Summary: Jupyter notebook containing microscope automation code and supplementary tools (utils) used in Jason Town's 2023 PLOS Biology paper from Orion Weiner's lab at UC San Francisco: Local negative feedback of Rac activity at the leading edge underlies a pilot pseudopod-like program for amoeboid cell guidance.
Paper abstract: To migrate efficiently, neutrophils must polarize their cytoskeletal regulators along a single axis of motion. This polarization process is thought to be mediated through local positive feedback that amplifies leading edge signals and global negative feedback that enables sites of positive feedback to compete for dominance. Though this two-component model efficiently establishes cell polarity, it has potential limitations, including a tendency to “lock” onto a particular direction, limiting the ability of cells to reorient. We use spatially-defined optogenetic control of a leading edge organizer (PI3K) to probe how neutrophil-like HL-60 cells balance “decisiveness” needed to polarize in a single direction with the flexibility needed to respond to new cues. Underlying this balancing act is a local Rac inhibition process that destabilizes the leading edge to promote exploration. We show that this local inhibition enables cells to process input signal dynamics, linking front stability and orientation to local temporal increases in input signals.
Notes: We used Pycromanager in combination with live-image analysis to create simple feedback-driven assays to probe how cells responded to a particular chemical signal defined in space and time. Our light-delivery system consisted of an individually controllable LED and digital micromirror device (DMD). For our setup, we could control LED intensity via serial commands and we controlled mirror states in the DMD by saving a binary image to a defined file location on the microscope computer. This code was highly customized to our particular hardware, so it will not work as-is on other systems. That said, we hope this will serve as a useful example of how to use Pycromanager in combination with other tools for smart-microscopy projects.