Advances in Metabolomics

A topical collection in Metabolites (ISSN 2218-1989). This collection belongs to the section "Advances in Metabolomics".

Viewed by 25072

Editors


E-Mail Website
Collection Editor
1. Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy
2. Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
3. Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), 50019 Sesto Fiorentino, Italy
Interests: applications of NMR-based metabolomics in biomedicine and in food science; NMR fingerprinting and profiling of biological samples; development of new analytical approaches for NMR metabolomics; development of new tools for NMR data analysis
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Collection Editor
Systems and Synthetic Biology, Wageningen University and Research, Wageningen, The Netherlands
Interests: mathematics; statistics; biostatistics; chemometrics; comparative genomics; data analysis; data mining; mathematical models; metabolomics; multivariate analysis; genomics; proteomics; statistical analysis; transcriptomics; health; systems biology; statistical sampling techniques; metagenomics; big data
Special Issues, Collections and Topics in MDPI journals

Topical Collection Information

Dear Colleagues,

At present, metabolomics is a mature research field with a considerable track-record of successful applications, especially in the domains of biomedical and agricultural sciences. During the last decade, it has become a valuable instrument for providing insights into the molecular mechanisms of numerous phenomena, thus contributing to the characterization of the biological functioning of living systems. Albeit no more in its infancy stage, metabolomics still needs constant technological improvement to be exploited to its full potential. For this reason, this Topical Collection aims to publish high-quality research papers or systematic reviews discussing bleeding edge innovative approaches that will boost metabolomics to the very vanguard of its technological advancement.

We make a call for articles from all the various fields of metabolomics applications ranging from biomedicine, pharmacology, biochemistry to nutrition, food and agricultural sciences. Without restrictions to any particular field of application or analytical platform, innovative aspects can be related, for instance, to 1) pre-analytical and analytical protocols, 2) instrumental development, 3) sample collection and data acquisition strategies, 4) data analysis algorithms, tools, and software, 4) multi-omic and multi-platform studies, and 5) groundbreaking applications with a high technology readiness level.

Dr. Leonardo Tenori
Dr. Edoardo Saccenti
Collection Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • metabolomics
  • technological advancements
  • analytical platforms
  • nuclear magnetic resonance
  • mass spectrometry
  • clinical applications
  • food science and nutrition
  • metabolite annotation and quantification
  • data mining and artificial intelligence
  • high technology readiness level

Published Papers (10 papers)

2024

Jump to: 2023, 2022, 2021

17 pages, 3312 KiB  
Article
Discrimination of Lipogenic or Glucogenic Diet Effects in Early-Lactation Dairy Cows Using Plasma Metabolite Abundances and Ratios in Combination with Machine Learning
by Xiaodan Wang, Sanjeevan Jahagirdar, Wouter Bakker, Carolien Lute, Bas Kemp, Ariette van Knegsel and Edoardo Saccenti
Metabolites 2024, 14(4), 230; https://doi.org/10.3390/metabo14040230 - 17 Apr 2024
Viewed by 178
Abstract
During early lactation, dairy cows have a negative energy balance since their energy demands exceed their energy intake: in this study, we aimed to investigate the association between diet and plasma metabolomics profiles and how these relate to energy unbalance of course in [...] Read more.
During early lactation, dairy cows have a negative energy balance since their energy demands exceed their energy intake: in this study, we aimed to investigate the association between diet and plasma metabolomics profiles and how these relate to energy unbalance of course in the early-lactation stage. Holstein-Friesian cows were randomly assigned to a glucogenic (n = 15) or lipogenic (n = 15) diet in early lactation. Blood was collected in week 2 and week 4 after calving. Plasma metabolite profiles were detected using liquid chromatography–mass spectrometry (LC-MS), and a total of 39 metabolites were identified. Two plasma metabolomic profiles were available every week for each cow. Metabolite abundance and metabolite ratios were used for the analysis using the XGboost algorithm to discriminate between diet treatment and lactation week. Using metabolite ratios resulted in better discrimination performance compared with the metabolite abundances in assigning cows to a lipogenic diet or a glucogenic diet. The quality of the discrimination of performance of lipogenic diet and glucogenic diet effects improved from 0.606 to 0.753 and from 0.696 to 0.842 in week 2 and week 4 (as measured by area under the curve, AUC), when the metabolite abundance ratios were used instead of abundances. The top discriminating ratios for diet were the ratio of arginine to tyrosine and the ratio of aspartic acid to valine in week 2 and week 4, respectively. For cows fed the lipogenic diet, choline and the ratio of creatinine to tryptophan were top features to discriminate cows in week 2 vs. week 4. For cows fed the glucogenic diet, methionine and the ratio of 4-hydroxyproline to choline were top features to discriminate dietary effects in week 2 or week 4. This study shows the added value of using metabolite abundance ratios to discriminate between lipogenic and glucogenic diet and lactation weeks in early-lactation cows when using metabolomics data. The application of this research will help to accurately regulate the nutrition of lactating dairy cows and promote sustainable agricultural development. Full article
Show Figures

Figure 1

19 pages, 2194 KiB  
Article
Application of Clinical Blood Metabogram to Type 2 Diabetes Mellitus
by Petr G. Lokhov, Elena E. Balashova, Oxana P. Trifonova, Dmitry L. Maslov, Ekaterina A. Shestakova, Marina V. Shestakova and Ivan I. Dedov
Metabolites 2024, 14(3), 168; https://doi.org/10.3390/metabo14030168 - 18 Mar 2024
Viewed by 771
Abstract
The clinical blood metabogram (CBM) was developed to match a tailored analysis of the blood metabolome to the time, cost, and reproducibility constraints of clinical laboratory testing. By analyzing the main blood metabolite groups, CBM offers clinically relevant information about the intake of [...] Read more.
The clinical blood metabogram (CBM) was developed to match a tailored analysis of the blood metabolome to the time, cost, and reproducibility constraints of clinical laboratory testing. By analyzing the main blood metabolite groups, CBM offers clinically relevant information about the intake of low-molecular substances into the organism, humoral regulation, liver function, amino acid level, and the lipid and carbohydrate metabolism. The purpose of this work was to investigate the relevance of using the CBM in patients with diabetes mellitus. For this, a CBM was obtained for 18 healthy individuals, 12 individuals with prediabetes, and 64 individuals with type 2 diabetes mellitus, separated into groups according to fasting blood glucose and oral glucose tolerance tests. The results showed that the CBM reveals diabetes-associated metabolic alterations in the blood, including changes in the levels of carbohydrates, ketone bodies, eicosanoids, phospholipids, and amino acids, which are consistent with the scientific data available to date. The CBM enabled the separation of diabetic patients according to their metabolic metabotypes, providing both a general overview of their metabolic alterations and detailing their individual metabolic characteristics. It was concluded that the CBM is a precise and clinically applicable test for assessing an individual’s metabolic status in diabetes mellitus for diagnostic and treatment purposes. Full article
Show Figures

Figure 1

2023

Jump to: 2024, 2022, 2021

10 pages, 1121 KiB  
Article
On the Fate of Butyl Methoxydibenzoylmethane (Avobenzone) in Coral Tissue and Its Effect on Coral Metabolome
by Fanny Clergeaud, Maeva Giraudo, Alice M. S. Rodrigues, Evane Thorel, Philippe Lebaron and Didier Stien
Metabolites 2023, 13(4), 533; https://doi.org/10.3390/metabo13040533 - 07 Apr 2023
Viewed by 1692
Abstract
The intensive use of sunscreen products has raised concerns regarding their environmental toxicity and the adverse impacts of ultraviolet (UV) filters on ecologically important coral communities. Prior metabolomic analyses on symbiotic coral Pocillopora damicornis exposed to the UV filter butyl methoxydibenzoylmethane (BM, avobenzone) [...] Read more.
The intensive use of sunscreen products has raised concerns regarding their environmental toxicity and the adverse impacts of ultraviolet (UV) filters on ecologically important coral communities. Prior metabolomic analyses on symbiotic coral Pocillopora damicornis exposed to the UV filter butyl methoxydibenzoylmethane (BM, avobenzone) revealed unidentified ions in the holobiont metabolome. In the present study, follow-up differential metabolomic analyses in BM-exposed P. damicornis detected 57 ions with significantly different relative concentrations in exposed corals. The results showed an accumulation of 17 BM derivatives produced through BM reduction and esterification. The major derivative identified C16:0-dihydroBM, which was synthesized and used as a standard to quantify BM derivatives in coral extracts. The results indicated that relative amounts of BM derivatives made up to 95% of the total BM (w/w) absorbed in coral tissue after 7 days of exposure. Among the remaining metabolites annotated, seven compounds significantly affected by BM exposure could be attributed to the coral dinoflagellate symbiont, indicating that BM exposure might impair the photosynthetic capacity of the holobiont. The present results suggest that the potential role of BM in coral bleaching in anthropogenic areas should be investigated and that BM derivatives should be considered in future assessments on the fate and effects of BM in the environment. Full article
Show Figures

Graphical abstract

2022

Jump to: 2024, 2023, 2021

10 pages, 424 KiB  
Article
Levels of Acylcarnitines and Branched-Chain Amino Acids in Antipsychotic-Treated Patients with Paranoid Schizophrenia with Metabolic Syndrome
by Irina A. Mednova, Alexander A. Chernonosov, Elena G. Kornetova, Arkadiy V. Semke, Nikolay A. Bokhan, Vladimir V. Koval and Svetlana A. Ivanova
Metabolites 2022, 12(9), 850; https://doi.org/10.3390/metabo12090850 - 09 Sep 2022
Cited by 2 | Viewed by 1909
Abstract
Several studies have shown that patients with schizophrenia are at high risk for metabolic syndrome (MetS) and bioenergetic dysfunction. Because acylcarnitines are involved in bioenergetic pathways and reflect the functioning of mitochondria, we hypothesized that these compounds are biomarkers of MetS in schizophrenia. [...] Read more.
Several studies have shown that patients with schizophrenia are at high risk for metabolic syndrome (MetS) and bioenergetic dysfunction. Because acylcarnitines are involved in bioenergetic pathways and reflect the functioning of mitochondria, we hypothesized that these compounds are biomarkers of MetS in schizophrenia. The aim of this work was to quantify acylcarnitines and branched-chain amino acids in patients with schizophrenia comorbid with MetS. The study included 112 patients with paranoid schizophrenia treated with antipsychotics. Among them, 39 subjects met criteria of MetS. Concentrations of 30 acylcarnitines and three amino acids in dry serum spots were measured by liquid chromatography coupled with tandem mass spectrometry. MetS patients were found to have higher levels of valeryl carnitine (C5), leucine/isoleucine, and alanine as compared with patients without MetS, indicating possible participation of these compounds in the pathogenesis of metabolic disorders in schizophrenia. In patients with paranoid schizophrenia with or without MetS, lower levels of carnitines C10, C10:1, C12, and C18 were recorded as compared with the healthy individuals (n = 70), implying deterioration of energy metabolism. We believe that this finding can be explained by effects of antipsychotic medication on an enzyme called carnitine-palmitoyl transferase I. Full article
Show Figures

Figure 1

24 pages, 2202 KiB  
Article
Comparative Metabolite Profiling and Fingerprinting of Medicinal Cinnamon Bark and Its Commercial Preparations via a Multiplex Approach of GC–MS, UV, and NMR Techniques
by Mohamed A. Farag, Sally E. Khaled, Zeina El Gingeehy, Samir Nabhan Shamma and Ahmed Zayed
Metabolites 2022, 12(7), 614; https://doi.org/10.3390/metabo12070614 - 01 Jul 2022
Cited by 17 | Viewed by 2592
Abstract
Various species of cinnamon (Cinnamomum sp.) are consumed as traditional medicine and popular spice worldwide. The current research aimed to provide the first comparative metabolomics study in nine cinnamon drugs and their different commercial preparations based on three analytical platforms, i.e., solid-phase [...] Read more.
Various species of cinnamon (Cinnamomum sp.) are consumed as traditional medicine and popular spice worldwide. The current research aimed to provide the first comparative metabolomics study in nine cinnamon drugs and their different commercial preparations based on three analytical platforms, i.e., solid-phase microextraction coupled to gas chromatography–mass spectrometry method (SPME/GC–MS), nuclear magnetic resonance (NMR), and ultraviolet-visible spectrophotometry (UV/Vis) targeting its metabolome. SPME/GC–MS of cinnamon aroma compounds showed a total of 126 peaks, where (E)-cinnamaldehyde was the major volatile detected at 4.2–60.9% and 6.3–64.5% in authenticated and commercial preparations, respectively. Asides, modeling of the GC/MS dataset could relate the commercial products CP-1 and CP-3 to C. cassia attributed to their higher coumarin and low (E)-cinnamaldehyde content. In contrast, NMR fingerprinting identified (E)-methoxy cinnamaldehyde and coumarin as alternative markers for C. verum and C. iners, respectively. Additionally, quantitative NMR (qNMR) standardized cinnamon extracts based on major metabolites. UV/Vis showed to be of low discrimination power, but its orthogonal projections to latent structures discriminant analysis (OPLS-DA) S-plot showed that C. iners was more abundant in cinnamic acid compared to other samples. Results of this study provide potential insights into cinnamon drugs QC analysis and identify alternative markers for their discrimination. Full article
Show Figures

Graphical abstract

14 pages, 1463 KiB  
Article
Intrapersonal Stability of Plasma Metabolomic Profiles over 10 Years among Women
by Oana A. Zeleznik, Clemens Wittenbecher, Amy Deik, Sarah Jeanfavre, Julian Avila-Pacheco, Bernard Rosner, Kathryn M. Rexrode, Clary B. Clish, Frank B. Hu and A. Heather Eliassen
Metabolites 2022, 12(5), 372; https://doi.org/10.3390/metabo12050372 - 20 Apr 2022
Cited by 8 | Viewed by 2046
Abstract
In epidemiological studies, samples are often collected long before disease onset or outcome assessment. Understanding the long-term stability of biomarkers measured in these samples is crucial. We estimated within-person stability over 10 years of metabolites and metabolite features (n = 5938) in [...] Read more.
In epidemiological studies, samples are often collected long before disease onset or outcome assessment. Understanding the long-term stability of biomarkers measured in these samples is crucial. We estimated within-person stability over 10 years of metabolites and metabolite features (n = 5938) in the Nurses’ Health Study (NHS): the primary dataset included 1880 women with 1184 repeated samples donated 10 years apart while the secondary dataset included 1456 women with 488 repeated samples donated 10 years apart. We quantified plasma metabolomics using two liquid chromatography mass spectrometry platforms (lipids and polar metabolites) at the Broad Institute (Cambridge, MA, USA). Intra-class correlations (ICC) were used to estimate long-term (10 years) within-person stability of metabolites and were calculated as the proportion of the total variability (within-person + between-person) attributable to between-person variability. Within-person variability was estimated among participants who donated two blood samples approximately 10 years apart while between-person variability was estimated among all participants. In the primary dataset, the median ICC was 0.43 (1st quartile (Q1): 0.36; 3rd quartile (Q3): 0.50) among known metabolites and 0.41 (Q1: 0.34; Q3: 0.48) among unknown metabolite features. The three most stable metabolites were N6,N6-dimethyllysine (ICC = 0.82), dimethylguanidino valerate (ICC = 0.72), and N-acetylornithine (ICC = 0.72). The three least stable metabolites were palmitoylethanolamide (ICC = 0.05), ectoine (ICC = 0.09), and trimethylamine-N-oxide (ICC = 0.16). Results in the secondary dataset were similar (Spearman correlation = 0.87) to corresponding results in the primary dataset. Within-person stability over 10 years is reasonable for lipid, lipid-related, and polar metabolites, and varies by metabolite class. Additional studies are required to estimate within-person stability over 10 years of other metabolites groups. Full article
Show Figures

Figure 1

14 pages, 941 KiB  
Article
Vertical Transfer of Metabolites Detectable from Newborn’s Dried Blood Spot Samples Using UPLC-MS: A Chemometric Study
by Alessandra Olarini, Madeleine Ernst, Gözde Gürdeniz, Min Kim, Nicklas Brustad, Klaus Bønnelykke, Arieh Cohen, David Hougaard, Jessica Lasky-Su, Hans Bisgaard, Bo Chawes and Morten Arendt Rasmussen
Metabolites 2022, 12(2), 94; https://doi.org/10.3390/metabo12020094 - 20 Jan 2022
Cited by 7 | Viewed by 3279
Abstract
The pregnancy period and first days of a newborn’s life is an important time window to ensure a healthy development of the baby. This is also the time when the mother and her baby are exposed to the same environmental conditions and intake [...] Read more.
The pregnancy period and first days of a newborn’s life is an important time window to ensure a healthy development of the baby. This is also the time when the mother and her baby are exposed to the same environmental conditions and intake of nutrients, which can be determined by assessing the blood metabolome. For this purpose, dried blood spots (DBS) of newborns are a valuable sampling technique to characterize what happens during this important mother-child time window. We used metabolomics profiles from DBS of newborns (age 2–3 days) and maternal plasma samples at gestation week 24 and postpartum week 1 from n=664 mother-child pairs of the Copenhagen Prospective Studies on Asthma in Childhood 2010 (COPSAC2010) cohort, to study the vertical mother-child transfer of metabolites. Further, we investigated how persistent the metabolites are from the newborn and up to 6 months, 18 months, and 6 years of age. Two hundred seventy two metabolites from UPLC-MS (Ultra Performance Liquid Chromatography-Mass Spectrometry) analysis of DBS and maternal plasma were analyzed using correlation analysis. A total of 11 metabolites exhibited evidence of transfer (R>0.3), including tryptophan betaine, ergothioneine, cotinine, theobromine, paraxanthine, and N6-methyllysine. Of these, 7 were also found to show persistence in their levels in the child from birth to age 6 years. In conclusion, this study documents vertical transfer of environmental and food-derived metabolites from mother to child and tracking of those metabolites through childhood, which may be of importance for the child’s later health and disease. Full article
Show Figures

Graphical abstract

2021

Jump to: 2024, 2023, 2022

16 pages, 3118 KiB  
Article
Promotion of In Vitro Hair Cell-like Cell Differentiation from Human Embryonic Stem Cells through the Regulation of Notch Signaling
by Fengjiao Chen, Ying Yang, Jianling Chen, Zihua Tang, Qian Peng, Jinfu Wang and Jie Ding
Metabolites 2021, 11(12), 873; https://doi.org/10.3390/metabo11120873 - 15 Dec 2021
Cited by 1 | Viewed by 2435
Abstract
The Notch signaling pathway plays an important role in otic neurogenesis by regulating the differentiation of inner ear hair cells and supporting cells. Notch-regulated differentiation is required for the regeneration of hair cells in the inner ear. The temporal expression pattern of Notch [...] Read more.
The Notch signaling pathway plays an important role in otic neurogenesis by regulating the differentiation of inner ear hair cells and supporting cells. Notch-regulated differentiation is required for the regeneration of hair cells in the inner ear. The temporal expression pattern of Notch ligands and receptors during in vitro hair cell-like cell differentiation from human embryonic stem cells (hESCs) was detected by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Subsequently, pAJ-U6-shRNA-CMV-Puro/GFP recombinant lentiviral vectors encoding short hairpin RNAs were used to silence JAG-1, JAG-2, and DLL-1, according to the temporal expression pattern of Notch ligands. Then, the effect of each ligand on the in vitro differentiation of hair cells was examined by RT-PCR, immunofluorescence, and scanning electron microscopy (SEM). The results showed that the individual deletion of JAG-2 or DLL-1 had no significant effect on the differentiation of hair cell-like cells. However, the simultaneous inhibition of both DLL-1 and JAG-2 increased the number of hair cell-like cells and decreased the number of supporting cells. JAG-2 and DLL-1 may have a synergistic role in in vitro hair cell differentiation. Full article
Show Figures

Graphical abstract

21 pages, 2589 KiB  
Article
Cross-Platform Evaluation of Commercially Targeted and Untargeted Metabolomics Approaches to Optimize the Investigation of Psychiatric Disease
by Lauren E. Chaby, Heather C. Lasseter, Kévin Contrepois, Reza M. Salek, Christoph W. Turck, Andrew Thompson, Timothy Vaughan, Magali Haas and Andreas Jeromin
Metabolites 2021, 11(9), 609; https://doi.org/10.3390/metabo11090609 - 08 Sep 2021
Cited by 5 | Viewed by 3425 | Correction
Abstract
Metabolomics methods often encounter trade-offs between quantification accuracy and coverage, with truly comprehensive coverage only attainable through a multitude of complementary assays. Due to the lack of standardization and the variety of metabolomics assays, it is difficult to integrate datasets across studies or [...] Read more.
Metabolomics methods often encounter trade-offs between quantification accuracy and coverage, with truly comprehensive coverage only attainable through a multitude of complementary assays. Due to the lack of standardization and the variety of metabolomics assays, it is difficult to integrate datasets across studies or assays. To inform metabolomics platform selection, with a focus on posttraumatic stress disorder (PTSD), we review platform use and sample sizes in psychiatric metabolomics studies and then evaluate five prominent metabolomics platforms for coverage and performance, including intra-/inter-assay precision, accuracy, and linearity. We found performance was variable between metabolite classes, but comparable across targeted and untargeted approaches. Within all platforms, precision and accuracy were highly variable across classes, ranging from 0.9–63.2% (coefficient of variation) and 0.6–99.1% for accuracy to reference plasma. Several classes had high inter-assay variance, potentially impeding dissociation of a biological signal, including glycerophospholipids, organooxygen compounds, and fatty acids. Coverage was platform-specific and ranged from 16–70% of PTSD-associated metabolites. Non-overlapping coverage is challenging; however, benefits of applying multiple metabolomics technologies must be weighed against cost, biospecimen availability, platform-specific normative levels, and challenges in merging datasets. Our findings and open-access cross-platform dataset can inform platform selection and dataset integration based on platform-specific coverage breadth/overlap and metabolite-specific performance. Full article
Show Figures

Figure 1

28 pages, 3076 KiB  
Article
Exploration of Blood Lipoprotein and Lipid Fraction Profiles in Healthy Subjects through Integrated Univariate, Multivariate, and Network Analysis Reveals Association of Lipase Activity and Cholesterol Esterification with Sex and Age
by Yasmijn Balder, Alessia Vignoli, Leonardo Tenori, Claudio Luchinat and Edoardo Saccenti
Metabolites 2021, 11(5), 326; https://doi.org/10.3390/metabo11050326 - 18 May 2021
Cited by 4 | Viewed by 4117
Abstract
In this study, we investigated blood lipoprotein and lipid fraction profiles, quantified using nuclear magnetic resonance, in a cohort of 844 healthy blood donors, integrating standard univariate and multivariate analysis with predictive modeling and network analysis. We observed a strong association of lipoprotein [...] Read more.
In this study, we investigated blood lipoprotein and lipid fraction profiles, quantified using nuclear magnetic resonance, in a cohort of 844 healthy blood donors, integrating standard univariate and multivariate analysis with predictive modeling and network analysis. We observed a strong association of lipoprotein and lipid main fraction profiles with sex and age. Our results suggest an age-dependent remodulation of lipase lipoprotein activity in men and a change in the mechanisms controlling the ratio between esterified and non-esterified cholesterol in both men and women. Full article
Show Figures

Figure 1

Back to TopTop