NJ-ACS Mass Spec Discussion Group

The NJ Mass Spectrometry Discussion Group presents its April Meeting on Tuesday, Apr 14, 2015 at at the Holiday Inn Somerset-Bridgewater, 195 Davidson Ave, Somerset NJ 08873 [ website ]

Sponsored by Agilent

Agilent Technologies

The evening is free for attendees, courtesy of our sponsor!

Please register here.


5:30 pm Social and registration

6:15 pm Complimentary dinner

7:00 pm Welcome and opening remarks

7:05 pm Dr. John A. McLean, Stevenson Professor of Chemistry, Vanderbilt University

Title: Targeting the untargeted: Structural mass spectrometry for the analysis of complex samples in systems, synthetic, and chemical biology

7:55 pm Closing remarks


One of the predominant challenges in systems-wide analyses is the broad-scale characterization of the molecular inventory in cells, tissues, and biological fluids. Advances in computational systems biology rely heavily on the experimental capacity to make panomics measurements, i.e. integrated metabolomics, proteomics, lipidomics, glycomics, etc., accompanied with fast minimal sample preparation, fast measurements, high concentration dynamic range, low limits of detection, and high selectivity. This confluence of figures-of-merit place demanding challenges on analytical platforms for such analyses. Ion mobility-mass spectrometry (IM-MS) provides rapid (ms) gas-phase electrophoretic separations on the basis of molecular structure and is well suited for integration with rapid (us) mass spectrometry detection techniques. Furthermore, the timescales of this multi-dimensional separation are well suited for combination with fast condensed-phase separations such as GC, SFC, and UPLC (min) for enhanced separation selectivity as the sample complexity becomes ever more challenging. This report will describe recent advances in IM-MS panomics measurement strategies in the analyses of complex biological samples of interest in systems, synthetic, and chemical biology. New advances in bioinformatics and biostatistics will also be described to approach biological queries from an unbiased and untargeted perspective and to quickly mine the data gathered to provide targeted and actionable information.