Poster Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

Exploiting 4D in Omics: Mass Offset Mobility Aligned (MOMA) and Mass Aligned Mobility Offset (MAMO) of Biological Analytes (#800)

Christopher M Adams 1 , Michael Krawitzky 1 , Guillaume Trementin 1 , Adam Rainczuk 2 , Pierre-Olivier Schmit 3 , Gary Kruppa 4
  1. Bruker Daltonics Inc, San Jose, CA, USA
  2. BRUKER Pty. LTD, Preston, Australia
  3. Bruker France, Wissembourg, France
  4. Bruker Daltonics Inc, Billerica, MA, USA

Small molecules, lipids, glycans and peptides are just a few of the classes of compounds, represented by vast diversity, that are measured in “OMXs” studies by mass spectrometers. By definition, the mass spectrometer measures molecular mass , and as such is incognizant to physiochemical properties that differentiate such things, as for example peptide isobars. Trapped Ion Mobility Spectrometry (TIMS) has the unique  capability of separating gaseous ions by mobility (CCS) prior to injection into the mass spectrometer . This additional dimension (CCS) coupled to a sensitive and fast scanning TOF affords deconvolution of analytes whose molecular mass is different but CCS (mobility) is the same, as is the case for SILAC, mTRAQ and di-methyl labeled peptides. We describe this principle with the acronym MOMA- Mass Offset Mobility Aligned where the precise delta mass of peptide labeled pairs co-eluting in time give rise to the same CCS term. Utilizing the delta mass shift in combination with the same retention time is a methodology previously describe as TOMAHAQa (Triggered by Offset, Multiplexed, Accurate-mass, High-resolution, and Absolute Quantification), where TMT0 at high levels conjugated to a desired target analyte is run in conjunction with a traditional TMT experiment and multiplex targeted quantitation can occur simultaneously with discovery multiplex proteomics . One of the pitfalls with this approach is, without the a priori knowledge of the target analyte retention time, targeted quantitation is highly prone to being falsely triggered. We and others have previously shown that CCS values for lipids and peptides can be predicted with high fidelity. Within this work we intend  to describe how using MOMA and predictive CCS we can perform TOMAHAQ-like experiments with higher throughput, sensitivity and target analyte fidelity on the timsTOF Pro.


  1. Erickson et al., 2017, Molecular Cell 65, 361–370 January 19, 2017 ª 2016 Elsevier Inc.