Dr. Cheng Li published a paper in Neuron with his collaborators.

Microglia are brain-resident immune cells with complex physiological functions. Exploring their proteomic heterogeneity at the single-cell level has remained technically challenging. Here, we optimized a label-free single-cell proteomics (SCP) workflow using Orbitrap Astral mass spectrometry (MS) and applied it to fluorescence-activated cell sorting (FACS)-sorted microglia from the hippocampus and prefrontal cortex of young, middle-aged, and aged mice. This yielded one of the largest SCP datasets to date, comprising 3,085 single cells, with an average of 1,153 protein groups identified per cell. Compared with single-cell transcriptomic data, the SCP dataset showed higher expression completeness and moderate cross-modality correlation. This dataset revealed spatiotemporal proteomic heterogeneity of microglia during aging. Notably, we defined the microglial “phagoproteome,” uncovering state-specific phagocytic preferences, and verified these results by imaging. This study underscores the potential of SCP to reveal subpopulation-specific proteomic dynamics and provides a new resource for studying microglial state transitions during aging.

Original link: https://www.cell.com/neuron/fulltext/S0896-6273(26)00385-5