Regulatory Mechanism of Fatty Acid‑Coa Metabolic Enzymes Under Endoplasmic Reticulum Stress in Lung Cancer
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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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. -
(12) Patent Application Publication (10) Pub. No.: US 2015/0337275 A1 Pearlman Et Al
US 20150337275A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2015/0337275 A1 Pearlman et al. (43) Pub. Date: Nov. 26, 2015 (54) BOCONVERSION PROCESS FOR Publication Classification PRODUCING NYLON-7, NYLON-7.7 AND POLYESTERS (51) Int. C. CI2N 9/10 (2006.01) (71) Applicant: INVISTATECHNOLOGIES S.a.r.l., CI2P 7/40 (2006.01) St. Gallen (CH) CI2PI3/00 (2006.01) CI2PI3/04 (2006.01) (72) Inventors: Paul S. Pearlman, Thornton, PA (US); CI2P 13/02 (2006.01) Changlin Chen, Cleveland (GB); CI2N 9/16 (2006.01) Adriana L. Botes, Cleveland (GB); Alex CI2N 9/02 (2006.01) Van Eck Conradie, Cleveland (GB); CI2N 9/00 (2006.01) Benjamin D. Herzog, Wichita, KS (US) CI2P 7/44 (2006.01) CI2P I 7/10 (2006.01) (73) Assignee: INVISTATECHNOLOGIES S.a.r.l., (52) U.S. C. St. Gallen (CH) CPC. CI2N 9/13 (2013.01); C12P 7/44 (2013.01); CI2P 7/40 (2013.01); CI2P 13/005 (2013.01); (21) Appl. No.: 14/367,484 CI2P 17/10 (2013.01); CI2P 13/02 (2013.01); CI2N 9/16 (2013.01); CI2N 9/0008 (2013.01); (22) PCT Fled: Dec. 21, 2012 CI2N 9/93 (2013.01); CI2P I3/04 (2013.01); PCT NO.: PCT/US2012/071.472 CI2P 13/001 (2013.01); C12Y 102/0105 (86) (2013.01) S371 (c)(1), (2) Date: Jun. 20, 2014 (57) ABSTRACT Embodiments of the present invention relate to methods for Related U.S. Application Data the biosynthesis of di- or trifunctional C7 alkanes in the (60) Provisional application No. -
The Role of the Mtor Pathway in Developmental Reprogramming Of
THE ROLE OF THE MTOR PATHWAY IN DEVELOPMENTAL REPROGRAMMING OF HEPATIC LIPID METABOLISM AND THE HEPATIC TRANSCRIPTOME AFTER EXPOSURE TO 2,2',4,4'- TETRABROMODIPHENYL ETHER (BDE-47) An Honors Thesis Presented By JOSEPH PAUL MCGAUNN Approved as to style and content by: ________________________________________________________** Alexander Suvorov 05/18/20 10:40 ** Chair ________________________________________________________** Laura V Danai 05/18/20 10:51 ** Committee Member ________________________________________________________** Scott C Garman 05/18/20 10:57 ** Honors Program Director ABSTRACT An emerging hypothesis links the epidemic of metabolic diseases, such as non-alcoholic fatty liver disease (NAFLD) and diabetes with chemical exposures during development. Evidence from our lab and others suggests that developmental exposure to environmentally prevalent flame-retardant BDE47 may permanently reprogram hepatic lipid metabolism, resulting in an NAFLD-like phenotype. Additionally, we have demonstrated that BDE-47 alters the activity of both mTOR complexes (mTORC1 and 2) in hepatocytes. The mTOR pathway integrates environmental information from different signaling pathways, and regulates key cellular functions such as lipid metabolism, innate immunity, and ribosome biogenesis. Thus, we hypothesized that the developmental effects of BDE-47 on liver lipid metabolism are mTOR-dependent. To assess this, we generated mice with liver-specific deletions of mTORC1 or mTORC2 and exposed these mice and their respective controls perinatally to -
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. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Loss of Fam60a, a Sin3a Subunit, Results in Embryonic Lethality and Is Associated with Aberrant Methylation at a Subset of Gene
RESEARCH ARTICLE Loss of Fam60a, a Sin3a subunit, results in embryonic lethality and is associated with aberrant methylation at a subset of gene promoters Ryo Nabeshima1,2, Osamu Nishimura3,4, Takako Maeda1, Natsumi Shimizu2, Takahiro Ide2, Kenta Yashiro1†, Yasuo Sakai1, Chikara Meno1, Mitsutaka Kadota3,4, Hidetaka Shiratori1†, Shigehiro Kuraku3,4*, Hiroshi Hamada1,2* 1Developmental Genetics Group, Graduate School of Frontier Biosciences, Osaka University, Suita, Japan; 2Laboratory for Organismal Patterning, RIKEN Center for Developmental Biology, Kobe, Japan; 3Phyloinformatics Unit, RIKEN Center for Life Science Technologies, Kobe, Japan; 4Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan Abstract We have examined the role of Fam60a, a gene highly expressed in embryonic stem cells, in mouse development. Fam60a interacts with components of the Sin3a-Hdac transcriptional corepressor complex, and most Fam60a–/– embryos manifest hypoplasia of visceral organs and die in utero. Fam60a is recruited to the promoter regions of a subset of genes, with the expression of these genes being either up- or down-regulated in Fam60a–/– embryos. The DNA methylation level of the Fam60a target gene Adhfe1 is maintained at embryonic day (E) 7.5 but markedly reduced at –/– *For correspondence: E9.5 in Fam60a embryos, suggesting that DNA demethylation is enhanced in the mutant. [email protected] (SK); Examination of genome-wide DNA methylation identified several differentially methylated regions, [email protected] (HH) which were preferentially hypomethylated, in Fam60a–/– embryos. Our data suggest that Fam60a is †These authors contributed required for proper embryogenesis, at least in part as a result of its regulation of DNA methylation equally to this work at specific gene promoters. -
Human ACOT11 Antibody Catalog Number: AFA0903
Human ACOT11 antibody Catalog Number: AFA0903 PRODUCT INPORMATION Catalog number AFA0903 Clone No. J4B2 Product type Monoclonal Antibody UnitProt No. Q8WXI4 NCBI Accession No. NP_671517 Alternative Names thioesterase, adipose associated isoform BFIT2, acyl-CoA thioesterase 11, thioesterase, adipose associated, STARD14, BFIT, KIAA0707, BFIT1, THEM1, StAR-related lipid transfer (START) domain containing 14 PRODUCT SPECIFICATION Antibody Host Mouse Reacts With Human Concentration 1mg/ml (determined by BCA assay) Formulation Liquid in. Phosphate-Buffered Saline (pH 7.4) with 0.02% Sodium Azide, 10% glycerol Immunogen Recombinant human ACOT11 (19-250aa) purified from E. coli Isotype IgG2b kappa Purification Note By protein-G affinity chromatography Application ELISA,WB,IHC Usage The antibody has been tested by ELISA, Western blot and IHC analysis to assure specificity and reactivity. Since application varies, however, each investigation should be titrated by the reagent to obtain optimal results. 1 Human ACOT11 antibody Catalog Number: AFA0903 Storage Can be stored at +2C to +8C for 1 week. For long term storage, aliquot and store at -20C to -80C. Avoid repeated freezing and thawing cycles. BACKGROUND Description ACOT11 (Acyl-CoA thioesterase11), also known as BFIT, is a protein with acyl-CoA thioesterase activity towards medium (C12) and long-chain (C18) fatty acyl-CoA substrates. Expression of this protein in mouse has been associated with obesity and alternative splicing results in two transcript variants encoding different isoforms. General References S. H. Adams, et al: (2001) Biochem. J. 360, 135-142. DATA Western blot analysis (WB) The cell lysates of LNCap, Hep3B (30ug) were resolved by SDS-PAGE, transferred to NC membrane and probed with anti-human ACOT11 (1:1000). -
Mergeomics: Multidimensional Data Integration to Identify Pathogenic Perturbations to Biological Systems
Shu et al. BMC Genomics (2016) 17:874 DOI 10.1186/s12864-016-3198-9 METHODOLOGY ARTICLE Open Access Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems Le Shu1, Yuqi Zhao1, Zeyneb Kurt1, Sean Geoffrey Byars2,3, Taru Tukiainen4, Johannes Kettunen4, Luz D. Orozco5, Matteo Pellegrini5, Aldons J. Lusis6, Samuli Ripatti4, Bin Zhang7, Michael Inouye2,3,8, Ville-Petteri Mäkinen1,9,10,11* and Xia Yang1,12* Abstract Background: Complex diseases are characterized by multiple subtle perturbations to biological processes. New omics platforms can detect these perturbations, but translating the diverse molecular and statistical information into testable mechanistic hypotheses is challenging. Therefore, we set out to create a public tool that integrates these data across multiple datasets, platforms, study designs and species in order to detect the most promising targets for further mechanistic studies. Results: We developed Mergeomics, a computational pipeline consisting of independent modules that 1) leverage multi-omics association data to identify biological processes that are perturbed in disease, and 2) overlay the disease- associated processes onto molecular interaction networks to pinpoint hubs as potential key regulators. Unlike existing tools that are mostly dedicated to specific data type or settings, the Mergeomics pipeline accepts and integrates datasets across platforms, data types and species. We optimized and evaluated the performance of Mergeomics using simulation and multiple independent datasets, and benchmarked the results against alternative methods. We also demonstrate the versatility of Mergeomics in two case studies that include genome-wide, epigenome-wide and transcriptome-wide datasets from human and mouse studies of total cholesterol and fasting glucose. -
Thioesterase Superfamily Member 1 Undergoes Stimulus-Coupled Conformational Reorganization to Regulate Metabolism in Mice
ARTICLE https://doi.org/10.1038/s41467-021-23595-x OPEN Thioesterase superfamily member 1 undergoes stimulus-coupled conformational reorganization to regulate metabolism in mice Yue Li 1,2, Norihiro Imai3, Hayley T. Nicholls 3, Blaine R. Roberts 4, Samaksh Goyal 1,2, Tibor I. Krisko 3, Lay-Hong Ang 1,2, Matthew C. Tillman4, Anne M. Roberts4, Mahnoor Baqai 1,2, Eric A. Ortlund 4, ✉ ✉ David E. Cohen 3 & Susan J. Hagen 1,2 1234567890():,; In brown adipose tissue, thermogenesis is suppressed by thioesterase superfamily member 1 (Them1), a long chain fatty acyl-CoA thioesterase. Them1 is highly upregulated by cold ambient temperature, where it reduces fatty acid availability and limits thermogenesis. Here, we show that Them1 regulates metabolism by undergoing conformational changes in response to β-adrenergic stimulation that alter Them1 intracellular distribution. Them1 forms metabolically active puncta near lipid droplets and mitochondria. Upon stimulation, Them1 is phosphorylated at the N-terminus, inhibiting puncta formation and activity and resulting in a diffuse intracellular localization. We show by correlative light and electron microscopy that Them1 puncta are biomolecular condensates that are inhibited by phosphorylation. Thus, Them1 forms intracellular biomolecular condensates that limit fatty acid oxidation and sup- press thermogenesis. During a period of energy demand, the condensates are disrupted by phosphorylation to allow for maximal thermogenesis. The stimulus-coupled reorganization of Them1 provides fine-tuning of thermogenesis and energy expenditure. 1 Division of General Surgery, Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA. 2 Department of Surgery, Harvard Medical School, Boston, MA, USA. 3 Division of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medical College, New York, NY, USA. -
The Unfolded Protein Response: an Overview
biology Review The Unfolded Protein Response: An Overview Adam Read 1,2 and Martin Schröder 1,2,* 1 Department of Biosciences, Durham University, South Road, Durham DH1 3LE, UK; [email protected] 2 Biophysical Sciences Institute, Durham University, South Road, Durham DH1 3LE, UK * Correspondence: [email protected]; Tel.: +44-191-334-1316 Simple Summary: The unfolded protein response (UPR) is the cells’ way of maintaining the balance of protein folding in the endoplasmic reticulum, which is the section of the cell designated for folding proteins with specific destinations such as other organelles or to be secreted by the cell. The UPR is activated when unfolded proteins accumulate in the endoplasmic reticulum. This accumulation puts a greater load on the molecules in charge of folding the proteins, and therefore the UPR works to balance this by lowering the number of unfolded proteins present in the cell. This is done in multiple ways, such as lowering the number of proteins that need to be folded; increasing the folding ability of the endoplasmic reticulum and by removing some of the unfolded proteins which take longer to fold. If the UPR is successful at reducing the number of unfolded proteins, the UPR is inactivated and the cells protein folding balance is returned to normal. However, if the UPR is unsuccessful, then this can lead to cell death. Abstract: The unfolded protein response is the mechanism by which cells control endoplasmic reticulum (ER) protein homeostasis. Under normal conditions, the UPR is not activated; however, under certain stresses, such as hypoxia or altered glycosylation, the UPR can be activated due to an accumulation of unfolded proteins. -
Adipose Tissue NAPE-PLD Controls Fat Mass Development by Altering the Browning Process and Gut Microbiota
ARTICLE Received 11 Jul 2014 | Accepted 4 Feb 2015 | Published 11 Mar 2015 DOI: 10.1038/ncomms7495 OPEN Adipose tissue NAPE-PLD controls fat mass development by altering the browning process and gut microbiota Lucie Geurts1, Amandine Everard1,*, Matthias Van Hul1,*, Ahmed Essaghir2, Thibaut Duparc1, Se´bastien Matamoros1, Hubert Plovier1, Julien Castel3, Raphael G.P. Denis3, Marie Bergiers1, Ce´line Druart1, Mireille Alhouayek4, Nathalie M. Delzenne1, Giulio G. Muccioli4, Jean-Baptiste Demoulin2, Serge Luquet3 & Patrice D. Cani1 Obesity is a pandemic disease associated with many metabolic alterations and involves several organs and systems. The endocannabinoid system (ECS) appears to be a key regulator of energy homeostasis and metabolism. Here we show that specific deletion of the ECS synthesizing enzyme, NAPE-PLD, in adipocytes induces obesity, glucose intolerance, adipose tissue inflammation and altered lipid metabolism. We report that Napepld-deleted mice present an altered browning programme and are less responsive to cold-induced browning, highlighting the essential role of NAPE-PLD in regulating energy homeostasis and metabolism in the physiological state. Our results indicate that these alterations are mediated by a shift in gut microbiota composition that can partially transfer the phenotype to germ-free mice. Together, our findings uncover a role of adipose tissue NAPE-PLD on whole-body metabolism and provide support for targeting NAPE-PLD-derived bioactive lipids to treat obesity and related metabolic disorders. 1 Metabolism and Nutrition Research Group, WELBIO-Walloon Excellence in Life Sciences and BIOtechnology, Louvain Drug Research Institute, Universite´ catholique de Louvain, Avenue E. Mounier, 73 B1.73.11, 1200 Brussels, Belgium. 2 de Duve Institute, Universite´ catholique de Louvain, Avenue Hippocrate, 74 B1.74.05, 1200 Brussels, Belgium. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase