BACKGROUND: The genus Salvia L., a member of the family Lamiaceae, is a keystone genus with a wide range of medicinal properties. It possesses a rich metabolite source that has long been used to treat different disorders.
OBJECTIVE: Due to a deficiency of untargeted metabolomic profiling in the genus Salvia, this work attempts to investigate a comprehensive mass spectral library matching, computational data annotations, exclusive biomarkers, specific chemotypes, intraspecific metabolite profile variation, and metabolite enrichment by a case study of five medicinal species of Salvia.
METHODS: Aerial parts of each species were subjected to QTRAP liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis workflow based on untargeted metabolites. A comprehensive and multivariate analysis was acquired on the metabolite dataset utilizing MetaboAnalyst 6.0 and the Global Natural Products Social Molecular Networking (GNPS) Web Platform.
RESULTS: The untargeted approach empowered the identification of 117 metabolites by library matching and 92 nodes annotated by automated matching. A machine learning algorithm as substructural topic modeling, MS2LDA, was further implemented to explore the metabolite substructures, resulting in four Mass2Motifs. The automated library newly discovered a total of 23 metabolites. In addition, 87 verified biomarkers of library matching, 58 biomarkers of GNPS annotations, and 11 specific chemotypes were screened.
CONCLUSIONS: Integrative spectral library matching and automated annotation by the GNPS platform provide comprehensive metabolite profiling through a workflow. In addition, QTRAP LC-MS/MS with multivariate analysis unveiled reliable information about inter and intraspecific levels of differentiation. The rigorous investigation of metabolite profiling presents a large-scale overview and new insights for chemotaxonomy and pharmaceutical studies.

Carfilzomib (CFZ) is the second-generation proteasome inhibitor that is approved by Food and Drug Administration (FDA) of USA for the treatment of relapsed and refractory multiple myeloma. Although the preclinical and clinical efficacy of CFZ is obvious, the mechanism by which CFZ leads to cell death has not been fully elucidated. Since CFZ primarily functions as a proteasome inhibitor, profiling CFZ-induced changes in protein turnover at the systematic level is sufficient and necessary. In this study, we characterize the effects of CFZ on the stability of 15,000 human proteins using Protein Turnover Assay (ProTA). CFZ affects fundamental cellular glycolysis, nitric oxide production and proteasome subunit homeostasis in multiple myeloma cells. In addition, LY294002 or KU-0063794 has synergistic effects with CFZ in multiple myeloma treatment. A profound understanding of how cells respond to chemotherapeutic agents provides insights into the basic mechanism of drug function and the rationale for CFZ combination therapy.

Amplicon sequencing stands as a cornerstone in microbiome profiling, yet concerns persist regarding its resolution and accuracy. The enhancement of reference databases and annotations marks a new era for 16S rRNA-based profiling. Capitalizing on this potential, we introduce PM-profiler, a novel tool for profiling amplicon short reads. PM-profiler is implemented by C++-based advanced algorithms, such as pre-allocated hash for reference construction, hybrid and dynamic short-read matching, big-data-guided dual-mode hierarchical taxonomy annotation strategy, and full-procedure parallel computing. This tool delivers species-level resolution and ultrafast speed for large-scale microbiomes, surpassing alignment-based approaches and the Naïve-Bayesian model. Furthermore, recognizing the global uneven distribution of microbes, we delineate optimal annotation strategies for each sampling habitat based on microbial patterns over 270,000 microbiomes. Integrated with the established workflow of Parallel-Meta Suite and the latest curated reference databases, this endeavor offers a swift and dependable solution for high-precision microbiome surveys.IMPORTANCEOur study introduces PM-profiler, a new tool that deciphers the complexity of microbial communities. With advanced algorithms, flexible annotation strategies, and well-organized big-data, PM-profiler provides a faster and more accurate way to study on microbiomes, paving the way for discoveries that could improve our understanding of microbiomes and their impact on the world.

The release of danger signals from tissues in response to trauma during cardiac surgery creates conditions to reprogram the immune system to subsequent challenges posed by pathogens in the postoperative period. To demonstrate this, we tested immunoreactivity before surgery as the baseline (tbaseline), followed by subsequent challenges during the acute phase (t24h), convalescence (t7d), and long-term recovery (t3m). For 108 patients undergoing elective heart surgery, whole blood was stimulated with lipopolysaccharide (LPS), Influenza A virus subtype N2 (H3N2), or the Flublok™ vaccine to represent common pathogenic challenges. Leukocytosis, platelet count, and serum C-reactive protein (CRP) were used to measure non-specific inflammation. Cytokines were measured after 18 h of stimulation to reflect activation of the various cell types (activated neutrophils-IL-8; activated T cells-IL-2, IFNγ, activated monocyte (MO)-TNFα, IL-6, and deactivated or atypically activated MO and/or T cells-M-CSF, IL-10). IL-2 and IL-10 were increased at t7d, while TNFα was suppressed at t24h when LPS was utilized. Interestingly, M-CSF and IL-6 production was elevated at seven days in response to all stimuli compared to baseline. While some non-specific markers of inflammation (white cell count, IL-6, and IL-8) returned to presurgical levels at t3m, CRP and platelet counts remained elevated. We showed that surgical stimulus reprograms leukocyte response to LPS with only partial restoration of non-specific markers of inflammation.

The gut microbiome is of tremendous relevance to human health and disease, so it is a hot topic of omics-driven biomedical research. However, a valid identification of gut microbiota-associated molecules in human blood or urine is difficult to achieve. We hypothesize that bowel evacuation is an easy-to-use approach to reveal such metabolites. A non-targeted and modifying group-assisted metabolomics approach (covering 40 types of modifications) was applied to investigate urine samples collected in two independent experiments at various time points before and after laxative use. Fasting over the same time period served as the control condition. As a result, depletion of the fecal microbiome significantly affected the levels of 331 metabolite ions in urine, including 100 modified metabolites. Dominating modifications were glucuronidations, carboxylations, sulfations, adenine conjugations, butyrylations, malonylations, and acetylations. A total of 32 compounds, including common, but also unexpected fecal microbiota-associated metabolites, were annotated. The applied strategy has potential to generate a microbiome-associated metabolite map (M3) of urine from healthy humans, and presumably also other body fluids. Comparative analyses of M3 vs. disease-related metabolite profiles, or therapy-dependent changes may open promising perspectives for human gut microbiome research and diagnostics beyond analyzing feces.

Mosquitoes of many species are key disease vectors, killing millions of people each year. Bacillus thuringiensis-based insecticide formulations are largely recognized as among the most effective, ecologically safe, and long-lasting methods of managing insect pests. New B. thuringiensis strains with high mosquito control effectiveness were isolated, identified, genetically defined, and physiologically characterized. Eight B. thuringiensis strains were identified and shown to carry endotoxin-producing genes. Using a scanning electron microscope, results revealed typical crystal forms of various shapes in B. thuringiensis strains. Fourteen cry and cyt genes were found in the strains examined. Although the genome of the B. thuringiensis A4 strain had twelve cry and cyt genes, not all of them were expressed, and only a few protein profiles were observed. The larvicidal activity of the eight B. thuringiensis strains was found to be positive (LC50: 1.4-28.5 g/ml and LC95: 15.3-130.3 g/ml). Bioassays in a laboratory environment demonstrated that preparations containing B. thuringiensis spores and crystals were particularly active to mosquito larvae and adults. These new findings show that the novel preparation containing B. thuringiensis A4 spores and crystals mixture might be used to control larval and adult mosquitoes in a sustainable and ecologically friendly manner.

Electro-Fenton (EF) process represents an energy-efficient and scalable advanced oxidation technology (AOT) for micropollutants removal in wastewaters. However, mechanistic profiling and quantitation of contribution of each subprocess (i.e., adsorption at electrode, coagulation, radical oxidation, electrode oxidation/reduction, and H2O2 oxidation) to the overall degradation are substantially unclear, resulting in difficulty in tunability and optimization for different treatment scenarios. In this study, we investigated degradation kinetics of a target micropollutant in an EF system. The contribution of all possible subprocesses was elucidated by comparing the observed degradation rate in the EF system with the sum of the kinetics in each subprocess. The results indicated that the overall degradation can be attributed to the synergistic action of the above-mentioned subprocesses. The radical oxidation accounts for 87% elimination, followed by electrode reoxidation/reduction of 7.7%. These results not only advance the fundamental understanding of synergistic effect in EF system, but also open new possibilities to optimize these techniques for better scalability. In addition, the methodology in this study could potentially boost the in-depth exploration of subprocess contribution in other Fenton-like systems.

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This study initially reported the selection and characterization of 17 unknown impurities attributed to the manufacture process of ketamine. A total of 150 seized ketamine samples were investigated through ultra-high-performance liquid chromatography-quadrupole-time of flight (UHPLC-Q-TOF). Seventeen characteristic impurities were selected in accordance with four criteria: The compound was detected in over 10% of all 150 seized ketamine samples, the compound had at least one nitrogen, the unsaturation of the compound was more than 5, and the compound was stable in the dilution solvent solution for 48 h. The accurate masses of the protonated molecules and product ions of the target impurities were obtained based on the full scan mode and the product ion mode of Q-TOF, respectively. Lastly, the possible structures of the above impurities were tentatively elucidated in accordance with the synthetic route of ketamine, protonated molecules, and MS2 product ions. All 17 impurities had the same skeleton of deschloroketamine (DCK), but were substituted with additional chlorine, hydroxyl, methyl, cyclohexane, and o-chlorophenyl cyclopentyl ketone substituents. Under the electrospray ionization (ESI), the above impurities showed similar characteristic fragment ions through the dissociation of the CH3NH2, C2H6NH, H2O, CO, C2H4O, C4H6, and C2H2 moieties. The above impurities have been routinely used for the profiling analysis of seized ketamine samples in the National Narcotics Laboratory of China and employed to establish the tactical intelligence for law enforcement agencies.

Profiles of citrus juice oxygenated heterocyclic aglycones (OHAs), which are notable marker secondary metabolites, were used to assess the authenticity of sweet orange and grapefruit juices in situations where mandarin and pomelo juices might be adulterants. Thirty-nine known OHAs, including 10 methoxyflavones, 13 coumarins, and 16 furanocoumarins, as well as 13 tentatively screened OHAs, were analyzed in orange, mandarin, grapefruit and pomelo juices using our newly developed high-resolution HPLC-UV and fluorescence detection method. Quantitative OHA profiles from 158 pure juice samples were obtained to establish a purity discriminant model using an omics strategy. Reduction of OHA variables showed that three important methoxyflavones, i.e. isosinensetin, tangeretin and sinensetin provided the best discrimination ability between sweet orange and mandarin juices. There are two subtypes of pomelos, Shatianyou Group and Wendan Group, of which juices should be separately compared to grapefruit juice. Five OHAs, namely meranzin, 3,5,6,7,8,3\',4\'-heptamethoxyflavone, osthole, 6\',7\'-epoxybergamottin, and bergamottin were found to discriminate Shatianyou Group of pomelo juice from grapefruit juice; whereas three OHAs, namely bergaptol, isomeranzin, and 6\',7\'-dihydroxybergamottin were able to discriminate Wendan Group of pomelo juice from grapefruit juice. The established partial least squares discriminant analysis (PLS-DA) models were capable of detecting as little as 10% mandarin juice in sweet orange juice and 10% pomelo juice in grapefruit juice, allowing for fast prescreening of excess addition with good reliability (root mean square error of prediction, RMSEP < 5%).