Abstract
AbstractCurrent spatial metabolomics techniques have transformed our understanding of cellular metabolism, yet accessible methods are limited in spatial resolution due to sensitivity constraints. MetaLens, a deep generative approach, disrupts this trade-off by quantitatively propagating cellular-resolutionin situimaging mass spectrometry readouts to subcellular scales through integration with high-resolution light microscopy. MetaLens identifies subcellular metabolic domains with distinct molecular composition, enabling accessible label-free subcellular metabolomic analysis from microscopy.
Publisher
Cold Spring Harbor Laboratory