Untargeted metabolomics: an emerging approach to determine the composition of herbal products

Widely Targeted Metabolomic Analysis Reveals the Improvement in Panax notoginseng Triterpenoids Triggered by Arbuscular Mycorrhizal Fungi via UPLC-ESI-MS/MS

Panax notoginseng is a highly valued perennial medicinal herb in China and is widely used in clinical treatments. The main purpose of this study was to elucidate the changes in the composition of P. notoginseng saponins (PNSs), which are the main bioactive substances, triggered by arbuscular mycorrhizal fungi (AMF) via ultrahigh-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS). A total of 202 putative terpenoid metabolites were detected, of which 150 triterpene glycosides were identified, accounting for 74.26% of the total. Correlation analysis, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) of the metabolites revealed that the samples treated with AMF (group Ce) could be clearly separated from the CK samples. In total, 49 differential terpene metabolites were identified between the Ce and CK groups, of which 38 and 11 metabolites were upregulated and downregulated, respectively, and most of the upregulated differentially abundant metabolites were mainly triterpene glycosides. The relative abundances of the two major notoginsenosides (MNs), ginsenosides Rd and Re, and 13 rare notoginsenosides (RNs), significantly increased. The differential saponins, especially RNs, were more easily clustered into one branch and had a high positive correlation. It could be concluded that the biosynthesis and accumulation of some RNs share the same pathways as those triggered by AMF. This study provides a new way to obtain more notoginsenoside resources, particularly RNs, and sheds new light on the scientization and rationalization of the use of AMF agents in the ecological planting of medicinal plants.

LC-QTOF/MS-Based Profiling of the Phytochemicals in Ice Plant (Mesembryanthemum crystallinum) and Their Bioactivities

Recent assessments of the correlations between food and medicine underscore the importance of functional foods in disease prevention and management. Functional foods offer health benefits beyond basic nutrition, with fresh fruits and vegetables being particularly prominent because of their rich polyphenol content. In this study, we elucidated the phytochemicals in ice plant (Mesembryanthemum crystallinum), a globally consumed vegetable, using an LC-QTOF/MS-based untargeted detection method. The phytochemicals were clustered based on their structural similarity using molecular networking and annotated using the in silico tool for network annotation propagation. To identify the bioactive compounds, eight compounds were isolated from ice plant extracts. These compounds were identified using extensive spectroscopic methods, including 1H and 13C nuclear magnetic resonance (NMR) spectroscopy. Additionally, we evaluated the antioxidant and anti-inflammatory activities of all the isolates. Among the tested compounds, three showed antioxidant activity and all eight showed anti-inflammatory activity, demonstrating the potential of ice plant as a functional food.

Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications

Prostate cancer (PCa) is a significant global contributor to mortality, predominantly affecting males aged 65 and above. The field of omics has recently gained traction due to its capacity to provide profound insights into the biochemical mechanisms underlying conditions like prostate cancer. This involves the identification and quantification of low-molecular-weight metabolites and proteins acting as crucial biochemical signals for early detection, therapy assessment, and target identification. A spectrum of analytical methods is employed to discern and measure these molecules, revealing their altered biological pathways within diseased contexts. Metabolomics and proteomics generate refined data subjected to detailed statistical analysis through sophisticated software, yielding substantive insights. This review aims to underscore the major contributions of multi-omics to PCa research, covering its core principles, its role in tumor biology characterization, biomarker discovery, prognostic studies, various analytical technologies such as mass spectrometry and Nuclear Magnetic Resonance, data processing, and recent clinical applications made possible by an integrative "omics" approach. This approach seeks to address the challenges associated with current PCa treatments. Hence, our research endeavors to demonstrate the valuable applications of these potent tools in investigations, offering significant potential for understanding the complex biochemical environment of prostate cancer and advancing tailored therapeutic approaches for further development.

Integrating High-Resolution Mass Spectral Data, Bioassays and Computational Models to Annotate Bioactives in Botanical Extracts: Case Study Analysis of C. asiatica Extract Associates Dicaffeoylquinic Acids with Protection against Amyloid-β Toxicity

Rapid screening of botanical extracts for the discovery of bioactive natural products was performed using a fractionation approach in conjunction with flow-injection high-resolution mass spectrometry for obtaining chemical fingerprints of each fraction, enabling the correlation of the relative abundance of molecular features (representing individual phytochemicals) with the read-outs of bioassays. We applied this strategy for discovering and identifying constituents of Centella asiatica (C. asiatica) that protect against Aβ cytotoxicity in vitro. C. asiatica has been associated with improving mental health and cognitive function, with potential use in Alzheimer's disease. Human neuroblastoma MC65 cells were exposed to subfractions of an aqueous extract of C. asiatica to evaluate the protective benefit derived from these subfractions against amyloid β-cytotoxicity. The % viability score of the cells exposed to each subfraction was used in conjunction with the intensity of the molecular features in two computational models, namely Elastic Net and selectivity ratio, to determine the relationship of the peak intensity of molecular features with % viability. Finally, the correlation of mass spectral features with MC65 protection and their abundance in different sub-fractions were visualized using GNPS molecular networking. Both computational methods unequivocally identified dicaffeoylquinic acids as providing strong protection against Aβ-toxicity in MC65 cells, in agreement with the protective effects observed for these compounds in previous preclinical model studies.

Metabolomic analysis of Thai Herbal Analgesic Formula based on ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry

Sahatsatara formula (STF), a Thai herbal medicine formula which has been commonly used as analgesic drugs to relieve musculoskeletal pain and numbness in Thai traditional medicine. The pharmacological studies of its ingredients have represented that have anti-inflammatory and antioxidant properties. However, the quality markers (Q-markers) for STF are still unknown and require further investigation. The primary goal of this study was to establish the chemical profile of STF though metabolomic analysis. Untargeted metabolomics were used to analyze global components and accurately qualify compounds. Multivariate analysis (MVA) was used to classify STF extract at three different concentrations and a quality control sample. Furthermore, samples' characteristics and identification-related markers were observed and compounds matched to the Traditional Chinese medicine library in UNIFI software. According to the results, chemical analysis revealed 63 compounds in positive mode and 33 compounds in negative mode within STF. Notably, 19 potential Q-markers were tentative identified in all three concentrations of STF, including alkaloids, terpenes, phenols, organic acids, disaccharides, fatty acids, glycosides, quinonoids, and steroids. The compounds exhibited pharmacological effects such as anti-inflammatory activity, anti-oxidant activity, and analgesic properties, which correlated to traditional properties of STF. Consequently, this study provides insights into the chemical profiles of the STF and identifies potential markers that can be utilized for qualitative and quantitative quality control of STF. Additionally, the findings can also be useful for further research into STF's anti-inflammatory properties through in vitro assays, as well as exploring its clinical efficacy to support evidence-based medicine for STF.

Mass spectrometry-based metabolomic analysis as a tool for quality control of natural complex products

Metabolomics is an area of intriguing and growing interest. Since the late 1990s, when the first Omic applications appeared to study metabolite's pool ("metabolome"), to understand new aspects of the global regulation of cellular metabolism in biology, there have been many evolutions. Currently, there are many applications in different fields such as clinical, medical, agricultural, and food. In our opinion, it is clear that developments in metabolomics analysis have also been driven by advances in mass spectrometry (MS) technology. As natural complex products (NCPs) are increasingly used around the world as medicines, food supplements, and substance-based medical devices, their analysis using metabolomic approaches will help to bring more and more rigor to scientific studies and industrial production monitoring. This review is intended to emphasize the importance of metabolomics as a powerful tool for studying NCPs, by which significant advantages can be obtained in terms of elucidation of their composition, biological effects, and quality control. The different approaches of metabolomic analysis, the main and basic techniques of multivariate statistical analysis are also briefly illustrated, to allow an overview of the workflow associated with the metabolomic studies of NCPs. Therefore, various articles and reviews are illustrated and commented as examples of the application of MS-based metabolomics to NCPs.

Detecting and Profiling of Milk Thistle Metabolites in Food Supplements: A Safety-Oriented Approach by Advanced Analytics

Milk thistle (Silybum marianum (L.) Gaertn.) is among the top-selling botanicals used as a supportive treatment for liver diseases. Silymarin, a mixture of unique flavonolignan metabolites, is the main bioactive component of milk thistle. The biological activities of silymarin have been well described in the literature, and its use is considered safe and well-tolerated in appropriate doses. However, commercial preparations do not always contain the recommended concentrations of silymarin, failing to provide the expected therapeutic effect. While the poor quality of raw material may explain the low concentrations of silymarin, its deliberate removal is suspected to be an adulteration. Toxic contaminants and foreign matters were also detected in milk thistle preparations, raising serious health concerns. Standard methods for determination of silymarin components include thin-layer chromatography (TLC), high-performance thin-layer chromatography (HPTLC), and high-performance liquid chromatography (HPLC) with various detectors, but nuclear magnetic resonance (NMR) and ultra-high-performance liquid chromatography (UHPLC) have also been applied. This review surveys the extraction techniques of main milk thistle metabolites and the quality, efficacy, and safety of the derived food supplements. Advanced analytical authentication approaches are discussed with a focus on DNA barcoding and metabarcoding to complement orthogonal chemical characterization and fingerprinting of herbal products.

Direct introduction MALDI FTICR MS based on dried droplet deposition applied to non-targeted metabolomics on Pisum Sativum root exudates

Non-targeted metabolomic approaches based on direct introduction (DI) through a soft ionization source are nowadays used for large-scale analysis and wide cover-up of metabolites in complex matrices. When coupled with ultra-high-resolution Fourier-Transform ion cyclotron resonance (FTICR MS), DI is generally performed through electrospray (ESI), which, despite the great analytical throughput, can suffer of matrix effects due to residual salts or charge competitors. In alternative, matrix assisted laser desorption ionization (MALDI) coupled with FTICR MS offers relatively high salt tolerance but it is mainly used for imaging of small molecule within biological tissues. In this study, we report a systematic evaluation on the performance of direct introduction ESI and MALDI coupled with FTICR MS applied to the analysis of root exudates (RE), a complex mixture of metabolites released from plant root tips and containing a relatively high salt concentration. Classic dried droplet deposition followed by screening of best matrices and ratio allowed the selection of high ranked conditions for non-targeted metabolomics on RE. Optimization of MALDI parameters led to improved reproducibility and precision. A RE desalted sample was used for comparison on ionization efficiency of the two sources and ion enhancement at high salinity was highlighted in MALDI by spiking desalted solution with inorganic salts. Application of a true lyophilized RE sample exhibited the complementarity of the two sources and the ability of MALDI in the detection of undisclosed metabolites suffering of matrix effects in ESI mode.

Comparative metabolomics analysis reveals alkaloid repertoires in young and mature Mitragyna speciosa (Korth.) Havil. Leaves

The fresh leaves of Mitragyna speciosa (Korth.) Havil. have been traditionally consumed for centuries in Southeast Asia for its healing properties. Although the alkaloids of M. speciosa have been studied since the 1920s, comparative and systematic studies of metabolite composition based on different leaf maturity levels are still lacking. This study assessed the secondary metabolite composition in two different leaf stages (young and mature) of M. speciosa, using an untargeted liquid chromatography-electrospray ionisation-time-of-flight-mass spectrometry (LC-ESI-TOF-MS) metabolite profiling. The results revealed 86 putatively annotated metabolite features (RT:m/z value) comprising 63 alkaloids, 10 flavonoids, 6 terpenoids, 3 phenylpropanoids, and 1 of each carboxylic acid, glucoside, phenol, and phenolic aldehyde. The alkaloid features were further categorised into 14 subclasses, i.e., the most abundant class of secondary metabolites identified. As per previous reports, indole alkaloids are the most abundant alkaloid subclass in M. speciosa. The result of multivariate analysis (MVA) using principal component analysis (PCA) showed a clear separation of 92.8% between the young and mature leaf samples, indicating a high variance in metabolite levels between them. Akuammidine, alstonine, tryptamine, and yohimbine were tentatively identified among the many new alkaloids reported in this study, depicting the diverse biological activities of M. speciosa. Besides delving into the knowledge of metabolite distribution in different leaf stages, these findings have extended the current alkaloid repository of M. speciosa for a better understanding of its pharmaceutical potential.

Multi-Omics Approaches in Colorectal Cancer Screening and Diagnosis, Recent Updates and Future Perspectives

Colorectal cancer (CRC) is common Cancer as well as the third leading cause of mortality around the world; its exact molecular mechanism remains elusive. Although CRC risk is significantly correlated with genetic factors, the pathophysiology of CRC is also influenced by external and internal exposures and their interactions with genetic factors. The field of CRC research has recently benefited from significant advances through Omics technologies for screening biomarkers, including genes, transcripts, proteins, metabolites, microbiome, and lipidome unbiasedly. A promising application of omics technologies could enable new biomarkers to be found for the screening and diagnosis of CRC. Single-omics technologies cannot fully understand the molecular mechanisms of CRC. Therefore, this review article aims to summarize the multi-omics studies of Colorectal cancer, including genomics, transcriptomics, proteomics, microbiomics, metabolomics, and lipidomics that may shed new light on the discovery of novel biomarkers. It can contribute to identifying and validating new CRC biomarkers and better understanding colorectal carcinogenesis. Discovering biomarkers through multi-omics technologies could be difficult but valuable for disease genotyping and phenotyping. That can provide a better knowledge of CRC prognosis, diagnosis, and treatments.

Simultaneous UHPLC-MS Quantification of Catechins and Untargeted Metabolomic Profiling for Proof-of-Concept Authenticity Determination of Maytenus ssp. Samples

Due to the widespread use of Maytenus ilicifolia leaves in the treatment of gastric ulcers, herbal medicines derived from such species are distributed by the national health system in Brazil. A related species, Maytenus aquifolium, is also used for the same disorders, and both are popularly known as Espinheira-santa. Due to their popular use, the quality and efficiency of the herbal medicines derived from these species is an important public health issue. The purpose of this study was to develop and test an analytical method that could quantify the content of catechin and epicatechin in dry Maytenus spp. leaves and simultaneously obtain their chemical profile to determine authenticity of the leaf samples. Ultra-high performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) was used to quantify these isomers, in the selected ion monitoring (SIM) mode, while simultaneously analyzing the extract in full-scan mode. This approach was successfully applied to the analysis of commercial and authentic samples of Maytenus spp. Fewer than half the samples presented the minimum epicatechin content of 2.8 mg per g of dry leaf mass, as specified in the 6th Brazilian Pharmacopoeia (2019) for M. ilicifolia. Furthermore, by using untargeted metabolomics, it was observed that the chemical profile of most the samples was not compatible with M. ilicifolia leaves, indicating the need for stricter quality control of this material. The method described herein could be used for this control; moreover, its concept could be adapted and used for an ample variety of medicinal plant products.

Generating Novel Aroma Phenotypes Using Commercial Wine Samples to Characterize an F1 Population

Due to their disease tolerance and cold hardy nature, interspecific hybrid grapes are widely grown in the Midwestern and Northeastern United States, with additional interest worldwide in the face of increased abiotic and biotic stresses from climate change. However, the aroma profile of these hybrids is unique and generally less popular in comparison with Vitis vinifera grapes. One of the challenges in any phenotyping project is first defining the traits of interest. As wine quality was our ultimate metric of interest, the aroma profile of commercial wines produced from the parents of a breeding population (Vitis aestivalis derived 'Norton' x V. vinifera. 'Cabernet Sauvignon') was first assessed for traits of interest. We investigated 11 commercial wines each of Norton, a popular hybrid in Missouri and Cabernet Sauvignon (Cab) for their volatile profiles using the more inclusive metabolomics-based workflow. We then analyzed 21 Norton and 21 Cab grapes from different sites and vintages for the free and bound volatile compounds using HS-SPME-GCMS to validate the differences in wine. The GCMS data was processed using XCMS software to find features that were different between the two cultivars. The two cultivars were found to have differences in their volatile profiles, with 304 features different for wine volatiles, 418 features different for free volatiles, and 302 features different for bound volatiles at 0.05 significance level and with at least a 1.5-fold change between the two cultivars. Those features were used to identify several odor-active compounds in both grapes and wines, including β-damascenone, β-ionone, eugenol, 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN), and methyl salicylate. Some of the identified compounds were higher in Norton than Cab; however, several features were higher in Cab. Using the identified aroma compounds as markers, we phenotyped an F1 population of Norton and Cab. The F1 population was found to be segregating for many aroma compounds with some genotypes demonstrating an even higher concentration of aroma volatiles than either of the parents. Ultimately, using commercially available samples paired with untargeted analysis proved to be an efficient way to determine phenotypes of interest for further analysis and may offer an easy way to choose potential parents with desired traits for breeding.

Living with a giant, flowering parasite: metabolic differences between Tetrastigma loheri Gagnep. (Vitaceae) shoots uninfected and infected with Rafflesia (Rafflesiaceae) and potential applications for propagation

Metabolites in Rafflesia-infected and non-infected Tetrastigma were compared which may have applications in Rafflesia propagation. Benzylisoquinoline alkaloids, here reported for the first time in Vitaceae, were abundant in non-infected shoots and may be a form of defense. In Rafflesia-infected shoots, oxylipins, which mediate immune response, were elevated. Endemic to the forests of Southeast Asia, Rafflesia (Rafflesiaceae) is a genus of holoparasitic plants producing the largest flowers in the world, yet completely dependent on its host, the tropical grape vine, Tetrastigma. Rafflesia species are threatened with extinction, making them an iconic symbol of plant conservation. Thus far, propagation has proved challenging, greatly decreasing efficacy of conservation efforts. This study compared the metabolites in the shoots of Rafflesia-infected and non-infected Tetrastigma loheri to examine how Rafflesia infection affects host metabolomics and elucidate the Rafflesia infection process. Results from LC-MS-based untargeted metabolomics analysis showed benzylisoquinoline alkaloids were naturally more abundant in non-infected shoots and are here reported for the first time in the genus Tetrastigma, and in the grape family, Vitaceae. These metabolites have been implicated in plant defense mechanisms and may prevent a Rafflesia infection. In Rafflesia-infected shoots, oxygenated fatty acids, or oxylipins, and a flavonoid, previously shown involved in plant immune response, were significantly elevated. This study provides a preliminary assessment of metabolites that differ between Rafflesia-infected and non-infected Tetrastigma hosts and may have applications in Rafflesia propagation to meet conservation goals.

Microbiota and Ocular Diseases

Recent advances have identified significant associations between the composition and function of the gut microbiota and various disorders in organ systems other than the digestive tract. Utilizing next-generation sequencing and multiomics approaches, the microbial community that possibly impacts ocular disease has been identified. This review provides an overview of the literature on approaches to microbiota analysis and the roles of commensal microbes in ophthalmic diseases, including autoimmune uveitis, age-related macular degeneration, glaucoma, and other ocular disorders. In addition, this review discusses the hypothesis of the "gut-eye axis" and evaluates the therapeutic potential of targeting commensal microbiota to alleviate ocular inflammation.

Unravelling the Anticancer Mechanisms of Traditional Herbal Medicines with Metabolomics

Metabolite profiling of cancer cells presents many opportunities for anticancer drug discovery. The Chinese, Indian, and African flora, in particular, offers a diverse source of anticancer therapeutics as documented in traditional folklores. In-depth scientific information relating to mechanisms of action, quality control, and safety profile will promote their extensive usage in cancer therapy. Metabolomics may be a more holistic strategy to gain valuable insights into the anticancer mechanisms of action of plants but this has remained largely unexplored. This review, therefore, presents the available metabolomics studies on the anticancer effects of herbal medicines commonly used in Africa and Asia. In addition, we present some scientifically understudied ‘candidate plants’ for cancer metabolomics studies and highlight the relevance of metabolomics in addressing other challenges facing the drug development of anticancer herbs. Finally, we discussed the challenges of using metabolomics to uncover the underlying mechanisms of potential anticancer herbs and the progress made in this regard.

Review of the recent developments in metabolomics-based phytochemical research

Phytochemicals are important bioactive components present in natural products. Although the health benefits of many food products are well-known and accepted as a common knowledge, the identity of the main bioactive molecules and the mechanism by which they interact in the body of human are often unknown. It was only in the last 30 years when the field of metabolomics had matured that the identification of such molecules with bioactivity has been made possible through the development of instruments to separate and computational techniques to characterize complex samples. This in turn has enabled in vitro studies to quantify the biological activity of the respective phytochemical either in mice models or in humans. In this review, the importance of key dietary phytochemicals such as phenolic acids, flavonoids, carotenoids, resveratrol, curcumin, and capsaicinoids are discussed together with their potential functions for human health. Untargeted metabolomics, in particular, liquid chromatography mass spectrometry, is the most used method to isolate, identify and profile bioactive compounds in the study of phytochemicals in foods. The application of metabolomics in drug discovery is a common practice nowadays and has boosted the drug and/or supplement manufacturing sector.HighlightsPhytochemicals are beneficial compounds for human healthPhytochemicals are plant-based bioactive and obtainable from natural productsUntargeted metabolomics has boosted the discovery of phytochemicals from foodTargeted metabolomics is key in the authentication and screening of phytochemicalsMetabolomics of phytochemicals is reshaping the road to drug and supplement manufacture.

Workflow to Investigate Subtle Differences in Wine Volatile Metabolome Induced by Different Root Systems and Irrigation Regimes

To allow for a broad survey of subtle metabolic shifts in wine caused by rootstock and irrigation, an integrated metabolomics-based workflow followed by quantitation was developed. This workflow was particularly useful when applied to a poorly studied red grape variety cv. Chambourcin. Allowing volatile metabolites that otherwise may have been missed with a targeted analysis to be included, this approach allowed deeper modeling of treatment differences which then could be used to identify important compounds. Wines produced on a per vine basis, over two years, were analyzed using SPME-GC-MS/MS. From the 382 and 221 features that differed significantly among rootstocks in 2017 and 2018, respectively, we tentatively identified 94 compounds by library search and retention index, with 22 confirmed and quantified using authentic standards. Own-rooted Chambourcin differed from other root systems for multiple volatile compounds with fewer differences among grafted vines. For example, the average concentration of β-Damascenone present in own-rooted vines (9.49 µg/L) was significantly lower in other rootstocks (8.59 µg/L), whereas mean Linalool was significantly higher in 1103P rootstock compared to own-rooted. β-Damascenone was higher in regulated deficit irrigation (RDI) than other treatments. The approach outlined not only was shown to be useful for scientific investigation, but also in creating a protocol for analysis that would ensure differences of interest to the industry are not missed.

Organic cultivation practices enhanced antioxidant activities and secondary metabolites in giant granadilla (Passiflora quadrangularis L.)

Passiflora quadrangularis L. belongs to the family Passifloraceae which bears larger fruit with edible juicy mesocarp and pulp known as a good source of phytochemicals. Cultivation and plant management practices are known to influence the phytochemical compositions of agricultural produce. This study aimed to examine the influence of the cultivation practices on the antioxidant activities and secondary metabolites of the organically and conventionally grown P. quadrangularis. Findings revealed organically treated P. quadrangularis plants showed enhancement in their antioxidant properties and secondary metabolites profiles. Among the plant parts, leaves of P. quadrangularis grown organically possessed higher antioxidant activities compared to the conventional in all assays evaluated. The antioxidant activities in the edible parts of the P. quadrangularis fruit have also been enhanced through organic cultivation with significantly higher total phenolic content and DPPH in mesocarp, and the pulp showed higher total flavonoid content, DPPH and FRAP. This observation is supported by a higher level of vitamins and secondary metabolites in the samples. The secondary metabolites profile showed mesocarps were phenolic rich, the pulps were flavonoids rich while leaves showed good composition of phenolics, flavonoids and terpenoids with outstanding antioxidant activities. The common secondary metabolites for organically produced P. quadrangularis in different plant parts include 2-isopropyl-3-methoxycinnamic acid (mesocarp and pulp), myricetin isomers (pulp and leaves), and malvidin-3-O-arabinoside isomers (pulp and leaves). This study confirmed that organic cultivated P. quadrangularis possessed higher antioxidant activities contributed by its vitamins and secondary metabolites.

Metabolomic Profile and Cytotoxic Activity of Cissus incisa Leaves Extracts

Cissus incisa leaves have been traditionally used in Mexican traditional medicine to treat certain cancerous illness. This study explored the metabolomic profile of this species using untargeted technique. Likewise, it determined the cytotoxic activity and interpreted all data by computational tools. The metabolomic profile was developed through UHPLC-QTOF-MS/MS for dereplication purposes. MetaboAnalyst database was used in metabolic pathway analysis and the network topological analysis. Hexane, chloroform/methanol, and aqueous extracts were evaluated on HepG2, Hep3B, HeLa, PC3, A549, and MCF7 cancer cell lines and IHH immortalized hepatic cells, using Cell Titer proliferation assay kit. Hexane extract was the most active against Hep3B (IC50 = 27 ± 3 μg/mL), while CHCl3/MeOH extract was the most selective (SI = 2.77) on the same cell line. A Principal Component Analysis (PCA) showed similar profiles between the extracts, while a Venn diagram revealed 80 coincident metabolites between the bioactive extracts. The sesquiterpenoid and triterpenoid biosynthesis pathway was the most significant identified. The Network Pharmacology (NP) approach revealed several targets for presqualene diphosphate, phytol, stearic acid, δ-tocopherol, ursolic acid and γ-linolenic acid, involved in cellular processes such as apoptosis. This work highlights the integration of untargeted metabolomic profile and cytotoxic activity to explore plant extracts, and the NP approach to interpreting the experimental results.

1H nuclear magnetic resonance-based metabolite profiling of guava leaf extract: an attempt to develop a prototype for standardization of plant extracts

Background

Herbal medicines are fast gaining popularity. However, their acceptability by modern practitioners is low which is often due to lack of standardization. Several approaches towards standardization of herbals have been employed. The current study attempted to recognize key peaks from ¹H NMR spectra which together would comprise of a spectral fingerprint relating to efficacy of Psidium guajava (guava) leaf extract as an antidiarrhoeal when a number of unidentified active principles are involved.

Methods

Ninety samples of guava leaves were collected from three locations over three seasons. Hydroalcoholic (water and ethanol, 50:50) extracts of these samples were prepared and their ¹H NMR spectra were acquired. Spectra were also obtained for quercetin, ferulic acid and gallic acid as standards. Eight bioassays reflecting different stages of diarrhoeal pathogenesis were undertaken and based on pre-decided cut-offs, the extracts were classified as ‘good’ or ‘poor’ extracts. The bioactivity data was then correlated with the ¹H NMR profiles using Regression or Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA).

Results

OPLS-DA showed seasonal and regional segregation of extracts. Significant models were established for seven bioassays, namely those for anti-bacterial activity against Shigella flexneri and Vibrio cholerae, adherence of E. coli, invasion of E. coli and S. flexneri and production and binding of toxin produced by V. cholerae. It was observed that none of the extracts were good or bad across all the bioassays. The spectral analysis showed multiple peaks correlating with a particular activity. Based on NMR and LC-MS/MS, it was noted that the extracts contained quercetin, ferulic acid and gallic acid. However, they did not correlate with the peaks that segregated extracts with good and poor activity.

Conclusions

The current study identified key peaks in ¹H NMR spectra contributing to the anti-diarrhoeal activity of guava leaf extracts. The approach of using spectral fingerprinting employed in the present study can thus be used as a prototype towards standardization of plant extracts with respect to efficacy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-021-03221-5.

Challenges and Perspective in Integrated Multi-Omics in Gut Microbiota Studies

The advent of omic technology has made it possible to identify viable but unculturable micro-organisms in the gut. Therefore, application of multi-omic technologies in gut microbiome studies has become invaluable for unveiling a comprehensive interaction between these commensals in health and disease. Meanwhile, despite the successful identification of many microbial and host-microbial cometabolites that have been reported so far, it remains difficult to clearly identify the origin and function of some proteins and metabolites that are detected in gut samples. However, the application of single omic techniques for studying the gut microbiome comes with its own challenges which may be overcome if a number of different omics techniques are combined. In this review, we discuss our current knowledge about multi-omic techniques, their challenges and future perspective in this field of gut microbiome studies.

Application of UPLC-QTOF-MS Based Untargeted Metabolomics in Identification of Metabolites Induced in Pathogen-Infected Rice

Metabolomics is a useful tool for comparing metabolite changes in plants. Because of its high sensitivity, metabolomics combined with high-resolution mass spectrometry (HR-MS) is the most widely accepted metabolomics tools. In this study, we compared the metabolites of pathogen-infected rice (Oryza sativa) with control rice using an untargeted metabolomics approach. We profiled the mass features of two rice groups using a liquid chromatography quadrupole time-of-flight mass spectrometry (QTOF-MS) system. Twelve of the most differentially induced metabolites in infected rice were selected through multivariate data analysis and identified through a mass spectral database search. The role of these compounds in metabolic pathways was finally investigated using pathway analysis. Our study showed that the most frequently induced secondary metabolites are prostanoids, a subclass of eicosanoids, which are associated with plant defense metabolism against pathogen infection. Herein, we propose a new untargeted metabolomics approach for understanding plant defense system at the metabolic level.

Metabolite Profiling of Alangium salviifolium Bark Using Advanced LC/MS and GC/Q-TOFTechnology

There is an urge for traditional herbal remedies as an alternative to modern medicine in treating several ailments. Alangium salviifolium is one such plant, used traditionally to treat several diseases. In several reports, there are findings related to the use of this plant extract that demonstrate its therapeutic value. However, very few attempts have been made to identify the extensive metabolite composition of this plant. Here, we performed metabolite profiling and identification from the bark of A. salviifolium by extracting the sample in organic and aqueous solvents. The organic and aqueous extracts were fraction-collected using the Agilent 1260 Analytical Scale Fraction Collection System. Each of the fractions was analyzed on Liquid Chromatogaphy/Quadrupole Time-of-Flight LC/Q-TOF and Gas Chromatography/Quadrupole Time-of-Flight GC/instruments. The Liquid Chromatography/Mass Spectrometry (LC/MS) analyses were performed using Hydrophilic Ineraction Liquid Chromatography (HILIC), as well as reversed-phase chromatography using three separate, orthogonal reverse phase columns. Samples were analyzed using an Agilent Jet Stream (AJS) source in both positive and negative ionization modes. The compounds found were flavonoids, fatty acids, sugars, and terpenes. Eighty-one secondary metabolites were identified as having therapeutic potential. The data produced was against the METLIN database using accurate mass and/or MS/MS library matching. Compounds from Alangium that could not be identified by database or library matching were subsequently searched against the ChemSpider) database of over 30 million structures using MSMS data and Agilent MSC software.In order to identify compounds generated by GC/MS, the data were searched against the AgilentFiehn GCMS Metabolomics Library as well as the Wiley/NIST libraries.

Integration of mass spectral fingerprinting analysis with precursor ion (MS1) quantification for the characterisation of botanical extracts: application to extracts of Centella asiatica (L.) Urban

INTRODUCTION

The phytochemical composition of plant material governs the bioactivity and potential health benefits as well as the outcomes and reproducibility of laboratory studies and clinical trials.

OBJECTIVE

The objective of this work was to develop an efficient method for the in-depth characterisation of plant extracts and quantification of marker compounds that can be potentially used for subsequent product integrity studies. Centella asiatica (L.) Urb., an Ayurvedic herb with potential applications in enhancing mental health and cognitive function, was used as a case study.

METHODS

A quadrupole time-of-flight analyser in conjunction with an optimised high-performance liquid chromatography (HPLC) separation was used for in-depth untargeted fingerprinting and post-acquisition precursor ion quantification to determine levels of distinct phytochemicals in various C. asiatica extracts.

RESULTS

We demonstrate the utility of this workflow for the characterisation of extracts of C. asiatica. This integrated workflow allowed the identification or tentative identification of 117 compounds, chemically interconnected based on Tanimoto chemical similarity, and the accurate quantification of 24 phytochemicals commonly found in C. asiatica extracts.

CONCLUSION

We report a phytochemical analysis method combining liquid chromatography, high resolution mass spectral data acquisition, and post-acquisition interrogation that allows chemical fingerprints of botanicals to be obtained in conjunction with accurate quantification of distinct phytochemicals. The variability in the composition of specialised metabolites across different C. asiatica accessions was substantial, demonstrating that detailed characterisation of plant extracts is a prerequisite for reproducible use in laboratory studies, clinical trials and safe consumption. The methodological approach is generally applicable to other botanical products.

Identification of metabolic biomarkers to predict treatment outcome and disease progression in multiple myeloma

The relationship between metabolites and multiple myeloma (MM) is becoming a research focus in the field. In this study, we performed metabolic profiling of multiple myeloma and identified potential metabolites associated with clinical characteristics, therapeutic efficacy, and prognosis of the disease. Fifty-five patients with newly-diagnosed multiple myeloma and thirty-seven healthy controls from August 2016 to October 2017 were randomly collected. The serum metabolic profiling was investigated by gas chromatography-mass spectrometry (GC-MS) technique and underwent statistical analysis. Twenty-seven metabolites were found to be significantly different between healthy controls and multiple myeloma patients. Eleven metabolites were significantly elevated, while sixteen metabolites were decreased in the multiple myeloma population. Metabolic changes were also observed in patients with renal impairment and bone destruction. Levels of urea were significantly decreased after treatment while levels of hypotaurine showed significant increase in the good-effect group (P<0.05), but not in the no-good-effect group (P>0.05). In multivariate statistical analyses, high cysteine and high hypotaurine are independent risk factors for poor treatment outcome. After adjustment for critical clinical characteristics, patients with high levels of glycolic acid and xylitol were found to be less likely to experience disease progression. Multiple myeloma demonstrates different metabolic characteristics compared with the healthy population. Among multiple myeloma patients, renal impairment and bone destruction showed additional metabolic characteristics. Cysteine and hypotaurine have value in predicting the treatment outcome, while glycolic acid and xylitol may be important prognostic factors for multiple myeloma.

A chemometric assessment of essential oil variation of three Salvia species indigenous to South Africa

Indigenous Salvia species from southern Africa are popular traditional medicines for the treatment of a variety of conditions. They produce fragrant volatiles that can be isolated as essential oils. Some of these volatile organic compounds may play a role in the biological activities of the extracts. Three indigenous Salvia species, Salvia africana-lutea, S. lanceolata and S. chamelaeagnea, were selected for this study as they are commonly used in traditional medicine in South Africa, and the essential oils from these species have potential for commercialisation. Although some studies have described the essential oil compositions and some biological activities, only single composite samples were used. The aim of this study was to investigate the intra- and interspecies variation of the essential oils, sampled over a wide geographical area and using a representative sample size, to encourage commercialisation of the essential oil. Essential oils were isolated from individual plants using conventional hydrodistillation of the aerial parts, harvested from several localities. Gas chromatography coupled simultaneously to mass spectrometry/flame ionisation detection (GC-MS/FID) was used to identify and quantify the volatile constituents. The essential oils of S. africana-lutea consisted mainly of terpinene-4-ol + β-caryophyllene (1.4 - 29.0%), T-cadinol (1.2 - 20.0%), α-eudesmol (trace - 23.0%) and β-eudesmol (trace - 26.0%), those of S. lanceolata comprised mainly terpinene-4-ol + β-caryophyllene (4.3 - 31.0%), α-humulene (2.3 - 15.0%), bicyclogermacrene (trace - 37.0%) and spathulenol (trace - 25.0%), while the essential oils of S. chamelaeagnea were characterised by δ-3-carene (trace - 18.0%), limonene (1.6 - 36.0%), viridiflorol (9.8 - 61.0%) and 1,8-cineole (not detected - 11.0%). The compounds identified in the essential oils of the three selected Salvia species have been identified in other Salvia essential oils. To add to the novelty of this study, the superior resolving power of two-dimensional gas chromatography was demonstrated through analysis of selected essential oils. Many additional compounds were identified, and previously co-eluting compounds were clearly separated. Chemometric modelling of the GC-MS data using SIMCA P+ 14 software allowed distinct clustering patterns to be discerned. The unsupervised principal component analysis model revealed separate clusters for the three species, confirming substantial chemical differences between their essential oils. Quantitative, rather than qualitative differences were evident when individual essential oil samples representing the same species, were compared. For each species, two chemically distinct groups were observed and unique marker compounds could be identified. This study has contributed detailed information on the major and minor volatile compounds present in the essential oils of the three Salvia species investigated.

Understanding glycaemic control and current approaches for screening antidiabetic natural products from evidence-based medicinal plants

Type 2 Diabetes Mellitus has reached epidemic proportions as a result of over-nutrition and increasingly sedentary lifestyles. Current therapies, although effective, are not without limitations. These limitations, the alarming increase in the prevalence of diabetes, and the soaring cost of managing diabetes and its complications underscores an urgent need for safer, more efficient and affordable alternative treatments. Over 1200 plant species are reported in ethnomedicine for treating diabetes and these represents an important and promising source for the identification of novel antidiabetic compounds. Evaluating medicinal plants for desirable bioactivity goes hand-in-hand with methods in analytical biochemistry for separating and identifying lead compounds. This review aims to provide a comprehensive summary of current methods used in antidiabetic plant research to form a useful resource for researchers beginning in the field. The review summarises the current understanding of blood glucose regulation and the general mechanisms of action of current antidiabetic medications, and combines knowledge on common experimental approaches for screening plant extracts for antidiabetic activity and currently available analytical methods and technologies for the separation and identification of bioactive natural products. Common in vivo animal models, in vitro models, in silico methods and biochemical assays used for testing the antidiabetic effects of plants are discussed with a particular emphasis on in vitro methods such as cell-based bioassays for screening insulin secretagogues and insulinomimetics. Enzyme inhibition assays and molecular docking are also highlighted. The role of metabolomics, metabolite profiling, and dereplication of data for the high-throughput discovery of novel antidiabetic agents is reviewed. Finally, this review also summarises sample preparation techniques such as liquid-liquid extraction, solid phase extraction, and supercritical fluid extraction, and the critical function of nuclear magnetic resonance and high resolution liquid chromatography-mass spectrometry for the dereplication, putative identification and structure elucidation of natural compounds from evidence-based medicinal plants.

Identification of Constituents Affecting the Secretion of Pro-Inflammatory Cytokines in LPS-Induced U937 Cells by UHPLC-HRMS-Based Metabolic Profiling of the Traditional Chinese Medicine Formulation Huangqi Jianzhong Tang

Within non-communicable diseases, chronic inflammatory conditions represent one of the biggest challenges for modern medicine. Traditional Chinese Medicine (TCM) has been practiced over centuries and has accumulated tremendous empirical knowledge on the treatment of such diseases. Huangqi Jianzhong Tang (HQJZT) is a famous TCM herbal formula composed of Radix Astragali, Ramulus Cinnamomi, Radix et Rhizoma Glycyrrhizae Praeparata cum Melle, Radix Paeoniae Alba, Rhizoma Zingiberis Recens, Fructus Jujubae and Saccharum Granorum (maltose), which has been used for the treatment of various chronic inflammatory gastrointestinal diseases. However, there is insufficient knowledge about its active constituents and the mechanisms responsible for its effects. The present study aimed at identifying constituents contributing to the bioactivity of HQJZT by combining in vitro cytokine production assays and LC-MS metabolomics techniques. From the HQJZT decoction as well as from its single herbal components, extracts of different polarities were prepared. Phytochemical composition of the extracts was analyzed by means of UPLC-QTOF-MS/MS. The inhibitory effects of the extracts on TNF-α, IL-1β and IFN-γ production were studied in U937 cells. Phytochemical and pharmacological bioactivity data were correlated by orthogonal projection to latent structures discriminant analysis (OPLS-DA) in order to identify those HQJZT constituents which may be relevant for the observed pharmacological activities. The investigations resulted in the identification of 16 HQJZT constituents, which are likely to contribute to the activities observed in U937 cells. Seven of them, namely calycosin, formononetin, astragaloside I, liquiritigenin, 18β-glycyrrhetinic acid, paeoniflorin and albiflorin were unambiguously identified. The predicted results were verified by testing these compounds in the same pharmacological assays as for the extracts. In conclusion, the anti-inflammatory activity of HQJZT could be substantiated by in vitro pharmacological screening, and the predicted activities of the OPLS-DA hits could be partially verified. Moreover, the benefits and limitations of MVDA for prediction pharmacologically active compounds contributing to the activity of a TCM mixture could be detected.

Novel applications of mass spectrometry-based metabolomics in herbal medicines and its active ingredients: Current evidence

Current evidence shows that herbal medicines could be beneficial for the treatment of various diseases. However, the complexities present in chemical compositions of herbal medicines are currently an obstacle for the progression of herbal medicines, which involve unclear bioactive compounds, mechanisms of action, undetermined targets for therapy, non-specific features for drug metabolism, etc. To overcome those issues, metabolomics can be a great to improve and understand herbal medicines from the small-molecule metabolism level. Metabolomics could solve scientific difficulties with herbal medicines from a metabolic perspective, and promote drug discovery and development. In recent years, mass spectrometry-based metabolomics was widely applied for the analysis of herbal constituents in vivo and in vitro. In this review, we highlight the value of mass spectrometry-based metabolomics and metabolism to address the complexity of herbal medicines in systems pharmacology, and to enhance their biomedical value in biomedicine, to shed light on the aid that mass spectrometry-based metabolomics can offer to the investigation of its active ingredients, especially, to link phytochemical analysis with the assessment of pharmacological effect and therapeutic potential. © 2019 Wiley Periodicals, Inc. Mass Spec Rev.

Understanding Camellia sinensis using Omics Technologies along with Endophytic Bacteria and Environmental Roles on Metabolism: A Review

Camellia sinensis is the most consumed beverage worldwide. It contains a wide variety of secondary metabolites, such as alkaloids, saponins, tannins, catechins, and polyphenols, generated through a condensation reaction of cinnamic acid with three malonyl-CoA groups. In addition to the metabolic processes occurring within this plant, there are also some plant-associated bacterial endophytes. These bacteria reside in the living tissues of the host plants without causing any harmful effect to them, thereby stimulating secondary metabolite production with a diverse range of biological effects. Omics technologies reveal understanding of the biological phenomena of transcriptomics, proteomics, and metabolomics. In this sense, the present review aims to provide a comprehensive review of various methods used to identify distinct plant compounds, namely transcriptomic, proteomic, and metabolomic analysis. The role of endophytic bacteria in C. sinensis metabolism, and C. sinensis antioxidant and antimicrobial effects, are also carefully highlighted.

Contribution of Untargeted Metabolomics for Future Assessment of Biotech Crops

The nutritional value and safety of food crops are ultimately determined by their chemical composition. Recent developments in the field of metabolomics have made it possible to characterize the metabolic profile of crops in a comprehensive and high-throughput manner. Here, we propose that state-of-the-art untargeted metabolomics technology should be leveraged for safety assessment of new crop products. We suggest generally applicable experimental design principles that facilitate the efficient and rigorous identification of both intended and unintended metabolic alterations associated with a newly engineered trait. Our proposition could contribute to increased transparency of the safety assessment process for new biotech crops.

Integrated analytical assets aid botanical authenticity and adulteration management

This article reviews and develops a perspective for the meaning of authenticity in the context of quality assessment of botanical materials and the challenges associated with discerning adulterations vs. contaminations vs. impurities. Authentic botanicals are by definition non-adulterated, a mutually exclusive relationship that is confirmed through the application of a multilayered set of analytical methods designed to validate the (chemo)taxonomic identity of a botanical and certify that it is devoid of any adulteration. In practice, the ever-increasing sophistication in the process of intentional adulteration, as well as the growing number of botanicals entering the market, altogether necessitate a constant adaptation and reinforcement of authentication methods with new approaches, especially new technologies. This article summarizes the set of analytical methods - classical and contemporary - that can be employed in the authentication of botanicals. Particular emphasis is placed on the application of untargeted metabolomics and chemometrics. An NMR-based untargeted metabolomic model is proposed as a rapid, systematic, and complementary screening for the discrimination of authentic vs. potentially adulterated botanicals. Such analytical model can help advance the evaluation of botanical integrity in natural product research.

Rapid discrimination of different Apiaceae species based on HPTLC fingerprints and targeted flavonoids determination using multivariate image analysis

INTRODUCTION

Species of Apiaceae are used in folk medicine as spices and in officinal medicinal preparations of drugs. They are an excellent source of phenolics exhibiting antioxidant activity, which are of great benefit to human health. Discrimination among Apiaceae medicinal herbs remains an intricate challenge due to their morphological similarity.

OBJECTIVE

In this study, a combined "untargeted" and "targeted" approach to investigate different Apiaceae plants species was proposed by using the merging of high-performance thin layer chromatography (HPTLC)-image analysis and pattern recognition methods which were used for fingerprinting and classification of 42 different Apiaceae samples collected from Egypt.

METHODOLOGY

Software for image processing was applied for fingerprinting and data acquisition. HPTLC fingerprint assisted by principal component analysis (PCA) and hierarchical cluster analysis (HCA)-heat maps resulted in a reliable untargeted approach for discrimination and classification of different samples. The "targeted" approach was performed by developing and validating an HPTLC method allowing the quantification of eight flavonoids.

RESULTS

The combination of quantitative data with PCA and HCA-heat-maps allowed the different samples to be discriminated from each other.

CONCLUSION

The use of chemometrics tools for evaluation of fingerprints reduced expense and analysis time. The proposed method can be adopted for routine discrimination and evaluation of the phytochemical variability in different Apiaceae species extracts.

Metabolomic analysis of the effects of cadmium and copper treatment in Oryza sativa L. using untargeted liquid chromatography coupled to high resolution mass spectrometry and all-ion fragmentation

While the knowledge of plant metabolomes has increased in the last few years, their response to the presence of toxicants is still poorly understood. Here, we analyse the metabolomic changes in Japanese rice (Oryza sativa var. Japonica) upon exposure to heavy metals (Cd(ii) and Cu(ii)) in concentrations from 10 to 1000 μM. After harvesting, rice metabolites were extracted from aerial parts of the plants and analysed by HPLC (HILIC TSK gel amide-80 column) coupled to a mass spectrometer quadrupole-Orbitrap (Q-Exactive). Full scan and all ion fragmentation (AIF) mass spectrometry modes were used during the analysis. The proposed untargeted metabolomics data analysis strategy is based on the application of the multivariate curve resolution alternating least squares (MCR-ALS) method for feature detection, allowing the simultaneous resolution of pure chromatographic profiles and mass spectra of all metabolites present in the analysed rice extracts. All-ion fragmentation data were used to confirm the identification of MCR-ALS resolved metabolites. A total of 112 metabolites were detected, and 97 of them were subsequently identified and confirmed. Pathway analysis of the observed metabolic changes suggested an underlying similarity of the responses of the plant to Cd(ii) and Cu(ii), although the former treatment appeared to be the more severe of the two. In both cases, secondary metabolism and amino acid-, purine-, carbon- and glycerolipid-metabolism pathways were affected, in a pattern consistent with reduction in plant growth and/or photosynthetic capacity and with induction of defence mechanisms to reduce cell damage.

High-performance liquid chromatography coupled with tandem mass spectrometry technology in the analysis of Chinese Medicine Formulas: A bibliometric analysis (1997-2015)

There is a recognized challenge in analyzing traditional Chinese medicine formulas because of their complex chemical compositions. The application of modern analytical techniques such as high-performance liquid chromatography coupled with a tandem mass spectrometry has improved the characterization of various compounds from traditional Chinese medicine formulas significantly. This study aims to conduct a bibliometric analysis to recognize the overall trend of high-performance liquid chromatography coupled with tandem mass spectrometry approaches in the analysis of traditional Chinese medicine formulas, its significance and possible underlying interactions between individual herbs in these formulas. Electronic databases were searched systematically, and the identified studies were collected and analyzed using Microsoft Access 2010, Graph Pad 5.0 software and Ucinet software package. 338 publications between 1997 and 2015 were identified, and analyzed in terms of annual growth and accumulated publications, top journals, forms of traditional Chinese medicine preparations and highly studied formulas and single herbs, as well as social network analysis of single herbs. There is a significant increase trend in using high-performance liquid chromatography coupled with tandem mass spectrometry related techniques in analysis of commonly used forms of traditional Chinese medicine formulas in the last 3 years. Stringent quality control is of great significance for the modernization and globalization of traditional Chinese medicine, and this bibliometric analysis provided the first and comprehensive summary within this field.

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Terroir refers to the combination of environmental factors that affect the characteristics of crops such as grapevine (Vitis vinifera) according to particular habitats and management practices. This article shows how certain terroir signatures can be detected in the berry metabolome and transcriptome of the grapevine cultivar Corvina using multivariate statistical analysis. The method first requires an appropriate sampling plan. In this case study, a specific clone of the Corvina cultivar was selected to minimize genetic differences, and samples were collected from seven vineyards representing three different macro-zones during three different growing seasons. An untargeted LC-MS metabolomics approach is recommended due to its high sensitivity, accompanied by efficient data processing using MZmine software and a metabolite identification strategy based on fragmentation tree analysis. Comprehensive transcriptome analysis can be achieved using microarrays containing probes covering ~99% of all predicted grapevine genes, allowing the simultaneous analysis of all differentially expressed genes in the context of different terroirs. Finally, multivariate data analysis based on projection methods can be used to overcome the strong vintage-specific effect, allowing the metabolomics and transcriptomics data to be integrated and analyzed in detail to identify informative correlations.

The metabolomic signature of hematologic malignancies

The ongoing accumulation of knowledge raises hopes that understanding tumor metabolism will provide new ways for predicting, diagnosing, and even treating cancers. Some metabolic biomarkers are at present routinely utilized to diagnose cancer and metabolic alterations of tumors are being confirmed as therapeutic targets. The growing utilization of metabolomics in clinical research may rapidly turn it into one of the most potent instruments used to detect and fight tumor. In fact, while the current state and trends of high throughput metabolomics profiling focus on the purpose of discovering biomarkers and hunting for metabolic mechanism, a prospective direction, namely reprogramming metabolomics, highlights the way to use metabolomics approach for the aim of treatment of disease by way of reconstruction of disturbed metabolic pathways. In this review, we present an ample summary of the current clinical appliances of metabolomics in hematological malignancies.

A comprehensive strategy to detect the fraudulent adulteration of herbs: The oregano approach

•

Two tier strategy proposed to detect oregano fraud.

•

FT-IR screening and HR-LC-MS confirmatory methods developed.

•

Unique biomarkers discovered in adulterants by HR-LC-MS.

•

Chemometric calibration models generated.

•

24% of oregano samples tested in UK/Ireland were found to be adulterated.

Fraud in the global food supply chain is becoming increasingly common due to the huge profits associated with this type of criminal activity. Food commodities and ingredients that are expensive and are part of complex supply chains are particularly vulnerable. Both herbs and spices fit these criteria perfectly and yet strategies to detect fraudulent adulteration are still far from robust. An FT-IR screening method coupled to data analysis using chemometrics and a second method using LC-HRMS were developed, with the latter detecting commonly used adulterants by biomarker identification. The two tier testing strategy was applied to 78 samples obtained from a variety of retail and on-line sources. There was 100% agreement between the two tests that over 24% of all samples tested had some form of adulterants present. The innovative strategy devised could potentially be used for testing the global supply chains for fraud in many different forms of herbs.

New frontiers in pharmaceutical analysis: A metabolomic approach to check batch compliance of complex products based on natural substances

Natural substances, particularly medicinal plants and their extracts, are still today intended as source for new Active Pharmaceutical Ingredients (APIs). Alternatively they can be validly employed to prepare medicines, food supplements or medical devices. The most adopted analytical approach used to verify quality of natural substances like medicinal plants is based still today on the traditional quantitative determination of marker compounds and/or active ingredients, besides the acquisition of a fingerprint by TLC, NIR, HPLC, GC. Here a new analytical approach based on untargeted metabolomic fingerprinting by means of Mass Spectrometry (MS) to verify the quality of grinTuss adulti syrup, a complex products based on medicinal plants, is proposed. Recently, untargeted metabolomic has been successfully applied to assess quality of natural substances, plant extracts, as well as corresponding formulated products, being the complexity a resource but not necessarily a limit. The untargeted metabolomic fingerprinting includes the monitoring of the main constituents, giving weighted relevance to the most abundant ones, but also considering minor components, that might be notable in view of an integrated - often synergistic - effect on the biological system. Two different years of production were investigated. The collected samples were analyzed by Flow Injection ElectroSpray Ionization Mass Spectrometry Analysis (FIA-ESI-MS) and a suitable data processing procedure was developed to transform the MS spectra into robust fingerprints. Multivariate Statistical Process Control (MSPC) was applied in order to obtain multivariate control charts that were validated to prove the effectiveness of the proposed method.

Botanical Integrity: Part 2: Traditional and Modern Analytical Approaches

The concept of botanical integrity (BI), introduced previously in HerbalGram issue 106, involves the determination of identity, homogeneity, bioactivity, and safety of plant-derived materials designated for human consumption.1 It goes beyond previously established quality control principles. The inaugural article in this series described the three major domains of expertise that are required to assess BI (as noted in Figure 1): botanical examination (botany), phytochemical analysis (chemistry), and biological efficacy and safety assessments (bioactivity, which encompasses the fields of pharmacology and toxicology).

Functional metabolomics: from biomarker discovery to metabolome reprogramming

Metabolomics is emerging as a powerful tool for studying metabolic processes, identifying crucial biomarkers responsible for metabolic characteristics and revealing metabolic mechanisms, which construct the content of discovery metabolomics. The crucial biomarkers can be used to reprogram a metabolome, leading to an aimed metabolic strategy to cope with alteration of internal and external environments, naming reprogramming metabolomics here. The striking feature on the similarity of the basic metabolic pathways and components among vastly different species makes the reprogramming metabolomics possible when the engineered metabolites play biological roles in cellular activity as a substrate of enzymes and a regulator to other molecules including proteins. The reprogramming metabolomics approach can be used to clarify metabolic mechanisms of responding to changed internal and external environmental factors and to establish a framework to develop targeted tools for dealing with the changes such as controlling and/or preventing infection with pathogens and enhancing host immunity against pathogens. This review introduces the current state and trends of discovery metabolomics and reprogramming metabolomics and highlights the importance of reprogramming metabolomics.

Correction of precursor and product ion relative abundances in order to standardize CID spectra and improve Ecom50 accuracy for non-targeted metabolomics

Quantitative biases in the abundance of precursor and product ions due to mass discrimination in RF-only ion guides results in inaccurate collision induced dissociation (CID) spectra. We evaluated the effects of collision cell RF voltage and collision energy on CID spectra using ten singly protonated compounds (46-854 Da) in an orthogonal acceleration time-of-flight mass spectrometer. The relative ion transfer efficiency, i.e. the relative amount of ions transferred through the ion guide at any particular RF voltage was shown to be dependent on the ion's m/z. We developed an algorithm to correct for the mass discriminating effects of RF voltage on CID spectra. The algorithm was tested for both precursor and product ions at multiple RF voltages and collision energies in order to ensure reliability. Our results suggest that compounds that generate major product ions with m/z values <150 have peak intensities that deviate substantially from their actual abundance. This has implications for small molecule metabolomics research, particularly for studies that rely on CID spectra matching methods for structure identification.