Membrane Biology

In this theme, we will explore membrane dynamics through a combination of quantitative imaging techniques and computational modeling. In particular, we will focus on how the unique features of membranes (curvature, fluidity, etc…) affect signal transduction. We will review how quantitative imaging techniques (localization microscopy, single particle tracking, fluorescence correlation spectroscopy) can be capture spatiotemporal events on the membrane and inform the choice of computational methodology. This will motivate our discussion of the various computational techniques that can both replicate and predict important events in membrane dynamics. This section of the summer school will include a variety of projects. All students will learn the computational techniques necessary to extract spatial and temporal statistics from real quantitative imaging data. We will then use these techniques in combination with a variety of membrane dynamics models to create mathematical models of diffusion, ligand interactions, and other membrane dynamics of interest. Access and knowledge of Matlab will be helpful, but is not strictly necessary.

This section of the summer school is organized by Bridget Wilson and Douglas Shepherd. Please address all questions about this section of the summer school to its organizers.

Speakers

Lecturers

• Adam Halasz, West Virginia University
• Diane Lidke, University of New Mexico
• Keith Lidke, University of New Mexico
• John Pearson, Los Alamos National Laboratory
• Samantha Schwartz, University of New Mexico
• Douglas Shepherd, University of Colorado Denver
• Mara Steinkamp, University of New Mexico
• Lydia Tapia, University of New Mexico
• Jim Werner, Los Alamos National Laboratory
• Michael Wester, University of New Mexico
• Bridget Wilson, University of New Mexico

Project Mentors

• Adam Halasz, West Virginia University
• Samantha Schwartz, University of New Mexico
• Douglas Shepherd, University of Colorado Denver
• Mara Steinkamp, University of New Mexico
• Michael Wester, University of New Mexico
• Bridget Wilson, University of New Mexico

Topics

• Membrane architecture and dynamics
• Single-cell and single-molecule experiments
• Mechanisms of membrane curvature and fusion/fission
• Spatiotemporal control of signal initiation
• Simulation of membrane bi-layers
• Special experimental techniques
• Geometry and signal amplification of immune cell membrane contacts
• Collection and analysis of single-particle tracking data
• Collection and analysis of super-resolution imaging data
• Using BioNetGen/MCell to simulate reaction diffusion dynamics.
• Stochastic simulations of membrane diffusion
• Using Smoldyn to simulate reaction-diffusion dynamics
• Ion Transport
• Membrane scaffolds for spatial control and signal amplification

Microscope Schedule

• These sessions will take place from 5-7PM during the first week of the school. Directions to the laboratory spaces will be provided via email.
• Super-resolution microscopy
  • Tuesday, July 29th 5-7PM: James Pino, Wenzhe Ma
  • Thursday, July 31st 5-7PM: Emine Guven, Bruna Jacobson, Leili Shahriyari
• Single-particle tracking
  • Tuesday, July 29th 5-7PM: Lu Xiao, Eshan Mitra
  • Thursday, July 31st 5-7PM: Katie Goodwin, Hoong Chuin Lim

Journal Club

• "Single-Molecule Microscopy Reveals Plasma Membrane Microdomains Created by Protein-Protein Networks that Exclude or Trap Signaling Molecules in T Cells", Adam D. Douglass & Ronald D. Vale, Cell 121(6) 2005 [html] [pdf]
• "In vitro membrane reconstitution of the T-cell receptor proximal signaling network", Enfu Hui & Ronald D Vale, Nature Structural & Molecular Biology 21 (2) 2014 [html] [pdf]
• "Objective comparison of particle tracking methods", Nicolas Chenouard et al., Nature Methods 11, 281–289 (2014) [html][pdf]

Software

• Simulation software
  • RuleBender
  • BioNetGen
  • MCell For further info see MCell at q-bio Summer School 2014.
  • Blender
  • CellBlender
  • NFsim
  • PySB

• Data analysis software
  • SuperCluster
  • DERIVEST suite (required by Supercluster)
  • Matlab (required by SuperCluster)
  • Matlab Image Processing Toolbox (required by SuperCluster)
  • Matlab Statistics Toolbox (required by SuperCluster)
  • TeamViewer (required to remotely connect to SPT data analysis computers)
  • MSD-Bayes (optional Bayesian SPT data analysis software)
  • vbSPT (optional Bayesian SPT data analysis software)
  • dipimage (free image processing package for both Matlab and C)