期刊
ANALYTICAL CHEMISTRY
卷 92, 期 19, 页码 13281-13289出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.0c02519
关键词
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资金
- Air Force Office of Scientific Research [AFOSR FA9550-16-1-0113]
- National Science Foundation under the Data-Driven Discovery Science in Chemistry (D3SC) for Early Concept Grants for Exploratory Research (EAGER Grant) [CHE-1734082]
- National Institute of Health [R01AG056290, P01AG036695]
Cell-type-specific metabolic profiling in tissue with heterogeneous composition has been of great interest across all mass spectrometry imaging (MSI) technologies. We report here a powerful new chemical imaging capability in desorption electrospray ionization (DESI) MSI, which enables cell-type-specific and in situ metabolic profiling in complex tissue samples. We accomplish this by combining DESI-MSI with immunofluorescence staining using specific cell-type markers. We take advantage of the variable frequency of each distinct cell type in the lateral septal nucleus (LSN) region of mouse forebrain. This allows computational deconvolution of the cell-type-specific metabolic profile in neurons and astrocytes by convex optimization-a machine learning method. Based on our approach, we observed 107 metabolites that show different distributions and intensities between astrocytes and neurons. We subsequently identified 23 metabolites using high-resolution mass spectrometry (MS) and tandem MS, which include small metabolites such as adenosine and N-acetylaspartate previously associated with astrocytes and neurons, respectively, as well as accumulation of several phospholipid species in neurons which have not been studied before. Overall, this method overcomes the relatively low spatial resolution of DESI-MSI and provides a new platform for in situ metabolic investigation at the cell-type level in complex tissue samples with heterogeneous cell-type composition.
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