"Top Down Proteomics in Native and Denatured Modes"
Professor Neil Kelleher, Northwestern University
"IR-MALDESI Mass Spectrometry Imaging: An Innovative Tool for Visualization of Molecular Distributions"
Milad Nazari, Laboratory of Professor David Muddiman, North Carolina State University, Department of Chemistry
Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI) is a powerful analytical platform for the visualization of endogenous and exogenous analytes within tissue sections. In IR-MALDESI analyses, an IR laser ablates a voxel of tissue at each rastered position, providing a complete and reproducible volume of a tissue section to be sampled with subsequent post-ionization of analytes by ESI. IR-MALDESI has been successfully applied to a variety of applications including targeted drug distribution and untargeted metabolic profiling studies. MSI has been primarily used to obtain qualitative information about spatial distribution of analytes; however, absolute quantification of analytes by MSI remains challenging. Through development and optimization of a quantitative MSI workflow, IR-MALDESI MSI provides absolute quantification of small molecule drugs in tissue. MSI variability from tissue microenvironments is reduced with the uniform incorporation of an internal standard for normalization of analyte on a per-voxel basis. Absolute quantification MSI is accomplished through the inclusion of a spatial calibration curve in the MSI analysis allowing direct correlation of observed ion abundance in MSI to absolute analyte concentration.
Untargeted metabolomic profiling of tissue sections is another exciting application of IR-MALDESI. Metabolite profiles provide valuable information for understanding the biological basis and progression of many diseases. Due to their remarkable structural diversity, different metabolites exhibit significant differences in their ionization efficiency. Therefore, analyzing tissue sections in positive and negative modes is essential for obtaining comprehensive metabolite coverage. To this end, an IR-MALDESI polarity switching MSI method was developed where adjacent voxels were analyzed with opposing polarities. The domestic hen model for spontaneous development of ovarian cancer was used to demonstrate the utility of this method. Differences in spatial distribution and relative abundance of more than 700 lipids and metabolites between healthy and cancerous tissue sections were simultaneously monitored and compared.