Emmanuel Lorenzo de los Santos 20.309 Presentation October 10, 2008 The Frequency Dependence of Osmo-Adaptation in S. Cerevisiae (van Oudenaarden et al.) Emmanuel Lorenzo de los Santos 20.309 Presentation October 10, 2008

Outline Background and Motivation Description of the System Examined Experimentation Results: Modeling and Validation Impact of the Research

Current Methods Used for Systems Biology are Limited Understanding of biological systems is important for future engineering applications Many biochemical pathways are complex Big range in reaction times - <1s to >103 s Can involve hundreds of reactions Difficult to identify dominant processes Many models incorporate all reactions but this has problems

Solution: Propagation of oscillating signals through a cascade Varying frequencies of input can give us insight into system dynamics Frequency response time can provide new direction for research Dominant processes can be easily identified by comparing wt vs. mutant system dynamics

Hog1-MAPK in S. cerevisiae is an ideal test system for this approach High Osmolarity Glycerol (HOG) MAP Kinase cascade is involved in hyperosmotic response Easy to measure: Input: NaCl Concentration Output: Hog1 Response Well studied components – validation Negative feedback loops on different time scales (de Nadal et al., EMBO Reports 2002)

The Experiment Shock cells with square wave pulses of medium with and without 0.2 M NaCl (To=2min-128min) Two cells, wt and MAPKK deficient Measure Cell Response – Hog1 Activation (Mettetal et al. , Science 2008)

Measurement Tools Input – Known Output – use colocalization: Hog1-YFP Nrd1-RFP (localized in nucleus) Measure <YFP>nuc/ <YFP>cell Approximate Input and Output as sine waves: To= , ω0 is the driving frequency Perform Fourier analysis on output

Results: LTI-Nonlinear model predicts Amplitude and Decay Time No biological concepts involved yet! (Mettetal et al. , Science 2008)

LTI Model Compared to Standard Biological Model LTI-Nonlinear Model Translated into two State Mechanistic Model: Biological System: parallel mechanisms Fps1 – Hog1 independent Hog1 dependent Good fit but dynamics suggest incomplete model (Mettetal et al. , Science 2008)

System Dynamics suggests further experiments Response generally over in 15 minutes – too fast for gene expression based response Test cell recovery while inhibiting protein expression Response to initial pulse is similar Different response in later pulses Longer frequency components discovered through system dynamics analysis (Mettetal et al. , Science 2008)

Oscillation response is a valuable tool in analyzing biological systems Determine dominant interactions in complex biochemical pathways Information on system dynamics leads to better understanding of the system as opposed to other methods (e.g. microarrays) Can be used in many pathways

Non-Linear Part