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The Identification of Genetic Determinants of Methanol
Journal of Fungi Article The Identification of Genetic Determinants of Methanol Tolerance in Yeast Suggests Differences in Methanol and Ethanol Toxicity Mechanisms and Candidates for Improved Methanol Tolerance Engineering Marta N. Mota 1,2, Luís C. Martins 1,2 and Isabel Sá-Correia 1,2,* 1 iBB—Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal; [email protected] (M.N.M.); [email protected] (L.C.M.) 2 Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal * Correspondence: [email protected] Abstract: Methanol is a promising feedstock for metabolically competent yeast strains-based biore- fineries. However, methanol toxicity can limit the productivity of these bioprocesses. Therefore, the identification of genes whose expression is required for maximum methanol tolerance is important for mechanistic insights and rational genomic manipulation to obtain more robust methylotrophic yeast strains. The present chemogenomic analysis was performed with this objective based on the screening of the Euroscarf Saccharomyces cerevisiae haploid deletion mutant collection to search for susceptibility ◦ phenotypes in YPD medium supplemented with 8% (v/v) methanol, at 35 C, compared with an equivalent ethanol concentration (5.5% (v/v)). Around 400 methanol tolerance determinants were Citation: Mota, M.N.; Martins, L.C.; identified, 81 showing a marked phenotype. The clustering of the identified tolerance genes indicates Sá-Correia, I. The Identification of an enrichment of functional categories in the methanol dataset not enriched in the ethanol dataset, Genetic Determinants of Methanol Tolerance in Yeast Suggests such as chromatin remodeling, DNA repair and fatty acid biosynthesis. -
Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids
Supplementary Materials: Evaluation of cytotoxicity and α-glucosidase inhibitory activity of amide and polyamino-derivatives of lupane triterpenoids Oxana B. Kazakova1*, Gul'nara V. Giniyatullina1, Akhat G. Mustafin1, Denis A. Babkov2, Elena V. Sokolova2, Alexander A. Spasov2* 1Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences, 71, pr. Oktyabrya, 450054 Ufa, Russian Federation 2Scientific Center for Innovative Drugs, Volgograd State Medical University, Novorossiyskaya st. 39, Volgograd 400087, Russian Federation Correspondence Prof. Dr. Oxana B. Kazakova Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences 71 Prospeсt Oktyabrya Ufa, 450054 Russian Federation E-mail: [email protected] Prof. Dr. Alexander A. Spasov Scientific Center for Innovative Drugs of the Volgograd State Medical University 39 Novorossiyskaya st. Volgograd, 400087 Russian Federation E-mail: [email protected] Figure S1. 1H and 13C of compound 2. H NH N H O H O H 2 2 Figure S2. 1H and 13C of compound 4. NH2 O H O H CH3 O O H H3C O H 4 3 Figure S3. Anticancer screening data of compound 2 at single dose assay 4 Figure S4. Anticancer screening data of compound 7 at single dose assay 5 Figure S5. Anticancer screening data of compound 8 at single dose assay 6 Figure S6. Anticancer screening data of compound 9 at single dose assay 7 Figure S7. Anticancer screening data of compound 12 at single dose assay 8 Figure S8. Anticancer screening data of compound 13 at single dose assay 9 Figure S9. Anticancer screening data of compound 14 at single dose assay 10 Figure S10. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Allele-Specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish
Allele-specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish by Ailu Chen A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Auburn, Alabama August 1, 2015 Keywords: catfish, interspecific hybrids, allele-specific expression, ribosomal protein Copyright 2015 by Ailu Chen Approved by Zhanjiang Liu, Chair, Professor, School of Fisheries, Aquaculture and Aquatic Sciences Nannan Liu, Professor, Entomology and Plant Pathology Eric Peatman, Associate Professor, School of Fisheries, Aquaculture and Aquatic Sciences Aaron M. Rashotte, Associate Professor, Biological Sciences Abstract Interspecific hybridization results in a vast reservoir of allelic variations, which may potentially contribute to phenotypical enhancement in the hybrids. Whether the allelic variations are related to the downstream phenotypic differences of interspecific hybrid is still an open question. The recently developed genome-wide allele-specific approaches that harness high- throughput sequencing technology allow direct quantification of allelic variations and gene expression patterns. In this work, I investigated allele-specific expression (ASE) pattern using RNA-Seq datasets generated from interspecific catfish hybrids. The objective of the study is to determine the ASE genes and pathways in which they are involved. Specifically, my study investigated ASE-SNPs, ASE-genes, parent-of-origins of ASE allele and how ASE would possibly contribute to heterosis. My data showed that ASE was operating in the interspecific catfish system. Of the 66,251 and 177,841 SNPs identified from the datasets of the liver and gill, 5,420 (8.2%) and 13,390 (7.5%) SNPs were identified as significant ASE-SNPs, respectively. -
Amino Acid Specificity in Translation
Opinion TRENDS in Biochemical Sciences Vol.30 No.12 December 2005 Amino acid specificity in translation Taraka Dale and Olke C. Uhlenbeck Department of Biochemistry, Molecular Biology, and Cell Biology, Northwestern University, Evanston, IL 60208, USA Recent structural and biochemical experiments indicate For example, in the course of deducing the recognition that bacterial elongation factor Tu and the ribosomal rules of aaRSs, several amber-suppressor tRNA bodies A-site show specificity for both the amino acid and the were deliberately mutated such that they were amino- tRNA portions of their aminoacyl-tRNA (aa-tRNA) acylated by a different aaRS, and the resulting ‘identity- substrates. These data are inconsistent with the swapped’ tRNAs were shown to insert the new amino acid traditional view that tRNAs are generic adaptors in into protein [7,8]. In addition, suppressor tRNAs esterified translation. We hypothesize that each tRNA sequence with O30 different unnatural amino acids have been has co-evolved with its cognate amino acid, such that all successfully incorporated into protein [9]. Together, these aa-tRNAs are translated uniformly. data suggest that the translational apparatus lacks specificity for different amino acids, once they are Introduction esterified onto tRNA. The mechanism of protein synthesis is traditionally In a few isolated cases, however, the translation considered to have two phases with different specificities machinery seems to show specificity for the esterified towards the 20 amino acid side chains (Figure 1). In the amino acid. A prominent example occurs in the transami- first phase, each amino acid is specifically recognized by dation pathway, which is used as an alternative to GlnRS its cognate aminoacyl-tRNA synthetase (aaRS) and to produce Gln-tRNAGln in many bacteria and archaea esterified to the appropriate tRNA to form an aminoacyl- [10,11]. -
Role of Mitochondrial Ribosomal Protein S18-2 in Cancerogenesis and in Regulation of Stemness and Differentiation
From THE DEPARTMENT OF MICROBIOLOGY TUMOR AND CELL BIOLOGY (MTC) Karolinska Institutet, Stockholm, Sweden ROLE OF MITOCHONDRIAL RIBOSOMAL PROTEIN S18-2 IN CANCEROGENESIS AND IN REGULATION OF STEMNESS AND DIFFERENTIATION Muhammad Mushtaq Stockholm 2017 All previously published papers were reproduced with permission from the publisher. Published by Karolinska Institutet. Printed by E-Print AB 2017 © Muhammad Mushtaq, 2017 ISBN 978-91-7676-697-2 Role of Mitochondrial Ribosomal Protein S18-2 in Cancerogenesis and in Regulation of Stemness and Differentiation THESIS FOR DOCTORAL DEGREE (Ph.D.) By Muhammad Mushtaq Principal Supervisor: Faculty Opponent: Associate Professor Elena Kashuba Professor Pramod Kumar Srivastava Karolinska Institutet University of Connecticut Department of Microbiology Tumor and Cell Center for Immunotherapy of Cancer and Biology (MTC) Infectious Diseases Co-supervisor(s): Examination Board: Professor Sonia Lain Professor Ola Söderberg Karolinska Institutet Uppsala University Department of Microbiology Tumor and Cell Department of Immunology, Genetics and Biology (MTC) Pathology (IGP) Professor George Klein Professor Boris Zhivotovsky Karolinska Institutet Karolinska Institutet Department of Microbiology Tumor and Cell Institute of Environmental Medicine (IMM) Biology (MTC) Professor Lars-Gunnar Larsson Karolinska Institutet Department of Microbiology Tumor and Cell Biology (MTC) Dedicated to my parents ABSTRACT Mitochondria carry their own ribosomes (mitoribosomes) for the translation of mRNA encoded by mitochondrial DNA. The architecture of mitoribosomes is mainly composed of mitochondrial ribosomal proteins (MRPs), which are encoded by nuclear genomic DNA. Emerging experimental evidences reveal that several MRPs are multifunctional and they exhibit important extra-mitochondrial functions, such as involvement in apoptosis, protein biosynthesis and signal transduction. Dysregulations of the MRPs are associated with severe pathological conditions, including cancer. -
Domain of Escherichia Coli 16S Ribosomal RNA Using Site-Directed Photoaffinity Crosslinking
Downloaded from rnajournal.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press RNA (1998), 4:1455–1466+ Cambridge University Press+ Printed in the USA+ Copyright © 1998 RNA Society+ Analysis of the conformation of the 39 major domain of Escherichia coli 16S ribosomal RNA using site-directed photoaffinity crosslinking ALEXANDRE MONTPETIT,1 CATHERINE PAYANT,1 JAMES M. NOLAN,2 and LÉA BRAKIER-GINGRAS1 1Département de Biochimie, Université de Montréal, Montréal, Québec H3T 1J4, Canada 2Department of Biochemistry, Tulane University Medical Center, New Orleans, Louisiana 70112, USA ABSTRACT The 39 major domain of Escherichia coli 16S rRNA, which occupies the head of the small ribosomal subunit, is involved in several functions of the ribosome. We have used a site-specific crosslinking procedure to gain further insights into the higher-order structure of this domain. Circularly permuted RNAs were used to introduce an azi- dophenacyl group at specific positions within the 39 major domain. Crosslinks were generated in a high-ionic strength buffer that has been used for ribosome reconstitution studies and so enables the RNA to adopt a structure recognized by ribosomal proteins. The crosslinking sites were identified by primer extension and confirmed by assessing the mobility of the crosslinked RNA lariats in denaturing polyacrylamide gels. Eight crosslinks were characterized. Among them, one crosslink demonstrates that helix 28 is proximal to the top of helix 34, and two others show that the 1337 region, located in an internal loop at the junction of helices 29, 30, 41, and 42, is proximal to the center of helix 30 and to a segment connecting helix 28 to helix 29. -
EF-Tu and Rnase E Are Functionally Connected
Till min familj List of Papers This thesis is based on the following papers, which are referred to in the text by their Roman numerals. I Hammarlöf, D.L., Hughes, D. (2008) Mutants of the RNA- processing enzyme RNase E reverse the extreme slow-growth phenotype caused by a mutant translation factor EF-Tu. Molecular Microbiology, 70(5), 1194-1209 II †Bergman, J., †Hammarlöf, D.L., Hughes D. (2011) Reducing ppGpp levels rescues the extreme growth defect of mutant EF-Tu. Manuscript III Hammarlöf, D.L., Liljas, L., Hughes, D. (2011) Temperature- sensitive mutants of RNase E in Salmonella enterica. Journal of Bacteriology. In press IV †Hammarlöf, D.L., †Bergman, J., Hughes, D. (2011) Extragenic suppressors of RNase E. Manuscript †These authors contributed equally. Reprints were made with permission from the respective publishers. Contents Introduction ................................................................................................... 11 Bacterial growth ....................................................................................... 11 Translation in bacteria .............................................................................. 12 The ribosome ....................................................................................... 12 The translation cycle ............................................................................ 13 Elongation Factor Tu ................................................................................ 14 The most abundant protein in the cell ................................................. -
Supplementary Figures 1-14 and Supplementary References
SUPPORTING INFORMATION Spatial Cross-Talk Between Oxidative Stress and DNA Replication in Human Fibroblasts Marko Radulovic,1,2 Noor O Baqader,1 Kai Stoeber,3† and Jasminka Godovac-Zimmermann1* 1Division of Medicine, University College London, Center for Nephrology, Royal Free Campus, Rowland Hill Street, London, NW3 2PF, UK. 2Insitute of Oncology and Radiology, Pasterova 14, 11000 Belgrade, Serbia 3Research Department of Pathology and UCL Cancer Institute, Rockefeller Building, University College London, University Street, London WC1E 6JJ, UK †Present Address: Shionogi Europe, 33 Kingsway, Holborn, London WC2B 6UF, UK TABLE OF CONTENTS 1. Supplementary Figures 1-14 and Supplementary References. Figure S-1. Network and joint spatial razor plot for 18 enzymes of glycolysis and the pentose phosphate shunt. Figure S-2. Correlation of SILAC ratios between OXS and OAC for proteins assigned to the SAME class. Figure S-3. Overlap matrix (r = 1) for groups of CORUM complexes containing 19 proteins of the 49-set. Figure S-4. Joint spatial razor plots for the Nop56p complex and FIB-associated complex involved in ribosome biogenesis. Figure S-5. Analysis of the response of emerin nuclear envelope complexes to OXS and OAC. Figure S-6. Joint spatial razor plots for the CCT protein folding complex, ATP synthase and V-Type ATPase. Figure S-7. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated by GO to nucleocytoplasmic transport (GO:0006913). Figure S-8. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated to endocytosis (GO:0006897). Figure S-9. Joint spatial razor plots for 401-set proteins annotated by GO to small GTPase mediated signal transduction (GO:0007264) and/or GTPase activity (GO:0003924). -
1 AGING Supplementary Table 2
SUPPLEMENTARY TABLES Supplementary Table 1. Details of the eight domain chains of KIAA0101. Serial IDENTITY MAX IN COMP- INTERFACE ID POSITION RESOLUTION EXPERIMENT TYPE number START STOP SCORE IDENTITY LEX WITH CAVITY A 4D2G_D 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ B 4D2G_E 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ C 6EHT_D 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ D 6EHT_E 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ E 6GWS_D 41-72 41 72 100 100 3.2Å PCNA X-RAY DIFFRACTION √ F 6GWS_E 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ G 6GWS_F 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ H 6IIW_B 2-11 2 11 100 100 1.699Å UHRF1 X-RAY DIFFRACTION √ www.aging-us.com 1 AGING Supplementary Table 2. Significantly enriched gene ontology (GO) annotations (cellular components) of KIAA0101 in lung adenocarcinoma (LinkedOmics). Leading Description FDR Leading Edge Gene EdgeNum RAD51, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, CENPW, HJURP, NDC80, CDCA5, NCAPH, BUB1, ZWILCH, CENPK, KIF2C, AURKA, CENPN, TOP2A, CENPM, PLK1, ERCC6L, CDT1, CHEK1, SPAG5, CENPH, condensed 66 0 SPC24, NUP37, BLM, CENPE, BUB3, CDK2, FANCD2, CENPO, CENPF, BRCA1, DSN1, chromosome MKI67, NCAPG2, H2AFX, HMGB2, SUV39H1, CBX3, TUBG1, KNTC1, PPP1CC, SMC2, BANF1, NCAPD2, SKA2, NUP107, BRCA2, NUP85, ITGB3BP, SYCE2, TOPBP1, DMC1, SMC4, INCENP. RAD51, OIP5, CDK1, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, ESCO2, CENPW, HJURP, TTK, NDC80, CDCA5, BUB1, ZWILCH, CENPK, KIF2C, AURKA, DSCC1, CENPN, CDCA8, CENPM, PLK1, MCM6, ERCC6L, CDT1, HELLS, CHEK1, SPAG5, CENPH, PCNA, SPC24, CENPI, NUP37, FEN1, chromosomal 94 0 CENPL, BLM, KIF18A, CENPE, MCM4, BUB3, SUV39H2, MCM2, CDK2, PIF1, DNA2, region CENPO, CENPF, CHEK2, DSN1, H2AFX, MCM7, SUV39H1, MTBP, CBX3, RECQL4, KNTC1, PPP1CC, CENPP, CENPQ, PTGES3, NCAPD2, DYNLL1, SKA2, HAT1, NUP107, MCM5, MCM3, MSH2, BRCA2, NUP85, SSB, ITGB3BP, DMC1, INCENP, THOC3, XPO1, APEX1, XRCC5, KIF22, DCLRE1A, SEH1L, XRCC3, NSMCE2, RAD21. -
A Combined Algorithm for Genome- Wide Prediction of Protein Function
letters to nature cluster for the synthesis of a class of cell wall lipids unique to pathogenic mycobacteria. J. Biol. Chem. tionally related yeast proteins. Links between characterized and 272, 16741±16745 (1997). uncharacterized proteins allow a general function to be assigned 9. Mathur, M. & Kolattukudy, P. E. Molecular cloning and sequencing of the gene for mycocerosic acid synthase, a novel fatty acid elongating multifunctional enzyme, from Mycobacterium tuberculosis var. to more than half of the 2,557 previously uncharacterized yeast bovis Bacillus Calmette-Guerin. J. Biol. Chem. 267, 19388±19395 (1992). proteins. Examples of functional links are given for a protein 10. Azad, A. K., Sirakova, T. D., Rogers, L. M. & Kolattukudy, P. E. Targeted replacement of the family of previously unknown function, a protein whose human mycocerosic acid synthase gene in Mycobacterium bovis BCG produces a mutant that lacks mycosides. homologues are implicated in colon cancer and the yeast prion Proc. Natl Acad. Sci. USA 93, 4787±4792 (1996). 11. Cole, S. T. et al. Deciphering the biology of Mycobactrium tuberculosis from the complete genome Sup35. sequence [see comments]. Nature 393, 537±544 (1998). The historical method of ®nding the function of a protein 12. Fitzmaurice, A. M. & Kolattukudy, P. E. An acyl-CoA synthase (acoas) gene adjacent to the involves extensive genetic and biochemical analyses, unless the mycocerosic acid synthase (mas) locus is necessary for mycocerosyl lipid synthesis in Mycobacterium tuberculosis var. bovis. BCG. J. Biol. Chem. 273, 8033±8039 (1998). amino-acid sequence of the protein resembles another whose 13. Fitzmaurice, A. M. & Kolattukudy, P. E. -
Archaeal Translation Initiation Revisited: the Initiation Factor 2 and Eukaryotic Initiation Factor 2B ␣--␦ Subunit Families
Proc. Natl. Acad. Sci. USA Vol. 95, pp. 3726–3730, March 1998 Evolution Archaeal translation initiation revisited: The initiation factor 2 and eukaryotic initiation factor 2B a-b-d subunit families NIKOS C. KYRPIDES* AND CARL R. WOESE Department of Microbiology, University of Illinois at Urbana-Champaign, B103 Chemical and Life Sciences, MC 110, 407 S. Goodwin, Urbana, IL 61801 Contributed by Carl R. Woese, December 31, 1997 ABSTRACT As the amount of available sequence data bacterial and eukaryotic translation initiation mechanisms, increases, it becomes apparent that our understanding of although mechanistically generally similar, were molecularly translation initiation is far from comprehensive and that unrelated and so had evolved independently. The Methano- prior conclusions concerning the origin of the process are coccus jannaschii genome (7–9), which gave us our first wrong. Contrary to earlier conclusions, key elements of trans- comprehensive look at the componentry of archaeal transla- lation initiation originated at the Universal Ancestor stage, for tion initiation, revealed that archaeal translation initiation homologous counterparts exist in all three primary taxa. showed considerable homology with eukaryotic initiation, Herein, we explore the evolutionary relationships among the which, if anything, reinforced the divide between bacterial components of bacterial initiation factor 2 (IF-2) and eukary- initiation and that seen in the other domains. We recently have otic IF-2 (eIF-2)/eIF-2B, i.e., the initiation factors involved in shown, however, that bacterial translation initiation factor 1 introducing the initiator tRNA into the translation mecha- (IF-1), contrary to previously accepted opinion, is related in nism and performing the first step in the peptide chain sequence to its eukaryotic/archaeal (functional) counterpart, elongation cycle.