7.81J/8.591J/9.531J Systems Biology Introducing ... Lectures: Recitations: TR 1:00 -2:30 PM W 4:00 - 5:00 PM Alexander van Oudenaarden Juan Pedraza Text books: none Handouts will be available on-line Good reference (biology textbook): Molecular biology of the cell Alberts et al. Matlab will be used intensively during the course, make sure you known (or learn) how to use it (necessary for problem sets) Intrinsic challenge of this class: mixed audience with wildly different backgrounds ? read up on your biology or math if needed ? recitations (W 4PM,) are intended to close the gaps and prepare for homework Systems Biology ? Systems Biology ≈ Network Biology GOAL: develop a quantitative understanding of the biological function of genetic and biochemical networks gene A gene C gene E gene B gene D gene F INPUT OUTPUT - function of gene product A-F can be known in detail but this is not sufficient to reveal the biological function of the INPUT-OUTPUT relation - a system approach (looking beyond one gene/protein) is necessary to reveal the biological function of this whole network - what is the function of the individual interactions (feedbacks and feedforwards) in the context of the entire network ? Three levels of complexity I Systems Microbiology (14 Lectures) ‘The cell as a well-stirred biochemical reactor’ II Systems Cell Biology (8 Lectures) ‘The cell as a compartmentalized system with concentration gradients’ III Systems Developmental Biology (3 Lectures) ‘The cell in a social context communicating with neighboring cells’ I Systems Microbiology (14 Lectures) ‘The cell as a well-stirred biochemical reactor’ L1 Introduction L2 Chemical kinetics, Equilibrium binding, cooperativity L3 Lambda phage L4 Stability analysis L5-6 Genetic switches L7 E. coli chemotaxis L8 Fine-tuned versus robust models L9 Receptor clustering L10-11 Stochastic chemical kinetics L12-13 Genetic oscillators L14 Circadian rhythms I Systems Microbiology (14 Lectures) ‘The cell as a well-stirred biochemical reactor’ L1 Introduction L2 Chemical kinetics, Equilibrium binding, cooperativity L3 Lambda phage L4 Stability analysis L5-6 Genetic switches L7 E. coli chemotaxis L8 Fine-tuned versus robust models L9 Receptor clustering L10-11 Stochastic chemical kinetics L12-13 Genetic oscillators L14 Circadian rhythms Introduction phage biology Phage genome: 48512 base pairs ~ 12 kB ‘phage.jpg’ ~ 10 kB Image removed due to copyright considerations. See Ptashne, Mark. A genetic switch: phage lambda. 3rd ed. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press, 2004. Image by MIT OCW. DNA DNA RNA Protein Nuclear Envelope Information Ribosome Protein TRANSLATION Protein Synthesis TRANSCRIPTION RNA Synthesis Cytoplasm Nucleus REPLICATION DNA Duplicates Information Information mRNA The central dogma defines three major groups of biomolecules (biopolymers): 1. DNA (passive library, 6×10 9 bp, 2 m/cell, 75×10 12 cells/human, total length 150×10 12 m/human ~ 1000 r sun-earth ) 2. RNA (‘passive’ intermediate) 3. Proteins (active work horses) The fourth (and final) group consists of so-called ‘small molecules’. 4. Small molecules (sugars, hormones, vitamines, ‘substrates’ etc.) The lysis-lysogeny decision: As the phage genome is injected phage genes are transcribed and translated by using the host’s machinery. Which set of phage proteins are expressed determines the fate of the phage: lysis or lysogeny Image by MIT OCW. The lysis-lysogeny decision is a genetic switch Image by MIT OCW. After Ptashne, Mark. A genetic switch : phage lambda. 3rd ed. Cold Spring Harbor, N.Y. : Cold Spring Harbor Laboratory Press, 2004. Single repressor dimer bound - three cases: I Negative control, dimer binding to OR2 inhibits RNAp binding to right P R promoter. Positive control, dimer binding to OR2 enhances RNAp binding to left P RM promoter. Image removed due to copyright considerations. See Ptashne, Mark. A genetic switch: phage lambda. 3rd ed. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press, 2004. II Negative control, dimer binding to OR1 inhibits RNAp binding to right P R promoter. Negative control, dimer binding to OR1 inhibits RNAp binding to left P RM promoter (too distant). Image removed due to copyright considerations. See Ptashne, Mark. A genetic switch: phage lambda. 3rd ed. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press, 2004. III Negative control, dimer binding to OR3 inhibits RNAp binding to left P RM promoter. Positive control, dimer binding to OR3 allows RNAp binding to right P R promoter. Image removed due to copyright considerations. See Ptashne, Mark. A genetic switch: phage lambda. 3rd ed. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press, 2004. Repressor-DNA binding is highly cooperative intrinsic association constants: K OR1 ~ 10 K OR2 ~ 10 K OR3 However K OR2 * >> K OR2 (positive cooperativity) Image removed due to copyright considerations. See Ptashne, Mark. A genetic switch: phage lambda. 3rd ed. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press, 2004. Flipping the switch by UV: Image removed due to copyright considerations. See Ptashne, Mark. A genetic switch: phage lambda. 3rd ed. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press, 2004. In lysogenic state, [repressor] is maintained at constant level by negative feedback Image by MIT OCW. UV radiation induces SOS response (DNA damage) protein RecA becomes specific protease for λ repressor Images removed due to copyright considerations. See Ptashne, Mark. A genetic switch : phage lambda. 3rd ed. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press, 2004. after cleavage monomers cannot dimerize anymore, [repressor dimers] decreases, when all repressors vacate DNA, Cro gene switches on. Image removed due to copyright considerations. See Ptashne, Mark. A genetic switch: phage lambda. 3rd ed. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press, 2004. Cooperative effects make sharp switch (‘well defined’ decision) Note: several layers of cooperativity: dimerization, cooperative repressor binding Images by MIT OCW. 1.0 0.8 0.6 0.4 0.2 0.0 0 1 2 3 4 5 (mM)[S] Y n H =1, non cooperative n H =3, positively cooperative 100 50 Repressor concentration % R e p r e s s i o n promoter controlled by a single repressor-operator system 99.7% repression lysogen lP D I Systems Microbiology (14 Lectures) ‘The cell as a well-stirred biochemical reactor’ L1 Introduction L2 Chemical kinetics, Equilibrium binding, cooperativity L3 Lambda phage L4 Stability analysis L5-6 Genetic switches L7 E. coli chemotaxis L8 Fine-tuned versus robust models L9 Receptor clustering L10-11 Stochastic chemical kinetics L12-13 Genetic oscillators L14 Circadian rhythms Images removed due to copyright considerations. The Flagellum Image removed due to copyright considerations. Absence of chemical attractant Image by MIT OCW. Tumble Run Presence of chemical attractant Image by MIT OCW. Tumble Chemical Gradient Sensed in a Temporal Manner Run Attractant Figure 1A in Mittal, N., E. O. Budrene, M. P. Brenner, and A. Van Oudenaarden. "Motility of Escherichia coli cells in clusters formed by chemotactic aggregation." Proc Natl Acad Sci U S A. 100, no. 23 ( Nov 11, 2003): 13259-63. Epub 2003 Nov 03. Copyright (2003) National Academy of Sciences, U. S. A. Chemotaxis of Escherichia coli Images removed due to copyright considerations. absence aspartate gradient random walk (diffusion) presence aspartate gradient biased random walk towards aspartate source Image by MIT OCW. After figure 4 in Falke, J. J., R. B. Bass, S. L. Butler, S. A. Chervitz, and M. A. Danielson. "The two-component signaling pathway of bacterial chemotaxis: a molecular view of signal transduction by receptors, kinases, and adaptation enzymes." Annu Rev Cell Dev Biol 13 (1997):457-512. Adaptation: Image by MIT OCW. 1 2 3 4 tumbling methylation add attractant Correlation of Receptor Methylation with Behavioral Response remove attractant add more attractant fast slow i n t e r m e d i a t e What is the simplest mathematical model that is consistent with the biology and reproduces the experiments ? Figures 2 in Spiro, P. A., J. S. Parkinson, and H. G. Othmer. "A model of excitation and adaptation in bacterial chemotaxis." Proc Natl Acad Sci U S A. 94, no. 14 (Jul 8, 1997): 7263-8. Copyright (1997) National Academy of Sciences, U. S. A. I Systems Microbiology (14 Lectures) ‘The cell as a well-stirred biochemical reactor’ L1 Introduction L2 Chemical kinetics, Equilibrium binding, cooperativity L3 Lambda phage L4 Stability analysis L5-6 Genetic switches L7 E. coli chemotaxis L8 Fine-tuned versus robust models L9 Receptor clustering L10-11 Stochastic chemical kinetics L12-13 Genetic oscillators L14 Circadian rhythms II Systems Cell Biology (8 Lectures) ‘The cell as a compartmentalized system with concentration gradients’ L15 Diffusion, Fick’s equations, boundary and initial conditions L16 Local excitation, global inhibition theory L17-18 Models for eukaryotic gradient sensing L19-20 Center finding algorithms L21-22 Modeling cytoskeleton dynamics II Systems Cell Biology (8 Lectures) ‘The cell as a compartmentalized system with concentration gradients’ L15 Diffusion, Fick’s equations, boundary and initial conditions L16 Local excitation, global inhibition theory L17-18 Models for eukaryotic gradient sensing L19-20 Center finding algorithms L21-22 Modeling cytoskeleton dynamics Eukaryotic Chemotaxis Image removed due to copyright considerations. How is this different from E. coli chemotaxis ? temporal versus spatial sensing cyclic AMP (cAMP) is an attractant for Dictyostelium (social amoeba) Image removed due to copyright considerations. Response of Dictyostelium to cAMP uniform step in cAMP cAMP gradient initial distribution t ~ 3 s steady-state distribution t ∞ uniform and transient polarized and persistent ¤ geometry of cell: circular inside cytoplasm: well-stirred inside membrane: diffusion-limited GFP-PH binds special lipids in membrane: PIP2 and PIP3 Image by MIT OCW. Chemoattractant Micropipette Cell Trailing edge Leading edge GFP-Protein q The molecules in the model: Image by MIT OCW. PI4P,5P 2 Plasma Membrane Endoplasmic Reticulum Receptor Regulated Step DG IP 3 Inositol PA CDP.DG CDP.DGS PIS DGK PI4K PITP Cytosol PLC PI4P5K + PI4P PI PIPA II Systems Cell Biology (8 Lectures) ‘The cell as a compartmentalized system with concentration gradients’ L15 Diffusion, Fick’s equations, boundary and initial conditions L16 Local excitation, global inhibition theory L17-18 Models for eukaryotic gradient sensing L19-20 Center finding algorithms L21-22 Modeling cytoskeleton dynamics how to find the middle of a cell ? Image removed due to copyright considerations. Most of MinE accumulates at the rim of this tube, in the shape of a ring (the E ring). The rim of the MinC/D tube and associated E ring move from a central position to the cell pole until both the tube and ring vanish. Meanwhile, a new MinC/D tube and associated E ring form in the opposite cell half, and the process repeats, resulting in a pole-to-pole oscillation cycle of the division inhibitor. A full cycle takes about 50 s. Image removed due to copyright considerations. Recent results demonstrate that the min proteins assemble in helices Image removed due to copyright considerations. II Systems Cell Biology (8 Lectures) ‘The cell as a compartmentalized system with concentration gradients’ L15 Diffusion, Fick’s equations, boundary and initial conditions L16 Local excitation, global inhibition theory L17-18 Models for eukaryotic gradient sensing L19-20 Center finding algorithms L21-22 Modeling cytoskeleton dynamics Center finding in an eukaryotic cell: fission yeast The importance of the cytoskeleton Image removed due to copyright considerations. III Systems Developmental Biology (3 Lectures) ‘The cell in a social context communicating with neighboring cells’ L23 Quorum sensing L24-25 Drosophila development III Systems Developmental Biology (3 Lectures) ‘The cell in a social context communicating with neighboring cells’ L23 Quorum sensing L24-25 Drosophila development major advantage of Drosphila: each stripe in the embryo corresponds to certain body parts in adult fly Image removed due to copyright considerations. interpreting the bicoid gradient (created by maternal effects) by zygotic effect (gene expression by embryo itself) Image removed due to copyright considerations. hunchback reads the bicoid gradient Image removed due to copyright considerations. Center finding in the Drosophila embryo Image removed due to copyright considerations. I Systems Microbiology (14 Lectures) ‘The cell as a well-stirred biochemical reactor’ L1 Introduction L2 Chemical kinetics, Equilibrium binding, cooperativity L3 Lambda phage L4 Stability analysis L5-6 Genetic switches L7 E. coli chemotaxis L8 Fine-tuned versus robust models L9 Receptor clustering L10-11 Stochastic chemical kinetics L12-13 Genetic oscillators L14 Circadian rhythms