Metabolic Profiling and Predicting the Free Radical Scavenging Activity of Guava ( Psidium guajava L.) Leaves According to Harvest Time by 1 H-Nuclear Magnetic Resonance Spectroscopy

Addressing amino acid-derived inhibitory metabolites and enhancing CHO cell culture performance through DOE-guided media modifications

Previously, we identified six inhibitory metabolites (IMs) accumulating in Chinese hamster ovary (CHO) cultures using AMBIC 1.0 community reference medium that negatively impacted culture performance. The goal of the current study was to modify the medium to control IM accumulation through design of experiments (DOE). Initial over-supplementation of precursor amino acids (AAs) by 100% to 200% in the culture medium revealed positive correlations between initial AA concentrations and IM levels. A screening design identified 5 AA targets, Lys, Ile, Trp, Leu, Arg, as key contributors to IMs. Response surface design analysis was used to reduce initial AA levels between 13% and 33%, and these were then evaluated in batch and fed-batch cultures. Lowering AAs in basal and feed medium and reducing feed rate from 10% to 5% reduced inhibitory metabolites HICA and NAP by up to 50%, MSA by 30%, and CMP by 15%. These reductions were accompanied by a 13% to 40% improvement in peak viable cell densities and 7% to 50% enhancement in IgG production in batch and fed-batch processes, respectively. This study demonstrates the value of tuning specific AA levels in reference basal and feed media using statistical design methodologies to lower problematic IMs.

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.

Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea

BACKGROUND

Neptunia oleracea is a plant consumed as a vegetable and which has been used as a folk remedy for several diseases. Herein, two regression models (partial least squares, PLS; and random forest, RF) in a metabolomics approach were compared and applied to the evaluation of the relationship between phenolics and bioactivities of N. oleracea. In addition, the effects of different extraction conditions on the phenolic constituents were assessed by pattern recognition analysis.

RESULTS

Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities.

CONCLUSION

Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry.

Investigation of the effect of genotype and agronomic conditions on metabolomic profiles of selected strawberry cultivars with different sensitivity to environmental stress

Strawberry is one of the most economically important and widely cultivated fruit crops across the world, so that there is a growing need to develop new analytical methodologies for the authentication of variety and origin, as well as the assessment of agricultural and processing practices. In this work, an untargeted metabolomic strategy based on gas chromatography mass spectrometry (GC-MS) combined with multivariate statistical techniques was used for the first time to characterize the primary metabolome of different strawberry cultivars and to study metabolite alterations in response to multiple agronomic conditions. For this purpose, we investigated three varieties of strawberries with different sensitivity to environmental stress (Camarosa, Festival and Palomar), cultivated in soilless systems using various electrical conductivities, types of coverage and substrates. Metabolomic analysis revealed significant alterations in primary metabolites between the three strawberry cultivars grown under different crop conditions, including sugars (fructose, glucose), organic acids (malic acid, citric acid) and amino acids (alanine, threonine, aspartic acid), among others. Therefore, it could be concluded that GC-MS based metabolomics is a suitable tool to differentiate strawberry cultivars and characterize metabolomic changes associated with environmental and agronomic conditions.

The Progress of Metabolomics Study in Traditional Chinese Medicine Research

Traditional Chinese medicine (TCM) has played important roles in health protection and disease treatment for thousands of years in China and has gained the gradual acceptance of the international community. However, many intricate issues, which cannot be explained by traditional methods, still remain, thus, new ideas and technologies are needed. As an emerging system biology technology, the holistic view adopted by metabolomics is similar to that of TCM, which allows us to investigate TCM with complicated conditions and multiple factors in depth. In this paper, we tried to give a timely and comprehensive update about the methodology progression of metabolomics, as well as its applications, in different fields of TCM studies including quality control, processing, safety and efficacy evaluation. The herbs investigated by metabolomics were selected for detailed examination, including Anemarrhena asphodeloides Bunge, Atractylodes macrocephala Kidd, Pinellia ternate, etc.; furthermore, some valuable results have been obtained and summarized. In conclusion, although the study of metabolomics is at the early phase and requires further scrutiny and validation, it still provides bright prospects to dissect the synergistic action of multiple components from TCM. Overall, with the further development of analytical techniques, especially multi-analysis techniques, we expect that metabolomics will greatly promote TCM research and the establishment of international standards, which is beneficial to TCM modernization.

Chemical characterization and antioxidant capacity of the araçá-pera (Psidium acutangulum): An exotic Amazon fruit

The "araçá-pera" (Psidium acutangulum DC) is an exotic guava consumed by the Brazilian Amazon population. This paper describes 22 compounds from this fruit by UHPLC-HRMS and NMR methods, being one disaccharide, five monosaccharides, two organic acids, one trihydroxycinnamic acid glucopyranosyl, one tannine digalloyl glucopyranosyl, five triterpenoid acids, and six fatty acids. It also quantifies the level of ascorbic acid (AA) by HPLC-MS (74.32±1.23mg/100g of fresh fruit), and defines the chemical antioxidant activities by DPPH and ABTS⁺ assays (24.96±0.75, 90.57±0.63mg of vitamin C/100g fresh fruit, respectively), and a cell-based assays (76-100%). These results have shown that this exotic guava can be consumed as a nutraceutical ingredient, as well as be used in the production of functional foods in the Amazonian diet to prevent chronic and oxidative diseases.

Small molecule-sensing strategy and techniques for understanding the functionality of green tea

Various low-molecular-weight phytochemicals in green tea (Camellia sinensis L.), especially (-)-epigallocatechin-3-O-gallate (EGCG), are known to be involved in health promotion and disease risk reduction. However, the underlying mechanism has remained elusive because of the absence of an analytical technique that can easily detect the precise behavior of such a small molecule. Recently, we have identified a cell-surface EGCG-sensing receptor and the related signaling molecules that control the physiological functions of EGCG. We also developed a novel in situ label-free imaging technique for visualizing spatially resolved biotransformations based on simultaneous mapping of EGCG and its phase II metabolites. Furthermore, we established a chemometric method capable of evaluating the functionality of multicomponent green tea extracts by focusing on their compositional balances. This review highlights our proposed small molecule-sensing techniques for detecting the complex behavior of green tea components and linking such information to an enhanced understanding of green tea functionality.

High-performance liquid chromatography-based multivariate analysis to predict the estrogenic activity of an Epimedium koreanum extract

This study characterizes the correlation between the chemical fingerprint and estrogenic activity of an Epimedium koreanum extract. The estrogenic activity of 31 E. koreanum extract samples was evaluated by a luciferase reporter gene assay, and the samples were classified into 3 groups based on their bioactivity. A chemical fingerprint analysis was performed on each sample by high-performance liquid chromatography (HPLC), and 44 common peaks were selected from the chromatogram and used as a dataset for a pattern recognition analysis. A canonical discriminant analysis performed on this dataset determined a distinct distribution of the samples according to their estrogenic activity on the scoring plot. The classification results showed that 90.3% of the original grouped cases had been correctly classified. The total content of the 4 major extract compounds, epimedin A, epimedin B, epimedin C, and icariin, exhibited good correlation (r=0.784) with the estrogenic activities of the respective extracts. This chromatographic fingerprint-chemometric analysis system could be useful for predicting the E. koreanum pharmacological activity and consequent biological activity-relevant quality control assessment.

The potential of metabolic fingerprinting as a tool for the modernisation of TCM preparations

A vast majority Chinese herbal medicines (CHM) are traditionally administered as individually prepared water decoctions (tang) which are rather complicated in practice and their dry extracts show technological problems that hamper straight production of more convenient application forms. Modernised extraction procedures may overcome these difficulties but there is lack of clinical evidence supporting their therapeutic equivalence to traditional decoctions and their quality can often not solely be attributed to the single marker compounds that are usually used for chemical extract optimisation. As demonstrated by the example of the rather simple traditional TCM formula Danggui Buxue Tang, both the chemical composition and the biological activity of extracts resulting from traditional water decoction are influenced by details of the extraction procedure and especially involve pharmacokinetic synergism based on co-extraction. Hence, a more detailed knowledge about the traditional extracts' chemical profiles and their impact on biological activity is desirable in order to allow the development of modernised extracts that factually contain the whole range of compounds relevant for the efficacy of the traditional application. We propose that these compounds can be identified by metabolomics based on comprehensive fingerprint analysis of different extracts with known biological activity. TCM offers a huge variety of traditional products of the same botanical origin but with distinct therapeutic properties, like differentially processed drugs and special daodi qualities. Through this variety, TCM gives an ideal field for the application of metabolomic techniques aiming at the identification of active constituents.