Regulatory architecture determines optimal regulation of gene expression in metabolic pathways

被引:49
|
作者
Chubukov, Victor [1 ,2 ]
Zuleta, Ignacio A. [1 ]
Li, Hao [1 ,2 ]
机构
[1] Univ Calif San Francisco, Dept Biochem & Biophys, San Francisco, CA 94143 USA
[2] Univ Calif Berkeley, Univ Calif San Francisco, Joint Grad Grp Bioengn, Berkeley, CA 94720 USA
基金
美国国家卫生研究院;
关键词
SACCHAROMYCES-CEREVISIAE; SALMONELLA-TYPHIMURIUM; ESCHERICHIA-COLI; YEAST; BIOSYNTHESIS; NETWORKS; SEQUENCE; PROTEIN; NOISE;
D O I
10.1073/pnas.1114235109
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
In response to environmental changes, the connections ("arrows") in gene regulatory networks determine which genes modulate their expression, but the quantitative parameters of the network ("the numbers on the arrows") are equally important in determining the resulting phenotype. What are the objectives and constraints by which evolution determines these parameters? We explore these issues by analyzing gene expression changes in a number of yeast metabolic pathways in response to nutrient depletion. We find that a striking pattern emerges that couples the regulatory architecture of the pathway to the gene expression response. In particular, we find that pathways controlled by the intermediate metabolite activation (IMA) architecture, in which an intermediate metabolite activates transcription of pathway genes, exhibit the following response: the enzyme immediately downstream of the regulatory metabolite is under the strongest transcriptional control, whereas the induction of the enzymes upstream of the regulatory intermediate is relatively weak. This pattern of responses is absent in pathways not controlled by an IMA architecture. The observation can be explained by the constraint imposed by the fundamental feedback structure of the network, which places downstream enzymes under a negative feedback loop and upstream ones under a positive feedback loop. This general design principle for transcriptional control of a metabolic pathway can be derived from a simple cost/benefit model of gene expression, in which the observed pattern is an optimal solution. Our results suggest that the parameters regulating metabolic enzyme expression are optimized by evolution, under the strong constraint of the underlying regulatory architecture.
引用
收藏
页码:5127 / 5132
页数:6
相关论文
共 50 条
  • [31] Integrating gene regulatory pathways into differential network analysis of gene expression data
    Tyler Grimes
    S. Steven Potter
    Somnath Datta
    Scientific Reports, 9
  • [32] Signaling pathways and regulation of gene expression in hematopoietic cells
    Bogush, Daniel
    Schramm, Joseph
    Ding, Yali
    He, Bing
    Singh, Chingakham
    Sharma, Arati
    Tukaramrao, Diwakar Bastihalli
    Iyer, Soumya
    Desai, Dhimant
    Nalesnik, Gregory
    Hengst, Jeremy
    Bhalodia, Riya
    Gowda, Chandrika
    Dovat, Sinisa
    ADVANCES IN BIOLOGICAL REGULATION, 2023, 88
  • [33] Research Resource: Interactome of Human Embryo Implantation: Identification of Gene Expression Pathways, Regulation, and Integrated Regulatory Networks
    Altmae, Signe
    Reimand, Jueri
    Hovatta, Outi
    Zhang, Pu
    Kere, Juha
    Laisk, Triin
    Saare, Merli
    Peters, Maire
    Vilo, Jaak
    Stavreus-Evers, Anneli
    Salumets, Andres
    MOLECULAR ENDOCRINOLOGY, 2012, 26 (01) : 203 - 217
  • [34] microRNA cross regulation of gene regulatory network and signaling pathways.
    Song, J. L.
    Stepicheva, N. A.
    MOLECULAR BIOLOGY OF THE CELL, 2017, 28
  • [35] Snake venom gene expression is coordinated by novel regulatory architecture and the integration of multiple co-opted vertebrate pathways
    Perry, Blair W.
    Gopalan, Siddharth S.
    Pasquesi, Giulia I. M.
    Schield, Drew R.
    Westfall, Aundrea K.
    Smith, Cara F.
    Koludarov, Ivan
    Chippindale, Paul T.
    Pellegrino, Mark W.
    Chuong, Edward B.
    Mackessy, Stephen P.
    Castoe, Todd A.
    GENOME RESEARCH, 2022, 32 (06) : 1058 - 1073
  • [36] Topology regulatory elements: From shaping genome architecture to gene regulation
    Chen, Liang-Fu
    Long, Hannah Katherine
    CURRENT OPINION IN STRUCTURAL BIOLOGY, 2023, 83
  • [37] Metabolic memory determines gene expression in liver and adipose tissue of undernourished ewes
    Fernandez-Foren, A.
    Meikle, A.
    de Brun, V.
    Grana-Baumgartner, A.
    Abecia, J. A.
    Sosa, C.
    LIVESTOCK SCIENCE, 2022, 260
  • [38] Metabolic regulation of gene expression through histone acylations
    Benjamin R. Sabari
    Di Zhang
    C. David Allis
    Yingming Zhao
    Nature Reviews Molecular Cell Biology, 2017, 18 : 90 - 101
  • [39] Metabolic Regulation of Gene Expression by Histone Lysine β-Hydroxybutyrylation
    Xie, Zhongyu
    Zhang, Di
    Chung, Dongjun
    Tang, Zhanyun
    Huang, He
    Dai, Lunzhi
    Qi, Shankang
    Li, Jingya
    Colak, Gozde
    Chen, Yue
    Xia, Chunmei
    Peng, Chao
    Ruan, Haibin
    Kirkey, Matt
    Wang, Danli
    Jensen, Lindy M.
    Kwon, Oh Kwang
    Lee, Sangkyu
    Pletcher, Scott D.
    Tan, Minjia
    Lombard, David B.
    White, Kevin P.
    Zhao, Hongyu
    Li, Jia
    Roeder, Robert G.
    Yang, Xiaoyong
    Zhao, Yingming
    MOLECULAR CELL, 2016, 62 (02) : 194 - 206
  • [40] Regulation of chromatin and gene expression by metabolic enzymes and metabolites
    Xinjian Li
    Gabor Egervari
    Yugang Wang
    Shelley L. Berger
    Zhimin Lu
    Nature Reviews Molecular Cell Biology, 2018, 19 : 563 - 578