Published papers

Lipids are prominent components of the nervous system. Here we performed a large-scale mass spectrometry-based analysis of the lipid composition of three brain regions as well as kidney and skeletal muscle of humans, chimpanzees, rhesus macaques, and mice. The human brain shows the most distinct lipid composition: 76% of 5,713 lipid compounds examined in our study are either enriched or depleted in the human brain. Concentration levels of lipids enriched in the brain evolve approximately four times faster among primates compared with lipids characteristic of non-neural tissues and show further acceleration of change in human neocortical regions but not in the cerebellum. Human-specific concentration changes are supported by human-specific expression changes for corresponding enzymes. These results provide the first insights into the role of lipids in human brain evolution.

The genus Balticola comprises a group of unicellular green flagellate algae and is composed of four species formerly classified in the genus Haematococcus. Balticola is closely related to a colonial green flagellate, Stephanosphaera pluvialis. Although the phylogeny among these genera was previously investigated based on two nuclear gene sequences, the phylogenetic sister of S. pluvialis has yet to be determined. In the present study, the species diversity of Balticola and Stephanosphaera was investigated using 18S rRNA gene sequences, and phylogenetic analyses of combined nuclear and chloroplast gene sequences were performed to understand the evolutionary origin of coloniality in Stephanosphaera. The divergence times of four colonial volvocalean flagellates from their respective unicellular sisters were also estimated. Six Balticola genotypes and a single Stephanosphaera genotype were recognized, and one Balticola genotype was resolved as the sister of S. pluvialis, showing that Balticola is a nonmonophyletic genus. The divergence time of Stephanosphaera from its nearest Balticola relative was estimated to be 4-63 million years ago, and these genera represent the most recently diverged pair of unicellular and colonial flagellates among the Volvocales.

Aphid infection reduces soybean (Glycine max [L.] Merr.) yield. Consequently, cultivation of aphid-resistant strains is a promising approach to pest control, and understanding the resistance mechanism is of importance. Here, we characterized the resistance of soybeans to foxglove aphid, Aulacorthum solani Kaltenbach, at the metabolite level. First, we evaluated aphid mortality and settlement rates on the leaves of two soybean strains, 'Tohoku149' and 'Suzuyutaka', and found that the former had strong resistance soon after introduction of the aphids. The metabolomic response to aphid introduction was analyzed using capillary electrophoresis-time-of-flight mass spectrometry. We found the following three features in the profiles: (1) concentrations of citrate, amino acids, and their intermediates were intrinsically higher for Tohoku149 than Suzuyutaka, (2) concentrations of several metabolites producing secondary metabolites, such as flavonoids and alkaloids, drastically changed 6. h after aphid introduction, and (3) concentrations of TCA cycle metabolites increased in Tohoku149 48. h after aphid introduction. We also profiled free amino acids in aphids reared on both soybean strains and under starvation, and found that the profile of the aphids on Tohoku149 was similar to that of the starved aphids, but different to that of aphids on Suzuyutaka. These tests confirmed that aphids suck phloem sap even from Tohoku149. This study demonstrates the metabolomic profiles of both soybean strains and aphids, which will contribute to the molecular level understanding of mechanisms of soybean resistance to aphids. © 2013 Elsevier B.V.

Metabolic microenvironment of tumor cells is influenced by oncogenic signaling and tissue-specific metabolic demands, blood supply, and enzyme expression. To elucidate tumor-specific metabolism, we compared the metabolomics of normal and tumor tissues surgically resected pairwise from nine lung and seven prostate cancer patients, using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). Phosphorylation levels of enzymes involved in central carbon metabolism were also quantified. Metabolomic profiles of lung and prostate tissues comprised 114 and 86 metabolites, respectively, and the profiles not only well distinguished tumor from normal tissues, but also squamous cell carcinoma from the other tumor types in lung cancer and poorly differentiated tumors from moderately differentiated tumors in prostate cancer. Concentrations of most amino acids, especially branched-chain amino acids, were significantly higher in tumor tissues, independent of organ type, but of essential amino acids were particularly higher in poorly differentiated than moderately differentiated prostate cancers. Organ-dependent differences were prominent at the levels of glycolytic and tricarboxylic acid cycle intermediates and associated energy status. Significantly high lactate concentrations and elevated activating phosphorylation levels of phosphofructokinase and pyruvate kinase in lung tumors confirmed hyperactive glycolysis. We highlighted the potential of CE-TOFMS-based metabolomics combined with phosphorylated enzyme analysis for understanding tissue-specific tumor microenvironments, which may lead to the development of more effective and specific anticancer therapeutics. © 2012 The Author(s).

Oil-rich algae have promising potential for a next-generation biofuel feedstock. Pseudochoricystis ellipsoidea MBIC 11204, a novel unicellular green algal strain, accumulates a large amount of oil (lipids) in nitrogen-deficient (-N) conditions. Although the oil bodies are easily visualized by lipophilic staining in the cells, little is known about how oil bodies are metabolically synthesized. Clarifying the metabolic profiles in -N conditions is important to understand the physiological mechanisms of lipid accumulations and will be useful to optimize culture conditions efficiently produce industrial oil. Metabolome and lipidome profiles were obtained, respectively, using capillary electrophoresis- and liquid chromatography-mass spectrometry from P. ellipsoidea in both nitrogen-rich (+N; rapid growth) and -N conditions. Relative quantities of more than 300 metabolites were systematically compared between these two conditions. Amino acids in nitrogen assimilation and N-transporting metabolisms were decreased to 1/20 the amount, or less, in -N conditions. In lipid metabolism, the quantities of neutral lipids increased greatly in -N conditions; however, quantities of nearly all the other lipids either decreased or only changed slightly. The morphological changes in +N and -N conditions were also provided by microscopy, and we discuss their relationship to the metabolic changes. This is the first approach to understand the novel algal strain's metabolism using a combination of wide-scale metabolome analysis and morphological analysis. © 2012 The Author(s).

Pyruvate treatment was found to alleviate clinical symptoms of mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome and is highly promising therapeutic. Using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), we measured time-changes of 161 intracellular and 85 medium metabolites to elucidate metabolic effects of pyruvate treatment on cybrid human 143B osteosarcoma cells harboring normal (2SA) and MELAS mutant (2SD) mitochondria. The results demonstrated dramatic and sustainable effects of pyruvate administration on the energy metabolism of 2SD cells, corroborating pyruvate as a metabolically rational treatment regimen for improving symptoms associated with MELAS and possibly other mitochondrial diseases. © 2012 Elsevier B.V. and Mitochondria Research Society.

Capillary electrophoresis coupled with time-offlight mass spectrometry was used to explore new serum biomarkers with high sensitivity and specificity for diabetic nephropathy (DN) diagnosis, through comprehensive analysis of serum metabolites with 78 diabetic patients. Multivariate analyses were used for identification of marker candidates and development of discriminative models. Of the 289 profiled metabolites, orthogonal partial leastsquares discriminant analysis identified 19 metabolites that could distinguish between DN with macroalbuminuria and diabetic patients without albuminuria. These identified metabolites included creatinine, aspartic acid, γ-butyrobetaine, citrulline, symmetric dimethylarginine (SDMA), kynurenine, azelaic acid, and galactaric acid. Significant correlations between all these metabolites and urinary albumin-to-creatinine ratios (p<0.009, Spearman's rank test) were observed. When five metabolites (including γ-butyrobetaine, SDMA, azelaic acid and two unknowns) were selected from 19 metabolites and applied for multiple logistic regressionmodel, AUC value for diagnosing DN was 0.927 using the whole dataset, and 0.880 in a cross-validation test. In addition, when four known metabolites (aspartic acid, SDMA, azelaic acid and galactaric acid) were applied, the resulting AUC was still high at 0.844 with the whole dataset and 0.792 with cross-validation. Combination of serum metabolomics with multivariate analyses enabled accurate discrimination of DN patients. The results suggest that capillary electrophoresis-mass spectrometry based metabolome analysis could be used for DN diagnosis. © Springer-Verlag 2012.

It is of practical interest to investigate the effect of nitrates on bacterial metabolic regulation of both fermentation and energy generation, as compared to aerobic and anaerobic growth without nitrates. Although gene level regulation has previously been studied for nitrate assimilation, it is important to understand this metabolic regulation in terms of global regulators. In the present study, therefore, we measured gene expression using DNA microarrays, intracellular metabolite concentrations using CE-TOFMS, and metabolic fluxes using the 13C-labeling technique for wild-type E. coli and the ΔarcA (a global regulatory gene for anoxic response control, ArcA) mutant to compare the metabolic state under nitrate conditions to that under aerobic and anaerobic conditions without nitrates in continuous culture conditions at a dilution rate of 0.2 h-1. In wild-type, although the measured metabolite concentrations changed very little among the three culture conditions, the TCA cycle and the pentose phosphate pathway fluxes were significantly different under each condition. These results suggested that the ATP production rate was 29% higher under nitrate conditions than that under anaerobic conditions, whereas the ATP production rate was 10% lower than that under aerobic conditions. The flux changes in the TCA cycle were caused by changes in control at the gene expression level. In ΔarcA mutant, the TCA cycle flux was significantly increased (4.4 times higher than that of the wild type) under nitrate conditions. Similarly, the intracellular ATP/ADP ratio increased approximately two-fold compared to that of the wild-type strain. © 2012 The Royal Society of Chemistry.

One of the ultimate goals of systems biology research is to obtain a comprehensive understanding of the control mechanisms of complex cellular metabolisms. Metabolic Flux Analysis (MFA) is a important method for the quantitative estimation of intracellular metabolic flows through metabolic pathways and the elucidation of cellular physiology. The primary challenge in the use of MFA is that many biological networks are underdetermined systems; it is therefore difficult to narrow down the solution space from the stoichiometric constraints alone. In this tutorial, we present an overview of Flux Balance Analysis (FBA) and 13C-Metabolic Flux Analysis ( 13C-MFA), both of which are frequently used to solve such underdetermined systems, and we demonstrate FBA and 13C-MFA using the genome-scale model and the central carbon metabolism model, respectively. Furthermore, because such comprehensive study of intracellular fluxes is inherently complex, we subsequently introduce various pathway mapping and visualization tools to facilitate understanding of these data in the context of the pathways. Specific visualization of MFA results using the BioCyc Omics Viewer and Pathway Projector are shown as illustrative examples. © 2011 American Chemical Society.

Its high nutritional content and sensory characteristics make edamame a popular vegetable bean. However, because of its short shelf-life, it is important to optimize the storage conditions to maintain its quality during distribution to consumers. We focused on storage conditions to investigate the temporal changes in the metabolic profiles and sensory characteristics of edamame during transportation from the site of harvest to the site of purchase/consumption. We conducted metabolomic analysis and sensory evaluation tests of edamame stored for different lengths and at different temperatures. Charged metabolites were profiled by capillary electrophoresis-mass spectrometry, and free sugars were quantified by liquid chromatography-tandem mass spectrometry. In comparison to the gradual decrease in its sensory characteristics over time, the changes in metabolite profiles manifested four different patterns. In particular, changes in amino acid levels were related to sensory attributes. The downstream metabolites of shikimate as well as phospholipids and γ-aminobutyric acid increased with increasing storage temperatures. © 2010 American Chemical Society.

Dry-cured hams are popular among consumers. To increase the attractiveness of the product, objective analytical methods and algorithms to evaluate the relationship between observable properties and consumer acceptability are required. In this study, metabolomics, which is used for quantitative profiling of hundreds of small molecules, was applied to 12 kinds of drycured hams from Japan and Europe. In total, 203 charged metabolites, including amino acids, organic acids, nucleotides, and peptides, were successfully identified and quantified. Metabolite profiles were compared for the samples with different countries of origin and processing methods (e.g., smoking or use of a starter culture). Principal component analysis of the metabolite profiles with sensory properties revealed significant correlations for redness, homogeneity, and fat whiteness. This approach could be used to design new ham products by objective evaluation of various features.

Objective: Physical activity is known to be preventive against various non-communicable diseases. We investigated the relationship between daily physical activity level and plasma metabolites using a targeted metabolomics approach in a population-based study. Methods: A total of 1,193 participants (male, aged 35 to 74 years) with fasting blood samples were selected from the baseline survey of a cohort study. Information on daily total physical activity, classified into four levels by quartile of metabolic equivalent scores, and sedentary behavior, defined as hours of sitting per day, was collected through a self-administered questionnaire. Plasma metabolite concentrations were quantified by capillary electrophoresis mass spectrometry method. We performed linear regression analysis models with multivariable adjustment and corrected p-values for multiple testing in the original population (n = 808). The robustness of the results was confirmed by replication analysis in a separate population (n = 385) created by random allocation. Results: Higher levels of total physical activity were associated with various metabolite concentrations, including lower concentrations of amino acids and their derivatives, and higher concentrations of pipecolate (FDR p <0.05 in original population). The findings persisted after adjustment for age, body mass index, smoking, alcohol intake, and energy intake. Isoleucine, leucine, valine, 4-methyl-2-oxoisopentanoate, 2-oxoisopentanoate, alanine, and proline concentrations were lower with a shorter sitting time. Conclusions: Physical activity is related to various plasma metabolites, including known biomarkers for future insulin resistance or type 2 diabetes. These metabolites might potentially play a key role in the protective effects of higher physical activity and/or less sedentary behavior on non-communicable diseases.

Intravenous administration of high-dose vitamin C has recently attracted attention as a cancer therapy. High-dose vitamin C induces pro-oxidant effects and selectively kills cancer cells. However, the anticancer mechanisms of vitamin C are not fully understood. Here, we analyzed metabolic changes induced by vitamin C in MCF7 human breast adenocarcinoma and HT29 human colon cancer cells using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). The metabolomic profiles of both cell lines were dramatically altered after exposure to cytotoxic concentrations of vitamin C. Levels of upstream metabolites in the glycolysis pathway and tricarboxylic acid (TCA) cycle were increased in both cell lines following treatment with vitamin C, while adenosine triphosphate (ATP) levels and adenylate energy charges were decreased concentration-dependently. Treatment with N-acetyl cysteine (NAC) and reduced glutathione (GSH) significantly inhibited vitamin C-induced cytotoxicity in MCF7 cells. NAC also suppressed vitamin C-dependent metabolic changes, and NAD treatment prevented vitamin C-induced cell death. Collectively, our data suggests that vitamin C inhibited energy metabolism through NAD depletion, thereby inducing cancer cell death.

© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Main Conclusion: Among seaweed groups, brown algae had characteristically high concentrations of mannitol, and green algae were characterised by fructose. In red algae, metabolite profiles of individual species should be evaluated. Seaweeds are metabolically different from terrestrial plants. However, general metabolite profiles of the three major seaweed groups, the brown, red, and green algae, and the effect of various extraction methods on metabolite profiling results have not been comprehensively explored. In this study, we evaluated the water-soluble metabolites in four brown, five red, and two green algae species collected from two sites in northern Japan, located in the Sea of Japan and the Pacific Ocean. Freeze-dried seaweed samples were processed by methanol–water extraction with or without chloroform and analysed by capillary electrophoresis- and liquid chromatography-mass spectrometry for metabolite characterisation. The metabolite concentration profiles showed distinctive characteristic depends on species and taxonomic groups, whereas the extraction methods did not have a significant effect. Taxonomic differences between the various seaweed metabolite profiles were well defined using only sugar metabolites but no other major compound types. Mannitol was the main sugar metabolites in brown algae, whereas fructose, sucrose, and glucose were found at high concentrations in green algae. In red algae, individual species had some characteristic metabolites, such as sorbitol in Pyropia pseudolinearis and panose in Dasya sessilis. The metabolite profiles generated in this study will be a resource and provide guidance for nutraceutical research studies because the information about metabolites in seaweeds is still very limited compared to that of terrestrial plants.

© 2018 American Chemical Society. Metabolome analysis using capillary electrophoresis (CE) coupled with high-resolution mass spectrometry (HRMS) has the potential to improve coverage of metabolite detection because of its high selectivity and sensitivity. Configuration of the interface between CE and HRMS to meet the ground connection is essential for enabling independent regulation of the electrical currents in the CE and electrospray field. In the present study, we applied an electrospray-ionization adapter equipped with a grounded nebulizer to CE-HRMS and tested the analytical performance for 34 charged compounds. The extracted-ion electropherograms, consisting of seven sets of isomers, showed reasonable peak shapes and separation for the annotation of each metabolite. The levels of 34 target analytes in a standard mixture were determined with a dynamic range of at least 10 2 , maintaining linearity with r 2 > 0.9. The repeatability and intermediate precision above the lower limit of quantification showed the relative standard deviation to be lower than 20%. In the spike-recovery experiment, 27 of the 34 metabolites in plasma extract were recovered at a rate of 80 to 120%, suggesting high accuracy. Furthermore, we assessed the feasibility of our platform in metabolome analysis using human-plasma extract. The results showed successful detection of 270 metabolites, indicating the potential of our platform to yield higher coverage of the metabolome. In addition, analysis of dilution integrity demonstrated the quantitative ability of metabolome analysis with CE-HRMS, although the existence of saturation or matrix effects were seen in the case of 33 of the metabolites. This study indicates that our platform has great potential for large-scale metabolome analysis of plasma for biological studies and clinical biomarker screening.

Objective: Metabolomics is a promising approach to the identification of biomarkers in plasma. Here, we performed a population-based, cross-sectional study to identify potential biomarkers of alcohol intake and alcohol-induced liver injury by metabolomic profiling using capillary electrophoresis-mass spectrometry (CE-MS). Methods: Fasting plasma samples were collected from 896 Japanese men who participated in the baseline survey of the Tsuruoka Metabolomics Cohort Study, and 115 polar metabolites were identified and absolutely quantified by CE-MS. Information on daily ethanol intake was collected through a standardized, self-administered questionnaire. The associations between ethanol intake and plasma concentration of metabolites were examined. Relationships between metabolite concentrations or their ratios and serum liver enzyme levels in the highest ethanol intake group (>46.0 g/day) were then examined by linear regression analysis. Replication analysis was conducted in 193 samples collected from independent population of this cohort. Results: Nineteen metabolites were identified to have an association with daily alcohol consumption both in the original and replication population. Three of these metabolites (threonine, glutamine, and guanidinosuccinate) were found to associate well with elevated levels of serum liver enzymes in the highest ethanol intake group, but not in the non-drinker group. We also found that the glutamate/glutamine ratio had a much stronger relation to serum γ-glutamyltransferase, aspartate transaminase, and alanine transaminase than glutamate or glutamine alone (standardized beta = 0.678, 0.558, 0.498, respectively). Conclusions: We found 19 metabolites associated with alcohol intake, and three biomarker candidates (threonine, guanidinosuccinate and glutamine) of alcohol-induced liver injury. Glutamate/glutamine ratio might also be good biomarker.

Recently, the extremely thermophilic bacterium Thermus thermophilus HB8 has been demonstrated to harbor a circular plasmid designated by pVV8 in addition to two well-known plasmids, pTT8 and pTT27, and its entire sequence has been determined. The absence of any obvious replication initiation gene in the 81. 2 kb plasmid prompted us to isolate its minimum replicon. By in vivo replication assays with fragments deleted in a stepwise manner, a minimum replicon containing a single ORF, TTHV001, was identified. A protein encoded by TTHV001 showed no amino acid sequence similarity to other function-known proteins. As the results of in vivo and in vitro experiments strongly suggested that the TTHV001 protein was involved in the replication initiation of pVV8, the protein and the gene were referred to as RepV and repV, respectively. The RepV protein binds to an inverted repeat sequence within its own repV gene and then triggers the unwinding of the DNA duplex in an A + T-rich region located just downstream from the inverted repeat. The in vivo replication assays with minimum replicon mutants in the RepV binding site or the unwinding region demonstrated that the unwinding in the region by the RepV binding was essential for pVV8 replication initiation. © 2012 Springer Japan.

The central dogma of molecular biology has come under scrutiny in recent years. Here, we reviewed high-throughput mRNA and protein expression data of Escherichia coli, Saccharomyces cerevisiae, and several mammalian cells. At both single cell and population scales, the statistical comparisons between the entire transcriptomes and proteomes show clear correlation structures. In contrast, the pair-wise correlations of single transcripts to proteins show nullity. These data suggest that the organizing structure guiding cellular processes is observed at omics-wide scale, and not at single molecule level. The central dogma, thus, globally emerges as an average integrated flow of cellular information. © 2012 Piras, Tomita and Selvarajoo.

We have developed a novel bioinformatics method called mass spectrum sequential subtraction (MSSS) to search large peptide spectra datasets produced by liquid chromatography/mass spectrometry (LC-MS/MS) against protein and large-sized nucleotide sequence databases. The main principle in MSSS is to search the peptide spectra set against the protein database, followed by removal of the spectra corresponding to the identified peptides to create a smaller set of the remaining peptide spectra for searching against the nucleotide sequences database. Therefore, we reduce the number of spectra to be searched to limit the peptide search space. Comparing MSSS and conventional search approach using a dataset of 27 LC-MS/MS runs of rice culture cells indicated that MSSS reduced the search queries to 50% and the search time to 75% on average. In addition, MSSS had no effect on the identification false-positive rate (FPR) or the novel peptide sequences identification ability. We used MSSS to analyze another dataset of 34 LC-MS/MS runs, resulting in identifying additional 74 novel peptides. Proteogenomic analysis with these additional peptides yielded 47 new genomic features in 24 rice genes plus 24 intergenic peptides. These results show that the utility of MSSS in searching large databases with large MS/MS datasets for proteogenomics. © 2012 The Authors Journal compilation © 2012 by the Molecular Biology Society of Japan/Blackwell Publishing Ltd.