Advanced tandem mass spectrometry in metabolomics and lipidomics-methods and applications

Comprehensive untargeted polar metabolite analysis using solvent switching liquid chromatography tandem mass spectrometry

Metabolomics analyses enable the examination and identification of endogenous biochemical reaction products, revealing information on the metabolic pathways and processes active within a living cell or organism. Determination of metabolic shifts can provide important information on a treatment or disease. Unlike other omics fields that typically have analytes of the same chemical class with common building blocks, those that fall under the nomenclature of metabolites encompass a wide array of different compounds with very diverse physiochemical properties. Development of a comprehensive metabolomic pipeline therefore can be a troublesome and complicated process for the analyst. Often single liquid chromatography-mass spectrometry methods on unfractionated samples are carried out in order to be time-efficient, however this could potentially produce data with a low number of identifiable metabolites. In the present studies, we developed a comprehensive polar metabolomics pipeline for cell-based metabolomics. SH-SY5Y neuroblastoma cells were selected as the sample matrix for method development since they are one of the most widely used cell lines for human neurotoxicity studies. This was accomplished by investigating and optimising different mass spectrometry source and chromatographic conditions to enhance the signal of polar metabolites. Optimised hydrophilic interaction liquid chromatography (HILIC) based metabolomic methods at different pH values were examined in positive, negative, and polarity switching modes to determine which combination yielded the highest number of confidently identified metabolites. Additionally, the use of sequentially running two methods was also compared to determine the degree of overlap and whether there is merit in running two separate methods on one sample. It was determined that solvent switching between two optimised methods, acidic chromatographic conditions in positive mode and basic chromatographic conditions in negative mode, yielded the highest number of unique identifiable metabolites. This could be run in a single analytical batch due to the large pH range of the column. A quick switch method in-between each method allowed both conditioning the column and preparation of the MS source conditions for the sequential method.

Isomer-resolved characterization of acylcarnitines reveals alterations in type 2 diabetes

BACKGROUND

Acylcarnitines (CARs) are metabolites of fatty acids that play crucial roles in various cellular energy metabolism pathways. The structural diversity of CAR species arises from several modifications localized on the fatty acyl chain and there is currently a lack of reports characterizing these detailed structures. High-performance liquid chromatography (HPLC)-electrospray mass spectrometry (ESI-MS) is the common tool for CARs analysis.

RESULTS

In this study, we improved the MS detection signals of CARs by adding NH4HCO3 as buffer in the mobile phase of LC system. We demonstrated that electron activated dissociation (EAD) on the ZenoTOF 7600 system is capable of localizing the hydroxyl group and methyl branching position in CARs. The benzophenone Paternò-Büchi (PB) reaction was used for derivatizing the carbon-carbon double bond (CC). The capability of profiling CARs with detailed structural information was demonstrated by analyzing complex lipid extracts from mouse plasma. Our results also provided visualization of isomers composition, including branched chain isomers of CAR 4:0 and CAR 5:0 and CC location isomers of unsaturated CARs. Notably, we observed significant changes in the relative compositions of branched-chain isomers of CAR 5:0 and CC location isomers of several unsaturated CARs in mouse plasma samples from type 2 diabetes (T2D) compared to normal controls, suggesting their potential as diagnostic indicators for T2D.

SIGNIFICANCE

In this work, we enhanced the limit of detection for acylcarnitine species by incorporating ammonium bicarbonate into the LC system. The CC positions in the acyl chain of CARs were identified using Paternò-Büchi (PB) derivatization coupled with tandem mass spectrometry. Modifications such as methyl branching and hydroxyl groups along the acyl chain were localized through Electron-Activated Dissociation (EAD) on the Zeno-TOF 7600 system.

Metabolic characteristics of benign and malignant pulmonary nodules and establishment of invasive lung adenocarcinoma model by high-resolution mass spectrometry

BACKGROUND

Increasing pulmonary nodule presentations in lung adenocarcinoma patients reveal diagnostic limitations of CT-based invasiveness assessment. The critical unmet need lies in developing non-invasive biomarkers differentiating invasive adenocarcinoma from premalignant lesions and benign nodules, while characterizing metabolic trajectory from health to metastatic disease.

METHODS

Untargeted metabolomics analyzed plasma samples from 102 subjects stratified into four cohorts: confirmed adenocarcinoma (n = 35), benign nodules (n = 22), precursor lesions (n = 24), and healthy controls (n = 21). Multivariate analysis identified discriminative metabolites for constructing an infiltration prediction model.

RESULTS

Three diagnostic groups exhibited distinct metabolic profiles. Hexaethylene glycol, tetraethylene glycol, and Met-Thr showed stage-dependent concentration gradients. Progressive malignancy correlated with elevated levels of 41 metabolites. An eight-metabolite panel achieved AUC 0.933 (0.873-0.994) in distinguishing precursors from early malignancies, sustained through internal validation (AUC 0.934, 0.905-0.966).

CONCLUSIONS

Met-Thr depletion inversely correlates with malignancy progression, while eight-metabolite signatures demonstrate diagnostic potential for preoperative infiltration assessment in nodular adenocarcinoma.

Advances in Tandem Mass Spectrometry Imaging for Next-Generation Spatial Metabolomics

Spatial metabolomics based on mass spectrometry imaging (MSI) is a promising approach for fundamental biological research and disease biomarker discovery. It simultaneously reveals the spatial distributions of hundreds of metabolites across tissue sections. While previous MSI experiments predominantly rely on high-resolution mass analysis for metabolite annotation, the high specificity in resolving molecular structures is essential to distinguish isomers or isobars to obtain ultimate identities of the metabolites. This is also critical for correlating their biological functions with spatial distribution patterns. Tandem mass spectrometry (MS/MS) is effectively used to obtain molecular structural information and has been integrated into MSI for spatial mapping of structurally distinct biomolecules, though typically with low coverage. The main technical challenge in achieving high-coverage, high-structure-resolving spatial mapping of biomolecules lies in the limited amount of sample available from each tissue pixel in conventional MS/MS analysis, which restricts the number of MS/MS scans that can be conducted on the metabolite precursors of interest. In this Perspective, we highlight recent developments in advanced MS/MS imaging strategies aimed at achieving high-coverage spatial metabolomics.

In-depth characterization of acylcarnitines: utilizing nitroxide radical-directed dissociation in tandem mass spectrometry

Acylcarnitines (ACs) are metabolic intermediates of fatty acids playing important roles in regulating cellular energy and lipid metabolism. The large structural diversity of ACs arises from variations in acyl chain length and the presence of chemical modifications, such as methyl branching, desaturation, hydroxylation, and carboxylation. Numerous studies have demonstrated that these structural isomers of ACs function as biomarkers for a variety of diseases. However, conventional tandem mass spectrometry (MS/MS) via low-energy collision-induced dissociation (CID) faces challenges in distinguishing these isomers. In this study, we report a radical-directed dissociation (RDD) approach for characterization of the intrachain modifications within ACs. The method involves derivatizing ACs with O-benzylhydroxylamine (O-BHA), followed by MS2 CID to produce a nitroxide radical for subsequent RDD along the fatty acyl chain. The above RDD approach was employed on a cyclic ion mobility spectrometry (cIMS) and reversed-phase liquid chromatography (RPLC), enabling the identification and relative quantification of branched chain isomers of ACs. By derivatizing carboxylated ACs with O-BHA, their mass is shifted to a higher region, thereby facilitating their separation from the isobars of hydroxylated ACs. Furthermore, this RDD method effectively allows for the assignment and localization of C = C and hydroxylation positions. This RDD approach has been applied for in-depth profiling of ACs in mice plasma extracts.

OzMALDI: A Gas-Phase, In-Source Ozonolysis Reaction for Efficient Double-Bond Assignment in Mass Spectrometry Imaging with Matrix-Assisted Laser Desorption/Ionization

Lipids make up an important class of biomolecules with diverse structures and varied chemical functions. This diversity is a major challenge in chemical analysis and limits our understanding of biological functions and regulation. A major way lipid isomers differ is by double-bond (db) position, and analyzing db-isomers is especially challenging for mass spectrometry imaging (MSI). Ozonolysis can be used to determine the db-position and has been paired with MSI before. However, previous techniques require increased analysis time to allow for gas-phase reactions within an ion trap or ion mobility cell or additional sample preparation time to allow for offline ozonation. Here, we introduce a new ozonolysis method inside the matrix-assisted laser desorption-ionization (MALDI) source, termed OzMALDI, that simultaneously produces ozonides from all unsaturated lipids. This allows us to determine db-positions without adding additional reaction time while maintaining the high mass resolution provided by Orbitrap MS. This new technique is especially effective at determining multiple db-positions in lipids containing polyunsaturated fatty acids, which is a limitation of many previous techniques. OzMALDI-MSI was applied to the analysis of rat brain and genetically engineered Camelina and soybean seed samples, demonstrating the utility of this method and uncovering novel biological information.

Imaging and spatially resolved mass spectrometry applications in nephrology

The application of spatially resolved mass spectrometry (MS) and MS imaging approaches for studying biomolecular processes in the kidney is rapidly growing. These powerful methods, which enable label-free and multiplexed detection of many molecular classes across omics domains (including metabolites, drugs, proteins and protein post-translational modifications), are beginning to reveal new molecular insights related to kidney health and disease. The complexity of the kidney often necessitates multiple scales of analysis for interrogating biofluids, whole organs, functional tissue units, single cells and subcellular compartments. Various MS methods can generate omics data across these spatial domains and facilitate both basic science and pathological assessment of the kidney. Optimal processes related to sample preparation and handling for different MS applications are rapidly evolving. Emerging technology and methods, improvement of spatial resolution, broader molecular characterization, multimodal and multiomics approaches and the use of machine learning and artificial intelligence approaches promise to make these applications even more valuable in the field of nephology. Overall, spatially resolved MS and MS imaging methods have the potential to fill much of the omics gap in systems biology analysis of the kidney and provide functional outputs that cannot be obtained using genomics and transcriptomic methods.

A Machine-Learned "Chemical Intuition" to Overcome Spectroscopic Data Scarcity

Machine learning models for predicting IR spectra of molecular ions (infrared ion spectroscopy, IRIS) have yet to be reported owing to the relatively sparse experimental data sets available. To overcome this limitation, we employ the Graphormer-IR model for neutral molecules as a knowledgeable starting point and then employ transfer learning to refine the model to predict the spectra of gaseous ions. A library of 10,336 computed spectra and a small data set of 312 experimental IRIS spectra is used for model fine-tuning. Nonspecific global graph encodings that describe the molecular charge state (i.e., (de)protonation, sodiation), combined with an additional transfer learning step that considers computed spectra for ions, improved model performance. The resulting Graphormer-IRIS model yields spectra that are 21% more accurate than those produced by commonly employed DFT quantum chemical models, while capturing subtle phenomena such as spectral red-shifts due to sodiation. Dimensionality reduction of model embeddings demonstrates derived "chemical intuition" of functional groups, trends in molecular electron density, and the location of charge sites. Our approach will enable fast IRIS predictions for determining the structures of unknown small molecule analytes (e.g., metabolites, lipids) present in biological samples.

Microbiota-Gut-Brain Axis: Mass-Spectrometry-Based Metabolomics in the Study of Microbiome Mediators-Stress Relationship

The microbiota-gut-brain axis is a complex bidirectional communication system that involves multiple interactions between intestinal functions and the emotional and cognitive centers of the brain. These interactions are mediated by molecules (metabolites) produced in both areas, which are considered mediators. To shed light on this complex mechanism, which is still largely unknown, a reliable characterization of the mediators is essential. Here, we review the most studied metabolites in the microbiota-gut-brain axis, the metabolic pathways in which they are involved, and their functions. This review focuses mainly on the use of mass spectrometry for their determination, reporting on the latest analytical methods, their limitations, and future perspectives. The analytical strategy for the qualitative-quantitative characterization of mediators must be reliable in order to elucidate the molecular mechanisms underlying the influence of the above-mentioned axis on stress resilience or vulnerability.

Single cell lipid biology

Lipids are major cell constituents endowed with astonishing structural diversity. The pathways responsible for the assembly and disposal of different lipid species are energetically demanding, and genes encoding lipid metabolic factors and lipid-related proteins comprise a sizable fraction of our coding genome. Despite the importance of lipids, the biological significance of lipid structural diversity remains largely obscure. Recent technological developments have enabled extensive lipid analysis at the single cell level, revealing unexpected cell-cell variability in lipid composition. This new evidence suggests that lipid diversity is exploited in multicellularity and that lipids have a role in the establishment and maintenance of cell identity. In this review, we highlight the emerging concepts and technologies in single cell lipid analysis and the implications of this research for future studies.

XCMS-METLIN: data-driven metabolite, lipid, and chemical analysis

In this Correspondence, G. Siuzdak and colleagues present XCMS-METLIN, an extensive resource for metabolomics, lipidomics, and chemical analysis.

Online Direct Infusion Mass Spectrometry of Liquid-Liquid Extraction Phases for Metabolite and Lipid Profiling with the Direct Infusion Probe

Background/Objectives: Profiling of metabolites and lipids in biological samples can provide invaluable insights into life-sustaining chemical processes. The ability to detect both metabolites and lipids in the same sample can enhance these understandings and connect cellular dynamics. However, simultaneous detection of metabolites and lipids is generally hampered by chromatographic systems tailored to one molecular type. This void can be filled by direct infusion mass spectrometry (MS), where all ionizable molecules can be detected simultaneously. However, in direct infusion MS, the high chemical complexity of biological samples can introduce limitations in detectability due to matrix effects causing ionization suppression. Methods: Decreased sample complexity and increased detectability and molecular coverage was provided by combining our direct infusion probe (DIP) with liquid-liquid extraction (LLE) and directly sampling the different phases for direct infusion. Three commonly used LLE methods for separating lipids and metabolites were evaluated. Results: The butanol-methanol (BUME) method was found to be preferred since it provides high molecular coverage and have low solvent toxicity. The established BUME DIP-MS method was used as a fast and sensitive analysis tool to study chemical changes in insulin-secreting cells upon glucose stimulation. By analyzing the metabolome at distinct time points, down to 1-min apart, we found high dynamics of the intracellular metabolome. Conclusions: The rapid workflow with LLE DIP-MS enables higher sensitivity of phase separated metabolites and lipids. The application of BUME DIP-MS provides novel information on the dynamics of the intracellular metabolome of INS-1 during the two phases of insulin release for both metabolite and lipid classes.

Untargeted metabolomics analysis of cerebrospinal fluid in patients with leptomeningeal metastases from non-small cell lung cancer

OBJECTIVE

To explore and analyze the diagnostic value of metabolic markers in cerebrospinal fluid (CSF) in leptomeningeal metastases (LM) of non-small cell lung cancer (NSCLC).

METHODS

Forty-six CSF samples from patients with NSCLC-LM were collected. Another 48 CSF samples from patients with nonmalignant neurological diseases were selected as control group. Metabolomic analysis of CSF was performed by high-performance liquid chromatography-mass spectrometry. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were applied for modeling. A multi-criteria evaluation system (variable importance value >1, multiple of change >2 and P < 0.05 for univariate analysis) was used to find differential metabolites between two groups. The subject working characteristic curves and pathway enrichment analysis were used to screen metabolites and pathways associated with NSCLC-LM.

RESULTS

The PCA model and OPLS-DA model showed good overall data quality. Thirty endogenous differential metabolites were screened, and six potential biomarkers were further identified, including tyrosine (t = 3.37, P = 0.024, AUC = 0.967), phenylalanine (t = 3.98, P < 0.001, AUC = 0.992), pyruvate (t = 4.48, P < 0.001, AUC = 0.976), tryptophan (t = -2.5, P = 0.014, AUC = 0.935), adenosine monophosphate (t = -6.13, P < 0.001, AUC = 0.932) and glucose (t = -4.00, P < 0.001, AUC = 0.993). Thirty differential metabolites screened were subjected to metabolic pathway enrichment analysis and matched to 20 relevant metabolic pathways, of which the four most likely to cause metabolite changes were as follows: glycolysis and sugar metabolism synthesis, pyruvate metabolism, phenylalanine metabolism, and phenylalanine, tyrosine and tryptophan biosynthesis.

CONCLUSIONS

Untargeted metabolomics can effectively screen for CSF metabolites specific to NSCLC-LM patients, and six potential metabolites and their metabolic pathways might be involved in the pathogenesis of NSCLC-LM.

Cross-Validation of Lipid Structure Assignment Using Orthogonal Ion Activation Modalities on the Same Mass Spectrometer

The onset and progression of cancer is associated with changes in the composition of the lipidome. Therefore, better understanding of the molecular mechanisms of these disease states requires detailed structural characterization of the individual lipids within the complex cellular milieu. Recently, changes in the unsaturation profile of membrane lipids have been observed in cancer cells and tissues, but assigning the position(s) of carbon-carbon double bonds in fatty acyl chains carried by membrane phospholipids, including the resolution of lipid regioisomers, has proven analytically challenging. Conventional tandem mass spectrometry approaches based on collision-induced dissociation of ionized glycerophospholipids do not yield spectra that are indicative of the location(s) of carbon-carbon double bonds. Ozone-induced dissociation (OzID) and ultraviolet photodissociation (UVPD) have emerged as alternative ion activation modalities wherein diagnostic product ions can enable de novo assignment of position(s) of unsaturation based on predictable fragmentation behaviors. Here, for the first time, OzID and UVPD (193 nm) mass spectra are acquired on the same mass spectrometer to evaluate the relative performance of the two modalities for lipid identification and to interrogate the respective fragmentation pathways under comparable conditions. Based on investigations of lipid standards, fragmentation rules for each technique are expanded to increase confidence in structural assignments and exclude potential false positives. Parallel application of both methods to unsaturated phosphatidylcholines extracted from isogenic colorectal cancer cell lines provides high confidence in the assignment of multiple double bond isomers in these samples and cross-validates relative changes in isomer abundance.

Studying the Intrinsic Reactivity of Chromanes by Gas-Phase Infrared Spectroscopy

Tandem mass spectrometry is routinely used for the structural analysis of organic molecules, but many fragmentation reactions are not well understood. Because several potential structures can correspond to a measured mass, the assignment of product ions is ambiguous using mass spectrometry alone. Here, we combine mass spectrometry with high-resolution gas-phase infrared spectroscopy and computational chemistry tools to identify product ion structures and derive collision-induced fragmentation mechanisms of the chromane derivatives Trolox and Methyltrolox. We find that protonated Trolox and Methyltrolox fragment identically via dehydration and decarbonylation, while deprotonated ions display substantially diverging reactivities. For deprotonated Methyltrolox, we observe unusual radical fragmentation reactions and suggest a [1,2]-Wittig rearrangement involving aryl migration in the gas phase. Overall, the combined experimental and theoretical approach presented here revealed complex proton dynamics and intramolecular rearrangement reactions, which expand our understanding on structure-reactivity relationships of isolated molecules in different protonation states.

Study on the correlation and difference of qualitative information among three types of UPLC-HRMS and potential generalization in metabolites annotation

The variation of qualitative information among different types of mainstream hyphenated instruments of ultra-performance liquid chromatography coupled to high-resolution mass spectrometry (UPLC-HRMS) makes data sharing and standardization, and further comparison of results consistency in metabolite annotation not easy to attain. In this work, a quantitative study of correlation and difference was first achieved to systematically investigate the variation of retention time (tR), precursor ion (MS1), and product fragment ions (MS2) generated by three typical UPLC-HRMS instruments commonly used in metabolomics area. In terms of the findings of systematic and correlated variation of tR, MS1, and MS2 between different instruments, a computational strategy for integrated metabolite annotation was proposed to reduce the influence of differential ions, which made full use of the characteristic (common) and non-common fragments for scoring assessment. The regular variations of MS2 among three instruments under four collision energy voltages of high, medium, low, and hybrid levels were respectively inspected with three technical replicates at each level. These discoveries could improve general metabolite annotation with a known database and similarity comparison. It should provide the potential for metabolite annotation to generalize qualitative information obtained under different experimental conditions or using instruments from various manufacturers, which is still a big headache in untargeted metabolomics. The mixture of standard compounds and serum samples with the addition of standards were applied to demonstrate the principle and performance of the proposed method. The results showed that it could be an optional strategy for general use in HRMS-based metabolomics to offset the difference in metabolite annotation. It has some potential in untargeted metabolomics.

Reproducible MS/MS library cleaning pipeline in matchms

Mass spectral libraries have proven to be essential for mass spectrum annotation, both for library matching and training new machine learning algorithms. A key step in training machine learning models is the availability of high-quality training data. Public libraries of mass spectrometry data that are open to user submission often suffer from limited metadata curation and harmonization. The resulting variability in data quality makes training of machine learning models challenging. Here we present a library cleaning pipeline designed for cleaning tandem mass spectrometry library data. The pipeline is designed with ease of use, flexibility, and reproducibility as leading principles.Scientific contributionThis pipeline will result in cleaner public mass spectral libraries that will improve library searching and the quality of machine-learning training datasets in mass spectrometry. This pipeline builds on previous work by adding new functionality for curating and correcting annotated libraries, by validating structure annotations. Due to the high quality of our software, the reproducibility, and improved logging, we think our new pipeline has the potential to become the standard in the field for cleaning tandem mass spectrometry libraries.

Spatially and temporally probing distinctive glycerophospholipid alterations in Alzheimer's disease mouse brain via high-resolution ion mobility-enabled sn-position resolved lipidomics

Dysregulated glycerophospholipid (GP) metabolism in the brain is associated with the progression of neurodegenerative diseases including Alzheimer's disease (AD). Routine liquid chromatography-mass spectrometry (LC-MS)-based large-scale lipidomic methods often fail to elucidate subtle yet important structural features such as sn-position, hindering the precise interrogation of GP molecules. Leveraging high-resolution demultiplexing (HRdm) ion mobility spectrometry (IMS), we develop a four-dimensional (4D) lipidomic strategy to resolve GP sn-position isomers. We further construct a comprehensive experimental 4D GP database of 498 GPs identified from the mouse brain and an in-depth extended 4D library of 2500 GPs predicted by machine learning, enabling automated profiling of GPs with detailed acyl chain sn-position assignment. Analyzing three mouse brain regions (hippocampus, cerebellum, and cortex), we successfully identify a total of 592 GPs including 130 pairs of sn-position isomers. Further temporal GPs analysis in the three functional brain regions illustrates their metabolic alterations in AD progression.

First Proof of Concept of a Click Inverse Electron Demand Diels-Alder Reaction for Assigning the Regiochemistry of Carbon-Carbon Double Bonds in Untargeted Lipidomics

Lipidomics by high-resolution mass spectrometry (HRMS) has become a prominent tool in clinical chemistry due to the proven connections between lipid dysregulation and the insurgence of pathologies. However, it is difficult to achieve structural characterization beyond the fatty acid level by HRMS, especially when it comes to the regiochemistry of carbon-carbon double bonds, which play a major role in determining the properties of cell membranes. Several approaches have been proposed for elucidating the regiochemistry of double bonds, such as derivatization before MS analysis by photochemical reactions, which have shown great potential for their versatility but have the unavoidable drawback of splitting the MS signal. Among other possible approaches for derivatizing electron-rich double bonds, the emerging inverse-electron-demand Diels-Alder (IEDDA) reaction with tetrazines stands out for its unmatchable kinetics and has found several applications in basic biology and protein imaging. In this study, a catalyst-free click IEDDA reaction was employed for the first time to pinpoint carbon-carbon double bonds in free and conjugated fatty acids. Fatty acid and glycerophospholipid regioisomers were analyzed alone and in combination, demonstrating that the IEDDA reaction had click character and allowed the obtention of diagnostic product ions following MS/MS fragmentation as well as the possibility of performing relative quantitation of lipid regioisomers. The IEDDA protocol was later employed in an untargeted lipidomics study on plasma samples of patients suffering from prostate cancer and benign prostatic conditions, confirming the applicability of the proposed reaction to complex matrices of clinical interest.

UPLC-Q-TOF/MS-Based Serum Metabolomics Reveals Potential Anti-tumor Mechanism of Banxia Xiexin Decoction in Colorectal Cancer Mice

OBJECTIVE

To clarify the potential mechanism of Banxia Xiexin Decoction (BXD) on colorectal cancer (CRC) from the perspective of metabolomics.

METHODS

Forty male C57BL/6 mice were randomly divided into normal control (NC), azoxymethane/dextran sulfate sodium (AOM/DSS) model, low-dose BXD (L-BXD), high-dose BXD (H-BXD) and mesalamine (MS) groups according to a random number table, 8 mice in each group. Colorectal cancer model was induced by AOM/DSS. BXD was administered daily at doses of 3.915 (L-BXD) and 15.66 g/kg (H-BXD) by gavage for consecutive 21 days, and 100 mg/kg MS was used as positive control. Following the entire modeling cycle, colon length of mice was measured and quantity of colorectal tumors were counted. The spleen and thymus index were determined by calculating the spleen/thymus weight to body weight. Inflammatory cytokine and changes of serum metabolites were analyzed by enzyme-linked immunosorbent assay kits and ultra performance liquid chromatography-quadrupole/time-of-flight mass spectrometry (UPLC-Q/TOF-MS), respectively.

RESULTS

Notably, BXD supplementation protected against weight loss, mitigated tumor formation, and diminished histologic damage in mice treated with AOM/DSS (P<0.05 or P<0.01). Moreover, BXD suppressed expression of serum inflammatory enzymes, and improved the spleen and thymus index (P<0.05). Compared with the normal group, 102 kinds of differential metabolites were screened in the AOM/DSS group, including 48 potential biomarkers, involving 18 main metabolic pathways. Totally 18 potential biomarkers related to CRC were identified, and the anti-CRC mechanism of BXD was closely related to D-glutamine and D-glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, arginine biosynthesis, nitrogen metabolism and so on.

CONCLUSION

BXD exerts partial protective effects on AOM/DSS-induced CRC by reducing inflammation, protecting organism immunity ability, and regulating amino acid metabolism.

Mass spectrometry for metabolomics analysis: Applications in neonatal and cancer screening

Chemical analysis by analytical instrumentation has played a major role in disease diagnosis, which is a necessary step for disease treatment. While the treatment process often targets specific organs or compounds, the diagnostic step can occur through various means, including physical or chemical examination. Chemically, the genome may be evaluated to give information about potential genetic outcomes, the transcriptome to provide information about expression actively occurring, the proteome to offer insight on functions causing metabolite expression, or the metabolome to provide a picture of both past and ongoing physiological function in the body. Mass spectrometry (MS) has been elevated among other analytical instrumentation because it can be used to evaluate all four biological machineries of the body. In addition, MS provides enhanced sensitivity, selectivity, versatility, and speed for rapid turnaround time, qualities that are important for instance in clinical procedures involving the diagnosis of a pediatric patient in intensive care or a cancer patient undergoing surgery. In this review, we provide a summary of the use of MS to evaluate biomarkers for newborn screening and cancer diagnosis. As many reviews have recently appeared focusing on MS methods and instrumentation for metabolite analysis, we sought to describe the biological basis for many metabolomic and additional omics biomarkers used in newborn screening and how tandem MS methods have recently been applied, in comparison to traditional methods. Similar comparison is done for cancer screening, with emphasis on emerging MS approaches that allow biological fluids, tissues, and breath to be analyzed for the presence of diagnostic metabolites yielding insight for treatment options based on the understanding of prior and current physiological functions of the body.

Integrating the analysis of human biopsies using post-translational modifications proteomics

Proteome diversities and their biological functions are significantly amplified by post-translational modifications (PTMs) of proteins. Shotgun proteomics, which does not typically survey PTMs, provides an incomplete picture of the complexity of human biopsies in health and disease. Recent advances in mass spectrometry-based proteomic techniques that enrich and study PTMs are helping to uncover molecular detail from the cellular level to system-wide functions, including how the microbiome impacts human diseases. Protein heterogeneity and disease complexity are challenging factors that make it difficult to characterize and treat disease. The search for clinical biomarkers to characterize disease mechanisms and complexity related to patient diagnoses and treatment has proven challenging. Knowledge of PTMs is fundamentally lacking. Characterization of complex human samples that clarify the role of PTMs and the microbiome in human diseases will result in new discoveries. This review highlights the key role of proteomic techniques used to characterize unknown biological functions of PTMs derived from complex human biopsies. Through the integration of diverse methods used to profile PTMs, this review explores the genetic regulation of proteoforms, cells of origin expressing specific proteins, and several bioactive PTMs and their subsequent analyses by liquid chromatography and tandem mass spectrometry.

Electron-activated dissociation (EAD) for the complementary annotation of metabolites and lipids through data-dependent acquisition analysis and feature-based molecular networking, applied to the sentinel amphipod Gammarus fossarum

The past decades have marked the rise of metabolomics and lipidomics as the -omics sciences which reflect the most phenotypes in living systems. Mass spectrometry-based approaches are acknowledged for both quantification and identification of molecular signatures, the latter relying primarily on fragmentation spectra interpretation. However, the high structural diversity of biological small molecules poses a considerable challenge in compound annotation. Feature-based molecular networking (FBMN) combined with database searches currently sets the gold standard for annotation of large datasets. Nevertheless, FBMN is usually based on collision-induced dissociation (CID) data, which may lead to unsatisfying information. The use of alternative fragmentation methods, such as electron-activated dissociation (EAD), is undergoing a re-evaluation for the annotation of small molecules, as it gives access to additional fragmentation routes. In this study, we apply the performances of data-dependent acquisition mass spectrometry (DDA-MS) under CID and EAD fragmentation along with FBMN construction, to perform extensive compound annotation in the crude extracts of the freshwater sentinel organism Gammarus fossarum. We discuss the analytical aspects of the use of the two fragmentation modes, perform a general comparison of the information delivered, and compare the CID and EAD fragmentation pathways for specific classes of compounds, including previously unstudied species. In addition, we discuss the potential use of FBMN constructed with EAD fragmentation spectra to improve lipid annotation, compared to the classic CID-based networks. Our approach has enabled higher confidence annotations and finer structure characterization of 823 features, including both metabolites and lipids detected in G. fossarum extracts.

Compound Similarity Network as a Novel Data Mining Strategy for High-Throughput Investigation of Degradation Pathways of Organic Pollutants in Industrial Wastewater Treatment

Identification of degradation products and pathways is crucial for investigating emerging pollutants and evaluation of wastewater treatment methods. Nontargeted analysis is a powerful tool to comprehensively investigate the degradation pathways of organic pollutants in real-world wastewater samples but often generates large data sets, making it difficult to effectively locate the exact information on interests. Herein, to efficiently establish the linkages among compounds in the same degradation pathways, we introduce a compound similarity network (CSN) as a novel data mining strategy for LC-MS-based nontargeted analysis of complex wastewater samples. Different from molecular networks that cluster compounds based on MS/MS spectra similarity, our CSN strategy harnesses molecular fingerprints to establish linkages among compounds and thus is spectra-independent. The effectiveness of CSN was demonstrated by nontargeted identification of degradation pathways and products of organic pollutants in leather industrial wastewater that underwent laboratory-scale activated carbon adsorption (ACD) and ozonation treatments. Utilizing CSN in interpreting nontargeted data, we tentatively annotated 4324 compounds in the untreated leather industrial wastewater, 3246 after ACD, and 3777 after ACD/ozonation. We located 145 potential degradation pathways of organic pollutants in the ACD/ozonation process using CSN and validated 7 pathways with 15 chemical standards. CSN also revealed 5 clusters of emerging pollutants, from which 3 compounds were selected for in vitro cytotoxicity study to evaluate their potential biohazards as new pollutants. As CSN offers an efficient way to connect massive compounds and to find multiple degradation pathways in a high-throughput manner, we anticipate that it will find wide applications in nontargeted analysis of diverse environmental samples.

An omics review and perspective of researches on intrahepatic cholestasis of pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is one of the common pregnancy complications that may threaten the health of both pregnant women and their fetuses. Hence, it is of vital importance to identify key moleculars and the associated functional pathways of ICP, which will help us to better understand the pathological mechanisms as well as to develop precise clinical biomarkers. The emerging and developing of multiple omics approaches enable comprehensive studies of the genome, transcriptome, proteome and metabolome of clinical samples. The present review collected and summarized the omics based studies of ICP, aiming to provide an overview of the current progress, limitations and future directions. Briefly, these studies covered a broad range of research contents by the comparing of different experimental groups including ICP patients, ICP subtypes, ICP fetuses, ICP models and other complications. Correspondingly, the studied samples contain various types of clinical samples, in vitro cultured tissues, cell lines and the samples from animal models. According to the main research objectives, we further categorized these studies into two groups: pathogenesis and diagnosis analyses. The pathogenesis studies identified tens of functional pathways that may represent the key regulatory events for the occurrence, progression, treatment and fetal effects of ICP. On the other hand, the diagnosis studies tested more than 40 potential models for the early-prediction, diagnosis, grading, prognosis or differential diagnosis of ICP. Apart from these achievements, we also evaluated the limitations of current studies, and emphasized that many aspects of clinical characteristics, sample processing, and analytical method can greatly affect the reliability and repeatability of omics results. Finally, we also pointed out several new directions for the omics based analyses of ICP and other perinatal associated conditions in the future.

Towards personalized genome-scale modeling of inborn errors of metabolism for systems medicine applications

Inborn errors of metabolism (IEMs) are a group of more than 1000 inherited diseases that are individually rare but have a cumulative global prevalence of 50 per 100,000 births. Recently, it has been recognized that like common diseases, patients with rare diseases can greatly vary in the manifestation and severity of symptoms. Here, we review omics-driven approaches that enable an integrated, holistic view of metabolic phenotypes in IEM patients. We focus on applications of Constraint-based Reconstruction and Analysis (COBRA), a widely used mechanistic systems biology approach, to model the effects of inherited diseases. Moreover, we review evidence that the gut microbiome is also altered in rare diseases. Finally, we outline an approach using personalized metabolic models of IEM patients for the prediction of biomarkers and tailored therapeutic or dietary interventions. Such applications could pave the way towards personalized medicine not just for common, but also for rare diseases.

Metabolomics and mitochondrial dysfunction in cardiometabolic disease

Circulating metabolites are indicators of systemic metabolic dysfunction and can be detected through contemporary techniques in metabolomics. These metabolites are involved in numerous mitochondrial metabolic processes including glycolysis, fatty acid β-oxidation, and amino acid catabolism, and changes in the abundance of these metabolites is implicated in the pathogenesis of cardiometabolic diseases (CMDs). Epigenetic regulation and direct metabolite-protein interactions modulate metabolism, both within cells and in the circulation. Dysfunction of multiple mitochondrial components stemming from mitochondrial DNA mutations are implicated in disease pathogenesis. This review will summarize the current state of knowledge regarding: i) the interactions between metabolites found within the mitochondrial environment during CMDs, ii) various metabolites' effects on cellular and systemic function, iii) how harnessing the power of metabolomic analyses represents the next frontier of precision medicine, and iv) how these concepts integrate to expand the clinical potential for translational cardiometabolic medicine.

Development of an Efficient On-Tissue Epoxidation Reaction Mediated by Urea Hydrogen Peroxide for MALDI MS/MS Imaging of Lipid C═C Location Isomers

Unsaturated lipids containing different numbers and locations of C═C bonds are significantly associated with a variety of cellular and metabolic functions. Although matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) has been used to visualize the spatial distribution patterns of various lipids in biological tissues, in situ identification, discrimination, and visualization of lipid C═C location isomers remain challenging. Herein, an efficient and fast on-tissue chemical derivatization (OTCD) approach was developed to pinpoint the locations of C═C bonds in complex lipids in situ via methyltrioxorhenium (MTO)-catalyzed epoxidation of C═C with a urea hydrogen peroxide (UHP)/hexafluoroisopropanol (HFIP) system. The efficiency of OTCD could reach 100% via one-step spray deposition of the solution mixture of MTO/UHP/HFIP at room temperature. The developed OTCD method provided rich structural information on lipid C═C location isomers, and their accurate spatial distribution patterns were resolved in mouse brain tissues. Tissue-specific distributions and changes of lipid C═C location isomers in the liver sections of obese ob/ob and diabetic db/db mice were further investigated, and their correlation in two animal models was revealed. The simplicity and high efficiency of the OTCD method developed for MALDI tandem MSI of lipid C═C location isomers possess great potential for functional spatial lipidomics.

Revolutions in Lipid Isomer Resolution: Application of Ultrahigh-Resolution Ion Mobility to Reveal Lipid Diversity

Many families of lipid isomers remain unresolved by contemporary liquid chromatography-mass spectrometry approaches, leading to a significant underestimation of the structural diversity within the lipidome. While ion mobility coupled to mass spectrometry has provided an additional dimension of lipid isomer resolution, some isomers require a resolving power beyond the capabilities of conventional platforms. Here, we present the application of high-resolution traveling-wave ion mobility for the separation of lipid isomers that differ in (i) the location of a single carbon-carbon double bond, (ii) the stereochemistry of the double bond (cis or trans), or, for glycerolipids, (iii) the relative substitution of acyl chains on the glycerol backbone (sn-position). Collisional activation following mobility separation allowed identification of the carbon-carbon double-bond position and sn-position, enabling confident interpretation of variations in mobility peak abundance. To demonstrate the applicability of this method, double-bond and sn-position isomers of an abundant phosphatidylcholine composition were resolved in extracts from a prostate cancer cell line and identified by comparison to pure isomer reference standards, revealing the presence of up to six isomers. These findings suggest that ultrahigh-resolution ion mobility has broad potential for isomer-resolved lipidomics and is attractive to consider for future integration with other modes of ion activation, thereby bringing together advanced orthogonal separations and structure elucidation to provide a more complete picture of the lipidome.

Imaging and Structural Characterization of Phosphatidylcholine Isomers from Rat Brain Tissue Using Sequential Collision-Induced Dissociation/Electron-Induced Dissociation

The chemical complexity of biological tissues creates challenges in the analysis of lipids via imaging mass spectrometry. The presence of isobaric and isomeric compounds introduces chemical noise that makes it difficult to unambiguously identify and accurately map the spatial distributions of these compounds. Electron-induced dissociation (EID) has previously been shown to profile phosphatidylcholine (PCs) sn-isomers directly from rat brain tissue in matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry. However, the acquisition of true pixel-by-pixel images, as opposed to regional profiling measurements, using EID is difficult due to low fragmentation efficiency and precursor ion signal dilution into multiple fragment ion channels, resulting in low sensitivity. In this work, we have developed a sequential collision-induced dissociation (CID)/EID method to visualize the distribution of sn-isomers in MALDI imaging mass spectrometry experiments. Briefly, CID is performed on sodium-adducted PCs, which results in facile loss of the phosphocholine headgroup. This ion is then subjected to an EID analysis. Since the lipid headgroup is removed prior to EID, a major fragmentation pathway common to EID ion activation is eliminated, resulting in a more sensitive analysis. This sequential CID/EID workflow generates sn-specific fragment ions allowing for the assignment of the sn-positions. Carbon-carbon double-bond (C═C) positions are also localized along the fatty acyl tails by the presence of a 2 Da shift pattern in the fragment ions arising from carbon-carbon bond cleavages. Moreover, the integration of the CID/EID method into MALDI imaging mass spectrometry enables the mapping of the absolute and relative distribution of sn-isomers at every pixel. The localized relative abundances of sn-isomers vary throughout brain substructures and likely reflect different biological functions and metabolism.

Inherited Metabolic Diseases from Past to Present: A Bibliometric Analysis (1968-2023)

Bibliometric studies on inherited metabolic diseases (IMDs) do not exist in the literature. Therefore, our research aims to conduct a bibliometric study to determine the current status, trending topics, and missing points of publications on IMDs. Between 1968 and 2023, we conducted a literature search with the keyword "inherited metabolic disease" in the SCOPUS database. We included research articles in medicine written in English and published in the final section. We created our data pool using VOSviewer, SciMAT, and Rstudio software programs for the bibliometric parameters of the articles that met the inclusion criteria. We performed a bibliometric analysis of the data with the R package "bibliometrix" and BibExcel programs. We included 2702 research articles published on IMDs. The top three countries that have written the most articles in this field are the USA (n = 501), the United Kingdom (n = 182), and China (n = 172). The most preferred keywords by the authors were: newborn screening (n = 54), mutation (n = 43), phenylketonuria (n = 42), children (n = 35), genetics (n = 34), and maple syrup urine disease (n = 32). Trending topics were osteoporosis, computed tomography, bone marrow transplantation in the early years of the study, chronic kidney disease, urea cycle disorders, next-generation sequencing, newborn screening, and familial hypercholesterolemia in the final years of the study. This study provides clinicians with a new perspective, showing that molecular and genetic studies of inherited metabolic diseases will play an essential role in diagnosis and treatment in the future.

The Crosstalk between Gut Microbiota and Nervous System: A Bidirectional Interaction between Microorganisms and Metabolome

Several studies have shown that the gut microbiota influences behavior and, in turn, changes in the immune system associated with symptoms of depression or anxiety disorder may be mirrored by corresponding changes in the gut microbiota. Although the composition/function of the intestinal microbiota appears to affect the central nervous system (CNS) activities through multiple mechanisms, accurate epidemiological evidence that clearly explains the connection between the CNS pathology and the intestinal dysbiosis is not yet available. The enteric nervous system (ENS) is a separate branch of the autonomic nervous system (ANS) and the largest part of the peripheral nervous system (PNS). It is composed of a vast and complex network of neurons which communicate via several neuromodulators and neurotransmitters, like those found in the CNS. Interestingly, despite its tight connections to both the PNS and ANS, the ENS is also capable of some independent activities. This concept, together with the suggested role played by intestinal microorganisms and the metabolome in the onset and progression of CNS neurological (neurodegenerative, autoimmune) and psychopathological (depression, anxiety disorders, autism) diseases, explains the large number of investigations exploring the functional role and the physiopathological implications of the gut microbiota/brain axis.

Lipidomics in food quality and authentication: A comprehensive review of novel trends and applications using chromatographic and spectroscopic techniques

Lipid analysis is an integral part of food authentication and quality control which provides consumers with the necessary information to make an informed decision about their lipid intake. Recent advancement in lipid analysis and lipidome scope represents great opportunities for food science. In this review we provide a comprehensive overview of available tools for extraction, analysis and interpretation of data related to dietary fats analyses. Different analytical platforms are discussed including GC, MS, NMR, IR and UV with emphasis on their merits and limitations alongside complementary tools such as chemometric models and lipid-targeted online databases. Applications presented here include quality control, authentication of organic and delicacy food, tracing dietary fat source and investigating the effect of heat/storage on lipids. A multitude of analytical methods with different sensitivity, affordability, reproducibility and ease of operation are now available to comprehensively analyze dietary fats. Application of these methods range from studies which favor the use of large data generating platforms such as MS-based methods, to routine quality control which demands easy to use affordable equipment as TLC and IR. Hence, this review provides a navigation tool for food scientists to help develop an optimal protocol for their future lipid analysis quest.

New Approach for the Identification of Isobaric and Isomeric Metabolites

The structural elucidation of metabolite molecules is important in many branches of the life sciences. However, the isomeric and isobaric complexity of metabolites makes their identification extremely challenging, and analytical standards are often required to confirm the presence of a particular compound in a sample. We present here an approach to overcome these challenges using high-resolution ion mobility spectrometry in combination with cryogenic vibrational spectroscopy for the rapid separation and identification of metabolite isomers and isobars. Ion mobility can separate isomeric metabolites in tens of milliseconds, and cryogenic IR spectroscopy provides highly structured IR fingerprints for unambiguous molecular identification. Moreover, our approach allows one to identify metabolite isomers automatically by comparing their IR fingerprints with those previously recorded in a database, obviating the need for a recurrent introduction of analytical standards. We demonstrate the principle of this approach by constructing a database composed of IR fingerprints of eight isomeric/isobaric metabolites and use it for the identification of these isomers present in mixtures. Moreover, we show how our fast IR fingerprinting technology allows to probe the IR fingerprints of molecules within just a few seconds as they elute from an LC column. This approach has the potential to greatly improve metabolomics workflows in terms of accuracy, speed, and cost.

Metabolomic differentiation of benign vs malignant pulmonary nodules with high specificity via high-resolution mass spectrometry analysis of patient sera

Differential diagnosis of pulmonary nodules detected by computed tomography (CT) remains a challenge in clinical practice. Here, we characterize the global metabolomes of 480 serum samples including healthy controls, benign pulmonary nodules, and stage I lung adenocarcinoma. The adenocarcinoma demonstrates a distinct metabolomic signature, whereas benign nodules and healthy controls share major similarities in metabolomic profiles. A panel of 27 metabolites is identified in the discovery cohort (n = 306) to distinguish between benign and malignant nodules. The discriminant model achieves an AUC of 0.915 and 0.945 in the internal validation (n = 104) and external validation cohort (n = 111), respectively. Pathway analysis reveals elevation in glycolytic metabolites associated with decreased tryptophan in serum of lung adenocarcinoma vs benign nodules and healthy controls, and demonstrates that uptake of tryptophan promotes glycolysis in lung cancer cells. Our study highlights the value of the serum metabolite biomarkers in risk assessment of pulmonary nodules detected by CT screening.

High-Definition Ion Mobility/Mass Spectrometry with Structural Isotopic Shifts for Nominally Isobaric Isotopologues

We had reported the isotopic envelopes in differential IMS (FAIMS) separations depending on the ion structure. However, this new approach to distinguish isomers was constrained by the unit-mass resolution commingling all nominally isobaric isotopologues. Here, we directly couple high-definition FAIMS to ultrahigh-resolution (Orbitrap) MS and employ the resulting platform to explore the FAIMS spectra for isotopic fine structure. The peak shifts therein for isotopologues of halogenated anilines with ¹⁵N and ¹³C (split by 6 mDa) in N₂/CO₂ buffers dramatically differ, more than for the ¹³C, ³⁷Cl, or ⁸¹Br species apart by 1 or 2 Da. The shifts in FAIMS space upon different elemental isotopic substitutions are orthogonal mutually and to the underlying separations, forming fingerprint multidimensional matrices and 3-D trajectories across gas compositions that redundantly delineate all isomers considered. The interlocking instrumental and methodological upgrades in this work take the structural isotopic shift approach to the next level.

MS2Query: reliable and scalable MS2 mass spectra-based analogue search

Metabolomics-driven discoveries of biological samples remain hampered by the grand challenge of metabolite annotation and identification. Only few metabolites have an annotated spectrum in spectral libraries; hence, searching only for exact library matches generally returns a few hits. An attractive alternative is searching for so-called analogues as a starting point for structural annotations; analogues are library molecules which are not exact matches but display a high chemical similarity. However, current analogue search implementations are not yet very reliable and relatively slow. Here, we present MS2Query, a machine learning-based tool that integrates mass spectral embedding-based chemical similarity predictors (Spec2Vec and MS2Deepscore) as well as detected precursor masses to rank potential analogues and exact matches. Benchmarking MS2Query on reference mass spectra and experimental case studies demonstrate improved reliability and scalability. Thereby, MS2Query offers exciting opportunities to further increase the annotation rate of metabolomics profiles of complex metabolite mixtures and to discover new biology.

Integrating the potential of ion mobility spectrometry-mass spectrometry in the separation and structural characterisation of lipid isomers

It is increasingly evident that a more detailed molecular structure analysis of isomeric lipids is critical to better understand their roles in biological processes. The occurrence of isomeric interference complicates conventional tandem mass spectrometry (MS/MS)-based determination, necessitating the development of more specialised methodologies to separate lipid isomers. The present review examines and discusses recent lipidomic studies based on ion mobility spectrometry combined with mass spectrometry (IMS-MS). Selected examples of the separation and elucidation of structural and stereoisomers of lipids are described based on their ion mobility behaviour. These include fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and sterol lipids. Recent approaches for specific applications to improve isomeric lipid structural information using direct infusion, coupling imaging, or liquid chromatographic separation workflows prior to IMS-MS are also discussed, including: 1) strategies to improve ion mobility shifts; 2) advanced tandem MS methods based on activation of lipid ions with electrons or photons, or gas-phase ion-molecule reactions; and 3) the use of chemical derivatisation techniques for lipid characterisation.

Mass spectrometry DDA parameters and global coverage of the metabolome: Spectral molecular networks of momordica cardiospermoides plants

INTRODUCTION

Molecular networking (MN) has emerged as a key strategy to organize and annotate untargeted tandem mass spectrometry (MS/MS) data generated using either data independent- or dependent acquisition (DIA or DDA). The latter presents a time-efficient approach where full scan (MS¹) and MS² spectra are obtained with shorter cycle times. However, there are limitations related to DDA parameters, some of which are (i) intensity threshold and (ii) collision energy. The former determines ion prioritization for fragmentation, and the latter defines the fragmentation of selected ions. These DDA parameters inevitably determine the coverage and quality of spectral data, which would affect the outputs of MN methods.

OBJECTIVES

This study assessed the extent to which the quality of the tandem spectral data relates to MN topology and subsequent implications in the annotation of metabolites and chemical classification relative to the different DDA parameters employed.

METHODS

Herein, characterising the metabolome of Momordica cardiospermoides plants, we employ classical MN performance indicators to investigate the effects of collision energies and intensity thresholds on the topology of generated MN and propagated annotations.

RESULTS

We demonstrated that the lowest predefined intensity thresholds and collision energies result in comprehensive molecular networks. Comparatively, higher intensity thresholds and collision energies resulted in fewer MS² spectra acquisition, subsequently fewer nodes, and a limited exploration of the metabolome through MN.

CONCLUSION

Contributing to ongoing efforts and conversations on improving DDA strategies, this study proposes a framework in which multiple DDA parameters are utilized to increase the coverage of ions acquired and improve the global coverage of MN, propagated annotations, and the chemical classification performed.

Characterization of the lipidomic profile of clam Meretrix petechialis in response to Vibrio parahaemolyticus infection

Vibrio parahaemolyticus is a devastating pathogen of clam Meretrix petechialis, which brings about huge economic losses in aquaculture breeding industry. In our previous study, we have found that Vibrio infection is closely associated with lipid metabolism of clams. In this study, an untargeted lipidomics approach was used to explore the lipid profiling changes upon Vibrio infection. The results demonstrated that the hepatopancreas of clams was composed of five lipid categories including fatty acyls, glycerolipids, glycerophospholipids, sphingolipids and sterol lipids. And the content of lipid classes altered during Vibrio infection, implying that Vibrio infection altered intracellular lipid homeostasis in clams. Meanwhile, a total of 200 lipid species including 82 up-regulated and 118 down-regulated significantly were identified in response to Vibrio infection, of which ceramide (Cer), phosphatidylcholine (PC) and triglyceride (TG) accounted for the largest proportion. Notably, all Cers showed a significantly decreased trend while nearly all TG species were increased significantly during Vibrio infection, which suggested that Cer and TG could be determined as effective biomarkers. Furthermore, these differentially expressed lipid species were enriched in 20 metabolic pathways and sphingolipid metabolism was one of the most enriched pathways. These results evidenced how the lipid metabolism altered in the process of Vibrio infection and opened a new perspective on the response of marine bivalves to pathogen infection.

Targeted Small-Molecule Identification Using Heartcutting Liquid Chromatography-Infrared Ion Spectroscopy

Infrared ion spectroscopy (IRIS) can be used to identify molecular structures detected in mass spectrometry (MS) experiments and has potential applications in a wide range of analytical fields. However, MS-based approaches are often combined with orthogonal separation techniques, in many cases liquid chromatography (LC). The direct coupling of LC and IRIS is challenging due to the mismatching timescales of the two technologies: an IRIS experiment typically takes several minutes, whereas an LC fraction typically elutes in several seconds. To resolve this discrepancy, we present a heartcutting LC-IRIS approach using a setup consisting of two switching valves and two sample loops as an alternative to direct online LC-IRIS coupling. We show that this automated setup enables us to record multiple IR spectra for two LC-features from a single injection without degrading the LC-separation performance. We demonstrate the setup for application in drug metabolism research by recording six m/z-selective IR spectra for two drug metabolites from a single 2 μL sample of cell incubation extract. Additionally, we measure the IR spectra of two closely eluting diastereomeric biomarkers for the inborn error of metabolism pyridoxine-dependent epilepsy (PDE-ALDH7A1), which shows that the heartcutting LC-IRIS setup has good sensitivity (requiring ∼μL injections of ∼μM samples) and that the separation between closely eluting isomers is maintained. We envision applications in a range of research fields, where the identification of molecular structures detected by LC-MS is required.

Targeting mitochondrial impairment for the treatment of cardiovascular diseases: From hypertension to ischemia-reperfusion injury, searching for new pharmacological targets

Mitochondria and mitochondrial proteins represent a group of promising pharmacological target candidates in the search of new molecular targets and drugs to counteract the onset of hypertension and more in general cardiovascular diseases (CVDs). Indeed, several mitochondrial pathways result impaired in CVDs, showing ATP depletion and ROS production as common traits of cardiac tissue degeneration. Thus, targeting mitochondrial dysfunction in cardiomyocytes can represent a successful strategy to prevent heart failure. In this context, the identification of new pharmacological targets among mitochondrial proteins paves the way for the design of new selective drugs. Thanks to the advances in omics approaches, to a greater availability of mitochondrial crystallized protein structures and to the development of new computational approaches for protein 3D-modelling and drug design, it is now possible to investigate in detail impaired mitochondrial pathways in CVDs. Furthermore, it is possible to design new powerful drugs able to hit the selected pharmacological targets in a highly selective way to rescue mitochondrial dysfunction and prevent cardiac tissue degeneration. The role of mitochondrial dysfunction in the onset of CVDs appears increasingly evident, as reflected by the impairment of proteins involved in lipid peroxidation, mitochondrial dynamics, respiratory chain complexes, and membrane polarization maintenance in CVD patients. Conversely, little is known about proteins responsible for the cross-talk between mitochondria and cytoplasm in cardiomyocytes. Mitochondrial transporters of the SLC25A family, in particular, are responsible for the translocation of nucleotides (e.g., ATP), amino acids (e.g., aspartate, glutamate, ornithine), organic acids (e.g. malate and 2-oxoglutarate), and other cofactors (e.g., inorganic phosphate, NAD⁺, FAD, carnitine, CoA derivatives) between the mitochondrial and cytosolic compartments. Thus, mitochondrial transporters play a key role in the mitochondria-cytosol cross-talk by leading metabolic pathways such as the malate/aspartate shuttle, the carnitine shuttle, the ATP export from mitochondria, and the regulation of permeability transition pore opening. Since all these pathways are crucial for maintaining healthy cardiomyocytes, mitochondrial carriers emerge as an interesting class of new possible pharmacological targets for CVD treatments.

Structural Identification of Eicosanoids with Ring Structures Using Differential Mobility Spectrometry-Electron Impact Excitation of Ions from Organics Mass Spectrometry

We developed a structural identification method for eicosanoids with various ring structures using mass spectrometry. We discovered that an electron beam with a kinetic energy of 10 eV, which is in the Electron Impact Excitation of Ions from Organics (EIEIO) regime, cleaved the fatty acids enough to distinguish constitutional and cis/trans isomers. In addition to EIEIO, a comparison to authentic standards using differential mobility spectrometry (DMS) can identify diastereomers, which was difficult by EIEIO. The combination of EIEIO and DMS can provide a high-throughput method to identify complete structures of eicosanoids in mixed samples, which is not allowed with conventional analytical methods though eicosanoids are important signaling molecules in biosystems.

Recent Advances in Gas-phase Ion/Ion Chemistry for Lipid Analysis

Gas-phase ion/ion reactions can be used to alter analyte ion-types for subsequent dissociation both quickly and efficiently without the need for altering analyte ionization conditions. This capability can be particularly useful when the ion-type that is most efficiently generated by the ionization method at hand does not provide the structural information of interest using available dissociation methods. This situation often arises in the analysis of lipids, which constitute a diverse array of chemical species with many possibilities for isomers. Gas-phase ion/ion reactions have been demonstrated to be capable of enhancing the ability of tandem mass spectrometry to characterize the structures of various lipid classes. This review summarizes progress to date in the application of gas-phase ion/ion reactions to lipid structural characterization.

The critical role that spectral libraries play in capturing the metabolomics community knowledge

BACKGROUND

Spectral library searching is currently the most common approach for compound annotation in untargeted metabolomics. Spectral libraries applicable to liquid chromatography mass spectrometry have grown in size over the past decade to include hundreds of thousands to millions of mass spectra and tens of thousands of compounds, forming an essential knowledge base for the interpretation of metabolomics experiments.

AIM OF REVIEW

We describe existing spectral library resources, highlight different strategies for compiling spectral libraries, and discuss quality considerations that should be taken into account when interpreting spectral library searching results. Finally, we describe how spectral libraries are empowering the next generation of machine learning tools in computational metabolomics, and discuss several opportunities for using increasingly accessible large spectral libraries.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review focuses on the current state of spectral libraries for untargeted LC-MS/MS based metabolomics. We show how the number of entries in publicly accessible spectral libraries has increased more than 60-fold in the past eight years to aid molecular interpretation and we discuss how the role of spectral libraries in untargeted metabolomics will evolve in the near future.

Applications of liquid chromatography-mass spectrometry based metabolomics in predictive and personalized medicine

Metabolomics is a fast-developing technique used in biomedical researches focusing on pathological mechanism illustration or novel biomarker development for diseases. The ability of simultaneously quantifying thousands of metabolites in samples makes metabolomics a promising technique in predictive or personalized medicine-oriented researches and applications. Liquid chromatography-mass spectrometry is the most widely employed analytical strategy for metabolomics. In this current mini-review, we provide a brief update on the recent developments and novel applications of LC-MS based metabolomics in the predictive and personalized medicine sector, such as early diagnosis, molecular phenotyping or prognostic evaluation. COVID-19 related metabolomic studies are also summarized. We also discuss the prospects of metabolomics in precision medicine-oriented researches, as well as critical issues that need to be addressed when employing metabolomic strategy in clinical applications.

Structural Characterization and Quantitation of Ether-Linked Glycerophospholipids in Peroxisome Biogenesis Disorder Tissue by Ultraviolet Photodissociation Mass Spectrometry

The biological impact of ether glycerophospholipids (GP) in peroxisomal disorders and other diseases makes them significant targets as biomarkers for diagnostic assays or deciphering pathology of the disorders. Ether lipids include both plasmanyl and plasmenyl lipids, which each contain an ether or a vinyl ether bond at the sn-1 linkage position, respectively. This linkage, in contrast to traditional diacyl GPs, precludes their detailed characterization by mass spectrometry via traditional collisional-based MS/MS techniques. Additionally, the isomeric nature of plasmanyl and plasmenyl pairs of ether lipids introduces a further level of complexity that impedes analysis of these species. Here, we utilize 213 nm ultraviolet photodissociation mass spectrometry (UVPD-MS) for detailed characterization of phosphatidylethanolamine (PE) and phosphatidylcholine (PC) plasmenyl and plasmanyl lipids in mouse brain tissue. 213 nm UVPD-MS enables the successful differentiation of these four ether lipid subtypes for the first time. We couple this UVPD-MS methodology to reversed-phase liquid chromatography (RPLC) for characterization and relative quantitation of ether lipids from normal and diseased (Pex7 deficiency modeling the peroxisome biogenesis disorder, RCDP) mouse brain tissue, highlighting the ability to pinpoint specific structural features of ether lipids that are important for monitoring aberrant lipid metabolism in peroxisomal disorders.

Simplifying the complex: accessible microfluidic solutions for contemporary processes within in vitro diagnostics

In vitro diagnostics (IVDs) form the cornerstone of modern medicine. They are routinely employed throughout the entire treatment pathway, from initial diagnosis through to prognosis, treatment planning, and post-treatment surveillance. Given the proven links between high quality diagnostic testing and overall health, ensuring broad access to IVDs has long been a focus of both researchers and medical professionals. Unfortunately, the current diagnostic paradigm relies heavily on centralized laboratories, complex and expensive equipment, and highly trained personnel. It is commonly assumed that this level of complexity is required to achieve the performance necessary for sensitive and specific disease diagnosis, and that making something affordable and accessible entails significant compromises in test performance. However, recent work in the field of microfluidics is challenging this notion. By exploiting the unique features of microfluidic systems, researchers have been able to create progressively simple devices that can perform increasingly complex diagnostic assays. This review details how microfluidic technologies are disrupting the status quo, and facilitating the development of simple, affordable, and accessible integrated IVDs. Importantly, we discuss the advantages and limitations of various approaches, and highlight the remaining challenges within the field.