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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biology".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 4702

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Dr. Maria Assunta Acquavia

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Department of Basic and Applied Sciences, University of Basilicata, Viale dell’Ateneo Lucano, 10-85100 Potenza, Italy
Interests: liquid chromatography; mass spectrometry; high-resolution mass spectrometry; food; metabolomics; environment
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Special Issue Information

Dear Colleagues,

To date, metabolomics has emerged as an indispensable platform for the overall analysis of the metabolites, i.e. all the small molecules occurring in the biological systems, including humans, plants, foods, animals and microbes, to discover networks and interactions between them. Moreover, metabolomic studies can help in the discovering of new biomarkers for the diagnosis of health diseases. Studies concerning metabolomics are in continuous progress, allowing new developments in the analytical methods and data analysis tools. This Special Issue is focused on the progresses of the metabolomic technology, both analytical methods and data analysis, in the fields of health and diseases. The topics covered include but are not limited to the application of the modern analytical techniques, such as GC-MS, LC-MS/MS and HRMS, for the comprehensive evaluation of the metabolic fingerprint of biological systems related to the diagnosis and mechanisms elucidations of health diseases involving human or animal samples, or the target identification of specific classes of compounds as well as the manipulation of the big data produced during metabolomic analysis.

Dr. Maria Assunta Acquavia
Guest Editor

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Keywords

metabolomics
health
diseases
target metabolites
mass spectrometry
hyphenated techniques

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Published Papers (6 papers)

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Research

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20 pages, 2879 KiB

Open AccessArticle

The Determination of Trimethylamine N-Oxide and Organic Acids Connected with Gut Microbiota in the Urine of Parkinson’s Disease Patients: A Pilot Study

by Paulina Gątarek, Małgorzata Pawełczyk, Barbara Bobrowska-Korczaka, Joanna Giebułtowicz, Andrzej Głąbiński and Joanna Kałużna-Czaplińska

Int. J. Mol. Sci. 2025, 26(10), 4575; https://doi.org/10.3390/ijms26104575 - 10 May 2025

Viewed by 253

Abstract

Parkinson’s disease (PD) progression appears closely tied to gut microbiota alterations, with microbial metabolites potentially influencing neurodegeneration. This pilot study employed GC-MS and LC-MS/MS to analyze the urinary levels of gut-derived metabolites—including succinic acid, p-hydroxyphenylacetic acid, homovanillic acid (HVA), vanillylmandelic acid (VMA), adipic acid, and trimethylamine N-oxide (TMAO)—in 20 PD patients versus 20 age-matched controls. The key findings revealed that PD patients exhibited significantly elevated succinic acid (p = 0.0018) and HVA (p = 0.0002) levels alongside reduced TMAO (p = 1.65 × 10⁻⁵). Notably, succinic acid showed an inverse correlation with disease severity (Hoehn and Yahr scale: r = −0.63; p = 0.0028), while TMAO demonstrated a strong positive association (r = 0.81; p = 0.00001). The elevated HVA, a dopamine metabolite, may serve as a potential biomarker for monitoring levodopa treatment efficacy. These results suggest that gut microbiota metabolites contribute to PD pathogenesis, with TMAO and succinic acid emerging as promising biomarkers for tracking disease progression. This study highlights the clinical potential of non-invasive urinary metabolite profiling using GC-MS and LC-MS/MS techniques. However, further investigation through larger-scale studies is needed to confirm these findings and elucidate the underlying mechanisms connecting gut microbiota dysbiosis to PD neurodegeneration. Full article

(This article belongs to the Special Issue Research Progress of Metabolomics in Health and Disease)

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16 pages, 2719 KiB

Open AccessArticle

Methoxylated Chrysin and Quercetin as Potent Stimulators of Melanogenesis

by Pattara Poungcho, Rita Hairani, Chatchai Chaotham, Wanchai De-Eknamkul and Warinthorn Chavasiri

Int. J. Mol. Sci. 2025, 26(7), 3281; https://doi.org/10.3390/ijms26073281 - 1 Apr 2025

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Abstract

Polymethoxyflavonoids (PMFs) from plants are known to exhibit melanogenic activity. Very little is known about their structure-activity relationships, and this was the aim of this study. Several series of alkoxy flavonoids were synthesized via semisynthetic and total synthetic pathways. Their structures were identified by NMR analyses, followed by evaluating their potency on the stimulation of melanogenesis using mouse B16F10 and human MNT-1 cells. Among more than twenty methoxylated flavonoids, 5,7-dimethoxychrysin (dimethoxylated chrysin, F1) and 3,3′,4′,5,7-pentamethoxyquercetin (pentamethoxylated quercetin, F21) appeared to be the most active melanogenic-stimulating compounds in a dose-dependent manner. Both compounds showed no effect on cell viability as determined by MTT assay. The structure-activity relationship study of PMFs revealed that the -OCH₃ substituent at 5 and 7 positions of A-ring are the most important as melanogenic-stimulating part (e.g., 5,7-dimethoxychrysin, F1) followed by at 3′ and 4′ positions of B-ring, and at 3 positions of C-ring (e.g., 3,3′,4′,5,7-pentamethoxyquercetin, F21), Therefore, both natural methoxylated flavonoid derivatives of chrysin and quercetin have a potential to be developed further as melanogenic stimulators. Full article

(This article belongs to the Special Issue Research Progress of Metabolomics in Health and Disease)

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23 pages, 3859 KiB

Open AccessArticle

Deciphering Colorectal Cancer–Hepatocyte Interactions: A Multiomics Platform for Interrogation of Metabolic Crosstalk in the Liver–Tumor Microenvironment

by Alisa B. Nelson, Lyndsay E. Reese, Elizabeth Rono, Eric D. Queathem, Yinjie Qiu, Braedan M. McCluskey, Alexandra Crampton, Eric Conniff, Katherine Cummins, Ella Boytim, Senali Dansou, Justin Hwang, Sandra E. Safo, Patrycja Puchalska, David K. Wood, Kathryn L. Schwertfeger and Peter A. Crawford

Int. J. Mol. Sci. 2025, 26(5), 1976; https://doi.org/10.3390/ijms26051976 - 25 Feb 2025

Viewed by 763

Abstract

Metabolic reprogramming is a hallmark of cancer, enabling tumor cells to adapt to and exploit their microenvironment for sustained growth. The liver is a common site of metastasis, but the interactions between tumor cells and hepatocytes remain poorly understood. In the context of liver metastasis, these interactions play a crucial role in promoting tumor survival and progression. This study leverages multiomics coverage of the microenvironment via liquid chromatography and high-resolution, high-mass-accuracy mass spectrometry-based untargeted metabolomics, ¹³C-stable isotope tracing, and RNA sequencing to uncover the metabolic impact of co-localized primary hepatocytes and a colon adenocarcinoma cell line, SW480, using a 2D co-culture model. Metabolic profiling revealed disrupted Warburg metabolism with an 80% decrease in glucose consumption and 94% decrease in lactate production by hepatocyte–SW480 co-cultures relative to SW480 control cultures. Decreased glucose consumption was coupled with alterations in glutamine and ketone body metabolism, suggesting a possible fuel switch upon co-culturing. Further, integrated multiomics analysis indicates that disruptions in metabolic pathways, including nucleoside biosynthesis, amino acids, and TCA cycle, correlate with altered SW480 transcriptional profiles and highlight the importance of redox homeostasis in tumor adaptation. Finally, these findings were replicated in three-dimensional microtissue organoids. Taken together, these studies support a bioinformatic approach to study metabolic crosstalk and discovery of potential therapeutic targets in preclinical models of the tumor microenvironment. Full article

(This article belongs to the Special Issue Research Progress of Metabolomics in Health and Disease)

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19 pages, 3204 KiB

Open AccessArticle

Microbiota Co-Metabolism Alterations Precede Changes in the Host Metabolism in the Early Stages of Diet-Induced MASLD in Wistar Rats

by María Martín-Grau, Pilar Casanova, Laura Moreno-Morcillo, José Manuel Morales, Vannina G. Marrachelli and Daniel Monleón

Int. J. Mol. Sci. 2025, 26(3), 1288; https://doi.org/10.3390/ijms26031288 - 2 Feb 2025

Viewed by 1130

Abstract

Metabolic-dysfunction-associated steatotic liver disease (MASLD) affects around 30% of the global population. The sexual dimorphism and gut microbiota play an important role in the early development of MASLD. The main objective of this research was to investigate metabolic changes during the early subclinical MASLD progression, for identifying the sequence of events and evaluating the impact of sexual dimorphism and the microbiota on the initial stages of MASLD development. Male and female Wistar rats 18 weeks old were randomly divided into different groups and fed a chow diet or a 45% high-fat diet for 21 weeks. Every three weeks, samples of serum, urine, and faeces were collected and studied by metabolomics. Furthermore, the liver was analysed at the endpoint. In addition, the gut microbiota was analysed from faecal samples over time using 16S rRNA gene-targeted group-specific primers. Our results revealed that three weeks on an HFD reduced the bacterial diversity in the faecal microbiota of Wistar rats, accompanied by changes in the faecal and urine metabolome. The HFD-induced alterations in microbiota-related co-metabolites in the liver, blood, urine, and faeces indicate a significant role of host–microbiota co-metabolism changes in the early stages of MASLD. In this study, we provide a comprehensive longitudinal analysis, detailing the sequence of events in the early development of MASLD. Our findings suggest that alterations in the gut microbiota diversity and co-metabolism occur before changes in host metabolism in the early onset of liver steatosis, a subclinical phase of MASLD. Full article

(This article belongs to the Special Issue Research Progress of Metabolomics in Health and Disease)

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Review

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28 pages, 1205 KiB

Open AccessReview

Application of Multiomics in Perinatology: A Metabolomics Integration-Focused Review

by Alice Bosco, Francesca Arru, Alessandra Abis, Vassilios Fanos and Angelica Dessì

Int. J. Mol. Sci. 2025, 26(9), 4164; https://doi.org/10.3390/ijms26094164 - 27 Apr 2025

Viewed by 258

Abstract

Precision medicine stems from a new approach to the prevention, diagnosis and treatment of patients, due to the shift in focus away from pathology and towards the uniqueness of the individual, personalising the diagnostic–therapeutic pathway. This paradigm shift has been made possible by the emergence of new high-throughput technologies capable of generating large amounts of data on multiple levels of a biological system, identifying pathology-related genes, transcripts, proteins and metabolites. Metabolomics plays a primary role in this context, providing, through non-invasive sampling, a very close image of the phenotype of the organism being studied by detecting metabolites, end products downstream of gene transcription, present in cells, tissues, organs and biological fluids. The enormous amount of data that these modern technologies make available, together with the need to elucidate the complex interplay of the various biological levels by combining data from distinct omics, has led to the need to employ advanced informatics techniques, among which artificial intelligence has recently emerged. These innovations are of great interest in the field of perinatology, representing an attempt to optimise the diagnostic timeline for the most critical newborns. In addition, they may contribute to the improvement of prevention strategies available to date. All these contributions prove to be crucial at very vulnerable life stages, allowing crucial intervention opportunities. In this review, we have analysed studies that have integrated metabolomics with at least one other omics in the perinatal field, attempting to highlight the usefulness of multiomics integration and the different methods employed. Full article

(This article belongs to the Special Issue Research Progress of Metabolomics in Health and Disease)

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20 pages, 1951 KiB

Open AccessReview

Advances in Metabolomics: A Comprehensive Review of Type 2 Diabetes and Cardiovascular Disease Interactions

by Lilian Fernandes Silva and Markku Laakso

Int. J. Mol. Sci. 2025, 26(8), 3572; https://doi.org/10.3390/ijms26083572 - 10 Apr 2025

Viewed by 676

Abstract

Type 2 diabetes (T2D) and cardiovascular diseases (CVDs) are major public health challenges worldwide. Metabolomics, the exhaustive assessment of metabolites in biological systems, offers important insights regarding the metabolic disturbances related to these disorders. Recent advances toward the integration of metabolomics into clinical practice to facilitate the discovery of novel biomarkers that can improve the diagnosis, prognosis, and treatment of T2D and CVDs are discussed in this review. Metabolomics offers the potential to characterize the key metabolic alterations associated with disease pathophysiology and treatment. T2D is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms; therefore, the disease-causing pathways of T2D are not completely understood. Recent studies have identified several robust clusters of T2D variants representing biologically meaningful, distinct pathways, such as the beta cell and proinsulin cluster related to pancreatic insulin secretion, obesity, lipodystrophy, the liver/lipid cluster, glycemia, and blood pressure, and metabolic syndrome clusters representing different pathways causing insulin resistance. Regarding CVDs, recent studies have allowed the metabolomic profile to delineate pathways that contribute to atherosclerosis and heart failure, as well as to the development of targeted therapy. This review also covers the role of metabolomics in integrated metabolic genomics and other omics platforms to better understand disease mechanisms, along with the transition toward precision medicine. This review further investigates the use of metabolomics in multi-metabolite modeling to enhance risk prediction models for predicting the first occurrence of major adverse cardiovascular events among individuals with T2D, highlighting the value of such approaches in optimizing the preventive and therapeutic models used in clinical practice. Full article

(This article belongs to the Special Issue Research Progress of Metabolomics in Health and Disease)

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