Effect of Sampling Rate and Data Pretreatment for Targeted and Nontargeted Analysis by Means of Liquid Chromatography Coupled to Drift Time Ion Mobility Quadruple Time-of-Flight Mass Spectrometry

Evaluating Ion Mobility Data Acquisition, Calibration, and Processing for Small Molecules: A Cross-Platform Assessment of Drift Tube and Traveling Wave Methodologies

As ion mobility spectrometry (IMS) separations continue to be added to analytical workflows due to their power in environmental and biological sample analyses, harmonization and capability understanding between existing and newly released instruments are desperately needed. Developments in IMS platforms often exhibit focus on increasing resolving power (Rp) to better separate molecules of similar structure. While the additional separation capacity is advantageous, ensuring these developments coincide with appropriate data extraction and analysis methods is imperative to ensure routine adoption. Herein, we assess the performance of the MOBILion MOBIE in relation to a commercially available drift tube IMS-MS, the Agilent 6560, and evaluate feature extraction and analysis pipelines. Both instruments were operated using matched conditions when possible, and performance metrics of scan speed, Rp, limits of detection (LOD), and propensity for isomer separation via LC-IMS-MS were evaluated. Similar scan speeds pertaining to IMS-MS frame generation were noted for both platforms, and collision cross section (CCS) values for the MOBIE were generally within ≤ 1% difference from previously reported drift tube values. Both platforms were also able to generate quantitative data (comparable limits of detection) in experiments with perfluoroalkyl substances (PFAS) mixtures in a cell-based model (both medium and cell lysates), as demonstrated in Skyline with adjusted mobility filtering parameters. Higher Rp was, however, noted on the MOBIE in comparison to the 6560 (200-300 vs 45-60 CCS/ΔCCS without data processing), allowing the detection of more PFAS isomers and indicating promise toward future applications in chemical exposomics studies and biomarker discovery when molecules exhibit similar structures.

In-depth profile of biosignatures for T2DM cohort utilizing an integrated targeted LC-MS platform

The profiling of metabolites provides an immediate snapshot that depicts crucial physiological information, holding immense potential for the early diagnosis and prognosis of diseases, including diabetes. Herein, we proposed an optimized and in-depth target-based metabolome platform through an integration of six distinct conditions, including a normal phase, a pre-column chemical derivatization and four reversed phase separation methods for the quantification of a total of 1609 small molecules (32 sub-classes) in serum after normalization using isotope-labeled internal standards. After undergoing rigorous methodological validation and comprehensive comparison with untargeted strategies, we present a new dataset of metabolomic profile encompassing a cohort of 200 healthy individuals and 100 newly diagnosed Type 2 diabetes mellitus (T2DM) patients from the northern region of China. The overall differential analysis results indicated obvious metabolic disturbance of amino acid, fatty acids, lysophosphatidyl-choline and triacylglycerol in T2DM. We hereby make these technical validation results and the profiling dataset publicly available to the scientific community, showcasing its exceptional sensitivity and robustness as an invaluable tool for the comprehensive targeted metabolome analysis.

Streamlining Phenotype Classification and Highlighting Feature Candidates: A Screening Method for Non-Targeted Ion Mobility Spectrometry-Mass Spectrometry (IMS-MS) Data

Nontargeted analysis (NTA) is increasingly utilized for its ability to identify key molecular features beyond known targets in complex samples. NTA is particularly advantageous in exploratory studies aimed at identifying phenotype-associated features or molecules able to classify various sample types. However, implementing NTA involves extensive data analyses and labor-intensive annotations. To address these limitations, we developed a rapid data screening capability compatible with NTA data collected on a liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) platform that allows for sample classification while highlighting potential features of interest. Specifically, this method aggregates the thousands of IMS-MS spectra collected across the LC space for each sample and collapses the LC dimension, resulting in a single summed IMS-MS spectrum for screening. The summed IMS-MS spectra are then analyzed with a bootstrapped Lasso technique to identify key regions or coordinates for phenotype classification via support vector machines. Molecular annotations are then performed by examining the features present in the selected coordinates, highlighting potential molecular candidates. To demonstrate this summed IMS-MS screening approach, we applied it to clinical plasma lipidomic NTA data and exposomic NTA data from water sites with varying contaminant levels. Distinguishing coordinates were observed in both studies, enabling the evaluation of phenotypic molecular annotations and resulting in screening models capable of classifying samples with up to a 25% increase in accuracy compared to models using annotated data.

An Untargeted Lipidomics Workflow Incorporating High-Resolution Demultiplexing (HRdm) Drift Tube Ion Mobility-Mass Spectrometry

Global discovery lipidomics can provide comprehensive chemical information toward understanding the intricacies of metabolic lipid disorders such as dyslipidemia; however, the isomeric complexity of lipid species remains an analytical challenge. Orthogonal separation strategies, such as ion mobility (IM), can be inserted into liquid chromatography-mass spectrometry (LC-MS) untargeted lipidomic workflows for additional isomer separation and high-confidence annotation, and the emergence of high-resolution ion mobility (HRIM) strategies provides marked improvements to the resolving power (Rp > 200) that can differentiate small structural differences characteristic of isomers. One such HRIM strategy, high-resolution demultiplexing (HRdm), utilizes multiplexed drift tube ion mobility spectrometry (DTIMS) with post-acquisition algorithmic deconvolution to access high IM resolutions while retaining the measurement precision inherent to the drift tube technique; however, HRdm has yet to be utilized in untargeted studies. In this manuscript, a proof-of-concept study using ATP10D dysfunctional murine models was investigated to demonstrate the utility of HRdm-incorporated untargeted lipidomic analysis pipelines. Total lipid features were found to increase by 2.5-fold with HRdm compared to demultiplexed DTIMS as a consequence of more isomeric lipids being resolved. An example lipid, PC 36:5, was found to be significantly higher in dysfunctional ATP10D mice with two resolved peaks observed by HRdm that were absent in both the functional ATP10D mice and the standard demultiplexed DTIMS acquisition mode. The benefits of utilizing HRdm for discerning isomeric lipids in untargeted workflows have the potential to enhance our analytical understanding of lipids related to disease complexity and biologically relevant studies.

Exploring Ion Mobility Mass Spectrometry Data File Conversions to Leverage Existing Tools and Enable New Workflows

Ion mobility (IM) is often combined with LC-MS experiments to provide an additional dimension of separation for complex sample analysis. While highly complex samples are better characterized by the full dimensionality of LC-IM-MS experiments to uncover new information, downstream data analysis workflows are often not equipped to properly mine the additional IM dimension. For many samples the data acquisition benefits of including IM separations are all that is necessary to uncover sample information and the full dimensionality of the data is not required for data analysis. Postacquisition reduction and adaptation of the dimensions of LC-IM-MS and IM-MS experiments into an LC-MS format opens the possibility to use a plethora of existing software tools. In this work, we developed data file conversion tools to reduce the complexity of IM data analysis. Three data file transformations are introduced in the PNNL PreProcessor software: (1) mapping the IM axis to the LC axis for IM-MS data, (2) converting the drift time vs m/z space to CCS/z vs m/z space, and (3) transforming All Ions IM/MS mobility aligned fragmentation data to a standard LC-MS DDA data file format. These new data file conversions are demonstrated with corresponding lipidomics and proteomics workflows that leverage existing LC-MS data analysis software to highlight the benefits of the data transformations.

Potential of atmospheric pressure ionization sources for the analysis of free fatty acids in clinical and biological samples by gas chromatography-mass spectrometry

Because of the central role of fatty acids in biological systems, their accurate quantification is still important. However, the impact of the complex matrix of biologically and clinically relevant samples such as plasma, serum, or cells makes the analysis still challenging, especially, when free non-esterified fatty acids have to be quantified. Here we developed and characterized a novel GC-MS method using pentafluorobenzyl bromide as a derivatization agent and compared different ionization techniques such as atmospheric pressure chemical ionization (APCI), atmospheric pressure chemical photoionization (APPI), and negative ion chemical ionization (NICI). The GC-APCI-MS showed the lowest limits of detection from 30 to 300 nM for a broad range of fatty acids and a similar response for various fatty acids from a chain length of 10 to 20 carbon atoms. This allows the number of internal standards necessary for accurate quantification to be reduced. Moreover, the use of pentafluorobenzyl bromide allows the direct derivatization of free fatty acids making them accessible for GC-MS analysis without labor-intense sample pretreatment.

Recent developments in data acquisition, treatment and analysis with ion mobility-mass spectrometry for lipidomics

Lipids are involved in many biological processes and their study is constantly increasing. To identify a lipid among thousand requires of reliable methods and techniques. Ion Mobility (IM) can be coupled with Mass Spectrometry (MS) to increase analytical selectivity in lipid analysis of lipids. IM-MS has experienced an enormous development in several aspects, including instrumentation, sensitivity, amount of information collected and lipid identification capabilities. This review summarizes the latest developments in IM-MS analyses for lipidomics and focusses on the current acquisition modes in IM-MS, the approaches for the pre-treatment of the acquired data and the subsequent data analysis. Methods and tools for the calculation of Collision Cross Section (CCS) values of analytes are also reviewed. CCS values are commonly studied to support the identification of lipids, providing a quasi-orthogonal property that increases the confidence level in the annotation of compounds and can be matched in CCS databases. The information contained in this review might be of help to new users of IM-MS to decide the adequate instrumentation and software to perform IM-MS experiments for lipid analyses, but also for other experienced researchers that can reconsider their routines and protocols. This article is protected by copyright. All rights reserved.

Supercritical Fluid Chromatography Coupled with Drift Time Ion Mobility Quadrupole Time-of-Flight Mass Spectrometry as a Tool for Lipid Characterization of HepG2 Cells

Lipidomic studies are often conducted using shotgun mass spectrometry (MS) or reversed-phase liquid chromatography coupled with MS (LC–MS). However, chromatographic separation offers several advantages such as an additional identification parameter (retention time), lower ion suppression, and separation of isobaric species. In contrast, quantification is more difficult because ion suppression is not the same over the whole analysis, and as a consequence more standards are needed to compensate for this. Supercritical fluid chromatography (SFC) offers orthogonal separation compared to reversed-phase LC. While the separation of lipids in reversed-phase LC is mainly based on the length of the carbon chain and the number of double bonds, lipids in SFC are mainly separated according to their lipid classes, which simplifies quantification with standards. In this study, SFC coupled with drift time ion mobility quadrupole time-of-flight mass spectrometry (DTIMS-QTOF-MS)was used to characterize the HepG2 lipidome.