Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants

Metabolomics is an ‘omics’ approach that aims to analyze all metabolites in a biological sample comprehensively. The detailed metabolite profiling of thousands of plant samples has great potential for directly elucidating plant metabolic processes. However, both a comprehensive analysis and a high throughput are difficult to achieve at the same time due to the wide diversity of metabolites in plants. Here, we have established a novel and practical metabolomics methodology for quantifying hundreds of targeted metabolites in a high-throughput manner. Multiple reaction monitoring (MRM) using tandem quadrupole mass spectrometry (TQMS), which monitors both the specific precursor ions and product ions of each metabolite, is a standard technique in targeted metabolomics, as it enables high sensitivity, reproducibility and a broad dynamic range. In this study, we optimized the MRM conditions for specific compounds by performing automated flow injection analyses with TQMS. Based on a total of 61,920 spectra for 860 authentic compounds, the MRM conditions of 497 compounds were successfully optimized. These were applied to high-throughput automated analysis of biological samples using TQMS coupled with ultra performance liquid chromatography (UPLC). By this analysis, approximately 100 metabolites were quantified in each of 14 plant accessions from Brassicaceae, Gramineae and Fabaceae. A hierarchical cluster analysis based on the metabolite accumulation patterns clearly showed differences among the plant families, and family-specific metabolites could be predicted using a batch-learning self-organizing map analysis. Thus, the automated widely targeted metabolomics approach established here should pave the way for large-scale metabolite profiling and comparative metabolomics

Proteotyping of <i>Campylobacter jejuni</i> by MALDI-TOF MS and Strain Solution Version 2 Software

Identification of microorganisms by MALDI-TOF MS has become a popular method in the past 20 years. Strain Solution ver. 2 software appended with MALDI-TOF MS enables accurate discrimination of serotypes and strains beyond the genus and species level by creating a theoretical mass-based database. In this study, we constructed a theoretical mass database with the validated biomarkers to proteotype Campylobacter jejuni. Using 10 strains belonging to Campylobacter spp. available from culture collections and 41 Campylobacter jejuni strains isolated from humans and foods, the ribosomal protein subunits L36, L32, S14, L24, L23, L7/L12, and S11 could be selected as the effective biomarkers for the proteotyping of C. jejuni at MALDI-TOF MS. An accurate database of their theoretical mass-based values was constructed by matching these gene DNA sequences and the observed mass peaks. We attempted to automatically classify 41 strains isolated from nature using this database and Strain Solution ver. 2 software, and 38 strains (93%) were correctly classified into the intended group based on the theoretical mass-based values. Thus, the seven biomarkers found in this study and Strain Solution ver. 2 are promising for the proteotyping of C. jejuni by MALDI-TOF MS

Metabolic intervention by low carbohydrate diet suppresses the onset and progression of neuroendocrine tumors

Abstract Insulin signaling often plays a role in the regulation of cancer, including tumor initiation, progression, and response to treatment. In addition, the insulin-regulated PI3K-Akt-mTOR pathway plays an important role in the regulation of islet cell proliferation, and this pathway is hyperactivated in human non-functional pancreatic neuroendocrine tumors (PanNETs). We, therefore, investigated the effect of a very low carbohydrate diet (ketogenic diet) on a mouse model that develops non-functional PanNETs to ask how reduced PI3K-Akt-mTOR signaling might affect the development and progression of non-functional PanNET. We found that this dietary intervention resulted in lower PI3K-Akt-mTOR signaling in islet cells and a significant reduction in PanNET formation and progression. We also found that this treatment had a significant effect on the suppression of pituitary NET development. Furthermore, we found that non-functional PanNET patients with lower blood glucose levels tend to have a better prognosis than patients with higher blood glucose levels. This preclinical study shows that a dietary intervention that results in lower serum insulin levels leads to lower insulin signals within the neuroendocrine cells and has a striking suppressive effect on the development and progression of both pancreatic and pituitary NETs

Arabidopsis Bile Acid:Sodium Symporter Family Protein 5 is Involved in Methionine-Derived Glucosinolate Biosynthesis

Glucosinolates (GSLs) are a group of plant secondary metabolites that have repellent activity against herbivore insects and pathogens, and anti-carcinogenic activity in humans. They are produced in plants of the Brassicaceae and other related families. Biosynthesis of GSLs from precursor amino acids takes place in two subcellular compartments; amino acid biosynthesis and side chain elongation occur mainly in the chloroplast, whereas the following core structure synthesis takes place in the cytosol. Although the genes encoding biosynthetic enzymes of GSLs are well known in Arabidopsis thaliana, the transporter genes responsible for translocation of biosynthetic intermediates between the chloroplast and cytosol are as yet unidentified. In this study, we identified the bile acid:sodium symporter family protein 5 (BASS5) gene in Arabidopsis as a candidate transporter gene involved in methionine-derived GSL (Met-GSL) biosynthesis by means of transcriptome co-expression analysis. Knocking out BASS5 resulted in a decrease of Met-GSLs and concomitant increase of methionine. A transient assay using fluorescence fusion proteins indicated a chloroplastic localization of BASS5. These results supported the idea that BASS5 plays a role in translocation across the chloroplast membranes of the biosynthetic intermediates of Met-GSLs

Direct measurement of the 7Be(n, α)4 He reaction cross sections for the cosmological Li problem

The cross sections of the 7Be(n, α)4He reaction for p-wave neutrons were experimentally determined at Ec.m. = 0.20−0.81 MeV close to the Big Bang nucleosynthesis (BBN) energy window for the first time on the basis of the detailed balance principle by measuring the time-reverse reaction. The obtained cross sections are much larger than the cross sections for s-wave neutrons inferred from the recent measurement at the n_TOF facility in CERN, but significantly smaller than the theoretical estimation widely used in the BBN calculations. The present results suggest the 7Be(n, α)4 He reaction rate is not large enough to solve the cosmological lithium proble

Direct measurement of the

The cross sections of the 7Be(n, α)4He reaction for p-wave neutrons were experimentally determined at Ec.m. = 0.20−0.81 MeV close to the Big Bang nucleosynthesis (BBN) energy window for the first time on the basis of the detailed balance principle by measuring the time-reverse reaction. The obtained cross sections are much larger than the cross sections for s-wave neutrons inferred from the recent measurement at the n_TOF facility in CERN, but significantly smaller than the theoretical estimation widely used in the BBN calculations. The present results suggest the 7Be(n, α)4 He reaction rate is not large enough to solve the cosmological lithium proble

Omics-Based Approaches to Methionine Side Chain Elongation in Arabidopsis: Characterization of the Genes Encoding Methylthioalkylmalate Isomerase and Methylthioalkylmalate Dehydrogenase

Glucosinolates (GSLs) are secondary metabolites in Brassicaceae plants synthesized from amino acids. Methionine-derived GSLs (Met-GSLs) with diverse side chains of various lengths are the major GSLs in Arabidopsis. Methionine chain elongation enzymes are responsible for variations in chain length in Met-GSL biosynthesis. The genes encoding methionine chain elongation enzymes are considered to have been recruited from the leucine biosynthetic pathway in the course of evolution. Among them, the genes encoding methylthioalkylmalate synthases and aminotransferases have been identified; however, the remaining genes that encode methylthioalkylmalate isomerase (MAM-I) and methylthioalkylmalate dehydro-genase (MAM-D) remain to be identified. In a previous study based on transcriptome co-expression analysis, we identified candidate genes for the large subunit of MAM-I and MAM-D. In this study, we confirmed their predicted functions by targeted GSL analysis of the knockout mutants, and named the respective genes MAM-IL1/AtleuC1 and MAM-D1/AtIMD1. Metabolic profiling of the knockout mutants of methionine chain elongation enzymes, conducted by means of widely targeted metabolomics, implied that these enzymes have roles in controlling metabolism from methionine to primary and methionine-related secondary metabolites. As shown here, an omics-based approach is an efficient strategy for the functional elucidation of genes involved in metabolism