Nontargeted Serum Lipid Profiling of Nonalcoholic Steatohepatitis by Multisegment Injection-Nonaqueous Capillary Electrophoresis-Mass Spectrometry: A Multiplexed Separation Platform for Resolving Ionic Lipids.

New methods are needed for global lipid profiling due to the complex chemical structures and diverse physicochemical properties of lipids. Herein we introduce a robust data workflow to unambiguously select lipid features from serum ether extracts by multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS). An iterative three-stage screening strategy is developed for nontargeted lipid analyses when using multiplexed electrophoretic separations coupled to an Orbitrap mass analyzer under negative ion mode. This approach enables the credentialing of 270 serum lipid features annotated based on their accurate mass and relative migration time, including 128 ionic lipids reliably measured (median CV ≈ 13%) in most serum samples (>75%) from nonalcoholic steatohepatitis (NASH) patients (n = 85). A mobility map is introduced to classify charged lipid classes over a wide polarity range with selectivity complementary to chromatographic separations, including lysophosphatidic acids, phosphatidylcholines, phosphatidylinositols, phosphatidylethanolamines, and nonesterified fatty acids (NEFAs). Serum lipidome profiles were also used to differentiate high- from low-risk NASH patients using a k-means clustering algorithm, where elevated circulating NEFAs (e.g., palmitic acid) were associated with increased glucose intolerance, more severe liver fibrosis, and greater disease burden. MSI-NACE-MS greatly expands the metabolome coverage of conventional aqueous-based CE-MS protocols and is a promising platform for large-scale lipidomic studies.

High Throughput Screening of Serum γ-Glutamyl Dipeptides for Risk Assessment of Nonalcoholic Steatohepatitis with Impaired Glutathione Salvage Pathway.

Nonalcoholic fatty liver disease (NAFLD) is the most common preventable chronic liver disorder in developed countries, the prevalence of which is increasing worldwide due to its association with obesity and type 2 diabetes. However, the exact mechanisms of NAFLD pathophysiology remain poorly understood including its progression to the more severe nonalcoholic steatohepatitis (NASH). New advances for early detection and monitoring of NASH progression are limited due to the lack of specific blood biomarkers, thus requiring invasive liver biopsies for histopathology. Herein, multisegment injection-capillary electrophoresis-tandem mass spectrometry (MSI-CE-MS/MS) is validated as a high throughput, robust, and quantitative platform for targeted analysis of a panel of 16 serum γ-glutamyl dipeptides from a cohort of NASH adult patients from Japan (median age = 53 years, median BMI = 27 kg/m2, n = 116). Multiplexed separations based on MSI-CE-MS/MS enable the design of unique data workflows that rely on customizable serial sample injection formats for accurate determination of γ-glutamyl dipeptides with quality control. Also, the introduction of a liquid coolant device to the capillary outlet improves long-term migration time stability in CE. Unsupervised pattern recognition methods revealed two distinctive NASH subgroups based on their contrasting γ-glutamyl dipeptide status despite patients having similar clinical phenotypes and NASH activity scores (median NAS ≈ 6.0). There was an inverse correlation between serum γ-glutamyl dipeptide concentrations and γ-glutamyltransferease (GGT) enzyme activity (r = -0.46; p = 2.5 × 10-7), which was indicative of a low-risk (n = 64) as compared to a high-risk (n = 52) patient subgroup with impaired glutathione salvage pathway and likely poor clinical prognosis. Our findings highlight the key role of defects in the γ-glutamyl cycle for differentiation of NASH patients, which may enable better risk assessment of long-term survivorship as a complement to standard liver enzyme screens and histopathology.

Metabolomic profiling of gastric cancer tissues identified potential biomarkers for predicting peritoneal recurrence.

BACKGROUND: Metabolomics is useful for analyzing the nutrients necessary for cancer progression, as the proliferation is regulated by available nutrients. We studied the metabolomic profile of gastric cancer (GC) tissue to elucidate the associations between metabolism and recurrence. METHODS: Cancer and adjacent non-cancerous tissues were obtained in a pair-wise manner from 140 patients with GC who underwent gastrectomy. Frozen tissues were homogenized and analyzed by capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). Metabolites were further assessed based on the presence or absence of recurrence. RESULTS: Ninety-three metabolites were quantified. In cancer tissues, the lactate level was significantly higher and the adenylate energy charge was lower than in non-cancerous tissues. The Asp, ß-Ala, GDP, and Gly levels were significantly lower in patients with recurrence than in those without. Based on ROC analyses to determine the cut-off values of the four metabolites, patients were categorized into groups at high risk and low risk of peritoneal recurrence. Logistic regression and Cox proportional hazard analyses identified ß-Ala as an independent predictor of peritoneal recurrence (hazard ratio [HR] 5.21 [95% confidence interval 1.07-35.89], p = 0.029) and an independent prognostic factor for the overall survival (HR 3.44 [95% CI 1.65-7.14], p < 0.001). CONCLUSIONS: The metabolomic profiles of cancer tissues differed from those of non-cancerous tissues. In addition, four metabolites were significantly associated with recurrence in GC. ß-Ala was both a significant predictor of peritoneal recurrence and a prognostic factor.

Metabolomics Platform with Capillary Electrophoresis Coupled with High-Resolution Mass Spectrometry for Plasma Analysis.

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 102, maintaining linearity with r2 > 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.

Taxonomic classification for microbiome analysis, which correlates well with the metabolite milieu of the gut.

BACKGROUND: 16S rRNA gene amplicon sequencing analysis (16S amplicon sequencing) has provided considerable information regarding the ecology of the intestinal microbiome. Recently, metabolomics has been used for investigating the crosstalk between the intestinal microbiome and the host via metabolites. In the present study, we determined the accuracy with which 16S rRNA gene data at different classification levels correspond to the metabolome data for an in-depth understanding of the intestinal environment. RESULTS: Over 200 metabolites were identified using capillary electrophoresis and time-of-flight mass spectrometry (CE-TOFMS)-based metabolomics in the feces of antibiotic-treated and untreated mice. 16S amplicon sequencing, followed by principal component analysis (PCA) of the intestinal microbiome at each taxonomic rank, revealed differences between the antibiotic-treated and untreated groups in the first principal component in the family-, genus, and species-level analyses. These differences were similar to those observed in the PCA of the metabolome. Furthermore, a strong correlation between principal component (PC) scores of the metabolome and microbiome was observed in family-, genus-, and species-level analyses. CONCLUSIONS: Lower taxonomic ranks such as family, genus, or species are preferable for 16S amplicon sequencing to investigate the correlation between the microbiome and metabolome. The correlation of PC scores between the microbiome and metabolome at lower taxonomic levels yield a simple method of integrating different "-omics" data, which provides insights regarding crosstalk between the intestinal microbiome and the host.

Plasma metabolome analysis of patients with major depressive disorder.

AIM: This study sought to characterize the plasma metabolite profiling of patients with major depressive disorder (MDD). METHODS: Psychiatric assessments were made with the Structured Clinical Interview for DSM-IV Axis I Disorders. In the exploratory cohort, plasma metabolite profiles of 34 MDD patients and 31 mentally healthy controls were compared using capillary electrophoresis-mass spectrometry. Among the candidate metabolites, we focused on a metabolite showing the largest difference. The absolute concentrations were measured in two cohorts from a psychiatric primary care clinic to characterize the accuracy of the metabolite biomarker. RESULTS: Among 23 metabolites significantly lower in the MDD group than in healthy controls, we focused on phosphoethanolamine (PEA) as a candidate. The reduction of PEA levels in MDD was checked in independent clinical sample sets. An ion-chromatography-fluorescence detection method was developed to measure plasma PEA levels. In the preliminary cohort, we examined 34 MDD and 43 non-MDD subjects. The area under the receiver-operator curve (AUC) was 0.92, with sensitivity/specificity greater than 88%, at a cut-off of 1.46 µM. In the checking cohort, with 10 MDD and 13 non-MDD subjects, AUC was 0.89, with sensitivity/specificity of 86% and 100%, respectively, at a cut-off of 1.48 µM. Plasma PEA inversely correlated with MDD severity, depressed mood, loss of interest, and psychomotor retardation. CONCLUSION: These results suggest that plasma PEA level could be a candidate biomarker of MDD in the clinical setting. Further studies comparing MDD and mentally healthy controls are needed to confirm the utility of PEA as a biomarker for depression.

Mutations of the glycine cleavage system genes possibly affect the negative symptoms of schizophrenia through metabolomic profile changes.

AIM: Hypofunction of N-methyl-D-aspartate receptors (NMDAR) may contribute to the pathophysiology of schizophrenia (SCZ). Recently, the glycine cleavage system (GCS) was shown to affect NMDAR function in the brain. GCS functional defects cause nonketotic hyperglycinemia, the atypical phenotype of which presents psychiatric symptoms similar to SCZ. Here, we examined the involvement of GCS in SCZ. METHODS: First, to identify the rare variants and the exonic deletions, we resequenced all the coding exons and the splice sites of four GCS genes (GLDC, AMT, GCSH, and DLD) in 474 patients with SCZ and 475 controls and performed multiplex ligation-dependent probe amplification analysis in SCZ. Next, we performed metabolome analysis using plasma of patients harboring GCS variants (n = 5) and controls (n = 5) by capillary electrophoresis time-of-flight mass spectrometry. The correlation between plasma metabolites and Positive and Negative Syndrome Scale score was further examined. RESULTS: Possibly damaging variants were observed in SCZ: A203V, S801N in GLDC, near the atypical nonketotic hyperglycinemia causative mutations (A202V, A802V); G825D in GLDC, a potential neural tube defect causative mutation; and R253X in AMT. Marked elevation of plasma 5-oxoproline (pyroglutamic acid), aspartate, and glutamate, which might affect NMDAR function, was observed in patients harboring GCS variants. The aspartate level inversely correlated with negative symptoms (r = -0.942, P = 0.0166). CONCLUSION: These results suggest that GCS rare variants possibly contribute to the pathophysiology of SCZ by affecting the negative symptoms through elevation of aspartate.

A Novel Evaluation Method for Displacement between Carbon Beam Axis and Positioning X-ray Axis Using an Imaging Plate.

PURPOSE: We developed an evaluation method for easily calculating displacement directly between the carbon beam axis and positioning X-ray axis. METHODS: A verification image was acquired by irradiating an imaging plate with a carbon beam and X-ray. The X-ray passed through a lead plate inserted in the range compensator holder. The displacement was calculated on the verification image from the center of a wire irradiated with carbon using a multi leaf collimator (MLC) and a wire irradiated with X-ray also using MLC. The accuracy of the method was evaluated by moving the carbon beam axis, the X-ray axis, and the setup angle. The weekly changes of vertical and lateral beams in all rooms were also evaluated. RESULTS: The displacements of the carbon beam axis and the setup angle did not influence the calculation results, whereas the displacement of the X-ray axis did (R=0.999). The displacements including weekly changes were all less than 1.00 mm. CONCLUSION: An evaluation method for calculating the displacement directly and simply between the carbon beam axis and positioning X-ray axis was developed and verified. The weekly changes of displacement between axes were evaluated to be acceptable at our facility.

Statistical hypothesis testing of factor loading in principal component analysis and its application to metabolite set enrichment analysis.

BACKGROUND: Principal component analysis (PCA) has been widely used to visualize high-dimensional metabolomic data in a two- or three-dimensional subspace. In metabolomics, some metabolites (e.g., the top 10 metabolites) have been subjectively selected when using factor loading in PCA, and biological inferences are made for these metabolites. However, this approach may lead to biased biological inferences because these metabolites are not objectively selected with statistical criteria. RESULTS: We propose a statistical procedure that selects metabolites with statistical hypothesis testing of the factor loading in PCA and makes biological inferences about these significant metabolites with a metabolite set enrichment analysis (MSEA). This procedure depends on the fact that the eigenvector in PCA for autoscaled data is proportional to the correlation coefficient between the PC score and each metabolite level. We applied this approach to two sets of metabolomic data from mouse liver samples: 136 of 282 metabolites in the first case study and 66 of 275 metabolites in the second case study were statistically significant. This result suggests that to set the number of metabolites before the analysis is inappropriate because the number of significant metabolites differs in each study when factor loading is used in PCA. Moreover, when an MSEA of these significant metabolites was performed, significant metabolic pathways were detected, which were acceptable in terms of previous biological knowledge. CONCLUSIONS: It is essential to select metabolites statistically to make unbiased biological inferences from metabolomic data when using factor loading in PCA. We propose a statistical procedure to select metabolites with statistical hypothesis testing of the factor loading in PCA, and to draw biological inferences about these significant metabolites with MSEA. We have developed an R package "mseapca" to facilitate this approach. The "mseapca" package is publicly available at the CRAN website.

A parent-rating scale of postpartum depression: Maternity-monitoring scale by parents (MMSP).

Postpartum depression (PPD) is an illness that is difficult for the affected women themselves to recognize. Moreover, many mothers believe that mothers should not complain about the mental difficulties of taking care of their children. Therefore, in addition to self-evaluation for PPD, evaluation from others is also necessary. We aimed to develop a novel measure to screen for PPD based on a parent-rating scale that is administered to the parents of postpartum mothers. The 15-item maternity-monitoring scale by parents (MMSP) was designed and applied to the feasibility cohort (n = 61) and the emergency cohort (n = 55). The Edinburgh Postnatal Depression Scale (EPDS) (threshold score of 8/9) was used to evaluate a high risk of PPD. An egogram-based index, the over-adaptation index for depression (OAID), was performed along with the EPDS and MMSP. In the feasibility cohort, MMSP was moderately correlated with EPDS. In the emergency cohort, under the circumstance of the state of emergency declaration over the coronavirus disease 2019 in Japan, application of the MMSP was delayed, resulting in the proportion of parents who overlooked PPD symptoms in their daughters increasing from 33 % to 50 %. Our findings suggest that a novel approach of parent-rated PDD screening of postpartum women is potentially possible, and the MMSP is a potential candidate for screening. Moreover, the OAID is also helpful in identifying women with hidden PPD, along with the EPDS. The performance of the MMSP should be confirmed in the parents of patients with PPD diagnosed by psychiatrists.

Metabolome analysis of photosynthesis and the related primary metabolites in the leaves of transgenic rice plants with increased or decreased Rubisco content.

Because the comprehensive effects on metabolism by genetic manipulation of leaf Rubisco content are unknown, metabolome analysis was carried out on transgenic rice plants with increased or decreased Rubisco content using the capillary electrophoresis-time-of-flight mass spectrometry (CE-TOFMS) technique. In RBCS-sense plants, an increase in Rubisco content did not improve light-saturated photosynthesis. Glyceraldehyde 3-phosphate and sedoheputulose 7-phosphate levels increased, but ribulose bisphosphate (RuBP), ATP and ADP levels were not affected. It is considered from these results that RuBP regeneration independent of ATP supply became a bottleneck for photosynthesis. In RBCS-antisense plants, a decline in Rubisco content decreased photosynthesis with a substantial accumulation of RuBP. ATP and ADP levels also increased and were associated with increases in the diphosphate and triphosphate compounds of other nucleosides. These results imply that a decline in Rubisco content slowed down the Calvin cycle and that the resultant excess energy of ATP was transferred to other nucleoside diphosphates and triphosphates. The levels of amino acids tended to decline in RBCS-sense plants and increase in RBCS-antisense plants, probably reflecting the demand for Rubisco synthesis. Starch and carbohydrate levels decreased only in RBCS-antisense plants. Thus, genetic manipulation of Rubisco contents widely affected C and N metabolism in rice.

Depiction of metabolome changes in histidine-starved Escherichia coli by CE-TOFMS.

Metabolic changes in response to histidine starvation were observed in histidine-auxotrophic Escherichia coli using a capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS)-based metabolomics technique. Prior to the analysis, we prepared an E. coli metabolome list of 727 metabolites reported in the literature. An improved method for metabolite extraction was developed, which resulted in higher extraction efficiency in phosphate-rich metabolites, e.g., ATP and GTP. Based on the results, 375 charged, hydrophilic intermediates in primary metabolisms were analysed simultaneously, providing quantitative data of 198 metabolites. We confirmed that the intracellular levels of intermediates in histidine biosynthesis are rapidly accumulated in response to a drop in histidine level under histidine-starved conditions. Simultaneously, disciplined responses were observed in the glycolysis, tricarboxylic acid cycle, and amino acid and nucleotide biosynthesis pathways as regulated by amino acid starvation.

Comparison of metabolite production capability indices generated by network analysis methods.

UNLABELLED: A framework of constraint-based reconstruction and analysis (COBRA) is used for modeling large-scale metabolic networks. In COBRA, extreme pathway and optimization analyses are commonly used to study the properties of networks. While the results of both methods are completely consistent, extreme pathway analysis is considered to be better because of its wider representational ability. In this study, we assessed these two methods by computational knockout experiments. We examined a simple pathway model and found that the extreme pathway method led to misguided conclusions in specific cases, while optimization analysis calculated the correct knockout effects. We also investigated the Escherichia coli metabolic pathway model, and found that these methods result in inconsistent interpretations of the network properties. IN CONCLUSION: it has been claimed that these two methods result in the same producible metabolites, but we found a difference in individual results for a biological pathway. Our results could provide helpful guidance for when to use the methods, particularly extreme pathway analysis.

[Safe Use of Recent New Drugs-Current Status and Challenges].

　In Japan and overseas, Chugai Pharmaceutical Company handles numerous biopharmaceuticals, molecular targeted therapies and other pharmaceuticals with innovative modes of action. Expert safety evaluation is essential for promoting the appropriate use of these pharmaceuticals around the world and in gaining acceptance from patients and healthcare professionals (HCPs), while speedy decision-making is crucial for the timely collection and provision of safety information and thus ensuring safety. In 2015, we collected safety information on more than 180000 cases and evaluated it from a medical standpoint. We have established a system for recording the collected information in a global database, and are conducting signal detection of adverse drug reactions using this database. With this system, we promptly disclose information to regulatory authorities in Japan, the US, Europe and Asia. We have in-house medical doctors with abundant clinical experience who conduct expert safety evaluations. Many innovative drugs, such as anticancer drugs or biopharmaceuticals, require wider-ranging, more rigorous management, including the provision of appropriate safety information to HCPs, management of distribution through wholesalers and dispensing pharmacies, and confirmation of conditions of use, in addition to all-case registration surveillance. With progress in the development of individualized medicine and drugs with new modes of action, in order for HCPs to understand the characteristics of these new drugs and use them appropriately, pharmacists and pharmaceutical companies should cooperate in promoting their appropriate use in the spirit of 'All Pharmacists for Patients'.

Metabolome analysis of esophageal cancer tissues using capillary electrophoresis-time-of-flight mass spectrometry.

Reports of the metabolomic characteristics of esophageal cancer are limited. In the present study, we thus conducted metabolome analysis of paired tumor tissues (Ts) and non-tumor esophageal tissues (NTs) using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). The Ts and surrounding NTs were surgically excised pair-wise from 35 patients with esophageal cancer. Following tissue homogenization and metabolite extraction, a total of 110 compounds were absolutely quantified by CE-TOFMS. We compared the concentrations of the metabolites between Ts and NTs, between pT1 or pT2 (pT1-2) and pT3 or pT4 (pT3-4) stage, and between node-negative (pN-) and node-positive (pN+) samples. Principal component analysis and hierarchical clustering analysis revealed clear metabolomic differences between Ts and NTs. Lactate and citrate levels in Ts were significantly higher (P=0.001) and lower (P<0.001), respectively, than those in NTs, which corroborated with the Warburg effect in Ts. The concentrations of most amino acids apart from glutamine were higher in Ts than in NTs, presumably due to hyperactive glutaminolysis in Ts. The concentrations of malic acid (P=0.015) and citric acid (P=0.008) were significantly lower in pT3-4 than in pT1-2, suggesting the downregulation of tricarboxylic acid (TCA) cycle activity in pT3-4. On the whole, in this study, we demonstrate significantly different metabolomic characteristics between tumor and non-tumor tissues and identified a novel set of metabolites that were strongly associated with the degree of tumor progression. A further understanding of cancer metabolomics may enable the selection of more appropriate treatment strategies, thereby contributing to individualized medicine.

Calreticulin and integrin alpha dissociation induces anti-inflammatory programming in animal models of inflammatory bowel disease.

Inflammatory bowel disease (IBD), including ulcerative colitis and Crohn's disease, is a chronic intestinal inflammatory condition initiated by integrins-mediated leukocyte adhesion to the activated colonic microvascular endothelium. Calreticulin (CRT), a calcium-binding chaperone, is known as a partner in the activation of integrin α subunits (ITGAs). The relationship between their interaction and the pathogenesis of IBD is largely unknown. Here we show that a small molecule, orally active ER-464195-01, inhibits the CRT binding to ITGAs, which suppresses the adhesiveness of both T cells and neutrophils. Transcriptome analysis on colon samples from dextran sodium sulfate-induced colitis mice reveals that the increased expression of pro-inflammatory genes is downregulated by ER-464195-01. Its prophylactic and therapeutic administration to IBD mouse models ameliorates the severity of their diseases. We propose that leukocytes infiltration via the binding of CRT to ITGAs is necessary for the onset and development of the colitis and the inhibition of this interaction may be a novel therapeutic strategy for the treatment of IBD.

Model-based definition of population heterogeneity and its effects on metabolism in sporulating Bacillus subtilis.

The soil bacterium Bacillus subtilis forms dormant, robust spores as a tactic to ensure survival under conditions of starvation. However, the sporulating culture includes sporulating and non-sporulating cells, because a portion of the cell population initiates sporulation in wild-type strain. We anticipated that the population effect must be considered carefully to analyse samples yielding population heterogeneity. We first built a mathematical model and simulated for signal transduction of the sporulation cue to see what mechanisms are responsible for generating the heterogeneity. The simulated results were confirmed experimentally, where heterogeneity is primarily modulated by negative feedback circuits, resulting in generation of a bistable response within the sporulating culture. We also confirmed that mutants relevant to negative feedback yield either sporulating or non-sporulating subpopulations. To see the effect of molecular mechanism between sporulating and non-sporulating cells in distinct manner, metabolome analysis was conducted using the above mutants. The metabolic profiles exhibited distinct characteristics with time regardless of whether sporulation was initiated or not. In addition, several distinct characteristics of metabolites were observed between strains, which was inconsistent with previously reported data. The results imply that careful consideration must be made in the interpretation of data obtained from cells yielding population heterogeneity.

P-BOSS: a new filtering method for treasure hunting in metabolomics.

Metabolomics is expected to boost data driven research. In biomarker discovery, powerful filtering methods to remove noise and outliers are essential for screening significant candidates from the huge volume of omic data. Here we propose a post-measurement peak filtering method (named P-BOSS) for CE electrospray ionization-time-of-flight MS (CE-TOFMS) data. Combining outlier detection method functions in parallel, we applied P-BOSS to the data using Escherichia coli knockout mutants of the tryptophan and purine biosynthesis pathways. As the result, P-BOSS showed remarkably superior performance, reducing 65% of all peaks, while leaving significant peaks.

Alignment-based approach for durable data storage into living organisms.

The practical realization of DNA data storage is a major scientific goal. Here we introduce a simple, flexible, and robust data storage and retrieval method based on sequence alignment of the genomic DNA of living organisms. Duplicated data encoded by different oligonucleotide sequences was inserted redundantly into multiple loci of the Bacillus subtilis genome. Multiple alignment of the bit data sequences decoded by B. subtilis genome sequences enabled the retrieval of stable and compact data without the need for template DNA, parity checks, or error-correcting algorithms. Combined with the computational simulation of data retrieval from mutated message DNA, a practical use of this alignment-based method is discussed.

Metabolic profile alterations in the postmortem brains of patients with schizophrenia using capillary electrophoresis-mass spectrometry.

OBJECTIVE: We aimed to find the alterations in the profiles of low-molecular-weight metabolites in the brains of schizophrenia patients that may reflect the pathophysiology of the disorder. METHOD: Human postmortem brain tissues from the frontal cortex (15 schizophrenia patients and 15 controls) and the hippocampus (14 schizophrenia patients and 15 controls) were obtained from the Stanley Foundation Neuropathology Consortium. We analyzed ~300 metabolites, using capillary electrophoresis with time-of-flight mass spectrometry. RESULTS: In the frontal cortex, the mean levels of 29 metabolites were significantly different between the schizophrenia and control groups. In the hippocampus, only a dipeptide, glycylglycine was significantly (p≤0.001, nominal p-value) increased in schizophrenia. Glycylglycine was also significantly (p=0.007) increased in the frontal cortex of schizophrenia. The pathway analyses revealed that several metabolic pathways including KEGG "Central carbon metabolism in cancer" and "Protein digestion and absorption" were commonly affected in the frontal cortex and the hippocampus of schizophrenia patients. CONCLUSION: These findings point out alterations in glucose metabolism and proteolysis in the brains of schizophrenia.