L17. Robustness in bacterial chemotaxis response BME 265-05. March 22, 2005 L17. Robustness in bacterial chemotaxis response Lingchong You

Homework 1&2 graded; pick in office during office hours No class March 24th. Instead, attend one or both of the following: March 23, 3:00pm, 130 North Bldg, Richard Watanabe: “Integrating Compartmental Models and Genetics to Understand Glucose Tolerance” March 24, 10am, CIEMAS auditorium B, Pak Kin Wong: “One In a Million” Bio-Nano- and Information Technologies for Controlling Complex Biological Systems

Groups & topics presentation order Name email: @duke.edu Project topics 2 Blais, Pierre Emmanuel peb5 Stochastic simulation of bistability 5 Chaudhry, Rajeev rc16 circadian rhythms (with Ramlingam) 6 Chu, Edward William ewc4 circadian rhythms (with peter)? 3 Donahoe, Casey D cdd4 circadian rhythms (with Prangkio) 4 Hanson, Megan mmh13 viral infection 8 Koreishi, Anjum Faruk afk cell cycle 7 Lee, Jiwon jl54 cell-cell communication 1 Leung, Alan Tsun Lim atl6 circadian rhythms 10 Novick, Paul Andrew pan3 Prangkio, Panchika pp9 circadian rhythms (with Donahoe) Ramalingam, Sundhar sr20 circadian rhythms (with Chaudhry) 9 Polikov, Vadim vsp cytokines

Project assistance Week of 4/4-4/9; Each group must make ½ hr appointment with me to discuss your project progress. Week of 4/12-4/15; No class. Optional appointments with me to assist with your projects

Tentative final presentation schedule (25 min/group, including Q&A) Dates may change; you need to attend all presentations: 4/19: groups 1, 2, 3 4/21: 4, 5, 6 4/26: 7, 8, 9, 10 Project report due by 5/1 (both electronic & paper copies)

Brief review: network architecture  system property - Negative feedback (no time delay) Homeostasis + Positive feedback Switch, bistability When we examine network dynamics, there are two aspects involved. On one hand, we may have the knowledge of the underlying network. In this case, we can ask what the possible output from the network can be generated. Here are some elementary examples. If we have negative feedback, we can potentially generate a stable output (homeostasis) or oscillations, depending on whether there is time delay involved. If we have a positive feedback, we can then potentially generate switching behavior caused by bistability. On the other hand, if we observe some system property, we can then guess what the underlying network structure maybe. In some cases, we know there are only a small number of network structures that can generate rate a certain behavior. For example, if we observe bistability, we know there must be a positive feedback involved. This perspective is useful, because it gives a new way of generating hypothesis, suggesting mechanisms or interactions to look for. - Negative feedback (+ long time delay) Oscillations

Oscillator based on negative feedback only Oscillator based on activator-inhibitor architecture

Robustness by communication Coordination Large numbers

Prototype: a population control circuit extinction No cell-cell variations AHL ? R R I survival luxR luxI ccdB With cell-cell variations PluxI CcdB You et al, Nature (2004)

Typical simulation results

Typical dynamics in Top10F’ (pH=7; 34C) OFF Typical dynamics in Top10F’ (pH=7; 34C) ON Population behavior Stable regulation Damped oscillations Captured by model Mutants arose after ~100 hrs ON OFF

Long term monitoring of circuit dynamics Balaggade, You et al. 2005, submitted

Robustness in bacterial chemotaxis Fluorescent flagellar filaments of E. coli.

Random walk by E. coli Berg, Physics Today, “Motile behavior of bacteria” (http://www.aip.org/pt/jan00/berg.htm)

Clockwise Counter-clockwise Run Tumble

Attractant (e.g. nutrient) Repellent (e.g. toxin) Chemotaxis: reduction in tumbling frequency to drive swimming toward attractant

Input regulation Output

Perfect Adaptation in Bacterial Chemotaxis Signaling Segall, J. E., Block, S. M. & Berg, H. E. Temporal comparisons in bacterial chemotaxis. Proc. Natl. Acad. Sci. USA 83, 8987-8991 (1986). Adaptation precision = Yss Y0 + Asp

What’s the basis for perfect adaptation? Two explanations: The kinetic parameters are fine-tuned. E. g.: Spiro et al. A model of excitation and adaptation in bacterial chemotaxis. PNAS, 1997 Perfect adaptation is a robust property of the underlying network. Barkai & Leibler 1997, Nature (Modeling) Alon et al 1999, Nature (Experiment)

McAdams, et al 2004. Nat. Rev. Genetics

More simplified view R: CheR W: CheW A: CheA B: CheB Y: CheY Y-p: phosphorylated CheY Alon et al 1999. Nature

A two-state model Key reactions: Binding and unbinding of the receptor complex to ligand Methylation and demethylation of the complex Each receptor complex may have several methylation sites Phosphorylation and dephosphorylation of B System activity (output): number of receptors in active form (different methylation states and occupancy of ligands affect the activity of each receptor state) Barkai & Leibler 1997 Nature

Key assumptions Input = ligand. Ligand binding and unbinding happens at the fastest time scale. Binding affinity is independent of receptor’s activity and its degree of methylation. CheB only demethylates phosphorylated receptors. CheR works at saturating level, or methylation of receptors follows a constant rate. Demethylation is independent of ligand binding

Perfect adaptation: Always returns to the same steady state Barkai & Leibler 1997, Nature

Adaptation precision robust to perturbations

Adaptation time NOT robust

Experiment: perfect adaptation No stimulation Stimulated by attractant (1mM L-aspartate)

Experimental measurements Perfect adaptation (Robust) Highly variable adaptation time & s.s. tumbling frequency Not robust

Changes in other parameters Not robust Robust Also: perfect adaptation precision highly variant steady state levels and adaptation time

Summary The adaptation precision of the E. coli chemotaxis network is highly robust to perturbations Other system properties (steady state level or the adaptation time) are not robust. In general, for many biological systems, only some system properties are robust to perturbations, but others are often sensitive

Why perfect adaptation Possible reason: Compensation for continued stimulation “Preparation” for responding to further stimuli Evidence: Cells deficient in adaptation are poor in chemotaxis even if their steady state tumbling is similar to wild type Cells capable of perfect adaptation are similar to WT in chemotaxis even if their steady state tumbling is quite different.

A highly simplified view of chemotaxis response Input Output Tyson et al. Current Opinion in Cell Biology 2003, 15:221–231