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

An integrated analysis strategy for characterization of chromones and coumarins from Saposhnikovia divaricata (Turcz.) Schischk. by UHPLC-QTOF-MS

This study aimed to employ a comprehensive data screening strategy to identify the chromones and coumarins present in Saposhnikovia divaricata (SD). Initially, the five-point mass defect filter (MDF) method was utilized to screen the respective three subclasses of chromones and coumarins for MS1. In comparison to the traditional MDF method, the number of interference peaks was reduced from 3462 to 1053, representing a decrease of 69.58 %. Then, diagnostic fragment ion filtering (DFIF) was used to screen product ions selected by MDF method, which was based on the fragmentation rules of each subclass to screen whether it met the conditions. Finally, we characterized 94 compounds from SD, including 40 chromones and 54 coumarins, among them, 82 chromones and coumarins were identified by combining the above two methods, 12 coumarins were identified by combining MDF and references, they were classified into other coumarins. Twenty one compounds were identified for the first time from SD, and 3 chromones and 7 coumarins were unknown compounds. Through untargeted metabolomics analysis of SD samples from 12 different regions, significant differences were found in SD samples from different areas, and 20 differential metabolites were distinguished, including 13 chromones and 7 coumarins. This study established for the first time a comprehensive strategy combining MDF, DFIF, and untargeted metabolomics to evaluate SD quality. The results indicated that this method is an efficient, accurate, and promising approach for classifying and exploring compounds in complex natural product systems, providing a basis for evaluating the quality of SD from different sources.

Identifying of Anticoagulant Ingredients From Moutan Cortex Based on Spectrum-Effect Relationship Analysis Combined With GRA, PLS, and SVM Algorithms

Moutan Cortex (MC) is a renowned Chinese medicine used for promoting blood circulation and removing blood stasis. However, the active ingredients are unclear. This study aimed to identify and validate the active ingredients of MC. UPLC fingerprints of 23 batches of MC from various origins were analyzed. The activating blood efficacy of MC was assessed by evaluating the inhibitory effects on thrombin and factor Xa (FXa) using the chromogenic substrate method. Active ingredients were identified through spectrum-effect relationship analysis using gray relation analysis (GRA), partial least squares (PLS), and support vector machine (SVM) algorithms. Consequently, five components were identified as potential active ingredients: mudanpioside H, oxypaeoniflorin, 1,2,3,4,6-penta-O-galloyl-β-d-glucose (PGG), benzoyloxypaeoniflorin, and suffruticoside A/B/C/D. The pharmacological activities of these five active ingredients were further confirmed by measuring their thrombin inhibition ability and antithrombotic effects in zebrafish, and their interactions with thrombin and FXa were examined using molecular docking technology. Oxypaeoniflorin, benzoyloxypaeoniflorin, and PGG demonstrated significant efficacy in promoting blood circulation and resolving blood stasis, as well as strong binding affinities. This study provides a biochemical foundation for the anticoagulant effects of MC and offers valuable insights for quality control and the development of novel anticoagulant ingredients drugs.

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.

Advances in AI-based strategies and tools to facilitate natural product and drug development

Natural products and their derivatives have been important for treating diseases in humans, animals, and plants. However, discovering new structures from natural sources is still challenging. In recent years, artificial intelligence (AI) has greatly aided the discovery and development of natural products and drugs. AI facilitates to: connect genetic data to chemical structures or vice-versa, repurpose known natural products, predict metabolic pathways, and design and optimize metabolites biosynthesis. More recently, the emergence and improvement in neural networks such as deep learning and ensemble automated web based bioinformatics platforms have sped up the discovery process. Meanwhile, AI also improves the identification and structure elucidation of unknown compounds from raw data like mass spectrometry and nuclear magnetic resonance. This article reviews these AI-driven methods and tools, highlighting their practical applications and guide for efficient natural product discovery and drug development.

Quantification of plant specialized metabolites for quality determination of medicinal and aromatic plants: Findings in the absence of a reference standard

The analysis and quantification of plant metabolites is a major challenge as medicinal and aromatic plant extracts are very complex and there is a lack of commercially pure standards that are important for both identification and quantification. The aim of this work is to compare the performance of different detectors (PDA and MS) used in high performance liquid chromatography and acquisition modes (Selected Ion Monitoring (SIM) and Selected Reaction Monitoring (SRM) in MS) for the quantification of specialized plant metabolites (i.e. phenolic and triterpenic compounds). All metabolites were quantified using the above detection methods with the reference standard and with a compound with similar UV and MS spectra (semi-quantification) to simulate the very common cases where the reference standard is not available or accessible. The precision of each quantification approach was evaluated by the percentage relative error based on the actual concentration of the quantified compound. The quantification precision was also tested in the presence of interferences and in two case studies, i.e. leaf extracts of Cynara cardunculus subsp. cardunculus L. and Punica granatum L.. The results show that quantification with the reference standard is certainly more precise. For semi-quantification, SIM and especially SRM are less suitable as they are more selective compared to PDA, but they allow detection and approximate quantification of the molecule of interest limiting interference, especially in complex matrices where coelution is sometimes unavoidable. A correction method is also proposed to overcome the over-underestimation that can occur with semi-quantification.

Deep tissue sensing of chiral molecules using polarization-enhanced photoacoustics

Chiral molecule sensing is typically performed using techniques like chromatography, electrophoresis, enzymatic assays, mass spectrometry, and chiroptical methods. While polarimetry allows for in vivo sensing up to 1 mm depth using ultraviolet-visible light, it is limited by dominant light scattering beyond this depth. We propose that photoacoustic sensing in the near-infrared II (NIR-II) window can enable deep tissue sensing as acoustic waves scatter less than light. To achieve this, we developed a photoacoustic polarization-enhanced optical rotation sensing (PAPEORS) system, capable of estimating optical rotation from photoacoustic signals and correlating it with chiral molecular concentration for depths up to 3.5 mm. Experiments were conducted using aqueous glucose solutions, naproxen, serum-based glucose samples, and ex vivo chicken tissue. PAPEORS achieved a detection limit of 80 mg/dl while using circularly polarized light with serum samples, demonstrating the potential for deep-tissue chiral molecular sensing. PAPEORS holds promise for in vivo sensing and easy miniaturization using single wavelength.

Integrated untargeted metabolomics and bioactivity studies as new insights into the chemotaxonomy of Hura crepitans specimens from Peru and Sub-Saharan Africa

Hura crepitans (Euphorbiaceae), is widespread in the Amazon rainforest and on plantations in sub-Saharan Africa. This tree produces an irritating milky latex rich in secondary metabolites, notably daphnane-type diterpenes and cerebrosides. Previous studies have shown that huratoxin, the main daphnane in the latex, significantly and selectively inhibited the growth of colorectal cancer cells through a unique mechanism involving the activation of PKCζ. One major challenge in isolating active molecules from natural products is the accessibility of the resource. This study explores the phytochemical composition and cytotoxic activities of latexes collected in Peru, Benin, and Togo using UHPLC-MS and metabolomics tools to identify a renewable source of bioactive compounds. Significant inter- and intra-continental differences in chemical composition have been highlighted, with daphnanes being concentrated in the Peruvian samples. Extracts form latexes collected in Peru showed cytostatic activity on Caco-2 cells, correlated with the presence of daphnanes, while some African samples exhibited cytotoxic activity on Jurkat and Hela cancer cell lines, leading to the identification of potential other new bioactive compounds such as elasterol and cerebrosides. OBJECTIVE: To compare the composition of different Hura crepitans latex samples and determine their cytotoxic activity in order to identify new bioactive compounds CONCLUSIONS: Inter- and intra-continental variations in the phytochemical composition of latex were observed, leading to significant cytotoxic activities on different cell lines. Daphnanes were identified as responsible for the activity on Caco-2 cells, while elasterol and cerebrosides were putatively associated with the activity on Hela cells.

Embryonic Zebrafish Irritant-evoked Hyperlocomotion (EZIH) as a high-throughput behavioral model for nociception

Behavioral models have served a key role in understanding nociception, the sensory system by which animals detect noxious stimuli in their environment. Developing zebrafish (Danio rerio) are a powerful study organism for examining nociceptive pathways, given the vast array of genetic, developmental, and neuroscience tools available for these animals. However, at present there are few widely-adopted behavioral models for nociception in developing zebrafish. This study examines the locomotor response of hatching-stage zebrafish embryos to dilute solutions of the noxious chemical and TRPA1 agonist allyl isothiocyanate (AITC). At this developmental stage, AITC exposure induces a robust uniphasic hyperlocomotion response. This behavior was thoroughly characterized by determining the effects of pre-treatment with an array of pharmacological agents, including anesthetics, TRPA1 agonists/antagonists, opioids, NSAIDs, benzodiazepines, SSRIs, and SNRIs. Anesthetics suppressed the response to AITC, pre-treatment with TRPA1 agonists induced hyperlocomotion and blunted the response to subsequent AITC exposures, and TRPA1 antagonists and the opioid buprenorphine tended to reduce the response to AITC. The behavioral responses of zebrafish embryos to a noxious chemical were minimally affected by the other pharmacological agents examined. The feasibility of using this behavioral model as a screening platform for drug discovery efforts was then evaluated by assaying a library of natural product mixtures from microbial extracts and fractions. Overall, our results indicate that irritant-evoked locomotion in embryonic zebrafish is a robust behavioral model for nociception with substantial potential for examining the molecular and cellular pathways associated with nociception and for drug discovery efforts.

NPENN: A Noise Perturbation Ensemble Neural Network for Microbiome Disease Phenotype Prediction

With advances in microbiomics, the crucial role of microbes in disease progression is increasingly recognized. However, predicting disease phenotypes using microbiome data remains challenging due to data complexity, heterogeneity, and limited model generalization. Current methods often depend on specific datasets and are vulnerable to adversarial attacks. To address these issues, this paper introduces a novel Noise Perturbation Ensemble Neural Network model (NPENN), which combines noise mechanisms with Gradient Boosting (GB) techniques for robust neural network ensemble learning. NPENN, validated on multiple microbiome datasets, shows superior accuracy and generalization compared to traditional methods, effectively handling data complexity and variability. This approach enhances model robustness and feature learning by integrating GB prior knowledge. Additionally, the study explores microbial community roles in various diseases, providing insights into disease mechanisms and potential biomarkers for personalized precision diagnosis and treatment strategies.

Harnessing NMR technology for enhancing field crop improvement: applications, challenges, and future perspectives

INTRODUCTION

Nuclear Magnetic Resonance (NMR) spectroscopy has emerged as a transformative technology in agricultural research, offering powerful analytical capabilities for field crop improvement. With global challenges such as food security and climate change intensifying, there is an urgent need for innovative methodologies to enhance our understanding of plant health, metabolic pathways, and crop-environment interactions. NMR's ability to provide nondestructive, real-time analysis of plant metabolites and soil chemistry positions it as a critical tool for addressing these pressing concerns.

OBJECTIVE

This review aims to elucidate the potential of NMR spectroscopy in advancing field crop improvement by highlighting its applications, challenges, and future perspectives in agricultural methodologies. The focus is on the evolution and application of NMR in agricultural research, particularly in metabolomics, phenotyping, and quality assessment.

METHOD

A comprehensive literature review was conducted to analyze recent advancements in NMR applications in agriculture. Particular emphasis was given to high-resolution magic angle spinning (HR-MAS) and time-domain NMR techniques, which have been instrumental in elucidating plant metabolites and soil chemistry. Studies showcasing the integration of NMR with complementary technologies for enhanced metabolic profiling and genetic marker identification were reviewed.

RESULTS

Findings indicate that NMR spectroscopy is an indispensable tool in agriculture due to its ability to identify biomarkers indicative of crop resilience, monitor soil composition, and contribute to food safety and quality assessments. The integration of NMR with other technologies has accelerated metabolic profiling, aiding in the breeding of high-yielding and stress-resistant crop varieties. However, challenges such as sensitivity limitations and the need for standardization remain.

CONCLUSION

NMR spectroscopy holds immense potential for revolutionizing agricultural research and crop improvement. Overcoming existing challenges, such as sensitivity and standardization, is crucial for its broader application in practical agricultural settings. Collaborative efforts among researchers, agronomists, and policymakers will be essential for leveraging NMR technology to address global food security challenges and promote sustainable agricultural practices.

A novel UPLC-based method to identify elephant and mammoth ivory

The illegal ivory trade has led to a sharp decline in wild elephant populations in recent decades, while mammoth (Mammuthus primigenius) ivory products have increasingly flooded the marketplace, complicating identification efforts by frontline law enforcement. Existing ivory identification methods face several challenges, including inconsistent accuracy due to sample quality, high costs, slow turnaround times, and destructive sample requirements. Currently, there is a lack of a fast, convenient, and highly effective solution to address these issues. To tackle these challenges, this study developed a novel, efficient, and accurate method for identifying and characterizing ivory products using ultra-performance liquid chromatography with a fluorescence detector (UPLC-FLR). The technique focuses on various organic small-molecule compounds in ivory that have been largely overlooked. A chemical fingerprint library was created using 72 African elephant and 69 mammoth ivory samples. Comprehensive comparative analyses, including principal component analysis, compound distribution analysis, proportion analysis, chord diagrams, and statistical significance tests, revealed significant differences between the organic compounds in the two sample groups, confirming the method's reliability. Six widely used machine learning classification models were then applied to construct a discriminant model based on 11 key feature compounds among the 85 identified, with each model achieving 100% classification accuracy. Compared to the conventional 'gold standard' molecular biology method, this UPLC-based approach shortened detection time from 24 h to just 1 h, reduced the sample requirement by 50%, and cut costs by 90%, making it a more efficient, user-friendly solution for frontline law enforcement. Widespread adoption of this method in law enforcement could become a powerful tool in the fight against the illegal ivory trade.

The role of salivary metabolomics in chronic periodontitis: bridging oral and systemic diseases

BACKGROUND

Chronic periodontitis is a condition impacting approximately 50% of the world's population. As chronic periodontitis progresses, the bacteria in the oral cavity change resulting in new microbial interactions which in turn influence metabolite production. Chronic periodontitis manifests with inflammation of the periodontal tissues, which is progressively developed due to bacterial infection and prolonged bacterial interaction with the host immune response. The bi-directional relationship between periodontitis and systemic diseases has been reported in many previous studies. Traditional diagnostic methods for chronic periodontitis and systemic diseases such as chronic kidney diseases (CKD) have limitations due to their invasiveness, requiring practised individuals for sample collection, frequent blood collection, and long waiting times for the results. More rapid methods are required to detect such systemic diseases, however, the metabolic profiles of the oral cavity first need to be determined.

AIM OF REVIEW

In this review, we explored metabolomics studies that have investigated salivary metabolic profiles associated with chronic periodontitis and systemic illnesses including CKD, oral cancer, Alzheimer's disease, Parkinsons's disease, and diabetes to highlight the most recent methodologies that have been applied in this field.

KEY SCIENTIFIC CONCEPTS OF THE REVIEW

Of the rapid, high throughput techniques for metabolite profiling, Nuclear magnetic resonance (NMR) spectroscopy was the most applied technique, followed by liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). Furthermore, Raman spectroscopy was the most used vibrational spectroscopic technique for comparison of the saliva from periodontitis patients to healthy individuals, whilst Fourier Transform Infra-Red Spectroscopy (FT-IR) was not utilised as much in this field. A recommendation for cultivating periodontal bacteria in a synthetic medium designed to replicate the conditions and composition of saliva in the oral environment is suggested to facilitate the identification of their metabolites. This approach is instrumental in assessing the potential of these metabolites as biomarkers for systemic illnesses.

Comprehensive Metabolomics Profiling and Bioactivity Study of Lycium shawii (Awsaj) Extracts with Particular Emphasis on Potential Anti-Malarial Properties

Background/Objectives: Although malaria is one of the oldest known human diseases, it continues to be a major global health challenge. According to UNICEF, the global malaria mortality rate exceeded 600,000 annually in 2022, which includes more than 1000 children dying each day. This study aimed to investigate the comprehensive chemical profile and biological activities, particularly the antimalarial activity, of Lycium shawii (Awsaj), a shrub traditionally used in the Arabian Peninsula, Middle East, India, and Africa to treat a myriad of ailments. Methods: Crude extracts of L. shawii were prepared using water, ethanol, methanol, and acetone. Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) were utilized to perform untargeted metabolomics to maximize metabolite detection and tentatively identify bioactive phytochemicals. The total phenolic content (TPC) was measured for each extract, and bioassays were conducted to evaluate their antimalarial, antibacterial, and anti-inflammatory activities, particularly those of the water extract, which is the traditional method of consumption in Arabian folk medicine. Results: A total of 148 metabolites were detected, 45 of which were classified as phytochemicals. The bioassays revealed that the water extract that is traditionally used showed promising antimalarial potential by significantly inhibiting β-hematin formation in vitro at 1 mg/mL (with an absorbance of 0.140 ± 0.027). This is likely due to the rich presence of quinoline in the aqueous extract among several other bioactive phytochemicals, such as phenylpropanoids, alkaloids, flavonoids, and benzenoids. However, their anti-inflammatory and antibacterial activities were found to be weak, with only a minor inhibition of nitric oxide (NO) production in LPS-induced RAW 264.7 cells at a concentration of 500 µg/mL and weak antibacterial effects against pathogens like P. aeruginosa, MRSA, A. baumannii, and K. pneumoniae with an MIC of 500 μg/mL. The results also revealed that the methanolic extract had the highest TPC at 26.265 ± 0.005 mg GAE/g. Conclusions: The findings support the traditional medicinal use of L. shawii and highlight its potential as a source of novel therapeutic compounds, particularly for treating malaria. This study encourages further research to isolate and develop effective plant-based anti-malarial agents.

Bioactivity and metabolic profiling of crude extracts from endophytic bacteria linked to Solanum mauritianum scope: Discovery of antibacterial and anticancer properties

Bacterial endophytes associated with Solanum mauritianum Scop. represent a promising source of novel bioactive compounds with potential antibacterial and anticancer properties. This study aimed to investigate the diversity, distribution, and bioactivity of crude extracts derived from endophytic bacteria, focusing on their effects against bacterial pathogens of public health relevance and two cancer cell lines. Fresh, healthy plant samples were collected, and endophytes were isolated using standard cultural techniques. Identification of the endophytes was carried out through conventional and molecular methods. The comprehensive profiling and characterization of crude secondary metabolites were conducted using Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry (LC-QTOF-MS/MS) and Gas Chromatography-High Resolution Time-of-Flight Mass Spectrometry (GC-HRTOF-MS). The antibacterial activity and minimum inhibitory concentration were evaluated for the secondary metabolites using the Resazurin Microtitre assay. The anticancer activity of the metabolites was evaluated against A549 Lung carcinoma cells and U87MG Glioblastoma cells (ATCC culture cell lines). The result revealed a diversity of bacterial endophytes, including Pantoea species, Luteibacter sp. Bacillus safensis, Arthrobacter sp., and Bacillus licheniformis. These endophytes displayed distinct-tissue-specific distribution patterns within S. mauritianum. Metabolic profiling of three endophytes (P. ananatis, B. licheniformis, and Arthrobacter sp.) revealed 14 common and numerous unique metabolites. The crude secondary metabolites exhibited broad-spectrum antibacterial activity against reference strains of Bacillus cereus, Pseudomonas aeruginosa, and Staphylococcus epidermidis, where MICs as low as 0.125 mg/ml were recorded across several secondary metabolites of Pantoea ananatis, Bacillus licheniformis, and Arthrobacter sp. The cytotoxicity assays on UMG87 glioblastoma and A549 lung carcinoma cells revealed that the secondary metabolites did not induce cell death but instead promoted cell proliferation with different viability rates. While this proliferative effect limits their direct application as anticancer agents, it raises intriguing possibilities for their role in tissue regeneration or repair. This study provides critical insights into the microbial diversity of S. mauritianum and underscores the potential of its endophytic bacteria as sources of bioactive compounds with diverse biotechnological applications.

Exploring Elastic Lipid Nanovesicles for Enhanced Skin Permeation of Whole Plant Extract: A Comprehensive Investigation

A new method is developed using elastic lipid nanovesicles (ELNs) loaded with ethanolic extract of Lantana camara (LC) to enhance skin permeation of plant actives. The ELNs contained cholesterol, 1, 2-distearoyl-sn-glycero-3-phosphocholine, span 80, and tween 80. Firstly, 15 formulations were produced to examine critical factors likely affecting formulation characteristics. In addition, surface characteristics, vesicle size, polydispersity index, zeta potential, degree of deformability, and % entrapment efficiency (% EE) of ELN were examined. As a significant parameter, skin permeation was measured (using Start-M; it highly resembles human skin). The influence of size, hydrophilic-lipophilic balance (HLB), and surface ratio were vital to permeation through Start-M. In particular, the % LC extract permeation decreased at more extensive size ranges, 400, and 350-450 nm. In contrast, the % LC extract permeation increased significantly at smaller size ranges, such as 200 and 100 nm. More than 75% of the LC extract was permeated within 8 h when the surfactant ratio was (span 80:tween 80; 25%:75%). Permeation studies conducted based on HLB values revealed that 78% of LC extract was permeated in 8 h when HLB was 12.2, and that permeation decreased with an increase in HLB. Cell viability assay using SK-MEL-37 cells (skin cancer) revealed that ELN reduced the viability by ~80% in 24 h, further validating the formulation. Future research could investigate the long-term safety and therapeutic potential of these ELNs in clinical settings and their effectiveness in delivering other plant-based extracts for transdermal applications via ELNs.

Characterization of differences in volatile compounds and metabolites of six varieties of potato with different processing properties

Potato is the fourth-most important food crop around the world, and most of the potatoes are used for foodstuffs and starch products. The aim of this paper is to identify the volatile compounds and metabolites in potatoes with different processing properties. The results showed large differences of volatile and metabolite compounds such as 2,4-Heptadienal and rhoifolin in potatoes and indicated the potential regulations between volatile compounds and metabolites. Moreover, the differences in volatile and metabolite compounds were compared between fresh eating and processing type potatoes. Compared to process type potatoes, fresh eating potatoes contained a higher proportion of aldehyde and alcohol compounds, but being lower in hydrocarbon, furan, and ketone compounds. Moreover, the different expressed metabolites were involved in the metabolism of amino acids, flavone and flavanol biosynthesis, and tryptophan metabolism. The Random forest showed that the fresh eating and processing type potatoes could be distinguished by the content of amino acids and phenols.

Unveiling Anthraquinones: Diverse Health Benefits of an Essential Secondary Metabolite

Since ancient times, plants have been used as a remedy for numerous diseases. The pharmacological properties of plants are due to the presence of secondary metabolites like terpenoids, flavonoids, alkaloids, etc. Anthraquinones represent a group of naturally occurring quinones found generously across various plant species. Anthraquinones attract a significant amount of attention due to their reported efficacy in treating a wide range of diseases. Their complex chemical structures, combined with inherent medicinal properties, underscore their potential as agents for therapy. They demonstrate several therapeutic properties such as laxative, antitumor, antimalarial, antibacterial, antifungal, antioxidant, etc. Anthraquinones are found in different forms (derivatives) in plants, and they exhibit various medicinal properties due to their structure and chemical nature. The precursors for the biosynthesis of anthraquinones in higher plants are provided by different pathways such as plastidic hemiterpenoid 2-C-methyl-D-erthriol4-phosphate (MEP), mevalonate (MVA), isochorismate synthase and polyketide. Anthraquinones possess several medicinal properties and a complex biosynthetic pathway, making them good candidates for patenting new products, synthesis methods, and biotechnological production advancements. By conducting a thorough analysis of scientific literature, this review provides insights into the intricate interplay between anthraquinone biosynthesis and its broad-ranging contributions to human health.

HPTLC Combined with sHetCA and Multivariate Statistics for the Detection of Bioactive Compounds in Complex Mixtures

High-Performance Thin Layer Chromatography (HPTLC) is widely utilized in natural products research due to its simplicity, low cost, and short total analysis time, including data treatment. While bioautography can be used for rapid detection of bioactive compounds in extracts, the number of available bioautographic methods is limited mainly due to the high cost and difficulty in developing protocols that lead to accurate and reproducible results. For this reason, an alternative method for the detection of bioactive compounds in plant extracts prior to their isolation using HPTLC, combined with multivariate chemometrics, was previously explored by our lab. To evaluate this method and compare it to other chemometrics-based methods, an artificial mixture (ArtExtr) of 59 standard compounds was used as a case study. The ArtExtr was fractionated by FCPC and the inhibitory activity of all fractions against DPPH was evaluated, while their chemical profiles were recorded using HPTLC. Multivariate statistics and the heterocovariance approach (HetCA) were employed and compared, with the success rate in detecting the ArtExtr bioactive substances being 85.7% via sparse heterocovariance (sHetCA). HPTLC combined with sHetCA can serve as a valuable tool for the detection of bioactive compounds in complex mixtures when bioautography is not feasible.

Isomer Differentiation by UHPLC-Q-Exactive-Orbitrap MS led to Enhanced Identification of Daphnane Diterpenoids in Daphne tangutica

INTRODUCTION

Liquid chromatography-mass spectrometry (LC-MS) has enhanced the rapid, accurate analysis of complex plant extracts, eliminating the need for extensive isolation. Tandem mass spectrometry (MS/MS) further enhances this process by providing detailed structural information. However, differentiating structural isomers remains a challenge due to their minor spectral and structural differences.

OBJECTIVE

This study aimed to extend the applicability of LC-MS/MS for the structural identification of daphnane diterpenoids, with a particular focus on distinguishing functional isomers.

METHODS

LC-MS analyses were performed using an UHPLC-Q-Exactive-Orbitrap MS. The MS conditions for distinguishing isomers were optimized using in-source CID and HCD modes with reference compounds. A qualitative analysis was then conducted on the extract of Daphne tangutica. The chemical structures of the detected daphnane diterpenoids were estimated by analyzing the fragmentation patterns in both the mass spectra and product ion spectra. These identifications were further validated by isolation and comparison with an in-house daphnane diterpenoid library.

RESULTS

By optimizing MS conditions, especially in the negative ion mode, it was possible to accurately distinguish structural isomers such as yuanhuajine and gniditrin. Qualitative analysis of D. tangutica identified a total of 28 daphnanes, including seven previously unreported compounds. Furthermore, a novel geometric isomer of gniditrin was isolated by conducting isolation on the crude diterpenoid fraction.

CONCLUSION

This study demonstrated that LC-MS/MS analysis can effectively distinguish functional isomers of daphnane diterpenoids, thereby enhancing the identification of daphnanes in plant extracts and highlighting its potential as a powerful tool for phytochemical analysis.

Can NMR-HetCA be a Reliable Prediction Tool for the Direct Identification of Bioactive Substances in Complex Mixtures?

Conventional isolation methods in natural products chemistry are time-consuming and costly and often result in the isolation of moderately active compounds or the detection of already known natural products (NPs). A fast and cost-effective way to identify bioactive metabolites in plant extracts prior to isolation has been developed based on the nuclear magnetic resonance (NMR)-heterocovariance approach (NMR-HetCA). In order to evaluate in depth the application of this chemometrics-based drug discovery methodology, simple mixtures of 10 standard NPs simulating a fast centrifugal partition chromatography (FCPC) fractionation (artificial fractions, ArtFrcts), as well as a more complex mixture of 59 natural standard substances simulating a crude plant extract (artificial extract, ArtExtr), were prepared. FCPC was employed for the fractionation of the ArtExtr, while the inhibitory activity of all fractions against DPPH was evaluated, and their chemical profile was recorded using NMR spectroscopy. Spectral information was processed in the MATLAB environment, and statistical approaches, including HetCA and statistical total correlation spectroscopy (STOCSY), were applied to identify bioactive compounds. Total heterocovariance plots (pseudospectra) facilitated the detection of highly correlated metabolites and led to the direct identification of 52.6% of the active compounds. The success in identifying the ArtExtr bioactive substances increased to 63.2% when spectral alignment was implemented. HetCA incorporates chromatographic (fractionation), spectroscopic (NMR profiling), and bioactivity results along with advanced chemometrics and could be established as a method of choice for the rapid and effective identification of bioactive NPs in plant extracts prior to isolation.

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.

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.

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.

Phytochemical Analysis and Biological Evaluation of Carob Leaf (Ceratonia siliqua L.) Crude Extracts Using NMR and Mass Spectroscopic Techniques

Carob leaves have gained attention for their bioactive properties and traditional medicinal uses, including as treatment for diabetes, digestive disorders, and microbial infections. The aim of this study was to explore the phytochemical composition of carob leaf acetone extracts using advanced spectroscopic techniques. The combined use of heteronuclear nuclear magnetic resonance (NMR) experiments with 1D selective nuclear Overhauser effect spectroscopy (NOESY) offers detailed structural insights and enables the direct identification and quantification of key bioactive constituents in carob leaf extract. In particular, the NMR and mass spectrometry techniques revealed the presence of myricitrin as a predominant flavonoid, as well as a variety of glycosylated derivatives of myricetin and quercetin, in acetone extract. Furthermore, siliquapyranone and related gallotannins are essential constituents of the extract. The potent inhibitory effects of the carob leaf extract on Staphylococcus aureus (MIC = 50 μg mL-1) and a-glucosidase enzyme (IC50 = 67.5 ± 2.4 μg mL-1) were also evaluated. Finally, the antibacterial potency of carob leaf constituents were calculated in silico; digalloyl-parasorboside and gallic acid 4-O-glucoside exert a stronger bactericidal activity than the well-known myricitrin and related flavonoids. In summary, our findings provide valuable insights into the bioactive composition and health-promoting properties of carob leaves and highlight their potential for pharmaceutical and nutraceutical applications.

Exploring the Benefits of Herbal Medicine Composite 5 (HRMC5) for Skin Health Enhancement

The skin, as the body's largest organ, is vital for protecting against environmental stressors, regulating temperature, and preventing water loss. Here, we examined the potential of a mixture of five traditional Korean herbal extracts-Cimicifuga racemosa, Paeonia lactiflora, Phellodendron amurense, Rheum rhaponticum, and Scutellaria baicalensis-referred to as herbal medicine composite 5 (HRMC5) for enhancing skin health and managing menopausal symptoms. High-performance liquid chromatography identified 14 bioactive compounds, including flavonoids, phenolic acids, anthraquinones, and alkaloids. In vitro studies revealed an optimal concentration of 0.625 g/L for cell survival and UV protection, with the mixture demonstrating significant wound-healing properties comparable to epidermal growth factor. HRMC5 exhibited anti-inflammatory effects by downregulating COX2 expression and upregulating the key skin barrier proteins. A 4-week clinical trial involving 20 postmenopausal women showed significant improvements in skin redness, hemoglobin concentration, and skin moisture content. Visual analog scale assessments indicated substantial reductions in facial flushing severity and the associated sweating. The topical application of HRMC5 cream offered potential advantages over ingested phytoestrogens by reducing the systemic side effects. These findings suggest that HRMC5 is a promising non-invasive treatment for vasomotor symptoms in menopausal women and overall skin health, warranting further research on its long-term efficacy and safety in larger populations.

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.

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.

Phytovesicular Nanoconstructs for Advanced Delivery of Medicinal Metabolites: An In-Depth Review

Phytochemicals, the bioactive compounds in plants, possess therapeutic benefits, such as antimicrobial, antioxidant, and pharmacological activities. However, their clinical use is often hindered by poor bioavailability and stability. Phytosome technology enhances the absorption and efficacy of these compounds by integrating vesicular systems like liposomes, niosomes, transfersomes, and ethosomes. Phytosomes offer diverse biological benefits, including cardiovascular protection through improved endothelial function and oxidative stress reduction. They enhance cognitive function and protect against neurodegenerative diseases in the nervous system, aid digestion and reduce inflammation in the gastrointestinal system, and provide hepatoprotective effects by enhancing liver detoxification and protection against toxins. In the genitourinary system, phytosomes improve renal function and exhibit anti-inflammatory properties. They also modulate the immune system by enhancing immune responses and reducing inflammation and oxidative stress. Additionally, phytosomes promote skin health by protecting against UV radiation and improving hydration and elasticity. Recent patented phytosome technologies have led to innovative formulations that improve the stability, bioavailability, and therapeutic efficacy of phytochemicals, although commercialization challenges like manufacturing scalability and regulatory hurdles remain. Secondary metabolites from natural products are classified into primary and secondary metabolites, with a significant focus on terpenoids, phenolic compounds, and nitrogen-containing compounds. These metabolites have notable biological activities: antimicrobial, antioxidant, antibiotic, antiviral, anti-inflammatory, and anticancer effects. In summary, this review amalgamates the latest advancements in phytosome technology and secondary metabolite research, presenting a holistic view of their potential to advance therapeutic interventions and contribute to the ever-evolving landscape of natural product-based medicine.

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.