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Effects of substrate topography on actin dynamics and B c ell receptor clustering

REU program sponsored by the National Science Foundation Award Number: PHY1156454. Effects of substrate topography on actin dynamics and B c ell receptor clustering. Jacob Fondriest , Christina Ketchum, Arpita Upadhyaya. TREND 2013 Training and Research Experience in Nonlinear Dynamics.

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Effects of substrate topography on actin dynamics and B c ell receptor clustering

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  1. REU program sponsored by the National Science Foundation Award Number: PHY1156454 Effects of substrate topography on actin dynamics and B cell receptor clustering Jacob Fondriest, Christina Ketchum, ArpitaUpadhyaya TREND 2013 Training and Research Experience in Nonlinear Dynamics

  2. Actin and B lymphocyte Behavior • B cells circulate through the body in search of infection. • Upon contact with a certain antigen, the B cell spreads to contact more antigen. • Over time, the B Cell Receptors (BCR) that contact the antigen begin to form clusters. • Actin plays a role in almost every cell operation, and has been shown to be linked to BCR clustering. BCR clusters

  3. Motivation • How does substrate topography affect actin dynamics and BCR movement? • What is the relationship between the movements of the actin cytoskeleton and the movements of BCR clusters? • Dr. Fourkas and Xiaovu Sun, from the University of Maryland, provide nanopatternsubstrates which simulate the topography of antigen presenting cells. W Y X

  4. Experimental Methods • We use B cells from mice, genetically modified with GFP and labeled with mbFab AF546. • We use Total internal reflection fluorescence (TIRF) microscopy and to record videos of B Cell actin and BCR dynamics on the nanopattern substrates. 3 µm Actin BCR Brightfield Overlay

  5. Particle Image Velocimetry analysis using MATLAB On Ridge • Track actin and BCR as they move. • PIVlab creates a vector field for every frame of the video. • Measure average velocity and net flow rates and directions • Specify Regions of Interest for analysis Between Ridges 3 µm 3 µm PIVlab - Time-Resolved Digital Particle Image Velocimetry Tool for MATLAB Developed by Dipl. Biol. William Thielicke and Prof. Dr. Eize J. Stamhuis

  6. Direction of Flow with respect to ridges Actin B Cell Receptors • The direction of actin and BCR flow is mostly chaotic, but slightly favors movement along the ridges.

  7. Resultant displacement over time Actin BCR Time Lapsed: 5 Minutes • Over a longer period of time, the chaotic drift reveals much more clear paths. • If we put particles in the center of the cell, these are the paths they might take.

  8. Role of ridge spacing on actin velocity dynamics 3 µm ridges 5 µm ridges Comparison by using a student’s T-Test reveals significant evidence that on 3 µm ridges, actin moves more quickly between the ridges than on the ridges. The actin is unaffected on 5 µm ridges. On ridges On ridges Between ridges Between ridges

  9. Actin and BCR line intensity profile comparison Time Lapsed: 15 seconds • Actin and BCR clusters tend to aggregate near ridges, resulting in greater intensity values at those areas. • Even between ridges there is definitive colocalization of actin and BCR. • Intensity charts confirm B cell receptors tend to form clusters, whereas actin is more evenly distributed throughout the cell. 3 µm 3 µm • Actin and BCR clusters tend to aggregate near ridges, resulting in greater intensity values at those areas. • Even between ridges there is apparent colocalizationof actin and BCR.

  10. Future Work • Investigate the effects of more narrow nanopatterns on the dynamics of actin and BCR clusters. Our research suggests narrower gaps will have more profound effects on actin and BCR dynamics. • Study the effect of nanotopography on B cell activation. • Perturbation experiments to examine the role of various cytoskeletal components (e.g. actin and myosin) on cell responses to nanotopography. • Improve Matlab software to streamline analysis and improve accuracy

  11. Acknowledgements • Christina Ketchum • Dr. ArpitaUpadhyaya • Ming Zhang • MikheilAzatov • Dr. John Fourkas and XiaoyuSun (Fourkas Lab) • TREND Program • NSF

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