How cells make decisions?. The cell is a (bio)chemical computer Information Processing System Hanahan & Weinberg (2000) External signals outputs.

Slides:



Advertisements
Similar presentations
Network Dynamics and Cell Physiology John J. Tyson Biological Sciences Virginia Tech.
Advertisements

Bioinformatics 3 V18 – Kinetic Motifs Mon, Jan 12, 2015.
Two ways to Regulate a Metabolic Pathway
Network Dynamics and Cell Physiology John J. Tyson Dept. Biological Sciences Virginia Tech.
Simulation of Prokaryotic Genetic Circuits Jonny Wells and Jimmy Bai.
Chapter 18 Regulation of Gene Expression in Prokaryotes
CELL TO CELL COMMUNICATION Part 2. Transduction: Cascades relay signals Signal transduction involves multiple steps Multistep pathways can amplify a signal.
Genetic Regulatory Mechanisms. Control of Gene Expression Transcriptional control Clustering of genes with related function Coordinate control of genes.
Lecture 3: Models of gene regulation. DNA Replication RNA Protein TranscriptionTranslation.
Regulation and Control of Metabolism in Bacteria
Regulation of gene expression Premedical - Biology.
Genetic Regulatory Mechanisms
Enzyme Regulation. Constitutive enzymes –Enzymes needed at the same level all of the time Regulated enzymes –Enzymes needed under some conditions but.
Mukund Thattai NCBS Bangalore genetic networks in theory and practice.
Chapter 18 Regulation of Gene Expression.
Control Mechanisms (Prokaryote) SBI4U. Controlling Expression  When a gene is being used by a cell, it gets transcribed, and then the mRNA is translated.
CHAPTER 8 Metabolic Respiration Overview of Regulation Most genes encode proteins, and most proteins are enzymes. The expression of such a gene can be.
Control of Prokaryotic Gene Expression. Prokaryotic Regulation of Genes Regulating Biochemical Pathway for Tryptophan Synthesis. 1.Produce something that.
AP Biology Chapter 18: Gene Regulation. Regulation of Gene Expression Important for cellular control and differentiation. Understanding “expression” is.
Bacterial Operons A model of gene expression regulation Ch 18.4.
Bacterial Physiology (Micr430) Lecture 13 Regulation of Gene Expression (Text Chapter: 6) (Moat book)
Bacterial Physiology (Micr430) Lecture 1 Overview of Bacterial Physiology (Text Chapters: 1 and 2)
Signaling and the Signal Transduction Cascade. Question?????? External Stimulus Inside cell Nucleus, Gene transcription Other cellular effects.
Molecular Physiology: Enzymes and Cell Signaling.
Protein Networks Week 5. Linear Response A simple example of protein dynamics: protein synthesis and degradation Using the law of mass action, we can.
Gene regulation  Two types of genes: 1)Structural genes – encode specific proteins 2)Regulatory genes – control the level of activity of structural genes.
Synthetic biology: New engineering rules for emerging discipline Andrianantoandro E; Basu S; Karig D K; Weiss R. Molecular Systems Biology 2006.
Today: Regulating gene expression in bactria Exam #1 T 2/17 in class Available: F and M 10-11am, noon-2pm, after 3pm T after 2pm.
Stochastic simulations Application to molecular networks
Gene Expression and Regulation
Metabolic pathway alteration, regulation and control (5) -- Simulation of metabolic network Xi Wang 02/07/2013 Spring 2013 BsysE 595 Biosystems Engineering.
Alexander van Oudenaarden Lab Final Presentation Mashaal Sohail
Bacterial Gene Expression and Regulation
AMATH 382: Computational Modeling of Cellular Systems Dynamic modelling of biochemical, genetic, and neural networks Introductory Lecture, Jan. 6, 2014.
Gene repression and activation
Section 2 CHAPTER 10. PROTEIN SYNTHESIS IN PROKARYOTES Both prokaryotic and eukaryotic cells are able to regulate which genes are expressed and which.
Network Dynamics and Cell Physiology John J. Tyson Department of Biological Sciences & Virginia Bioinformatics Institute & Virginia Bioinformatics Institute.
Complexities of Gene Expression Cells have regulated, complex systems –Not all genes are expressed in every cell –Many genes are not expressed all of.
Cell Signaling. Local Signaling Paracrine Paracrine Synaptic Synaptic.
© 2011 Pearson Education, Inc. Lectures by Stephanie Scher Pandolfi BIOLOGICAL SCIENCE FOURTH EDITION SCOTT FREEMAN 17 Control of Gene Expression in Bacteria.
Controlling Gene Expression. Control Mechanisms Determine when to make more proteins and when to stop making more Cell has mechanisms to control transcription.
22. Lecture WS 2005/06Bioinformatics III1 V22 Modelling Dynamic Cellular Processes John TysonBela Novak Mathematical description of signalling pathways.
16. Lecture WS 2006/07Bioinformatics III1 V16 Modelling Dynamic Cellular Processes John TysonBela Novak Mathematical description of signalling pathways.
Bistable and Oscillatory Systems. Bistable Systems Systems which display two stable steady states with a third unstable state are usually termed bistable.
Chapter 13: Gene Regulation. The Big Picture… A cell contains more genes than it expresses at any given time – why? Why are cells in multicellular organisms.
Metabolic pathways. What do we mean by metabolism? Metabolism is the collective term for the thousands of biochemical _________ that occur within a living.
Gene Expression & Regulation Chapter 8.6. KEY CONCEPT Gene expression is carefully regulated in both prokaryotic and eukaryotic cells.
Higher Human Biology Unit 1 Human Cells KEY AREA 6: Metabolic Pathways.
Gene Expression Chapter 16. DNA regulatory sequence All on DNA Promoters – Start transcription Promoters – Start transcription Terminators – End Transcription.
Control of Metabolic Pathways Higher Human Biology Unit 1 – Section 6 Metabolic Pathways.
Dynamics of biological switches 2. Attila Csikász-Nagy King’s College London Randall Division of Cell and Molecular Biophysics Institute for Mathematical.
BCB 570 Spring Signal Transduction Julie Dickerson Electrical and Computer Engineering.
Warm Up Write down 5 times it would be beneficial for a gene to be ‘turned off’ and the protein not be expressed 1.
Gene Expression and Regulation
Human Cells Metabolic pathways
Control of Gene Expression
Bioinformatics 3 V20 – Kinetic Motifs
„Self Control is the quality that distinguishes the fittest to survive” - George Bernard Shaw.
Controlling Gene Expression
Daily Warm-Up Tuesday, Jan. 7th
„Self Control is the quality that distinguishes the fittest to survive” - George Bernard Shaw.
Nonlinear Control Systems ECSE-6420
AMATH 882: Computational Modeling of Cellular Systems
„Self Control is the quality that distinguishes the fittest to survive” - George Bernard Shaw.
Bioinformatics 3 V20 – Kinetic Motifs
„Self Control is the quality that distinguishes the fittest to survive” - George Bernard Shaw.
Chapter 18 Bacterial Regulation of Gene Expression
Dale Muzzey, Alexander van Oudenaarden  Cell 
Protein Dimerization Generates Bistability in Positive Feedback Loops
Presentation transcript:

How cells make decisions?

The cell is a (bio)chemical computer Information Processing System Hanahan & Weinberg (2000) External signals outputs

? ?

Signal transduction networks Hanahan & Weinberg (2000) p21 Smad MAPK MKK MAPK-P PP

‘Birth control’ for proteins d [protein] dt = synthesis - degradation DNA RNA protein transcription factor transciption translation

Gene expression R S k1k1 k2k2 S = mRNA R = protein response (R) signal (S) linear synthesisdegradation S=1 3 2 R rate (dR/dt) degradation synthesis Signal-response curve

Protein phosphorylation-dephosphorylation

Michaelis-Menten enzyme kinetics since [E o ] = [E] + [ES]

Protein phosphorylation R S RP ATP ADP H2OH2O PiPi k1k1 k2k2 response (RP) signal (S) sigmoidal phosphorylation dephosphorylation R 0 1 rate (dRP/dt) RP dephospho- rylation phospho- rylation ‘Buzzer’ zero order ultrasensitivity Goldbeter & Koshland, 1981 Signal-response curve graded and reversible

Multiple phosphorylation RRP RP 2 RP n …… kpkp kpkp for n=2 where K=k/p

n=2 R RP 2 K=k/p n=3 R RP 3 K=k/p n=4 R RP 4 K=k/p Hill equation: Multiple phosphorylation

Coupling of modules

Perfect adaptation S X R time adapted R S X k1k1 k2k2 k3k3 k4k4 Two linear modules R rate (dR/dt) synthesis degradation Response is independent of Signal

Feed-forward loop S R X S R X R increases for S increase R decreases for S decrease R decreases for S increase R increases for S decrease

Feed-forward loop with two buzzers X XAXA RARA R + + S RARA S XAXA Cock and fire

R’R S k1k1 k2k2 k3k3 k0k0 Another way to get perfect adaptation

R’R S k1k1 k2k2 k3k3 k0k0 The same principle, different deployment swimming (counter-clockwise) tumbling (clockwise) Bacterial chemotaxis

Feedback controls

response (R) signal (S) mutual activation R S EP E k1k1 k0k0 k2k2 k3k3 k4k4 R rate (dR/dt) synthesis degradation Linear module & buzzer Protein synthesis: positive feedback ‘Fuse’ response (R) signal (S) S crit2 S crit1 ‘Toggle’ switch bistability closed open

Example: Fuse response (R) signal (S) dying Apoptosis (Programmed Cell Death) living

The lac operon (‘toggle’ switch) S (extracellular lactose) R S EP E k1k1 k0k0 k2k2 k3k3 k4k4 R (intracellular lactose) EP

Nature 427, (19 February 2004) Multistability in the lactose utilization network of Escherichia coli ERTUGRUL M. OZBUDAK 1,*, MUKUND THATTAI 1,*, HAN N. LIM 1, BORIS I. SHRAIMAN 2 & ALEXANDER VAN OUDENAARDEN 1 Initially uninduced cells grown for 20 hrs in 18  M TMG Initially uninduced cells (lower panel) and induced cells (upper panel) grown in media containing different concentration of TMG TMG = thio-methylgalactoside

‘Death control’ for proteins d [protein] dt = synthesis - degradation  proteasome degraded protein ubiquitilation system

response (R) signal (S) mutual inhibition Linear module & buzzer R S EP E k1k1 k0k0 k2k2 k3k3 k4k4 k2'k2' Protein degradation: mutual inhibition R rate (dR/dt) synthesis degradation

Oscillators: three modules

X R PhasePlane response (R) signal (S) S crit1 S crit2 Positive and negative feedback oscillations (activator-inhibitor) R S EP E X k0k0 k1k1 k2k2 k2'k2' k3k3 k4k4 k5k5 k6k6

p53 Mdm2 p53-CFP and Mdm2-YFP levels in the nucleus after  -irradiation Period of oscillation: 440  100 min

X R response (R) signal (S) S crit1 S crit2 R S EP E X k1k1 k2k2 k3k3 k4k4 k0'k0' k0k0 Positive and negative feedback oscillations (substrate depletion)

Negative feedback and oscillation S X Y YP R RP (1) k0k0 k1k1 k2k2 (2) k2'k2' k3k3 k4k4 k5k5 k6k6 time X YP RP response (RP) signal (S) S crit2 S crit1

R S E EP Negative feedback and homeostasis k0k0 k3k3 k4k4 k2k2 signal (S) homeostatic response (R) rate (dR/dt) R production removal

Typical biosynthetic pathway protein demand aminoacid