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A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Advances in Metabolomics".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 7970

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Dr. Xinyu Liu

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Key Laboratory of Medical Proteomics, CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
Interests: metabolomics; exposomics; mass spectrometry imaging; metabolic reprogramming and markers
Special Issues, Collections and Topics in MDPI journals

Dr. Chunxiu Hu

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Key Laboratory of Medical Proteomics, CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
Interests: single-cell metabolomics; lipidomics; metabolomics; mass spectrometry; disease biomarker discovery; spatial metabolomics

Dr. Xianzhe Shi

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Key Laboratory of Medical Proteomics, CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
Interests: single-cell metabolomics; nanomaterials; multi-dimensional liquid chromatography; mass spectrometry; spatial metabolomics

Special Issue Information

Dear Colleagues,

This Special Issue aims to publish novel research results and reviews presented at the 53rd International Symposium on High-Performance Liquid-Phase Separations and Related Techniques (HPLC 2024 Dalian) to be held on Oct. 21–23, 2024, in Dalian, China. We invite scholars, especially conference participants, to contribute original research papers and review articles dealing with all aspects of new analytical techniques and applications of metabolomics and/or lipidomics. Topics of interest include, but are not limited to, the following:

non-targeted, targeted, and pseudotargeted metabolomics and/or lipidomics;
high-coverage metabolomics and/or lipidomics;
high-throughput metabolomics and/or lipidomics;
high-precision quantitative metabolomics and/or lipidomics;
single-cell metabolomics and/or lipidomics;
spatial/spatially resolved metabolomics and/or lipidomics;
applications of metabolomics and/or lipidomics in different fields.

Dr. Xinyu Liu
Dr. Chunxiu Hu
Dr. Xianzhe Shi
Guest Editors

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Keywords

metabolomics
lipidomics
applications of metabolomics and/or lipidomics

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Published Papers (11 papers)

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Research

14 pages, 3635 KiB

Open AccessArticle

Aromatic Volatile Substances in Different Types of Guangnan Dixu Tea Based on HS-SPME-GC-MS Odor Activity Value

by Ying Feng, Di Tian, Chaoliang Wang, Yong Huang, Yang Luo, Xiuqiong Zhang and Lei Li

Metabolites 2025, 15(4), 257; https://doi.org/10.3390/metabo15040257 - 9 Apr 2025

Viewed by 97

Abstract

Dixu tea is one of the characteristic tea germplasm resources of southeastern Yunnan, and is also a precious wild tea germplasm resource. Background: In order to further develop Dixu tea products and improve their flavor, this article studies the effects of different processing methods on the aroma quality of Dixu tea. Methods: A comprehensive analysis of the aroma quality of Diwei tea was conducted using HS-SPME combined with GC-MS and multivariate statistical analysis. A principal component analysis (PCA) was applied to process the detected volatile substances and an orthogonal partial least squares-discriminant analysis (OPLS-DA) model was established. We evaluated the contribution of major compounds in the tea aroma by calculating the odor activity value (OAV). Results: The results showed that a total of 67 compounds were identified. A total of 27 major aromatic volatile compounds (OAV > 1) were screened, and 17 key differential volatile compounds were identified in different tea samples, including octanoic acid, d-citrol, laurene, hexanal, citral, β-cyclic citral, trans-2-hexenal, γ-nonanolide, β-ionone, geranylacetone, 1,1,6-trimethyl-1,2-dihydronaphthalene, geraniol, methyl salicylate, linalool, nerolidol, and 7,11-dimethyl-3-methylene-1,6,10-dodecatriene. Combined with the OAV analysis, it is shown that a floral fragrance is a common feature of Guangnan Dixu tea varieties. In addition, white tea also has a fragrant aroma, while black tea, green tea, and bamboo tube tea are all accompanied by a fruity aroma. Conclusions: In summary, processing techniques regulate the aroma characteristics of various types of tea by changing the types and contents of volatile aroma compounds. This provides a theoretical basis for exploring and utilizing tea production resources in the future. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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12 pages, 3161 KiB

Open AccessArticle

Profiling and Discrimination of Euryale Ferox Seeds from Different Processing Methods Using Liquid Chromatography High-Resolution Mass Spectrometry Combined with Molecular Networking and Statistical Analysis

by Xiaoyu Xie, Chuntao Zeng, Ruonan Zhang, Wenting Zhu, Huijie Li and Zhi Huang

Metabolites 2025, 15(4), 225; https://doi.org/10.3390/metabo15040225 - 25 Mar 2025

Viewed by 143

Abstract

Background: Euryale ferox seeds (EFSs) serve both medicinal and culinary purposes. They possess high nutritional value and are rich in polysaccharides, polyphenols, glycolipids, cyclic peptides, and other beneficial components. EFSs are known for their effects in tonifying the kidneys and strengthening essence, invigorating the spleen and alleviating diarrhea, as well as removing dampness and leucorrhea. Processing can alter the chemical composition of EFSs, with different methods yielding varying effects on their chemical makeup and, consequently, their efficacy. However, to date, no studies have systematically investigated the overall chemical composition of EFSs using different processing methods. Methods: In this study, we employed liquid chromatography high-resolution mass spectrometry (LC-HRMS) to identify the compounds in EFSs by searching databases and Global Natural Products Social Molecular Networking (GNPS), and we comprehensively explored the changes in the chemical composition of EFSs resulting from various processing methods via statistical analysis. Results: A total of 438 compounds were identified from EFSs, of which 283 were identified through database searches and 155 were identified via GNPS propagation. Statistical analysis revealed 32 and 38 differential compounds in dry-fried Euryale ferox seeds (DFEFSs) and bran-fried Euryale ferox seeds (BFEFSs), respectively. Additionally, we found a significant increase in the lipid content of the fried EFSs. Conclusions: This study provides valuable data to support the quality evaluation of processed EFSs and contributes to the research on the material basis of their medicinal efficacy. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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18 pages, 11082 KiB

Open AccessArticle

Metabolic Reprogramming of Gastric Cancer Revealed by a Liquid Chromatography–Mass Spectrometry-Based Metabolomics Study

by Lina Zhou, Benzhe Su, Zexing Shan, Zhenbo Gao, Xingyu Guo, Weiwei Wang, Xiaolin Wang, Wenli Sun, Shuai Yuan, Shulan Sun, Jianjun Zhang, Guowang Xu and Xiaohui Lin

Metabolites 2025, 15(4), 222; https://doi.org/10.3390/metabo15040222 - 25 Mar 2025

Viewed by 337

Abstract

Background/Objectives: Gastric cancer (GC) is a prevalent malignant tumor worldwide, with its pathological mechanisms largely unknown. Understanding the metabolic reprogramming associated with GC is crucial for the prevention and treatment of this disease. This study aims to identify significant alterations in metabolites and pathways related to the development of GC. Methods: A liquid chromatography–mass spectrometry-based non-targeted metabolomics data acquisition was performed on paired tissues from 80 GC patients. Differences in metabolic profiles between tumor and adjacent normal tissues were first investigated through univariate and multivariate statistical analyses. Additionally, differential correlation network analysis and a newly proposed network analysis method (NAM) were employed to explore significant metabolite pathways and subnetworks related to tumorigenesis and various TNM stages of GC. Results: Over half of the annotated metabolites exhibited significant alterations. Phosphatidylcholine (PC)_30_0 and fatty acid C20_3 demonstrated strong diagnostic performance for GC, with AUCs of 0.911 and 0.934 in the discovery and validation sets, respectively. Differential correlation network analysis revealed significant fatty acid-related metabolic reprogramming in GC with elevated levels of medium-chain acylcarnitines and increased activity of medium-chain acyl-CoA dehydrogenase, firstly observed in clinical GC tissues. Of note, using NAM, two correlation subnetworks were identified as having significant alterations across different TNM stages, centered with choline and carnitine C4_0-OH, respectively. Conclusions: The identified significant alterations in fatty acid metabolism and TNM-related metabolic subnetworks in GC tissues will facilitate future investigations into the metabolic reprogramming associated with gastric cancer. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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20 pages, 15032 KiB

Open AccessArticle

Multi-Omics Profiling Reveals Glycerolipid Metabolism-Associated Molecular Subtypes and Identifies ALDH2 as a Prognostic Biomarker in Pancreatic Cancer

by Jifeng Liu, Shurong Ma, Dawei Deng, Yao Yang, Junchen Li, Yunshu Zhang, Peiyuan Yin and Dong Shang

Metabolites 2025, 15(3), 207; https://doi.org/10.3390/metabo15030207 - 18 Mar 2025

Viewed by 316

Abstract

Background: The reprogramming of lipid metabolism, especially glycerolipid metabolism (GLM), plays a key role in cancer progression and response to therapy. However, the role and molecular characterization of GLM in pancreatic cancer (PC) remain unclear. Methods: A pan-cancer analysis of glycerolipid metabolism-related genes (GMRGs) was first conducted to assess copy-number variants, single-nucleotide variations, methylation, and mRNA expression. Subsequently, GLM in PC was characterized using lipidomics, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomic analysis. A cluster analysis based on bulk RNA sequencing data from 930 PC samples identified GLM-associated subtypes, which were then analyzed for differences in prognosis, biological function, immune microenvironment, and drug sensitivity. To prioritize prognostically relevant GMRGs in PC, we employed a random forest (RF) algorithm to rank their importance across 930 PC samples. Finally, the key biomarker of PC was validated using PCR and immunohistochemistry. Results: Pan-cancer analysis identified molecular features of GMRGs in cancers, while scRNA-seq, spatial transcriptomics, and lipidomics highlighted GLM heterogeneity in PC. Two GLM-associated subtypes with significant prognostic, biofunctional, immune microenvironmental, and drug sensitivity differences were identified in 930 PC samples. Finally, ALDH2 was identified as a novel prognostic biomarker in PC and validated in a large number of datasets and clinical samples. Conclusions: This study highlights the crucial role of GLM in PC and defines a new PC subtype and prognostic biomarker. These findings establish a novel avenue for studying prognostic prediction and precision medicine in PC patients. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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17 pages, 5439 KiB

Open AccessArticle

Metabolomics Approach Revealed Polyunsaturated Fatty Acid Disorders as Pathogenesis for Chronic Pancreatitis−Induced Osteoporosis in Mice

by Xinlin Liu, Fenglin Hu, Yunshu Zhang, Shurong Ma, Haihua Liu, Dong Shang and Peiyuan Yin

Metabolites 2025, 15(3), 173; https://doi.org/10.3390/metabo15030173 - 3 Mar 2025

Viewed by 664

Abstract

Background: Osteoporosis is frequently observed in patients with chronic pancreatitis, and both conditions are closely associated with systemic metabolic disorders. However, the underlying mechanisms linking chronic pancreatitis and osteoporosis remain unclear. Methods: In this study, we utilized high−performance liquid chromatography–mass spectrometry (HPLC−MS) to conduct metabolomics and lipidomics analyses on pancreatic, serum, and other tissues from a mouse model of chronic pancreatitis−induced osteoporosis (CP−OP), with the aim to elucidate the metabolism−related pathogenic mechanisms of CP−OP. Results: We identified over 405 metabolites and 445 lipids, and our findings revealed that several metabolites involving the tricarboxylic acid (TCA) cycle, as well as triacylglycerols and diacylglycerols with higher saturation, were significantly increased in the CP−OP model. In contrast, triglycerides with higher unsaturation were decreased. Differential pathways were enriched in n−3 long−chain polyunsaturated fatty acid metabolism in both pancreatic and bone tissues, and these pathways exhibited positive correlations with bone−related parameters. Furthermore, the modulation of these polyunsaturated fatty acids by Qingyi granules demonstrated significant therapeutic effects on CP−OP, as validated in mouse models. Conclusions: Through the metabolomics approach, we uncovered that disorders in polyunsaturated fatty acids play a critical role in the pathogenesis of CP−OP. This study not only enhances our understanding of the pathogenesis of CP−OP but also highlights the therapeutic potential of targeting polyunsaturated fatty acids as a future intervention strategy for osteoporosis treatment. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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14 pages, 2993 KiB

Open AccessArticle

Reference Intervals of Serum Metabolites and Lipids of a Healthy Chinese Population Determined by Liquid Chromatography-Mass Spectrometry

by Yuqing Zhang, Jinhui Zhao, Hui Zhao, Xin Lu, Xueni Jia, Xinjie Zhao and Guowang Xu

Metabolites 2025, 15(2), 106; https://doi.org/10.3390/metabo15020106 - 7 Feb 2025

Viewed by 684

Abstract

Background: Metabolomics serves as a very useful tool for elucidating disease mechanisms and identifying biomarkers. Establishing reference intervals (RIs) of metabolites in a healthy population is crucial to the application of metabolomics in life sciences and clinics. Methods: We enrolled 615 healthy Chinese adults aged between 21 and 85 years. Their health status was ascertained through clinical examinations, biochemical parameters, and medical history. Targeted metabolomics and lipidomics analyses were applied to quantify 705 metabolites and lipids in the serum, establishing RIs and investigating the effect of sex and age on the metabolome and lipidome. Results: This study is the first large-scale effort in China to establish RIs for metabolites in the apparently healthy population. We found that most of the sex-related metabolites, including amino acids, acyl-carnitines and triacylglycerols, had higher concentrations in males, while the other sex-related lipids showed higher concentrations in females. Most of the age-related metabolites increased with age, including those associated with protein synthesis, nitric oxide synthesis, energy metabolism, and lipid metabolism. Conclusions: This study gives the reference intervals of the healthy Chinese metabolome and lipidome and their relationship with sex and age, which facilitates life sciences and precision medicine, especially for disease research and biomarker discovery. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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13 pages, 894 KiB

Open AccessArticle

Metabolomic Characterisation of Low-Density Lipoproteins Isolated from Iodixanol and KBr-Based Density Gradient Ultracentrifugation

by Richard J. Webb, John K. Lodge, Sophie S. Scott and Ian G. Davies

Metabolites 2025, 15(2), 68; https://doi.org/10.3390/metabo15020068 - 22 Jan 2025

Viewed by 863

Abstract

Background/Objectives: Salt-based density gradient ultracentrifugation (SBUC) is frequently used to isolate lipoproteins for their subsequent analysis. However, the addition of salts may disrupt their molecular composition. Therefore, the aim of the present study was to assess the impact of SBUC upon the molecular composition of low-density lipoprotein (LDL) particles, compared to a validated non-salt method involving iodixanol gradient ultracentrifugation (IGUC). Methods: Whole human plasma was analysed for various lipid parameters before LDL particles were isolated using both SBUC and IGUC methods. Each fraction was then filtered to obtain low-molecular-weight compounds. The LDL molecular content of the resulting fractions from both methods was determined using untargeted liquid chromatography–mass spectrometry (LC-MS) in positive and negative modes. Results: A total of 1041 and 401 features were putatively identified using positive and negative modes, respectively. Differences were shown in the molecular composition of LDL prepared using SBUC and IGUC; in positive mode ionisation, the PLS-DA model showed reasonable fit and discriminatory power (R2 = 0.63, Q2 = 0.58, accuracy 0.88) and permutation testing was significant (p < 0.001). Conclusions: The findings reveal distinct differences in the small molecule composition of LDL prepared using the two methods, with IGUC exhibiting greater variation. In negative mode, both methods detected phospholipids, long-chain sphingolipids, and ceramides, but IGUC showed higher fold differences for some phospholipids. However, in positive mode, non-native brominated adducts were found in LDL isolated using SBUC and evidence of potential bacterial contamination was discovered in samples prepared using IGUC, both of which have the capacity to affect in vitro experiments. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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14 pages, 5115 KiB

Open AccessArticle

Comparative Study of Lipid Profile for Mice Treated with Cyclophosphamide by HPLC-HRMS and Bioinformatics

by Ekaterina Demicheva, Fernando Jonathan Polanco Espino, Pavel Vedeneev, Vadim Shevyrin, Aleksey Buhler, Elena Mukhlynina, Olga Berdiugina, Alicia del Carmen Mondragon, Alberto Cepeda Sáez, Aroa Lopez-Santamarina, Alejandra Cardelle-Cobas, Olga Solovyova, Irina Danilova, Jose Manuel Miranda and Elena Kovaleva

Metabolites 2025, 15(1), 60; https://doi.org/10.3390/metabo15010060 - 16 Jan 2025

Viewed by 861

Abstract

Purpose: Immunodeficiency conditions, which are characterized by reduced immune activity that promotes the development of chronic diseases, are needed for efficient monitoring. A promising area of monitoring and early diagnosis of immunodeficiency diseases is the determination of metabolic biomarkers in the blood. Methods: In this work, we identified a set of lipid biomarkers of immunodeficiency states by performing high-performance liquid chromatography–high-resolution mass spectrometry (HPLC-HRMS) analysis of blood plasma samples from mice and processing them with bioinformatics approaches. Potential biomarkers were selected through statistical analysis and further validated by MS/MS. Conclusions: As a result, 15 lipids were confirmed and selected as potential biomarkers of immunodeficiency states. The selected biomarkers can be further studied and serve as promising targets for the early diagnosis of immunodeficiency diseases. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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14 pages, 5767 KiB

Open AccessArticle

Early Diagnosis of Bloodstream Infections Using Serum Metabolomic Analysis

by Shuang Han, Ruihua Li, Hao Wang, Lin Wang, Yiming Gao, Yaolin Wen, Tianyang Gong, Shiyu Ruan, Hui Li and Peng Gao

Metabolites 2024, 14(12), 685; https://doi.org/10.3390/metabo14120685 - 6 Dec 2024

Viewed by 734

Abstract

Background: Bloodstream infections (BSIs) pose a great challenge to treating patients, especially those with underlying diseases, such as immunodeficiency diseases. Early diagnosis helps to direct precise empirical antibiotic administration and proper clinical management. This study carried out a serum metabolomic analysis using blood specimens sampled from patients with a suspected infection whose routine culture results were later demonstrated to be positive. Methods: A liquid chromatograph-mass spectrometry-based metabolomic analysis was carried out to profile the BSI serum samples. The serum metabolomics data could be used to successfully differentiate BSIs from non-BSIs. Results: The major classes of the isolated pathogens (e.g., Gram-positive and Gram-negative bacteria) could be differentiated using our optimized statistical algorithms. In addition, by using different machine-learning algorithms, the isolated pathogens could also be classified at the species levels (e.g., Escherichia coli and Klebsiella pneumoniae) or according to their specific antibiotic-resistant phenotypes (e.g., extended-spectrum β-lactamase-producing and non-producing phenotypes) if needed. Conclusions: This study provides an early diagnosis method that could be an alternative to the traditional time-consuming culture process to identify BSIs. Moreover, this metabolomics strategy was less affected by several risk factors (e.g., antibiotics administration) that could produce false culture results. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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13 pages, 2396 KiB

Open AccessArticle

Exploration of Freshness Identification Method for Refrigerated Vegetables Based on Metabolomics

by Zixuan Meng, Haichao Zhang, Jing Wang, Lianfeng Ai and Weijun Kang

Metabolites 2024, 14(12), 665; https://doi.org/10.3390/metabo14120665 - 1 Dec 2024

Viewed by 961

Abstract

Background: The rapid development of refrigerated transportation technology for fresh vegetables has extended their shelf life. Some vegetables may appear undamaged on the surface, but their freshness may have decreased, often resulting in the phenomenon of passing off inferior vegetables as good. It is very important to establish a detection method for identifying and assessing the freshness of vegetables. Methods: Therefore, based on metabolomics methods, this study innovatively employed UHPLC-Q-Exactive Orbitrap MS and GC–MS techniques to investigate the metabolites in the refrigerated storage of four vegetables, namely chard (Beta vulgaris var. cicla L), lettuce (Lactuca sativa var. ramose Hort.), crown daisy (Glebionis coronaria (L.) Cass. ex Spach), and tomato (Solanum lycopersicum L.), exploring key biomarkers for assessing their freshness. UPLC-TQ MS was used for the quantitative analysis of key metabolites. Results: The results showed that arginine biosynthesis and the metabolism of alanine, aspartate, and glutamate are key pathways in vegetable metabolism. Four key metabolites were selected from chard, five from lettuce, three from crown daisy, and five from tomato. Conclusions: Comparing the content of substances such as alanine and arginine can help infer the freshness and nutritional value of the vegetables, providing important references for detecting spoilage, determining storage time, and improving transportation conditions. This research holds significant relevance for the vegetable transportation industry. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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21 pages, 6832 KiB

Open AccessArticle

Identification of Spatial Specific Lipid Metabolic Signatures in Long-Standing Diabetic Kidney Disease

by Yiran Zhang, Hai-Long Piao and Di Chen

Metabolites 2024, 14(11), 641; https://doi.org/10.3390/metabo14110641 - 20 Nov 2024

Cited by 1 | Viewed by 1100

Abstract

Background: Diabetic kidney disease (DKD) is a major complication of diabetes leading to kidney failure. Methods: This study investigates lipid metabolism profiles of long-standing DKD (LDKD, diabetes duration > 10 years) by integrative analysis of available single-cell RNA sequencing and spatial multi-omics data (focusing on spatial continuity samples) from the Kidney Precision Medicine Project. Results: Two injured cell types, an injured thick ascending limb (iTAL) and an injured proximal tubule (iPT), were identified and significantly elevated in LDKD samples. Both iTAL and iPT exhibit increased lipid metabolic and biosynthetic activities and decreased lipid and fatty acid oxidative processes compared to TAL/PT cells. Notably, compared to PT, iPT shows significant upregulation of specific injury and fibrosis-related genes, including FSHR and BMP7. Meanwhile, comparing iTAL to TAL, inflammatory-related genes such as ANXA3 and IGFBP2 are significantly upregulated. Furthermore, spatial metabolomics analysis reveals regionally distributed clusters in the kidney and notably differentially expressed lipid metabolites, such as triglycerides, glycerophospholipids, and sphingolipids, particularly pronounced in the inner medullary regions. Conclusions: These findings provide an integrative description of the lipid metabolism landscape in LDKD, highlighting injury-associated cellular processes and potential molecular mechanisms. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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