scholarly journals Ion Mobility-Mass Spectrometry Imaging Workflow

2020 ◽  
Vol 31 (12) ◽  
pp. 2437-2442 ◽  
Author(s):  
Daniela Mesa Sanchez ◽  
Steve Creger ◽  
Veerupaksh Singla ◽  
Ruwan T. Kurulugama ◽  
John Fjeldsted ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Mass Spectrometry Imaging ◽  
Ion Mobility Mass Spectrometry

scholarly journals An Ion Mobility-Mass Spectrometry Imaging Workflow

2020 ◽  
Author(s):  
Daniela Mesa Sanchez ◽  
Steve Creger ◽  
Veerupaksh Singla ◽  
Ruwan T. Kurulugama ◽  
John Fjeldsted ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Mass Spectrometry Imaging ◽  
Feature Detection ◽  
Drift Time ◽  
Biological Tissues ◽  
Ion Mobility Mass Spectrometry ◽  
Label Free ◽  
User Input ◽  
Spatially Resolved

<p>Mass spectrometry imaging (MSI) is a powerful technique for the label-free spatially-resolved analysis of biological tissues. Coupling ion mobility (IM) separation with MSI allows separation of isobars in the mobility dimension and increases confidence of peak assignments. Recently, imaging experiments have been implemented on the Agilent 6560 Ion Mobility Quadrupole Time of Flight Mass Spectrometer, making MSI experiments more broadly accessible to the MS community. However, the absence of data analysis software for this system presents a bottleneck. Herein, we present a vendor-specific imaging workflow to visualize IM-MSI data produced on the Agilent IM-MS system. Specifically, we have developed a Python script, the ion mobility-mass spectrometry image creation script (IM-MSIC), which interfaces Agilent’s Mass Hunter Mass Profiler software with the MacCoss lab’s Skyline software and generates drift time and mass-to-charge selected ion images. In the workflow, Mass Profiler is used for an untargeted feature detection. The IM-MSIC script mediates user input of data and extracts ion chronograms utilizing Skyline’s command-line interface, then proceeds towards ion image generation within a single user interface. Ion image post-processing is subsequently performed using different tools implemented in accompanying scripts.</p>

scholarly journals An Ion Mobility-Mass Spectrometry Imaging Workflow

2020 ◽  
Author(s):  
Daniela Mesa Sanchez ◽  
Steve Creger ◽  
Veerupaksh Singla ◽  
Ruwan T. Kurulugama ◽  
John Fjeldsted ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Mass Spectrometry Imaging ◽  
Feature Detection ◽  
Drift Time ◽  
Biological Tissues ◽  
Ion Mobility Mass Spectrometry ◽  
Label Free ◽  
User Input ◽  
Spatially Resolved

<p>Mass spectrometry imaging (MSI) is a powerful technique for the label-free spatially-resolved analysis of biological tissues. Coupling ion mobility (IM) separation with MSI allows separation of isobars in the mobility dimension and increases confidence of peak assignments. Recently, imaging experiments have been implemented on the Agilent 6560 Ion Mobility Quadrupole Time of Flight Mass Spectrometer, making MSI experiments more broadly accessible to the MS community. However, the absence of data analysis software for this system presents a bottleneck. Herein, we present a vendor-specific imaging workflow to visualize IM-MSI data produced on the Agilent IM-MS system. Specifically, we have developed a Python script, the ion mobility-mass spectrometry image creation script (IM-MSIC), which interfaces Agilent’s Mass Hunter Mass Profiler software with the MacCoss lab’s Skyline software and generates drift time and mass-to-charge selected ion images. In the workflow, Mass Profiler is used for an untargeted feature detection. The IM-MSIC script mediates user input of data and extracts ion chronograms utilizing Skyline’s command-line interface, then proceeds towards ion image generation within a single user interface. Ion image post-processing is subsequently performed using different tools implemented in accompanying scripts.</p>

Rapid Diagnosis of Parkinson’s Disease from Sebum using Paper Spray Ionisation Ion Mobility Mass Spectrometry

2020 ◽  
Author(s):  
Depanjan Sarkar ◽  
Drupad Trivedi ◽  
Eleanor Sinclair ◽  
Sze Hway Lim ◽  
Caitlin Walton-Doyle ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Ion Mobility ◽  
Neurodegenerative Disorder ◽  
Treatment Options ◽  
Ion Mobility Mass Spectrometry ◽  
Paper Spray ◽  
Molecular Features ◽  
Validation Set

Parkinson’s disease (PD) is the second most common neurodegenerative disorder for which identification of robust biomarkers to complement clinical PD diagnosis would accelerate treatment options and help to stratify disease progression. Here we demonstrate the use of paper spray ionisation coupled with ion mobility mass spectrometry (PSI IM-MS) to determine diagnostic molecular features of PD in sebum. PSI IM-MS was performed directly from skin swabs, collected from 34 people with PD and 30 matched control subjects as a training set and a further 91 samples from 5 different collection sites as a validation set. PSI IM-MS elucidates ~ 4200 features from each individual and we report two classes of lipids (namely phosphatidylcholine and cardiolipin) that differ significantly in the sebum of people with PD. Putative metabolite annotations are obtained using tandem mass spectrometry experiments combined with accurate mass measurements. Sample preparation and PSI IM-MS analysis and diagnosis can be performed ~5 minutes per sample offering a new route to for rapid and inexpensive confirmatory diagnosis of this disease.

P‐97: Separation of Isomeric OLED Materials Using Ion Mobility‐Mass Spectrometry (IM‐MS)

2021 ◽  
Vol 52 (1) ◽  
pp. 1444-1447
Author(s):  
Hirotaka Shioji ◽  
Azusa Uematsu ◽  
Motoshi Onoda ◽  
Keiko Matsuda ◽  
Keisuke Sawada ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Ion Mobility Mass Spectrometry
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