Current approaches and challenges for the metabolite profiling of complex natural extracts

Untargeted metabolomics analyses to identify a new sweet compound released during post-fermentation maceration of wine

The sensory quality of a wine is mainly based on its aroma and flavor. Sweetness contributes in the gustatory balance of red wines. The investigation of compounds involved in this flavor was based on empirical observations, such as the increase in wine sweetness during yeast autolysis, concomitant to post-fermentation maceration in red winemaking. An untargeted metabolomics approach using UHPLC-HRMS has been developed to discover a new sweet molecule released during this stage. Among several markers highlighted, one compound was selected to be isolated by various separative techniques. It was unambiguously identified by NMR as N6-succinyladenosine and is reported for the first time in wine at an average concentration of 3.16 mg/L in 85 red wines. Furthermore, sensory analysis has highlighted its sweetness. In addition to discovering a new sweet compound in wine, this study proposes new tools for studying taste-active compounds in natural matrices.

Jatropha Diterpenes: An Updated Review Concerning Their Structural Diversity, Therapeutic Performance, and Future Pharmaceutical Applications

The Euphorbiaceae family is a rich source of bioactive terpenoids. Among its genera, Jatropha is a conspicuous producer of diterpenes and includes approximately 175 species, many of which have medicinal uses. To date, 140 diterpenes from Jatropha (JTDs) have been reported. Given their structural diversity and notable biological activities, this work aims to highlight the pharmaceutical potential of JTDs. To achieve this goal, an extensive literature review was conducted, encompassing studies on structural elucidation through NMR and pharmacological assays, both in vitro and in vivo. Based on 132 selected papers, a thorough discussion is presented on the biosynthesis, extraction, isolation, and structural characterization of JTDs, including a compilation of their 13C NMR chemical shifts. The review also covers their synthetic production and biological effects. Additionally, an in silico analysis predicting the drug-likeness of 141 JTDs was carried out. Notably, the occurrence of macrocyclic diterpenes has doubled in the past decade, and the summary of their NMR data provides a useful resource for future research. Furthermore, 21 distinct pharmacological activities were identified, with potent cytotoxic effects targeting new molecular pathways being particularly significant. Recent advances highlight the contributions of modern approaches in organic synthesis and the pharmacological evaluation of natural products. The drug-likeness analysis identified JTD classes and compounds with favorable physicochemical and ADMET features for pharmaceutical development. In light of these findings, the use of nanotechnology is proposed as a future direction for continued research on JTDs, a fascinating class of natural compounds. This work opens up new avenues for the study of Euphorbiaceae species, particularly the Jatropha genus and its bioactive compounds.

Recent advances in natural products and derivatives with antiviral activity against respiratory syncytial virus (RSV)

Respiratory syncytial virus (RSV) is a widespread viral infection that causes millions of high-risk illnesses annually. Medicinal herbs such as ginseng root, echinacea purpurea, and radix astragali have a positive effect on antiviral activity by preventing viral adhesion, syncytial development, inhibiting viral internalization, relieving respiratory inflammation, strengthening the immune system, and stimulating the release of interferons. The potential benefits of natural products in terms of lower costs, better patient outcomes, and fewer adverse effects are discussed. This review examines the current evidence on the prevention and control of RSV with natural ingredients and the challenges and opportunities in clinical practice.

Exploring the molecular mechanism of Toddalia asiatica (L.) lam on the treatment of thrombosis based on zebrafish models, network pharmacology and experimental verification

Toddalia asiatica (L.) Lam. (TA) is a traditional folk medicine of ethnic minorities in the southwest of China. It is widely used in the treatment of dispersing blood stasis and activating blood. However, the effective substance and pharmacological mechanism have not been fully elucidated. The zebrafish larvae were treated with Phenylhydrazine (PHZ) to establish a thrombus model, and the staining intensity of zebrafish red blood cells was analyzed. The antithrombotic activity of TA was verified for the first time, and it was found that the inhibition rate of TA on thrombosis was up to 60.85 %. The chemical ingredients of TA were collected by combining UPLC-HRMS analysis and the literature research. Network pharmacology revealed that six key targets were obtained, which including TNF, AKT1, EGFR, PTGS2, PPARG, and IFNG. It showed that the PI3K-Akt pathway was a core signaling pathway. Coagulation factor III(TF), playing an important role in the process of hemostasis and thrombosis, which ranks high in the PPI network. Moreover, the results of molecular docking showed that the active components had a strong binding force with TF, which indicated that TF might be the key target of TA in treating thrombosis. In vitro experiments showed that TA could inhibit TNF-α-induced high expression of TF in EA.hy926 cells. In addition, TA could inhibit TNF-α-activated expression of Akt, IκBα and P65 protein phosphorylation in PI3K-Akt pathway. The results showed that TA had antithrombotic activity and exerted an antithrombotic effect by inhibiting the expression of TF through the PI3K-Akt-NF-κB signaling pathway.

Production of marine-derived bioactive peptide molecules for industrial applications: A reverse engineering approach

This review examines a wide range of marine microbial-derived bioactive peptide molecules, emphasizing the significance of reverse engineering in their production. The discussion encompasses the advancements in Marine Natural Products (MNPs) bio-manufacturing through the integration of omics-driven microbial engineering and bioinformatics. The distinctive features of non-ribosomally synthesised peptides (NRPs), and ribosomally synthesised precursor peptides (RiPP) biosynthesis is elucidated and presented. Additionally, the article delves into the origins of common peptide modifications. It highlights various genome mining approaches for the targeted identification of Biosynthetic Gene Clusters (BGCs) and novel RiPP and NRPs-derived peptides. The review aims to demonstrate the advancements, prospects, and obstacles in engineering both RiPP and NRP biosynthetic pathways.

FragHub: A Mass Spectral Library Data Integration Workflow

Open mass spectral libraries (OMSLs) are critical for metabolite annotation and machine learning, especially given the rising volume of untargeted metabolomic studies and the development of annotation pipelines. Despite their importance, the practical application of OMSLs is hampered by the lack of standardized file formats, metadata fields, and supporting ontology. Current libraries, often restricted to specific topics or matrices, such as natural products, lipids, or the human metabolome, may limit the discovery potential of untargeted studies. The goal of FragHub is to provide users with the capability to integrate various OMSLs into a single unified format, thereby enhancing the annotation accuracy and reliability. FragHub addresses these challenges by integrating multiple OMSLs into a single comprehensive database, supporting various data formats, and harmonizing metadata. It also proposes some generic filters for the mass spectrum using a graphical user interface. Additionally, a workflow to generate in-house libraries compatible with FragHub is proposed. FragHub dynamically segregates libraries based on ionization modes and chromatography techniques, thereby enhancing data utility in metabolomic research. The FragHub Python code is publicly available under a MIT license, at the following repository: https://github.com/eMetaboHUB/FragHub. Generated data can be accessed at 10.5281/zenodo.11057687.

Analytical insights for ensuring authenticity of Greek agriculture products: Unveiling chemical marker applications

Food authentication, including the differentiation of geographical or botanical origin, the method of production i.e. organic vs. conventional farming as well as the detection of food fraud/adulteration, has been a rapidly growing field over the past two decades due to increasing public awareness regarding food quality and safety, nutrition, and health. Concerned parties include consumers, producers, and legislators. Thus, the development of rapid, accurate, sensitive, and reproducible analytical methods to guarantee the authenticity of foods is of primary interest to scientists and technologists. The aim of the present article is to summarize research work carried out on the authentication of Greek agricultural products using spectroscopic (NIR, FTIR, UV-Vis, Raman and fluorescence spectroscopy, NMR, IRMS, ICP-OES, ICP-MS) and chromatographic (GC, GC/MS, HPLC, HPLC/MS, etc.) methods of analysis in combination with chemometrics highlighting the chemical markers that enable product authentication. The review identified a large number of chemical markers including volatiles, phenolic substances, natural pigments, elements, isotopes, etc. which can be used for (i) the differentiation of botanical/geographical origin; conventional from organic farming; production procedure and vintage year, etc. and (ii) detection of adulteration of high quality plant and animal origin foods with lower value substitutes. Finally, the constant development of reliable analytical techniques in combination with law enforcement authorities will ensure authentic foods in terms of quality and safety for consumers.

Omics approaches open new horizons in major depressive disorder: from biomarkers to precision medicine

Major depressive disorder (MDD) is a recurrent episodic mood disorder that represents the third leading cause of disability worldwide. In MDD, several factors can simultaneously contribute to its development, which complicates its diagnosis. According to practical guidelines, antidepressants are the first-line treatment for moderate to severe major depressive episodes. Traditional treatment strategies often follow a one-size-fits-all approach, resulting in suboptimal outcomes for many patients who fail to experience a response or recovery and develop the so-called "therapy-resistant depression". The high biological and clinical inter-variability within patients and the lack of robust biomarkers hinder the finding of specific therapeutic targets, contributing to the high treatment failure rates. In this frame, precision medicine, a paradigm that tailors medical interventions to individual characteristics, would help allocate the most adequate and effective treatment for each patient while minimizing its side effects. In particular, multi-omic studies may unveil the intricate interplays between genetic predispositions and exposure to environmental factors through the study of epigenomics, transcriptomics, proteomics, metabolomics, gut microbiomics, and immunomics. The integration of the flow of multi-omic information into molecular pathways may produce better outcomes than the current psychopharmacological approach, which targets singular molecular factors mainly related to the monoamine systems, disregarding the complex network of our organism. The concept of system biomedicine involves the integration and analysis of enormous datasets generated with different technologies, creating a "patient fingerprint", which defines the underlying biological mechanisms of every patient. This review, centered on precision medicine, explores the integration of multi-omic approaches as clinical tools for prediction in MDD at a single-patient level. It investigates how combining the existing technologies used for diagnostic, stratification, prognostic, and treatment-response biomarkers discovery with artificial intelligence can improve the assessment and treatment of MDD.

Integrated network pharmacology and pharmacological investigations to explore the potential mechanism of Ding-Chuan-Tang against chronic obstructive pulmonary disease

ETHNOPHARMACOLOGICAL RELEVANCE

Ding-Chuan-Tang (Abbreviated as DCT) is frequently prescribed for treatment of respiratory diseases, including chronic obstructive pulmonary disease (COPD), which is characterized by coughing, wheezing, and chest tightness in traditional Chinese medicine (TCM). However, the potential mechanism of DCT has not been investigated.

AIM OF STUDY

The aim of the study is to explore the efficiency of DCT in the treatment of COPD in vivo and in vitro, and to illustrate the possible mechanism against COPD.

METHODS

COPD model was induced by exposure of mice to cigarette smoke (CS) for 16 weeks. Enzyme-linked immunosorbent assay (ELISA), immunofluorescence assay, Western blot, etc., were used to explore the efficiency and mechanisms of DCT. Network pharmacology analysis, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, etc., was performed to explore the potential targets in the treatment of DCT on COPD.

RESULTS

DCT significantly alleviated pulmonary pathological changes in mouse COPD model, and inhibited inflammatory response induced by CS and LPS in vivo and in vitro. Network pharmacology analysis suggested that DCT alleviated COPD via inhibiting inflammation by regulating PI3K-AKT pathway. In cell-based models, DCT suppressed the phosphorylation of PI3K and AKT, which further regulated its downstream targets Nrf2 and NF-κB, and inhibited inflammatory response.

CONCLUSIONS

DCT effectively attenuated COPD in the mouse model induced by CS. The therapeutic mechanism of DCT against COPD was closely associated with the regulation of PI3K-AKT pathway and its downstream transcription factors, Nrf2 and NF-κB.

Soil metabolomics: Deciphering underground metabolic webs in terrestrial ecosystems

Soil metabolomics is an emerging approach for profiling diverse small molecule metabolites, i.e., metabolomes, in the soil. Soil metabolites, including fatty acids, amino acids, lipids, organic acids, sugars, and volatile organic compounds, often contain essential nutrients such as nitrogen, phosphorus, and sulfur and are directly linked to soil biogeochemical cycles driven by soil microorganisms. This paper presents an overview of methods for analyzing soil metabolites and the state-of-the-art of soil metabolomics in relation to soil nutrient cycling. We describe important applications of metabolomics in studying soil carbon cycling and sequestration, and the response of soil organic pools to changing environmental conditions. This includes using metabolomics to provide new insights into the close relationships between soil microbiome and metabolome, as well as responses of soil metabolome to plant and environmental stresses such as soil contamination. We also highlight the advantage of using soil metabolomics to study the biogeochemical cycles of elements and suggest that future research needs to better understand factors driving soil function and health.

Comparative metabolite analysis of Piper sarmentosum organs approached by LC-MS-based metabolic profiling

Piper sarmentosum Roxb. (Piperaceae) is a traditional medicinal and food plant widely distributed in the tropical and subtropical regions of Asia, offering both health and culinary benefits. In this study the secondary metabolites in different organs of P. sarmentosum were identified and their relative abundances were characterized. The metabolic profiles of leaves, roots, stems and fruits were comprehensively investigated by liquid chromatography high-resolution mass spectrometry (LC-HR-MS) and the data subsequently analyzed using multivariate statistical methods. Manual interpretation of the tandem mass spectrometric (MS/MS) fragmentation patterns revealed the presence of 154 tentatively identified metabolites, mostly represented by alkaloids and flavonoids. Principle component analysis and hierarchical clustering indicated the predominant occurrence of flavonoids, lignans and phenyl propanoids in leaves, aporphines in stems, piperamides in fruits and lignan-amides in roots. Overall, this study provides extensive data on the metabolite composition of P. sarmentosum, supplying useful information for bioactive compounds discovery and patterns of their preferential biosynthesis or storage in specific organs. This can be used to optimize production and harvesting as well as to maximize the plant's economic value as herbal medicine or in food applications.

Influence of Cold Stress on Physiological and Phytochemical Characteristics and Secondary Metabolite Accumulation in Microclones of Juglans regia L

The current study investigated the impact of cold stress on the morphological, physiological, and phytochemical properties of Juglans regia L. (J. regia) using in vitro microclone cultures. The study revealed significant stress-induced changes in the production of secondary antioxidant metabolites. According to gas chromatography-mass spectrometry (GC-MS) analyses, the stress conditions profoundly altered the metabolism of J. regia microclones. Although the overall spectrum of metabolites was reduced, the production of key secondary antioxidant metabolites significantly increased. Notably, there was a sevenfold (7×) increase in juglone concentration. These findings are crucial for advancing walnut metabolomics and enhancing our understanding of plant responses to abiotic stress factors. Additionally, study results aid in identifying the role of individual metabolites in these processes, which is essential for developing strategies to improve plant resilience and tolerance to adverse conditions.

Emerging strategies and therapeutic innovations for combating drug resistance in Staphylococcus aureus strains: A comprehensive review

In recent years, antibiotic therapy has encountered significant challenges due to the rapid emergence of multidrug resistance among bacteria responsible for life-threatening illnesses, creating uncertainty about the future management of infectious diseases. The escalation of antimicrobial resistance in the post-COVID era compared to the pre-COVID era has raised global concern. The prevalence of nosocomial-related infections, especially outbreaks of drug-resistant strains of Staphylococcus aureus, have been reported worldwide, with India being a notable hotspot for such occurrences. Various virulence factors and mutations characterize nosocomial infections involving S. aureus. The lack of proper alternative treatments leading to increased drug resistance emphasizes the need to investigate and examine recent research to combat future pandemics. In the current genomics era, the application of advanced technologies such as next-generation sequencing (NGS), machine learning (ML), and quantum computing (QC) for genomic analysis and resistance prediction has significantly increased the pace of diagnosing drug-resistant pathogens and insights into genetic intricacies. Despite prompt diagnosis, the elimination of drug-resistant infections remains unattainable in the absence of effective alternative therapies. Researchers are exploring various alternative therapeutic approaches, including phage therapy, antimicrobial peptides, photodynamic therapy, vaccines, host-directed therapies, and more. The proposed review mainly focuses on the resistance journey of S. aureus over the past decade, detailing its resistance mechanisms, prevalence in the subcontinent, innovations in rapid diagnosis of the drug-resistant strains, including the applicants of NGS and ML application along with QC, it helps to design alternative novel therapeutics approaches against S. aureus infection.

Screening of leaf extraction and storage conditions for eco-metabolomics studies

Mass spectrometry-based plant metabolomics is frequently used to identify novel natural products or study the effect of specific treatments on a plant's metabolism. Reliable sample handling is required to avoid artifacts, which is why most protocols mandate shock freezing of plant tissue in liquid nitrogen and an uninterrupted cooling chain. However, the logistical challenges of this approach make it infeasible for many ecological studies. Especially for research in the tropics, permanent cooling poses a challenge, which is why many of those studies use dried leaf tissue instead. We screened a total of 10 extraction and storage approaches for plant metabolites extracted from maize leaf tissue across two cropping seasons to develop a methodology for agroecological studies in logistically challenging tropical locations. All methods were evaluated based on changes in the metabolite profile across a 2-month storage period at different temperatures with the goal of reproducing the metabolite profile of the living plant as closely as possible. We show that our newly developed on-site liquid-liquid extraction protocol provides a good compromise between sample replicability, extraction efficiency, material logistics, and metabolite profile stability. We further discuss alternative methods which showed promising results and feasibility of on-site sample handling for field studies.

Bisdechlorogeodin from antarctic Pseudogymnoascus sp. LAMAI 2784 for citrus canker control

AIMS

Citrus canker caused by Xanthomonas citri subsp. citri (X. citri) is a disease of economic importance. Control of this disease includes the use of metallic copper, which is harmful to the environment and human health. Previous studies showed that the crude extract from the fungus Pseudogymnoascus sp. LAMAI 2784 isolated from Antarctic soil had in vitro antibacterial action against X. citri. The aim of the present study was to expand the applications of this extract.

METHODS AND RESULTS

In greenhouse assays, the crude extract was able to reduce bacterial infection on citrus leaves from 1.55 lesions/cm2 (untreated plants) to 0.04 lesions/cm2. Bisdechlorogeodin was identified as the main compound of the bioactive fraction produced by Pseudogymnoascus sp. LAMAI 2784, which inhibited bacterial growth in vitro (IC90 ≈ 156 µg ml-1) and permeated 80% of X. citri cells, indicating that the membrane is the primary target.

CONCLUSION

The present results showed that the bioactive fraction of the extract is mainly composed of the compound bisdechlorogeodin, which is likely responsible for the biological activity against X. citri, and the main mechanism of action is the targeting of the cell membrane. This study indicates that bisdechlorogeodin has valuable potential for the control of X. citri.

Metabolomic study of the estrogenic and anti-osteoporotic potential of Erythrina bidwillii leaf

Erythrina bidwillii Lindl., Leguminosae, constitutes a valuable crop for horticulture and medicine; however, it is rarely investigated. Menopause is a crucial transitional period in women's health. Women worldwide consider the use of phytoestrogens as a safe hormone replacement therapy to alleviate detrimental menopausal symptoms. Thus, the discovery of novel phytoestrogens is highly demanded. The present study aimed to investigate, for the first time, the metabolomic profile and the estrogenic potential of E. bidwillii Lindl. leaf. Ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry and gas chromatography-mass spectrometry metabolite profiling revealed the prevalence of alkaloids, flavonoids, isoflavonoids and fatty acids. Additionally, five erythrinan alkaloids, cristanine A (1), 8-oxoerythraline (2), (+)-erythrinine (3), (+)-erythraline (4) and 8-oxoerythrinine (5), along with the isoflavonoid genistin (6), were isolated. Erythrina bidwillii leaf extract exhibited significant in vivo estrogenic, anti-osteoporotic, anti-hyperlipidemic, hepatoprotective, and nephroprotective activities, utilizing ovariectomized rat model. Moreover, ethyl acetate and hexane fractions possessed significant in vitro estrogeic potential on MCF-7 cell lines. An in silico study of the isolated metabolites revealed that (+)-erythrinine (3) and 8-oxoerythrinine (5) exhibited the highest affinity for ERα and ERβ, respectively, modeling them as potential estrogenic lead metabolites. Therefore, E. bidwillii leaf could be employed as promising hormone replacement therapy for postmenopausal women after thorough clinical trials.

Proteomics and Its Current Application in Biomedical Area: Concise Review

Biomedical researchers tirelessly seek cutting-edge technologies to advance disease diagnosis, drug discovery, and therapeutic interventions, all aimed at enhancing human and animal well-being. Within this realm, proteomics stands out as a pivotal technology, focusing on extensive studies of protein composition, structure, function, and interactions. Proteomics, with its subdivisions of expression, structural, and functional proteomics, plays a crucial role in unraveling the complexities of biological systems. Various sophisticated techniques are employed in proteomics, including polyacrylamide gel electrophoresis, mass spectrometry analysis, NMR spectroscopy, protein microarray, X-ray crystallography, and Edman sequencing. These methods collectively contribute to the comprehensive understanding of proteins and their roles in health and disease. In the biomedical field, proteomics finds widespread application in cancer research and diagnosis, stem cell studies, and the diagnosis and research of both infectious and noninfectious diseases. In addition, it plays a pivotal role in drug discovery and the emerging frontier of personalized medicine. The versatility of proteomics allows researchers to delve into the intricacies of molecular mechanisms, paving the way for innovative therapeutic approaches. As infectious and noninfectious diseases continue to emerge and the field of biomedical research expands, the significance of proteomics becomes increasingly evident. Keeping abreast of the latest developments in proteomics applications becomes paramount for the development of therapeutics, translational research, and study of diverse diseases. This review aims to provide a comprehensive overview of proteomics, offering a concise outline of its current applications in the biomedical domain. By doing so, it seeks to contribute to the understanding and advancement of proteomics, emphasizing its pivotal role in shaping the future of biomedical research and therapeutic interventions.

Identification of potential anti-inflammatory components in Moutan Cortex by bio-affinity ultrafiltration coupled with ultra-performance liquid chromatography mass spectrometry

Moutan Cortex (MC) has been used in treating inflammation-associated diseases and conditions in China and other Southeast Asian countries. However, the active components of its anti-inflammatory effect are still unclear. The study aimed to screen and identify potential cyclooxygenase-2 (COX-2) inhibitors in MC extract. The effect of MC on COX-2 was determined in vitro by COX-2 inhibitory assays, followed by bio-affinity ultrafiltration in combination with ultra-performance liquid chromatography-mass spectrometry (BAUF-UPLC-MS). To verify the reliability of the constructed approach, celecoxib was applied as the positive control, in contrast to adenosine which served as the negative control in this study. The bioactivity of the MC components was validated in vitro by COX-2 inhibitor assay and RAW264.7 cells. Their in vivo anti-inflammatory activity was also evaluated using LPS-induced zebrafish inflammation models. Finally, molecular docking was hired to further explore the internal interactions between the components and COX-2 residues. The MC extract showed an evident COX-2-inhibitory effect in a concentration-dependent manner. A total of 11 potential COX-2 inhibitors were eventually identified in MC extract. The COX-2 inhibitory activity of five components, namely, gallic acid (GA), methyl gallate (MG), galloylpaeoniflorin (GP), 1,2,3,6-Tetra-O-galloyl-β-D-glucose (TGG), and 1,2,3,4,6-Penta-O-galloyl-β-D-glucopyranose (PGG), were validated through both in vitro assays and experiments using zebrafish models. Besides, the molecular docking analysis revealed that the potential inhibitors in MC could effectively inhibit COX-2 by interacting with specific residues, similar to the mechanism of action exhibited by celecoxib. In conclusion, BAUF-UPLC-MS combining the molecular docking is an efficient approach to discover enzyme inhibitors from traditional herbs and understand the mechanism of action.

Natural Products Dereplication: Databases and Analytical Methods

The development of efficient methods for dereplication has been critical in the re-emergence of the research in natural products as a source of drug leads. Current dereplication workflows rapidly identify already known bioactive secondary metabolites in the early stages of any drug discovery screening campaign based on natural extracts or enriched fractions. Two main factors have driven the evolution of natural products dereplication over the last decades. First, the availability of both commercial and public large databases of natural products containing the key annotations against which the biological and chemical data derived from the studied sample are searched for. Second, the considerable improvement achieved in analytical technologies (including instrumentation and software tools) employed to obtain robust and precise chemical information (particularly spectroscopic signatures) on the compounds present in the bioactive natural product samples. This chapter describes the main methods of dereplication, which rely on the combined use of large natural product databases and spectral libraries, alongside the information obtained from chromatographic, UV-Vis, MS, and NMR spectroscopic analyses of the samples of interest.

Metabolomics of natural samples: A tutorial review on the latest technologies

Metabolomics is the study of metabolites present in a living system. It is a rapidly growing field aimed at discovering novel compounds, studying biological processes, diagnosing diseases, and ensuring the quality of food products. Recently, the analysis of natural samples has become important to explore novel bioactive compounds and to study how environment and genetics affect living systems. Various metabolomics techniques, databases, and data analysis tools are available for natural sample metabolomics. However, choosing the right method can be a daunting exercise because natural samples are heterogeneous and require untargeted approaches. This tutorial review aims to compile the latest technologies to guide an early-career scientist on natural sample metabolomics. First, different extraction methods and their pros and cons are reviewed. Second, currently available metabolomics databases and data analysis tools are summarized. Next, recent research on metabolomics of milk, honey, and microbial samples is reviewed. Finally, after reviewing the latest trends in technologies, a checklist is presented to guide an early-career researcher on how to design a metabolomics project. In conclusion, this review is a comprehensive resource for a researcher planning to conduct their first metabolomics analysis. It is also useful for experienced researchers to update themselves on the latest trends in metabolomics.

High-speed countercurrent chromatography with offline detection by electrospray mass spectrometry and nuclear magnetic resonance detection as a tool to resolve complex mixtures: A practical approach using Coffea arabica leaf extract

INTRODUCTION

Many secondary metabolites isolated from plants have been described in the literature owing to their important biological properties and possible pharmacological applications. However, the identification of compounds present in complex plant extracts has remained a great scientific challenge, is often laborious, and requires a long research time with high financial cost.

OBJECTIVES

The aim of this study was to develop a method that allows the identification of secondary metabolites in plant extracts with a high degree of confidence in a short period of time.

MATERIAL AND METHODS

In this study, an ethanolic extract of Coffea arabica leaves was used to validate the proposed method. Countercurrent chromatography was chosen as the initial step for extraction fractionation using gradient elution. Resulting fractions presented a variation of compounds concentrations, allowing for statistical total correlation spectroscopy (STOCSY) calculations between liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) and NMR across fractions.

RESULTS

The proposed method allowed the identification of 57 compounds. Of the annotated compounds, 20 were previously described in the literature for the species and 37 were reported for the first time. Among the inedited compounds, we identified flavonoids, alkaloids, phenolic acids, coumarins, and terpenes.

CONCLUSION

The proposed method presents itself as a valid alternative for the study of complex extracts in an effective, fast, and reliable way that can be reproduced in the study of other extracts.

Therapeutic potential of natural antisense transcripts and various mechanisms involved for clinical applications and disease prevention

Antisense transcription, a prevalent occurrence in mammalian genomes, gives rise to natural antisense transcripts (NATs) as RNA molecules. These NATs serve as agents of diverse transcriptional and post-transcriptional regulatory mechanisms, playing crucial roles in various biological processes vital for cell function and immune response. However, when their normal functions are disrupted, they can contribute to human diseases. This comprehensive review aims to establish the molecular foundation linking NATs to the development of disorders like cancer, neurodegenerative conditions, and cardiovascular ailments. Additionally, we evaluate the potential of oligonucleotide-based therapies targeting NATs, presenting both their advantages and limitations, while also highlighting the latest advancements in this promising realm of clinical investigation.Abbreviations: NATs- Natural antisense transcripts, PRC1- Polycomb Repressive Complex 1, PRC2- Polycomb Repressive Complex 2, ADARs- Adenosine deaminases acting on RNA, BDNF-AS- Brain-derived neurotrophic factor antisense transcript, ASOs- Antisense oligonucleotides, SINEUPs- Inverted SINEB2 sequence-mediated upregulating molecules, PTBP1- Polypyrimidine tract binding protein-1, HNRNPK- heterogeneous nuclear ribonucleoprotein K, MAPT-AS1- microtubule-associated protein tau antisense 1, KCNQ1OT- (KCNQ1 opposite strand/antisense transcript 1, ERK- extracellular signal-regulated kinase 1, USP14- ubiquitin-specific protease 14, EGF- Epidermal growth factor, LSD1- Lysine Specific Demethylase 1, ANRIL- Antisense Noncoding RNA in the INK4 Locus, BWS- Beckwith-Wiedemann syndrome, VEGFA- Vascular Endothelial Growth component A.

Unraveling Compositional Study, Chemometric Analysis, and Cell-Based Antioxidant Potential of Selective High Nutraceutical Value Amaranth Cultivars Using a GC-MS and NMR-Based Metabolomics Approach

Amaranthus (family Amaranthaceae) is a potentially nutritious pseudocereal also known as a functional food owing to its high nutritional quality grains especially rich in essential amino acids. Emerging study, however, unambiguously indicates that apart from essential nutrients like protein, other phytochemicals present in amaranth seeds provide excellent health benefits. Squalene is one such phytonutrient found in Amaranthus seeds, which is also its largest vegetal source. In this research work, GC-MS and NMR spectroscopy-based metabolomics have been utilized for the compositional analysis of Amaranthus seeds coupled with a multivariate data set. Investigation of nonpolar and polar seed extracts of six different cultivars of amaranth identified 47 primary and secondary metabolites. One-way ANOVA showed significant quantitative metabolic variations in different cultivars of amaranth. Multivariate principal component analysis of both the GC-MS and NMR analyzed data broadly classified in two groups showed significant variations in the polar (lysine, arginine, GABA, and myoinositol) and nonpolar (squalene, tryptophan, and alkylated phenols, which are potential nutraceutical agents) metabolites. The squalene content estimated using HPLC varied significantly (1.61 to 4.72 mg g-1 seed dry weight) among six different cultivars. Positive correlations were found among the cellular antioxidant activity and squalene content. Cultivar AM-3 having the maximum squalene content showed the highest antioxidant activity evaluated on the cellular level over human embryonic kidney cells, clearly revealing potent intercellular reactive oxygen species scavenging capacity and strong membrane lipid peroxidation inhibition potential. Oxidative stress markers such as MDA, SOD, GSH, and CAT levels in cells further corroborated the research work. The study also indicated high concentrations of lysine (80.49 mg g-1 dry seeds) in AM-2, squalene (0.47% by weight) in AM-3, and 2,4-di-tert-butyl phenol (18.64% peak area) and myoinositol (79.07 mg g-1 dry seeds) in AM-5. This novel comparative metabolomic study successfully profiles the nutrient composition of amaranth cultivars and provides the opportunity for the development of nutraceuticals and natural antioxidants from this functional food.

Automated silylation of flavonoids using 3D printed microfluidics prior to chromatographic analysis: system development

Flavonoids are a class of secondary plant metabolites with low molecular weights. Most flavonoids are highly polar and unsuitable for gas chromatographic analyses. Derivatization is commonly used to make them amenable to gas chromatography by altering their physicochemical properties. Although highly effective, derivatization techniques introduce extra preparation steps and often use hazardous chemicals. The aim of this study was to automate derivatization (specifically, silylation) by developing 3D printed microfluidic devices in which derivatization of flavonoids can occur. A microfluidic device was designed and 3D printed using clear polypropylene. Quercetin and other flavonoids (TED 13 and ZTF 1016) isolated from plant extracts were silylated with N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide (MTBSTFA) at room temperature both in batch and in continuous flow. All the samples were analyzed using Fourier transform infrared (FTIR) spectroscopy, gas chromatography combined with mass spectrometry (GC-MS), and high-resolution accurate mass spectrometry (HR-MS). Interestingly, the HR-MS results showed that the flow method was about 25 times more efficient than the batch method for quercetin samples. The TED 13 flavonoid was completely derivatized in the flow method compared to the batch method where the reaction was incomplete. Similar results were observed for ZTF 1016, where the flow method resulted in a four times derivatized compound, while the compound was only derivatized once in batch. In conclusion, 3D printed microfluidic devices have been developed and used to demonstrate a semi-automated, inexpensive, and more efficient natural product derivatization method based on continuous flow chemistry as an alternative to the traditional batch method.

Bioassay-Guided Assessment of Antioxidative, Anti-Inflammatory and Antimicrobial Activities of Extracts from Medicinal Plants via High-Performance Thin-Layer Chromatography

Natural products and their analogues have contributed significantly to treatment options, especially for anti-inflammatory and infectious diseases. Thus, the primary objective of this work was to compare the bioactivity profiles of selected medicinal plants that are historically used in folk medicine to treat inflammation and infections in the body. Chemical HPTLC fingerprinting was used to assess antioxidant, phenolic and flavonoid content, while bioassay-guided HPTLC was used to detect compounds with the highest antibacterial and anti-inflammatory activities. The results of this study showed that green tea leaf, walnut leaf, St. John's wort herb, wild thyme herb, European goldenrod herb, chamomile flower, and immortelle flower extracts were strong radical scavengers. Green tea and nettle extracts were the most active extracts against E. coli, while calendula flower extract showed significant potency against S. aureus. Furthermore, green tea, greater celandine, and fumitory extracts exhibited pronounced potential in suppressing COX-1 activity. The bioactive compounds from the green tea extract, as the most bioactive, were isolated by preparative thin-layer chromatography and characterized with their FTIR spectra. Although earlier studies have related green tea's anti-inflammatory properties to the presence of catechins, particularly epigallocatechin-3-gallate, the FTIR spectrum of the compound from the most intense bioactive zone showed the strongest anti-inflammatory activity can be attributed to amino acids and heterocyclic compounds. As expected, antibacterial activity in extracts was related to fatty acids and monoglycerides.

Exploratory optimisation of a LC-HRMS based analytical method for untargeted metabolomic screening of Cannabis Sativa L. through Data Mining

BACKGROUND

Recent increase in public acceptance of cannabis as a natural medical alternative for certain neurological pathologies has led to its approval in different regions of the world. However, due to its previous illegal background, little research has been conducted around its biochemical insights. Therefore, in the current framework, metabolomics may be a suitable approach for deepening the knowledge around this plant species. Nevertheless, experimental methods in metabolomics must be carefully handled, as slight modifications can lead to metabolomic coverage loss. Hence, the main objective of this work was to optimise an analytical method for appropriate untargeted metabolomic screening of cannabis.

RESULTS

We present an empirically optimised experimental procedure through which the broadest metabolomic coverage was obtained, in which extraction solvents for metabolite isolation, chromatographic columns for LC-qOrbitrap analysis and plant-representative biological tissues were compared. By exploratory means, it was determined that the solvent combination composed of CHCl3:H2O:CH3OH (2:1:1, v/v) provided the highest number of features from diverse chemical classes, as it was a two-phase extractant. In addition, a reverse phase 2.6 μm C18 100 Å (150 × 3 mm) chromatographic column was determined as the appropriate choice for adequate separation and further detection of the diverse metabolite classes. Apart from that, overall chromatographic peak quality provided by each column was observed and the need for batch correction methods through quality control (QC) samples was confirmed. At last, leaf and flower tissues resulted to provide complementary metabolic information of the plant, to the detriment of stem tissue, which resulted to be negligible.

SIGNIFICANCE

It was concluded that the optimised experimental procedure could significantly ease the path for future research works related to cannabis metabolomics by LC-HRMS means, as the work was based on previous plant metabolomics literature. Furthermore, it is crucial to highlight that an optimal analytical method can vary depending on the main objective of the research, as changes in the experimental factors can lead to different outcomes, regardless of whether the results are better or worse.

Metabolite Profile Characterization of Cyanobacterial Strains with Bioactivity on Lipid Metabolism Using In Vivo and In Vitro Approaches

Cyanobacteria have demonstrated their therapeutic potential for many human diseases. In this work, cyanobacterial extracts were screened for lipid reducing activity in zebrafish larvae and in fatty-acid-overloaded human hepatocytes, as well as for glucose uptake in human hepatocytes and ucp1 mRNA induction in murine brown adipocytes. A total of 39 cyanobacteria strains were grown and their biomass fractionated, resulting in 117 chemical fractions. Reduction of neutral lipids in zebrafish larvae was observed for 12 fractions and in the human hepatocyte steatosis cell model for five fractions. The induction of ucp1 expression in murine brown adipocytes was observed in six fractions, resulting in a total of 23 bioactive non-toxic fractions. All extracts were analyzed by untargeted UPLC-Q-TOF-MS mass spectrometry followed by multivariate statistical analysis to prioritize bioactive strains. The metabolite profiling led to the identification of two markers with lipid reducing activity in zebrafish larvae. Putative compound identification using mass spectrometry databases identified them as phosphatidic acid and aromatic polyketides derivatives-two compound classes, which were previously associated with effects on metabolic disorders. In summary, we have identified cyanobacterial strains with promising lipid reducing activity, whose bioactive compounds needs to be identified in the future.

Mass spectrometry-based approaches to assess the botanical authenticity of dietary supplements

Dietary supplements are legally considered foods despite frequently including medicinal plants as ingredients. Currently, the consumption of herbal dietary supplements, also known as plant food supplements (PFS), is increasing worldwide and some raw botanicals, highly demanded due to their popularity, extensive use, and/or well-established pharmacological effects, have been attaining high prices in the international markets. Therefore, botanical adulteration for profit increase can occur along the whole PFS industry chain, from raw botanicals to plant extracts, until final PFS. Besides the substitution of high-value species, unintentional mislabeling can happen in morphologically similar species. Both cases represent a health risk for consumers, prompting the development of numerous works to access botanical adulterations in PFS. Among different approaches proposed for this purpose, mass spectrometry (MS)-based techniques have often been reported as the most promising, particularly when hyphenated with chromatographic techniques. Thus, this review aims at describing an overview of the developments in this field, focusing on the applications of MS-based techniques to targeted and untargeted analysis to detect botanical adulterations in plant materials, extracts, and PFS.

Rapid Chemical Profiling of Filipendula ulmaria Using CPC Fractionation, 2-D Mapping of 13C NMR Data, and High-Resolution LC-MS

Filipendula ulmaria, commonly known as meadowsweet, is a wild herbaceous flowering plant that is widely distributed in Europe. A range of salicylic acid derivatives and flavonol glycosides have been previously associated with the antirheumatic and diuretic properties of F. ulmaria. In the present work, a hydroalcoholic extract from F. ulmaria aerial parts was extensively profiled using an efficient NMR-based dereplication strategy. The approach involves the fractionation of the crude extract by centrifugal partition chromatography (CPC), 13C NMR analysis of the fractions, 2D-cluster mapping of the entire NMR dataset, and, finally, structure elucidation using a natural metabolite database, validated by 2D NMR data interpretation and liquid chromatography coupled with mass spectrometry. The chemodiversity of the aerial parts was extensive, with 28 compounds unambiguously identified, spanning various biosynthetic classes. The F. ulmaria extract and CPC fractions were screened for their potential to enhance skin epidermal barrier function and skin renewal properties using in vitro assays performed on Normal Human Epidermal Keratinocytes. Fractions containing quercetin, kaempferol glycosides, ursolic acid, pomolic acid, naringenin, β-sitosterol, and Tellimagrandins I and II were found to upregulate genes related to skin barrier function, epidermal renewal, and stress responses. This research is significant as it could provide a natural solution for improving hydration and skin renewal properties.

A comparison of high- and low-resolution gas chromatography-mass spectrometry for herbal product classification: A case study with Ocimum essential oils

INTRODUCTION

Selection of marker compounds for targeted chemical analysis is complicated when considering varying instrumentation and closely related plant species. High-resolution gas chromatography-mass spectrometry (GC-MS), via orbitrap detection, has yet to be evaluated for improved marker compound selection.

OBJECTIVE

This study directly compares high- and low-resolution GC-MS for botanical maker compound selection using Ocimum tenuiflorum L. (OT) and Ocimum gratissimum L. (OG) for botanical ingredient authentication.

METHODS

The essential oils of OT and OG were collected via hydrodistillation before untargeted chemical analysis with gas chromatography coupled to single-quadrupole (GC-SQ) and orbitrap (GC-Orbitrap) detectors. The Global Natural Products Social Molecular Networking (GNPS) software was used for compound annotation, and a manual search was used to find the 41 most common Ocimum essential oil metabolites.

RESULTS

The GC-Orbitrap resulted in 1.7-fold more metabolite detection and increased dynamic range compared to the GC-SQ. Spectral matching and manual searching were improved with GC-Orbitrap data. Each instrument had differing known compound concentrations; however, there was an overlap of six compounds with higher abundance in OG than OT and three compounds with a higher abundance in OT than OG, suggesting consistent detection of the most variable compounds. An unsupervised principal component analysis (PCA) could not discern the two species with either dataset.

CONCLUSION

GC-Orbitrap instrumentation improves compound detection, dynamic range, and feature annotation in essential oil analysis. However, considering both high- and low-resolution data may improve reliable marker compound selection, as GC-Orbitrap analysis alone did not improve unsupervised separation of two Ocimum species compared to GC-SQ data.

Expanding our coverage: Strategies to detect a greater range of metabolites

Whilst the study of metabolites can arguably be traced back several hundred years it began in earnest in the 20th century with studies based on single metabolites or simple metabolic pathways. The advent of metabolomics and in particular the adoption of high-resolution mass spectrometry now means we can faithfully annotate and quantify in excess of 1000 plant metabolites. Whilst this is an impressive leap it falls well short of the estimated number of metabolites in the plant kingdom. This, whilst considerable and important insights have been achieved using commonly utilized approaches, there is a need to improve the coverage of the metabolome. Here, we review three largely complementary strategies (i) methods based on using chemical libraries (ii) methods based on molecular networking and (iii) approaches that link metabolomics and genetic variance. It is our contention that using all three approaches in tandem represents the best approach to tackle this challenge.

Advanced Methods for Natural Products Discovery: Bioactivity Screening, Dereplication, Metabolomics Profiling, Genomic Sequencing, Databases and Informatic Tools, and Structure Elucidation

Natural Products (NP) are essential for the discovery of novel drugs and products for numerous biotechnological applications. The NP discovery process is expensive and time-consuming, having as major hurdles dereplication (early identification of known compounds) and structure elucidation, particularly the determination of the absolute configuration of metabolites with stereogenic centers. This review comprehensively focuses on recent technological and instrumental advances, highlighting the development of methods that alleviate these obstacles, paving the way for accelerating NP discovery towards biotechnological applications. Herein, we emphasize the most innovative high-throughput tools and methods for advancing bioactivity screening, NP chemical analysis, dereplication, metabolite profiling, metabolomics, genome sequencing and/or genomics approaches, databases, bioinformatics, chemoinformatics, and three-dimensional NP structure elucidation.

Detection and analysis of chiral molecules as disease biomarkers

The chirality of small metabolic molecules is important in controlling physiological processes and indicating the health status of humans. Abnormal enantiomeric ratios of chiral molecules in biofluids and tissues occur in many diseases, including cancers and kidney and brain diseases. Thus, chiral small molecules are promising biomarkers for disease diagnosis, prognosis, adverse drug-effect monitoring, pharmacodynamic studies and personalized medicine. However, it remains difficult to achieve cost-effective and reliable analysis of small chiral molecules in clinical procedures, in part owing to their large variety and low concentration. In this Review, we describe current and emerging techniques that detect and quantify small-molecule enantiomers and their biological importance.

Untargeted Metabolomics Using UHPLC-HRMS Reveals Metabolic Changes of Fresh-Cut Potato during Browning Process

Surface browning plays a major role in the quality loss of fresh-cut potatoes. Untargeted metabolomics were used to understand the metabolic changes of fresh-cut potato during the browning process. Their metabolites were profiled by ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UHPLC-HRMS). Data processing and metabolite annotation were completed by Compound Discoverer 3.3 software. Statistical analysis was applied to screen the key metabolites correlating with browning process. Fifteen key metabolites responsible for the browning process were putatively identified. Moreover, after analysis of the metabolic causes of glutamic acid, linolenic acid, glutathione, adenine, 12-OPDA and AMP, we found that the browning process of fresh-cut potatoes was related to the structural dissociation of the membrane, oxidation and reduction reaction and energy shortage. This work provides a reference for further investigation into the mechanism of browning in fresh-cut products.

LC-IMS-HRMS for identification of biomarkers in untargeted metabolomics: The effects of pterostilbene and resveratrol consumption in liver steatosis, animal model

Untargeted metabolomics with the combination of ion mobility separation coupled to high resolution mass spectrometry (IMS-HRMS) was applied to investigate the impact of resveratrol and pterostilbene supplementation on the metabolic fingerprint of the Wistar rats liver with induced liver steatosis. RP-LC and HILIC in both ionisation modes were employed to analyse the liver samples (n = 40) from Wistar rats fed with a high-fat and high-fructose diet, supplemented or not with resveratrol and pterostilbene. After univariate and multivariate statistical analysis, 34 metabolites were highlighted in the different diets and elucidated. Despite the structural similarity, different alterations in liver metabolism were observed by the supplementations. Resveratrol treatment was characterised by the alteration in metabolism of 17 lysophospholipids, while pterostilbene affected some vitamins and derivatives, among others. IMS has demonstrated great potential in the elucidation process thanks to the additional structural descriptor the CCS (Ų), providing more confidence in the identification.

Deciphering interactions between the marine dinoflagellate Prorocentrum lima and the fungus Aspergillus pseudoglaucus

The comprehension of microbial interactions is one of the key challenges in marine microbial ecology. This study focused on exploring chemical interactions between the toxic dinoflagellate Prorocentrum lima and a filamentous fungal species, Aspergillus pseudoglaucus, which has been isolated from the microalgal culture. Such interspecies interactions are expected to occur even though they were rarely studied. Here, a co-culture system was designed in a dedicated microscale marine-like condition. This system allowed to explore microalgal-fungal physical and metabolic interactions in presence and absence of the bacterial consortium. Microscopic observation showed an unusual physical contact between the fungal mycelium and dinoflagellate cells. To delineate specialized metabolome alterations during microalgal-fungal co-culture metabolomes were monitored by high-performance liquid chromatography coupled to high-resolution mass spectrometry. In-depth multivariate statistical analysis using dedicated approaches highlighted (1) the metabolic alterations associated with microalgal-fungal co-culture, and (2) the impact of associated bacteria in microalgal metabolome response to fungal interaction. Unfortunately, only a very low number of highlighted features were fully characterized. However, an up-regulation of the dinoflagellate toxins okadaic acid and dinophysistoxin 1 was observed during co-culture in supernatants. Such results highlight the importance to consider microalgal-fungal interactions in the study of parameters regulating toxin production.

Microbiome and Metabolomics in Liver Cancer: Scientific Technology

Primary liver cancer is a heterogeneous disease. Liver cancer metabolism includes both the reprogramming of intracellular metabolism to enable cancer cells to proliferate inappropriately and adapt to the tumor microenvironment and fluctuations in regular tissue metabolism. Currently, metabolomics and metabolite profiling in liver cirrhosis, liver cancer, and hepatocellular carcinoma (HCC) have been in the spotlight in terms of cancer diagnosis, monitoring, and therapy. Metabolomics is the global analysis of small molecules, chemicals, and metabolites. Metabolomics technologies can provide critical information about the liver cancer state. Here, we review how liver cirrhosis, liver cancer, and HCC therapies interact with metabolism at the cellular and systemic levels. An overview of liver metabolomics is provided, with a focus on currently available technologies and how they have been used in clinical and translational research. We also list scalable methods, including chemometrics, followed by pathway processing in liver cancer. We conclude that important drivers of metabolomics science and scientific technologies are novel therapeutic tools and liver cancer biomarker analysis.

Iphiona mucronata (Forssk.) Asch. & Schweinf. A Comprehensive Phytochemical Study via UPLC-Q-TOF-MS in the Context of the Embryo- and Cytotoxicity Profiles

Iphiona mucronata (Family Asteraceae) is widely distributed in the Eastern desert of Egypt. It is a promising plant material for phytochemical analysis and pharmacologic studies, and so far, its specific metabolites and biological activity have not yet been thoroughly investigated. Herein, we report on the detailed phytochemical study using UPLC-Q-TOF-MS approach. This analysis allowed the putative annotation of 48 metabolites belonging to various phytochemical classes, including mostly sesquiterpenes, flavonoids, and phenolic acids. Further, zebrafish embryotoxicity has been carried out, where 100 µg/mL extract incubated for 72 h resulted in a slow touch response of the 10 examined larvae, which might be taken as a sign of a disturbed peripheral nervous system. Results of in vitro testing indicate moderate cytotoxicity towards VERO, FaDu, and HeLa cells with CC50 values between 91.6 and 101.7 µg/mL. However, selective antineoplastic activity in RKO cells with CC50 of 54.5 µg/mL was observed. To the best of our knowledge, this is the first comprehensive profile of I. mucronata secondary metabolites that provides chemical-based evidence for its biological effects. A further investigation should be carried out to precisely define the underlying mechanisms of toxicity.

New insights into the Van Krevelen diagram: Automated molecular formula determination from HRMS for a large chemical profiling of lichen extracts

INTRODUCTION

In recent years, LC-MS has become the golden standard for metabolomic studies. Indeed, LC is relatively easy to couple with the soft electrospray ionization. As a consequence, many tools have been developed for the structural annotation of tandem mass spectra. However, it is sometimes difficult to do data-dependent acquisition (DDA), especially when developing new methods that stray from the classical LC-MS workflow.

OBJECTIVE

An old tool from petroleomics that has recently gained popularity in metabolomics, the Van Krevelen diagram, is adapted for an overview of the molecular diversity profile in lichens through high-resolution mass spectrometry (HRMS).

METHODS

A new method is benchmarked against the state-of-the-art classification tool ClassyFire using a database containing most known lichen metabolites (n ≈ 2,000). Four lichens known for their contrasted chemical composition were selected, and extractions with apolar, aprotic polar, and protic polar solvents were performed to cover a wide range of polarities. Extracts were analyzed with direct infusion electrospray ionization mass spectrometry (DI-ESI-MS) and atmospheric solids analysis probe mass spectrometry (ASAP-MS) techniques to be compared with the chemical composition described in the literature.

RESULTS

The most common lichen metabolites were efficiently classified, with more than 90% of the molecules in some classes being matched with ClassyFire. Results from this method are consistent with the various extraction protocols in the present case study.

CONCLUSION

This approach is a rapid and efficient tool to gain structural insight regarding lichen metabolites analyzed by HRMS without relying on DDA by LC-MS/MS analysis. It may notably be of use during the development phase of novel MS-based metabolomic approaches.

Current and future approaches for in vitro hit discovery in diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a serious public health problem. In this review, we discuss current and promising future drugs, targets, in vitro assays and emerging omics technologies in T2DM. Importantly, we open the perspective to image-based high-content screening (HCS), with the focus of combining it with metabolomics or lipidomics. HCS has become a strong technology in phenotypic screens because it allows comprehensive screening for the cell-modulatory activity of small molecules. Metabolomics and lipidomics screen for perturbations at the molecular level. The combination of these data-intensive comprehensive technologies is enabled by the rapid development of artificial intelligence. It promises a deep cellular and molecular phenotyping directly linked to chemical information about the applied drug candidates or complex mixtures.

Amplified Drought Alters Leaf Litter Metabolome, Slows Down Litter Decomposition, and Modifies Home Field (Dis)Advantage in Three Mediterranean Forests

In Mediterranean ecosystems, the projected rainfall reduction of up to 30% may alter plant-soil interactions, particularly litter decomposition and Home Field Advantage (HFA). We set up a litter transplant experiment in the three main forests encountered in the northern part of the Medi-terranean Basin (dominated by either Quercus ilex, Quercus pubescens, or Pinus halepensis) equipped with a rain exclusion device, allowing an increase in drought either throughout the year or concentrated in spring and summer. Senescent leaves and needles were collected under two precipitation treatments (natural and amplified drought plots) at their "home" forest and were left to decompose in the forest of origin and in other forests under both drought conditions. MS-based metabolomic analysis of litter extracts combined with multivariate data analysis enabled us to detect modifications in the composition of litter specialized metabolites, following amplified drought treatment. Amplified drought altered litter quality and metabolomes, directly slowed down litter decomposition, and induced a loss of home field (dis)advantage. No indirect effect mediated by a change in litter quality on decomposition was observed. These results may suggest major alterations of plant-soil interactions in Mediterranean forests under amplified drought conditions.

Allelopathic Potential of Mangroves from the Red River Estuary against the Rice Weed Echinochloa crus-galli and Variation in Their Leaf Metabolome

Mangroves are the only forests located at the sea–land interface in tropical and subtropical regions. They are key elements of tropical coastal ecosystems, providing numerous ecosystem services. Among them is the production of specialized metabolites by mangroves and their potential use in agriculture to limit weed growth in cultures. We explored the in vitro allelopathic potential of eight mangrove species’ aqueous leaf extracts (Avicennia marina, Kandelia obovata, Bruguiera gymnorhiza, Sonneratia apetala, Sonneratia caseolaris, Aegiceras corniculatum, Lumnitzera racemosa and Rhizophora stylosa) on the germination and growth of Echinochloa crus-galli, a weed species associated with rice, Oryza sativa. Leaf methanolic extracts of mangrove species were also studied via UHPLC-ESI/qToF to compare their metabolite fingerprints. Our results highlight that A. corniculatum and S. apetala negatively affected E. crus-galli development with a stimulating effect or no effect on O. sativa. Phytochemical investigations of A. corniculatum allowed us to putatively annotate three flavonoids and two saponins. For S. apetala, three flavonoids, a tannin and two unusual sulfated ellagic acid derivatives were found. Some of these compounds are described for the first time in these species. Overall, A. corniculatum and S. apetala leaves are proposed as promising natural alternatives against E. crus-galli and should be further assessed under field conditions.

UV Fingerprinting Approaches for Quality Control Analyses of Food and Functional Food Coupled to Chemometrics: A Comprehensive Analysis of Novel Trends and Applications

(1) Background: Ultraviolet-visible (UV-Vis) spectroscopy is a common analytical tool to detect chromophore in compounds by monitoring absorbance spectral wavelengths. Further, it could provide spectral information about complex conjugated systems in mixtures aided by chemometric tools to visualize large UV-Vis datasets as typical in food samples. This review provides novel insight on UV-Vis applications in the last 20 years, as an advanced analytical tool in the quality control of food and dietary supplements, as well as several other applications, including chemotaxonomy, authentication, fingerprinting, and stability studies. (2) Conclusions: A critical assessment of the value of UV application and its novel trends in the quality control (QC) of nutraceuticals reveals the advantages and limitations, focusing on areas where future advancements are in need. Although simple, UV and its novel trends present potential analytical tools with an acceptable error for QC applications from a non-targeted perspective compared to other expensive spectral tools.

Metabolomics as a Prospective Tool for Soybean (Glycine max) Crop Improvement

Global demand for soybean and its products has stimulated research into the production of novel genotypes with higher yields, greater drought and disease tolerance, and shorter growth times. Genetic research may be the most effective way to continue developing high-performing cultivars with desirable agronomic features and improved nutritional content and seed performance. Metabolomics, which predicts the metabolic marker for plant performance under stressful conditions, is rapidly gaining interest in plant breeding and has emerged as a powerful tool for driving crop improvement. The development of increasingly sensitive, automated, and high-throughput analytical technologies, paired with improved bioinformatics and other omics techniques, has paved the way for wide characterization of genetic characteristics for crop improvement. The combination of chromatography (liquid and gas-based) with mass spectrometry has also proven to be an indisputable efficient platform for metabolomic studies, notably plant metabolic fingerprinting investigations. Nevertheless, there has been significant progress in the use of nuclear magnetic resonance (NMR), capillary electrophoresis, and Fourier-transform infrared spectroscopy (FTIR), each with its own set of benefits and drawbacks. Furthermore, utilizing multivariate analysis, principal components analysis (PCA), discriminant analysis, and projection to latent structures (PLS), it is possible to identify and differentiate various groups. The researched soybean varieties may be correctly classified by using the PCA and PLS multivariate analyses. As metabolomics is an effective method for evaluating and selecting wild specimens with desirable features for the breeding of improved new cultivars, plant breeders can benefit from the identification of metabolite biomarkers and key metabolic pathways to develop new genotypes with value-added features.

Global analysis of qualitative and quantitative metabolism of Notoginsenoside R1 in rat liver-brain-gut axis based on LC-IT-TOF/MS combing mMDF strategy

BACKGROUND

The metabolism study of active components for traditional Chinese medicine (TCM) in target organs is conducive to clarify the authentic active ingredients. Notoginsenoside R1 (NG-R1), one of the bioactive components of Panax notoginsenoside (PNS), is commonly acknowledged as the characteristic marker of PNS. However, the metabolism of NG-R1 in target organs has not been clarified yet due to the lack of robust technique and approach.

PURPOSE

The present study aimed to develop a reliable and efficient strategy and technology for revealing the qualitative and quantitative metabolism of active components of TCMs in target organs, and to clarify the biotransformation of NG-R1 in liver-brain-intestinal axis.

METHODS

The metabolic transformation of NG-R1 in the brain gut axis was investigated in the in vitro incubation system of fresh rat brain, liver homogenate, and intestinal flora. To quickly lock the target metabolites, we set the mass defect filter (MDF) in different ranges to screen metabolites with different molecular weight (MW). This strategy was defined as multi-stage MDF (mMDF). In addition, we performed relative quantitative analysis on all metabolites according to the peak area acquired by LC-IT-TOF/MS to overcome the challenge that metabolites are difficult to be quantified due to the lack of standards.

RESULTS

When MDF was set at 0.50 to 0.65 to screen metabolites with MW of 900 to 1200 Da, 6 novel metabolites were quickly found, and then identified as glucuronic acid binding, oxidation, dehydrogenation, methylation and hydrogenation products according to their LC and MS characteristics. When setting MDF at 0.42 - 0.52, 6 metabolites with MW of 600 to 900 Da were effectively screened and identified as Rg1, NG-R2, Rh1, Rg1+CH₂+2H and Rg1+CH₂. To screen the metabolites with MW of 300 to 600 Da, MDF was set at 0.25 - 0.42, and 4 novel metabolites were screened rapidly. The results of quantitative metabolism suggested that intestinal flora was the main metabolic site of NG-R1 in rat, and more than 60% of NG-R1 was converted to Rg1 by deglycosylation in the intestinal flora.

CONCLUSION

The mMDF strategy can significantly improve the research efficiency of qualitative metabolism of saponins. Although NG-R1 could be transformed into a variety of metabolites in rat liver and brain homogenate, it still existed mainly in prototype form. In the rat flora, NG-R1 mainly existed in the form of deglycosylated metabolite Rg1.