Léa Ledoux (Villeneuve d'Ascq / FR), Yanis Zirem (Villeneuve d'Ascq / FR), Laurine Lagache (Villeneuve d'Ascq / FR), Michel Salzet (Villeneuve d'Ascq / FR), Isabelle Fournier (Villeneuve d'Ascq / FR)
Introduction
Biological tissues exhibit complex spatial heterogeneity that directs the functions of multicellular organisms. Quantifying the expression of molecules is essential for elucidating processes within these complex biological assemblies. Indeed, spatial omics can provide deep insights into cellular compositions and interactions in tissues.
Mass spectrometry imaging is a powerful emerging tool for mapping the spatial distribution of molecules across tissue surfaces. However, it does not permit the identification of detected molecules without post-analysis. Past efforts to achieve spatially resolved proteome across tissues have had limited proteome coverage and have relied on multi-step workflows. Here, we demonstrate an automated approach to imaging that uses label-free quantification omics (proteins, lipids, and metabolites) to analyze rat brain tissue sections with a spatial resolution of 220 µm.
Methods
The SpiderMass technique is used here to microsample a region of tissue the size of the laser beam at the focal point (220um). The advantage, given its wavelength and energy, is that glass is transparent at the wavelength used, allowing irradiation to be performed from the back, with tissue ablation towards the front of the slide. This facilitates the collection of ablated tissue, which can then be processed for all types of omic analysis.
Rat brains were irradiated, extracted tissue fragments are then collected in a tube containing 200 µl of ACN and subjected to a Folch extraction to recover three samples, which are used for simultaneous lipidomic, metabolomic, and proteomic analysis by LC-MS.
Results
Various parameters were tested and refined to achieve optimal proteomic analysis via backside irradiation. Key parameters included tissue section thickness, extraction method, sample collection technique, protein digestion type, and slide type. These parameters were optimized using LC-MS analysis of 220 µm irradiation zone tenplicates in RB cortex. Excellent proteomic results (more than 5000 proteins) were obtained with 12 µm-thick tissue sections and Trypsin liquid digestion for both fresh and FFPE tissue. This methodology is compatible with white or ITO slides, demonstrating its feasibility for post-MSI analysis or post-HE staining.
Additionally, this methodology was used to create 2D protein images of rat brain tissue sections, including various areas of interest. Using the LFQ, it was possible to map the expression levels of all detected proteins back onto the tissue image. This highlights the specific localization of certain proteins, which is of immense interest for future analyses of cancerous tissues, biomarker localization, and direct identification.
The optimized parameters were similarly used to achieve high-quality results in additional omics analyses (lipids, metbolites). This comprehensive approach allows for a robust, multi-dimensional understanding of the molecular composition and spatial distribution within biological tissues.
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