Dimethylcysteine (DiCys)/o-Phthalaldehyde Derivatization for Chiral Metabolite Analyses: Cross-Comparison of Six Chiral Thiols

Metabolomics profiling using liquid chromatography-mass spectrometry (LC-MS) has become an important tool in biomedical research. However, resolving enantiomers still represents a significant challenge in the metabolomics study of complex samples. Here, we introduced N,N-dimethyl-l-cysteine (dimethylcysteine, DiCys), a chiral thiol, for the o-phthalaldehyde (OPA) derivatization of enantiomeric amine metabolites. We took interest in DiCys because of its potential for multiplex isotope-tagged quantification. Here, we characterized the usefulness of DiCys in reversed-phase LC-MS analyses of chiral metabolites, compared against five commonly used chiral thiols: N-acetyl-l-cysteine (NAC); N-acetyl-d-penicillamine (NAP); isobutyryl-l-cysteine (IBLC); N-(tert-butoxycarbonyl)-l-cysteine methyl ester (NBC); and N-(tert-butylthiocarbamoyl)-l-cysteine ethyl ester (BTCC). DiCys and IBLC showed the best overall performance in terms of chiral separation, fluorescence intensity, and ionization efficiency. For chiral separation of amino acids, DiCys/OPA also outperformed Marfey’s reagents: 1-fluoro-2-4-dinitrophenyl-5-l-valine amide (FDVA) and 1-fluoro-2-4-dinitrophenyl-5-l-alanine amide (FDAA). As proof of principle, we compared DiCys and IBLC for detecting chiral metabolites in aqueous extracts of rice. By LC–MS analyses, both methods detected twenty proteinogenic l-amino acids and seven d-amino acids (Ala, Arg, Lys, Phe, Ser, Tyr, and Val), but DiCys showed better analyte separation. We conclude that DiCys/OPA is an excellent amine-derivatization method for enantiomeric metabolite detection in LC-MS analyses.     

Chemical composition analysis of Angelica sinensis (Oliv.) Diels and its four processed products by ultra-high-performance liquid chromatography coupled with quadrupole-orbitrap mass spectrometry combining with nontargeted metabolomics

Angelica sinensis (Oliv.) Diels. has been used for women to enrich the blood, prevent and treat blood deficiency syndrome in Traditional Chinese Medicine for thousands of years. Wine-processed Angelica sinensis, soil-processed Angelica sinensis, oil-processed Angelica sinensis, and charred-processed Angelica sinensis are the most significant four processed products used in Chinese clinic. However, there have been few studies aimed at comparing their chemical differences. Ultra-high-performance liquid chromatography coupled with quadrupole-orbitrap mass spectrometry combining with nontargeted metabolomics was applied to investigate the diversity of processed products of Angelica sinensis. A total of 74 compounds with the variable importance in the projection value more than 1.5 and P less than 0.05 in ANOVA were highlighted as the compounds that contribute most to the discrimination of Angelica sinensis and four processed products. The results showed the metabolic changes between Angelica sinensis and its four processed products, there were 19 metabolites, 3 metabolites, 6 metabolites, and 45 metabolites were tentatively assigned in soil-processed Angelica sinensis, wine-processed Angelica sinensis, oil-processed Angelica sinensis, and charred-processed Angelica sinensis, respectively. These results suggested that the proposed metabolomics approach was useful for the quality evaluation and control of processed products of Angelica sinensis.     

A Multi-Omics Analysis Reveals Anti-Osteoporosis Mechanism of Four Components from Crude and Salt-Processed Achyranthes bidentata Blume in Ovariectomized Rats

The root of Achyranthes bidentata Blume (AB) is a well-known traditional Chinese medicine for treating osteoporosis. Plenty of studies focused on the pharmacological mechanism of the whole extract; however, the contribution of different components to the anti-osteoporosis effect remains unknown. The aim of this study is to explore the anti-osteoporosis mechanism of different components of crude and salt-processed AB under the guidance of network pharmacology, metabolomics, and microbiomics. First, network pharmacology analysis was applied to constructing the compound-target-disease network of AB to provide a holistic view. Second, the anti-osteoporosis effects of the four components were evaluated in female Wistar rats. The subjects were divided into a normal group, a model group, a 17α-estradiol (E2)-treated group, a polysaccharide-component-treated groups, and a polysaccharide-knockout-component-treated groups. All the serum, urine, and feces samples of the six groups were collected after 16 weeks of treatment. Biochemical and microcomputed tomography (μCT) parameters were also acquired. Coupled with orthogonal partial least-squares discrimination analysis, one dimensional nuclear magnetic resonance (NMR) was used to monitor serum metabolic alterations. A total of twenty-two biomarkers, including lipids, amino acids, polyunsaturated fatty acids, glucose, and so on were identified for the different components-treated groups. Through pathway analysis, it is indicated that glyoxylate and dicarboxylate metabolism, glycine, serine, and threonine metabolism, alanine, aspartate, and glutamate metabolism, d-glutamine, and d-glutamate metabolism were the major intervened pathways. Levels of these biomarkers shifted away from the model group and were restored to normal after treatment with the four components. In addition, 16S rDNA sequencing demonstrated that the abundance of Anaerofilum, Rothia, and Turicibacter bacteria was positively correlated with an anti-osteoporosis effect, whereas the abundance of Oscillospira was negatively correlated. The osteoprotective effect of the polysaccharide components of crude and salt-processed AB is related to the regulation of the abundance of these gut microbiota.     

NMF-Based Approach for Missing Values Imputation of Mass Spectrometry Metabolomics Data

In mass spectrometry (MS)-based metabolomics, missing values (NAs) may be due to different causes, including sample heterogeneity, ion suppression, spectral overlap, inappropriate data processing, and instrumental errors. Although a number of methodologies have been applied to handle NAs, NA imputation remains a challenging problem. Here, we propose a non-negative matrix factorization (NMF)-based method for NA imputation in MS-based metabolomics data, which makes use of both global and local information of the data. The proposed method was compared with three commonly used methods: k-nearest neighbors (kNN), random forest (RF), and outlier-robust (ORI) missing values imputation. These methods were evaluated from the perspectives of accuracy of imputation, retrieval of data structures, and rank of imputation superiority. The experimental results showed that the NMF-based method is well-adapted to various cases of data missingness and the presence of outliers in MS-based metabolic profiles. It outperformed kNN and ORI and showed results comparable with the RF method. Furthermore, the NMF method is more robust and less susceptible to outliers as compared with the RF method. The proposed NMF-based scheme may serve as an alternative NA imputation method which may facilitate biological interpretations of metabolomics data.     

Untargeted Metabolomics Combined with Bioassay Reveals the Change in Critical Bioactive Compounds during the Processing of Qingzhuan Tea

Qingzhuan tea (QZT) is a typical Chinese dark tea that has a long-time manufacturing process. In the present study, liquid chromatography coupled with tandem mass spectrometry was used to study the chemical changes of tea samples during QZT processing. Untargeted metabolomics analysis revealed that the pile-fermentation and turnover (post-fermentation, FT) was the crucial stage in transforming the main compounds of QZT, whose contents of flavan-3-ols and flavonoids glycosides were decreased significantly. The bioactivities, including the antioxidant capacities and inhibitory effects on α-amylase and α-glucosidase, were also reduced after the FT process. It was suggested that although the QZT sensory properties improved following pile-fermentation and aging, the bioactivities remained restrained. Correlation analysis indicated that the main galloylated catechins and flavonoid glycosides were highly related to their antioxidant capacity and inhibitory effects on α-amylase and α-glucosidase.     

近期工业微生物关键技术和应用

近年来,随着宏基因组学、蛋白质组学和代谢组学等技术的发展,工业微生物技术在资源、医药和手性合成等领域已经成为热点技术,并开拓了电子和纳米技术等新的应用领域.本文综述了几项最新的工业微生物技术,主要包括:微生物环氧化水解酶催化合成手性二醇、微生物甲酸脱氢酶用于再生氧化还原反应的辅因子、通过噬菌体展示技术得到纳米级金属丝、代谢网络改造和重建用于传统发酵生产以及有机溶剂耐受菌和宏基因组技术的应用.     

Comparative Metabolomic Analysis of Four Fabaceae and Relationship to In Vitro Nematicidal Activity against Xiphinema index

The grapevine fanleaf virus (GFLV), responsible for fanleaf degeneration, is spread in vineyards by the soil nematode Xiphinema index. Nematicide molecules were used to limit the spread of the disease until they were banned due to negative environmental impacts. Therefore, there is a growing interest in alternative methods, including plant-derived products with antagonistic effects to X. index. In this work, we evaluated the nematicidal potential of the aerial parts and roots of four Fabaceae: sainfoin (Onobrychis viciifolia), birdsfoot trefoil (Lotus corniculatus), sweet clover (Melilotus albus), and red clover (Trifolium pratense), as well as that of sainfoin-based commercial pellets. For all tested plants, either aerial or root parts, or both of them, exhibited a nematicidal effect on X. index in vitro, pellets being as effective as freshly harvested plants. Comparative metabolomic analyses did not reveal molecules or molecule families specifically associated with antagonistic properties toward X. index, suggesting that the nematicidal effect is the result of a combination of different molecules rather than associated with a single compound. Finally, scanning electron microscope observations did not reveal the visible impact of O. viciifolia extract on X. index cuticle, suggesting that alteration of the cuticle may not be the primary cause of their nematicidal effect.     

Targeted and Untargeted Metabolomic Analyses Reveal Organ Specificity of Specialized Metabolites in the Model Grass Brachypodium distachyon

Brachypodium distachyon, because of its fully sequenced genome, is frequently used as a model grass species. However, its metabolome, which constitutes an indispensable element of complex biological systems, remains poorly characterized. In this study, we conducted comprehensive, liquid chromatography-mass spectrometry (LC-MS)-based metabolomic examination of roots, leaves and spikes of Brachypodium Bd21 and Bd3-1 lines. Our pathway enrichment analysis emphasised the accumulation of specialized metabolites representing the flavonoid biosynthetic pathway in parallel with processes related to nucleotide, sugar and amino acid metabolism. Similarities in metabolite profiles between both lines were relatively high in roots and leaves while spikes showed higher metabolic variance within both accessions. In roots, differences between Bd21 and Bd3-1 lines were manifested primarily in diterpenoid metabolism, while differences within spikes and leaves concerned nucleotide metabolism and nitrogen management. Additionally, sulphate-containing metabolites differentiated Bd21 and Bd3-1 lines in spikes. Structural analysis based on MS fragmentation spectra enabled identification of 93 specialized metabolites. Among them phenylpropanoids and flavonoids derivatives were mainly determined. As compared with closely related barley and wheat species, metabolic profile of Brachypodium is characterized with presence of threonate derivatives of hydroxycinnamic acids.     

Research on Processing-Induced Chemical Variations in Polygonatum Cyrtonema Rhizome by Integrating Metabolomics and Glycomics

Polygonatum cyrtonema rhizome (PCR), the dried sweet rhizome of Polygonatum cyrtonema Hua, is commonly used as a tonic remedy and a functional food in Asia, Europe, and North America. Multiple components, including secondary metabolites, monosaccharides, oligosaccharides, and polysaccharides, collectively contribute to the therapeutic effects of PCR. Processing time exerts a significant influence on the quality of PCR, but the various processing stages have not been comprehensively chemically profiled. It is urgent to study processing-induced chemical variations in PCR to control the processing degree. In this study, multiple chromatographic and mass spectrometric techniques were used in combination with multivariate statistical analysis to perform qualitative and quantitative research on secondary metabolites and carbohydrates in PCR during processing. The results demonstrated that PCR processing can be divided into three stages, namely the raw stage (0 h), the middle stage (1–6 h), and the late stage (8–18 h). Twenty differential compounds were screened from secondary metabolites and oligosaccharides to distinguish PCR in different processing stages. Furthermore, the chemical variations of Polygonatum cyrtonema polysaccharides (PCP) also entered a new stage after processing for 6 h. Multiple chemical mechanisms, including hydrolysis, oxidative decomposition, dehydration, Maillard reaction, and polymerization were involved in the processing. This work provides a scientific basis to reveal the relationship between processing stage and chemical variations.