Recent Developments along the Analytical Process for Metabolomics Workflows

Exploring the roles of excess amino acids, creatine, creatinine, and glucose in the formation of heterocyclic aromatic amines by UPLC-MS/MS

The prevention and control of heterocyclic aromatic amines (HAA) formation to mitigate of potential risks to humans, can be achieved by targeting their precursors. In this study, the detailed roles of individual and excess component (20 common α-amino acids, creatine, creatinine, and glucose) on HAA formation in roasted beef patties were examined using UPLC-MS/MS. The results confirmed the reported classical precursors of HAAs. Some components regulated the competitive production of Norharman and Harman. Glycine (Gly) and glucose favored Norharman formation, while cysteine (Cys) and phenylalanine (Phe) for Harman. Serine (Ser) and threonine (Thr) were identified as potential precursors for IQx-type HAAs. Interestingly, methionine (Met), Gly, Thr, Cys, alanine (Ala), and Ser were revealed as more targeted underlying precursors for 1,6-DMIP and 1,5,6-TMIP, and the formation mechanism was inferred. Furthermore, Pro, Leu, His, Ile, Lys and Asp were considered as great inhibitors for HAAs.

A GC×GC-MS method based on solid-state modulator for non-targeted metabolomics: Comparison with traditional GC-MS method

The formidable challenge posed by the presence of extremely high amounts of compounds and large differences in concentrations in plasma significantly complicates non-targeted metabolomics analyses. In this study, a comprehensive two-dimensional gas chromatography-quadrupole mass spectrometry (GC×GC-qMS) method with a solid-state modulator (SSM) for non-targeted metabolomics in beagle plasma was first established based on a GC-MS method, and the qualitative and quantitative performance of the two platforms were compared. Identification of detected compounds was accomplished utilizing NIST database match scores, retention indices (RIs) and standards. Semi-quantification involved the calculation of peak area ratios to internal standards. Metabolite identification sheets were generated for plasma samples on both analytical platforms, featuring 22 representative metabolites chosen for validating qualitative accuracy, and for conducting comparisons of linearity, accuracy, precision, and sensitivity. The outcomes revealed a threefold increase in the number of identifiable metabolites on the GC×GC-MS platform, with lower limits of quantitation (LLOQs) reduced to 0.5-0.05 times those achieved on the GC-MS platform. Accuracy in quantification for both GC×GC-MS and GC-MS fell within the range of 85-115%, and the vast majority of intra- and inter-day precisions were within the range of 20%. These findings underscore that relative to the conventional GC-MS method, the GC×GC-MS method developed in this study, combined with SSM, exhibits enhanced qualitative capabilities, heightened sensitivity, and comparable accuracy and precision, rendering it more suitable for non-targeted metabolomics analyses.

HCMMD: systematic evaluation of metabolites in body fluids as liquid biopsy biomarker for human cancers

Metabolomics is a rapidly expanding field in systems biology used to measure alterations of metabolites and identify metabolic biomarkers in response to disease processes. The discovery of metabolic biomarkers can improve early diagnosis, prognostic prediction, and therapeutic intervention for cancers. However, there are currently no databases that provide a comprehensive evaluation of the relationship between metabolites and cancer processes. In this review, we summarize reported metabolites in body fluids across pan-cancers and characterize their clinical applications in liquid biopsy. We conducted a search for metabolic biomarkers using the keywords ("metabolomics" OR "metabolite") AND "cancer" in PubMed. Of the 22,254 articles retrieved, 792 were deemed potentially relevant for further review. Ultimately, we included data from 573,300 samples and 17,083 metabolic biomarkers. We collected information on cancer types, sample size, the human metabolome database (HMDB) ID, metabolic pathway, area under the curve (AUC), sensitivity and specificity of metabolites, sample source, detection method, and clinical features were collected. Finally, we developed a user-friendly online database, the Human Cancer Metabolic Markers Database (HCMMD), which allows users to query, browse, and download metabolite information. In conclusion, HCMMD provides an important resource to assist researchers in reviewing metabolic biomarkers for diagnosis and progression of cancers.

Metabolomics distinguishes different grades of Scrophularia ningpoensis hemsl: Towards a biomarker discovery and quality evaluation

In managing unique complexities associated with Chinese medicinal quality assessment, metabolomics serves as an innovative tool. This study proposes an analytical approach to assess differing qualities of Scrophularia ningpoensis （S. ningpoensis）Hemsl by identifying potential biomarker metabolites and their activity with the corresponding secondary metabolites. The methodology includes four steps; first, a GC-MS based metabolomics exploration of the Scrophularia ningpoensis Hemsl. Second, a multivariate statistical analysis (PCA, PLS-DA, OPLS-DA) for quality assessment and biomarker identification. Third, the application of ROC analysis and pathway analysis based on identified biomarkers. Finally, validation of the associated active ingredients by HPLC. The analysis showed distinct metabolite profiles across varying grades of S. ningpoensis Hemsl, establishing a grading dependency relationship. Select biomarkers (gluconic Acid, d-xylulose, sucrose, etc.) demonstrated robust grading performances. Further, the Pentose Phosphate Pathway, deemed as most influential in grading, was tied to the synthesis of key constituents (iridoids, phenylpropanoids). HPLC validation tests affirm a decreasing trend in harpagoside and cinnamic acid levels between first and third-grade samples. In conclusion, this GC-MS based metabolomics combined HPLC method offers a sound approach to assess and distinguish quality variations in S. ningpoensis Hemsl samples.

Stress adaptation in Tibetan cashmere goats is governed by inherent metabolic differences and manifested through variable cashmere phenotypes

Tibetan cashmere goats are not only served as a valuable model for studying adaptation to hypoxia and high-altitude conditions but also playing a pivotal role in bolstering local economies through the provision of premium quality cashmere yarn. In this study, we performed an integration and network analysis of metabolomic, transcriptomic and proteomic to elucidate the role of differentially expressed genes, important metabolites, and relevant cellular and metabolic pathways between the fine (average 12.04 ± 0.03 μm of mean fiber diameter) and coarse cashmere (average 14.88 ± 0.05 μm of mean fber diameter) producing by Tibetan cashmere goats. We identified a distinction of 56 and 71 differential metabolites (DMs) between the F and C cashmere groups under positive and negative ion modes, respectively. The KEGG pathway enrichment analysis of these DMs highlighted numerous pathways predominantly involved in amino acid and protein metabolism, as indicated by the finding that the most impactful pathway was the mammalian target of rapamycin (mTOR) signalling pathway. In the F group, we identified a distinctive metabolic profile where amino acid metabolites including serine, histidine, asparagine, glutamic acid, arginine, valine, aspartic acid, tyrosine, and methionine were upregulated, while lysine, isoleucine, glutamine, tryptophan, and threonine were downregulated. The regulatory network and gene co-expression network revealed crucial genes, metabolites, and metabolic pathways. The integrative omics analysis revealed a high enrichment of several pathways, notably encompassing protein digestion and absorption, sphingolipid signalling, and the synaptic vesicle cycle. Within the sphere of our integrative analysis, DNMT3B was identified as a paramount gene, intricately associated with significant proteins such as HMCN1, CPB2, GNG12, and LRP1. Our present study delineated the molecular underpinnings governing the variations in cashmere characteristics by conducting comprehensive analyses across metabolomic, transcriptomic, and proteomic dimensions. This research provided newly insights into the mechanisms regulating cashmere traits and facilitated the advancement of selective breeding programs aimed at cultivating high-quality superfine Tibetan cashmere goats.

Metabolomic approaches to explore chemodiversity in seeds of guaraná (Paullinia cupana) using UPLC-QTOF-MSE and NMR analysis

The growing interest in health and well-being has spurred the evolution of functional foods, which provide enhanced health benefits beyond basic nutrition. Guaraná seeds (Paullinia cupana) have been widely studied and used as a functional food due to their richness in caffeine, phenolic compounds, amino acids, and other nutrients. This has established guaraná as a significant food supplement, with Brazil being the largest producer of the world. This study aims to propose a set of analytical methods to chemically evaluate fifty-six different guaraná clones, from the Guaraná Germplasm Active Bank, to accommodate the diverse requirements of the food industry. Metabolomic approaches were employed, in which a non-target metabolomic analysis via UPLC-QTOF-MSE led to the annotation of nineteen specialized metabolites. Furthermore, targeted metabolomics was also used, leading to the identification and quantification of metabolites by NMR. The extensive data generated were subjected to multivariate analysis, elucidating the similarities and differences between the evaluated guaraná seeds, particularly concerning the varying concentration levels of the metabolites. The metabolomics approach based on the combination of UPLC-QTOF-MSE, NMR and chemometric tools provided sensitivity, precision and accuracy to establish the chemical profiles of guaraná seeds. In conclusion, evaluating and determining the metabolic specificities of different guarana clones allow for their application in the development of products with different levels of specific metabolites, such as caffeine. This caters to various purposes within the food industry. Moreover, the recognized pharmacological properties of the annotated specialized metabolites affirm the use of guarana clones as an excellent nutritional source.

Structural elucidation of derivatives of polyfunctional metabolites after methyl chloroformate derivatization by high-resolution mass spectrometry gas chromatography. Application to microbiota metabolites

Metabolomics has become an essential discipline in the study of microbiome, emerging gas chromatography coupled to mass spectrometry as the most mature, robust, and reproducible analytical technique. Silylation is the most widely used chemical derivatization strategy, although it has some limitations. In this regard, alkylation by alkyl chloroformate offers some advantages, such as a rapid reaction, milder conditions, better reproducibility, and the generation of more stable derivatives. However, commercial spectral libraries do not include many of the alkyl derivatives, mainly for polyfunctional metabolites, which can form multiple derivatives. That introduces a huge bias in untargeted metabolomics leading to common errors such as duplicates, unknowns, misidentifications, wrong assignations, and incomplete results from which non-reliable findings and conclusions will be retrieved. For this reason, the purpose of this study is to overcome these shortcomings and to expand the knowledge of metabolites in general and especially those closely related to the gut microbiota through the thorough study of the reactivity of the different functional groups in real matrix derivatized by methyl chloroformate, a common representative alkylation reagent. To this end, a systematic workflow has been developed based on exhaustive structural elucidation, along with computational simulation, and taking advantage of the high sensitivity and high-resolution gas chromatography-mass spectrometry. Several empirical rules have been established according to chemically different entities (free fatty acids, amino acids, polyols, sugars, amines, and polyfunctional groups, etc.) to predict the number of derivatives formed from a single metabolite, as well as their elution order and structure. In this work, some methyl chloroformate derivatives not previously reported as well as the mechanisms to explain them are given. Extremely important is the interconversion of E- and Z- geometric isomers of unsaturated dicarboxylic acids (case of fumaric-maleic and case of citraconic-mesaconic acids), or the formation of cycled derivatives for amino acids, as well as common metabolites, as in the case of serine and cysteine, and many others.

Study on the anti-mitochondrial apoptosis mechanism of Erigeron breviscapus injection based on UPLC-Q-TOF-MS metabolomics and molecular docking in rats with cerebral ischemia-reperfusion injury

ETHNOPHARMACOLOGICAL RELEVANCE

Erigeron breviscapus is a common medicine of eight ethnic minorities, including Miao, Naxi, and Yi. As early as the Ming Dynasty (AD 1368-1644), Lanmao's Materia Medica of Southern Yunnan (AD 1436) recorded that the medicine is used for the treatment of "Zuo tan you huan." In modern pharmacological research, Erigeron breviscapus injection is the most commonly used preparation in the treatment of ischemic stroke caused by acute cerebral infarction, but its mechanism of action in the treatment of ischemic stroke is not well understood.

AIM OF THE STUDY

In this study, a metabonomics study based on ultraperformance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-QTOF-MS) was used in investigating the effect of a traditional Chinese medicine preparation Erigeron breviscapus injection on the rat model of focal cerebral ischemia-reperfusion and the affinity of its main components with the targets of mitochondrial apoptotic pathways.

MATERIALS AND METHODS

This study used molecular docking technology to verify the effective binding ability of main effective components of Erigeron breviscapus injection to target proteins related to mitochondrial apoptosis pathway. This study developed a metabonomics method based on the ultra-performance liquid chromatography combined with quadrupole time-of-flight tandem mass spectrometry (UPLC Q-TOF MS) to evaluate the efficacy and study the mechanism of traditional Chinese medicine preparation. With pattern recognition analysis (principal component analysis and partial least squares-discriminate analysis) of urinary metabolites, a clear separation of focal cerebral ischemia-reperfusion model group and healthy control group was achieved.

RESULTS

Erigeron breviscapus injection can significantly reduce the area of cerebral infarction, improve tissue morphological lesion in rats, and can increase the number of Nissl bodies. It may be a promoting factor by inhibiting hippocampal nerve cell apoptosis and Bax protein expression and by exerting effects against ischemia reperfusion after the induction of apoptosis. Thus, it plays a role in brain protection. Moreover, it can considerably promote the recovery of neurological deficiency signs in advance. Meanwhile, Erigeron breviscapus decreased malondialdehyde content and T-NOS activity. Its curative effect from strong to weak order: low dose > high dose > medium dose. The representative components of Erigeron breviscapus have good affinity with the active sites of mitochondrial apoptosis-related proteins. Metabolomics found that the potential biomarkers regulated by breviscapine are kynurequinolinic acid, succinylornithine, and leucine proline. It is speculated that it may participate in TRP-kynurequinolinic acid and succinylornithine-urea cycle-NO metabolic pathways.

CONCLUSIONS

This paper revealed the potential biomarkers and metabolic pathways regulated by Erigeron breviscapus. It was speculated that the mechanism is related to its inhibition of mitochondrion-mediated apoptosis. Erigeron breviscapus could restore the metabolic profiles of the model animals to normal animal levels. The mechanism may be related to the potential biomarkers of quinolinic acid, succinylornithine, and leucine proline and the metabolic pathways involved. However, the exact mechanism by which Erigeron breviscapus inhibits mitochondrion-mediated apoptosis remains to be further explored.

Quantification and isotope abundance determination of 13C labeled intracellular sugar metabolites with hydrophilic interaction liquid chromatography

Metabolic flux analysis (MFA) using stable isotope labeled tracers is a powerful tool to estimate fluxes through metabolic pathways. It finds applications in studying metabolic changes in diseases, regulation of cellular energetics, and novel strategies for metabolic engineering. Accurate and precise quantification of the concentration of metabolites and their labeling states is critical for correct MFA results. Utilizing an ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) system, an analytical method for simultaneously quantifying the concentration of sugar metabolites and their mass isotopologue distribution (MID) was developed. The method performs with good linearity and coefficient of determination (R2) > 0.99, while the detection limit ranged from 0.1 to 50 mg L-1. Seven sugar metabolites were detected in a labeled Brevibacterium flavum sample using the method. The detected quantities ranged from 6.15 to 3704.21 mg L-1, and 13C abundance was between 12.77% and 66.67% in the fermentation fluid and 16.28% and 91.93% in the bacterial body. Overall, the method is efficient, accurate, and suitable for analysis of labeled sugar metabolites in 13C MFA studies.

Non-invasive Sampling of Human Body Fluids Using In Vivo SPME

Noninvasive body fluids offer attractive sources to gain insights into human health. The in vivo solid-phase microextraction (SPME) technique is a fast and versatile sample preparation technique for the noninvasive sampling of human body fluids in various fields. This chapter summarizes the applications of SPME coupled with mass spectrometry (MS)-based approaches for noninvasive investigations of human body fluids, including urine, sweat, and saliva. New features of noninvasive SPME sampling and MS-based analysis are highlighted, and the prospects on their further development are also discussed.

Metabolomics meets systems immunology

Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.

Filling gaps in animal welfare assessment through metabolomics

Sustainability has become a central issue in Italian livestock systems driving food business operators to adopt high standards of production concerning animal husbandry conditions. Meat sector is largely involved in this ecological transition with the introduction of new label claims concerning the defense of animal welfare (AW). These new guarantees referred to AW provision require new tools for the purpose of authenticity and traceability to assure meat supply chain integrity. Over the years, European Union (EU) Regulations, national, and international initiatives proposed provisions and guidelines for assuring AW introducing requirements to be complied with and providing tools based on scoring systems for a proper animal status assessment. However, the comprehensive and objective assessment of the AW status remains challenging. In this regard, phenotypic insights at molecular level may be investigated by metabolomics, one of the most recent high-throughput omics techniques. Recent advances in analytical and bioinformatic technologies have led to the identification of relevant biomarkers involved in complex clinical phenotypes of diverse biological systems suggesting that metabolomics is a key tool for biomarker discovery. In the present review, the Five Domains model has been employed as a vademecum describing AW. Starting from the individual Domains-nutrition (I), environment (II), health (III), behavior (IV), and mental state (V)-applications and advances of metabolomics related to AW setting aimed at investigating phenotypic outcomes on molecular scale and elucidating the biological routes most perturbed from external solicitations, are reviewed. Strengths and weaknesses of the current state-of-art are highlighted, and new frontiers to be explored for AW assessment throughout the metabolomics approach are argued. Moreover, a detailed description of metabolomics workflow is provided to understand dos and don'ts at experimental level to pursue effective results. Combining the demand for new assessment tools and meat market trends, a new cross-strategy is proposed as the promising combo for the future of AW assessment.

Metabolomics as a Critical Tool for Studying Clinical Surgery

Metabolomics enables the analysis of metabolites within an organism, which offers the closest direct measurement of the physiological activity of the organism, and has advanced efforts to characterize metabolic states, identify biomarkers, and investigate metabolic pathways. A high degree of innovation in analytical techniques has promoted the application of metabolomics, especially in the study of clinical surgery. Metabolomics can be employed as a clinical testing method to maximize therapeutic outcomes, and has been applied in rapid diagnosis of diseases, timely postoperative monitoring, prognostic assessment, and personalized medicine. This review focuses on the use of mass spectrometry and nuclear magnetic resonance-based metabolomics in clinical surgery, including identifying metabolic changes before and after surgery, finding disease-associated biomarkers, and exploring the potential of personalized therapy. Challenges and opportunities of metabolomics in organ transplantation are also discussed, with a particular emphasis on metabolomics in donor organ evaluation and protection, prognostic outcome prediction, as well as postoperative adverse reaction monitoring. In the end, current limitations of metabolomics in clinical surgery and future research directions are presented.

Current State and Future Perspectives on Personalized Metabolomics

Metabolomics is one of the most promising 'omics' sciences for the implementation in medicine by developing new diagnostic tests and optimizing drug therapy. Since in metabolomics, the end products of the biochemical processes in an organism are studied, which are under the influence of both genetic and environmental factors, the metabolomics analysis can detect any changes associated with both lifestyle and pathological processes. Almost every case-controlled metabolomics study shows a high diagnostic accuracy. Taking into account that metabolomics processes are already described for most nosologies, there are prerequisites that a high-speed and comprehensive metabolite analysis will replace, in near future, the narrow range of chemical analyses used today, by the medical community. However, despite the promising perspectives of personalized metabolomics, there are currently no FDA-approved metabolomics tests. The well-known problem of complexity of personalized metabolomics data analysis and their interpretation for the end-users, in addition to a traditional need for analytical methods to address the quality control, standardization, and data treatment are reported in the review. Possible ways to solve the problems and change the situation with the introduction of metabolomics tests into clinical practice, are also discussed.

Combining NMR and MS to Describe Pyrrole-2-Carbaldehydes in Wheat Bran of Radiation

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are indispensable analytical tools to provide chemical fingerprints in metabolomics studies. The present study evaluated radiation breeding wheat lines for chemical changes by non-targeted NMR-based metabolomics analysis of bran extracts. Multivariate analysis following spectral binning suggested pyrrole-2-carbaldehydes as chemical markers of four mutant lines with distinct NMR fingerprints in a δ_H range of 9.28-9.40 ppm. Further NMR and MS data analysis, along with chromatographic fractionation and synthetic preparation, aimed at structure identification of marker metabolites and identified five pyrrole-2-carbaldehydes. Quantum-mechanical driven ¹H iterative full spin analysis (QM-HiFSA) on synthetic pyrrole-2-carbaldehydes provided a precise description of complex peak patterns. Biological evaluation of pyrrole-2-carbaldehydes was performed with nine synthetic products, and six compounds showed hepatoprotective effects via modulation of reactive oxygen species production. Given that three out of five identified in wheat bran of radiation were described for hepatoprotective activity, the value of radiation mutation to greatly enhance pyrrole-2-carbaldehyde production was supported.

Plasma lipidomics in subjects with combat posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is complex neuropsychiatric disorder triggered by a traumatic event and characterized by the symptoms that represent large burden to patients, as well as to society. Lipidomic approach can be applied as a useful tool for discovery of novel diagnostic, prognostic and therapeutic lipid biomarkers of various disorders, whose etiology is complex and still unknown, including PTSD. Since changes in the levels of lipid metabolites might indicate impairments in various metabolic pathways and cellular processes, the aim of this lipidomic study was to determine altered levels of lipid compounds in PTSD. The study enrolled 235 male patients with combat PTSD and 241 healthy male control subjects. Targeted lipidomic analysis of plasma samples was conducted using reverse-phase liquid chromatography coupled with mass spectrometry. Lipids that have been analyzed belong to the group of ceramides, cholesterol esters, diacylglycerols, lysophosphatidylcholines, lysophosphatidylethanolamines, phosphatidylcholines, phosphatidylethanolamines, sphingomyelins and triglycerides. The levels of fifteen lipid compounds were found to be significantly different between PTSD patients and healthy control subjects, including four phosphatidylcholines, two phosphatidylethanolamines, five sphingomyelins, two cholesterol esters and two ceramides. The lipid metabolites whose levels significantly differed between patients with PTSD and control subjects are associated with various biological processes, including impairments of membrane integrity and function, mitochondrial dysfunction, inflammation and oxidative stress. As these processes might be associated with development and progression of PTSD, altered lipid compounds represent potential biomarkers that could facilitate the diagnosis of PTSD, prediction of the disease, as well as identification of novel treatment approaches in PTSD.

Recent advances in proteomics and metabolomics in plants

Over the past decade, systems biology and plant-omics have increasingly become the main stream in plant biology research. New developments in mass spectrometry and bioinformatics tools, and methodological schema to integrate multi-omics data have leveraged recent advances in proteomics and metabolomics. These progresses are driving a rapid evolution in the field of plant research, greatly facilitating our understanding of the mechanistic aspects of plant metabolisms and the interactions of plants with their external environment. Here, we review the recent progresses in MS-based proteomics and metabolomics tools and workflows with a special focus on their applications to plant biology research using several case studies related to mechanistic understanding of stress response, gene/protein function characterization, metabolic and signaling pathways exploration, and natural product discovery. We also present a projection concerning future perspectives in MS-based proteomics and metabolomics development including their applications to and challenges for system biology. This review is intended to provide readers with an overview of how advanced MS technology, and integrated application of proteomics and metabolomics can be used to advance plant system biology research.

A dynamic multiple reaction monitoring strategy to develop and optimize targeted metabolomics methods: Analyzing bile acids in capecitabine-induced diarrhea

OBJECTIVE

We sought to develop and optimize a targeted bile acids (BAs) metabolomics method based on a dynamic multiple reaction monitoring (dMRM) strategy and explored the dynamic alterations of BAs in diarrhea induced by capecitabine in a mouse model.

METHOD

The targeted metabolomics method was developed using an Agilent 6460A triple quadrupole mass spectrometer, and 41 types of BAs were monitored in negative ionization mode. The mass spectrometer detection was optimized using dMRM to enhance the responses, separation, and peak shape and to shorten the analysis time. A mouse model of diarrhea was established by multiple administration of capecitabine, and plasma samples were collected at baseline and the end of drug administration for subsequent BAs analysis.

RESULTS

The targeted BA metabolomics method achieved shorter chromatographic separation time (10 min) for 41 BAs, with good peak shapes and response increases of 3- to 10-fold after application of dMRM. The mouse model of capecitabine-induced diarrhea was established, and the three BAs 23-norcholic acid, isolithocholic acid, and isodeoxycholic acid in the baseline samples contributed the most to differentiating mice with diarrhea from those without diarrhea. For mice that ultimately developed diarrhea, apocholic acid, isodeoxycholic acid, and 7-ketodeoxycholic acid exhibited the largest change in concentrations compared with their baseline concentrations.

CONCLUSION

The dMRM strategy has obvious advantages compared with common MRM. The results in model mice showed that a differentiated profile of BAs in the baseline may indicate biomarkers of diarrhea induced by capecitabine, and disturbed homeostasis may explain the metabolomic mechanism of diarrhea occurrence.

Metabolomics: A New Approach in the Evaluation of Effects in Human Beings and Wildlife Associated with Environmental Exposition to POPs

Human beings and wild organisms are exposed daily to a broad range of environmental stressors. Among them are the persistent organic pollutants that can trigger adverse effects on these organisms due to their toxicity properties. There is evidence that metabolomics can be used to identify biomarkers of effect by altering the profiles of endogenous metabolites in biological fluids or tissues. This approach is relatively new and has been used in vitro studies mainly. Therefore, this review addresses those that have used metabolomics as a key tool to identify metabolites associated with environmental exposure to POPs in wildlife and human populations and that can be used as biomarkers of effect. The published results suggest that the metabolic pathways that produce energy, fatty acids, and amino acids are commonly affected by POPs. Furthermore, these pathways can be promoters of additional effects. In the future, metabolomics combined with other omics will improve understanding of the origin, development, and progression of the effects caused by environmental exposure.

Time-Domain-Based Methyl Proton NMR with Absolute Quantitation Ability for Targeted Metabolomics

In high-throughput scenarios of targeted metabolomics, it is a significant challenge to process complex NMR spectra with severely overlapping signals produced by metabolites with similar chemical structures. Traditional frequency-domain NMR is ineffective to some degree due to the low sensitivity and poor resolution, and the precision of quantitation is usually affected by poorly or inconsistently phased and baselined spectra. Here, we established a strategy based on time-domain NMR focusing on methyl protons for targeted metabolomics. The targeted metabolomics focusing on bufadienolides for varietal discrimination of three toad venoms was conducted to demonstrate the practicability of time-domain-based methyl proton NMR. It revealed that the signals could be precisely identified and quantitated with an signal-to-noise ratio (SNR) of about 10 and a resolution of about 1.0 Hz. The sensitivity and resolution improvement make it particularly applicable in targeted metabolomics. The precise and absolute quantitation ability confirmed by triple-quadrupole mass spectrometry (QqQ-MS) could further extend its application range. Importantly, the methyl group is common in metabolites with a relatively wide chemical shift range. Time-domain analysis could be conducted in common NMR software. This technique is very easy and convenient for general researchers when employed as a complementary alternative to traditional frequency-domain NMR, especially in the field of targeted metabolomics.

High-Coverage Quantitative Metabolomics of Human Urine: Effects of Freeze-Thaw Cycles on the Urine Metabolome and Biomarker Discovery

Urine sample storage after collection at ultra-low-temperature (e.g., -80 °C) is normally required for comparative metabolome analysis of many samples, and therefore, freeze-thaw cycles (FTCs) are unavoidable. However, the reported effects of FTCs on the urine metabolome are controversial. Moreover, there is no report on the study of how urine FTCs affect biomarker discovery. Herein, we present our study of the FTC effects on the urine metabolome and biomarker discovery using a high-coverage quantitative metabolomics platform. Our study involved two centers located in Hangzhou, China, and Edmonton, Canada, to perform metabolome analysis of two separate cohorts of urine samples. The same workflow of sample preparation and dansylation isotope labeling LC-MS was used for in-depth analysis of the amine/phenol submetabolome. The analysis of 320 samples from the Hangzhou cohort consisting of 80 healthy subjects with each urine being subjected to four FTCs resulted in relative quantification of 3682 metabolites with 3307 identified or mass-matched. The analysis of 176 samples from the Edmonton cohort of 44 subjects with four FTCs quantified 3516 metabolites with 3166 identified or mass-matched. Multivariate and univariate analyses indicated that significant variations (fold change ≥ 1.5 with q-value ≤ 0.05) from FTCs were only observed in a very small fraction of the metabolites (<0.3%). Moreover, various metabolites did not show a consistent pattern of concentration changes from one to four FTCs, allowing the use of two separate cohorts of samples to remove these randomly changed metabolites. Three metabolite biomarkers for separating males and females were discovered, and FTC did not influence their discovery.

Metabolic perturbations and health impact from exposure to a combination of multiple harmful Maillard reaction products on Sprague-Dawley rats

The present study aimed to investigate the metabolic perturbations and health impact of the co-accumulation of Maillard reaction products (MRPs), including acrylamide, harmane, and N^ε-(carboxymethyl)lysine (CML), via serum biochemical and histopathological examinations as well as metabolomic analysis. Sprague-Dawley rats were treated with acrylamide (2 mg per kg body weight [bw]), harmane (1 mg per kg bw), CML (2 mg per kg bw), and combinations of these MRPs. Harmane did not cause adverse effects on the health of rats, whereas acrylamide and CML resulted in significantly (P < 0.05) decreased insulin sensitivity (HOMA-IR > 1), increased oxidative stress levels, and pathological injuries to the pancreas, liver, and gastrocnemius. Owing to the antioxidant and anti-diabetic activities of harmane, the effects of the combination of the MRPs on oxidative stress levels, blood glucose metabolism, and pathological injuries to the pancreas and gastrocnemius were relieved. However, new health problems, including pathological injury of the kidneys and increased cancer risk, were observed. Metabolomic analysis revealed that this may be related to the effects of MRPs on the arginine biosynthesis pathway, which resulted in the abnormal metabolism of fumaric acid and the tricarboxylic acid cycle. These results indicated that the mechanisms of the combined effect of MRPs and their effects on health cannot be predicted from the effects of individual MRPs.

Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)

INTRODUCTION

The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research.

OBJECTIVES

This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data.

RESULTS

The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities.

CONCLUSIONS

The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.

Advances and challenges in ginseng research from 2011 to 2020: the phytochemistry, quality control, metabolism, and biosynthesis

Covering: 2011 to the end of 2020Panax species (Araliaceae), particularly P. ginseng, P. quinquefolius, and P. notoginseng, have a long history of medicinal use because of their remarkable tonifying effects, and currently serve as crucial sources for various healthcare products, functional foods, and cosmetics, aside from their vast clinical preparations. The huge market demand on a global scale prompts the continuous prosperity in ginseng research concerning the discovery of new compounds, precise quality control, ADME (absorption/disposition/metabolism/excretion), and biosynthesis pathways. Benefitting from the ongoing rapid development of analytical technologies, e.g. multi-dimensional chromatography (MDC), personalized mass spectrometry (MS) scan strategies, and multi-omics, highly recognized progress has been made in driving ginseng analysis towards "systematicness, integrity, personalization, and intelligentization". Herein, we review the advances in the phytochemistry, quality control, metabolism, and biosynthesis pathway of ginseng over the past decade (2011-2020), with 410 citations. Emphasis is placed on the introduction of new compounds isolated (saponins and polysaccharides), and the emerging novel analytical technologies and analytical strategies that favor ginseng's authentic use and global consumption. Perspectives on the challenges and future trends in ginseng analysis are also presented.

Metabolic Status of Lean and Obese Zucker Rats Based on Untargeted and Targeted Metabolomics Analysis of Serum

Obesity is growing worldwide epidemic. Animal models can provide some clues about the etiology, development, prevention, and treatment of obesity. We examined and compared serum metabolites between seven lean (L) and seven obese (O) female Zucker rats to investigate the individual serum metabolic profile. A combination of HPLC-UV, HPLC-ECD, and LC-MS revealed more than 400 peaks. The 50 highest quality peaks were selected as the focus of our study. Untargeted metabolomics analysis showed significantly higher mean peak heights for 20 peaks in L rats, generally distributed randomly, except for a cluster (peaks 44–50) where L showed stable dominancy over O. Only eight peaks were significantly higher in O rats. Peak height ratios between pairs of L and O rats were significantly higher at 199 positions in L rats and at 123 positions in O rats. Targeted metabolomics analysis showed significantly higher levels of methionine, cysteine, tryptophan, kynurenic acid, and cysteine/cystine ratio in L rats and significantly higher levels of cystine and tyrosine in O rats. These results contribute to a better understanding of systemic metabolic perturbations in the obese Zucker rat model, emphasizing the value of both whole metabolome and individual metabolic profiles in the design and interpretation of studies using animal models.

Metabolomics for personalized medicine: the input of analytical chemistry from biomarker discovery to point-of-care tests

Metabolomics refers to the large-scale detection, quantification, and analysis of small molecules (metabolites) in biological media. Although metabolomics, alone or combined with other omics data, has already demonstrated its relevance for patient stratification in the frame of research projects and clinical studies, much remains to be done to move this approach to the clinical practice. This is especially true in the perspective of being applied to personalized/precision medicine, which aims at stratifying patients according to their risk of developing diseases, and tailoring medical treatments of patients according to individual characteristics in order to improve their efficacy and limit their toxicity. In this review article, we discuss the main challenges linked to analytical chemistry that need to be addressed to foster the implementation of metabolomics in the clinics and the use of the data produced by this approach in personalized medicine. First of all, there are already well-known issues related to untargeted metabolomics workflows at the levels of data production (lack of standardization), metabolite identification (small proportion of annotated features and identified metabolites), and data processing (from automatic detection of features to multi-omic data integration) that hamper the inter-operability and reusability of metabolomics data. Furthermore, the outputs of metabolomics workflows are complex molecular signatures of few tens of metabolites, often with small abundance variations, and obtained with expensive laboratory equipment. It is thus necessary to simplify these molecular signatures so that they can be produced and used in the field. This last point, which is still poorly addressed by the metabolomics community, may be crucial in a near future with the increased availability of molecular signatures of medical relevance and the increased societal demand for participatory medicine.

Optimization of metabolomic data processing using NOREVA

A typical output of a metabolomic experiment is a peak table corresponding to the intensity of measured signals. Peak table processing, an essential procedure in metabolomics, is characterized by its study dependency and combinatorial diversity. While various methods and tools have been developed to facilitate metabolomic data processing, it is challenging to determine which processing workflow will give good performance for a specific metabolomic study. NOREVA, an out-of-the-box protocol, was therefore developed to meet this challenge. First, the peak table is subjected to many processing workflows that consist of three to five defined calculations in combinatorially determined sequences. Second, the results of each workflow are judged against objective performance criteria. Third, various benchmarks are analyzed to highlight the uniqueness of this newly developed protocol in (1) evaluating the processing performance based on multiple criteria, (2) optimizing data processing by scanning thousands of workflows, and (3) allowing data processing for time-course and multiclass metabolomics. This protocol is implemented in an R package for convenient accessibility and to protect users' data privacy. Preliminary experience in R language would facilitate the usage of this protocol, and the execution time may vary from several minutes to a couple of hours depending on the size of the analyzed data.

Non-targeted LC-MS and CE-MS for biomarker discovery in bioreactors: Influence of separation, mass spectrometry and data processing tools

Liquid separation coupled to mass spectrometry is often used for non-targeted analyses in various fields, such as metabolomics. However, the combination of non-standardized methods, various mass spectrometers (MS) and processing tools for data evaluation affect biomarker discovery potentially. Here, we present a comprehensive study of these factors based on non-targeted liquid chromatography coupled to time-of-flight (TOF) and Orbitrap MS and capillary zone electrophoresis to Orbitrap analyses of the same bioreactor samples, describing the correlation of its gas yield with changing feature signal intensity. The three datasets were processed with MZmine 2 and XCMS online and subsequential Partial Least Square Regression (PLSR) with Variable Importance in Projection (VIP) ranking for feature prioritization. The six feature tables were compared to evaluate their overlap of shared features and the influence of the processing software and MS instrument on the VIP values and fold changes. The overlaps, defined as a fraction of one feature table found in the comparative table, were from 27% to 57% for the comparison of MZmine and XCMS and from 15% to 50% between Orbitrap and TOF data sets, respectively. Considering the most relevant features only (VIP >1.5), the overlaps were increased significantly in all cases from 26% to 95%. For the same data set, both VIP values and fold changes were well correlated, however, varied significantly between TOF and Orbitrap. CE-MS showed higher total feature numbers compared to LC-MS, most likely due to its more appropriate selectivity, different sample preparation, and/or the sensitive nano-ESI interface. Since only less than 10% of MS/MS data overlapped, CE-MS provided complementary information to LC-MS. Overall, our systematic study proves the benefits of using different separation techniques and processing tools but also indicates a significant influence of mass spectrometry on comprehensive biomarker discovery.

Unveiling Metabolic Phenotype Alterations in Anorexia Nervosa through Metabolomics

Anorexia nervosa (AN) is a mental disorder characterized by an intense fear of weight gain that affects mainly young women. It courses with a negative body image leading to altered eating behaviors that have devastating physical, metabolic, and psychological consequences for the patients. Although its origin is postulated to be multifactorial, the etiology of AN remains unknown, and this increases the likelihood of chronification and relapsing. Thus, expanding the available knowledge on the pathophysiology of AN is of enormous interest. Metabolomics is proposed as a powerful tool for the elucidation of disease mechanisms and to provide new insights into the diagnosis, treatment, and prognosis of AN. A review of the literature related to studies of AN patients by employing metabolomic strategies to characterize the main alterations associated with the metabolic phenotype of AN during the last 10 years is described. The most common metabolic alterations are derived from chronic starvation, including amino acid, lipid, and carbohydrate disturbances. Nonetheless, recent findings have shifted the attention to gut-microbiota metabolites as possible factors contributing to AN development, progression, and maintenance. We have identified the areas of ongoing research in AN and propose further perspectives to improve our knowledge and understanding of this disease.

Application of Skyline for Analysis of Protein-Protein Interactions In Vivo

Quantitative and qualitative analyses of cell protein composition using liquid chromatography/tandem mass spectrometry are now standard techniques in biological and clinical research. However, the quantitative analysis of protein–protein interactions (PPIs) in cells is also important since these interactions are the bases of many processes, such as the cell cycle and signaling pathways. This paper describes the application of Skyline software for the identification and quantification of the biotinylated form of the biotin acceptor peptide (BAP) tag, which is a marker of in vivo PPIs. The tag was used in the Proximity Utilizing Biotinylation (PUB) method, which is based on the co-expression of BAP-X and BirA-Y in mammalian cells, where X or Y are interacting proteins of interest. A high level of biotinylation was detected in the model experiments where X and Y were pluripotency transcription factors Sox2 and Oct4, or heterochromatin protein HP1γ. MRM data processed by Skyline were normalized and recalculated. Ratios of biotinylation levels in experiment versus controls were 86 ± 6 (3 h biotinylation time) and 71 ± 5 (9 h biotinylation time) for BAP-Sox2 + BirA-Oct4 and 32 ± 3 (4 h biotinylation time) for BAP-HP1γ + BirA-HP1γ experiments. Skyline can also be applied for the analysis and identification of PPIs from shotgun proteomics data downloaded from publicly available datasets and repositories.

Review of the recent developments in metabolomics-based phytochemical research

Phytochemicals are important bioactive components present in natural products. Although the health benefits of many food products are well-known and accepted as a common knowledge, the identity of the main bioactive molecules and the mechanism by which they interact in the body of human are often unknown. It was only in the last 30 years when the field of metabolomics had matured that the identification of such molecules with bioactivity has been made possible through the development of instruments to separate and computational techniques to characterize complex samples. This in turn has enabled in vitro studies to quantify the biological activity of the respective phytochemical either in mice models or in humans. In this review, the importance of key dietary phytochemicals such as phenolic acids, flavonoids, carotenoids, resveratrol, curcumin, and capsaicinoids are discussed together with their potential functions for human health. Untargeted metabolomics, in particular, liquid chromatography mass spectrometry, is the most used method to isolate, identify and profile bioactive compounds in the study of phytochemicals in foods. The application of metabolomics in drug discovery is a common practice nowadays and has boosted the drug and/or supplement manufacturing sector.HighlightsPhytochemicals are beneficial compounds for human healthPhytochemicals are plant-based bioactive and obtainable from natural productsUntargeted metabolomics has boosted the discovery of phytochemicals from foodTargeted metabolomics is key in the authentication and screening of phytochemicalsMetabolomics of phytochemicals is reshaping the road to drug and supplement manufacture.

Comparative metabolomics analysis of bronchial epithelium during barrier establishment after allergen exposure

Background

Several studies have shown a correlation between an altered metabolome and respiratory allergies. The epithelial barrier hypothesis proposes that an epithelial barrier dysfunction can result in allergic diseases development. Der p 1 allergen from house dust mite is a renowned epithelial barrier disruptor and allergy initiator due to its cysteine‐protease activity. Here, we compared the metabolic profile of the bronchial epithelium exposed or not to Der p 1 during barrier establishment to understand its active role in allergy development.

Methods

Calu‐3 cells were cultivated in air‐liquid interface cultures and exposed to either Der p 1 or Ole e 1 allergens during barrier establishment. The comparative metabolomics analysis of apical and basolateral media were performed using liquid chromatography and capillary electrophoresis both coupled to mass spectrometry.

Results

We showed that epithelial barrier disruption by Der p 1 was associated with a specific metabolic profile, which was highly dependent on the state of the epithelium at the time of contact. Moreover, an apical‐basolateral distribution of the metabolites was also observed, indicating a compartmentalization of the response with differential metabolic patterns. A number of metabolites were changed by Der p 1, mainly related to amino acids metabolism, such as L‐arginine, L‐kynurenine and L‐methionine.

Conclusion

This work is the first report on the metabolic response in human bronchial epithelial cells associated with cysteine‐protease Der p 1 activity, which could contribute to allergy development. Moreover, it supports a reformulated epithelial barrier hypothesis that might help to explain allergies and their increasing prevalence.

The Importance of Metabolism for Immune Homeostasis in Allergic Diseases

There is increasing evidence that the metabolic status of T cells and macrophages is associated with severe phenotypes of chronic inflammation, including allergic inflammation. Metabolic changes in immune cells have a crucial role in their inflammatory or regulatory responses. This notion is reinforced by metabolic diseases influencing global energy metabolism, such as diabetes or obesity, which are known risk factors of severity in inflammatory conditions, due to the metabolic-associated inflammation present in these patients. Since several metabolic pathways are closely tied to T cell and macrophage differentiation, a better understanding of metabolic alterations in immune disorders could help to restore and modulate immune cell functions. This link between energy metabolism and inflammation can be studied employing animal, human or cellular models. Analytical approaches rank from classic immunological studies to integrated analysis of metabolomics, transcriptomics, and proteomics. This review summarizes the main metabolic pathways of the cells involved in the allergic reaction with a focus on T cells and macrophages and describes different models and platforms of analysis used to study the immune system and its relationship with metabolism.

Multiomics Imaging Using High-Energy Water Gas Cluster Ion Beam Secondary Ion Mass Spectrometry [(H2O)n-GCIB-SIMS] of Frozen-Hydrated Cells and Tissue

Integration of multiomics at the single-cell level allows the unambiguous dissecting of phenotypic heterogeneity at different states such as health, disease, and biomedical response. Imaging mass spectrometry holds the promise of being able to measure multiple types of biomolecules in parallel in the same cell. We have explored the possibility of using water gas cluster ion beam secondary ion mass spectrometry [(H2O)n-GCIB-SIMS] as an analytical tool for multiomics assay. (H2O)n-GCIB has been hailed as an ideal ionization source for biological sampling owing to the enhanced chemical sensitivity and reduced matrix effect. Taking advantage of 1 μm spatial resolution by using a high-energy beam system, we have clearly shown the enhancement of multiple intact biomolecules up to a few hundredfold in single cells. Coupled with the cryogenic sample preparation/measurement, the lipids and metabolites were imaged simultaneously within the cellular region, uncovering the pristine chemistry for integrated omics in the same sample. We have demonstrated that double-charged myelin protein fragments and single-charged multiple lipids and metabolites can be localized in the same cells/tissue with a single acquisition. Our exploration has also been extended to the capability of (H2O)n-GCIB in the generation of multiple charged peptides on protein standards. Frozen hydration combined with (H2O)n-GCIB provides the possibility of universal enhancement for the ionization of multiple bio-molecules, including peptides/proteins which has allowed "omics" to become feasible in the same sample using SIMS.

Metabolomics reveals synergy between Ag and g-C3N4 in Ag/g-C3N4 composite photocatalysts: a unique feature among Ag-doped biocidal materials

INTRODUCTION

The silver/graphitic carbon nitride (Ag/g-C₃N₄) composite system exerts biocidal activity against the pathogenic bacterium Escherichia coli 1337-H that is stronger than that of well-known silver and titanium oxide (TiO₂)-based composites. However, whether the Ag/g-C₃N₄ composite system has biocidal properties that the parent components do or do not have as separate chemical entities and whether they differ from those in Ag/TiO₂ composite photocatalysts have not been clarified.

OBJECTIVE

We investigated the chemical (cooperative charge handling and electronic properties) and biological (metabolic) effects exerted by the addition of Ag to g-C₃N₄ and to TiO₂.

METHODS

In this work, we undertook metabolome-wide analysis by liquid chromatography-electrospray ionization-quadrupole-time of flight-mass spectrometry to compare the metabolite profiles of untreated E. coli 1337-H cells or those subjected to disinfection with Ag, g-C₃N₄, 2Ag/g-C₃N₄, TiO₂ and 2Ag/TiO₂.

RESULTS

While Ag or g-C₃N₄ moderately affected microbial metabolism according to the mean of the altered metabolites, multiple cell systems contributing to rapid cell death were immediately affected by the light-triggered radical species produced when Ag and g-C₃N₄ were as xAg/g-C₃N_4. The effects include drastically reduced production of small metabolites essential for detoxifying reactive oxygen species and those that regulate DNA replication fidelity, cell morphology and energy status. These biological consequences were different from those caused by Ag/TiO₂-based biocides, demonstrating the uniqueness of the Ag/g-C₃N₄ system.

CONCLUSIONS

Our results support the idea that the unique Ag/g-C₃N₄ biocidal properties are based on synergistic action and reveal new directions for designing future photocatalysts for use in disinfection and microbial control.

The Effects of Sampling and Storage Conditions on the Metabolite Profile of the Marine Sponge Geodia barretti

Geodia barretti is a deep-sea marine sponge common in the north Atlantic and waters outside of Norway and Sweden. The sampling and subsequent treatment as well as storage of sponges for metabolomics analyses can be performed in different ways, the most commonly used being freezing (directly upon collection or later) or by storage in solvent, commonly ethanol, followed by freeze-drying. In this study we therefore investigated different sampling protocols and their effects on the detected metabolite profiles in liquid chromatography-mass spectrometry (LC-MS) using an untargeted metabolomics approach. Sponges (G. barretti) were collected outside the Swedish west coast and pieces from three sponge specimens were either flash frozen in liquid nitrogen, frozen later after the collection cruise, stored in ethanol or stored in methanol. The storage solvents as well as the actual sponge pieces were analyzed, all samples were analyzed with hydrophilic interaction liquid chromatography as well as reversed phase liquid chromatography with high resolution mass spectrometry using full-scan in positive and negative ionization mode. The data were evaluated using multivariate data analysis. The highest metabolite intensities were found in the frozen samples (flash frozen and frozen after sampling cruise) as well as in the storage solvents (methanol and ethanol). Metabolites extracted from the sponge pieces that had been stored in solvent were found in very low intensity, since the majority of metabolites were extracted to the solvents to a high degree. The exception being larger peptides and some lipids. The lowest variation between replicates were found in the flash frozen samples. In conclusion, the preferred method for sampling of sponges for metabolomics was found to be immediate freezing in liquid nitrogen. However, freezing the sponge samples after some time proved to be a reliable method as well, albeit with higher variation between the replicates. The study highlights the importance of saving ethanol extracts after preservation of specimens for biology studies; these valuable extracts could be further used in studies of natural products, chemosystematics or metabolomics.

Benchmarking Non-Targeted Metabolomics Using Yeast-Derived Libraries

Non-targeted analysis by high-resolution mass spectrometry (HRMS) is an essential discovery tool in metabolomics. To date, standardization and validation remain a challenge. Community-wide accepted cost-effective benchmark materials are lacking. In this work, we propose yeast (Pichia pastoris) extracts derived from fully controlled fermentations for this purpose. We established an open-source metabolite library of >200 identified metabolites based on compound identification by accurate mass, matching retention times, and MS/MS, as well as a comprehensive literature search. The library includes metabolites from the classes of (1) organic acids and derivatives (2) nucleosides, nucleotides, and analogs, (3) lipids and lipid-like molecules, (4) organic oxygen compounds, (5) organoheterocyclic compounds, (6) organic nitrogen compounds, and (7) benzoids at expected concentrations ranges of sub-nM to µM. As yeast is a eukaryotic organism, key regulatory elements are highly conserved between yeast and all annotated metabolites were also reported in the human metabolome database (HMDB). Orthogonal state-of-the-art reversed-phase (RP-) and hydrophilic interaction chromatography mass spectrometry (HILIC-MS) non-targeted analysis and authentic standards revealed that 104 out of the 206 confirmed metabolites were reproducibly recovered and stable over the course of three years when stored at −80 °C. Overall, 67 out of these 104 metabolites were identified with comparably stable areas over all three yeast fermentation and are the ideal starting point for benchmarking experiments. The provided yeast benchmark material enabled not only to test for the chemical space and coverage upon method implementation and developments but also allowed in-house routines for instrumental performance tests. Transferring the quality control strategy of proteomics workflows based on the number of protein identification in HeLa extracts, metabolite IDs in the yeast benchmarking material can be used as metabolomics quality control. Finally, the benchmark material opens new avenues for batch-to-batch corrections in large-scale non-targeted metabolomics studies.

Sphingolipidomics in Translational Sepsis Research-Biomedical Considerations and Perspectives

Scientific Background: Sphingolipids are a highly diverse group of lipids with respect to physicochemical properties controlling either structure, distribution, or function, all of them regulating cellular response in health and disease. Mass spectrometry, on the other hand, is an analytical technique characterizing ionized molecules or fragments thereof by mass-to-charge ratios, which has been prosperingly developed for rapid and reliable qualitative and quantitative identification of lipid species. Parallel to best performance of in-depth chromatographical separation of lipid classes, preconditions of precise quantitation of unique molecular species by preprocessing of biological samples have to be fulfilled. As a consequence, “lipid profiles” across model systems and human individuals, esp. complex (clinical) samples, have become eminent over the last couple of years due to sensitivity, specificity, and discriminatory capability. Therefore, it is significance to consider the entire experimental strategy from sample collection and preparation, data acquisition, analysis, and interpretation.

Areas Covered: In this review, we outline considerations with clinical (i.e., human) samples with special emphasis on sample handling, specific physicochemical properties, target measurements, and resulting profiling of sphingolipids in biomedicine and translational research to maximize sensitivity and specificity as well as to provide robust and reproducible results. A brief commentary is also provided regarding new insights of “clinical sphingolipidomics” in translational sepsis research.

Expert Opinion: The role of mass spectrometry of sphingolipids and related species (“sphingolipidomics”) to investigate cellular and compartment-specific response to stress, e.g., in generalized infection and sepsis, is on the rise and the ability to integrate multiple datasets from diverse classes of biomolecules by mass spectrometry measurements and metabolomics will be crucial to fostering our understanding of human health as well as response to disease and treatment.

Utilizing Plant Synthetic Biology to Improve Human Health and Wellness

Plants offer a vast source of bioactive chemicals with the potential to improve human health through the prevention and treatment of disease. However, many potential therapeutics are produced in small amounts or in species that are difficult to cultivate. The rapidly evolving field of plant synthetic biology provides tools to capitalize on the inventive chemistry of plants by transferring metabolic pathways for therapeutics into far more tenable plants, increasing our ability to produce complex pharmaceuticals in well-studied plant systems. Plant synthetic biology also provides methods to enhance the ability to fortify crops with nutrients and nutraceuticals. In this review, we discuss (1) the potential of plant synthetic biology to improve human health by generating plants that produce pharmaceuticals, nutrients, and nutraceuticals and (2) the technological challenges hindering our ability to generate plants producing health-promoting small molecules.

Analysis of the metabolic switch induced by the spirulina peptide SP6 in high fat diet ApoE-/- mice model: A direct infusion FT-ICR-MS based approach

Atherosclerosis, dyslipidemia and hypertension are comorbid diseases often found in combination. Among different pharmacological approaches the employment of natural multifunctional peptides is an attractive option as side therapy. Mass spectrometry-based metabolomics provide valuable information on metabolic changes and can be useful to elucidate peptide pharmacodynamics. In this this work we performed a preliminary investigation on the potential effect of a recently characterized Spirulina platensis peptide named SP6 (GIVAGDVTPI) on the modulation of metabolism in a high fat diet ApoE^-/- mice atherosclerotic model. A direct infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FT-ICR-MS) approach was used to elucidate polar and non-polar metabolites extracted by mice plasma following four weeks SP6 treatment. The method delivered fast analysis time, repeatability, high mass accuracy and resolution for unambiguous molecular formula assignment. Multivariate statistical analysis (PLS-DA) highlighted a clear class separation, revealing the alteration of numerous metabolites levels belonging to different classes. In particular sphingolipids, glycerophospholipids, TCA cycle intermediates, and amino acids, which are key players in the atherosclerotic process and progression, were upregulated in saline alone HFD ApoE^-/- group, while were sensibly decreased after treatment with SP6 peptide. These results could open the way to further, large-scale, investigation of SP6 peptide effects in the regulation of atherosclerotic disease development and progression, and show the potential of DI-FT-ICR as fast analytical tool to take snaphshots of metabolic changes before moving to targeted MS-based approaches.

Recent development of nanoparticle-assisted metabolites analysis with mass spectrometry

Metabolomics systematically studies the changes of metabolites in biological systems in the temporal or spatial dimensions. It is a challenging task for comprehensive analysis of metabolomics because of diverse physicochemical properties and wide concentration distribution of metabolites. Used as enrichment sorbents, chemoselective probes, chromatographic stationary phases, MS ionization matrix, nanomaterials play excellent roles in improving the selectivity, separation performance, detection sensitivity and identification efficiency of metabolites when mass spectrometry is employed as the detection technique. This review summarized the recent development of nanoparticle-assisted metabolites analysis in terms of assisting the pretreatment of biological samples, improving the separation performance and enhancing the MALDI-MS detection.