Structure-drift time relationships in ion mobility mass spectrometry

Chromatography based mass spectrometry approaches (xC-MS) are commonly used in untargeted metabolomics, providing retention time, m/z values and metabolite specific-fragments all of which are used to identify and validate an unknown analyte. Ion mobility-mass spectrometry (IM-MS) is emerging as an enhancement to classic xC-MS strategies, by offering additional separation as well as collision cross section (CCS) determination. In order to apply such an approach to a synthetic biology workflow, verified data from metabolite standards is necessary. In this work we present experimental DTCCSN2 values for a range of metabolites in positive and negative ionisation modes using drift time-ion mobility-mass spectrometry (DT-IM-MS) with nitrogen as the buffer gas. Creating a useful database containing DTCCSN2 measurements for application in metabolite identification relies on a robust technique that acquires measurements of high reproducibility. We report that 86% of the metabolites measured in replicate have a relative standard deviation lower than 0.2 %. Examples of metabolites with near identical mass are demonstrated to be separated by ion mobility with over 4% difference in DTCCSN2 values. We conclude that the integration of ion mobility into current LC-MS workflows can aid in small molecule identification for both targeted and untargeted metabolite screening which is commonly performed in synthetic biology.

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Increasing Compound Identification Rates in Untargeted Lipidomics Research with Liquid Chromatography Drift Time–Ion Mobility Mass Spectrometry

Analytical Chemistry ◽

10.1021/acs.analchem.8b01527 ◽

2018 ◽

Vol 90 (18) ◽

pp. 10758-10764 ◽

Cited By ~ 33

Author(s):

Ivana Blaženović ◽

Tong Shen ◽

Sajjan S. Mehta ◽

Tobias Kind ◽

Jian Ji ◽

...

Keyword(s):

Mass Spectrometry ◽

Liquid Chromatography ◽

Ion Mobility ◽

Drift Time ◽

Ion Mobility Mass Spectrometry ◽

Compound Identification

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Applications of Ion Mobility-Mass Spectrometry in Carbohydrate Chemistry and Glycobiology

Molecules ◽

10.3390/molecules23102557 ◽

2018 ◽

Vol 23 (10) ◽

pp. 2557 ◽

Cited By ~ 3

Author(s):

Yuqing Mu ◽

Benjamin Schulz ◽

Vito Ferro

Keyword(s):

Mass Spectrometry ◽

Ion Mobility ◽

Drift Time ◽

Structural Complexity ◽

Ion Mobility Mass Spectrometry ◽

Vast Number ◽

Disease States ◽

Coupled Technique ◽

Analytical Tools

Carbohydrate analyses are often challenging due to the structural complexity of these molecules, as well as the lack of suitable analytical tools for distinguishing the vast number of possible isomers. The coupled technique, ion mobility-mass spectrometry (IM-MS), has been in use for two decades for the analysis of complex biomolecules, and in recent years it has emerged as a powerful technique for the analysis of carbohydrates. For carbohydrates, most studies have focused on the separation and characterization of isomers in biological samples. IM-MS is capable of separating isomeric ions by drift time, and further characterizing them by mass analysis. Applications of IM-MS in carbohydrate analysis are extremely useful and important for understanding many biological mechanisms and for the determination of disease states, although efforts are still needed for higher sensitivity and resolution.

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Prediction of peptide drift time in ion mobility mass spectrometry from sequence-based features

BMC Bioinformatics ◽

10.1186/1471-2105-14-s8-s9 ◽

2013 ◽

Vol 14 (S8) ◽

Cited By ~ 8

Author(s):

Bing Wang ◽

Jun Zhang ◽

Peng Chen ◽

Zhiwei Ji ◽

Shuping Deng ◽

...

Keyword(s):

Mass Spectrometry ◽

Ion Mobility ◽

Drift Time ◽

Ion Mobility Mass Spectrometry

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An Ion Mobility-Mass Spectrometry Imaging Workflow

10.26434/chemrxiv.12408083 ◽

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

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.

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Mobilising Ion Mobility Mass Spectrometry in a Synthetic Biology Analytics Workflow

10.26434/chemrxiv.6149204 ◽

2018 ◽

Author(s):

Eleanor Sinclair ◽

Katherine A. Hollywood ◽

Cunyu Yan ◽

Richard Blankley ◽

Rainer Breitling ◽

...

Keyword(s):

Mass Spectrometry ◽

Synthetic Biology ◽

Ion Mobility ◽

Collision Cross Section ◽

Drift Time ◽

Metabolite Identification ◽

Ion Mobility Mass Spectrometry ◽

Buffer Gas ◽

High Reproducibility ◽

Relative Standard

Chromatography based mass spectrometry approaches (xC-MS) are commonly used in untargeted metabolomics, providing retention time, m/z values and metabolite specific-fragments all of which are used to identify and validate an unknown analyte. Ion mobility-mass spectrometry (IM-MS) is emerging as an enhancement to classic xC-MS strategies, by offering additional separation as well as collision cross section (CCS) determination. In order to apply such an approach to a synthetic biology workflow, verified data from metabolite standards is necessary. In this work we present experimental DTCCSN2 values for a range of metabolites in positive and negative ionisation modes using drift time-ion mobility-mass spectrometry (DT-IM-MS) with nitrogen as the buffer gas. Creating a useful database containing DTCCSN2 measurements for application in metabolite identification relies on a robust technique that acquires measurements of high reproducibility. We report that 86% of the metabolites measured in replicate have a relative standard deviation lower than 0.2 %. Examples of metabolites with near identical mass are demonstrated to be separated by ion mobility with over 4% difference in DTCCSN2 values. We conclude that the integration of ion mobility into current LC-MS workflows can aid in small molecule identification for both targeted and untargeted metabolite screening which is commonly performed in synthetic biology.

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Prediction of Drift Time in Ion Mobility-Mass Spectrometry Based on Peptide Molecular Weight

Protein and Peptide Letters ◽

10.2174/092986610791760360 ◽

2010 ◽

Vol 17 (9) ◽

pp. 1143-1147 ◽

Cited By ~ 1

Author(s):

Bing Wang ◽

Steve Valentine ◽

Manolo Plasencia ◽

Xiang Zhang

Keyword(s):

Mass Spectrometry ◽

Molecular Weight ◽

Ion Mobility ◽

Drift Time ◽

Ion Mobility Mass Spectrometry

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An Ion Mobility-Mass Spectrometry Imaging Workflow

10.26434/chemrxiv.12408083.v1 ◽

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

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.

Download Full-text