In Saccharomyces Cerevisiae
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
An Essential Role for Maternal Control of Nodal Signaling
RESEARCH ARTICLE elife.elifesciences.org An essential role for maternal control of Nodal signaling Pooja Kumari1,2†, Patrick C Gilligan1†, Shimin Lim1,3, Long Duc Tran4, Sylke Winkler5, Robin Philp6‡, Karuna Sampath1,2,3* 1Temasek Life Sciences Laboratory, National University of Singapore, Singapore, Singapore; 2Department of Biological Sciences, National University of Singapore, Singapore, Singapore; 3School of Biological Sciences, Nanyang Technological University, Singapore, Singapore; 4Mechanobiology Institute, National University of Singapore, Singapore, Singapore; 5Department of Cell Biology and Genetics, Max Planck Institute for Molecular Cell Biology and Genetics, Dresden, Germany; 6Bioprocessing Technology Institute, A*STAR, Singapore, Singapore Abstract Growth factor signaling is essential for pattern formation, growth, differentiation, and maintenance of stem cell pluripotency. Nodal-related signaling factors are required for axis formation and germ layer specification from sea urchins to mammals. Maternal transcripts of the zebrafish Nodal factor, Squint (Sqt), are localized to future embryonic dorsal. The mechanisms by which maternal sqt/nodal RNA is localized and regulated have been unclear. Here, we show that maternal control of Nodal signaling via the conserved Y box-binding protein 1 (Ybx1) is essential. We identified Ybx1 via a proteomic screen. Ybx1 recognizes the 3’ untranslated region (UTR) of *For correspondence: karuna@ sqt RNA and prevents premature translation and Sqt/Nodal signaling. Maternal-effect mutations in tll.org.sg zebrafish ybx1 lead to deregulated Nodal signaling, gastrulation failure, and embryonic lethality. Implanted Nodal-coated beads phenocopy ybx1 mutant defects. Thus, Ybx1 prevents ectopic † These authors contributed Nodal activity, revealing a new paradigm in the regulation of Nodal signaling, which is likely to equally to this work be conserved. -
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. -
A Flexible Microfluidic System for Single-Cell Transcriptome Profiling
www.nature.com/scientificreports OPEN A fexible microfuidic system for single‑cell transcriptome profling elucidates phased transcriptional regulators of cell cycle Karen Davey1,7, Daniel Wong2,7, Filip Konopacki2, Eugene Kwa1, Tony Ly3, Heike Fiegler2 & Christopher R. Sibley 1,4,5,6* Single cell transcriptome profling has emerged as a breakthrough technology for the high‑resolution understanding of complex cellular systems. Here we report a fexible, cost‑efective and user‑ friendly droplet‑based microfuidics system, called the Nadia Instrument, that can allow 3′ mRNA capture of ~ 50,000 single cells or individual nuclei in a single run. The precise pressure‑based system demonstrates highly reproducible droplet size, low doublet rates and high mRNA capture efciencies that compare favorably in the feld. Moreover, when combined with the Nadia Innovate, the system can be transformed into an adaptable setup that enables use of diferent bufers and barcoded bead confgurations to facilitate diverse applications. Finally, by 3′ mRNA profling asynchronous human and mouse cells at diferent phases of the cell cycle, we demonstrate the system’s ability to readily distinguish distinct cell populations and infer underlying transcriptional regulatory networks. Notably this provided supportive evidence for multiple transcription factors that had little or no known link to the cell cycle (e.g. DRAP1, ZKSCAN1 and CEBPZ). In summary, the Nadia platform represents a promising and fexible technology for future transcriptomic studies, and other related applications, at cell resolution. Single cell transcriptome profling has recently emerged as a breakthrough technology for understanding how cellular heterogeneity contributes to complex biological systems. Indeed, cultured cells, microorganisms, biopsies, blood and other tissues can be rapidly profled for quantifcation of gene expression at cell resolution. -
Supplementary Materials
Supplementary Materials COMPARATIVE ANALYSIS OF THE TRANSCRIPTOME, PROTEOME AND miRNA PROFILE OF KUPFFER CELLS AND MONOCYTES Andrey Elchaninov1,3*, Anastasiya Lokhonina1,3, Maria Nikitina2, Polina Vishnyakova1,3, Andrey Makarov1, Irina Arutyunyan1, Anastasiya Poltavets1, Evgeniya Kananykhina2, Sergey Kovalchuk4, Evgeny Karpulevich5,6, Galina Bolshakova2, Gennady Sukhikh1, Timur Fatkhudinov2,3 1 Laboratory of Regenerative Medicine, National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of Ministry of Healthcare of Russian Federation, Moscow, Russia 2 Laboratory of Growth and Development, Scientific Research Institute of Human Morphology, Moscow, Russia 3 Histology Department, Medical Institute, Peoples' Friendship University of Russia, Moscow, Russia 4 Laboratory of Bioinformatic methods for Combinatorial Chemistry and Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia 5 Information Systems Department, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow, Russia 6 Genome Engineering Laboratory, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia Figure S1. Flow cytometry analysis of unsorted blood sample. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S2. Flow cytometry analysis of unsorted liver stromal cells. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S3. MiRNAs expression analysis in monocytes and Kupffer cells. Full-length of heatmaps are presented. -
2012-2013 Seminars
2012-13 Archived Seminars 8/14/14 12:42 PM A Cornell University • Deparhnent of Iv1olecular Biology and Genetics 2012-13 Archived Seminars May 24, 2013 Speaker: Julius Lucks Department of Chemical and Biomedical Engineering Cornell University Title: "Towards Unraveling the RNA Sequence-Structure Code Using High Throughput RNA Structrure Characterizaion" Host: Sylvia Lee http://www.cheme.cornell.edu/people/profile.cfm?netid=jl564 May 17, 2013 W. Lee Kraus Distinguished Chair & Director, Cecil H. and Ida Green Ctr. for Reproductive Biology Sciences Professor & Vice Chair for Basic Science, Dept of Ob/Gyn Professor, Department of Pharmacology University of Texas Southwestern Medical Ctr. @ Dallas Title: "Chromatin-Mediated Gene Regulation by PARP-1: Control of Cellular Signaling and Differentiation Programs" Host: John Lis http://www.utsouthwestern.edu/education/medical-school/departments/green-center/index.html May 9, 2013 (THURSDAY) Brenton Graveley University of Connecticut Health Center Genetics and Developmental Biology Title: "Insights into RNA Biology in Drosophila from Genome-Wide Studies" Host: Jeff Pleiss http://genetics.uchc.edu/faculty/assoc_professors/graveley.html May 3, 2013 Bill Kelly Emory University Department of Biology Title: "Remembrance of Transcriptiones Past: Germline-Specific Modes of Transcription Regulation in C. elegans" Host: Kelly Liu http://www.biology.emory.edu/research/Kelly/members/Bill.html April 26, 2013 Kevin Struhl Harvard Medical School Dept. of Biological Chemistry & Molecular Pharmacology Title: "Transcriptional -
DR1 Antibody A
Revision 1 C 0 2 - t DR1 Antibody a e r o t S Orders: 877-616-CELL (2355) [email protected] Support: 877-678-TECH (8324) 7 4 Web: [email protected] 4 www.cellsignal.com 6 # 3 Trask Lane Danvers Massachusetts 01923 USA For Research Use Only. Not For Use In Diagnostic Procedures. Applications: Reactivity: Sensitivity: MW (kDa): Source: UniProt ID: Entrez-Gene Id: WB, IP H M R Mk Endogenous 19 Rabbit Q01658 1810 Product Usage Information 7. Yeung, K.C. et al. (1994) Genes Dev 8, 2097-109. 8. Kim, T.K. et al. (1995) J Biol Chem 270, 10976-81. Application Dilution 9. Kamada, K. et al. (2001) Cell 106, 71-81. Western Blotting 1:1000 Immunoprecipitation 1:50 Storage Supplied in 10 mM sodium HEPES (pH 7.5), 150 mM NaCl, 100 µg/ml BSA and 50% glycerol. Store at –20°C. Do not aliquot the antibody. Specificity / Sensitivity DR1 Antibody recognizes endogenous levels of total DR1 protein. Species Reactivity: Human, Mouse, Rat, Monkey Species predicted to react based on 100% sequence homology: D. melanogaster, Zebrafish, Dog, Pig Source / Purification Polyclonal antibodies are produced by immunizing animals with a synthetic peptide corresponding to residues surrounding Gly112 of human DR1 protein. Antibodies are purified by protein A and peptide affinity chromatography. Background Down-regulator of transcription 1 (DR1), also known as negative cofactor 2-β (NC2-β), forms a heterodimer with DR1 associated protein 1 (DRAP1)/NC2-α and acts as a negative regulator of RNA polymerase II and III (RNAPII and III) transcription (1-5). -
Product Data Sheet
For research purposes only, not for human use Product Data Sheet DRAP1 siRNA (Rat) Catalog # Source Reactivity Applications CRR4301 Synthetic R RNAi Description siRNA to inhibit DRAP1 expression using RNA interference Specificity DRAP1 siRNA (Rat) is a target-specific 19-23 nt siRNA oligo duplexes designed to knock down gene expression. Form Lyophilized powder Gene Symbol DRAP1 Alternative Names Dr1-associated corepressor; Dr1-associated protein 1; Negative cofactor 2-alpha; NC2-alpha Entrez Gene 293674 (Rat) SwissProt A0JPP1 (Rat) Purity > 97% Quality Control Oligonucleotide synthesis is monitored base by base through trityl analysis to ensure appropriate coupling efficiency. The oligo is subsequently purified by affinity-solid phase extraction. The annealed RNA duplex is further analyzed by mass spectrometry to verify the exact composition of the duplex. Each lot is compared to the previous lot by mass spectrometry to ensure maximum lot-to-lot consistency. Components We offers pre-designed sets of 3 different target-specific siRNA oligo duplexes of rat DRAP1 gene. Each vial contains 5 nmol of lyophilized siRNA. The duplexes can be transfected individually or pooled together to achieve knockdown of the target gene, which is most commonly assessed by qPCR or western blot. Our siRNA oligos are also chemically modified (2’-OMe) at no extra charge for increased stability and enhanced knockdown in vitro and in vivo. Application key: E- ELISA, WB- Western blot, IH- Immunohistochemistry, IF- Immunofluorescence, FC- Flow cytometry, IC- Immunocytochemistry, -
Malaria Polyclonal B Cell Activator Activation of the Memory
Increased B Cell Survival and Preferential Activation of the Memory Compartment by a Malaria Polyclonal B Cell Activator This information is current as Daria Donati, Bobo Mok, Arnaud Chêne, Hong Xu, Mathula of October 2, 2021. Thangarajh, Rickard Glas, Qijun Chen, Mats Wahlgren and Maria Teresa Bejarano J Immunol 2006; 177:3035-3044; ; doi: 10.4049/jimmunol.177.5.3035 http://www.jimmunol.org/content/177/5/3035 Downloaded from References This article cites 35 articles, 15 of which you can access for free at: http://www.jimmunol.org/content/177/5/3035.full#ref-list-1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on October 2, 2021 *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2006 by The American Association of Immunologists All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Increased B Cell Survival and Preferential Activation of the Memory Compartment by a Malaria Polyclonal B Cell Activator1 Daria Donati,2† Bobo Mok,* Arnaud Cheˆne,*† Hong Xu,† Mathula Thangarajh,‡ Rickard Glas,† Qijun Chen,§ Mats Wahlgren,* and Maria Teresa Bejarano*† Chronic malaria infection is characterized by polyclonal B cell activation, hyperglobulinemia, and elevated titers of autoantibod- ies. -
Anti-DR1 Antibody (ARG58552)
Product datasheet [email protected] ARG58552 Package: 50 μl anti-DR1 antibody Store at: -20°C Summary Product Description Rabbit Polyclonal antibody recognizes DR1 Tested Reactivity Ms Predict Reactivity Hu, Rat, Cow, Dog, Gpig, Hrs, Pig, Rb, Zfsh Tested Application WB Host Rabbit Clonality Polyclonal Isotype IgG Target Name DR1 Antigen Species Human Immunogen Synthetic peptide of Human DR1. (within the following sequence: KKTISPEHVIQALESLGFGSYISEVKEVLQECKTVALKRRKASSRLENLG) Conjugation Un-conjugated Alternate Names Dr1l; NC2; TATA-binding protein-associated phosphoprotein; Protein Dr1; NC2-beta; 1700121L09Rik; NC2beta; Down-regulator of transcription 1; Negative cofactor 2-beta; NC2B; NCB2 Application Instructions Predict Reactivity Note Predicted homology based on immunogen sequence: Cow: 100%; Dog: 100%; Guinea Pig: 93%; Horse: 100%; Human: 100%; Pig: 100%; Rabbit: 100%; Rat: 100%; Zebrafish: 100% Application table Application Dilution WB 1 µg/ml Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Positive Control Mouse kidney Calculated Mw 19 kDa Properties Form Liquid Purification Affinity purified. Buffer PBS, 0.09% (w/v) Sodium azide and 2% Sucrose. Preservative 0.09% (w/v) Sodium azide Stabilizer 2% Sucrose Concentration Batch dependent: 0.5 - 1 mg/ml www.arigobio.com 1/2 Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C or below. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. Note For laboratory research only, not for drug, diagnostic or other use. -
Open Data for Differential Network Analysis in Glioma
International Journal of Molecular Sciences Article Open Data for Differential Network Analysis in Glioma , Claire Jean-Quartier * y , Fleur Jeanquartier y and Andreas Holzinger Holzinger Group HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, 8036 Graz, Austria; [email protected] (F.J.); [email protected] (A.H.) * Correspondence: [email protected] These authors contributed equally to this work. y Received: 27 October 2019; Accepted: 3 January 2020; Published: 15 January 2020 Abstract: The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics. We exploit openly available data via cancer gene expression analysis, we apply refinement as well as enrichment analysis via gene ontology and conclude with graph-based visualization of involved protein interaction networks as a basis for signaling. The different databases allowed for the construction of huge networks or specified ones consisting of high-confidence interactions only. Several genes associated to glioma were isolated via a network analysis from top hub nodes as well as from an outlier analysis. The latter approach highlights a mitogen-activated protein kinase next to a member of histondeacetylases and a protein phosphatase as genes uncommonly associated with glioma. Cluster analysis from top hub nodes lists several identified glioma-associated gene products to function within protein complexes, including epidermal growth factors as well as cell cycle proteins or RAS proto-oncogenes. -
Suppression of Spontaneous Genome Rearrangements in Yeast DNA Helicase Mutants
Suppression of spontaneous genome rearrangements in yeast DNA helicase mutants Kristina H. Schmidt*†‡ and Richard D. Kolodner*§¶ *Ludwig Institute for Cancer Research and §Departments of Medicine and Cellular and Molecular Medicine and Cancer Center, University of California at San Diego, La Jolla, CA 92093; and †Division of Cell Biology, Microbiology, and Molecular Biology, Department of Biology, University of South Florida, Tampa, FL 33620 Contributed by Richard D. Kolodner, October 2, 2006 (sent for review June 16, 2006) Saccharomyces cerevisiae mutants lacking two of the three DNA the hyperrecombination and DNA-damage sensitive phenotypes of helicases Sgs1, Srs2, and Rrm3 exhibit slow growth that is sup- srs2 mutants are suppressed by HR defects (31). The physical pressed by disrupting homologous recombination. Cells lacking interaction between Srs2 and Pol32, a structural subunit of DNA Sgs1 and Rrm3 accumulate gross-chromosomal rearrangements polymerase delta, suggests that Srs2 may act during DNA replica- (GCRs) that are suppressed by the DNA damage checkpoint and by tion (32). Srs2 also is required for proper activation of Rad53 in homologous recombination-defective mutations. In contrast, rrm3, response to DNA-damaging agents (7, 33), and Srs2 itself is srs2, and srs2 rrm3 mutants have wild-type GCR rates. GCR types in phosphorylated after cells are exposed to methyl-methanesulfon- helicase double mutants include telomere additions, transloca- ate, hydroxyurea, or UV light; however, the significance of this tions, and broken DNAs healed by a complex process of hairpin- phosphorylation is unknown (33). mediated inversion. Spontaneous activation of the Rad53 check- Unlike Sgs1 and Srs2, the Rrm3 helicase has 5Ј-to-3Ј polarity and point kinase in the rrm3 mutant depends on the Mec3͞Rad24 DNA shares homology throughout its helicase domain with the S. -
Supplementary Table S1
Supplemental Data Table 1A Gene Regulation in PBMCs from normal donors following 18hr IFN-α treatment in vitro Fold Change Post vs Pre- Gene Function treatment Ubiquitin specific protease 18 (USP18) Ubiquitin-dependent protein catabolism 15.1 CD38 antigen (p45) (CD38) Apoptosis 8.8 Interferon-induced protein 44 (IFI44) Antiviral response 7.5 DEAD (Asp-Glu-Ala-Asp) box polypeptide 58 (DDX58) Helicase, Deoxyribonuclease, ubiquitin-protein ligase 7.1 Hect domain and RLD5 (HERC5) Regulation of cyclin dependent protein kinase activity 7.0 2'-5'-oligoadenylate synthetase 2 (OAS2) Immune response, nucleic acid metabolism 6.7 2'-5'-oligoadenylate synthetase-like (OASL) Immune response, nucleic acid metabolism 6.2 Lymphocyte antigen 6 complex, locus E (LY6E) T cell differentiation and activation, antiviral response 5.8 Serine palmitoyltransferase, long chain base subunit 2 (SPTLC2) Unknown 4.6 Likely ortholog of mouse D11lgp2 (LGP2) DNA restriction 4.3 Interferon stimulated gene 20kDa (ISG20) Immune response, proliferation 3.9* Retinoic acid- and interferon-inducible protein (IFIT2) Immune response 3.8 Three prime repair exonuclease 1 (TREX1) DNA repair and replication 3.6 Metallothionein 1H (MT1H) Metal ion binding 3.4 Phospholipid scramblase 1 (PLSCR1) Phospholipid scramblase 3.2* Metallothionein 1 pseudogene 2 (M1P2) Metal ion binding 3.2 Metallothionein 2A (MT2A) Metal ion binding 3.0 SP110 nuclear body protein (SP110) Regulation of transcription, transcription factor 3.0* Tripartite motif-containing 21 (TRIM21) Protein ubiquitination 2.9