Coupling Mixed Mode Chromatography/ESI Negative MS Detection with Message-Passing Neural Network Modeling for Enhanced Metabolome Coverage and Structural Identification

A key unmet need in metabolomics continues to be the specific, selective, accurate detection of traditionally difficult to retain molecules including simple sugars, sugar phosphates, carboxylic acids, and related amino acids. Designed to retain the metabolites of central carbon metabolism, this Mixed Mode (MM) chromatography applies varied pH, salt concentration and organic content to a positively charged quaternary amine polyvinyl alcohol stationary phase. This MM method is capable of separating glucose from fructose, and four hexose monophosphates a single chromatographic run. Coupled to a QExactive Orbitrap Mass Spectrometer with negative ESI, linearity, LLOD, %CV, and mass accuracy were assessed using 33 metabolite standards. The standards were linear on average >3 orders of magnitude (R2 > 0.98 for 30/33) with LLOD < 1 pmole (26/33), median CV of 12% over two weeks, and median mass accuracy of 0.49 ppm. To assess the breadth of metabolome coverage and better define the structural elements dictating elution, we injected 607 unique metabolites and determined that 398 are well retained. We then split the dataset of 398 documented RTs into training and test sets and trained a message-passing neural network (MPNN) to predict RT from a featurized heavy atom connectivity graph. Unlike traditional QSAR methods that utilize hand-crafted descriptors or pre-defined structural keys, the MPNN aggregates atomic features across the molecular graph and learns to identify molecular subgraphs that are correlated with variations in RTs. For sugars, sugar phosphates, carboxylic acids, and isomers, the model achieves a predictive RT error of <2 min on 91%, 50%, 77%, and 72% of held-out compounds from these subsets, with overall root mean square errors of 0.11, 0.34, 0.18, and 0.53 min, respectively. The model was then applied to rank order metabolite IDs for molecular features altered by GLS2 knockout in mouse primary hepatocytes.

Retention dependences support highly confident identification of lipid species in human plasma by reversed-phase UHPLC/MS

Reversed-phase ultrahigh-performance liquid chromatography - mass spectrometry (RP-UHPLC/MS) method was developed with the aim to unambiguously identify a large number of lipid species from multiple lipid classes in human plasma. The optimized RP-UHPLC/MS method employed the C18 column with sub-2 micrometer particles with the total run time of 25 min. The chromatographic resolution was investigated with 42 standards from 18 lipid classes. The UHPLC system was coupled to high-resolution quadrupole - time-of-flight (QTOF) mass analyzer using electrospray ionization (ESI) measuring full scan and tandem mass spectra (MS/MS) in positive- and negative-ion modes with high mass accuracy. Our identification approach was based on m/z values measured with mass accuracy within 5 ppm tolerance in the full scan mode, characteristic fragment ions in MS/MS, and regularity in chromatographic retention dependences for individual lipid species, which provides the highest level of confidence for reported identifications of lipid species including regioisomeric and other isobaric forms. The graphs of dependences of retention times on the carbon number or on the number of double bond(s) in fatty acyl chains were constructed to support the identification of lipid species in homologous lipid series. Our list of identified lipid species is also compared with previous publications investigating human blood samples by various MS based approaches. In total, we have reported more than 500 lipid species representing 26 polar and nonpolar lipid classes detected in NIST Standard reference material 1950 human plasma.

Orbitool: a software tool for analyzing online Orbitrap mass spectrometry data

The Orbitrap mass spectrometer has recently been proved to be a powerful instrument to accurately measure gas-phase and particle-phase organic compounds with a greater mass resolving power than other widely used online mass spectrometers in atmospheric sciences. We develop an open-source software tool (Orbitool, https://orbitrap.catalyse.cnrs.fr, last access: 4 February 2021) to facilitate the analysis of long-term online Orbitrap data. Orbitool can average long-term data while improving the mass accuracy by re-calibrating each mass spectrum, assign molecular formulae of compounds and their isotopes to measured signals, and export time series and mass defect plots. The noise reduction procedure in Orbitool can separate signal peaks from noise and reduce the computational and storage expenses. Chemical ionization Orbitrap data from laboratory experiments on ozonolysis of monoterpenes and ambient measurements in urban Shanghai were used to test Orbitool. For the test dataset, the average mass accuracy was improved from <2 to <0.5 ppm by mass calibrating each spectrum. The denoising procedure removed 97 % of the noise peaks from a spectrum averaged for 30 min while maintaining the signal peaks, substantially helping the automatic assignment of unknown species. To illustrate the capabilities of Orbitool, we used the most challenging and complex dataset we have collected so far, which consists of ambient gas-phase measurements in urban Shanghai. These tests showed that Orbitool was able to automatically assign hundreds of molecular formulae as well as their isotopes with high accuracy.

Mass Spectrometry Imaging Using Dynamically Harmonized FT-ICR at Million Resolving Power: Rationalizing and Optimizing Sample Preparation and Instrumental Parameters

<p><i>MALDI mass spectrometry imaging (MSI) is a powerful analytical method giving access to the 2D localizations of compounds in a thin section of a sample. To properly discern isobaric compounds in complex biological samples, dynamically harmonized ICR cell (ParaCell©) has been introduce to achieve extreme spectral resolution. However, high resolution MS images realized on a 9.4T FTICR High resolution instrument with recommended parameters suffered from an abnormal shifting of m/z ratios pixel to pixel. Resulting datasets show poor mass accuracy measurements and resolutions under estimations. By following the behavior of the Total Ion Current in function of the number of laser shots, the abnormal mass shifting phenomenon has been linked to the stability of the Total Ion Current (TIC) during images acquisitions. An optimization of laser parameters is proposed in order to limit the observed mass shift to retain machine specifications during MSI analyses. It is also shown that the method has been successfully employed to realize quality MS images with resolution above 1,000,000 in the lipid mass range across the whole image.</i></p>

Mass Spectrometry Imaging Using Dynamically Harmonized FT-ICR at Million Resolving Power: Rationalizing and Optimizing Sample Preparation and Instrumental Parameters

<p><i>MALDI mass spectrometry imaging (MSI) is a powerful analytical method giving access to the 2D localizations of compounds in a thin section of a sample. To properly discern isobaric compounds in complex biological samples, dynamically harmonized ICR cell (ParaCell©) has been introduce to achieve extreme spectral resolution. However, high resolution MS images realized on a 9.4T FTICR High resolution instrument with recommended parameters suffered from an abnormal shifting of m/z ratios pixel to pixel. Resulting datasets show poor mass accuracy measurements and resolutions under estimations. By following the behavior of the Total Ion Current in function of the number of laser shots, the abnormal mass shifting phenomenon has been linked to the stability of the Total Ion Current (TIC) during images acquisitions. An optimization of laser parameters is proposed in order to limit the observed mass shift to retain machine specifications during MSI analyses. It is also shown that the method has been successfully employed to realize quality MS images with resolution above 1,000,000 in the lipid mass range across the whole image.</i></p>

Orbitool: A software tool for analyzing online Orbitrap mass spectrometry data

The Orbitrap mass spectrometer has recently been proved to be a powerful instrument to accurately measure gas-phase and particle-phase organic compounds with a greater mass resolving power than other widely-used online mass spectrometers in atmospheric sciences. We develop an open-source software tool (Orbitool, https://orbitrap.catalyse.cnrs.fr) to facilitate the analysis of long-term online Orbitrap data. Orbitool can average long-term data while maintaining the mass accuracy by re-calibrating each mass spectrum, identify chemical compositions and isotopes of measured signals, and export time series and mass defect plots. The noise reduction procedure in Orbitool can separate signal peaks from noise and greatly reduce the computational and storage expenses. Chemical-ionization Orbitrap data from laboratory experiments on ozonolysis of monoterpenes and ambient measurements in urban Shanghai were used to successfully test Orbitool. For the test dataset, the average mass accuracy was improved from

Petroleomics: Tools, Challenges, and Developments

The detailed molecular characterization of petroleum-related samples by mass spectrometry, often referred to as petroleomics, continues to present significant analytical challenges. As a result, petroleomics continues to be a driving force for the development of new ultrahigh resolution instrumentation, experimental methods, and data analysis procedures. Recent advances in ionization, resolving power, mass accuracy, and the use of separation methods, have allowed for record levels of compositional detail to be obtained for petroleum-related samples. To address the growing size and complexity of the data generated, vital software tools for data processing, analysis, and visualization continue to be developed. The insights gained impact upon the fields of energy and environmental science and the petrochemical industry, among others. In addition to advancing the understanding of one of nature's most complex mixtures, advances in petroleomics methodologies are being adapted for the study of other sample types, resulting in direct benefits to other fields.