New Optical Imaging Method Reveals Metabolic Activity of Blood Immune Cells Without Destroying Them

A new imaging method can reveal how active individual immune cells are inside a routine blood sample, without destroying them, according to a study published in the journal Biophotonics Discovery. The technique targets peripheral blood mononuclear cells (PBMCs), a mix of immune cells widely used to study infections, autoimmune disorders, cancer and the immune system's response to treatment.

Scientists typically identify these cells using fluorescent labels that attach to specific surface markers, a method that reveals little about how the cells are functioning and can alter them during preparation. "PBMCs can be isolated clinically really easily, and they're already used in the clinical workflow," said senior author Melissa Skala of the Morgridge Institute for Research and the University of Wisconsin–Madison. "So, the question is, what can we get from them that we aren't already getting?"

The researchers used optical metabolic imaging (OMI), a technique developed by the Skala Lab that relies on the natural fluorescence of molecules involved in cellular energy production. Two-photon microscopy excites these naturally occurring metabolic cofactors inside cells and measures how long they emit light, information that reflects a cell's metabolism and activation state, without adding external dyes or destroying the cells.

Applying OMI to PBMC samples from three healthy donors, the team analyzed thousands of individual cells in resting and activated states, using machine-learning algorithms to test whether metabolic measurements alone could identify cell types and detect immune activation. The method distinguished activated from resting PBMCs with close to 94% accuracy just two hours after stimulation, identified monocytes with 96% accuracy in resting samples and 88% in activated samples, and identified natural killer cells with about 74% accuracy in both states.

The single-cell approach also revealed substantial variation within the immune-cell population that would be hidden by measurements averaged across a whole sample. The researchers note that the technology remains primarily a research tool and does not yet match the accuracy of established labeling methods for identifying every immune-cell subtype, though its nondestructive nature could make it useful for assessing cell quality before manufacturing therapies such as CAR T-cell treatments, which use PBMCs as their starting material.