Light controlled motility in E.coli bacteria: from individual response to population dynamics

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1 Light controlled motility in E.coli bacteria: from individual response to population dynamics Ph.D. Candidate: Supervisor: GIACOMO FRANGIPANE Dr. ROBERTO DI LEONARDO

2 Escherichia Coli A model organism for biological studies: a bacterium commonly found in our gut P. Siuti, J. Yazbek, and T. K. Lu, Synthetic circuits integrating logic and memory in living cells, Nature Biotechnology (2013)

3 Escherichia Coli POPULATION BEHAVIORS Colony growth, biofilm formation and collective behavior l ~ 2 μm v ~ 20 μm/s HYDRODYNAMICS A rod shaped self-propelling bacteria that swims to explore a world of low Reynolds numbers thanks to its flagellar motor

4 Motility: run and-tumble TWO STATE MODEL All flagella spin CCW -> RUN : cell moves on straight lines One or more flagella spin CW -> TUMBLE : cell reorients randomly Darnton et al. Journal of Bacteriology, 2007

5 From: Individual temporal response Impulse stimuli Coli is able to sense external temporal signals and tune its motility. This property enables it to move toward a desired environment or to flee from harmful environment CHEMOTAXIS Step stimuli λ t = λ 0 [1 LINEAR MODEL t R t t c x t, t dt ] TUMBLING RATE 1 τ run RESPONSE CONCENTRATION Segall et al. PNAS, 1986

6 To: Population stationary spatial distribution NON-EQUILIBRIUM STATISTICAL MECHANICS R t ρ x Clark and Grant. PNAS, 2005 Kafri et al. PRL, 2008 Photograph by J.S. Parkinson Lab

7 Light and phototaxis Many organisms can sense light signals direct their motion toward to light (e.g. algae) E. coli presents a weak photo-repulsive response Can we enhance this effect? Illustration by L. Zong & Y. Liang 1. Mutant strain with mutations in heme biosynthesis pathway 1 2. Introduce a plasmid codifying for a chimeric receptor that links blue light to the chemotaxis machinery 2 1 Yang et al. PNAS, Jung et al. Journal of Bacteriology, 2010

8 Setup Digital Micromirror Device

9 Trajectories analysis Necessity of a solid tracking algorithm to analyse trajectories so to obtain data on quantities of interest including distribution of swimming speeds, various measures of trajectory curvature, turning angles, the frequency of reorientations Tracked cell positions (r 0,, r T ) Displacement vectors d t = r t+1 r t Framewise speeds s t = d t / t Framewise angle θ t [ π, π] It is necessary to segment observed tracks into swimming and reorientation phases to extract useful statistics. A tumble is identified when the bacteria slows under a threshold proportional to its mean velocity

10 Tracking E. coli trajectories We developed a tracking algorithm in python taking advantage of OpenCV libraries for image analysis

11 Effect of blue light on trajectories BLUE OFF BLUE ON

12 Measuring change in bias and velocity to a step blue light stimulus B cw = CW CW + CCW

13 Relative increment in function of blue light intensity The intensity of the effect seems to has a linear relation with the amplitude of the step gradient.

14 Summary Study of phototactic E. coli Measure individual response function Measure stationary distribution in light pattern arbitrary distributed in time and space Theoretical model to connect individual response function to stationary distribution that can be directly verified against measurement (previously unavailable)

15 Applications Di Leonardo et al. PNAS, 2010 Koumakis et al. Nature Communications, 2013

16 Thanks for your attention