Authors
Jessica K Lukowski, Heather Olson, Marija Velickovic, Juan Wang, Jennifer E Kyle, Young-Mo Kim, Sarah M Williams, Ying Zhu, Heidi L Huyck, Matthew D McGraw, Cory Poole, Lisa Rogers, Ravi Misra, Theodore Alexandrov, Charles Ansong, Gloria S Pryhuber, Geremy Clair, Joshua N Adkins, James P Carson, Christopher R Anderton
Publication date
2022/11/16
Journal
Frontiers in Molecular Biosciences
Volume
9
Pages
1022775
Publisher
Frontiers Media SA
Description
Human disease states are biomolecularly multifaceted and can span across phenotypic states, therefore it is important to understand diseases on all levels, across cell types, and within and across microanatomical tissue compartments. To obtain an accurate and representative view of the molecular landscape within human lungs, this fragile tissue must be inflated and embedded to maintain spatial fidelity of the location of molecules and minimize molecular degradation for molecular imaging experiments. Here, we evaluated agarose inflation and carboxymethyl cellulose embedding media and determined effective tissue preparation protocols for performing bulk and spatial mass spectrometry-based omics measurements. Mass spectrometry imaging methods were optimized to boost the number of annotatable molecules in agarose inflated lung samples. This optimized protocol permitted the observation of unique lipid distributions within several airway regions in the lung tissue block. Laser capture microdissection of these airway regions followed by high-resolution proteomic analysis allowed us to begin linking the lipidome with the proteome in a spatially resolved manner, where we observed proteins with high abundance specifically localized to the airway regions. We also compared our mass spectrometry results to lung tissue samples preserved using two other inflation/embedding media, but we identified several pitfalls with the sample preparation steps using this preservation method. Overall, we demonstrated the versatility of the inflation method, and we can start to reveal how the metabolome, lipidome, and proteome are connected …
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