BE 150/Bi 250 Spring 2014

Systems Biology
Instructors Michael Elowitz (Bi/BE/APh) Richard Murray (CDS/BE) Lectures: MWF 11-12, 200 BRD	Teaching Assistants Victoria Hsiao (BE) Vipul Singhal (CNS) Recitation: Fr 11-12, location ANN107
This is the course homepage for BE 150/Bi 250 for Spring 2014. This page contains all of the information about the material that will be covered in the class, as well as links to the homeworks and information about the course projects and grading. There is also a forum for students to ask questions, and can be accessed here. You will need to create a Piazza account to enroll.

Lecture Schedule

There will be 2-3 one-hour lectures each week, as well as occasional one-hour tutorials, recitations or journal club.

Week	Date	Topic	Reading	Homework
1	31 Mar 2 Apr MBE/RMM	Course overview, gene circuit dynamics Introduction to the course Rate equations enable analysis of gene regulation circuits Degradation rates control response times in simple open-loop gene regulation Autoregulatory feedback loops modulate the response times of genetic circuits, limit variability, and can enable rate-responsive systems Cooperative responses can enable switch-like regulation and bistability Circuit motifs can help identify functional modules in complex circuits Recitation section: 4 Apr MATLAB and SimBiology Tutorial Useful MATLAB commands: useful_matlab.m SimBiology example: Simbiology Project File MATLAB/ode45 example: pos_reg_main.m and pos_reg.m Simbiology Tutorial	Bi 250b: Alon, Ch 1: Introduction Alon, Ch 2: Transcription networks : basic concepts Alon, Ch 3: Autoregulation : a network motif BE 150: BFS Ch 1: Introductory Concepts (skim) BFS Ch 2: Modeling of Core Processes Section 2.1: Modeling Techniques (skim) Sections 2.2-2.3: transcription and translation, transcriptional regulation	HW1 pplane8 (Needed for Problem 2)
2	7 Apr 9 Apr+ MBE	Circuit motifs Feed-forward loops enable temporal filtering and pulse generation ‘Futile cycles’ generate zero-order ultrasensitivity (phospho-switches) Multi-gene positive feedback loops can enable toggle switch behaviors Positive feedback can generate hysteresis and irreversibility - example: Xenopus oocyte maturation Paradoxical regulation by cytokines could enable regulation of a population response Recitation (11 Apr): sample problems MATLAB/curve fitting tool example: cftools_example.m	Bi 250b: Alon, Ch 4: The feed-forward loop network motif Alon, Ch 6: Network motifs in developmental, signal transduction, and neuronal networks BE 150: BFS Ch 2: Modeling of Core Processes Section 2.4: post-transcriptional regulation Section 2.5: cellular subsystems Papers discussed in lecture: Protein sequestration generates a flexible ultrasensitive response in a genetic network, N. E. Buchler and F. R. Cross. Molecular Systems Biology, 5:272, 2009. Quantitative Characteristics of Gene Regulation by Small RNA Levine et al. "PLOS Biology" 2007	HW2 I1FFL.sbproj
3	14 Apr+ 16 Apr+ MBE	Robustness Critical features of genetic circuits may be robust to variation in their own components, and the principle of robustness can be used to select identify likely circuit architectures: In the bacterial chemotaxis circuit, perfect adaptation is robust to fluctuations in key cellular components Bifunctional kinases can generate ideal linear amplifiers with robustness to component concentrations Cosubstrate compensation provides oxygen homeostasis across a broad range of oxygen levels (Kueh)	Alon, Ch 7: Robustness of protein circuits : the example of bacterial chemotaxis BE 150: BFS Ch 2: Sec 2.4: Post-transcriptional regulation BFS Ch 3: Sec 3.2 (Robustness) BFS Sec 5.2: Bacterial chemotaxis Papers discussed in lecture: Maintenance of Mitochondrial Oxygen Homeostasis by Cosubstrate Compensation, Kueh HY, Niethammer P., Mitchison TJ. Biophys J, 104 (6) 1338-1348 2013.	HW3
4	21 Apr 23 Apr+ MBE	Guest lecture: Joe Markson Clock-like oscillations can be implemented in cells: Delayed negative feedback can enable clock-like oscillations in individual cells (Repressilator) Combined positive/negative feedback enables relaxation oscillation whose period and amplitude can be tuned independently A simple three-protein system can generate accurate clock-like oscillations of phosphorylation state April 25: Course Project Assignments	BE 150: BFS Ch 3: Analysis of Dynamic Behavior Sections 3.5: Oscillatory Behavior Papers discussed in lecture: Robust, Tunable Biological Oscillations from Interlinked Positive and Negative Feedback Loops, Tsai, Choi, Ma, Pomerening, Tang and Ferrell. Science Signaling, 321(5885): 126, 2008 A synthetic oscillatory network of transcriptional regulators, Elowitz and Leibler. Nature, 403:335-338, 2000. A fast, robust and tunable synthetic gene oscillator, Stricker, et al.. Nature, 456:516-519, 2008. Circadian control of global gene expression by the cyanobacterial master regulator RpaA, Markson JS, et al. Cell, 2013 Dec 5;155(6):1396-408. Ordered phosphorylation governs oscillation of a three-protein circadian clock. Rust et al. Science, 318(5851), 809–812. 2007. The molecular clockwork of a protein-based circadian oscillator. Markson, J. S., & O'Shea, E. K. (2009). FEBS Letters, 583(24), 3938–3947.	HW4 dde.m
5	28 Apr 30 Apr RMM	Stochasticity, or ‘noise’ is ubiquitous in genetic circuits: Intrinsic noise (stochasticity) in gene expression limits the accuracy of gene regulation Variability can be controlled by altering burst parameters	Stochastic Gene Expression in a Single Cell, Michael B. Elowitz, Arnold J. Levine, Eric D. Siggia and Peter S. Swain. Science, 297(5584):1183-1186, 2002. Stochastic protein expression in individual cells at the single molecule level, Long Cai, Nir Friedman and X. Sunney Xie. Nature, 440:358-362, 2006. Regulatory Activity Revealed by Dynamic Correlations in Gene Expression Noise Mary J. Dunlop, Robert Sidney Cox, Joseph H. Levine, Richard M. Murray, and Michael B. Elowitz. Nat Genet. Dec 2008; 40(12): 1493–1498. BE 150: BFS Ch 4: Stochastic behavior App B: Probability and random processes (optional)	HW5
6	5 May 7 May* RMM	Patterning Self-enhanced degradation makes morphogen gradients robust to variation in morphogen production rates. Shuttling mechanisms enable morphogen-based patterning systems to scale with tissue size.	Alon, Ch 8: Robust Patterning in Development Robustness of the BMP morphogen gradient in Drosophila embryonic patterning, Eldar et al. Nature 419, 304-308 (19 September 2002) Self-Enhanced Ligand Degradation Underlies Robustness of Morphogen Gradients, Avigdor Eldar, Dalia Rosin, Ben-Zion Shilo, and Naama Barkai. Developmental Cell, Vol. 5, 635–646, October, 2003 Scaling of morphogen gradients by an expansion-repression integral feedback control, Danny Ben-Zvia and Naama Barkai. PNAS, 107(15):6924-6929, 2010.
	9 May	Course project discussion with TAs
7	12 May 14 May RMM	Engineered circuits Current approaches for analysis and design of engineered biocircuits + limitations Tools for analyzing/designing biocircuits to predict limiting effects	BFS Ch 3: Sec 3.2 (sensitivity analysis) BFS Ch 5: Biological Circuit Components BFS Ch 6: Interconnecting Components BFS Ch 7: Design Tradeoffs	HW6
8	19 May 21 May MBE	Stochastic pulsing provides multiple functions in cells, similar to the role of oscillatory signals in engineering Frequency modulation coordinates the responses of diverse genetic targets (example: yeast stress response) Excitability is a noise-dependent mechanism that enables probabilistic control of transient, stereotyped differentiation events Pulsing can enable dynamic multiplexing (example: p53)	Development of Genetic Circuitry Exhibiting Toggle Switch or Oscillatory Behavior in Escherichia coli, Mariette R. Atkinson et al. Cell, Volume 113, Issue 5, 30 May 2003, Pages 597–607 Frequency-modulated nuclear localization bursts coordinate gene regulation, Long Cai, Chiraj K. Dalal and Michael B. Elowitz. Nature 455:485-490, 2008. Antibiotic interactions that select against resistance., Remy Chait et al. Nature, 2007 Apr 5;446(7136):668-71. Modular epistasis in yeast metabolism., Daniel Segrè et al. Nature Genetics, 37, 77 - 83 (2004) .
9	29 May 30 May 2 Jun	Project presentations

Course Description

BE 150/Bi 250b is a jointly taught class that shares lectures but has different reading material and homework assignments. Students in BE 150 are expected to have a more quantitative background and the course material includes a combination of analytical and conceptual tools. Students in Bi 250b are expected to have more knowledge of basic biological processes and the course material focuses on the principles and tools for understanding biological processes and systems.

BE 150: Quantitative studies of cellular and developmental systems in biology, including the architecture of specific genetic circuits controlling microbial behaviors and multicellular development in model organisms. Specific topics include chemotaxis, multistability and differentiation, biological oscillations, stochastic effects in circuit operation, as well as higher-level circuit properties such as robustness. Organization of transcriptional and protein-protein interaction networks at the genomic scale. Topics are approached from experimental, theoretical and computational perspectives.

Bi 250b: The class will focus on quantitative studies of cellular and developmental systems in biology. It will examine the architecture of specific genetic circuits controlling microbial behaviors and multicellular development in model organisms. The course will approach most topics from both experimental and theoretical/computational perspectives. Specific topics include chemotaxis, multistability and differentiation, biological oscillations, stochastic effects in circuit operation, as well as higher-level circuit properties such as robustness. The course will also consider the organization of transcriptional and protein-protein interaction networks at the genomic scale.

Textbook

The primary text for the BE 150 and Bi 250b is

[Alon]

U. Alon, An Introduction to Systems Biology: Design Principles of Biological Circuits, CRC Press, 2006.

Students in BE 150 should also obtain the following notes (freely downloadable from the web):

[BFS]

D. Del Vecchio and R. M. Murray, Biomolecular Feedback Systems (available online) Note: these notes are being written and will be updated during the course The public version is missing some copyrighted figures. These are available in the class version. Class version (Caltech access only, 5 Jan 2013): TOC, Ch 1, Ch 2, Ch 3, Ch 4, Sec 5.2, App B, Refs

The following additional texts and notes may be useful for some students:

[Klipp]	Edda Klipp, Wolfram Liebermeister, Christoph Wierling, Axel Kowald, Hans Lehrach, Ralf Herwig, Systems biology: A textbook. Wiley, 2009.
[Strogatz]	Steven Strogatz, Nonlinear Dynamics And Chaos: With Applications To Physics, Biology, Chemistry, And Engineering. Westview Press, 2001.

Course project

All students enrolled in the course will be expected to participate in a course project, which will be assigned after the fourth week of class. Course projects will generally consist of reviewing one or more papers on a topic that makes use principles and tools discussed in the course. Each project will be undertaking by two students (nominally one from BE 150, one from Bi 250). Topic suggestions are posted here. Students can also propose their own topic of student by preparing a 1-2 page proposal and submitting this to the instructors no later than 4 Feb for consideration.

Course project timeline:

• 1 Feb (Fri): course projects posted on home page and announced in class
• 4 Feb (Mon): course project preferences due
• 6 Feb (Wed): project assignments available
• 20 Feb (Wed): discussion of course projects with TAs and others
• 4-13 Mar: course project presentations. 15-20 minutes per project + 5-10 minutes questions.

Course preference instructions

• Each student should send e-mail no later than 4 Feb (Mon) with the following information
  • Course: (BE 150/Bi 250b/Audit)
  • Up to three project preferences (use titles from project listings)
  • Optional preferred partner (both students should e-mail identical preferences)
• Students will work in pairs, with most teams consisting of a BE 150 student and a Bi 250b student
• To propose your own project, please e-mail a 1-2 page proposal in addition to at least two project preferences selected from the list of course projects

Grading

The final grade will be based on biweekly homework sets (75%) and a course project (25%). The homework will be due in class approximately one week after they are assigned. Late homework will not be accepted without prior permission from the instructor. The lowest homework score you receive will be dropped in computing your homework average. The class project will be assigned and the end of the 5th week of instruction and project presentations will be scheduled for the last two weeks of class.

Collaboration Policy

Collaboration on homework assignments and the course project is encouraged. You may consult outside reference materials, other students, the TA, or the instructor. Use of solutions from previous years in the course is not allowed. All solutions that are handed in should reflect your understanding of the subject matter at the time of writing. Your course project presentation to properly acknowledge all source materials.