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A Preprocessing Tool for Enhanced Ion Mobility-Mass Spectrometry-Based Omics Workflows

Authors :
Yehia M. Ibrahim
Richard D. Smith
Erin S. Baker
Bryson C. Gibbons
Samuel H. Payne
Aivett Bilbao
John C. Fjeldsted
Sarah M. Stow
Jennifer E. Kyle
Kent J. Bloodsworth
Source :
J Proteome Res
Publication Year :
2021

Abstract

The ability to improve the data quality of ion mobility-mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

Details

ISSN :
15353907
Volume :
21
Issue :
3
Database :
OpenAIRE
Journal :
Journal of proteome research
Accession number :
edsair.doi.dedup.....a69d57ad21949f90d6853c437231014c