1
|
Terakawa A, Hu Y, Kokaji T, Yugi K, Morita K, Ohno S, Pan Y, Bai Y, Parkhitko AA, Ni X, Asara JM, Bulyk ML, Perrimon N, Kuroda S. Trans-omics analysis of insulin action reveals a cell growth subnetwork which co-regulates anabolic processes. iScience 2022; 25:104231. [PMID: 35494245 PMCID: PMC9044165 DOI: 10.1016/j.isci.2022.104231] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/09/2022] [Accepted: 04/06/2022] [Indexed: 12/16/2022] Open
Abstract
Insulin signaling promotes anabolic metabolism to regulate cell growth through multi-omic interactions. To obtain a comprehensive view of the cellular responses to insulin, we constructed a trans-omic network of insulin action in Drosophila cells that involves the integration of multi-omic data sets. In this network, 14 transcription factors, including Myc, coordinately upregulate the gene expression of anabolic processes such as nucleotide synthesis, transcription, and translation, consistent with decreases in metabolites such as nucleotide triphosphates and proteinogenic amino acids required for transcription and translation. Next, as cell growth is required for cell proliferation and insulin can stimulate proliferation in a context-dependent manner, we integrated the trans-omic network with results from a CRISPR functional screen for cell proliferation. This analysis validates the role of a Myc-mediated subnetwork that coordinates the activation of genes involved in anabolic processes required for cell growth. A trans-omic network of insulin action in Drosophila cells was constructed Insulin co-regulates various anabolic processes in a time-dependent manner The trans-omic network and a CRISPR screen for cell proliferation were integrated A Myc-mediated subnetwork promoting anabolic processes is required for cell growth
Collapse
Affiliation(s)
- Akira Terakawa
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yanhui Hu
- Department of Genetics, Blavatnik Institute, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Toshiya Kokaji
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
- Data Science Center, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara, Japan
| | - Katsuyuki Yugi
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
- Institute for Advanced Biosciences, Keio University, Fujisawa, 252-8520, Japan
| | - Keigo Morita
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Satoshi Ohno
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
- Molecular Genetics Research Laboratory, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
| | - Yifei Pan
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Yunfan Bai
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Andrey A. Parkhitko
- Department of Genetics, Blavatnik Institute, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
- Aging Institute of UPMC and the University of Pittsburgh, Pittsburgh, PA, USA
| | - Xiaochun Ni
- Department of Genetics, Blavatnik Institute, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - John M. Asara
- Division of Signal Transduction, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02175, USA
| | - Martha L. Bulyk
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Brigham & Women’s Hospital and Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Norbert Perrimon
- Department of Genetics, Blavatnik Institute, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
- Howard Hughes Medical Institute, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
- Corresponding author
| | - Shinya Kuroda
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
- Molecular Genetics Research Laboratory, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
- Corresponding author
| |
Collapse
|
2
|
Budi EH, Hoffman S, Gao S, Zhang YE, Derynck R. Integration of TGF-β-induced Smad signaling in the insulin-induced transcriptional response in endothelial cells. Sci Rep 2019; 9:16992. [PMID: 31740700 PMCID: PMC6861289 DOI: 10.1038/s41598-019-53490-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Accepted: 10/22/2019] [Indexed: 01/09/2023] Open
Abstract
Insulin signaling governs many processes including glucose homeostasis and metabolism, and is therapeutically used to treat hyperglycemia in diabetes. We demonstrated that insulin-induced Akt activation enhances the sensitivity to TGF-β by directing an increase in cell surface TGF-β receptors from a pool of intracellular TGF-β receptors. Consequently, increased autocrine TGF-β signaling in response to insulin participates in insulin-induced angiogenic responses of endothelial cells. With TGF-β signaling controlling many cell responses, including differentiation and extracellular matrix deposition, and pathologically promoting fibrosis and cancer cell dissemination, we addressed to which extent autocrine TGF-β signaling participates in insulin-induced gene responses of human endothelial cells. Transcriptome analyses of the insulin response, in the absence or presence of a TGF-β receptor kinase inhibitor, revealed substantial positive and negative contributions of autocrine TGF-β signaling in insulin-responsive gene responses. Furthermore, insulin-induced responses of many genes depended on or resulted from autocrine TGF-β signaling. Our analyses also highlight extensive contributions of autocrine TGF-β signaling to basal gene expression in the absence of insulin, and identified many novel TGF-β-responsive genes. This data resource may aid in the appreciation of the roles of autocrine TGF-β signaling in normal physiological responses to insulin, and implications of therapeutic insulin usage.
Collapse
Affiliation(s)
- Erine H Budi
- Departments of Cell and Tissue Biology, and Anatomy, Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California at San Francisco, San Francisco, CA, 94143-0669, USA
| | - Steven Hoffman
- Departments of Cell and Tissue Biology, and Anatomy, Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California at San Francisco, San Francisco, CA, 94143-0669, USA
| | - Shaojian Gao
- Thoracic and Gastrointestinal Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, 20892-1906, USA
| | - Ying E Zhang
- Laboratory of Cellular and Molecular Biology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, 20892-4256, USA
| | - Rik Derynck
- Departments of Cell and Tissue Biology, and Anatomy, Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California at San Francisco, San Francisco, CA, 94143-0669, USA.
| |
Collapse
|
3
|
Dai Y, Ghosh S, Shin BC, Devaskar SU. Role of microRNA-122 in hepatic lipid metabolism of the weanling female rat offspring exposed to prenatal and postnatal caloric restriction. J Nutr Biochem 2019; 73:108220. [PMID: 31630081 PMCID: PMC6896790 DOI: 10.1016/j.jnutbio.2019.108220] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 06/23/2019] [Accepted: 07/30/2019] [Indexed: 12/17/2022]
Abstract
We examined the role of hepatocyte micro-RNA-122 and hypothalamic neuropeptides, in weanling (21d) female rats exposed to calorie restriction induced growth restriction either prenatally (IUGR), postnatally (PNGR) or both (IPGR) vs. ad lib fed controls (CON). IUGR were hyperinsulinemic, hyperleptinemic and dyslipidemic with high circulating miR-122. In contrast, PNGR and IPGR displayed insufficient glucose, insulin and leptin amidst high ketones with a dichotomy in circulating miR-122 of PNGR
Collapse
Affiliation(s)
- Yun Dai
- Department of Pediatrics and the Children's Discovery and Innovation Institute, David Geffen School of Medicine UCLA, Los Angeles, CA
| | - Shubhamoy Ghosh
- Department of Pediatrics and the Children's Discovery and Innovation Institute, David Geffen School of Medicine UCLA, Los Angeles, CA
| | - Bo-Chul Shin
- Department of Pediatrics and the Children's Discovery and Innovation Institute, David Geffen School of Medicine UCLA, Los Angeles, CA
| | - Sherin U Devaskar
- Department of Pediatrics and the Children's Discovery and Innovation Institute, David Geffen School of Medicine UCLA, Los Angeles, CA.
| |
Collapse
|
4
|
Kawata K, Hatano A, Yugi K, Kubota H, Sano T, Fujii M, Tomizawa Y, Kokaji T, Tanaka KY, Uda S, Suzuki Y, Matsumoto M, Nakayama KI, Saitoh K, Kato K, Ueno A, Ohishi M, Hirayama A, Soga T, Kuroda S. Trans-omic Analysis Reveals Selective Responses to Induced and Basal Insulin across Signaling, Transcriptional, and Metabolic Networks. iScience 2018; 7:212-229. [PMID: 30267682 PMCID: PMC6161632 DOI: 10.1016/j.isci.2018.07.022] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 07/13/2018] [Accepted: 07/26/2018] [Indexed: 12/18/2022] Open
Abstract
The concentrations of insulin selectively regulate multiple cellular functions. To understand how insulin concentrations are interpreted by cells, we constructed a trans-omic network of insulin action in FAO hepatoma cells using transcriptomic data, western blotting analysis of signaling proteins, and metabolomic data. By integrating sensitivity into the trans-omic network, we identified the selective trans-omic networks stimulated by high and low doses of insulin, denoted as induced and basal insulin signals, respectively. The induced insulin signal was selectively transmitted through the pathway involving Erk to an increase in the expression of immediate-early and upregulated genes, whereas the basal insulin signal was selectively transmitted through a pathway involving Akt and an increase of Foxo phosphorylation and a reduction of downregulated gene expression. We validated the selective trans-omic network in vivo by analysis of the insulin-clamped rat liver. This integrated analysis enabled molecular insight into how liver cells interpret physiological insulin signals to regulate cellular functions.
Collapse
Affiliation(s)
- Kentaro Kawata
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Atsushi Hatano
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Katsuyuki Yugi
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; YCI Laboratory for Trans-Omics, Young Chief Investigator Program, RIKEN Center for Integrative Medical Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan; Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan; PRESTO, Japan Science and Technology Agency, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Hiroyuki Kubota
- Division of Integrated Omics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Takanori Sano
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Masashi Fujii
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; Molecular Genetics Research Laboratory, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yoko Tomizawa
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Toshiya Kokaji
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Kaori Y Tanaka
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Shinsuke Uda
- Division of Integrated Omics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Yutaka Suzuki
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Masaki Matsumoto
- Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Keiichi I Nakayama
- Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Kaori Saitoh
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Keiko Kato
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Ayano Ueno
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Maki Ohishi
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Akiyoshi Hirayama
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Tomoyoshi Soga
- Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Shinya Kuroda
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan; Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Bunkyo-ku, Tokyo 113-0033, Japan.
| |
Collapse
|
5
|
Self-assembling asymmetric peptide-dendrimer micelles - a platform for effective and versatile in vitro nucleic acid delivery. Sci Rep 2018; 8:4832. [PMID: 29556057 PMCID: PMC5859181 DOI: 10.1038/s41598-018-22902-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Accepted: 02/12/2018] [Indexed: 12/18/2022] Open
Abstract
Despite advancements in the development of high generation cationic-dendrimer systems for delivery of nucleic acid-based therapeutics, commercially available chemical agents suffer from major drawbacks such as cytotoxicity while being laborious and costly to synthesize. To overcome the aforementioned limitations, low-generation cationic peptide asymmetric dendrimers with side arm lipid (cholic and decanoic acid) conjugation were designed, synthesized and systematically screened for their ability to self-assemble into micelles using dynamic light scattering. Cytotoxicity profiling revealed that our entire asymmetric peptide dendrimer library when trialled alone, or as asymmetric dendrimer micelle-nucleic acid complexes, were non-cytotoxic across a broad concentration range. Further, the delivery efficiency of asymmetric peptide dendrimers in H-4-II-E (rat hepatoma), H2K (mdx mouse myoblast), and DAOY (human medulloblastoma) cells demonstrated that cholic acid-conjugated asymmetric dendrimers possess far superior delivery efficiency when compared to the commercial standards, Lipofectamine 2000 or Lipofectin®.
Collapse
|
6
|
Shannon CE, Daniele G, Galindo C, Abdul-Ghani MA, DeFronzo RA, Norton L. Pioglitazone inhibits mitochondrial pyruvate metabolism and glucose production in hepatocytes. FEBS J 2017; 284:451-465. [PMID: 27987376 DOI: 10.1111/febs.13992] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Revised: 12/09/2016] [Accepted: 12/12/2016] [Indexed: 01/03/2023]
Abstract
Pioglitazone is used globally for the treatment of type 2 diabetes mellitus (T2DM) and is one of the most effective therapies for improving glucose homeostasis and insulin resistance in T2DM patients. However, its mechanism of action in the tissues and pathways that regulate glucose metabolism are incompletely defined. Here we investigated the direct effects of pioglitazone on hepatocellular pyruvate metabolism and the dependency of these observations on the purported regulators of mitochondrial pyruvate transport, MPC1 and MPC2. In cultured H4IIE hepatocytes, pioglitazone inhibited [2-14 C]-pyruvate oxidation and pyruvate-driven oxygen consumption and, in mitochondria isolated from both hepatocytes and human skeletal muscle, pioglitazone selectively and dose-dependently inhibited pyruvate-driven ATP synthesis. Pioglitazone also suppressed hepatocellular glucose production (HGP), without influencing the mRNA expression of key HGP regulatory genes. Targeted siRNA silencing of MPC1 and 2 caused a modest inhibition of pyruvate oxidation and pyruvate-driven ATP synthesis, but did not alter pyruvate-driven HGP and, importantly, it did not influence the actions of pioglitazone on either pathway. In summary, these findings outline a novel mode of action of pioglitazone relevant to the pathogenesis of T2DM and suggest that targeting pyruvate metabolism may lead to the development of effective new T2DM therapies.
Collapse
Affiliation(s)
| | - Giuseppe Daniele
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX, USA
| | - Cynthia Galindo
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX, USA
| | | | - Ralph A DeFronzo
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX, USA
| | - Luke Norton
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX, USA
| |
Collapse
|
7
|
Sano T, Kawata K, Ohno S, Yugi K, Kakuda H, Kubota H, Uda S, Fujii M, Kunida K, Hoshino D, Hatano A, Ito Y, Sato M, Suzuki Y, Kuroda S. Selective control of up-regulated and down-regulated genes by temporal patterns and doses of insulin. Sci Signal 2016; 9:ra112. [PMID: 27879394 DOI: 10.1126/scisignal.aaf3739] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Secretion of insulin transiently increases after eating, resulting in a high circulating concentration. Fasting limits insulin secretion, resulting in a low concentration of insulin in the circulation. We analyzed transcriptional responses to different temporal patterns and doses of insulin in the hepatoma FAO cells and identified 13 up-regulated and 16 down-regulated insulin-responsive genes (IRGs). The up-regulated IRGs responded more rapidly than did the down-regulated IRGs to transient stepwise or pulsatile increases in insulin concentration, whereas the down-regulated IRGs were repressed at lower concentrations of insulin than those required to stimulate the up-regulated IRGs. Mathematical modeling of the insulin response as two stages-(i) insulin signaling to transcription and (ii)transcription and mRNA stability-indicated that the first stage was the more rapid stage for the down-regulated IRGs, whereas the second stage of transcription was the more rapid stage for the up-regulated IRGs. A subset of the IRGs that were up-regulated or down-regulated in the FAO cells was similarly regulated in the livers of rats injected with a single dose of insulin. Thus, not only can cells respond to insulin but they can also interpret the intensity and pattern of signal to produce distinct transcriptional responses. These results provide insight that may be useful in treating obesity and type 2 diabetes associated with aberrant insulin production or tissue responsiveness.
Collapse
Affiliation(s)
- Takanori Sano
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Kentaro Kawata
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Satoshi Ohno
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Katsuyuki Yugi
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.,Precursory Research for Embryonic Science and Technology (PRESTO), Japan Science and Technology Agency, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Hiroaki Kakuda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Hiroyuki Kubota
- Division of Integrated Omics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan.,PRESTO, Japan Science and Technology Agency, Higashi-ku, Fukuoka 812-8582, Japan
| | - Shinsuke Uda
- Division of Integrated Omics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Masashi Fujii
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Katsuyuki Kunida
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Daisuke Hoshino
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Atsushi Hatano
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yuki Ito
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Miharu Sato
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yutaka Suzuki
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan
| | - Shinya Kuroda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan. .,Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.,Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Bunkyo-ku, Tokyo 113-0033, Japan
| |
Collapse
|
8
|
Li Y, Ozment T, Wright GL, Peterson JM. Identification of Putative Receptors for the Novel Adipokine CTRP3 Using Ligand-Receptor Capture Technology. PLoS One 2016; 11:e0164593. [PMID: 27727322 PMCID: PMC5058508 DOI: 10.1371/journal.pone.0164593] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Accepted: 09/27/2016] [Indexed: 02/06/2023] Open
Abstract
C1q TNF Related Protein 3 (CTRP3) is a member of a family of secreted proteins that exert a multitude of biological effects. Our initial work identified CTRP3’s promise as an effective treatment for Nonalcoholic fatty liver disease (NAFLD). Specifically, we demonstrated that mice fed a high fat diet failed to develop NAFLD when treated with CTRP3. The purpose of this current project is to identify putative receptors which mediate the hepatic actions of CTRP3.
Collapse
Affiliation(s)
- Ying Li
- Quillen College of Medicine, Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee, United States of America
| | - Tammy Ozment
- Quillen College of Medicine, Department of Internal Medicine, East Tennessee State University, Johnson City, Tennessee, United States of America
| | - Gary L. Wright
- Quillen College of Medicine, Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee, United States of America
| | - Jonathan M. Peterson
- Quillen College of Medicine, Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee, United States of America
- College of Public Health, Department of Health Sciences, East Tennessee State University, Johnson City, Tennessee, United States of America
- * E-mail:
| |
Collapse
|
9
|
Celli GB, Kalt W, Brooks MSL. Gastroretentive systems - a proposed strategy to modulate anthocyanin release and absorption for the management of diabetes. Drug Deliv 2016; 23:1892-901. [PMID: 26873039 DOI: 10.3109/10717544.2016.1143058] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Several reports have indicated a positive correlation between the consumption of anthocyanins (ACN) and biomarkers relating to the improvement of type 2 diabetes (T2D). However, the results from in vitro studies often do not translate into clinical evidence. Potential causes of these discrepancies are experimental conditions that lack physiological relevancy; extensive degradation of these compounds in vivo due to changes in pH and metabolism; and a short residence time in the absorption window in relation to the absorption rate. Here, gastroretentive systems (GRS) are proposed as a strategy to overcome the limitations in ACN delivery and to reduce the existing bench-to-subject gap. This review summarizes recent literature on the use of ACN for the management and control of T2D, followed by GRS platforms to promote a sustained release of ACN for increased health benefits.
Collapse
Affiliation(s)
- Giovana Bonat Celli
- a Department of Process Engineering and Applied Science , Dalhousie University , Halifax , NS , Canada and
| | - Wilhelmina Kalt
- b Atlantic Food and Horticulture Research Centre, Agriculture and Agri-Food Canada , Kentville , NS , Canada
| | - Marianne Su-Ling Brooks
- a Department of Process Engineering and Applied Science , Dalhousie University , Halifax , NS , Canada and
| |
Collapse
|
10
|
Norton L, Chen X, Fourcaudot M, Acharya NK, DeFronzo RA, Heikkinen S. The mechanisms of genome-wide target gene regulation by TCF7L2 in liver cells. Nucleic Acids Res 2014; 42:13646-61. [PMID: 25414334 PMCID: PMC4267646 DOI: 10.1093/nar/gku1225] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
In the liver Wnt-signaling contributes to the metabolic fate of hepatocytes, but the precise role of the TCF7L2 in this process is unknown. We employed a temporal RNA-Seq approach to examine gene expression 3–96 h following Tcf7l2 silencing in rat hepatoma cells, and combined this with ChIP-Seq to investigate mechanisms of target gene regulation by TCF7L2. Silencing Tcf7l2 led to a time-dependent appearance of 406 differentially expressed genes (DEGs), including key regulators of cellular growth and differentiation, and amino acid, lipid and glucose metabolism. Direct regulation of 149 DEGs was suggested by strong proximal TCF7L2 binding (peak proximity score > 10) and early mRNA expression changes (≤18 h). Indirect gene regulation by TCF7L2 likely occurred via alternate transcription factors, including Hnf4a, Foxo1, Cited2, Myc and Lef1, which were differentially expressed following Tcf7l2 knock-down. Tcf7l2-silencing enhanced the expression and chromatin occupancy of HNF4α, and co-siRNA experiments revealed that HNF4α was required for the regulation of a subset of metabolic genes by TCF7L2, particularly those involved in lipid and amino-acid metabolism. Our findings suggest TCF7L2 is an important regulator of the hepatic phenotype, and highlight novel mechanisms of gene regulation by TCF7L2 that involve interplay between multiple hepatic transcriptional pathways.
Collapse
Affiliation(s)
- Luke Norton
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX 78229, USA
| | - Xi Chen
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX 78229, USA
| | - Marcel Fourcaudot
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX 78229, USA
| | - Nikhil K Acharya
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX 78229, USA
| | - Ralph A DeFronzo
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX 78229, USA
| | - Sami Heikkinen
- Institute of Biomedicine, University of Eastern Finland, Kuopio 70211, Finland
| |
Collapse
|