A single-cell proteomics study has produced one of the most detailed protein-level maps yet of the developing human brain, revealing widespread differences between gene expression and protein abundance that are invisible to RNA-based approaches.
Researchers from the University of California, San Francisco and Stanford University designed a label-free mass spectrometry workflow capable of quantifying hundreds of proteins from individual cells in prenatal human brain tissue. The approach enables direct measurement of protein abundance without relying on antibody panels or transcriptomic proxies.
The team applied the method to human cortical tissue collected at gestational weeks 13, 15, and 19, profiling more than 2,300 individual cells. After quality control, protein profiles from over 1,500 brain-derived cells were used to resolve major neural and non-neural populations, including radial glia, intermediate progenitors, excitatory neurons, interneurons, oligodendrocyte progenitors, microglia, and vascular cells.
Comparisons with matched single-cell RNA sequencing data revealed extensive discordance between transcripts and proteins across nearly all cell types. Many genes that appeared broadly expressed at the RNA level showed sharply restricted protein expression, indicating that post-transcriptional regulation plays a central role in defining cellular identity during brain development. Overall, protein abundance proved substantially more cell-type-specific than mRNA levels.
The proteomic data were particularly informative during the transition from intermediate progenitor cells to excitatory neurons, a key developmental stage linked to neurodevelopmental vulnerability. Protein co-expression analysis revealed distinct modules emerging during this transition, many conserved across species and enriched for genes implicated in autism spectrum disorders. Notably, several high-risk genes showed high transcript levels but constrained protein abundance, pointing to active buffering of protein expression during early neurogenesis.
By anchoring developmental trajectories directly in protein abundance, the approach offers a way to examine how genetic risk and regulatory control converge during narrow windows of brain development. The researchers suggest that applying single-cell proteomics across additional developmental stages, and integrating it with genetic and functional data, could help clarify how disruptions in protein regulation contribute to neurodevelopmental disorders.
They also note that extending the workflow to disease tissue could offer new insight into how early molecular dysregulation manifests later in life.
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