Optical and analysis methods for measuring the organization, dynamics, and interactions of proteins in living cells.
The K.A. Lidke Laboratory works on the development and application of optical methods, principally fluorescence microscopy, for measuring the organization, dynamics, and interactions of proteins in living cells. We build the microscopes, estimation algorithms, and software needed to observe individual molecular events, and we apply them to questions in protein dynamics and cell signaling. The lab is affiliated with the UNM Comprehensive Cancer Center and the PAIS-MMC, a shared multiscale microscopy center directed by K. Lidke and used by research groups across campus.
Much of this work confronts a central obstacle: diffraction. Fluorophores spaced closer than about 250 nm blur together in a conventional microscope, yet the protein assemblies that organize signaling at the cell membrane are far smaller and constantly in motion. Our methods are built to recover what diffraction obscures at nanometer length scales: the positions of individual molecules, their trajectories, and the interactions between them.
The lab pursues two complementary approaches. In single-molecule localization super-resolution, fluorophores are switched on a few at a time and localized with nanometer-scale precision, so the resolution of the reconstructed image is set by that precision and by label density rather than by diffraction. In multicolor single-particle tracking, fluorophores are distinguished by their emission spectra, so two spectrally distinct molecules can be localized simultaneously and precisely even when their diffraction-limited images overlap. This lets us follow interactions between individual proteins as they move in live cells. In both, we treat imaging as an estimation problem: the aim is to recover positions, distances, and rates, each with a quantified uncertainty.
Current projects extend these ideas in two directions: quantum-optimal imaging, which seeks measurement and estimation schemes that approach the fundamental quantum limits of localization and resolution, and adaptive microscopy, in which machine learning controls the instrument to optimize data collection in real time.
Read about specific research highlights →
A modular, high-performance Julia ecosystem for single-molecule localization microscopy, composed as a stack of small, focused packages spanning simulation, point-spread-function modeling, GPU fitting, drift correction, tracking, and visualization. github.com/JuliaSMLM
Instrument-control software and the SMITE MATLAB analysis toolbox. github.com/LidkeLab
K. Lidke directs the PAIS Multiscale Microscopy Center (PAIS-MMC), a shared facility that makes the lab's single-molecule, super-resolution, hyperspectral, and light-sheet instruments, along with other advanced microscopes, available to the wider UNM research community.
Prof. Lidke develops open-source tools for scientific computing and AI-assisted software development on his GitHub profile, including Ship of Tools, an environment for developing with AI coding agents across machines and repositories, and SlackClaw.jl, a Slack-driven interface for dispatching tasks to AI coding agents.