Background

Mapping Your Life and Everything Else

Presented by Prof. John A. McLean at TED^x Vanderbilt University:

[youtube https://www.youtube.com/watch?v=QRvP5TfNwsQ]

Guiding Theory

Our research focuses on the design, construction, and application of advanced technologies for structural mass spectrometry, in particular, for studies in biomolecular separations, biophysics, chemical and synthetic biology. To identify and structurally characterize the inventory of biomolecules arising from complex samples, we perform multidimensional chemical separations centered around condensed-phase chromatography (GC, LC, SFC) combined with ion mobility-mass spectrometry (IM-MS), the latter of which provides separations on the basis of apparent surface area (ion-neutral collision cross section) and mass-to-charge (m/z), respectively. Biomolecular structural information is interpreted by comparing experimentally obtained collision cross-sections in the context of those obtained via predictions from empirical models, machine learning, and molecular dynamics simulations.

Figure 1. A multidimensional analysis of five lipid classes (two sphingolipids and three phospholipids) using data obtained from an IM-MS experiment¹. (A) The raw IM-MS spectrum is projected as a heat map, with m/z on the x-axis, IM drift time on the y-axis, and signal intensity on the color mapping scale. (B) Feature extraction of singly-charged ions is performed, resulting in a “conformational space” plot of mass versus collision cross-section. (C) The accurate mass measurement (ca. 5 ppm in this work) can also be subjected to a mass defect scaling, resulting in a mass vs. mass defect plot. (D) Both the IM-MS conformational space map and the mass defect plot reveal groupings the data based on their respective lipid class, with sphingolipids separated from phospholipids.

¹JC May and JA McLean, Advanced multidimensional separations in mass spectrometry: navigating the big data deluge. Annual Review of Analytical Chemistry 9:387-409 (2016).