DOCSLIB.ORG

Complete Genome Sequence of the Hyperthermophilic Bacteria- Thermotoga Sp

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

COMPLETE GENOME SEQUENCE OF THE HYPERTHERMOPHILIC BACTERIA- THERMOTOGA SP. STRAIN RQ7 Rutika Puranik A Thesis Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May 2015 Committee: Zhaohui Xu, Advisor Scott Rogers George Bullerjahn © 2015 Rutika Puranik All Rights Reserved iii ABSTRACT Zhaohui Xu, Advisor The genus Thermotoga is one of the deep-rooted genus in the phylogenetic tree of life and has been studied for its thermostable enzymes and the property of hydrogen production at higher temperatures. The current study focuses on the complete genome sequencing of T. sp. strain RQ7 to understand and identify the conserved as well as variable properties between the strains and its genus with the approach of comparative genomics. A pipeline was developed to assemble the complete genome based on the next generation sequencing (NGS) data. The pipeline successfully combined computational approaches with wet lab experiments to deliver a completed genome of T. sp. strain RQ7 that has the genome size of 1,851,618 bp with a GC content of 47.1%. The genome is submitted to Genbank with accession CP07633. Comparative genomic analysis of this genome with three other strains of Thermotoga, helped identifying putative natural transformation and competence protein coding genes in addition to the absence of TneDI restriction- modification system in T. sp. strain RQ7. Genome analysis also assisted in recognizing the unique genes in T. sp. strain RQ7 and CRISPR/Cas system. This strain has 8 CRISPR loci and an array of Cas coding genes in the entire genome. The genome sequencing of this strain has provided a platform for studying the development of genetic tools, which would make these strains industrially applicable for biofuel generation. iv I dedicate this work to my parents Mr. Rajiv Puranik and Mrs. Radhika Puranik. v ACKNOWLEDGMENTS I sincerely thank my advisor Dr. Zhaohui Xu for constantly guiding me in my entire course of Master’s program. I am grateful for her support and patience. I wish to thank my committee members Dr. Scott Rogers and Dr. George Bullerjahn for accepting to be on my thesis committee and their valuable inputs. I appreciate the enormous support and help of my lab members Dr. Dongmei Han, Hui Xu and Dr. Uksha Saini and all my friends in the department. I am especially thankful to my husband Akshay Joshi for motivating me and believing in me. vi TABLE OF CONTENTS Page I. INTRODUCTION ............................................................................................................. 1 Genus Thermotoga ..................................................................................................... 1 Genome Sequencing .................................................................................................. 3 Genome Annotation ................................................................................................... 6 II. MATERIALS AND METHODS ...................................................................................... 9 Growth conditions and DNA isolation ...................................................................... 9 Genome sequencing by BGI America’s .................................................................... 10 Genome assembly and analysis ................................................................................. 11 Overview of completing the genome ......................................................................... 11 Primer Walking and PCR........................................................................................... 13 Genome annotation .................................................................................................... 16 III. RESULTS ........................................................................................................................ 19 Completion of Thermotoga sp. strain RQ7 genome .................................................. 19 Genome details and features ...................................................................................... 30 Features analyzed in the genome ............................................................................... 31 Unique genes in T. sp. strain RQ7 ................................................................. 31 Natural Transformation .................................................................................. 32 The Type II Restriction-Modification system TneDI .................................... 42 CRISPRs ........................................................................................................ 44 IV. DISCUSSION .................................................................................................................. 47 vii V. CONCLUSIONS ............................................................................................................. 49 VI. REFERENCES ................................................................................................................ 50 viii LIST OF FIGURES Figure Page 1 Phylogenetic tree of life based on the small subunit rRNA sequences ...................... 2 2 Small subunit rRNA phylogeny of different Thermotoga strains .............................. 3 3 The principle of Sanger sequencing ........................................................................... 4 4 Schematic representation of steps involved in Illumina sequencing technology ...... 5 5 The approach of Paired-End reads ............................................................................. 6 6 Multistep annotation process ..................................................................................... 7 7 Dataflow schematic for genome annotation .............................................................. 8 8 Method used by BGI America’s for data production and quality control ................. 10 9 The pipeline of genome assembling and gap closure ................................................ 12 10 Schematic overview of GapFish algorithm................................................................ 14 11 Schematic representation of the steps performed during primer walking ................. 16 12 Diagram summarizing the overall outline of prokaryotic genome annotation Pipeline ...................................................................................................................... 17 13 Multiple genome alignment of four different Thermotoga isolates using Mauve alignment tool ............................................................................................................ 22 14 Amplification of randomly selected genes in the big gap of T. sp. strain RQ7 ......... 23 15 Wet lab approach to confirm the existence of the minigaps ...................................... 26 16 Differences in obtaining PCR products for easy genes and difficult genes found in the big gap of T. sp. strain RQ7 ................................................................................. 27 17 The approach of Nested PCR for amplifying the difficult genes in the big gap of T. sp. strain RQ7 ........................................................................................................ 28 ix 18 Nested PCR with internal primers for obtaining the final PCR product of difficult gene ............................................................................................................................ 29 19 Metabolic reaction of sulfate reduction pathway ....................................................... 31 20 CDD (Conserved Domain Database) analysis using amino acid sequences of the PilZ protein in V. cholerae, P. aeruginosa and T. sp. strain RQ7 ............................. 34 21 CDD analysis using amino acid sequences of PilB protein in V. cholerae, P. aeruginosa and T. sp. strain RQ7 .......................................................................... 35 22 CDD analysis of PilQ amino acid sequence in N. gonorrhoeae showing the presence of important conserved secretin domain ..................................................... 36 23 Conserved domains of PilC protein in P. stutzeri and putative PilC in T. sp. strain RQ7 analyzed by CDD ........................................................................... 36 24 CDD analysis using amino acid sequences outlines the conserved domains of PilD in N. gonorrhoeae, V. vulnificus and putative PilD in T. sp. strain RQ7 .......... 37 25 Outline of the conserved domains of PilT protein in N. gonorrhoea and putative PilT in T. sp. strain RQ7 ............................................................................................ 38 26 CDD analysis using amino acid sequences of PilE in P. aeruginosa and N. gonorrhoeae and putative PilE in T. sp. strain RQ7 ............................................. 38 27 CDD analysis using amino acid sequence of ComM in H. influenzae and putative ComM in T. sp. strain RQ7 .......................................................................... 39 28 CDD analysis of putative ComE in T. sp. strain RQ7 and ComE in the reference organism B. subtilis .................................................................................................... 40 29 CDD analysis using amino acid sequence of ComEC protein in B. subtilis and putative ComEC in T. sp. strain RQ7 ........................................................................ 40 x 30 CDD analysis using amino acid sequence of putative ComFC in T. sp.strain RQ7 and ComFC in B. subtilis ..........................................................................................
Recommended publications
  • Functional Aspects and Genomic Analysis

    Functional Aspects and Genomic Analysis

    Discussion IV./ Discussion IV.1. The discovery of UEV protein and its role in different cellular processes In our studies of cell differentiation and cell cycle control, we have isolated a new gene that is downregulated upon cell differentiation. We have demonstrated that this gene, previously called CROC1 and considered a transcriptional activator of c-fos (Rothofsky and Lin, 1997), is highly conserved in phylogeny, and constitutes, by sequence relationship, a novel subfamily of the ubiquitin-conjugating, or E2, enzymes. We have demonstrated that these proteins are very conserved in all eukaryotic organisms and that they are very similar to the E2 enzymes in sequence and structure, but these proteins lack a conserved cysteine residue responsible for the catalytic activity of the E2 enzymes (Chen et al., 1993; Jentsch, 1992a). We have given these proteins the name UEV (ubiquitin-conjugating E2 enzyme variant). Work by other laboratories has shown that experimental mutagenesis of this cysteine in the catalytic center leads to the inactivation of the E2 enzyme activity, and the mutated protein can behave as a dominant negative variant (Banerjee et al., 1995; Sung et al., 1990; Madura et al., 1993). However, in our initial experiments with recombinant proteins, UEV did not behave as a negative regulator of ubiquitination (Sancho et al., 1998). We have demonstrated also the existence of at least two different human UEV genes, one coding for UEV1/CROC-1, and the other coding for UEV2. The second protein has also been given different names by others, DDVit-1 (Fritsche et al., 1997). 30 Discussion The transcripts from the two human UEV genes differ in their 3’untranslated regions, and produce almost identical proteins.
  • Aglycone Specificity of Thermotoga Neapolitana B-Glucosidase 1A

    Aglycone Specificity of Thermotoga Neapolitana B-Glucosidase 1A

    Khan et al. BMC Biochemistry 2011, 12:11 http://www.biomedcentral.com/1471-2091/12/11 RESEARCHARTICLE Open Access Aglycone specificity of Thermotoga neapolitana b-glucosidase 1A modified by mutagenesis, leading to increased catalytic efficiency in quercetin-3-glucoside hydrolysis Samiullah Khan1, Tania Pozzo1, Márton Megyeri1,2, Sofia Lindahl3, Anders Sundin3, Charlotta Turner3, Eva Nordberg Karlsson1* Abstract Background: The thermostable b-glucosidase (TnBgl1A) from Thermotoga neapolitana is a promising biocatalyst for hydrolysis of glucosylated flavonoids and can be coupled to extraction methods using pressurized hot water. Hydrolysis has however been shown to be dependent on the position of the glucosylation on the flavonoid, and e.g. quercetin-3-glucoside (Q3) was hydrolysed slowly. A set of mutants of TnBgl1A were thus created to analyse the influence on the kinetic parameters using the model substrate para-nitrophenyl-b-D-glucopyranoside (pNPGlc), and screened for hydrolysis of Q3. Results: Structural analysis pinpointed an area in the active site pocket with non-conserved residues between specificity groups in glycoside hydrolase family 1 (GH1). Three residues in this area located on b-strand 5 (F219, N221, and G222) close to sugar binding sub-site +2 were selected for mutagenesis and amplified in a protocol that introduced a few spontaneous mutations. Eight mutants (four triple: F219L/P165L/M278I, N221S/P165L/M278I, G222Q/P165L/M278I, G222Q/V203M/K214R, two double: F219L/K214R, N221S/P342L and two single: G222M and N221S) were produced in E. coli, and purified to apparent homogeneity. Thermostability, measured as Tm by differential scanning calorimetry (101.9°C for wt), was kept in the mutated variants and significant decrease (ΔTof5 - 10°C) was only observed for the triple mutants.
  • Heat Resistant Thermophilic Endospores in Cold Estuarine Sediments

    Heat Resistant Thermophilic Endospores in Cold Estuarine Sediments

    Heat resistant thermophilic endospores in cold estuarine sediments Emma Bell Thesis submitted for the degree of Doctor of Philosophy School of Civil Engineering and Geosciences Faculty of Science, Agriculture and Engineering February 2016 Abstract Microbial biogeography explores the spatial and temporal distribution of microorganisms at multiple scales and is influenced by environmental selection and passive dispersal. Understanding the relative contribution of these factors can be challenging as their effects can be difficult to differentiate. Dormant thermophilic endospores in cold sediments offer a natural model for studies focusing on passive dispersal. Understanding distributions of these endospores is not confounded by the influence of environmental selection; rather their occurrence is due exclusively to passive transport. Sediment heating experiments were designed to investigate the dispersal histories of various thermophilic spore-forming Firmicutes in the River Tyne, a tidal estuary in North East England linking inland tributaries with the North Sea. Microcosm incubations at 50-80°C were monitored for sulfate reduction and enriched bacterial populations were characterised using denaturing gradient gel electrophoresis, functional gene clone libraries and high-throughput sequencing. The distribution of thermophilic endospores among different locations along the estuary was spatially variable, indicating that dispersal vectors originating in both warm terrestrial and marine habitats contribute to microbial diversity in estuarine and marine environments. In addition to their persistence in cold sediments, some endospores displayed a remarkable heat-resistance surviving multiple rounds of autoclaving. These extremely heat-resistant endospores are genetically similar to those detected in deep subsurface environments, including geothermal groundwater investigated from a nearby terrestrial borehole drilled to >1800 m depth with bottom temperatures in excess of 70°C.
  • Gene Prediction Using Deep Learning

    Gene Prediction Using Deep Learning

    FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Gene prediction using Deep Learning Pedro Vieira Lamares Martins Mestrado Integrado em Engenharia Informática e Computação Supervisor: Rui Camacho (FEUP) Second Supervisor: Nuno Fonseca (EBI-Cambridge, UK) July 22, 2018 Gene prediction using Deep Learning Pedro Vieira Lamares Martins Mestrado Integrado em Engenharia Informática e Computação Approved in oral examination by the committee: Chair: Doctor Jorge Alves da Silva External Examiner: Doctor Carlos Manuel Abreu Gomes Ferreira Supervisor: Doctor Rui Carlos Camacho de Sousa Ferreira da Silva July 22, 2018 Abstract Every living being has in their cells complex molecules called Deoxyribonucleic Acid (or DNA) which are responsible for all their biological features. This DNA molecule is condensed into larger structures called chromosomes, which all together compose the individual’s genome. Genes are size varying DNA sequences which contain a code that are often used to synthesize proteins. Proteins are very large molecules which have a multitude of purposes within the individual’s body. Only a very small portion of the DNA has gene sequences. There is no accurate number on the total number of genes that exist in the human genome, but current estimations place that number between 20000 and 25000. Ever since the entire human genome has been sequenced, there has been an effort to consistently try to identify the gene sequences. The number was initially thought to be much higher, but it has since been furthered down following improvements in gene finding techniques. Computational prediction of genes is among these improvements, and is nowadays an area of deep interest in bioinformatics as new tools focused on the theme are developed.
  • Fermentation of Biodegradable Organic Waste by the Family Thermotogaceae

    Fermentation of Biodegradable Organic Waste by the Family Thermotogaceae

    resources Review Fermentation of Biodegradable Organic Waste by the Family Thermotogaceae Nunzia Esercizio 1 , Mariamichela Lanzilli 1 , Marco Vastano 1 , Simone Landi 2 , Zhaohui Xu 3 , Carmela Gallo 1 , Genoveffa Nuzzo 1 , Emiliano Manzo 1 , Angelo Fontana 1,2 and Giuliana d’Ippolito 1,* 1 Institute of Biomolecular Chemistry, National Research Council of Italy, Via Campi Flegrei 34, 80078 Pozzuoli, Italy; [email protected] (N.E.); [email protected] (M.L.); [email protected] (M.V.); [email protected] (C.G.); [email protected] (G.N.); [email protected] (E.M.); [email protected] (A.F.) 2 Department of Biology, University of Naples “Federico II”, Via Cinthia, I-80126 Napoli, Italy; [email protected] 3 Department of Biological Sciences, Bowling Green State University, Bowling Green, OH 43403, USA; [email protected] * Correspondence: [email protected] Abstract: The abundance of organic waste generated from agro-industrial processes throughout the world has become an environmental concern that requires immediate action in order to make the global economy sustainable and circular. Great attention has been paid to convert such nutrient- rich organic waste into useful materials for sustainable agricultural practices. Instead of being an environmental hazard, biodegradable organic waste represents a promising resource for the Citation: Esercizio, N.; Lanzilli, M.; production of high value-added products such as bioenergy, biofertilizers, and biopolymers. The Vastano, M.; Landi, S.; Xu, Z.; Gallo, ability of some hyperthermophilic bacteria, e.g., the genera Thermotoga and Pseudothermotoga, to C.; Nuzzo, G.; Manzo, E.; Fontana, A.; anaerobically ferment waste with the concomitant formation of bioproducts has generated great d’Ippolito, G.
  • Crude-Oil-Degrading Thermophilic Bacterium Isolated from an Oil Field

    Crude-Oil-Degrading Thermophilic Bacterium Isolated from an Oil Field

    175 Crude-oil-degrading thermophilic bacterium isolated from an oil field Ruixia Hao, Anhuai Lu, and Guanyu Wang Abstract: Thermophilic bacterium strain C2, which has the ability to transform crude oils, was isolated from the reser- voir of the Shengli oil field in East China. The Gram-negative, rod-shaped, nonmotile cells were grown at a high tem- perature, up to 83 °C, in the neutral to alkaline pH range. Depending on the culture conditions, the organism occurred as single rods or as filamentous aggregates. Strain C2 was grown chemoorganotrophically and produced metabolites, such as volatile fatty acids, 1,2-benzenedicarboxylic acid, bis(2-ethylhexyl)ester, dibutyl phthalate, and di-n-octyl phthalate. It could metabolize different organic substrates (acetate, D-glucose, fructose, glycerol, maltose, pyruvate, starch, sucrose, xylose, hexadecane). The G+C content (68 mol%) and the 16S rRNA sequence of strain C2 indicated that the isolate belonged to the genus Thermus. The strain affected different crude oils and changed their physical and chemical prop- erties. The biochemical interactions between crude oils and strain C2 follow distinct trends characterized by a group of chemical markers (saturates, aromatics, resins, asphaltenes). Those trends show an increase in saturates and a decrease in aromatics, resins, and asphaltenes. The bioconversion of crude oils leads to an enrichment in lighter hydrocarbons and an overall redistribution of these hydrocarbons. Key words: thermophile, metabolite, crude oil, degradation, conversion. Résumé : La souche de bactéries thermophiles C2, qui a la capacité de transformer les pétroles bruts, a été isolée d’un réservoir du champs pétrolifère de Shengli dans la Chine orientale.
  • Cep-2020-00633.Pdf

    Cep-2020-00633.Pdf

    Clin Exp Pediatr Vol. 64, No. 5, 208–222, 2021 Review article CEP https://doi.org/10.3345/cep.2020.00633 Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis Seoung Wan Nam, MD, PhD1,*, Kwang Seob Lee, MD2,*, Jae Won Yang, MD, PhD3,*, Younhee Ko, PhD4, Michael Eisenhut, MD, FRCP, FRCPCH, DTM&H5, Keum Hwa Lee, MD, MS6,7,8, Jae Il Shin, MD, PhD6,7,8, Andreas Kronbichler, MD, PhD9 1Department of Rheumatology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea; 2Severance Hospital, Yonsei University College of Medicine, Seoul, Korea; 3Department of Nephrology, Yonsei University Wonju College of Medicine, Wonju, Korea; 4Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Korea; 5Department of Pediatrics, Luton & Dunstable University Hospital NHS Foundation Trust, Luton, UK; 6Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea; 7Division of Pediatric Nephrology, Severance Children’s Hospital, Seoul, Korea; 8Institute of Kidney Disease Research, Yonsei University College of Medicine, Seoul, Korea; 9Department of Internal Medicine IV (Nephrology and Hypertension), Medical University Innsbruck, Innsbruck, Austria 1,3) The publication of genetic epidemiology meta-analyses has analyses have redundant duplicate topics and many errors. increased rapidly, but it has been suggested that many of the Although there has been an impressive increase in meta-analyses statistically significant results are false positive. In addition, from China, particularly those on genetic associa tions, most most such meta-analyses have been redundant, duplicate, and claimed candidate gene associations are likely false-positives, erroneous, leading to research waste. In addition, since most suggesting an urgent global need to incorporate genome-wide claimed candidate gene associations were false-positives, cor- data and state-of-the art statistical inferences to avoid a flood of rectly interpreting the published results is important.
  • Bioinformatics: a Practical Guide to the Analysis of Genes and Proteins, Second Edition Andreas D

    Bioinformatics: a Practical Guide to the Analysis of Genes and Proteins, Second Edition Andreas D

    BIOINFORMATICS A Practical Guide to the Analysis of Genes and Proteins SECOND EDITION Andreas D. Baxevanis Genome Technology Branch National Human Genome Research Institute National Institutes of Health Bethesda, Maryland USA B. F. Francis Ouellette Centre for Molecular Medicine and Therapeutics Children’s and Women’s Health Centre of British Columbia University of British Columbia Vancouver, British Columbia Canada A JOHN WILEY & SONS, INC., PUBLICATION New York • Chichester • Weinheim • Brisbane • Singapore • Toronto BIOINFORMATICS SECOND EDITION METHODS OF BIOCHEMICAL ANALYSIS Volume 43 BIOINFORMATICS A Practical Guide to the Analysis of Genes and Proteins SECOND EDITION Andreas D. Baxevanis Genome Technology Branch National Human Genome Research Institute National Institutes of Health Bethesda, Maryland USA B. F. Francis Ouellette Centre for Molecular Medicine and Therapeutics Children’s and Women’s Health Centre of British Columbia University of British Columbia Vancouver, British Columbia Canada A JOHN WILEY & SONS, INC., PUBLICATION New York • Chichester • Weinheim • Brisbane • Singapore • Toronto Designations used by companies to distinguish their products are often claimed as trademarks. In all instances where John Wiley & Sons, Inc., is aware of a claim, the product names appear in initial capital or ALL CAPITAL LETTERS. Readers, however, should contact the appropriate companies for more complete information regarding trademarks and registration. Copyright ᭧ 2001 by John Wiley & Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic or mechanical, including uploading, downloading, printing, decompiling, recording or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the Publisher.
  • Genes & Gene Finding

    Genes & Gene Finding

    Genes & Gene Finding Ben Langmead Department of Computer Science Please sign guestbook (www.langmead-lab.org/teaching-materials) to tell me briefly how you are using the slides. For original Keynote files, email me ([email protected]). Gene finding Recall the "Central Dogma" and the centrality of genes DNA Transcription RNA Translation DNA molecules contain information about Protein how to create proteins; this is transcribed into RNA molecules, which, in turn, direct chemical machinery to translate the message into a protein. Hunter, Lawrence. "Life and its molecules: A brief introduction." AI Magazine 25.1 (2004): 9. Picture from: Roy H, Ibba M. Molecular biology: sticky end in protein synthesis. Nature. 2006 Sep 7;443(7107):41-2. Bacterial genes Genes (colored arrows) packed tightly into the Staphylococcus aureus genome In bacteria, one gene corresponds to one continuous interval on the genome We have good methods for predicting where these genes are Bacterial gene finding Approaches can identify exact bacterial genes with as high as 92% accuracy; can identity gene ends with ≥98% accuracy Delcher, Arthur L., et al. "Identifying bacterial genes and endosymbiont DNA with Glimmer." Bioinformatics 23.6 (2007): 673-679. Eukaryotic genes Eukaryotic genes are more complex than prokaryotic (bacterial) genes for several reasons, as we’ll see Likewise, finding eukaryotic genes computationally is harder Gene finding During the Human Genome Project, there was public debate about how many genes were in the human genome A range of predictions were
  • Biochemical and Structural Analysis of Thermostable Esterases

    Biochemical and Structural Analysis of Thermostable Esterases

    Biochemical and Structural Analysis of Thermostable Esterases Mark Levisson Thesis supervisors: Prof. dr. J. van der Oost Personal chair at the Laboratory of Microbiology Wageningen University Prof. dr. W.M. de Vos Professor of Microbiology Wageningen University Thesis co-supervisor: Dr. S.W.M. Kengen Assistant Professor at the Laboratory of Microbiology Wageningen University Other members: Prof. dr. ir. H. Gruppen Wageningen University Dr. M.C.R Franssen Wageningen University Dr. T. Sonke DSM, Geleen Prof. dr. B.W. Dijkstra University of Groningen Dr. A.M.W.H Thunnissen University of Groningen This research was conducted under the auspices of the Graduate School VLAG Biochemical and Structural Analysis of Thermostable Esterases Mark Levisson Thesis submitted in partial fulfilment of the requirements for the degree of doctor at Wageningen University by the authority of the Rector Magnificus Prof. dr. M.J. Kropff, in the presence of the Thesis Committee appointed by the Doctorate Board to be defended in public on Monday 28 September 2009 at 4 PM in the Aula Levisson, M. Biochemical and Structural Analysis of Thermostable Esterases PhD Thesis, Wageningen University, Wageningen, The Netherlands (2009) 170 pages - With references, and with summaries in English and Dutch ISBN: 978-90-8585-459-3 TABLE OF contents Aim and outline 1 Chapter 1 Introduction 5 Chapter 2 Characterization and structural modeling of a new type of 21 thermostable esterase from Thermotoga maritima Chapter 3 Crystallization and preliminary crystallographic analysis of
  • Comparative Kinetic Modeling of Growth and Molecular Hydrogen Overproduction by Engineered Strains of Thermotoga Maritima

    Comparative Kinetic Modeling of Growth and Molecular Hydrogen Overproduction by Engineered Strains of Thermotoga Maritima

    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by DigitalCommons@University of Nebraska University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Chemical and Biomolecular Engineering -- All Chemical and Biomolecular Engineering, Faculty Papers Department of 2019 Comparative kinetic modeling of growth and molecular hydrogen overproduction by engineered strains of Thermotoga maritima Raghuveer Singh University of Nebraska-Lincoln, [email protected] Rahul Tevatia University of Nebraska-Lincoln, [email protected] Derrick White University of Nebraska-Lincoln Yasar Demirel University of Nebraska-Lincoln, [email protected] Paul H. Blum University of Nebraska - Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/chemengall Part of the Biomedical Engineering and Bioengineering Commons, and the Catalysis and Reaction Engineering Commons Singh, Raghuveer; Tevatia, Rahul; White, Derrick; Demirel, Yasar; and Blum, Paul H., "Comparative kinetic modeling of growth and molecular hydrogen overproduction by engineered strains of Thermotoga maritima " (2019). Chemical and Biomolecular Engineering -- All Faculty Papers. 88. https://digitalcommons.unl.edu/chemengall/88 This Article is brought to you for free and open access by the Chemical and Biomolecular Engineering, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Chemical and Biomolecular Engineering -- All Faculty Papers by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. digitalcommons.unl.edu Comparative kinetic modeling of growth and molecular hydrogen overproduction by engineered strains of Thermotoga maritima Raghuveer Singh,1 Rahul Tevatia,2 Derrick White,1 Yaşar Demirel,2 Paul Blum 1 1 Beadle Center for Genetics, University of Nebraska-Lincoln, 68588, USA 2 Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, 68588, USA Corresponding authors — R.
  • Computational Gene Finding

    Computational Gene Finding

    Computational gene finding Devika Subramanian Comp 470 Outline (3 lectures) The biological context Lec 1 Markov models and Hidden Markov models Lec 2 Ab-initio methods for gene finding Comparative methods for gene finding Lec 3 Evaluating gene finding programs (c) Devika Subramanian, 2009 2 The biological context Introduction to the human genome and genes The central dogma: transcription and translation (c) Devika Subramanian, 2009 3 Facts about the human genome The human genome contains 3 billion chemical nucleotide bases (A, C, T, and G). About 20,500 genes are estimated to be in the human genome. Chromosome 1 (the largest human chromosome) has the most genes (2968), and the Y chromosome has the fewest (231). http://www.pnas.org/content/104/49/19428.abstract ~17,000 genes confirmed experimentally/Ensembl2009 (c) Devika Subramanian, 2009 4 More facts The average gene consists of 3000 bases, but sizes vary greatly, with the largest known human gene being dystrophin at 2.4 million bases. (c) Devika Subramanian, 2009 5 More facts Genes appear to be concentrated in random areas along the genome, with vast expanses of non-coding DNA between. About 2% of the genome encodes instructions for the synthesis of proteins. We do not know the function of more than 50% of the discovered genes. (c) Devika Subramanian, 2009 6 More facts The human genome sequence is almost (99.9%) exactly the same in all people. There are about 3 million locations where single-base DNA differences occur in humans (Single Nucleotide Polymorphisms or SNPs). Over 40% of the predicted human proteins share similarity with fruit-fly or worm proteins.