bioRxivBiochemistry
Deep MALDI-MS Spatial Omics guided by Quantum Cascade Laser Mid-infrared Imaging Microscopy
L. Gruber, S. Schmidt, T. Enzlein, H. G. Vo, J. L. Cairns, Y. Ucal, F. Keller, D. Abu Sammour, R. Rudolf, M. Eckhardt, S. A. Iakab, L. Bindila, C. Hopf
Abstract
In spatial omics, highly confident molecular identifications are indispensable for the investigation of complex biology and for spatial biomarker discovery. However, current mass spectrometry (MS)-based spatial omics must compromise between data acquisition speed and biochemical profiling depth, thus often leading to only "putative" molecular identifications. Here, we introduce fast quantum cascade laser mid-infrared imaging microscopy to guide MS imaging to confined tissue areas of high interest, e.g., multicellular spheroid cores or kidney glomeruli, for spatial lipidomics profiling at maximized analytical depth utilizing magnetic resonance-MS imaging at >106 resolution or prm-PASEF-MS2 fragmentation imaging. Instigating selective sulfatide accumulation in arylsulfatase A-deficient mice as ground truth concept, we demonstrate that deep QCL-infrared-guided on-tissue spatial omics unequivocally identifies 120 sulfatides. This approach enables identifications of odd-chain sulfatides and studies of structure-ion mobility-relationships that provide chemical rationales for improvements to current ion mobility prediction algorithms. Workflows and data processing tools are provided as community resources.
- organism: mouse
- assay: spatial transcriptomics
- assay: metabolomics
- research focus: cell type annotation
- research focus: differential expression
- approach: deep learning
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