NFIA differentially controls adipogenic and myogenic gene program through distinct pathways to ensure brown and beige adipocyte differentiation


Autoři: Yuta Hiraike aff001;  Hironori Waki aff001;  Kana Miyake aff001;  Takahito Wada aff001;  Misato Oguchi aff001;  Kaede Saito aff001;  Shuichi Tsutsumi aff002;  Hiroyuki Aburatani aff002;  Toshimasa Yamauchi aff001;  Takashi Kadowaki aff001
Působiště autorů: Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan aff001;  Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan aff002;  Department of Diabetes and Lifestyle-Related diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan aff003;  Toranomon Hospital, Tokyo, Japan aff004
Vyšlo v časopise: NFIA differentially controls adipogenic and myogenic gene program through distinct pathways to ensure brown and beige adipocyte differentiation. PLoS Genet 16(9): e32767. doi:10.1371/journal.pgen.1009044
Kategorie: Research Article
doi: 10.1371/journal.pgen.1009044

Souhrn

The transcription factor nuclear factor I-A (NFIA) is a regulator of brown adipocyte differentiation. Here we show that the C-terminal 17 amino acid residues of NFIA (which we call pro#3 domain) are required for the transcriptional activity of NFIA. Full-length NFIA—but not deletion mutant lacking pro#3 domain—rescued impaired expression of PPARγ, the master transcriptional regulator of adipogenesis and impaired adipocyte differentiation in NFIA-knockout cells. Mechanistically, the ability of NFIA to penetrate chromatin and bind to the crucial Pparg enhancer is mediated through pro#3 domain. However, the deletion mutant still binds to Myod1 enhancer to repress expression of MyoD, the master transcriptional regulator of myogenesis as well as proximally transcribed non-coding RNA called DRReRNA, via competition with KLF5 in terms of enhancer binding, leading to suppression of myogenic gene program. Therefore, the negative effect of NFIA on the myogenic gene program is, at least partly, independent of the positive effect on PPARγ expression and its downstream adipogenic gene program. These results uncover multiple ways of action of NFIA to ensure optimal regulation of brown and beige adipocyte differentiation.

Klíčová slova:

Adipocyte differentiation – Adipocytes – Gene expression – Chromatin – Muscle differentiation – Proline – Transcription factors – Transcriptional control


Zdroje

1. Kajimura S, Spiegelman BM, Seale P. Brown and beige fat: Physiological roles beyond heat generation. Cell Metab. 2015;22: 546–559. doi: 10.1016/j.cmet.2015.09.007 26445512

2. Hiraike Y, Waki H, Yu J, Nakamura M, Miyake K, Nagano G, et al. NFIA co-localizes with PPARγ and transcriptionally controls the brown fat gene program. Nat Cell Biol. 2017;19: 1081–1092. doi: 10.1038/ncb3590 28812581

3. Alevizopoulos A, Dusserre Y, Tsai-Pflugfelder M, von der Weid T, Wahli W, Mermod N. A proline-rich TGF-beta-responsive transcriptional activator interacts with histone H3. Genes Dev. 1995;9: 3051–3066. doi: 10.1101/gad.9.24.3051 8543151

4. Morel Y, Barouki R. The repression of nuclear factor I/CCAAT transcription factor (NFI/CTF) transactivating domain by oxidative stress is mediated by a critical cysteine (Cys-427). Biochem J. 2000;348 Pt 1: 235–240. doi: 10.1042/0264-6021:3480235

5. Tsai P-F, Dell’Orso S, Rodriguez J, Vivanco KO, Ko K-D, Jiang K, et al. A Muscle-Specific Enhancer RNA Mediates Cohesin Recruitment and Regulates Transcription In trans. Mol Cell. 2018;71: 129–141. doi: 10.1016/j.molcel.2018.06.008 29979962

6. Sunadome K, Suzuki T, Usui M, Ashida Y, Nishida E. Antagonism between the Master Regulators of Differentiation Ensures the Discreteness and Robustness of Cell Fates. Mol Cell. 2014;54: 526–535. doi: 10.1016/j.molcel.2014.03.005 24703953

7. Gronostajski RM. Roles of the NFI/CTF gene family in transcription and development. Gene. 2000. pp. 31–45. doi: 10.1016/S0378-1119(00)00140-2

8. Himeda CL, Ranish JA, Pearson RCM, Crossley M, Hauschka SD. KLF3 Regulates Muscle-Specific Gene Expression and Synergizes with Serum Response Factor on KLF Binding Sites. Mol Cell Biol. 2010;30: 3430–3443. doi: 10.1128/MCB.00302-10 20404088

9. Sunadome K, Yamamoto T, Ebisuya M, Kondoh K, Sehara-Fujisawa A, Nishida E. ERK5 Regulates Muscle Cell Fusion through Klf Transcription Factors. Dev Cell. 2011;20: 192–205. doi: 10.1016/j.devcel.2010.12.005 21316587

10. Hayashi S, Manabe I, Suzuki Y, Relaix F, Oishi Y. Klf5 regulates muscle differentiation by directly targeting muscle-specific genes in cooperation with MyoD in mice. Elife. 2016;5: 1–23. doi: 10.7554/elife.17462 27743478

11. Thakore PI, D’Ippolito AM, Song L, Safi A, Shivakumar NK, Kabadi AM, et al. Highly specific epigenome editing by CRISPR-Cas9 repressors for silencing of distal regulatory elements. Nat Methods. 2015;12: 1143–1149. doi: 10.1038/nmeth.3630 26501517

12. Dell’Orso S, Wang AH, Shih HY, Saso K, Berghella L, Gutierrez-Cruz G, et al. The Histone Variant MacroH2A1.2 Is Necessary for the Activation of Muscle Enhancers and Recruitment of the Transcription Factor Pbx1. Cell Rep. 2016;14: 1156–1168. doi: 10.1016/j.celrep.2015.12.103 26832413

13. Matsumura Y, Nakaki R, Inagaki T, Yoshida A, Kano Y, Kimura H, et al. H3K4/H3K9me3 Bivalent Chromatin Domains Targeted by Lineage-Specific DNA Methylation Pauses Adipocyte Differentiation. Mol Cell. 2015;60: 584–96. doi: 10.1016/j.molcel.2015.10.025 26590716

14. Kirilusha A, Pope BD, Learned K, Sandstrom R, Tanzer A, Flicek P, et al. A comparative encyclopedia of DNA elements in the mouse genome. Nature. 2014;515: 355–364. doi: 10.1038/nature13992 25409824

15. Mikkelsen TS, Xu Z, Zhang X, Wang L, Gimble JM, Lander ES, et al. Comparative epigenomic analysis of murine and human adipogenesis. Cell. 2010;143: 156–169. doi: 10.1016/j.cell.2010.09.006 20887899

16. Zaret KS, Mango SE. Pioneer transcription factors, chromatin dynamics, and cell fate control. Curr Opin Genet Dev. 2016;37: 76–81. doi: 10.1016/j.gde.2015.12.003 26826681

17. Liisberg Aune U, Ruiz L, Kajimura S. Isolation and Differentiation of Stromal Vascular Cells to Beige/Brite Cells. J Vis Exp. 2013; 1–6. doi: 10.3791/50191 23568137

18. Haeussler M, Schönig K, Eckert H, Eschstruth A, Mianné J, Renaud JB, et al. Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR. Genome Biol. 2016;17: 1–12. doi: 10.1186/s13059-015-0866-z 26753840

19. Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10. doi: 10.1186/gb-2009-10-3-r25 19261174

20. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9: 357–9. doi: 10.1038/nmeth.1923 22388286

21. Giardine B, Riemer C, Hardison RC, Burhans R, Elnitski L, Shah P, et al. Galaxy: A platform for interactive large-scale genome analysis. Genome Res. 2005;15: 1451–1455. doi: 10.1101/gr.4086505 16169926

22. Afgan E, Baker D, Batut B, Van Den Beek M, Bouvier D, Ech M, et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Res. 2018;46: W537–W544. doi: 10.1093/nar/gky379 29790989

23. Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, et al. Model-based Analysis of ChIP-Seq (MACS). Genome Biol. 2008;9: R137. doi: 10.1186/gb-2008-9-9-r137 18798982

24. Liu T, Ortiz JA, Taing L, Meyer CA, Lee B, Zhang Y, et al. Cistrome: an integrative platform for transcriptional regulation studies. Genome Biol. 2011;12: R83. doi: 10.1186/gb-2011-12-8-r83 21859476

25. Machanick P, Bailey TL. MEME-ChIP: Motif analysis of large DNA datasets. Bioinformatics. 2011;27: 1696–1697. doi: 10.1093/bioinformatics/btr189 21486936

26. Ramírez F, Ryan DP, Grüning B, Bhardwaj V, Kilpert F, Richter AS, et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 2016;44: W160–W165. doi: 10.1093/nar/gkw257 27079975

27. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: Ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29: 15–21. doi: 10.1093/bioinformatics/bts635 23104886

28. Huang DW, Lempicki R a, Sherman BT. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4: 44–57. doi: 10.1038/nprot.2008.211 19131956

29. Reich M, Liefeld T, Gould J, Lerner J, Tamayo P, Mesirov JP. GenePattern 2.0. Nat Genet. 2006;38: 500–1. doi: 10.1038/ng0506-500 16642009


Článek vyšel v časopise

PLOS Genetics


2020 Číslo 9

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

Imunitní trombocytopenie (ITP) u dospělých pacientů
nový kurz
Autoři: prof. MUDr. Tomáš Kozák, Ph.D., MBA

Pěnová skleroterapie
Autoři: MUDr. Marek Šlais

White paper - jak vidíme optimální péči o zubní náhrady
Autoři: MUDr. Jindřich Charvát, CSc.

Hemofilie - série kurzů

Faktory ovlivňující léčbu levotyroxinem
Autoři:

Všechny kurzy
Kurzy Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

VIRTUÁLNÍ ČEKÁRNA ČR Jste praktický lékař nebo pediatr? Zapojte se! Jste praktik nebo pediatr? Zapojte se!

×