The Ugtome: the Expanding Diversity of UDP Glycosyltransferases and Its Impact on Small Molecule Metabolism
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Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
Propranolol-Mediated Attenuation of MMP-9 Excretion in Infants with Hemangiomas
Supplementary Online Content Thaivalappil S, Bauman N, Saieg A, Movius E, Brown KJ, Preciado D. Propranolol-mediated attenuation of MMP-9 excretion in infants with hemangiomas. JAMA Otolaryngol Head Neck Surg. doi:10.1001/jamaoto.2013.4773 eTable. List of All of the Proteins Identified by Proteomics This supplementary material has been provided by the authors to give readers additional information about their work. © 2013 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/01/2021 eTable. List of All of the Proteins Identified by Proteomics Protein Name Prop 12 mo/4 Pred 12 mo/4 Δ Prop to Pred mo mo Myeloperoxidase OS=Homo sapiens GN=MPO 26.00 143.00 ‐117.00 Lactotransferrin OS=Homo sapiens GN=LTF 114.00 205.50 ‐91.50 Matrix metalloproteinase‐9 OS=Homo sapiens GN=MMP9 5.00 36.00 ‐31.00 Neutrophil elastase OS=Homo sapiens GN=ELANE 24.00 48.00 ‐24.00 Bleomycin hydrolase OS=Homo sapiens GN=BLMH 3.00 25.00 ‐22.00 CAP7_HUMAN Azurocidin OS=Homo sapiens GN=AZU1 PE=1 SV=3 4.00 26.00 ‐22.00 S10A8_HUMAN Protein S100‐A8 OS=Homo sapiens GN=S100A8 PE=1 14.67 30.50 ‐15.83 SV=1 IL1F9_HUMAN Interleukin‐1 family member 9 OS=Homo sapiens 1.00 15.00 ‐14.00 GN=IL1F9 PE=1 SV=1 MUC5B_HUMAN Mucin‐5B OS=Homo sapiens GN=MUC5B PE=1 SV=3 2.00 14.00 ‐12.00 MUC4_HUMAN Mucin‐4 OS=Homo sapiens GN=MUC4 PE=1 SV=3 1.00 12.00 ‐11.00 HRG_HUMAN Histidine‐rich glycoprotein OS=Homo sapiens GN=HRG 1.00 12.00 ‐11.00 PE=1 SV=1 TKT_HUMAN Transketolase OS=Homo sapiens GN=TKT PE=1 SV=3 17.00 28.00 ‐11.00 CATG_HUMAN Cathepsin G OS=Homo -
Contig Protein Description Symbol Anterior Posterior Ratio
Table S2. List of proteins detected in anterior and posterior intestine pooled samples. Data on protein expression are mean ± SEM of 4 pools fed the experimental diets. The number of the contig in the Sea Bream Database (http://nutrigroup-iats.org/seabreamdb) is indicated. Contig Protein Description Symbol Anterior Posterior Ratio Ant/Pos C2_6629 1,4-alpha-glucan-branching enzyme GBE1 0.88±0.1 0.91±0.03 0.98 C2_4764 116 kDa U5 small nuclear ribonucleoprotein component EFTUD2 0.74±0.09 0.71±0.05 1.03 C2_299 14-3-3 protein beta/alpha-1 YWHAB 1.45±0.23 2.18±0.09 0.67 C2_268 14-3-3 protein epsilon YWHAE 1.28±0.2 2.01±0.13 0.63 C2_2474 14-3-3 protein gamma-1 YWHAG 1.8±0.41 2.72±0.09 0.66 C2_1017 14-3-3 protein zeta YWHAZ 1.33±0.14 4.41±0.38 0.30 C2_34474 14-3-3-like protein 2 YWHAQ 1.3±0.11 1.85±0.13 0.70 C2_4902 17-beta-hydroxysteroid dehydrogenase 14 HSD17B14 0.93±0.05 2.33±0.09 0.40 C2_3100 1-acylglycerol-3-phosphate O-acyltransferase ABHD5 ABHD5 0.85±0.07 0.78±0.13 1.10 C2_15440 1-phosphatidylinositol phosphodiesterase PLCD1 0.65±0.12 0.4±0.06 1.65 C2_12986 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase delta-1 PLCD1 0.76±0.08 1.15±0.16 0.66 C2_4412 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-2 PLCG2 1.13±0.08 2.08±0.27 0.54 C2_3170 2,4-dienoyl-CoA reductase, mitochondrial DECR1 1.16±0.1 0.83±0.03 1.39 C2_1520 26S protease regulatory subunit 10B PSMC6 1.37±0.21 1.43±0.04 0.96 C2_4264 26S protease regulatory subunit 4 PSMC1 1.2±0.2 1.78±0.08 0.68 C2_1666 26S protease regulatory subunit 6A PSMC3 1.44±0.24 1.61±0.08 -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Enzyme DHRS7
Toward the identification of a function of the “orphan” enzyme DHRS7 Inauguraldissertation zur Erlangung der Würde eines Doktors der Philosophie vorgelegt der Philosophisch-Naturwissenschaftlichen Fakultät der Universität Basel von Selene Araya, aus Lugano, Tessin Basel, 2018 Originaldokument gespeichert auf dem Dokumentenserver der Universität Basel edoc.unibas.ch Genehmigt von der Philosophisch-Naturwissenschaftlichen Fakultät auf Antrag von Prof. Dr. Alex Odermatt (Fakultätsverantwortlicher) und Prof. Dr. Michael Arand (Korreferent) Basel, den 26.6.2018 ________________________ Dekan Prof. Dr. Martin Spiess I. List of Abbreviations 3α/βAdiol 3α/β-Androstanediol (5α-Androstane-3α/β,17β-diol) 3α/βHSD 3α/β-hydroxysteroid dehydrogenase 17β-HSD 17β-Hydroxysteroid Dehydrogenase 17αOHProg 17α-Hydroxyprogesterone 20α/βOHProg 20α/β-Hydroxyprogesterone 17α,20α/βdiOHProg 20α/βdihydroxyprogesterone ADT Androgen deprivation therapy ANOVA Analysis of variance AR Androgen Receptor AKR Aldo-Keto Reductase ATCC American Type Culture Collection CAM Cell Adhesion Molecule CYP Cytochrome P450 CBR1 Carbonyl reductase 1 CRPC Castration resistant prostate cancer Ct-value Cycle threshold-value DHRS7 (B/C) Dehydrogenase/Reductase Short Chain Dehydrogenase Family Member 7 (B/C) DHEA Dehydroepiandrosterone DHP Dehydroprogesterone DHT 5α-Dihydrotestosterone DMEM Dulbecco's Modified Eagle's Medium DMSO Dimethyl Sulfoxide DTT Dithiothreitol E1 Estrone E2 Estradiol ECM Extracellular Membrane EDTA Ethylenediaminetetraacetic acid EMT Epithelial-mesenchymal transition ER Endoplasmic Reticulum ERα/β Estrogen Receptor α/β FBS Fetal Bovine Serum 3 FDR False discovery rate FGF Fibroblast growth factor HEPES 4-(2-Hydroxyethyl)-1-Piperazineethanesulfonic Acid HMDB Human Metabolome Database HPLC High Performance Liquid Chromatography HSD Hydroxysteroid Dehydrogenase IC50 Half-Maximal Inhibitory Concentration LNCaP Lymph node carcinoma of the prostate mRNA Messenger Ribonucleic Acid n.d. -
140503 IPF Signatures Supplement Withfigs Thorax
Supplementary material for Heterogeneous gene expression signatures correspond to distinct lung pathologies and biomarkers of disease severity in idiopathic pulmonary fibrosis Daryle J. DePianto1*, Sanjay Chandriani1⌘*, Alexander R. Abbas1, Guiquan Jia1, Elsa N. N’Diaye1, Patrick Caplazi1, Steven E. Kauder1, Sabyasachi Biswas1, Satyajit K. Karnik1#, Connie Ha1, Zora Modrusan1, Michael A. Matthay2, Jasleen Kukreja3, Harold R. Collard2, Jackson G. Egen1, Paul J. Wolters2§, and Joseph R. Arron1§ 1Genentech Research and Early Development, South San Francisco, CA 2Department of Medicine, University of California, San Francisco, CA 3Department of Surgery, University of California, San Francisco, CA ⌘Current address: Novartis Institutes for Biomedical Research, Emeryville, CA. #Current address: Gilead Sciences, Foster City, CA. *DJD and SC contributed equally to this manuscript §PJW and JRA co-directed this project Address correspondence to Paul J. Wolters, MD University of California, San Francisco Department of Medicine Box 0111 San Francisco, CA 94143-0111 [email protected] or Joseph R. Arron, MD, PhD Genentech, Inc. MS 231C 1 DNA Way South San Francisco, CA 94080 [email protected] 1 METHODS Human lung tissue samples Tissues were obtained at UCSF from clinical samples from IPF patients at the time of biopsy or lung transplantation. All patients were seen at UCSF and the diagnosis of IPF was established through multidisciplinary review of clinical, radiological, and pathological data according to criteria established by the consensus classification of the American Thoracic Society (ATS) and European Respiratory Society (ERS), Japanese Respiratory Society (JRS), and the Latin American Thoracic Association (ALAT) (ref. 5 in main text). Non-diseased normal lung tissues were procured from lungs not used by the Northern California Transplant Donor Network. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Molecular Mechanisms Regulating Copper Balance in Human Cells
MOLECULAR MECHANISMS REGULATING COPPER BALANCE IN HUMAN CELLS by Nesrin M. Hasan A dissertation submitted to Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland August 2014 ©2014 Nesrin M. Hasan All Rights Reserved Intended to be blank ii ABSTRACT Precise copper balance is essential for normal growth, differentiation, and function of human cells. Loss of copper homeostasis is associated with heart hypertrophy, liver failure, neuronal de-myelination and other pathologies. The copper-transporting ATPases ATP7A and ATP7B maintain cellular copper homeostasis. In response to copper elevation, they traffic from the trans-Golgi network (TGN) to vesicles where they sequester excess copper for further export. The mechanisms regulating activity and trafficking of ATP7A/7B are not well understood. Our studies focused on determining the role of kinase-mediated phosphorylation in copper induced trafficking of ATP7B, and identifying and characterizing novel regulators of ATP7A. We have shown that Ser- 340/341 region of ATP7B plays an important role in interactions between the N-terminus and the nucleotide-binding domain and that mutations in these residues result in vesicular localization of the protein independent of the intracellular copper levels. We have determined that structural changes that alter the inter-domain interactions initiate exit of ATP7B from the TGN and that the role of copper-induced kinase-mediated hyperphosphorylation might be to maintain an open interface between the domains of ATP7B. In a separate study, seven proteins were identified, which upon knockdown result in increased intracellular copper levels. We performed an initial characterization of the knock-downs and obtained intriguing results indicating that these proteins regulate ATP7A protein levels, post-translational modifications, and copper-dependent trafficking. -
(12) Patent Application Publication (10) Pub. No.: US 2003/0082511 A1 Brown Et Al
US 20030082511A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2003/0082511 A1 Brown et al. (43) Pub. Date: May 1, 2003 (54) IDENTIFICATION OF MODULATORY Publication Classification MOLECULES USING INDUCIBLE PROMOTERS (51) Int. Cl." ............................... C12O 1/00; C12O 1/68 (52) U.S. Cl. ..................................................... 435/4; 435/6 (76) Inventors: Steven J. Brown, San Diego, CA (US); Damien J. Dunnington, San Diego, CA (US); Imran Clark, San Diego, CA (57) ABSTRACT (US) Correspondence Address: Methods for identifying an ion channel modulator, a target David B. Waller & Associates membrane receptor modulator molecule, and other modula 5677 Oberlin Drive tory molecules are disclosed, as well as cells and vectors for Suit 214 use in those methods. A polynucleotide encoding target is San Diego, CA 92121 (US) provided in a cell under control of an inducible promoter, and candidate modulatory molecules are contacted with the (21) Appl. No.: 09/965,201 cell after induction of the promoter to ascertain whether a change in a measurable physiological parameter occurs as a (22) Filed: Sep. 25, 2001 result of the candidate modulatory molecule. Patent Application Publication May 1, 2003 Sheet 1 of 8 US 2003/0082511 A1 KCNC1 cDNA F.G. 1 Patent Application Publication May 1, 2003 Sheet 2 of 8 US 2003/0082511 A1 49 - -9 G C EH H EH N t R M h so as se W M M MP N FIG.2 Patent Application Publication May 1, 2003 Sheet 3 of 8 US 2003/0082511 A1 FG. 3 Patent Application Publication May 1, 2003 Sheet 4 of 8 US 2003/0082511 A1 KCNC1 ITREXCHO KC 150 mM KC 2000000 so 100 mM induced Uninduced Steady state O 100 200 300 400 500 600 700 Time (seconds) FIG. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Lipoprotein Lipase: a General Review Moacir Couto De Andrade Júnior1,2*
Review Article iMedPub Journals Insights in Enzyme Research 2018 www.imedpub.com Vol.2 No.1:3 ISSN 2573-4466 DOI: 10.21767/2573-4466.100013 Lipoprotein Lipase: A General Review Moacir Couto de Andrade Júnior1,2* 1Post-Graduation Department, Nilton Lins University, Manaus, Amazonas, Brazil 2Department of Food Technology, Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Amazonas, Brazil *Corresponding author: MC Andrade Jr, Post-Graduation Department, Nilton Lins University, Manaus, Amazonas, Brazil, Tel: +55 (92) 3633-8028; E-mail: [email protected] Rec date: March 07, 2018; Acc date: April 10, 2018; Pub date: April 17, 2018 Copyright: © 2018 Andrade Jr MC. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Citation: Andrade Jr MC (2018) Lipoprotein Lipase: A General Review. Insights Enzyme Res Vol.2 No.1:3 Abstract Lipoprotein Lipase: Historical Hallmarks, Enzymatic Activity, Characterization, and Carbohydrates (e.g., glucose) and lipids (e.g., free fatty acids or FFAs) are the most important sources of energy Present Relevance in Human for most organisms, including humans. Lipoprotein lipase (LPL) is an extracellular enzyme (EC 3.1.1.34) that is Pathophysiology and Therapeutics essential in lipoprotein metabolism. LPL is a glycoprotein that is synthesized and secreted in several tissues (e.g., Macheboeuf, in 1929, first described chemical procedures adipose tissue, skeletal muscle, cardiac muscle, and for the isolation of a plasma protein fraction that was very rich macrophages). At the luminal surface of the vascular in lipids but readily soluble in water, such as a lipoprotein [1]. -
Toxicogenomic Approach to Impact Assessment of Whole Wastewater Effluents and Development of Effluent- Title Responsive Biomarker
Toxicogenomic Approach to Impact Assessment of Whole Wastewater Effluents and Development of Effluent- Title Responsive Biomarker Author(s) 山村, 宏江 Citation 北海道大学. 博士(工学) 甲第11137号 Issue Date 2013-09-25 DOI 10.14943/doctoral.k11137 Doc URL http://hdl.handle.net/2115/77180 Type theses (doctoral) File Information Hiroe_Yamamura.pdf Instructions for use Hokkaido University Collection of Scholarly and Academic Papers : HUSCAP Doctoral Thesis Toxicogenomic Approach to Impact Assessment of Whole Wastewater Effluents and Development of Effluent-Responsive Biomarker Hiroe Hara-Yamamura Acknowledgement My doctoral research works presented here cannot be completed without a numerous number of tangible and intangible supports from my peers, my supervisor, instructors, friends, and family. I would first express my deepest gratitude to Prof. Satoshi OKABE for his technical advices and crisp ideas which often came to break the deadlock of my research progress, and for continued provision of another chance to me, even in the least fruitful season. Indeed, my three years in Prof. OKABE’s lab was “luxuri- ous” time in my life with a lot of supports, encouragements, and chances. In addition, I appreciate both Prof. Daisuke SANO and Dr. Satoshi ISHII for offering their insights on my experimental design and data analysis as well as giving me words of encouragements from time to time. Also, thank you to Prof. Takashi KUSUI from Toyama Prefectural University for his assistance to bioassay techniques and valuable discussion dur- ing my 1st year and 2nd year evaluation presentations. Furthermore, I would like to express my gratitude to specific efforts kindly provide by: Mr. Kenzo Kudo, Prof.