Lee A. Gethings

Introduction: Accurate metabolite identification remains a major challenge in untargeted metabolomics due to overlapping signals, isomeric compounds, and insufficient mass resolution. The multi-reflecting time-of-flight (MRT) platform provides mass resolution exceeding 200,000 Full Width at Half Maximum and sub-ppm mass accuracy, enabling detailed isotopic fine structure analysis. Objectives: The performance of the MRT platforms in identifying lipids and metabolites was evaluated using selected serum samples from a group of hospitalized COVID-19 patients. Methods: Lipids and polar metabolites were extracted from human serum samples from the Manchester Asthma, Allergy and Thoracic Surgery Biobank and analysed using the MRT platform with data-independent acquisition. Results: The MRT platform facilitated the resolution of overlapping lipid species and improved annotation confidence. In a pilot cohort ( n = 8), metabolomic differences associated with disease severity were observed, alongside annotation of clinically relevant metabolites including sulphated bile acids and retained iohexol associated with renal dysfunction. Conclusions: These findings demonstrate that MRT platform enhances confidence in metabolite identification and supports high-throughput metabolomics, offering significant potential for biomarker discovery in clinical studies.

Rationale: High‐resolution mass spectrometry is routinely used for the analysis of complex samples in pharmaceutical, environmental, and omics related studies. Such applications demand instrumentation to be capable of combining sub‐ppm mass accuracy, high resolving power, rapid full m/z range acquisition over a wide dynamic range. Methods: Achieving the above requirements places constraints on analyzer design and performance. Multi‐reflecting time‐of‐flight (MRT) based analyzers have previously been reported as a means of significantly extending the effective flight path in compact TOF designs. Here, further instrument and functionality advances in a compact MRT mass spectrometer design are described. Results: The impact of these enhancements was assessed for targeted and non‐targeted omics applications, examining the impact of acquisition speed on resolving power, dynamic range including limits of quantitation, and quantitative precision. Conclusion: The results obtained characterize the performance of the enhanced design features of a compact MRT mass spectrometer. Operation at elevated acquisition rates up to 200 Hz was observed without loss in resolving power, isotopic ratio accuracy or quantitative precision.

A bstract: High-resolution mass spectrometry is routinely used for the analysis of complex samples in pharmaceutical, environmental, and omics related studies. Such applications require instrumentation to be capable of combining sub-ppm mass accuracy, high resolving power, rapid full m/z range acquisition, and a wide dynamic range. Achieving these requirements simultaneously places constraints on analyzer design and performance. Multi-reflecting time-of-flight (MRT) based analyzers have been previously reported as a means of extending effective flight path length in compact TOF designs. Here, further instrument and functionality advances in a compact MRT mass spectrometer design are described and the impact of these enhancements is demonstrated for omics applications.

Mass spectrometry imaging reveals lipid composition of intestinal cell lines.

Identification of features with high levels of confidence in liquid chromatography–mass spectrometry (LC–MS) lipidomics research is an essential part of biomarker discovery, but existing software platforms can give inconsistent results, even from identical spectral data. This poses a clear challenge for reproducibility in biomarker identification. In this work, we illustrate the reproducibility gap for two open-access lipidomics platforms, MS DIAL and Lipostar, finding just 14.0% identification agreement when analyzing identical LC–MS spectra using default settings. Whilst the software platforms performed more consistently using fragmentation data, agreement was still only 36.1% for MS2 spectra. This highlights the critical importance of validation across positive and negative LC–MS modes, as well as the manual curation of spectra and lipidomics software outputs, in order to reduce identification errors caused by closely related lipids and co-elution issues. This curation process can be supplemented by data-driven outlier detection in assessing spectral outputs, which is demonstrated here using a novel machine learning approach based on support vector machine regression combined with leave-one-out cross-validation. These steps are essential to reduce the frequency of false positive identifications and close the reproducibility gap, including between software platforms, which, for downstream users such as bioinformaticians and clinicians, can be an underappreciated source of biomarker identification errors.

Amino acids (AAs) and their metabolites are important building blocks, energy sources, and signaling molecules associated with various pathological phenotypes. The quantification of AA and tryptophan (TRP) metabolites in human serum and plasma is therefore of great diagnostic interest. Therefore, robust, reproducible sample extraction and processing workflows as well as rapid, sensitive absolute quantification are required to identify candidate biomarkers and to improve screening methods. We developed a validated semi-automated robotic liquid extraction and processing workflow and a rapid method for absolute quantification of 20 free, underivatized AAs and six TRP metabolites using dual-column U(H)PLC-MRM-MS. The extraction and sample preparation workflow in a 96-well plate was optimized for robust, reproducible high sample throughput allowing for transfer of samples to the U(H)PLC autosampler directly without additional cleanup steps. The U(H)PLC-MRM-MS method, using a mixed-mode reversed-phase anion exchange column with formic acid and a high-strength silica reversed-phase column with difluoro-acetic acid as mobile phase additive, provided absolute quantification with nanomolar lower limits of quantification within 7.9 min. The semi-automated extraction workflow and dual-column U(H)PLC-MRM-MS method was applied to a human prostate cancer study and was shown to discriminate between treatment regimens and to identify metabolites responsible for discriminating between healthy controls and patients on active surveillance.

There has been increasing interest in bacterial lipids in recent years due, in part, to their emerging role as molecular signalling molecules. Bacteroides thetaiotaomicron is an important member of the mammalian gut microbiota that has been shown to produce sphingolipids (SP) that pass through the gut epithelial barrier to impact host SP metabolism and signal into host inflammation pathways. B. thetaiotaomicron also produces a novel family of N-acyl amines (called glycine lipids) that are potent ligands of host Toll-like receptor 2 (TLR2). Here, we specifically examine the lipid signatures of four species of gut-associated Bacteroides. In total we identify 170 different lipids, and we report that the range and diversity of Bacteroides lipids is species specific. Multivariate analysis reveals that the differences in the lipid signatures are largely driven by the presence and absence of plasmalogens, glycerophosphoinositols and certain SP. Moreover, we show that, in B. thetaiotaomicron, mutations altering either SP or glycine lipid biosynthesis result in significant changes in the levels of other lipids, suggesting the existence of a compensatory mechanisms required to maintain the functionality of the bacterial membrane.

The metabolism and pharmacokinetics of fasiglifam (TAK-875, 2-[(3S)-6-[[3-[2,6-dimethyl-4-(3-methylsulfonylpropoxy)phenyl]phenyl]methoxy]-2,3-dihydro-1-benzofuran-3-yl]acetic acid), a selective fre...

There has been increasing interest in bacterial lipids in recent years due, in part, to their emerging role as molecular signalling molecules. Bacteroides thetaiotaomicron is an important member of the mammalian gut microbiota that has been shown to produce sphingolipids (SP) that pass through the gut epithelial barrier to impact host SP metabolism and signal into host inflammation pathways. B. thetaiotaomicron also produces a novel family of N-acyl amines (called glycine lipids) that are potent ligands of host Toll-like receptor 2 (TLR2). Here, we specifically examine the lipid signatures of 4 species of gut associated Bacteroides . In total we identify 170 different lipids and we report that the range and diversity of Bacteroides lipids is species-specific. Multi-variate analysis reveals that the differences in the lipid signatures are largely driven by the presence/absence of plasmalogens, glycerophosphoinositols and certain SP. Moreover, we show that, in B. thetaiotaomicron , mutations altering either SP or glycine lipid biosynthesis results in significant changes in the levels of other lipids suggesting the existence of compensatory mechanisms required to maintain the functionality of the bacterial membrane. Importance: Bacteroides are important beneficial members of the gut microbiome that produce lipids that can function as cross-kingdom signalling molecules. We describe, for the first time, a comprehensive and qualitative comparison of the lipid signatures of 4 important Bacteroides species. We identify a group of Bacteroides core lipids and uncover species-specific differences in plasmalogen, glycerophospholipid and SP metabolism with more subtle differences observed in glycine lipid production. This data will provide a useful platform for the further characterisation of the lipid-based host-microbe dialogue and the influence of microbial lipids on host health and disease states.