Mass Spectrometry-Based Metabolomics

Metabolic biomarkers in irritable bowel syndrome diagnosis

Irritable bowel syndrome (IBS) is a chronic gastrointestinal (GI) disorder characterized by altered bowel habits and abdominal discomfort during defecation. It significantly impacts life quality and work productivity for those affected. Global data suggests a slightly higher prevalence in females than in males. Today, unambiguous diagnosis of IBS remains challenging due to the absence of a specific biochemical, histopathological, or radiological test. Current diagnosis relies heavily on thorough symptom evaluation. Efforts by the Rome committees have established standardized diagnostic criteria (Rome I-IV), improving consistency and clinical applicability. Recent studies in this framework, seem to have successfully employed metabolomics techniques to identify distinct metabolite profiles in breath and stool samples of IBS patients, differentiating them from healthy controls and those with other functional GI disorders, such as inflammatory bowel disease (IBD). Building on this success, researchers are investigating the presence of similar metabolites in easily accessible biofluids such as urine, potentially offering a less invasive diagnostic approach. Accordingly, this review focuses on key metabolites specifically detected in IBS patients' biological specimens, with a focus on urinary metabolites, using various methods, particularly mass spectrometry (MS)-based techniques, including gas chromatography-MS (GC-MS), liquid chromatography-tandem MS (LC-MS/MS), and capillary electrophoresis-MS (CE-MS) metabolomics assays. These findings may make provision for a new set of non-invasive biomarkers for IBS diagnosis and management.

Multiomics analysis of platelet-rich plasma promoting biological performance of mesenchymal stem cells

Mesenchymal Stem Cells are ideal seed cells for tissue repair and cell therapy and have promising applications in regenerative medicine and tissue engineering. Using Platelet-Rich Plasma as an adjuvant to create and improve the microenvironment for Mesenchymal Stem Cells growth can enhance the biological properties of Mesenchymal Stem Cells and improve the efficacy of cell therapy. However, the mechanism by which Platelet-Rich Plasma improves the biological performance of Mesenchymal Stem Cells is still unknown. In this study, by examining the effects of Platelet-Rich Plasma on the biological performance of Mesenchymal Stem Cells, combined with multiomics analysis (Transcriptomics, Proteomics and Metabolomics) and related tests, we analyzed the specific pathways, related mechanisms and metabolic pathways of Platelet-Rich Plasma to improve the biological performance of Mesenchymal Stem Cells. In an in vitro cell culture system, the biological performance of Mesenchymal Stem Cells was significantly improved after replacing Foetal Bovine Serum with Platelet-Rich Plasma, and the genes (ESM1, PDGFB, CLEC7A, CCR1 and ITGA6 et al.) related to cell proliferation, adhesion, growth, migration and signal transduction were significantly upregulated. Platelet-Rich Plasma can enhance the secretion function of MSC exosomes, significantly upregulate many proteins related to tissue repair, immune regulation and anti-infection, and enhance the repair effect of exosomes on skin injury. After replacing Foetal Bovine Serum with Platelet-Rich Plasma, Mesenchymal Stem Cells underwent metabolic reprogramming, the metabolism of amino acids and fatty acids and various signaling pathways were changed, the anabolic pathways of various proteins were enhanced. These results provide a theoretical and technical reference for optimizing the Mesenchymal Stem Cells culture system, improving the biological characteristics and clinical application effects of Mesenchymal Stem Cells.

Study on pulp metabolism of patients with pulpitis using ultra-performance liquid chromatography coupled with Orbitrap mass spectrometry

BACKGROUND AND AIMS

Pulpitis, a pulp disease caused by caries, trauma, and other factors, has a high clinical incidence. This study focused on identifying possible metabolic biomarkers of pulpitis cases and analyzing the related metabolic pathways for providing a theoretical foundation to diagnose and prevent pulpitis.

MATERIALS AND METHODS

Pulp samples from 20 pulpitis cases together with 20 normal participants were analyzed with a serum metabolomics approach using ultra-high-performance liquid chromatography (UPLC)/Orbitrap mass spectrometry. Moreover, this work carried out multivariate statistical analysis for screening potential biomarkers of pulpitis.

RESULTS

Through biomarker analysis and identification, such as partial least squares discrimination analysis, orthogonal partial least squares discriminant analysis model establishment, correlation analysis, and biomarker pathway analysis, 40 biomarkers associated with 20 metabolic pathways were identified, including 20 upregulated and 20 downregulated metabolites. Those major biomarkers included oxoglutaric acid, inosine, citric acid, and PA(14:1(9Z)/PGD1). Among them, oxoglutaric acid and inosine were most significantly downregulated and had the highest correlation with pulpitis. Among these metabolic pathways, GABAergic synapse and alanine, aspartate, and glutamate metabolism were positively correlated with pulpitis. 4.

CONCLUSIONS

These biomarkers as well as metabolic pathways may offer the theoretical foundation to understand pulpitis pathogenesis and develop preventive drugs.

Database-assisted, globally optimized targeted secondary electrospray ionization high resolution mass spectrometry (dGOT-SESI-HRMS) and spectral stitching enhanced volatilomics analysis of bacterial metabolites

Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an innovative analytical technique for the rapid and non-invasive analysis of volatile organic compounds (VOCs). However, compound annotation and ion suppression in the SESI source has hindered feature detection, stability and reproducibility of SESI-HRMS in untargeted volatilomics. To address this, we have developed and optimized a novel pseudo-targeted approach, database-assisted globally optimized targeted (dGOT)-SESI-HRMS using the microbial-VOC (mVOC) database, and spectral stitching methods to enhance metabolite detection in headspace of anaerobic bacterial cultures. Headspace volatiles from representative bacteria strains were assessed using full scan with data dependent acquisition (DDA), conventional globally optimized targeted (GOT) method, and spectral stitching supported dGOT experiments based on a MS peaks list derived from mVOC. Our results indicate that spectral stitching supported dGOT-SESI-HRMS can proportionally fragment peaks with respect to different analysis windows, with a total of 109 VOCs fragmented from 306 targeted compounds. Of the collected spectra, 88 features were confirmed as culture derived volatiles with respect to media blanks. Annotation was also achieved with a total of 25 unique volatiles referenced to standard databases allowing for biological interpretation. Principal component analysis (PCA) summarizing the headspace volatile demonstrated improved separation of clusters when data was acquired using the dGOT method. Collectively, our dGOT-SESI-HRMS method afforded robust capability of capturing unique VOC profiles from different bacterial strains and culture conditions when compared to conventional GOT and DDA modes, suggesting the newly developed approach can serve as a more reliable analytical method for the sensitive monitoring of gut microbial metabolism.

Identification of a specific exporter that enables high production of aconitic acid in Aspergillus pseudoterreus

Aconitic acid is an unsaturated tricarboxylic acid that is attractive for its potential use in manufacturing biodegradable and biocompatible polymers, plasticizers, and surfactants. Previously Aspergillus pseudoterreus was engineered as a platform to produce aconitic acid by deleting the cadA (cis-aconitic acid decarboxylase) gene in the itaconic acid biosynthetic pathway. In this study, the aconitic acid transporter gene (aexA) was identified using comparative global discovery proteomics analysis between the wild-type and cadA deletion strains. The protein AexA belongs to the Major Facilitator Superfamily (MFS). Deletion of aexA almost abolished aconitic acid secretion, while its overexpression led to a significant increase in aconitic acid production. Transportation of aconitic acid across the plasma membrane is a key limiting step in its production. In vitro, proteoliposome transport assay further validated AexA's function and substrate specificity. This research provides new approaches to efficiently pinpoint and characterize exporters of fungal organic acids and accelerate metabolic engineering to improve secretion capability and lower the cost of bioproduction.

Early Pregnancy Markers in the Serum of Ewes Identified via Proteomic and Metabolomic Analyses

The diagnosis of ewes' pregnancy status at an early stage is an efficient way to enhance the reproductive output of sheep and allow producers to optimize production and management. The techniques of proteomics and metabolomics have been widely used to detect regulatory factors in various physiological processes of animals. The aim of this study is to explore the differential metabolites and proteins in the serum of pregnant and non-pregnant ewes by proteomics and metabolomics. The serum of ewes at 21, 28 and 33 days after artificial insemination (AI) were collected. The pregnancy stratus of the ewes was finally determined through ultrasound examination and then the ewes were grouped as Pregnant (n = 21) or N on-pregnant (n = 9). First, the serum samples from pregnant or non-pregnant ewes at 21 days after AI were selected for metabolomic analysis. It was found that the level of nine metabolites were upregulated and 20 metabolites were downregulated in the pregnant animals (p < 0.05). None of these differential metabolomes are suitable as markers of pregnancy due to their small foldchange. Next, the proteomes of serum from pregnant or non-pregnant ewes were evaluated. At 21 days after AI, the presence of 321 proteins were detected, and we found that the level of three proteins were upregulated and 11 proteins were downregulated in the serum of pregnant ewes (p < 0.05). The levels of serum amyloid A (SAA), afamin (AFM), serpin family A member 6 (SERPINA6) and immunoglobulin-like domain-containing protein between pregnant and non-pregnant ewes at 21-, 28- and 33-days post-AI were also analyzed via enzyme-linked immunosorbent assay (ELISA). The levels of SAA and AFM were significantly higher in pregnant ewes than in non-pregnant ewes, and could be used as markers for early pregnancy detection. Overall, our results show that SAA and AFM are potential biomarkers to determine the early pregnancy status of ewes.

Pesticide pestilence: Global scenario and recent advances in detection and degradation methods

Increased anthropogenic activities are confronted as the main cause for rising environmental and health concerns globally, presenting an indisputable threat to both environment and human well-being. Modern-day industrialization has given rise to a cascade of concurrent environmental and health challenges. The global human population is growing at an alarming rate, posing tremendous pressure on future food security, and healthy and environmentally sustainable diets for all. To feed all, the global food production needs to increase by 50% by 2050, but this increase has to occur from the limited arable land, and under the present-day climate variabilities. Pesticides have become an integral component of contemporary agricultural system, safeguarding crops from pests and diseases and their use must be reduce to fulfill the SDG (Sustainable Development Goals) agenda . However, their indiscriminate use, lengthy half-lives, and high persistence in soil and aquatic ecosystems have impacted global sustainability, overshot the planetary boundaries and damaged the pure sources of life with severe and negative impacts on environmental and human health. Here in this review, we have provided an overview of the background of pesticide use and pollution status and action strategies of top pesticide-using nations. Additionally, we have summarized biosensor-based methodologies for the rapid detection of pesticide residue. Finally, omics-based approaches and their role in pesticide mitigation and sustainable development have been discussed qualitatively. The main aim of this review is to provide the scientific facts for pesticide management and application and to provide a clean, green, and sustainable environment for future generations.

Identifying the intervention mechanisms of polydatin in hyperuricemia model rats by using UHPLC-Q-Exactive Orbitrap mass spectroscopy metabonomic approach

Introduction

Polydatin is a biologically active compound found in mulberries, grapes, and Polygonum cuspidatum, and it has uric acid-lowering effects. However, its urate-lowering effects and the molecular mechanisms underlying its function require further study.

Methods

In this study, a hyperuricemic rat model was established to assess the effects of polydatin on uric acid levels. The body weight, serum biochemical indicators, and histopathological parameters of the rats were evaluated. A UHPLC-Q-Exactive Orbitrap mass spectrometry-based metabolomics approach was applied to explore the potential mechanisms of action after polydatin treatment.

Results

The results showed a trend of recovery in biochemical indicators after polydatin administration. In addition, polydatin could alleviate damage to the liver and kidneys. Untargeted metabolomics analysis revealed clear differences between hyperuricemic rats and the control group. Fourteen potential biomarkers were identified in the model group using principal component analysis and orthogonal partial least squares discriminant analysis. These differential metabolites are involved in amino acid, lipid, and energy metabolism. Of all the metabolites, the levels of L-phenylalanine, L-leucine, O-butanoylcarnitine, and dihydroxyacetone phosphate decreased, and the levels of L-tyrosine, sphinganine, and phytosphingosine significantly increased in hyperuricemic rats. After the administration of polydatin, the 14 differential metabolites could be inverted to varying degrees by regulating the perturbed metabolic pathway.

Conclusion

This study has the potential to enhance our understanding of the mechanisms of hyperuricemia and demonstrate that polydatin is a promising potential adjuvant for lowering uric acid levels and alleviating hyperuricemia-related diseases.

Metabolomics Reveals Novel Serum Metabolic Signatures in Gastric Cancer by a Mass Spectrometry Platform

Gastric cancer (GAS) is one of the malignant tumors of the gastrointestinal system. Alterations in metabolite composition can reflect pathological processes of GAS and constitute a basis for diagnosis and treatment improvements. In this study, a total of 301 serum samples from 150 GAS patients at different tumor-node-metastasis (TNM) stages and 151 healthy controls were collected. Mass spectrometry platforms were performed to investigate the changes in GAS-related metabolites and explore the new potential serum biomarkers and the metabolic dysregulation associated with GAS progression. Twelve differential metabolites (ethyl 2,4-dimethyl-1,3-dioxolane-2-acetate, D-urobilinogen, 14-HDoHE, 13-hydroxy-9-methoxy-10-oxo-11-octadecenoic acid, 5,6-dihydroxyprostaglandin F1a, 9'-carboxy-gamma-tocotrienol, glutaric acid, alanine, tyrosine, C18:2(FFA), adipic acid, and suberic acid) were identified to establish the diagnosis model for GAS. The defined biomarker panel was also statistically significant for GAS progression with different TNM stages. KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment revealed the metabolic dysregulation associated with GAS progression. In conclusion, a diagnostic panel was established and validated, which could be used to further stage the early and advanced GAS patients from healthy controls. These findings may provide useful information for explaining the GAS metabolic alterations and try to facilitate the characterization of GAS patients in the early stage.

Efficacy evaluation, active ingredients, and multitarget exploration of herbal medicine

Evidence shows that herbal medicine (HM) could be beneficial for the treatment of various diseases. However, complexities present in HM due to the unclear bioactive compounds, mechanisms of action, undetermined targets for therapy, and nonspecific features for metabolism, are currently an obstacle for the progression of novel drug discovery. Metabolomics could be a potential tool to overcome these issues and for the understanding of HM from a small-molecule metabolism level. The chinmedomics-based metabolomics method assesses the overall metabolism of organisms with a holistic view and shows great potential for understanding metabolic pathways, evaluating curative effects, clarifying mechanisms, discovering active ingredients, and precision medicine. This review focuses on the efficacy evaluation, active ingredient discovery, and target exploration of HM based on metabolomics and chinmedomics.

Overall metabolic network analysis of urine in hyperlipidemic rats treated with Bidens bipinnata L

Hyperlipidemia has been highlighted as one of the most prominent and global chronic conditions nowadays. Bidens bipinnata L. (BBL), a folk medicine in contemporary China, has efficacy in the treatment of hyperlipidemia (HLP) in China. Although some physiological and pathological function parameters of hyperlipidemia have been investigated, little information about the changes in small metabolites in biofluids has been reported. In the present study, global metabolic profiling with high-performance liquid chromatography-linear ion trap/Orbitrap high-resolution mass spectrometry (HPLC-LTQ/Orbitrap MS) combined with a pattern recognition method was performed to discover the underlying lipid-regulating mechanisms of BBL on hyperlipidemic rats induced by high-fat diet (HFD). The total of four metabolites, up- or down-regulated (p < 0.05 or 0.01), were identified and contributed to the progression of hyperlipidemia. These promising identified biomarkers underpin the metabolic pathway, including glyoxylate and dicarboxylate metabolism, the TCA cycle, sphingolipid metabolism and purine metabolism. They are disturbed in hyperlipidemic rats, and are identified using pathway analysis with MetPA. The altered metabolite indices could be regulated closer to normal levels after BBL intervention. The results demonstrated that urinary metabolomics is a powerful tool in the clinical diagnosis and treatment of hyperlipidemia to provide information on changes in metabolite pathways.

Untargeted metabolomics of pulmonary tuberculosis patient serum reveals potential prognostic markers of both latent infection and outcome

Currently, there are no particularly effective biomarkers to distinguish between latent tuberculosis infection (LTBI) and active pulmonary tuberculosis (PTB) and evaluate the outcome of TB treatment. In this study, we have characterized the changes in the serum metabolic profiles caused by Mycobacterium tuberculosis (Mtb) infection and standard anti-TB treatment with isoniazid-rifampin-pyrazinamide-ethambutol (HRZE) using GC-MS and LC-MS/MS. Seven metabolites, including 3-oxopalmitic acid, akeboside ste, sulfolithocholic acid, 2-decylfuran (4,8,8-trimethyldecahydro-1,4-methanoazulen-9-yl)methanol, d-(+)-camphor, and 2-methylaminoadenosine, were identified to have significantly higher levels in LTBI and untreated PTB patients (T0) than those in uninfected healthy controls (Un). Among them, akeboside Ste and sulfolithocholic acid were significantly decreased in PTB patients with 2-month HRZE (T2) and cured PTB patients with 2-month HRZE followed by 4-month isoniazid-rifampin (HR) (T6). Receiver operator characteristic curve analysis revealed that the combined diagnostic model showed excellent performance for distinguishing LT from T0 and Un. By analyzing the biochemical and disease-related pathways, we observed that the differential metabolites in the serum of LTBI or TB patients, compared to healthy controls, were mainly involved in glutathione metabolism, ascorbate and aldarate metabolism, and porphyrin and chlorophyll metabolism. The metabolites with significant differences between the T0 group and the T6 group were mainly enriched in niacin and nicotinamide metabolism. Our study provided more detailed experimental data for developing laboratory standards for evaluating LTBI and cured PTB.

Metabonomics profile analysis in inflammation-induced preterm birth and the potential role of metabolites in regulating premature cervical ripening

BACKGROUND

Preterm birth (PTB) is the primary cause of infant morbidity and mortality. Moreover, previous studies have established that PTB is related to premature cervical ripening. However, the underlying mechanism remains to be elucidated. This study sought to identify differentially expressed metabolites and investigate their potential biological functions in PTB.

METHODS

Pregnant C57BL/6 J mice were treated with either LPS or normal saline and cervical alterations before labor were detected by staining. Metabolic profiles in the plasma of PTB and control mice were examined through non-targeted metabonomics analyses, quantitative polymerase chain reaction and immunofluorescence staining were performed on human cervical smooth cells.

RESULTS

The study demonstrated that the mRNA and protein levels of α-SMA, SM-22, and calponin in cervical smooth muscle cells of PTB mice were lower while OR was higher at both mRNA and protein levels compared to the CTL group. A total of 181 differentially expressed metabolites were analyzed, among them, 96 were upregulated, while 85 were downregulated in the PTB group. Differentially expressed metabolites may play a role in STAT3, RhoA, mTOR, TGF-β, and NK-κB signaling pathways. Furthermore, when treated with taurine, the levels of α-SMA and SM-22 in human cervical smooth muscle cells were elevated, whereas that of connexin-43 was decreased.

CONCLUSION

Our study highlighted the changes of metabolites in the peripheral blood changed prior to PTB and revealed that these differentially expressed metabolites might participate in the development of premature cervical ripening. Taurine was identified as an important metabolite may modulate human cervical smooth muscle cells. Our study provided new insights into the mechanism underlying premature cervical ripening in PTB.

Coral-like Magnetic Particles for Chemoselective Extraction of Anionic Metabolites

To date, advanced chemical biology tools for chemoselective extraction of metabolites are limited. In this study, unique coral-like polymer particles were synthesized via high concentrations of 1-ethyl-3-(3-(dimethylamino)propyl) carbodiimide hydrochloride (EDC)/N-hydroxysuccinimide (NHS), which are usually used as condensation agents. The polymers can wrap or adhere Fe3O4 nanoparticles (Fe3O4-NPs) to form polymer magnetic microparticles (PMMPs). With abundant NHS-activated moieties on their surface, the coral-like PMMPs could be modified by cystamine for the chemoselective extraction of phosphate/carboxylate anion metabolites from complex biological samples. Finally, 97 metabolites including nucleotides, phosphates, phosphate sugars, carboxylate sugars, and organic acids were extracted and identified from serum, tissues, and cells. These metabolites are involved in four major metabolic pathways including glycolysis, the tricarboxylic acid cycle, the pentose phosphate pathway, and nucleotide metabolism. This study has provided a cost-effective and easy-to-implement preparation of PMMPs with a robust chemoselective extraction ability and versatile applications.

Metabolomics Research in Periodontal Disease by Mass Spectrometry

Periodontology is a newer field relative to other areas of dentistry. Remarkable progress has been made in recent years in periodontology in terms of both research and clinical applications, with researchers worldwide now focusing on periodontology. With recent advances in mass spectrometry technology, metabolomics research is now widely conducted in various research fields. Metabolomics, which is also termed metabolomic analysis, is a technology that enables the comprehensive analysis of small-molecule metabolites in living organisms. With the development of metabolite analysis, methods using gas chromatography–mass spectrometry, liquid chromatography–mass spectrometry, capillary electrophoresis–mass spectrometry, etc. have progressed, making it possible to analyze a wider range of metabolites and to detect metabolites at lower concentrations. Metabolomics is widely used for research in the food, plant, microbial, and medical fields. This paper provides an introduction to metabolomic analysis and a review of the increasing applications of metabolomic analysis in periodontal disease research using mass spectrometry technology.

Bibliometric and Visual Analysis on Metabolomics in Coronary Artery Disease Research

Background

Metabolomics has immense research value in coronary artery disease and has drawn increasing attention over the past decades. Many articles have been published in this field, which may challenge researchers aiming to investigate all the available information. However, bibliometrics can provide deep insights into this research field.

Objective

We aimed to qualitatively and quantitatively study metabolomics and coronary artery disease research, visually analyse the development status, trends, research hotspots, and frontiers of this field, and provide a reference for research on coronary artery disease.

Methods

Articles were acquired from the Web of Science Core Collection. VOSviewer and CiteSpace software were used to analyse publication growth, country/region, institution, journal distribution, author, reference, and keywords, and detected the keywords with strong citation burstness to identify emerging topics.

Results

A total of 1121 references were obtained, and the annual number of publications increased over the past 16 years. Metabolomics research has shown a gradual upward trend in coronary artery disease. The United States of America and China ranked at the top in terms of percentage of articles. The institution with the highest number of research publications in this field was Harvard University, followed by the University of California System and Brigham Women's Hospital. The most frequently cited authors included Hazen SL, Tang WH, and Wang ZN. Ala-Korpela M was the most productive author, followed by Clish CB and Adamski J. The journal with the most publications in this field was Scientific Reports, followed by PLoS One and the Journal of Proteome Research. The keywords used at a high frequency were "risk," "biomarkers," "insulin resistance," and "atherosclerosis." Burst detection analysis of top keywords showed that "microbiota," "tryptophan," and "diabetes" are the current research frontiers in this field.

Conclusion

This study provides useful information for acquiring knowledge on metabolomics and coronary artery diseases. Metabolomics research has shown a gradual upward trend in coronary artery disease studies over the past 16 years. Research on tryptophan metabolism regulated by intestinal flora will become an emerging academic trend in this field, which can offer guidance for more extensive and in-depth studies in the future.

Metabolomics comparison of serum and urine in dairy cattle using proton nuclear magnetic resonance spectroscopy

OBJECTIVE

The aim of the study was to conduct metabolic profiling of dairy cattle serum and urine using proton nuclear magnetic resonance (1H-NMR) spectroscopy and to compare the results obtained with those of other dairy cattle herds worldwide so as to provide a basic dataset to facilitate research on metabolites in serum and urine.

METHODS

Six dairy cattle were used in this study; all animals were fed the same diet, which was composed of total mixed ration; the fed amounts were based on voluntary intake. Blood from the jugular neck vein of each steer was collected at the same time using a separate serum tube. Urine samples were collected by hand sweeping the perineum. The metabolites were determined by 1H-NMR spectroscopy, and the obtained data were statistically analyzed by performing principal component analysis, partial least squares-discriminant analysis, variable importance in projection scores, and metabolic pathway data using Metaboanalyst 4.0.

RESULTS

The total number of metabolites in the serum and urine was measured to be 115 and 193, respectively, of which 47 and 81, respectively were quantified. Lactate (classified as an organic acid) and urea (classified as an aliphatic acylic compound) exhibited the highest concentrations in serum and urine, respectively. Some metabolites that have been associated with diseases such as ketosis, bovine respiratory disease, and metritis, and metabolites associated with heat stress were also found in the serum and urine samples.

CONCLUSION

The metabolites measured in the serum and urine could potentially be used to detect diseases and heat stress in dairy cattle. The results could also be useful for metabolomic research on the serum and urine of ruminants in Korea.

Metabolomic Laboratory-Developed Tests: Current Status and Perspectives

Laboratory-developed tests (LDTs) are a subset of in vitro diagnostic devices, which the US Food and Drug Administration defines as "tests that are manufactured by and used within a single laboratory". The review describes the emergence and history of LDTs. The current state and development prospects of LDTs based on metabolomics are analyzed. By comparing LDTs with the scientific metabolomics study of human bio samples, the characteristic features of metabolomic LDT are shown, revealing its essence, strengths, and limitations. The possibilities for further developments and scaling of metabolomic LDTs and their potential significance for healthcare are discussed. The legal aspects of LDT regulation in the United States, European Union, and Singapore, demonstrating different approaches to this issue, are also provided. Based on the data presented in the review, recommendations were made on the feasibility and ways of further introducing metabolomic LDTs into practice.

Determination of the effect of germination on the folate content of the seeds of some legumes using HPTLC-mass spectrometry-multivariate image analysis

Legumes are the main sources of folates which are not synthesized in the human body. The five folate species: 5-methyl tetrahydrofolate, tetrahydrofolate, pteroyl glutamate, 5-formyl tetrahydrofolate and 10-formyl tetrahydrofolate were quantitatively determined in legumes seeds and sprouts by a newly developed and validated high performance thin layer chromatography method. High resolution plate imaging hyphenated to mass spectrometry was exploited for fingerprint analysis of tested samples. Results indicated that germination of all seeds resulted in a 2.5-4 fold increase in the content of total folates as well as the individual vitamers. The total amount of folate reached a maximum on the fifth day in the case of black-eyed peas (861 μg/100 g Fresh Weight), white beans (755 μg/100 g FW) and brown lentils (681 μg/100 g FW). 5-CH₃-H₄ folate was found to be the most dominating folate species reaching its maximum content in day 5 sprouts of black-eyed peas (490 μg/100 g FW).

Mass spectrometry-based metabolomics diagnostics - myth or reality?

ABSTACTIntroduction: Metabolomics, one of the most high-promising technologies, is the most recently developed post-genomics discipline for developing new diagnostic tests for future implementation in medicine. More than 2,000 scientific papers, using mass spectrometry-based (MS-based) metabolomics analysis for human disease diagnostics, have been published during the past two decades, and almost every metabolomics study shows high diagnostic accuracy. However, despite the great results and promising perspectives, there are currently no diagnostic tests based on metabolomics that have been approved and introduced into clinics.Areas covered: In this report, the advantages and challenges of MS-based metabolomics are discussed with a focus on its developing role in diagnostics, and the current trends in implementing metabolomics diagnostics in the clinic.Expert opinion: In the development of new clinical diagnostics tests, MS-based metabolomics has potential as both a preliminary discovery base for routine testing and a multi-test prototype, which is hoped to be introduced into clinical practice in the near future. A laboratory-developed test (LDT) is one possible way that multi-testing could be developed.

Serum Metabonomic Study of Patients With Acute Coronary Syndrome Using Ultra-Performance Liquid Chromatography Orbitrap Mass Spectrometer

Acute coronary syndrome (ACS) can cause arrhythmia, heart failure, and even sudden death. Our aim in this study was to identify potential metabolic biomarkers in patients with ACS. The serum metabonomics approach based on ultra-performance liquid chromatography (UPLC)/Orbitrap mass spectrometer (MS) was used to analyze the serum samples from 45 patients with ACS and 29 healthy controls. Multivariate statistical analysis was used to screen for ACS biomarkers. In total, 69 biomarkers were identified to be enriched in 19 metabolic pathways; 43 biomarkers were significantly up-regulated, while 26 biomarkers were significantly down-regulated in the ACS group. The main classes were lyso-sphingolipid (SM), cinnamic acids, cholines, and primary amides. Receiver operating characteristic (ROC) curve analysis showed that lysoPC(20:4(8Z,11Z,14Z,17Z)/0:0) (ROC area under the curve, AUC = 0.936), SM(d18:0/16:0) (ROC AUC = 0.932), and SM(d18:1/14:0) (ROC AUC = 0.923) had a high ACS diagnostic ability. The AUC value of the diagnostic model constructed using these combined biomarkers was 0.96. Therefore, these biomarkers may improve the diagnostic efficacy of ACS. The findings of this study also implied that glycerophospholipid metabolism; the biosynthesis of unsaturated fatty acids; linoleic acid metabolism; and valine, leucine, and isoleucine biosynthesis played important roles in ACS. Network analysis by ingenuity pathway analysis (IPA) showed these biomarkers were correlated to the cardiac hypertrophy signaling pathway, ERK/MAPK signaling pathway, NF-kappa B signaling pathway, nitric oxide (NO) signaling pathway in cardiovascular system, and TLR-signaling pathway. These findings will help to improve the ability of accurate diagnosis and intervention of ACS.

Mapping the Metabolic Networks of Tumor Cells and Cancer-Associated Fibroblasts

Metabolism is considered to be the core of all cellular activity. Thus, extensive studies of metabolic processes are ongoing in various fields of biology, including cancer research. Cancer cells are known to adapt their metabolism to sustain high proliferation rates and survive in unfavorable environments with low oxygen and nutrient concentrations. Hence, targeting cancer cell metabolism is a promising therapeutic strategy in cancer research. However, cancers consist not only of genetically altered tumor cells but are interwoven with endothelial cells, immune cells and fibroblasts, which together with the extracellular matrix (ECM) constitute the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs), which are linked to poor prognosis in different cancer types, are one important component of the TME. CAFs play a significant role in reprogramming the metabolic landscape of tumor cells, but how, and in what manner, this interaction takes place remains rather unclear. This review aims to highlight the metabolic landscape of tumor cells and CAFs, including their recently identified subtypes, in different tumor types. In addition, we discuss various in vitro and in vivo metabolic techniques as well as different in silico computational tools that can be used to identify and characterize CAF-tumor cell interactions. Finally, we provide our view on how mapping the complex metabolic networks of stromal-tumor metabolism will help in finding novel metabolic targets for cancer treatment.

Multi-Omics Driven Metabolic Network Reconstruction and Analysis of Lignocellulosic Carbon Utilization in Rhodosporidium toruloides

An oleaginous yeast Rhodosporidium toruloides is a promising host for converting lignocellulosic biomass to bioproducts and biofuels. In this work, we performed multi-omics analysis of lignocellulosic carbon utilization in R. toruloides and reconstructed the genome-scale metabolic network of R. toruloides. High-quality metabolic network models for model organisms and orthologous protein mapping were used to build a draft metabolic network reconstruction. The reconstruction was manually curated to build a metabolic model using functional annotation and multi-omics data including transcriptomics, proteomics, metabolomics, and RB-TDNA sequencing. The multi-omics data and metabolic model were used to investigate R. toruloides metabolism including lipid accumulation and lignocellulosic carbon utilization. The developed metabolic model was validated against high-throughput growth phenotyping and gene fitness data, and further refined to resolve the inconsistencies between prediction and data. We believe that this is the most complete and accurate metabolic network model available for R. toruloides to date.

High-Throughput Large-Scale Targeted Proteomics Assays for Quantifying Pathway Proteins in Pseudomonas putida KT2440

Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in Pseudomonas putida KT2440 grown on various carbon sources. The results from the two LC-SRM platforms are highly correlated. In addition, the response curve study of 248 peptides demonstrates that microflow LC-SRM has comparable sensitivity for the majority of detected peptides and better mass spectrometry signal and chromatography stability than nanoflow LC-SRM.

Synthetic microbial communities of heterotrophs and phototrophs facilitate sustainable growth

Microbial communities comprised of phototrophs and heterotrophs hold great promise for sustainable biotechnology. Successful application of these communities relies on the selection of appropriate partners. Here we construct four community metabolic models to guide strain selection, pairing phototrophic, sucrose-secreting Synechococcus elongatus with heterotrophic Escherichia coli K-12, Escherichia coli W, Yarrowia lipolytica, or Bacillus subtilis. Model simulations reveae metabolic exchanges that sustain the heterotrophs in minimal media devoid of any organic carbon source, pointing to S. elongatus-E. coli K-12 as the most active community. Experimental validation of flux predictions for this pair confirms metabolic interactions and potential production capabilities. Synthetic communities bypass member-specific metabolic bottlenecks (e.g. histidine- and transport-related reactions) and compensate for lethal genetic traits, achieving up to 27% recovery from lethal knockouts. The study provides a robust modelling framework for the rational design of synthetic communities with optimized growth sustainability using phototrophic partners.

Plasma Metabolomics and Lipidomics Reveal Perturbed Metabolites in Different Disease Stages of Chronic Obstructive Pulmonary Disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a common disease characterized by persistent respiratory symptoms and airflow restriction. It is usually manifested as airway and/or alveolar abnormalities caused by significant exposure to harmful particulates or gases.

OBJECTIVE

We aim to explore plasma metabolomic changes in the acute exacerbation stage of COPD (AECOPD) and stable stage of COPD (Stable COPD) to identify potential biomarkers for diagnosis or prognosis in clinical practice.

METHODS

Untargeted metabolomics and lipidomics analyses were performed to investigate dysregulated molecules in blood plasma of AECOPD patients (n=48) and Stable COPD (n=48), and a cohort of healthy people were included as a control group (n=48). Statistical analysis and bioinformatics analysis were performed to reveal dysregulated metabolites and perturbed metabolic pathways. SVM-based multivariate ROC analysis was used for candidate biomarker screening.

RESULTS

A total of 142 metabolites and 688 lipids were dysregulated in COPD patients. Pathway enrichment analysis showed that several metabolic pathways were perturbed after COPD onset. Several biomarker panels were proposed for diagnosis of COPD vs healthy control and AECOPD vs Stable COPD with AUC greater than 0.9.

CONCLUSION

Numerous plasma metabolites and several metabolic pathways were detected relevant to COPD disease onset or progression. These metabolites may be considered as candidate biomarkers for diagnosis or prognosis of COPD. The perturbed pathways involved in COPD provide clues for further pathological mechanism studies of COPD.

A Perspective and Framework for Developing Sample Type Specific Databases for LC/MS-Based Clinical Metabolomics

Metabolomics has the potential to greatly impact biomedical research in areas such as biomarker discovery and understanding molecular mechanisms of disease. However, compound identification (ID) remains a major challenge in liquid chromatography mass spectrometry-based metabolomics. This is partly due to a lack of specificity in metabolomics databases. Though impressive in depth and breadth, the sheer magnitude of currently available databases is in part what makes them ineffective for many metabolomics studies. While still in pilot phases, our experience suggests that custom-built databases, developed using empirical data from specific sample types, can significantly improve confidence in IDs. While the concept of sample type specific databases (STSDBs) and spectral libraries is not entirely new, inclusion of unique descriptors such as detection frequency and quality scores, can be used to increase confidence in results. These features can be used alone to judge the quality of a database entry, or together to provide filtering capabilities. STSDBs rely on and build upon several available tools for compound ID and are therefore compatible with current compound ID strategies. Overall, STSDBs can potentially result in a new paradigm for translational metabolomics, whereby investigators confidently know the identity of compounds following a simple, single STSDB search.

Impact of phytosterols on liver and distal colon metabolome in experimental murine colitis model: an explorative study

Phytosterols are known to reduce plasma cholesterol levels and thereby reduce cardiovascular risk. Studies conducted on human and animal models have demonstrated that these compounds have also anti-inflammatory effects. Recently, an experimental colitis model (dextran sulphate sodium-induced) has shown that pre-treatment with phytosterols decreases infiltration of inflammatory cells and accelerates mucosal healing. This study aims to understand the mechanism underlying the colitis by analysing the end-products of the metabolism in distal colon and liver excised from the same mice used in the previous work. In particular, an unsupervised gas chromatography-mass spectrometry (GC-MS) and NMR based metabolomics approach was employed to identify the metabolic pathways perturbed by the dextran sodium sulphate (DSS) insult (i.e. Krebs cycle, carbohydrate, amino acids, and nucleotide metabolism). Interestingly, phytosterols were able to restore the homeostatic equilibrium of the hepatic and colonic metabolome.