. The global gene expression differences between paired immature and mature beta cells have been studied, but the dynamics of transcriptional events, correlating with temporal development of glucose-stimulated insulin secretion (GSIS), remain to be fully defined. This aspect is important to identify which genes and pathways are necessary for beta-cell development or for maturation, as defective insulin secretion is linked with diseases such as diabetes. In this study, we assayed through RNA sequencing the global gene expression across six beta-cell developmental stages in mice, spanning from beta-cell progenitor to mature beta cells. A computational pipeline then selected genes differentially expressed with respect to progenitors and clustered them into groups with distinct temporal patterns associated with biological functions and pathways. These patterns were finally correlated with experimental GSIS, calcium influx, and insulin granule formation data. Gene expression temporal profiling revealed the timing of important biological processes across beta-cell maturation, such as the deregulation of beta-cell developmental pathways and the activation of molecular machineries for vesicle biosynthesis and transport, signal transduction of transmembrane receptors, and glucose-induced Ca2+ influx, which were established over a week before beta-cell maturation completes. In particular, beta cells developed robust insulin secretion at high glucose several days after birth, coincident with the establishment of glucose-induced calcium influx. Yet the neonatal beta cells displayed high basal insulin secretion, which decreased to the low levels found in mature beta cells only a week later. Different genes associated with calcium-mediated processes, whose alterations are linked with insulin resistance and deregulation of glucose homeostasis, showed increased expression across beta-cell stages, in accordance with the temporal acquisition of proper GSIS. Our temporal gene expression pattern analysis provided a comprehensive database of the underlying molecular components and biological mechanisms driving beta-cell maturation at different temporal stages, which are fundamental for better control of the in vitro production of functional beta cells from human embryonic stem/induced pluripotent cell for transplantation-based type 1 diabetes therapy.
引用
收藏
页数:15
相关论文
共 50 条
  • [41] Multi-tissue transcriptome analysis of two Begonia species reveals dynamic patterns of evolution in the chalcone synthase gene family
    Emelianova, Katie
    Martinez, Andrea Martinez
    Campos-Dominguez, Lucia
    Kidner, Catherine
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [42] Combined analysis of temporal metabolomics and transcriptomics reveals the metabolic patterns in goat oocytes during maturation
    Ma, Yixin
    Zhang, Wei
    Gao, Ming
    Li, Jiashuo
    Wang, Qiang
    Chen, Minjian
    Gu, Ling
    THERIOGENOLOGY, 2024, 218 : 69 - 78
  • [43] Transcriptome profiling reveals the spatial-temporal dynamics of gene expression essential for soybean seed development
    Hengyou Zhang
    Zhenbin Hu
    Yuming Yang
    Xiaoqian Liu
    Haiyan Lv
    Bao-Hua Song
    Yong-qiang Charles An
    Zhimin Li
    Dan Zhang
    BMC Genomics, 22
  • [44] Transcriptome profiling reveals the spatial-temporal dynamics of gene expression essential for soybean seed development
    Zhang, Hengyou
    Hu, Zhenbin
    Yang, Yuming
    Liu, Xiaoqian
    Lv, Haiyan
    Song, Bao-Hua
    An, Yong-qiang Charles
    Li, Zhimin
    Zhang, Dan
    BMC GENOMICS, 2021, 22 (01)
  • [45] Integrated analysis of the transcriptome and metabolome of purple and green leaves of Tetrastigma hemsleyanum reveals gene expression patterns involved in anthocyanin biosynthesis
    Yan, Jianli
    Qian, Lihua
    Zhu, Weidong
    Qiu, Jieren
    Lu, Qiujun
    Wang, Xianbo
    Wu, Qifeng
    Ruan, Songlin
    Huang, Yuqing
    PLOS ONE, 2020, 15 (03):
  • [46] Serial analysis of gene expression reveals identifiable patterns in transcriptome profiles of Palaemonetes pugio exposed to three common environmental stressors
    Griffitt, Robert J.
    Greig, Tom W.
    Chandlerj, G. Thomas
    Quattro, Joe A.
    ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY, 2007, 26 (11) : 2413 - 2419
  • [47] Single-Cell Transcriptome Analysis Reveals Paraspeckles Expression in Osteosarcoma Tissues
    Rothzerg, Emel
    Feng, Wenyu
    Song, Dezhi
    Li, Hengyuan
    Wei, Qingjun
    Fox, Archa
    Wood, David
    Xu, Jiake
    Liu, Yun
    CANCER INFORMATICS, 2022, 21
  • [48] Spatial and single-cell transcriptome analysis reveals changes in gene expression in response to drug perturbation in rat kidney
    Onoda, Naoki
    Kawabata, Ayako
    Hasegawa, Kumi
    Sakakura, Megumi
    Urakawa, Itaru
    Seki, Masahide
    Zenkoh, Junko
    Suzuki, Ayako
    Suzuki, Yutaka
    DNA RESEARCH, 2022, 29 (02)
  • [49] Cell type specific transcriptome analysis reveals a distinct gene expression pattern of cardiomyocytes in a mouse model of cardiac recovery
    Schnick, T.
    Gilsbach, R.
    Schmoele, I
    Stiller, B.
    Hein, L.
    NAUNYN-SCHMIEDEBERGS ARCHIVES OF PHARMACOLOGY, 2015, 388 : S39 - S39
  • [50] Transcriptome analysis of a cnidarian dinoflagellate mutualism reveals complex modulation of host gene expression
    Rodriguez-Lanetty, M
    Weis, VM
    Phillips, WS
    INTEGRATIVE AND COMPARATIVE BIOLOGY, 2005, 45 (06) : 1064 - 1064