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Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography–tandem mass spectrometry (GC-MS/MS), liquid chromatography–tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease. [ABSTRACT FROM AUTHOR]

As the ability to collect profiling data in metabolomics increases substantially with the advances in Liquid Chromatography–Mass Spectrometry (LC-MS) instruments, it is urgent to develop new and powerful data analysis approaches to match the big data collected and to extract as much meaningful information as possible from tens of thousands of molecular features. Here, we applied weighted gene co-expression network analysis (WGCNA), an algorithm popularly used in microarray or RNA sequencing, to plasma metabolomic data and demonstrated several advantages of WGCNA over conventional statistical approaches such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). By using WGCNA, a large number of molecular features were clustered into a few modules to reduce the dimension of a dataset, the impact of phenotypic traits such as diet type and genotype on the plasma metabolome was evaluated quantitatively, and hub metabolites were found based on the network graph. Our work revealed that WGCNA is a very powerful tool to decipher, interpret, and visualize metabolomic datasets. [ABSTRACT FROM AUTHOR]

This study was designed to evaluate the chemical fingerprints and the antioxidant, anti-inflammatory and hypolipidemic activity of selected Crepis species collected in Greece, namely, C. commutata, C. dioscoridis, C. foetida, C. heldreichiana, C. incana, C. rubra, and Phitosia crocifolia (formerly known as Crepis crocifolia). For the phytochemical analyses, sample measurements were carried out by using nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography coupled with mass spectrometry (LC-MS). Τhe extracts were evaluated both in vitro (radical scavenging activity: DPPH assay and total phenolic content: Folin–Ciocalteu) and in vivo (paw edema reduction and hypolipidemic activity: experimental mouse protocols). Among the tested extracts, C. incana presented the highest gallic acid equivalents (GAE) (0.0834 mg/mL) and the highest antioxidant activity (IC50 = 0.07 mg/mL) in vitro, as well as the highest anti-inflammatory activity with 32% edema reduction in vivo. Moreover, in the hypolipidemic protocol, the same extract increased plasma total antioxidant capacity (TAC) by 48.7%, and decreased cholesterol (41.3%) as well as triglycerides (37.2%). According to fractionation of the extract and the phytochemical results, this biological effect may be associated with the rich phenolic composition; caffeoyl tartaric acid derivatives (cichoric and caftaric acid) are regarded as the most prominent bioactive specialized metabolites. The present study contributes to the knowledge regarding the phytochemical and pharmacological profile of Crepis spp. [ABSTRACT FROM AUTHOR]

Catharanthus roseus (C. roseus) and Vinca minor (V. minor) are two common important medical plants belonging to the family Apocynaceae. In this study, we used non-targeted GC-MS and targeted LC-MS metabolomics to dissect the metabolic profile of two plants with comparable phenotypic and metabolic differences. A total of 58 significantly different metabolites were present in different quantities according to PCA and PLS-DA score plots of the GC-MS analysis. The 58 identified compounds comprised 16 sugars, eight amino acids, nine alcohols and 18 organic acids. We subjected these metabolites into KEGG pathway enrichment analysis and highlighted 27 metabolic pathways, concentrated on the TCA cycle, glycometabolism, oligosaccharides, and polyol and lipid transporter (RFOS). Among the primary metabolites, trehalose, raffinose, digalacturonic acid and gallic acid were revealed to be the most significant marker compounds between the two plants, presumably contributing to species-specific phenotypic and metabolic discrepancy. The profiling of nine typical alkaloids in both plants using LC-MS method highlighted higher levels of crucial terpenoid indole alkaloid (TIA) intermediates of loganin, serpentine, and tabersonine in V. minor than in C. roseus. The possible underlying process of the metabolic flux from primary metabolism pathways to TIA synthesis was discussed and proposed. Generally speaking, this work provides a full-scale comparison of primary and secondary metabolites between two medical plants and a metabolic explanation of their TIA accumulation and phenotype differences. [ABSTRACT FROM AUTHOR]

Salvia miltiorrhiza (S. miltiorrhiza) Bunge is broadly used as herbal medicine for the clinical treatments of cardiovascular and cerebrovascular diseases. Despite its commercial and medicinal values, few systematic studies on the metabolome of S. miltiorrhiza roots have been carried out so far. We systematically described the metabolic profiles of S. miltiorrhiza using high pressure liquid chromatography mass spectrometry (LC/MS) in conjunction with multivariate statistical analyses, aimed at monitoring their biological variations of secondary metabolites related to three locations and four S. miltiorrhiza genotypes. A total of 40 bioactive constituents were putatively annotated in S. miltiorrhiza root samples. This study found that both the same S. miltiorrhiza genotype growing at three different locations and four S. miltiorrhiza genotypes growing at the same location had significant metabonomic differences identified by the principal component analysis (PCA) approach. By using orthogonal projection to latent structure with discriminant analysis (OPLS-DA), 16 and 14 secondary metabolites can be used as potential location-specific and genotype-specific markers in S. miltiorrhiza, respectively. The specificity of LC/MS profiles offered a powerful tool to discriminate S. miltiorrhiza samples according to genotypes or locations. [ABSTRACT FROM AUTHOR]

Fermented aqueous extracts of Viscum album L. are widely used for cancer treatment in complementary medicine. The high molecular weight compounds viscotoxins and lectins are considered to be the main active substances in the extracts. However, a vast number of small molecules (≤1500 Da) is also expected to be present, and few studies have investigated their identities. In this study, a comprehensive metabolome analysis of samples of fermented aqueous extracts of V. album from two host tree species (Malus domestica and Pinus sylvestris), both prepared by two pharmaceutical manufacturing processes, was performed by liquid chromatography−high resolution tandem mass spectrometry (LC-HRMS/MS). A total of 212 metabolites were putatively annotated, including primary metabolites (e.g., amino acids, organic acids, etc.) and secondary metabolites (mostly phenolic compounds). A clear separation between V. album samples according to the host tree species, but not due to manufacturing processes, was observed by principal component analysis. The biomarkers responsible for this discrimination were assessed by partial least squares−discriminant analysis. Because V. album extracts from different host trees have different clinical applications, the present work highlights the possibility of characterizing the metabolome for identification and traceability of V. album fermented aqueous extracts. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]