Mobilising Ion Mobility Mass Spectrometry in a Synthetic Biology Analytics Workflow

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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Structure-drift time relationships in ion mobility mass spectrometry

International Journal for Ion Mobility Spectrometry ◽

10.1007/s12127-013-0129-1 ◽

2013 ◽

Vol 16 (2) ◽

pp. 117-132 ◽

Cited By ~ 21

Author(s):

Maíra Fasciotti ◽

Priscila M. Lalli ◽

Gabriel Heerdt ◽

Rafael A. Steffen ◽

Yuri E. Corilo ◽

...

Keyword(s):

Mass Spectrometry ◽

Ion Mobility ◽

Drift Time ◽

Ion Mobility Mass Spectrometry

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Recommendations for Reporting Ion Mobility Mass Spectrometry Measurements

10.26434/chemrxiv.7072070.v3 ◽

2018 ◽

Author(s):

Valerie Gabelica ◽

Alexandre A. Shvartsburg ◽

Carlos Afonso ◽

Perdita E. Barran ◽

Justin L. P. Benesch ◽

...

Keyword(s):

Mass Spectrometry ◽

Cross Section ◽

Ion Mobility ◽

Collision Cross Section ◽

Ion Mobility Mass Spectrometry ◽

Gas Temperature ◽

Mobility Data ◽

Community Effort ◽

Primary Standards ◽

Definition Of

Here we present a guide on ion mobility mass spectrometry experiments, which covers both linear and nonlinear methods: what is measured, how the measurements are done, and how to report the results, including the uncertainties on mobility and collision cross section values. The guide aims to clarify some possibly confusing concepts, and the reporting recommendations should help researchers, authors and reviewers to contribute comprehensive reports, so that the ion mobility data can be reused more confidently. Starting from the concept of the definition of the measurand, we emphasize that (i) mobility values (K0) depend intrinsically on ion structure, the nature of the bath gas, temperature, and E/N, (ii) ion mobility does not measure surfaces directly, but collision cross section (CCS) values are derived from mobility values using a physical model, (iii) methods relying on calibration are empirical (and thus may provide method-dependent results) only if the gas nature, temperature or E/N cannot match those of the primary method. Our analysis highlights the urgency of a community effort towards establishing primary standards and reference materials for ion mobility, and provides recommendations to do so.

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Rapid resolution of carbohydrate isomers via multi-site derivatization ion mobility-mass spectrometry

The Analyst ◽

10.1039/c7an01796k ◽

2018 ◽

Vol 143 (4) ◽

pp. 949-955 ◽

Cited By ~ 9

Author(s):

Li Li ◽

Kristin R. McKenna ◽

Zhao Li ◽

Mahipal Yadav ◽

Ramanarayanan Krishnamurthy ◽

...

Keyword(s):

Mass Spectrometry ◽

Cross Section ◽

Ion Mobility ◽

Collision Cross Section ◽

Ion Mobility Mass Spectrometry ◽

Rapid Resolution

Identifying small sugar isomers can be challenging by ion mobility-mass spectrometry (IM-MS) alone due to their small collision cross section differences.

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Artificial neural networks for the prediction of peptide drift time in ion mobility mass spectrometry

BMC Bioinformatics ◽

10.1186/1471-2105-11-182 ◽

2010 ◽

Vol 11 (1) ◽

Cited By ~ 17

Author(s):

Bing Wang ◽

Steve Valentine ◽

Manolo Plasencia ◽

Sriram Raghuraman ◽

Xiang Zhang

Keyword(s):

Mass Spectrometry ◽

Neural Networks ◽

Artificial Neural Networks ◽

Ion Mobility ◽

Drift Time ◽

Ion Mobility Mass Spectrometry ◽

Artificial Neural

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Characterisation of Calmodulin Structural Transitions by Ion Mobility Mass Spectrometry

Australian Journal of Chemistry ◽

10.1071/ch12047 ◽

2012 ◽

Vol 65 (5) ◽

pp. 504 ◽

Cited By ~ 5

Author(s):

Antonio N. Calabrese ◽

Lauren A. Speechley ◽

Tara L. Pukala

Keyword(s):

Mass Spectrometry ◽

Cross Section ◽

Cross Sections ◽

Ion Mobility ◽

Collision Cross Section ◽

Travelling Wave ◽

Ion Mobility Mass Spectrometry ◽

Structural Transitions ◽

Calmodulin Binding ◽

Negative Mode

This study demonstrates the ability of travelling wave ion mobility-mass spectrometry to measure collision cross-sections of ions in the negative mode, using a calibration based approach. Here, negative mode ion mobility-mass spectrometry was utilised to understand structural transitions of calmodulin upon Ca2+ binding and complexation with model peptides melittin and the plasma membrane Ca2+ pump C20W peptide. Coexisting calmodulin conformers were distinguished on the basis of their mass and cross-section, and identified as relatively folded and unfolded populations, with good agreement in collision cross-section to known calmodulin geometries. Titration of calcium tartrate to physiologically relevant Ca2+ levels provided evidence for intermediately metalated species during the transition from apo- to holo-calmodulin, with collision cross-section measurements indicating that higher Ca2+ occupancy is correlated with more compact structures. The binding of two representative peptides which exemplify canonical compact (melittin) and extended (C20W) peptide-calmodulin binding models has also been interrogated by ion mobility mass spectrometry. Peptide binding to calmodulin involves intermediates with metalation states from 1–4 Ca2+, which demonstrate relatively collapsed structures, suggesting neither the existence of holo-calmodulin or a pre-folded calmodulin conformation is a prerequisite for binding target peptides or proteins. The biological importance of the different metal unsaturated calmodulin complexes, if any, is yet to be understood.

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Correlating glycoforms of DC-SIGN with stability using a combination of enzymatic digestion and ion mobility MS

10.1101/2020.04.22.055046 ◽

2020 ◽

Author(s):

Hsin-Yung Yen ◽

Idlir Liko ◽

Joseph Gault ◽

Di Wu ◽

Weston B. Struwe ◽

...

Keyword(s):

Mass Spectrometry ◽

Gas Phase ◽

Ion Mobility ◽

Collision Cross Section ◽

Enzymatic Digestion ◽

Ion Mobility Mass Spectrometry ◽

Structural Detail ◽

The Core ◽

Glycosylation Sites ◽

The Stability

AbstractThe immune scavenger protein DC-SIGN interacts with glycosylated proteins and has a putative role in facilitating viral infection. How these recognition events take place with different viruses is not clear and the effects of glycosylation on the folding and stability of DC-SIGN have not been reported. Here, we develop and apply a mass spectrometry-based approach to both uncover and characterise the effects of O-glycans on the stability of DC-SIGN. We first quantify the Core 1 & 2 O-glycan structures on the carbohydrate recognition and extracellular domains of the protein via sequential exoglycosidase sequencing. We then use ion mobility mass spectrometry to show how specific O-glycans, and/or single monosaccharide substitutions, alter both the overall collision cross section and the gas-phase stability of the glycoprotein isoforms of DC-SIGN. We find that rather than the mass or length of glycoprotein modifications, the stability of DC-SIGN is better correlated with the number of glycosylation sites. Collectively, our results exemplify a combined multi-dimensional MS approach, proficient in evaluating protein stability in response to both glycoprotein macro- and micro-heterogeneity and adding structural detail to the infection enhancer DC-SIGN.

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