Increased throughput and ultra-high mass resolution in DESI FT-ICR MS imaging through new-generation external data acquisition system and advanced data processing approaches

Kooijman, PC, Nagornov, KO, Kozhinov, AN, Kilgour, DPA ORCID: https://orcid.org/0000-0002-3860-7532, Tsybin, YO, Heeren, RMA and Ellis, SR, 2019. Increased throughput and ultra-high mass resolution in DESI FT-ICR MS imaging through new-generation external data acquisition system and advanced data processing approaches. Scientific Reports, 9: 8. ISSN 2045-2322

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Abstract

Desorption electrospray ionisation-mass spectrometry imaging (DESI-MSI) is a powerful imaging technique for the analysis of complex surfaces. However, the often highly complex nature of biological samples is particularly challenging for MSI approaches, as options to appropriately address mass spectral complexity are limited. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) offers superior mass accuracy and mass resolving power, but its moderate throughput inhibits broader application.
Here we demonstrate the dramatic gains in mass resolution and/or throughput of DESI-MSI on an FT-ICR MS by developing and implementing a sophisticated data acquisition and data processing pipeline. The presented pipeline integrates, for the first time, parallel ion accumulation and detection, post-processing absorption mode Fourier transform and pixel-by-pixel internal re-calibration. To achieve that, first, we developed and coupled an external high-performance data acquisition system to an FT-ICR MS instrument to record the time-domain signals (transients) in parallel with the instrument’s built-in electronics. The recorded transients were then processed by the in-house developed computationally-efficient data processing and data analysis software. Importantly, the described pipeline is shown to be applicable even to extremely large, up to 1 TB, imaging datasets. Overall, this approach provides improved analytical figures of merits such as: (i) enhanced mass resolution at no cost in experimental time; and (ii) up to 4-fold higher throughput while maintaining a constant mass resolution. Using this approach, we not only demonstrate the record 1 million mass resolution for lipid imaging from brain tissue, but explicitly demonstrate such mass resolution is required to resolve the complexity of the lipidome.

Item Type:	Journal article
Publication Title:	Scientific Reports
Creators:	Kooijman, P.C., Nagornov, K.O., Kozhinov, A.N., Kilgour, D.P.A., Tsybin, Y.O., Heeren, R.M.A. and Ellis, S.R.
Publisher:	Nature Publishing Group
Date:	9 January 2019
Volume:	9
ISSN:	2045-2322
Identifiers:	Number Type 10.1038/s41598-018-36957-1 DOI
Rights:	Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2019.
Divisions:	Schools > School of Science and Technology
Record created by:	Linda Sullivan
Date Added:	12 Dec 2018 10:44
Last Modified:	23 Jan 2019 09:57
URI:	https://irep.ntu.ac.uk/id/eprint/35300

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