Chemical and genetic discrimination of commercial Guangchenpi (Citrus reticulata ‘Chachi’) by using UPLC-QTOF-MS/MS based metabolomics and DNA barcoding approaches

CRP (Citri Reticulatae Pericarpium), a famous traditional Chinese medicine, has also been extensively used in foods and condiments in dietary practice for centuries. According to the Chinese Pharmacopeia (2015 edition) it contains two subtypes, Guangchenpi (GCP) and Chenpi (CP). GCP exclusively originates from the pericarp of Citrus reticulata ‘Chachi’ cultivar and it''s generally believed that GCP has superior qualities compared with the other main cultivars (CP). In the present study, an integrated approach combining LC-QTOF MS-based untargeted metabolomics analysis and DNA barcoding molecular identification was conducted to study the genetic diversity and chemical differences between GCP and CP. A validated UPLC-QTOF MS metabolomics method was established to identify markers by using PCA and OPLS-DA models. 34 identified metabolites could be used as chemical markers to distinguish effectively between the two subtypes. Among them polymethoxyflavones (PMF) such as hexamethoxyflavone (nobiletin and natsudaidain), pentamethoxyflavone (tangeretin and sinensetin), and tetramethoxyflavone are the most influential markers. Support vector machines were employed to classify all the samples and these markers showed good prediction accuracy (100%). The results of DNA barcoding showed that the secondary structure of the ITS2 sequences were significantly different among GCP and other three cultivars. The study indicated the integrated method could be a powerful and reliable analytical tool for differentiating GCP from CP.

An integrated method, combining DNA barcoding with LC-MS metabolomics analysis, is a powerful and reliable way for differentiating Citrus reticulata ‘Chachi’ (GCP) from other Citrus cultivars.     

Phytochemistry by design: a case study of the chemical composition of Ocotea guianensis optimized extracts focused on untargeted metabolomics analysis

Untargeted metabolomics aim to provide a global chemical fingerprint of biological matrices. This research field can be used in phytochemical screenings for bioactive species or in the identification of species. Despite its importance in providing a global chemical profile, little research has focused on the optimization of the extraction methods, as each type of matrix requires a specific procedure. Therefore, we propose to evaluate the effect of different extraction features in an ultrasound-assisted extraction for the untargeted metabolomic study of an Ocotea species, a genus of great economical interest but little chemical exploitation. Method optimization was performed in a full factorial 2²3² design, evaluating the solvent composition, extraction temperature, sample particle size and sample : solvent ratio effects in the metabolomic response. The effect of these parameters on the quality of the untargeted metabolomic profiles was studied by analysis of the extraction yield as well as the chromatographic and spectrometric profiles. Most substances identified were glycosylated flavonoids and aporphinic alkaloids. The application of 70% ethanol enhanced the extraction of several specialized metabolites. Statistical analysis of extraction yield and chemical profiles indicates that high temperatures and low proportion between sample and extracting solvent reduce the quality and modify the chemical profile, both qualitatively and quantitatively. The use of 70% ethanol as the extracting solvent, 1 : 12 sample : solvent ratio, 40 °C as the extraction temperature and particle size of 0.595 mm were the optimized conditions to produce a comprehensive chemical profile for Ocotea guianensis.

Several extraction parameters were evaluated in order to establish their influence on the chemosystematic research of angiosperms.     

Use of metabolomics data analysis to identify fruit quality markers enhanced by the application of an aminopolysaccharide

Chitosan is a biostimulator that has a great effect either on plant physiology, productivity, or fruit quality. However, the metabolic mechanism regulated by chitosan still remains unknown. Untargeted metabolomics analysis, using LC-MS/MS mass spectrometry, was used to investigate fruit quality markers. Thus, this study was focused on the identification of untargeted metabolites of tomato fruits produced under the application of five doses of chitosan at different concentrations (0, 0.25, 0.50, 0.75, and 1 mg ml⁻¹) that was extracted from Parapenaeus longirostris shrimp shells. The identification was carried out using two ion modes (ESI⁻/ESI⁺), a web application “Metfamily” to analyze signals, and reference libraries. The analysis of data using partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) showed that chitosan application, especially 0.75 mg ml⁻¹, had a clear and remarkable effect regarding the number of metabolite families identified in both ion modes. This treatment has increased the relative abundance of many metabolites that belong to anthocyanins decorated with sugars, terpenoids, phenylpropanoids, acylsugars, glucosinolates, folates, galactolipids, fatty acids, and phospholipids. Thus, these results showed that chitosan application increased the quality of tomato fruits due to its involvement in the regulation of many metabolic pathways that might be responsible for enhancing the nutritional characteristics as well as the defense of fruits.

Combining bioinformatics tools with metabolomics showed that foliar spray with chitosan increased the level of valuable compounds in tomato fruits.     

Royal jelly fatty acids bioprofiling using TLC-MS and digital image analysis coupled with chemometrics and non-parametric regression for discovering efficient biomarkers against melanoma

A comprehensive approach of untargeted and targeted fatty acid bioprofiling of different royal jelly commercial and pharmaceutical products based on HPTLC-image analysis and melanoma cytotoxic activity together with chemometric analysis was applied in this study for discovering efficient biomarkers. Principal component analysis based on HPTLC-image analysis fingerprints of fatty acid loading plots were used to determine the chemical markers responsible for classification of royal jelly samples into fresh and lyophilized ones. These markers were identified using the HPTLC-MS technique as 8-hydroxyoctanoic acid, 3,10-dihydroxydecanoic acid, 10-hydroxy-2-decenoic acid, decanedioic acid and 10-hydroxydecanoic acid. These discriminating markers were quantified via the HPTLC-imaging technique for targeted profiling using two different methods: parametric and non-parametric regression. The non-parametric regression method exhibited superiority in terms of linearity, accuracy and precision. Biomarkers were determined from the 3D-loading plot of orthogonal projection to latent structures model based on the fatty acid quantitative data together with the melanoma cytotoxic activity data. 10-Hydroxy-2-decenoic acid showed the greatest reduction in melanoma cell viability followed by decanedioic acid then 8-hydroxyoctanoic acid. The present study is considered the first attempt to discriminate fresh and lyophilized royal jelly samples based on their holistic lipidomic profile to discover efficient fatty acid reducing melanoma cell viability.

Untargeted and targeted fatty acid bioprofiling of different royal jelly commercial and pharmaceutical products based on HPTLC-MS-image analysis and melanoma cytotoxic activity with chemometric analysis was applied to discover efficient biomarkers.     

Metabolome-based profiling of African baobab fruit (Adansonia digitata L.) using a multiplex approach of MS and NMR techniques in relation to its biological activity

Adansonia digitata L. also known as African baobab is one of the most important fruit-producing trees, widely distributed in the African continent. Baobab fruits are known to possess potential health benefits and nutritional value. This study aimed to holistically dissect the metabolome of A. digitata fruits using a novel comparative protocol using three different analytical platforms. Ultra high performance liquid chromatography coupled to high-resolution tandem mass spectrometry (UHPLC-HRMS/MS), and headspace solid-phase microextraction/gas chromatography coupled to mass spectrometry (HS-SPME/GC-MS) were respectively employed for phytonutrients and aroma profiling, whereas GC-MS post silylation provided an overview of nutrients i.e., sugars. UHPLC-HRMS/MS analysis allowed for the assignment of 77 metabolites, among which 50% are reported for the first time in the fruit. While GC-MS of silylated and aroma compounds led to the identification of 74 and 16 compounds, respectively. Finally, NMR-based metabolite fingerprinting permitted the quantification of the major metabolites for future standardization. In parallel, in vivo antidiabetic potential of the baobab fruit using a streptozotocin (STZ) induced diabetic rat model was assessed. Histopathological and immune-histochemical investigations revealed hepatoprotective and renoprotective effects of A. digitata fruit along with mitigation against diabetes complications. Moreover, the administration of A. digitata fruits (150 mg kg⁻¹) twice a week lowered fasting blood glucose levels.

Metabolites profiling of Adansonia digitata L. in relation to its biological activity.     

High-resolution lipidomics reveals dysregulation of lipid metabolism in respiratory syncytial virus pneumonia mice

Respiratory syncytial virus (RSV) is a leading viral pathogen responsible for lower respiratory tract infections, particularly in children under five years worldwide, often resulting in hospitalization. At present, the molecular-level interactions between RSV and its host and the underlying mechanisms of RSV-induced inflammation are poorly understood. Herein, we describe an untargeted high-resolution lipidomics platform based on UHPLC-Q-Exactive-MS to assess the lipid alterations of lung tissues and plasma from a mouse model of RSV pneumonia. Untargeted lipidomics using LC-MS with multivariate analysis was applied to describe the lipidomic profiling of the lung tissues and plasma in RSV pneumonia mice. Lipid identification was conducted via an in silico MS/MS LipidBlast library using the MS-DIAL software. We observed distinct compartmental lipid signatures in the mice lung tissues and plasma and significant lipid profile changes between the systematic and localized host responses to RSV. A total of 87 and 68 differential lipids were captured in the mice lung tissue and plasma, respectively, including phospholipids, sphingolipids, acylcarnitine, and fatty acids. Some of these lipids belong to pulmonary surfactants, illustrating that RSV pneumonia-induced aberrations of the pulmonary surfactant system may play a vital role in the etiology of respiratory inflammation. Our findings reveal that the host responses to RSV and various lipid metabolic pathways were linked to disease pathology. Furthermore, our findings could provide mechanistic insights into RSV pneumonia.

Respiratory syncytial virus (RSV) is a leading viral pathogen responsible for lower respiratory tract infections, particularly in children under five years worldwide, often resulting in hospitalization.     

UHPLC-MS metabolome based classification of umbelliferous fruit taxa: a prospect for phyto-equivalency of its different accessions and in response to roasting

Herbs of the Umbelliferae family are popular spices valued worldwide for their many nutritional and health benefits. Herein, five chief umbelliferous fruits viz., cumin, fennel, anise, coriander and caraway were assessed for its secondary metabolites diversity along with compositional changes incurring upon roasting as analyzed via ultra-high performance liquid chromatography coupled to photodiode array and electrospray ionization mass detectors UHPLC-qToF/MS. A total of 186 metabolites were annotated, according to metabolomics society guidelines, belonging mainly to flavonoids, fatty acids and phenolic acids. Multivariate models viz., PCA, HCA and OPLS-DA were further employed to assess fruits'' heterogeneity in an untargeted manner and determine mechanistic changes in bioactive makeup post roasting viz., glycosidic cleavage, lipid degradation and Maillard reaction. Finally, the fruits'' antioxidant activity showed decline upon roasting and in correlation with its total phenolic content. This study presents the first complete map of umbelliferous fruit metabolome, compositional differences and its roasting effect.

First metabolome map for umbelliferous fruits secondary metabolites profiling via UHPLC-QToF/MS with scrutinizing its metabolome compositional changes incurred upon roasting.     

Serum metabolomic alterations in multiple myeloma revealed by targeted and untargeted metabolomics approaches: a pilot study

Multiple myeloma (MM) is the second most prevalent hematological malignancy characterized by rapid proliferation of plasma cells, which leads to overproduction of antibodies. MM affects around 15% of all hemato-oncology cases across the world. The present study involves identification of metabolomic alterations in the serum of an MM cohort compared to healthy controls using both LC-MRM/MS based targeted and GC-MS based untargeted approaches. Several MM specific serum metabolomic signatures were observed in this study. A total of 54 metabolites were identified as being significantly altered in MM cohort, out of which, 26 metabolites were identified from LC-MRM/MS based targeted analysis, whereas 28 metabolites were identified from the GC-MS based untargeted analysis. Receiver operating characteristic (ROC) curve analysis demonstrated that six metabolites each from both the datasets can be projected as marker metabolites to discriminate MM subjects with higher specificity and sensitivity. Moreover, pathway analysis deciphered that several metabolic pathways were altered in MM including pyrimidine metabolism, purine metabolism, amino acid metabolism, nitrogen metabolism, sulfur metabolism, and the citrate cycle. Comprehensively, this study contributes valuable information regarding MM induced serum metabolite alterations and their pathways, which could offer further insights into this cancer.

This study presents the potential of serum metabolomics approach towards the segregation of multiple myeloma cohort from healthy controls.     

Metabolomics study of the anti-inflammatory effects of endogenous omega-3 polyunsaturated fatty acids

Low-grade inflammation is usually defined as the chronic production and a low-grade state of inflammatory factors, it often does not have symptoms, and has been associated with neurodegenerative disease, obesity, and diabetes. Omega-3 polyunsaturated fatty acids (n-3 PUFAs) are the precursors of many anti-inflammatory metabolites, such as resolvins and neuroprotectins. It is of interest to study the metabolic profile of endogenous n-3 PUFAs in low-grade inflammatory conditions. To evaluate the protective effects of endogenous n-3 PUFAs on low-grade inflammation with the metabolomics approach, we fed fat-1 mice with an n-6 PUFAs rich diet for a long time to induce a low-grade inflammatory condition. Multi-analysis techniques, including structural analysis using quadrupole time-of-flight mass spectrometry with MS^E mode, were applied in untargeted metabolomics to search for meaningful metabolites with significant variance in fat-1 mice under low-grade inflammation. Following the untargeted metabolomics screening, several meaningful metabolites were selected which were associated with anti-inflammatory effects generated from endogenous n-3 PUFAs for further analysis. The results revealed that the purine metabolism, fatty acid metabolism and oxidative stress response pathways through insulin resistance were involved in anti-inflammatory mechanisms of n-3 PUFA in low-grade inflammatory conditions. For the first time, this study explored the highlighted pathways as contributors to the anti-inflammatory effects of endogenous n-3 PUFAs in low-grade inflammatory conditions.

Low-grade inflammation is usually defined as the chronic production and a low-grade state of inflammatory factors, it often does not have symptoms, and has been associated with neurodegenerative disease, obesity, and diabetes.     

Improving natural products identification through molecular features-oriented precursor ion selection and targeted MS/MS analysis: a case study of Zhi-Ke-Yang-Yin capsule

Chemical substance identification is an indispensable step in research on therapeutic materials based on traditional Chinese medicine and its formulas. The successful characterization of chemical substances mainly relies on high-quality MS/MS spectra. However, to date, relatively few studies have specifically addressed the issues of improving the acquisition of MS/MS spectra of compounds for characterization. The current auto-MS/MS mode, where the precursor ions are selected depending on their signal intensity, encounters a drawback when the sample contains many overlapping signals, leading to compounds with a lower or much lower abundance missing identification. To solve this problem, a strategy in which molecular features oriented precursor ion selection was followed by targeted MS/MS analysis for structure elucidation was proposed. The precursor ions were selected according to their first and second molecular features, namely m/z and retention time, irrespective of their intensities. By performing targeted MS/MS analysis, the MS/MS spectra of many more compounds of interest can be obtained, leading to an improvement in natural product identification. As an example, the chemical substances in the Zhi-Ke-Yang-Yin extract were analyzed using this strategy, and as a result, 431 ingredients were tentatively characterized, including both known and unknown or new compounds.

Chemical substance identification is an indispensable step in research on therapeutic materials based on traditional Chinese medicine and its formulas.     

Comparative metabolomics unveils molecular changes and metabolic networks of syringin against hepatitis B mice by untargeted mass spectrometry

Untargeted metabolomics technology was used to discover the metabolic pathways and biomarkers for revealing the potential biological mechanism of syringin on hepatitis B virus. Serum samples were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS)-based comparative metabolomics coupled with pattern recognition methods and network pathway. In addition, the histopathology, HBV DNA detection of liver tissue, and biochemical indicators of liver function change were also explored for investigating the antiviral effect of syringin. In comparison to the model group, the metabolic profiles of the turbulence in transgenic mice tended to recover to the same as the control group after syringin therapy. A total of 33 potential biomarkers were determined to explore the metabolic disorders in the hepatitis B animal model, of which 25 were regulated by syringin, and 8 metabolic pathways, such as phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, glyoxylate and dicarboxylate metabolism, were involved. Syringin markedly reduced the liver pathology change, inhibited HBV DNA replication, and improved liver function. Amino acid metabolism is a potential target for the treatment of hepatitis B. The hepatoprotective effect of syringin may contribute to ameliorating oxidative stress and preventing protein and DNA replication. Comparative metabolomics is a promising tool for discovering metabolic pathways and biomarkers of the hepatitis B animal model as targets to reveal the effects and mechanism of syringin, which benefits the development of natural products and advances the treatment of diseases.

Untargeted metabolomics technology was used to discover the metabolic pathways and biomarkers for revealing the potential biological mechanism of syringin on hepatitis B virus.     

Proteomics and metabolomics analysis reveal potential mechanism of extended-spectrum β-lactamase production in Escherichia coli

In this study, ten clinical susceptible strains and ten clinical ESBL-EC (extended-spectrum β-lactamase-producing Escherichia coli) were screened and obtained by microbial identification using ITEK® 2 Compact. TMT (Tandem Mass Tag) proteomics analysis discovered 1553 DEPs (differentially expressed proteins) between ESBL-EC and non-ESBL-EC. In addition, an untargeted metabolomics assay by using UHPLC-MS (ultra-high-performance liquid chromatography-mass spectrometry) was applied to compare the differential profiles of metabolites between β-lactam antibiotic-sensitive E. coli and multidrug-resistant ESBL-producing E. coli strains. The PCA (principal component analysis) score plots and OPLS-DA (orthogonal projections to latent structures discriminant analysis) plots clearly discriminated ESBL-EC and non-ESBL-EC, and volcano analysis presented 606 and 459 altered metabolites between ESBL-EC vs. non-ESBL-EC in positive and negative ion modes, respectively. Interestingly, the bioinformatics analysis demonstrated that the purine metabolism pathway was enriched in ESBL-EC. These results suggest that the existence of extended-spectrum β-lactamase affects the metabolite and protein profiles of E. coli. The correlation analysis of metabolomics and proteomics data established a correlation between DEPs and differential metabolites in the purine metabolism pathway. Moreover, three metabolite candidates in the purine metabolism pathway were validated by the UPLC-MRM-MS (ultra-performance liquid chromatography multiple reaction monitoring mass spectrometry) method. Our data suggest that these DEPs and differential metabolites may play important roles in the antibiotic resistance of ESBL-EC. Our study can provide scientific data for the mechanism study of antibiotic resistance of ESBL-EC at the metabolite and protein levels and targeting modulators to these pathways may be effective for treatment of ESBL-EC strains.

Proteomic and metabolomics revealed the underlying mechanism of extended-spectrum β-lactamase production in Escherichia coli.     

UHPLC-Q-TOF-MS/MS-oriented characteristic components dataset and multivariate statistical techniques for the holistic quality control of Usnea

The holistic quality evaluation of Traditional Chinese Medicine (TCM) is confronted with significant challenges due to its extreme chemical complexity. In this study, a sensitive strategy based on ultra-high-performance liquid chromatography-triple/time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS) and chemometric analysis was established and validated for the qualitative and semi-quantitative analyses of characteristic components in Usnea. First, three mass spectrometry fragmentation patterns of phenolic acid standards were studied and summarized. Then, an extract of this herb was analyzed by the full-scan MS spectra and identified by extracted ion chromatography (XIC). Based on the abovementioned methods, a total of 38 compounds (8 dibenzofurans, 11 didepsides, 13 depsidones, and 6 mono-substituted phenyl rings) were identified. Subsequently, the qualities of Usnea samples from different regions were evaluated by the semi-quantitative analysis based on their relative peak areas. Furthermore, principal component analysis (PCA) was performed to compare the Usnea herbs and to find possible diagnostic chemical components. This novel and powerful strategy could provide a potential approach for the holistic quality control of TCM.

The holistic quality evaluation of Traditional Chinese Medicine (TCM) is confronted with significant challenges due to its extreme chemical complexity.     

Matrix solid-phase dispersion as a greener alternative to obtain bioactive extracts from Haematococcus pluvialis. Characterization by UHPLC-QToF

So far, research on the microalga Haematococcus pluvialis has been focused mainly on the exploitation of its high astaxanthin content, leaving aside the use of other bioactive compounds present. This study is focused on obtaining and characterizing extracts enriched in bioactive compounds from this microalga red aplanospores. This is performed by means of Matrix Solid-Phase Dispersion (MSPD) extraction process, in an environmentally friendly way with low energy consumption and GRAS solvents. The effects of extraction parameters, particularly the extraction solvents (ethanol, ethyl lactate and water) are studied, in order to obtain maximum recovery of the main antioxidant compounds of interest (carotenoids, fatty acids and derivatives). Characterization of extracts is carried out by HPLC-DAD (High Performance Liquid Chromatography Diode Array Detector) and UHPLC-QToF (Ultra High-Performance Liquid Chromatography Quadrupole Time-of-Flight). The results show that MSPD produced extracts with higher bioactive compound recoveries than conventional cell disruption extractions. At the same time, a novel untargeted characterization for this species is performed, identifying compounds not previously dated in H. pluvialis, which include 10-phenyldecanoic acid and the -oxo and -hydroxy derivatives of palmitic acid. This approach, first applied to a freshwater microalgae, characterized by rigid and resistant aplanospores, provided a synergistic and sustainable extract, giving a broader focus on the use of this microalga.

Untargeted characterization and alternative extraction of carotenoids, fatty acids, and new bioactive compounds from microalga Haematococcus pluvialis using GRAS solvents.     

Metabolomic profiling to reveal the therapeutic potency of Posidonia oceanica nanoparticles in diabetic rats

Posidonia oceanica is a sea grass belonging to the family Posidoniaceae, which stands out as a substantial reservoir of bioactive compounds. In this study, the secondary metabolites of the P. oceanica rhizome were annotated using UPLC-HRESI-MS/MS, revealing 86 compounds including simple phenolic acids, flavonoids, and their sulphated conjugates. Moreover, the P. oceanica butanol extract exhibited substantial antioxidant and antidiabetic effects in vitro. Thus, a reliable, robust drug delivery system was developed through the encapsulation of P. oceanica extract in gelatin nanoparticles to protect active constituents, control their release and enhance their therapeutic activity. To confirm these achievements, untargeted GC-MS metabolomics analysis together with biochemical evaluation was employed to investigate the in vivo anti-diabetic potential of the P. oceanica nano-extract. The results of this study demonstrated that the P. oceanica gelatin nanoparticle formulation reduced the serum fasting blood glucose level significantly (p < 0.05) in addition to improving the insulin level, together with the elevation of glucose transporter 4 levels. Besides, multivariate/univariate analyses of the GC-MS metabolomic dataset revealed several dysregulated metabolites in diabetic rats, which were restored to normalized levels after treatment with the P. oceanica gelatin nanoparticle formulation. These metabolites mainly originate from the metabolism of amino acids, fatty acids and carbohydrates, indicating that this type of delivery was more effective than the plain extract in regulating these altered metabolic processes. Overall, this study provides novel insight for the potential of P. oceanica butanol extract encapsulated in gelatin nanoparticles as a promising and effective antidiabetic therapy.

The potential of P. oceanica butanol extract encapsulated in gelatin nanoparticles as a promising and effective antidiabetic therapy has been investigated via metabolomics.     

A holistic comparison of flavor signature and chemical profile in different harvesting periods of Chrysanthemum morifolium Ramat. based on metabolomics combined with bioinformatics and molecular docking strategy

Taiju and Duoju are products of Hangbaiju (HJ) obtained during different collection periods, and they have been commonly used as ingredients in tea beverages and dietary traditional Chinese medicine. This study reports an integrated strategy based on metabolomics, bioinformatics and molecular docking to further explore the effect of the harvesting period on the metabolic profile and clinical efficacy of HJ. Firstly, gas chromatography-mass spectrometry (GC-MS) and ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) were employed for non-targeted metabolomics profiling of essential oils and flavonoids. A sequential window acquisition of all theoretical fragment-ion spectra information-dependent acquisition (SWATH-IDA) bi-directionally verified (SIBDV) method was developed that integrates the advantages of both SWATH and IDA in characterizing flavonoids. Chemometric methods were then used to screen potential chemical markers. Furthermore, HJ is effective in hepatoprotective functions. Therefore, hepatocellular-carcinoma-related differentially expressed genes were obtained using bioinformatics, and the corresponding proteins were molecularly docked with diagnostic chemical markers. In total, 78 volatile oils and 63 flavonoids were tentatively identified. The results allowed the selection of 11 metabolites (5 volatile oils and 6 flavonoids), which are nominated as novel markers for material authentication of Taiju and Duoju. Additionally, two proteins associated with hepatoma were screened using bioinformatics. All six flavonoid markers with binding energies of <−5 kcal mol⁻¹ were considered to be anti-hepatoma biomarkers. Noticeably, in Taiju, the content of hydroxygenkwanin showed a downward trend, but the content of the other five flavonoids and the five flavored volatile difference compounds had an upward trend. This bestows a unique flavor profile on Taiju, leading to differences in sensory aroma and clinical efficacy in Taiju and Duoju. In conclusion, the transformation of secondary metabolites was the dominant trend during HJ growth. These findings lay the foundation for food development and distinguishing clinical applications.

This paper analyzed the differences between the two harvesting periods (Taiju and Duoju) on the ingredients and pharmacological activity in Chrysanthemum morifolium Ramat.     

Advances in mass spectrometry-based metabolomics for investigation of metabolites

Metabolomics is the systematic study of all the metabolites present within a biological system, which consists of a mass of molecules, having a variety of physical and chemical properties and existing over an extensive dynamic range in biological samples. Diverse analytical techniques are needed to achieve higher coverage of metabolites. The application of mass spectrometry (MS) in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques. Significant advances have also occurred in separation-based MS techniques (gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and ion mobility-mass spectrometry), as well as separation-free MS techniques (direct infusion-mass spectrometry, matrix-assisted laser desorption ionization-mass spectrometry, mass spectrometry imaging, and direct analysis in real time mass spectrometry) in the past decades. This review presents a brief overview of the recent advanced MS techniques and their latest applications in metabolomics. The software/websites for MS result analyses are also reviewed.

Metabolomics is the systematic study of all the metabolites present within a biological system, supply functional information and has received extensive attention in the field of life sciences.     

A review on phytochemical constituents and pharmacological potential of Calotropis procera

Calotropis procera is locally known as Aak or Madar in Hindi, milk weed in English and belongs to the family Apocynaceae and subfamily Asclepiadoideae. Although a wasteland plant, it is of sacred use as its flowers are offered for worshipping Lord Shiva, a Hindu God. Tribes all over the world use the plant in treatment of various diseases like snake bite, body pain, asthma, epilepsy, cancer, sexual disorders, skin diseases and many more. This plant contains various phytoconstituents such as flavonoids, terpenoids, cardenolides, steroids oxypregnanes etc. Though literature searches reveal many reviews about ethnomedicinal uses, chemical composition and pharmacological activities, no recent papers are available that provide an overview of the therapeutic potential and toxicity of Calotropis procera. Hence, the insight of this review is to provide a systemic summary of phytochemistry, pharmacology, toxicology and therapeutic potential of Calotropis procera and to highlight the gaps in the knowledge so as to offer inspiration for future research.

Calotropis procera is also known as Aak or Madar. The present review provides a systematic outline of phytochemistry, toxicology, pharmacology and therapeutic potential of Calotropis procera.