Enhanced Spatial Proteomics and Metabolomics from a Single Tissue Section Using MALDI-MSI and LCM-microPOTS Platforms
Marija Veličković, Le Day, Kevin Zemaitis, Isaac Attah, Kristin Burnum-Johnson, Christopher Anderton, Dušan Veličković
Abstract
Spatially resolved mass spectrometry (MS)-based multiomics workflows are becoming more utilized for revealing the complex biology that occurs within tissues. However, these approaches commonly require multiple independent tissue sections to analyze the metabolite and protein compositions of these samples. This poses a significant challenge in preserving cell- or region-specific molecular fidelity, as variations between tissue sections can compromise the accurate correlation of molecular data. Here, we developed workflows for comprehensive multiomics profiling from a single tissue section (STS) using different MS modalities. We enhanced the functionality of an electrically insulated substrate by employing metal-assisted approaches that enabled both MS-based untargeted spatial metabolomics and proteomics from STS. This allowed metabolite imaging using matrix-assisted laser desorption/ionization-MS imaging (MALDI-MSI), without compromising it for subsequent proteome profiling with laser capture microdissection (LCM)-based technology. Specifically, implementing copper tape as a backing for polyethylene naphthalate (PEN) slides enabled the detection of >140 metabolites across a poplar root tissue section using MALDI-trapped ion mobility spectrometry time-of-flight (timsTOF)-MS. Afterward, we detected 6571 unique proteins from two distinct root regions by leveraging LCM technology coupled to our microdroplet based sample preparation approach. We also developed an alternative workflow utilizing gold-coated PEN substrates for imaging with MALDI-Fourier-transform ion cyclotron resonance (FTICR)-MS, which permitted the profiling of >170 metabolites and the identification of 6542 unique proteins across a single poplar root tissue section. These results were comparable to using each omics analysis independently. These approaches offer new opportunities for high-resolution molecular profiling of multiple omics levels across biological tissues.