A metabolomic strategy based on integrating headspace gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry to differentiate the five cultivars of Chrysanthemum flower

Application of Data Fusion in Traditional Chinese Medicine: A Review

Traditional Chinese medicine is characterized by numerous chemical constituents, complex components, and unpredictable interactions among constituents. Therefore, a single analytical technique is usually unable to obtain comprehensive chemical information. Data fusion is an information processing technology that can improve the accuracy of test results by fusing data from multiple devices, which has a broad application prospect by utilizing chemometrics methods, adopting low-level, mid-level, and high-level data fusion techniques, and establishing final classification or prediction models. This paper summarizes the current status of the application of data fusion strategies based on spectroscopy, mass spectrometry, chromatography, and sensor technologies in traditional Chinese medicine (TCM) in light of the latest research progress of data fusion technology at home and abroad. It also gives an outlook on the development of data fusion technology in TCM analysis to provide references for the research and development of TCM.

Comprehensive metabolomic variations of hawthorn before and after insect infestation based on the combination analysis of 1H NMR and UPLC-MS

Hawthorn, the sliced and dried ripe fruits of Crataegus pinnatifida Bge. Var. Major N. E. Br. (Rosaceae), is an edible and medicinal substance with a variety of health-promoting benefits. Hawthorn needs to be stored in warehouses after harvesting to meet people's perennial demand. However, it is easily infested by insects of Plodia interpunctella and Tribolium castaneum during storage, which inevitably leads to poor quality and causes adverse effects on people's health. So far, there has been no report on insect-infested hawthorn. In this study, we analyzed the changes of metabolites in hawthorn before and after insect infestation and screened out potential biomarkers to effectively and quickly detect the occurrence of insect infestation. A combination analysis of 1H nuclear magnetic resonance (NMR) and ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) was used to identify the primary and secondary metabolites. By the comparison of hawthorn and insect-infested hawthorn samples, it was found that the differences were mainly manifested in the content of metabolites. The metabolites of 32 and 1463 were identified by 1H NMR and UPLC-MS analysis, respectively. According to the parameters of VIP >1 and P < 0.05, 10 differential metabolites were screened from 1H NMR analysis. Based on the parameters of VIP >1.0, P < 0.05, and (FC) > 1 or < 1, 47 differential metabolites were screened from UPLC-MS analysis. Therefore, a total of 57 differential metabolites were considered as differential biomarkers. The heat map analysis showed that the content of some differential biomarkers with significant pharmacological activities decreased after insect infestation. Through receiver operating characteristic (ROC) curve assessment, 52 differential biomarkers (6 of 1H NMR analysis and 46 of UPLC-MS analysis) were screened to distinguish whether insect infestation occurred in hawthorn. This is the first report on the changes of metabolites between hawthorn and insect-infested hawthorn and on the screening of differential biomarkers for monitoring insects. These results contributed to evaluate quality of hawthorn and ensure food safety for consumers. It also laid a foundation for further research on the infestation mechanism and safe storage monitoring in hawthorn.

Fast and non-destructive discriminating the geographical origin of Hangbaiju by hyperspectral imaging combined with chemometrics

Hangbaiju is highly appreciated flower tea for its health benefits, and its quality and price are affected by geographical origin. Fast and accurate identification of the geographical origin of Hangbaiju is very significant for producers, consumers and market regulators. In this work, hyperspectral imaging combined with chemometrics, was used, for the first time, to explore and implement the geographical origin classification of Hangbaiju. The hyperspectral images in the spectral range of 410-2500 nm for 75 samples of five different origins were collected. As a versatile chemometrics tool, bagging classification tree-radial basis function (BAGCT-RBFN), compared with classification tree (CT), radial basis function network (RBFN), was applied to discriminate Hangbaiju samples from different origins. The results showed that BAGCT-RBFN based on optimal wavelengths yielded superior classification performances to CT and RBFN with full wavelengths. The recognition rates (RR) of the training and prediction sets by BAGCT-RBFN were 96.0 % and 92.0 %, respectively. Hyperspectral imaging combined with chemometric can be considered as a powerful, feasible and convenient tool for the classification of Hangbaiju samples from different origins. It promises to be a potential way for origin discriminant analysis and quality monitor in food fields.

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.

Caffeoylquinic acids: chemistry, biosynthesis, occurrence, analytical challenges, and bioactivity

Caffeoylquinic acids (CQAs) are specialized plant metabolites we encounter in our daily life. Humans consume CQAs in mg-to-gram quantities through dietary consumption of plant products. CQAs are considered beneficial for human health, mainly due to their anti-inflammatory and antioxidant properties. Recently, new biosynthetic pathways via a peroxidase-type p-coumaric acid 3-hydroxylase enzyme were discovered. More recently, a new GDSL lipase-like enzyme able to transform monoCQAs into diCQA was identified in Ipomoea batatas. CQAs were recently linked to memory improvement; they seem to be strong indirect antioxidants via Nrf2 activation. However, there is a prevalent confusion in the designation and nomenclature of different CQA isomers. Such inconsistencies are critical and complicate bioactivity assessment since different isomers differ in bioactivity and potency. A detailed explanation regarding the origin of such confusion is provided, and a recommendation to unify nomenclature is suggested. Furthermore, for studies on CQA bioactivity, plant-based laboratory animal diets contain CQAs, which makes it difficult to include proper control groups for comparison. Therefore, a synthetic diet free of CQAs is advised to avoid interferences since some CQAs may produce bioactivity even at nanomolar levels. Biotransformation of CQAs by gut microbiota, the discovery of new enzymatic biosynthetic and metabolic pathways, dietary assessment, and assessment of biological properties with potential for drug development are areas of active, ongoing research. This review is focused on the chemistry, biosynthesis, occurrence, analytical challenges, and bioactivity recently reported for mono-, di-, tri-, and tetraCQAs.

Discovery of Quality Markers of Nucleobases, Nucleosides, Nucleotides and Amino Acids for Chrysanthemi Flos From Different Geographical Origins Using UPLC-MS/MS Combined With Multivariate Statistical Analysis

Nucleobases, nucleosides, nucleotides and amino acids, as crucial nutrient compositions, play essential roles in determining the flavor, function and quality of Chrysanthemi Flos. The quality of Chrysanthemi Flos from different geographical origins is uneven, but there have been no reports about the screening of their quality markers based on nutritional ingredients. Here, we developed a comprehensive strategy integrating ultra performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (UPLC-MS/MS) and multivariate statistical analysis to explore quality markers of Chrysanthemi Flos from different geographical origins and conduct quality evaluation and discrimination of them. Firstly, a fast, sensitive, and reliable UPLC-MS/MS method was established for simultaneous quantification 28 nucleobases, nucleosides, nucleotides and amino acids of Chrysanthemi Flos from nine different regions in China. The results demonstrated that Chrysanthemi Flos from nine different cultivation regions were rich in the above 28 nutritional contents and their contents were obvious different; however, correlation analysis showed that altitude was not the main factor for these differences, which required further investigation. Subsequently, eight crucial quality markers for nine different geographical origins of Chrysanthemi Flos, namely, 2'-deoxyadenosine, guanosine, adenosine 3',5'-cyclic phosphate (cAMP), guanosine 3',5'-cyclic monophosphate (cGMP), arginine, proline, glutamate and tryptophan, were screened for the first time using partial least squares discriminant analysis (PLS-DA) and the plot of variable importance for projection (VIP). Moreover, a hierarchical clustering analysis heat map was employed to intuitively clarify the distribution of eight quality markers in the nine different regions of Chrysanthemi Flos. Finally, based on the contents of selected eight quality markers, support vector machines (SVM) model was established to predict the geographical origins of Chrysanthemi Flos, which yielded excellent prediction performance with an average prediction accuracy of 100%. Taken together, the proposed strategy was suitable to discover the quality markers of Chrysanthemi Flos and could be used to discriminate its geographical origin.

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.

Current achievements and future prospects in the genetic breeding of chrysanthemum: a review

Chrysanthemum (Chrysanthemum morifolium Ramat.) is a leading flower with applied value worldwide. Developing new chrysanthemum cultivars with novel characteristics such as new flower colors and shapes, plant architectures, flowering times, postharvest quality, and biotic and abiotic stress tolerance in a time- and cost-efficient manner is the ultimate goal for breeders. Various breeding strategies have been employed to improve the aforementioned traits, ranging from conventional techniques, including crossbreeding and mutation breeding, to a series of molecular breeding methods, including transgenic technology, genome editing, and marker-assisted selection (MAS). In addition, the recent extensive advances in high-throughput technologies, especially genomics, transcriptomics, proteomics, metabolomics, and microbiomics, which are collectively referred to as omics platforms, have led to the collection of substantial amounts of data. Integration of these omics data with phenotypic information will enable the identification of genes/pathways responsible for important traits. Several attempts have been made to use emerging molecular and omics methods with the aim of accelerating the breeding of chrysanthemum. However, applying the findings of such studies to practical chrysanthemum breeding remains a considerable challenge, primarily due to the high heterozygosity and polyploidy of the species. This review summarizes the recent achievements in conventional and modern molecular breeding methods and emerging omics technologies and discusses their future applications for improving the agronomic and horticultural characteristics of chrysanthemum.

Metabolomics of Solanum lycopersicum Infected with Phytophthora infestans Leads to Early Detection of Late Blight in Asymptomatic Plants

Tomato crops suffer attacks of various pathogens that cause large production losses. Late blight caused by Phytophthora infestans is a devastating disease in tomatoes because of its difficultly to control. Here, we applied metabolomics based on liquid chromatography⁻mass spectrometry (LC-MS) and metabolic profiling by matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) in combination with multivariate data analysis in the early detection of late blight on asymptomatic tomato plants and to discriminate infection times of 4, 12, 24, 36, 48, 60, 72 and 96 h after inoculation (hpi). MALDI-MS and LC-MS profiles of metabolites combined with multivariate data analysis are able to detect early-late blight-infected tomato plants, and metabolomics based on LC-MS discriminates infection times in asymptomatic plants. We found the metabolite tomatidine as an important biomarker of infection, saponins as early infection metabolite markers and isocoumarin as early and late asymptomatic infection marker along the post infection time. MALDI-MS and LC-MS analysis can therefore be used as a rapid and effective method for the early detection of late blight-infected tomato plants, offering a suitable tool to guide the correct management and application of sanitary defense approaches. LC-MS analysis also appears to be a suitable tool for identifying major metabolites of asymptomatic late blight-infected tomato plants.

Non-targeted metabolite profiling and specific targeted discrimination strategy for quality evaluation of Cortex Phellodendri from different varieties

Cortex Phellodendri is derived from two species of Phellodendron amurense Rupr. and Phellodendron chinense Schneid. Traditionally, the two species are utilized interchangeably under the name of “huangbo” in the clinic because they are believed to share the same clinical efficacy. However, the chemical analysis in vitro couldn't directly reflect the pharmacological effects. Therefore, whether the constituents could be absorbed into the blood becomes the uppermost problem to account for the clinical efficacy differences of the two species. Therefore, a rapid and sensitive approach to differentiate the two species of Cortex Phellodendri based on non-targeted metabolite profiling and the specific targeted discrimination strategy was first established. Samples from different cultivars were clearly discriminated by principal component analysis and orthogonal partial least squares discriminant analysis. 17 prototype compounds and 22 metabolites contributing to the group separation were identified and tentatively characterized, three of which were found for the first time. Moreover, six of them were screened out as the chemical markers which contribute most to the differences between the two species. Taken together, the application of the non-targeted metabolite profiling and specific targeted discrimination strategy is suitable for the assessment of Cortex Phellodendri.

Non-targeted metabolite profiling and specific targeted discrimination strategy coupled with pattern recognition to differentiate the two varieties in rats.