Exploring single cell neurochemistry with multimodal MALDI MS

Brain function is dependent upon the active coordination of many different cell types and subtypes at cellular resolutions. While measuring neurochemistry at cellular resolutions is important for understanding emergent properties, such as cognition and memory, analyzing the chemical nature of the brain at the single cell level is primarily limited to a handful of analytical approaches which often are only capable of measuring a specific aspect of the cell. For instance, transcriptomics measures the expression level of different genes within a cell, while mass spectrometry (MS) measures gene products and metabolites themselves. Single cells are inherently sample limited, so means of extending or expanding the amount of information that can be garnered from an individual cell is important for understanding their complex neurochemistry. Here, we combine a multitude of analytical approaches with single cell matrixassisted laser desorption/ionization (MALDI) MS to increase the amount of information we can obtain from individual mammalian brain cells. We first developed an open source software, that simplifies microscopy-guided MALDI MS measurements and subsequent correlation of data from orthogonal approaches. Using this software, we analyzed tens of thousands of rodent cerebral cells with MALDI MS and detected over five hundred distinct lipid features. Using this metabolic information, we statistically clustered the cells in 101 unique clusters, while also finding rare lipids only present in a small fraction (