RiboTALE: A modular, inducible system for accurate gene expression control
|
|
|
- Hillary McGee
- 5 years ago
- Views:
Transcription
1 RiboTALE: A modular, inducible system for accurate gene expression control Navneet Rai, 1 Aura Ferreiro, Alexander Neckelmann, Amy Soon, Andrew Yao, 1, Justin Siegel, 1,, Marc Facciotti, 1, Ilias Tagkopoulos, 1,* 1 UC Davis Genome Center, University of California-Davis, Davis, CA, USA. Department of Biochemistry & Molecular Medicine, University of California-Davis, Davis, CA, USA. Department of Chemistry, University of California-Davis, Davis, CA, USA. Department of Biomedical Engineering, University of California-Davis, Davis, CA, USA. Department of Computer Science, University of California-Davis, Davis, CA, USA. UC Davis Undergraduate Program, University of California-Davis, Davis, CA, USA. *Corresponding author (itagkopoulos@ucdavis.edu). Supplementary material Contents Table S1 Constructs submitted to BioBrick registry... Table S List of primers... Table S List of synthesized gblocks... Table S Sequences of Riboswitch and TBS... Table S Strengths of P Const promoters and dissociation constants of TALE proteins... Figure S1. Repression of P Tet based target modules.... Figure S. Repression trajectories of P Tet based target modules... Figure S. Repression trajectories of P Const based target modules.... Figure S. Responses of cells expressing RiboTALE modules and P Const based target modules at single cell level
2 Table S1 Constructs submitted to BioBrick registry Construct BioBrick ID pribo1tale1 K1101 pribotale1 K11011 pribo1tale K1101 pribotale K1101 ptettbs1 K1101 ptettbs K1101 pc0tbs K1101 pc1tbs K110 pctbs K110 pctbs K110 Golden Gate compatible- K1100 -psbk Table S List of primers Primer Type Sequence ( ) TALE Forward TTTTTTGGTCTCACAAGATGTCCGACGCTTCGCCGG TALE Reverse AAAAAAGGTCTCAAAGCTCAACCGGTAGGATCCGGA GFP_lva Forward TTTTTTGGTCTCAGACAATGCGTAAAGGAGAAGAACT GFP_lva Reverse GGGCCTTTCTGCGTTTATAGCTTTGAGACCTTTTTT GFP_lva,_SDM Forward CCCAACGAAAAGAGAGATCACATGGTCCTTCTTGAG GFP_lva,_SDM Reverse CTCAAGAAGGACCATGTGATCTCTCTTTTCGTTGGG XbaI_TBS1 Forward ATAATGTCTAGATAAACAGATAAATAGACAA XbaI_TBS Forward ATAATGTCTAGATGAGTGCGGGAGCGTGGGG BBa_G00101 Reverse ATTACCGCCTTTGAGTGAGC psbk_sdm Forward CAGTGCTGCAATGATACCGCAAGACCCACGCTCACCGGCTC psbk_sdm Reverse GAGCCGGTGAGCGTGGGTCTTGCGGTATCATTGCAGCACTG Table S List of synthesized gblocks Part Oligonucleotide sequence ( ) pbad+ TATAGTGGTCTCAATGCACATTGATTATTTGCACGGCGTCACACTTTGCTAT Riboswitch-1 GCCATAGCAAGATAGTCCATAAGATTAGCGGATCCTACCTGACGCTTTTTAT +GFP CGCAACTCTCTACTGTTTCTCCATACCGTTTTTTTGGGCTAGCGGTGATACC AGCATCGTCTTGATGCCCTTGGCAGCACCCTGCTAAGGAGGTAACAACAAGT pbad+ Riboswitch- +GFP ptet+tbs1+ B00 ptet+tbs+ B00 GAGACCTCGATG TATAGTGGTCTCAATGCACATTGATTATTTGCACGGCGTCACACTTTGCTAT GCCATAGCAAGATAGTCCATAAGATTAGCGGATCCTACCTGACGCTTTTTAT CGCAACTCTCTACTGTTTCTCCATACCGTTTTTTTGGGCTAGCGGTGATACC AGCATCGTCTTGATGCCCTTGGCAGCACCCCGCTGCAGGACAACAAGTGAGA CCTCGATG TTTTTTGGTCTCAATGCTCCCTATCAGTGATAGAGATTGACATCCCTATCAG TGATAGAGATACTGAGCACTAAACAGATAAATAGAAAAGAGGAGAAAGACAT GAGACCAAAAAA TTTTTTGGTCTCAATGCTCCCTATCAGTGATAGAGATTGACATCCCTATCAG TGATAGAGATACTGAGCACTGAGTGCGGGAGCGTGGGGAAAGAGGAGAAAGA CATGAGACCAAAAAA
3 Table S Sequences of Riboswitch and TBS Sequences Riboswitch 1 Riboswitch GGUGAUACCAGCAUCGUCUUGAUGCCCUUGGCAGCACCCUGCUAAGGAGGUAACAACA AG GGUGAUACCAGCAUCGUCUUGAUGCCCUUGGCAGCACCCCGCUGCAGGACAACAAG TBS1 TAAACAGATAAATAGACAA TBS TGAGTGCGGGAGCGTGGGG Table S Strengths of PConst promoters and dissociation constants of TALE proteins Strengths of P Const promoters* Promoter BioBrick ID Relative promoter strengths* J100 1 J J10 0. J10 0. Dissociation constants (K D ) of TALEs 1 TALE1 0±0 nm TALE 1.±0. nm *parts.igem.org/promoters/catalog/anderson
4 Figure S1. Repression of P Tet based target modules. RiboTALE repression system that consists of (A) RiboTALE module pribotale1 and target module ptettbs1 at 0 ng/ml atc, (B) RiboTALE module pribotale1 and target module ptettbs1 at 100 ng/ml atc, (C) RiboTALE module pribotale and target module ptettbs at 0 ng/ml atc, (D) RiboTALE module pribotale and target module ptettbs at 100 ng/ml atc. KD of TALE1, 0±0 nm; KD of TALE, 1.±0. nm.. Error bars represent standard error of the mean (N=). 8
5 Figure S. Repression trajectories of P Tet based target modules. Repression trajectory, at saturating levels of atc (100 ng/ml), of RiboTALE repression system that consists of (A) RiboTALE module pribotale1 and target module ptettbs1, (B) RiboTALE module pribotale and target module ptettbs. Color bar indicates fold repression. KD of TALE1, 0±0 nm; KD of TALE, 1.±0. nm. 8
6 Figure S. Repression trajectories of P Const based target modules. Repression trajectory of RiboTALE repression system that consists of (A) RiboTALE module pribo1tale and target module pc0tbs, (B) RiboTALE module pribotale and target module pc0tbs, (C) RiboTALE module pribo1tale and target module pc1tbs, (D) RiboTALE module pribotale and target module pc1tbs. Color bar indicates fold repression.
7 Figure S. Responses of cells expressing RiboTALE modules and P Const based target modules at single cell level. (A) pribo1tale and pctbs, (B) pribotale and pctbs, (C) pribo1tale and pctbs, (D) pribotale and pctbs. (E) pribo1tale and pc0tbs, (F) pribotale and pc0tbs, (G) pribo1tale and pc1tbs, (H) pribotale and pc1tbs.
8 References 1 Meckler, J. F. et al. Quantitative analysis of TALE-DNA interactions suggests polarity effects. Nucleic Acids Res 1, (01). 8
A transcription activator-like effector induction system mediated by proteolysis
SUPPLEMENTARY INFORMATION A transcription activator-like effector induction system mediated by proteolysis Matthew F. Copeland 1,2, Mark C. Politz 1, Charles B. Johnson 1,3, Andrew L. Markley 1, Brian
Supplementary Materials for
www.sciencesignaling.org/cgi/content/full/7/345/ra91/dc1 Supplementary Materials for TGF-β induced epithelial-to-mesenchymal transition proceeds through stepwise activation of multiple feedback loops Jingyu
Cadmium Poisoning Ingestion of cadmium can cause: Cancer Renal failure Bone weakening and fracture Damage to nervous and immune systems Death Danger Level Present in over 60% of hazardous waste sites as
igem Jamboree MIT Nov 4th 2006 Imperial College
igem Jamboree MIT Nov 4th 2006 Engineering a Molecular Predation Oscillator igem 2006 @ Imperial Biomedical Engineers Electrical Engineer Biochemist Biologists Biomedical Engineers Biochemists Dr Mann
Welcome to Class 21!
Welcome to Class 21! Introductory Biochemistry! Lecture 21: Outline and Objectives l Regulation of Gene Expression in Prokaryotes! l transcriptional regulation! l principles! l lac operon! l trp attenuation!
Measuring TF-DNA interactions
Measuring TF-DNA interactions How is Biological Complexity Achieved? Mediated by Transcription Factors (TFs) 2 Regulation of Gene Expression by Transcription Factors TF trans-acting factors TF TF TF TF
Genomics and bioinformatics summary. Finding genes -- computer searches
Genomics and bioinformatics summary 1. Gene finding: computer searches, cdnas, ESTs, 2. Microarrays 3. Use BLAST to find homologous sequences 4. Multiple sequence alignments (MSAs) 5. Trees quantify sequence
A rule of seven in Watson-Crick base-pairing of mismatched sequences
A rule of seven in Watson-Crick base-pairing of mismatched sequences Ibrahim I. Cisse 1,3, Hajin Kim 1,2, Taekjip Ha 1,2 1 Department of Physics and Center for the Physics of Living Cells, University of
Bi 8 Lecture 11. Quantitative aspects of transcription factor binding and gene regulatory circuit design. Ellen Rothenberg 9 February 2016
Bi 8 Lecture 11 Quantitative aspects of transcription factor binding and gene regulatory circuit design Ellen Rothenberg 9 February 2016 Major take-home messages from λ phage system that apply to many
Lecture 4: Transcription networks basic concepts
Lecture 4: Transcription networks basic concepts - Activators and repressors - Input functions; Logic input functions; Multidimensional input functions - Dynamics and response time 2.1 Introduction The
L3.1: Circuits: Introduction to Transcription Networks. Cellular Design Principles Prof. Jenna Rickus
L3.1: Circuits: Introduction to Transcription Networks Cellular Design Principles Prof. Jenna Rickus In this lecture Cognitive problem of the Cell Introduce transcription networks Key processing network
ydci GTC TGT TTG AAC GCG GGC GAC TGG GCG CGC AAT TAA CGG TGT GTA GGC TGG AGC TGC TTC
Table S1. DNA primers used in this study. Name ydci P1ydcIkd3 Sequence GTC TGT TTG AAC GCG GGC GAC TGG GCG CGC AAT TAA CGG TGT GTA GGC TGG AGC TGC TTC Kd3ydcIp2 lacz fusion YdcIendP1 YdcItrgP2 GAC AGC
MITOCW MIT20_020S09_06_inverter
MITOCW MIT20_020S09_06_inverter >> Izzy: Dude, I like what you built there. What's it do? >> Dude: Oh...hi Iz. This is a cool bug. I made it using an electronics building kit that Sally got me. She wanted
MSc Drug Design. Module Structure: (15 credits each) Lectures and Tutorials Assessment: 50% coursework, 50% unseen examination.
Module Structure: (15 credits each) Lectures and Assessment: 50% coursework, 50% unseen examination. Module Title Module 1: Bioinformatics and structural biology as applied to drug design MEDC0075 In the
Analog Electronics Mimic Genetic Biochemical Reactions in Living Cells
Analog Electronics Mimic Genetic Biochemical Reactions in Living Cells Dr. Ramez Daniel Laboratory of Synthetic Biology & Bioelectronics (LSB 2 ) Biomedical Engineering, Technion May 9, 2016 Cytomorphic
Introduction. ECE/CS/BioEn 6760 Modeling and Analysis of Biological Networks. Adventures in Synthetic Biology. Synthetic Biology.
Introduction ECE/CS/BioEn 6760 Modeling and Analysis of Biological Networks Chris J. Myers Lecture 17: Genetic Circuit Design Electrical engineering principles can be applied to understand the behavior
Supplementary Information. Characteristics of Long Non-coding RNAs in the Brown Norway Rat and. Alterations in the Dahl Salt-Sensitive Rat
Supplementary Information Characteristics of Long Non-coding RNAs in the Brown Norway Rat and Alterations in the Dahl Salt-Sensitive Rat Feng Wang 1,2,3,*, Liping Li 5,*, Haiming Xu 5, Yong Liu 2,3, Chun
15.2 Prokaryotic Transcription *
OpenStax-CNX module: m52697 1 15.2 Prokaryotic Transcription * Shannon McDermott Based on Prokaryotic Transcription by OpenStax This work is produced by OpenStax-CNX and licensed under the Creative Commons
Chapter 15 Active Reading Guide Regulation of Gene Expression
Name: AP Biology Mr. Croft Chapter 15 Active Reading Guide Regulation of Gene Expression The overview for Chapter 15 introduces the idea that while all cells of an organism have all genes in the genome,
3.B.1 Gene Regulation. Gene regulation results in differential gene expression, leading to cell specialization.
3.B.1 Gene Regulation Gene regulation results in differential gene expression, leading to cell specialization. We will focus on gene regulation in prokaryotes first. Gene regulation accounts for some of
GENE ACTIVITY Gene structure Transcription Transcript processing mrna transport mrna stability Translation Posttranslational modifications
1 GENE ACTIVITY Gene structure Transcription Transcript processing mrna transport mrna stability Translation Posttranslational modifications 2 DNA Promoter Gene A Gene B Termination Signal Transcription
SUPPLEMENTARY INFORMATION
PRC2 represses dedifferentiation of mature somatic cells in Arabidopsis Momoko Ikeuchi 1 *, Akira Iwase 1 *, Bart Rymen 1, Hirofumi Harashima 1, Michitaro Shibata 1, Mariko Ohnuma 1, Christian Breuer 1,
SECOND PUBLIC EXAMINATION. Honour School of Physics Part C: 4 Year Course. Honour School of Physics and Philosophy Part C C7: BIOLOGICAL PHYSICS
2757 SECOND PUBLIC EXAMINATION Honour School of Physics Part C: 4 Year Course Honour School of Physics and Philosophy Part C C7: BIOLOGICAL PHYSICS TRINITY TERM 2013 Monday, 17 June, 2.30 pm 5.45 pm 15
Flow of Genetic Information
presents Flow of Genetic Information A Montagud E Navarro P Fernández de Córdoba JF Urchueguía Elements Nucleic acid DNA RNA building block structure & organization genome building block types Amino acid
BMD645. Integration of Omics
BMD645 Integration of Omics Shu-Jen Chen, Chang Gung University Dec. 11, 2009 1 Traditional Biology vs. Systems Biology Traditional biology : Single genes or proteins Systems biology: Simultaneously study
Electrical circuits as models for biological circuits
Electrical circuits as models for biological circuits State 1 1 State Trigger State 0 0 Time Electrical circuits (light bulb) are ideal models because a trigger (i.e. light switch) produces an immediate
Erzsébet Ravasz Advisor: Albert-László Barabási
Hierarchical Networks Erzsébet Ravasz Advisor: Albert-László Barabási Introduction to networks How to model complex networks? Clustering and hierarchy Hierarchical organization of cellular metabolism The
A Synthetic Oscillatory Network of Transcriptional Regulators
A Synthetic Oscillatory Network of Transcriptional Regulators Michael Elowitz & Stanislas Leibler Nature, 2000 Presented by Khaled A. Rahman Background Genetic Networks Gene X Operator Operator Gene Y
Introduction. Gene expression is the combined process of :
1 To know and explain: Regulation of Bacterial Gene Expression Constitutive ( house keeping) vs. Controllable genes OPERON structure and its role in gene regulation Regulation of Eukaryotic Gene Expression
A Visual Process Calculus for Biology
A Visual Process Calculus for Biology Andrew Phillips Microsoft Research 7 JJ Thomson Avenue CB3 0FB Cambridge UK Abstract. This chapter presents a visual process calculus for designing and simulating
Chapter 2: Chemical Basis of Life I. Introduction A. The study of chemistry is essential for the study of physiology because
Shier, Butler, and Lewis: Hole s Human Anatomy and Physiology, 11 th ed. Chapter 2: Chemical Basis of Life Chapter 2: Chemical Basis of Life I. Introduction A. The study of chemistry is essential for the
Multistability in the lactose utilization network of E. coli. Lauren Nakonechny, Katherine Smith, Michael Volk, Robert Wallace Mentor: J.
Multistability in the lactose utilization network of E. coli Lauren Nakonechny, Katherine Smith, Michael Volk, Robert Wallace Mentor: J. Ruby Abrams Motivation Understanding biological switches in the
REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR
REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR Grade Requirement: All courses required for the Biochemistry major (CH, MATH, PHYS, BI courses) must be graded and passed with a grade of C- or better. Core Chemistry
Name: TF: Section Time: LS1a ICE 5. Practice ICE Version B
Name: TF: Section Time: LS1a ICE 5 Practice ICE Version B 1. (8 points) In addition to ion channels, certain small molecules can modulate membrane potential. a. (4 points) DNP ( 2,4-dinitrophenol ), as
Supporting information for
Supporting information for Rewiring multi-domain protein switches: transforming a fluorescent Zn 2+ -sensor into a light-responsive Zn 2+ binding protein Stijn J.A. Aper and Maarten Merkx Laboratory of
Nature Genetics: doi: /ng Supplementary Figure 1. Plasmid diagrams of primary strains used in this work.
Supplementary Figure 1 Plasmid diagrams of primary strains used in this work. Refer to Supplementary Table 1 for additional information and full list of strains. Diagrams are not to scale. (a) Strain used
SUPPLEMENTARY INFORMATION
reverse 3175 3175 F L C 318 318 3185 3185 319 319 3195 3195 315 8 1 315 3155 315 317 Supplementary Figure 3. Stability of expression of the GFP sensor constructs return to warm conditions. Semi-quantitative
Newly made RNA is called primary transcript and is modified in three ways before leaving the nucleus:
m Eukaryotic mrna processing Newly made RNA is called primary transcript and is modified in three ways before leaving the nucleus: Cap structure a modified guanine base is added to the 5 end. Poly-A tail
UNIT 6 PART 3 *REGULATION USING OPERONS* Hillis Textbook, CH 11
UNIT 6 PART 3 *REGULATION USING OPERONS* Hillis Textbook, CH 11 REVIEW: Signals that Start and Stop Transcription and Translation BUT, HOW DO CELLS CONTROL WHICH GENES ARE EXPRESSED AND WHEN? First of
REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR
REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR Grade Requirement: All courses required for the Biochemistry major (CH, MATH, PHYS, BI courses) must be graded and passed with a grade of C- or better. Core Chemistry
Prokaryotic Gene Expression (Learning Objectives)
Prokaryotic Gene Expression (Learning Objectives) 1. Learn how bacteria respond to changes of metabolites in their environment: short-term and longer-term. 2. Compare and contrast transcriptional control
APGRU6L2. Control of Prokaryotic (Bacterial) Genes
APGRU6L2 Control of Prokaryotic (Bacterial) Genes 2007-2008 Bacterial metabolism Bacteria need to respond quickly to changes in their environment STOP u if they have enough of a product, need to stop production
Hole s Human Anatomy and Physiology Eleventh Edition. Chapter 2
Hole s Human Anatomy and Physiology Eleventh Edition Shier Butler Lewis Chapter 2 1 Copyright The McGraw-Hill Companies, Inc. Permission required for reproduction or display. CHAPTER 2 CHEMICAL BASIS OF
Bi 1x Spring 2014: LacI Titration
Bi 1x Spring 2014: LacI Titration 1 Overview In this experiment, you will measure the effect of various mutated LacI repressor ribosome binding sites in an E. coli cell by measuring the expression of a
Three-dimensional structure of a viral genome-delivery portal vertex
Three-dimensional structure of a viral genome-delivery portal vertex Adam S. Olia 1, Peter E. Prevelige Jr. 2, John E. Johnson 3 and Gino Cingolani 4 1 Department of Biological Sciences, Purdue University,
CS-E5880 Modeling biological networks Gene regulatory networks
CS-E5880 Modeling biological networks Gene regulatory networks Jukka Intosalmi (based on slides by Harri Lähdesmäki) Department of Computer Science Aalto University January 12, 2018 Outline Modeling gene
GENETICS - CLUTCH CH.12 GENE REGULATION IN PROKARYOTES.
GEETICS - CLUTCH CH.12 GEE REGULATIO I PROKARYOTES!! www.clutchprep.com GEETICS - CLUTCH CH.12 GEE REGULATIO I PROKARYOTES COCEPT: LAC OPERO An operon is a group of genes with similar functions that are
Biochemistry in Singulo:
Biochemistry in Singulo: When Less Means More Carlos Bustamante University of California, Berkeley The Ensemble Approach The study of chemical transforma9ons has been dominated by the ensemble method:
igem 2009 Team Newcastle
igem 2009 Team Newcastle Introduction Environmental project Heavy metal pollution in soil Cadmium accumulation issue Image: http://www.enst.umd.edu/people/weil/researchprojects.cfm Use of engineered micro-organisms
SUPPLEMENTARY INFORMATION
doi:10.1038/nature11589 Supplementary Figure 1 Ciona intestinalis and Petromyzon marinus neural crest expression domain comparison. Cartoon shows dorsal views of Ciona mid gastrula (left) and Petromyzon
Molecular biology and biochemistry of archaeal DNA replication
Molecular biology and biochemistry of archaeal DNA replication Isaac Cann Institute for Universal Biology, NASA Astrobiology Institute Department of Animal Science & Department of Microbiology University
A synthetic oscillatory network of transcriptional regulators
A synthetic oscillatory network of transcriptional regulators Michael B. Elowitz & Stanislas Leibler, Nature, 403, 2000 igem Team Heidelberg 2008 Journal Club Andreas Kühne Introduction Networks of interacting
(Lys), resulting in translation of a polypeptide without the Lys amino acid. resulting in translation of a polypeptide without the Lys amino acid.
1. A change that makes a polypeptide defective has been discovered in its amino acid sequence. The normal and defective amino acid sequences are shown below. Researchers are attempting to reproduce the
Dynamic modular architecture of protein-protein interaction networks beyond the dichotomy of date and party hubs
Dynamic modular architecture of protein-protein interaction networks beyond the dichotomy of date and party hubs Xiao Chang 1,#, Tao Xu 2,#, Yun Li 3, Kai Wang 1,4,5,* 1 Zilkha Neurogenetic Institute,
Biochemistry-BS Program Study Abroad Pathway
Biochemistry-BS Program Study Abroad Pathway (last revised September 2016) Table 1a: Undergraduate Program Schedule These undergraduate program schedules are subject to change. Please verify information
The geneticist s questions. Deleting yeast genes. Functional genomics. From Wikipedia, the free encyclopedia
From Wikipedia, the free encyclopedia Functional genomics..is a field of molecular biology that attempts to make use of the vast wealth of data produced by genomic projects (such as genome sequencing projects)
The Riboswitch is functionally separated into the ligand binding APTAMER and the decision-making EXPRESSION PLATFORM
The Riboswitch is functionally separated into the ligand binding APTAMER and the decision-making EXPRESSION PLATFORM Purine riboswitch TPP riboswitch SAM riboswitch glms ribozyme In-line probing is used
Topic 4: Equilibrium binding and chemical kinetics
Topic 4: Equilibrium binding and chemical kinetics Outline: Applications, applications, applications use Boltzmann to look at receptor-ligand binding use Boltzmann to look at PolII-DNA binding and gene
SynBioSS Wiki. Introduction to SynBioSS Wiki. Database Structure
I. SynBioSSWiki IntroductiontoSynBioSSWiki SynBioSS Wiki is a component of the Synthetic Biology Software Suite (synbioss.sourceforge.net). SynBioSS Wiki is practically two things: i) a web interface basedonthemediawikipackageandii)adatabaseforstoringmolecularcomponents,their
Maria V. Yamburenko, Yan O. Zubo, Radomíra Vanková, Victor V. Kusnetsov, Olga N. Kulaeva, Thomas Börner
ABA represses the transcription of chloroplast genes Maria V. Yamburenko, Yan O. Zubo, Radomíra Vanková, Victor V. Kusnetsov, Olga N. Kulaeva, Thomas Börner Supplementary data Supplementary tables Table
Nature Genetics: doi: /ng Supplementary Figure 1. The phenotypes of PI , BR121, and Harosoy under short-day conditions.
Supplementary Figure 1 The phenotypes of PI 159925, BR121, and Harosoy under short-day conditions. (a) Plant height. (b) Number of branches. (c) Average internode length. (d) Number of nodes. (e) Pods
EXPRESSION OF THE FIS2 PROMOTER IN ARABIDOPSIS THALIANA
EXPRESSION OF THE FIS2 PROMOTER IN ARABIDOPSIS THALIANA Item Type text; Electronic Thesis Authors Bergstrand, Lauren Janel Publisher The University of Arizona. Rights Copyright is held by the author. Digital
Regulation of Gene Expression
Chapter 18 Regulation of Gene Expression PowerPoint Lecture Presentations for Biology Eighth Edition Neil Campbell and Jane Reece Lectures by Chris Romero, updated by Erin Barley with contributions from
Optimization of the heme biosynthesis pathway for the production of. 5-aminolevulinic acid in Escherichia coli
Supplementary Information Optimization of the heme biosynthesis pathway for the production of 5-aminolevulinic acid in Escherichia coli Junli Zhang 1,2,3, Zhen Kang 1,2,3, Jian Chen 2,3 & Guocheng Du 2,4
Multiple Choice Review- Eukaryotic Gene Expression
Multiple Choice Review- Eukaryotic Gene Expression 1. Which of the following is the Central Dogma of cell biology? a. DNA Nucleic Acid Protein Amino Acid b. Prokaryote Bacteria - Eukaryote c. Atom Molecule
Correcting Errors Due to Species Correlations in the Marginal Probability Density Evolution
Utah State University DigitalCommons@USU All Graduate Theses and Dissertations Graduate Studies 5-2013 Correcting Errors Due to Species Correlations in the Marginal Probability Density Evolution Abiezer
a-fB. Code assigned:
This form should be used for all taxonomic proposals. Please complete all those modules that are applicable (and then delete the unwanted sections). For guidance, see the notes written in blue and the
56:198:582 Biological Networks Lecture 10
56:198:582 Biological Networks Lecture 10 Temporal Programs and the Global Structure The single-input module (SIM) network motif The network motifs we have studied so far all had a defined number of nodes.
Supplementary Figure 1. Confirmation of REF52-hE2F1p::4NLS-d4Venus reporter cells and characterization of E2F dynamics. (a) Alignment of E2F dynamics
Supplementary Figure 1. Confirmation of REF52-hE2F1p::4NLS-d4Venus reporter cells and characterization of E2F dynamics. (a) Alignment of E2F dynamics trajectories to endogenous E2F1 mrna expression. Gray
a-dB. Code assigned:
This form should be used for all taxonomic proposals. Please complete all those modules that are applicable (and then delete the unwanted sections). For guidance, see the notes written in blue and the
STOCHASTIC ANALYSIS OF SYNTHETIC GENETIC CIRCUITS
STOCHASTIC ANALYSIS OF SYNTHETIC GENETIC CIRCUITS by Curtis K. Madsen A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor
Supplementary information. A proposal for a novel impact factor as an alternative to the JCR impact factor
Supplementary information A proposal for a novel impact factor as an alternative to the JCR impact factor Zu-Guo Yang a and Chun-Ting Zhang b, * a Library, Tianjin University, Tianjin 300072, China b Department
Exploring the Sequence Dependent Structure and Dynamics of DNA with Molecular Dynamics Simulation
Exploring the Sequence Dependent Structure and Dynamics of DNA with Molecular Dynamics Simulation Sarah Harris School of Physics and Astronomy University of Leeds Introduction Calculations of the charge
Cellular Systems Biology or Biological Network Analysis
Cellular Systems Biology or Biological Network Analysis Joel S. Bader Department of Biomedical Engineering Johns Hopkins University (c) 2012 December 4, 2012 1 Preface Cells are systems. Standard engineering
Supplementary Information
Supplementary Information 11 1 1 1 1 1 1 1 1 0 1 SECTION S1: PROPOSED MODEL FOR INDUCTION AND SHUTDOWN OF THE CONJUGATION OPERON IN PAD1 AND PAM. Based on the organizational similarity, the model previously
AP Bio Module 16: Bacterial Genetics and Operons, Student Learning Guide
Name: Period: Date: AP Bio Module 6: Bacterial Genetics and Operons, Student Learning Guide Getting started. Work in pairs (share a computer). Make sure that you log in for the first quiz so that you get
56:198:582 Biological Networks Lecture 8
56:198:582 Biological Networks Lecture 8 Course organization Two complementary approaches to modeling and understanding biological networks Constraint-based modeling (Palsson) System-wide Metabolism Steady-state
Microscopy, Optical Spectroscopy, and Macroscopic Techniques
Microscopy, Optical Spectroscopy, and Macroscopic Techniques Methods in Molecular Biology John M, Walker, SERIES EDITOR 22. Microscopy, Optical Spectroscopy, and Macroscopic Techniques, edited by Christopher
REVIEW SESSION. Wednesday, September 15 5:30 PM SHANTZ 242 E
REVIEW SESSION Wednesday, September 15 5:30 PM SHANTZ 242 E Gene Regulation Gene Regulation Gene expression can be turned on, turned off, turned up or turned down! For example, as test time approaches,
Structural insights into bacterial flagellar hooks similarities and specificities
Supplementary information Structural insights into bacterial flagellar hooks similarities and specificities Young-Ho Yoon, Clive S. Barker, Paula V. Bulieris, Hideyuki Matsunami, Fadel A. Samatey* Affiliation:
CHEM 121: Chemical Biology
Instructors Prof. Jane M. Liu (HS-212) jliu3@drew.edu x3303 Office Hours Anytime my office door is open CHEM 121: Chemical Biology Class MF 2:30-3:45 pm PRE-REQUISITES: CHEM 117 COURSE OVERVIEW This upper-level
Written Exam 15 December Course name: Introduction to Systems Biology Course no
Technical University of Denmark Written Exam 15 December 2008 Course name: Introduction to Systems Biology Course no. 27041 Aids allowed: Open book exam Provide your answers and calculations on separate
2. Mathematical descriptions. (i) the master equation (ii) Langevin theory. 3. Single cell measurements
1. Why stochastic?. Mathematical descriptions (i) the master equation (ii) Langevin theory 3. Single cell measurements 4. Consequences Any chemical reaction is stochastic. k P d φ dp dt = k d P deterministic
Supplemental Data. Yamamoto et al. (2016). Plant Cell /tpc WT + HCO 3. slac1-4/δnc #5 + HCO 3 WT + ABA. slac1-4/δnc #5 + ABA
I (pa) I (pa) A WT + HCO 3 B 2 V (mv) 15 1 5 5 2 slac14/δnc #5 + HCO 3 4 6 WT (n = 6) 8 WT + HCO 3 (n = 7) slac14/δnc #5 (n = 6) slac14/δnc #5 + HCO 3 (n = 1) C WT + ABA D 2 V (mv) 15 1 5 5 2 slac14/δnc
Precisely Control Protein Expression.
Precisely Control Protein Expression Howard M. Salis 1, Ethan A. Mirsky 2, and Christopher A. Voigt 1* 1 Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA,
Chapter 4: Hidden Markov Models
Chapter 4: Hidden Markov Models 4.1 Introduction to HMM Prof. Yechiam Yemini (YY) Computer Science Department Columbia University Overview Markov models of sequence structures Introduction to Hidden Markov
CplexA: a Mathematica package to study macromolecularassembly control of gene expression
Journal-ref: Bioinformatics 26, 2060-2061 (2010) Includes Mathematica, Matlab, and Python implementation tutorials. Software can be downloaded at http://cplexa.sourceforge.net/ Gene Expression CplexA:
Supplementary Figure 1. Real time in vivo imaging of SG secretion. (a) SGs from Drosophila third instar larvae that express Sgs3-GFP (green) and
Supplementary Figure 1. Real time in vivo imaging of SG secretion. (a) SGs from Drosophila third instar larvae that express Sgs3-GFP (green) and Lifeact-Ruby (red) were imaged in vivo to visualize secretion
SUPPORTING INFORMATION FOR. SEquence-Enabled Reassembly of β-lactamase (SEER-LAC): a Sensitive Method for the Detection of Double-Stranded DNA
SUPPORTING INFORMATION FOR SEquence-Enabled Reassembly of β-lactamase (SEER-LAC): a Sensitive Method for the Detection of Double-Stranded DNA Aik T. Ooi, Cliff I. Stains, Indraneel Ghosh *, David J. Segal
The Research Plan. Functional Genomics Research Stream. Transcription Factors. Tuning In Is A Good Idea
Functional Genomics Research Stream The Research Plan Tuning In Is A Good Idea Research Meeting: March 23, 2010 The Road to Publication Transcription Factors Protein that binds specific DNA sequences controlling
CISC 636 Computational Biology & Bioinformatics (Fall 2016)
CISC 636 Computational Biology & Bioinformatics (Fall 2016) Predicting Protein-Protein Interactions CISC636, F16, Lec22, Liao 1 Background Proteins do not function as isolated entities. Protein-Protein
Research Proposal. Title: Multiple Sequence Alignment used to investigate the co-evolving positions in OxyR Protein family.
Research Proposal Title: Multiple Sequence Alignment used to investigate the co-evolving positions in OxyR Protein family. Name: Minjal Pancholi Howard University Washington, DC. June 19, 2009 Research
Chapter 16 Lecture. Concepts Of Genetics. Tenth Edition. Regulation of Gene Expression in Prokaryotes
Chapter 16 Lecture Concepts Of Genetics Tenth Edition Regulation of Gene Expression in Prokaryotes Chapter Contents 16.1 Prokaryotes Regulate Gene Expression in Response to Environmental Conditions 16.2
GRAPH-THEORETICAL COMPARISON REVEALS STRUCTURAL DIVERGENCE OF HUMAN PROTEIN INTERACTION NETWORKS
141 GRAPH-THEORETICAL COMPARISON REVEALS STRUCTURAL DIVERGENCE OF HUMAN PROTEIN INTERACTION NETWORKS MATTHIAS E. FUTSCHIK 1 ANNA TSCHAUT 2 m.futschik@staff.hu-berlin.de tschaut@zedat.fu-berlin.de GAUTAM
Bioinformatics: Network Analysis
Bioinformatics: Network Analysis Kinetics of Gene Regulation COMP 572 (BIOS 572 / BIOE 564) - Fall 2013 Luay Nakhleh, Rice University 1 The simplest model of gene expression involves only two steps: the
The geneticist s questions
The geneticist s questions a) What is consequence of reduced gene function? 1) gene knockout (deletion, RNAi) b) What is the consequence of increased gene function? 2) gene overexpression c) What does
Genome Assembly. Sequencing Output. High Throughput Sequencing
Genome High Throughput Sequencing Sequencing Output Example applications: Sequencing a genome (DNA) Sequencing a transcriptome and gene expression studies (RNA) ChIP (chromatin immunoprecipitation) Example
Hiromi Nishida. 1. Introduction. 2. Materials and Methods
Evolutionary Biology Volume 212, Article ID 342482, 5 pages doi:1.1155/212/342482 Research Article Comparative Analyses of Base Compositions, DNA Sizes, and Dinucleotide Frequency Profiles in Archaeal
Tutorial 1 Geometry, Topology, and Biology Patrice Koehl and Joel Hass
Tutorial 1 Geometry, Topology, and Biology Patrice Koehl and Joel Hass University of California, Davis, USA http://www.cs.ucdavis.edu/~koehl/ims2017/ Biology = Multiscale. 10 6 m 10 3 m m mm µm nm Å ps
Supplementary Material. Overexpression of a cytochrome P450 and a UDP-glycosyltransferase is associated with
Supplementary Material Overexpression of a cytochrome P450 and a UDP-glycosyltransferase is associated with imidacloprid resistance in the Colorado potato beetle, Leptinotarsa decemlineata Emine Kaplanoglu