Signal Processing in Single Cells Tony 03/30/2005.

Slides:



Advertisements
Similar presentations
What is life ? 1. How can biological order (life) be explaind by the basic laws of physics? 2. How does life deal with the statistic nature of molecular.
Advertisements

Non-Markovian dynamics of small genetic circuits Lev Tsimring Institute for Nonlinear Science University of California, San Diego Le Houches, 9-20 April,
Phenotypic variations in a monoclonal bacterial population
Modelling and Identification of dynamical gene interactions Ronald Westra, Ralf Peeters Systems Theory Group Department of Mathematics Maastricht University.
Simulation of Prokaryotic Genetic Circuits Jonny Wells and Jimmy Bai.
Stochastic Analysis of Bi-stability in Mixed Feedback Loops Yishai Shimoni, Hebrew University CCS Open Day Sep 18 th 2008.
Programmed population control by cell-cell communication and regulated killing Lingchong You, Robert Sidney Cox III, Ron Weiss & Frances H. Arnold Programmed.
N OISE P ROPAGATION IN G ENE N ETWORKS Juan M. Pedraza and Alexander van Oudenaarden 1 VC Lab, Dept. of Computer Science, NTHU, Taiwan.
Systems Biology Biological Sequence Analysis
Gene expression analysis summary Where are we now?
Deterministic and Stochastic Analysis of Simple Genetic Networks Adiel Loinger MS.c Thesis of under the supervision of Ofer Biham.
Noise and Bistability 12/10/07. Noisy gene expression at single cell level Elowitz 2002.
Systems Biology Biological Sequence Analysis
Adiel Loinger Ofer Biham Nathalie Q. Balaban Azi Lipshtat
An Application of Bendixson-Boincare Theorem MAT 574- Fall 2003 Arizona State University Math & Stat Dept.
Systems Biology Ophelia Venturelli CS374 December 6, 2005.
Goal: Students will be able to explain how DNA was identified as the genetic material, describe the basic processes of replication, transcription, and.
Synthetic gene networks that count Lv ChenChen. A counter!! A counter is a key component in digital circuits and computing that retains memory of events.
Demetris Kennes. Contents Aims Method(The Model) Genetic Component Cellular Component Evolution Test and results Conclusion Questions?
Synthetic Mammalian Transgene Negative Autoregulation Harpreet Chawla April 2, 2015 Vinay Shimoga, Jacob White, Yi Li, Eduardo Sontag & Leonidas Bleris.
Regulatory factors 1) Gene copy number 2) Transcriptional control 2-1) Promoters 2-2) Terminators, attenuators and anti-terminators 2-3) Induction and.
Synthetic biology: New engineering rules for emerging discipline Andrianantoandro E; Basu S; Karig D K; Weiss R. Molecular Systems Biology 2006.
Stochastic simulations Application to molecular networks
Course Structure Exam Structure & Review ADVANCED PLACEMENT BIOLOGY.
Reconstruction of Transcriptional Regulatory Networks
Understanding cell state with quantitative live cell imaging Copyright © 2000 Cell Press. The Hallmarks of Cancer Douglas Hanahan and Robert A. Weinberg.
GTL User Facilities Facility IV: Analysis and Modeling of Cellular Systems Jim K. Fredrickson.
Computational biology of cancer cell pathways Modelling of cancer cell function and response to therapy.
Biophysics of Systems Dieter Braun Systems Biophysics Master Program Biophysics: studiengaenge/master_physik/ma_phys_bio/curriculum.html.
Robustness in protein circuits: adaptation in bacterial chemotaxis 1 Information in Biology 2008 Oren Shoval.
By Rosalind Allen Regulatory networks Biochemical noise.
1 Stochasticity and robustness Steve Andrews Brent lab, Basic Sciences Division, FHCRC Lecture 5 of Introduction to Biological Modeling Oct. 20, 2010.
 Scientific evidence shows that life on Earth had one origin or multiple origins?
Problem Limited number of experimental replications. Postgenomic data intrinsically noisy. Poor network reconstruction.
Single Cell Variability The contribution of noise to biological systems.
1 Noise in gene expression networks? Ramu Anandakrishnan March 14, 2006 Bla h.. Shut up guys! I can’t hear what DNA it telling me to do... Rosenfeld et.
The Value of Tools in Biology Smolke Lab talk
Steady-state Analysis of Gene Regulatory Networks via G-networks Intelligent Systems & Networks Group Dept. Electrical and Electronic Engineering Haseong.
A Genetic Differential Amplifier: Design, Simulation, Construction and Testing Seema Nagaraj and Stephen Davies University of Toronto Edward S. Rogers.
Complexities of Gene Expression Cells have regulated, complex systems –Not all genes are expressed in every cell –Many genes are not expressed all of.
Engineered Gene Circuits Jeff Hasty. How do we predict cellular behavior from the genome? Sequence data gives us the components, now how do we understand.
Miscellaneous… & iGEM Design V1.0 - Xiuye
Distribution of fluorescence values of cells w/ LacY::YFP Cells begin to show “all or nothing” behavior at about uM TMG. Fluorescence intensity.
Bioinformatics 3 V8 – Gene Regulation Fri, Nov 9, 2012.
Biophysics of Systems Dieter Braun Lecture + Seminar
Fan-out in Gene Regulatory Networks Kyung Hyuk Kim Senior Fellow Department of Bioengineering University of Washington, Seattle 2 nd International Workshop.
Network Motifs See some examples of motifs and their functionality Discuss a study that showed how a miRNA also can be integrated into motifs Today’s plan.
Noise and Variability in Gene Expression Presenting: Tal Ashuah Advisor: Dr. Alon Zaslaver 10/05/15.
Orkhon Tsogtbaatar, ID: April 18, 2012
Single-cell NF-κB dynamics reveal digital activation and analogue information processing Savas Tay, Jacob J. Hughey, Timothy K. Lee, Tomasz Lipniacki,
(3) Gene Expression Gene Expression (A) What is Gene Expression?
Noise Propagation in Gene Networks
The Value of Tools in Biology
Systems-level modeling of genetic circuits Gene A Protein A Protein B
Noise in cellular circuitry
The Persistence of Long-Term Memory
The Frequency Dependence of Osmo-Adaptation in Saccharomyces cerevisae
Genetic variation in DREs could be a causative factor in dysregulation of distal target gene expression. Genetic variation in DREs could be a causative.
Jan Philipp Junker, Alexander van Oudenaarden  Molecular Cell 
Noise Induces Hopping between NF-κB Entrainment Modes
What is life ? Schrödinger considered 1943 the consequences of the molecular nature of the genetic code in a lecture about „Physics and biology“ 1. How.
Corentin Briat, Ankit Gupta, Mustafa Khammash  Cell Systems 
Andreas Hilfinger, Thomas M. Norman, Johan Paulsson  Cell Systems 
Michał Komorowski, Jacek Miękisz, Michael P.H. Stumpf 
Circadian Clock: Time for a Phase Shift of Ideas?
Luigi Warren, David Bryder, Irving L. Weissman, and Stephen R. Quake
Arjun Raj, Alexander van Oudenaarden  Cell 
Emmanuel Lorenzo de los Santos Presentation October 10, 2008
Probing the Limits to Positional Information
On the Dependency of Cellular Protein Levels on mRNA Abundance
Presentation transcript:

Signal Processing in Single Cells Tony 03/30/2005

How signals are transmitted through gene cascades in noisy cellular environments? The Question

Work by Rosenfeld et al Gene Regulation Function (GRF) –The relation between the concentration of active transcription factors in a cell and the rate at which their downstream gene products are produced through transcription and translation. Three fundamental aspects of GRF to study: –Mean shape –Typical deviation from this mean –Time scale over which such fluctuations persist

Gene cascade

Experimental tricks Regulator dilution method Relative fluorescence intensity of individual protein molecules  apparent number of molecules per cell. Hill function

Mean shape

Fluctuations After normalizing production rates to the average cell- cycle phase, substantial variation still remains in the production rates, and their standard deviation is ~40% of the mean GRF. Intrinsic noise –Results from stochasticity in the biochemical reactions at an individual gene and would cause identical copies of the same gene to express at different levels. –~20% of the total noise Extrinsic noise –Originates from fluctuations in cellular components such as metabolites, ribosomes, and polymerases. –Contributes a variation in protein production rates of ~35%.

Time scales of the fluctuations

Conclusions Slow fluctuations give the genetic circuits memory, or individuality, lasting roughly one cell cycle. They present difficulty for modeling genetic circuits. There is thus a fundamental tradeoff between accuracy and speed in purely transcriptional responses. Accurate cellular responses on faster time scales are likely to require feedback from their output.

Work by Pedraza & Oudenaarden Expression correlations between genes in single cells were measured. A model was developed that explains the complex behavior exhibited by the correlations and reveals the dominant noise sources.

Gene cascade

Experimental results

Model

Langevin approach Noise terms: –Intrinsic noise at specific gene –Transmitted intrinsic noise from the upstream genes The Intrinsic noise for upstream gene The effect of temporal averaging The susceptibility of downstream gene to upstream gene (logarithmic gain) –Global noise modulated by the network The direct effect on the gene The transmitted effect from upstream genes The effect of the correlated transmission

Results Even in a network where all components have low intrinsic noise, fluctuations can be substantial and the distributions of expression levels depend on the interactions between genes.