Takeshi Bamba

A metabolomic approach to lung cancer

Lung cancer is one of the most common cancers in the world, but no good clinical markers that can be used to diagnose the disease at an early stage and predict its prognosis have been found. Therefore, the discovery of novel clinical markers is required. In this study, metabolomic analysis of lung cancer patients was performed using gas chromatography mass spectrometry. Serum samples from 29 healthy volunteers and 33 lung cancer patients with adenocarcinoma (n=12), squamous cell carcinoma (n=11), or small cell carcinoma (n=10) ranging from stage I to stage IV disease and lung tissue samples from 7 lung cancer patients including the tumor tissue and its surrounding normal tissue were used. A total of 58 metabolites (57 individual metabolites) were detected in serum, and 71 metabolites were detected in the lung tissue. The levels of 23 of the 58 serum metabolites were significantly changed in all lung cancer patients compared with healthy volunteers, and the levels of 48 of the 71 metabolites were significantly changed in the tumor tissue compared with the non-tumor tissue. Partial least squares discriminant analysis, which is a form of multiple classification analysis, was performed using the serum sample data, and metabolites that had characteristic alterations in each histological subtype and disease stage were determined. Our results demonstrate that changes in metabolite pattern are useful for assessing the clinical characteristics of lung cancer. Our results will hopefully lead to the establishment of novel diagnostic tools.

High throughput and exhaustive analysis of diverse lipids by using supercritical fluid chromatography-mass spectrometry for metabolomics.

We have developed an analytical system that enables the simultaneous rapid analysis of lipids with varied structures and polarities through the use of supercritical fluid chromatography-mass spectrometry (SFC-MS). The separation conditions for SFC (column, modifier, back pressure, etc.) and the detection conditions for mass spectrometry (ionization method, parameters, etc.) were investigated to develop a simultaneous analytical method for lipid mixtures that included phospholipids, glycolipids, neutral lipids, and sphingolipids. When cyanopropylated silica gel-packed column was used for the separation, all lipids were successfully detected and the analysis time was less than 15 min. The use of an octadecylsilylated column resulted in separation, which was dependent on the differences in the unsaturation of the fatty acid side chains and isomer separation. This system is a powerful tool for studies on lipid metabolomics because it is useful not only as a fingerprinting method for the screening of diverse lipids but also for the detailed profiling of individual components.

Development of a method for comprehensive and quantitative analysis of plant hormones by highly sensitive nanoflow liquid chromatography–electrospray ionization-ion trap mass spectrometry

In recent plant hormone research, there is an increased demand for a highly sensitive and comprehensive analytical approach to elucidate the hormonal signaling networks, functions, and dynamics. We have demonstrated the high sensitivity of a comprehensive and quantitative analytical method developed with nanoflow liquid chromatography-electrospray ionization-ion trap mass spectrometry (LC-ESI-IT-MS/MS) under multiple-reaction monitoring (MRM) in plant hormone profiling. Unlabeled and deuterium-labeled isotopomers of four classes of plant hormones and their derivatives, auxins, cytokinins (CK), abscisic acid (ABA), and gibberellins (GA), were analyzed by this method. The optimized nanoflow-LC-ESI-IT-MS/MS method showed ca. 5-10-fold greater sensitivity than capillary-LC-ESI-IT-MS/MS, and the detection limits (S/N=3) of several plant hormones were in the sub-fmol range. The results showed excellent linearity (R(2) values of 0.9937-1.0000) and reproducibility of elution times (relative standard deviations, RSDs, <1.1%) and peak areas (RSDs, <10.7%) for all target compounds. Further, sample purification using Oasis HLB and Oasis MCX cartridges significantly decreased the ion-suppressing effects of biological matrix as compared to the purification using only Oasis HLB cartridge. The optimized nanoflow-LC-ESI-IT-MS/MS method was successfully used to analyze endogenous plant hormones in Arabidopsis and tobacco samples. The samples used in this analysis were extracted from only 17 tobacco dry seeds (1mg DW), indicating that the efficiency of analysis of endogenous plant hormones strongly depends on the detection sensitivity of the method. Our analytical approach will be useful for in-depth studies on complex plant hormonal metabolism.

High-Throughput Technique for Comprehensive Analysis of Japanese Green Tea Quality Assessment Using Ultra-performance Liquid Chromatography with Time-of-Flight Mass Spectrometry (UPLC/TOF MS)

Applications of metabolomics techniques along with chemometrics provide an understanding in the relationship between metabolome of green tea and its quality. A coupled of ultra-performance liquid chromatography with time-of-flight mass spectrometry (UPLC/TOF MS) allowed a high-throughput and comprehensive analysis with minimal sample preparation. Using this technique, a wide range of metabolites were investigated. Data analysis was rapid, considering that the fingerprinting technique was performed. A set of green tea samples from 2006 tea contest of the Kansai area was analyzed to prove usefulness of the developed technique. Green tea with different qualities were discriminated through principal component analysis (PCA). Consequently, projection to latent structure by means of partial least-squares (PLS) was performed to create a constructive quality-predictive model by means of metabolic fingerprinting. Beside epigallocatechin, other predominant catechins, including epigallocatechin gallate and epicatechin gallate, detected in green tea were found to be significant biomarkers to the high quality of Japanese green tea (Sencha).

Serum metabolomics as a novel diagnostic approach for gastrointestinal cancer.

Conventional tumor markers are unsuitable for detecting carcinoma at an early stage and lack clinical efficacy and utility. In this study, we attempted to investigate the differences in serum metabolite profiles of gastrointestinal cancers and healthy volunteers using a metabolomic approach and searched for sensitive and specific metabolomic biomarker candidates. Human serum samples were obtained esophageal (n = 15), gastric (n = 11), and colorectal (n = 12) cancer patients and healthy volunteers (n = 12). A model for evaluating metabolomic biomarker candidates was constructed using multiple classification analysis, and the results were assessed with receiver operating characteristic curves. Among the 58 metabolites, the levels of nine, five and 12 metabolites were significantly changed in the esophageal, gastric and colorectal cancer patients, respectively, compared with the healthy volunteers. Multiple classification analysis revealed that the variations in the levels of malonic acid and L-serine largely contributed to the separation of esophageal cancer; gastric cancer was characterized by changes in the levels of 3-hydroxypropionic acid and pyruvic acid; and L-alanine, glucuronoic lactone and L-glutamine contributed to the separation of colorectal cancer. Our approach revealed that some metabolites are more sensitive for detecting gastrointestinal cancer than conventional biomarkers. Our study supports the potential of metabolomics as an early diagnostic tool for cancer.

Metabolic profiling of lipids by supercritical fluid chromatography/mass spectrometry.

This review describes the usefulness of supercritical fluid chromatography (SFC) for the metabolic profiling of lipids. First, non-targeted lipid profiling by SFC/MS is described. The use of SFC/MS allows for high-throughput, exhaustive analysis of diverse lipids, and hence, this technique finds potential applications in lipidomics. Development of a polar lipid profiling method with trimethylsilyl (TMS) derivatization widens the scope of applicability of SFC/MS. SFC is a high-resolution technique that is suitable for non-targeted profiling aimed at the simultaneous analysis of many components. Next, targeted lipid profiling by SFC/MS is described. SFC is useful for the separation of lipids, such as carotenoids and triacylglycerols, which have numerous analogs with similar structures. In addition, SFC/MS shows the maximum efficiency for the target analysis of lipids in a biological sample that includes many matrices. Finally, a high-resolution, high-throughput analytical system based on SFC/MS is stated to be suitable for lipidomics because it is useful not only for the screening of lipid mixtures (as a fingerprint method) but also for the detailed profiling of individual components.

Development of a lipid profiling system using reverse-phase liquid chromatography coupled to high-resolution mass spectrometry with rapid polarity switching and an automated lipid identification software.

Lipidomics requires accurate lipid profiling, which until recently has been challenging at best. In the present study, we developed a practical workflow for high-throughput and exhaustive lipid profiling by combining reverse-phase liquid chromatography coupled to quadrupole orbitrap Fourier transform mass spectrometry, with an automated lipid identification software. This validated method enables highly sensitive and simultaneous analysis of lipids with varying polarities such as glycerophospholipids and sphingophospholipids, by switching the acquisition polarities in mass spectrometry. In addition, it facilitates data-dependent MS(2) analysis targeting the lipid molecular species without any influence from other ions by setting the inclusion list, the target m/z list for the product ion scanning. The m/z values of the target lipid molecular species, stored in the database of Lipid Search software, are added to the inclusion list. Moreover, optimizing the identification conditions of the software for the LC/MS system enables high-throughput and accurate identification of lipid molecular species existing in biological samples. Specifically, LC separation is essential for accurate identification of lipid molecular species that possess some fatty acid chains, because it can be difficult to determine fatty acid chain composition of detected molecular species especially in triacylglycerol compounds in direct infusion mass spectrometry. This method has high reproducibility and can be used for structural analysis even for low-abundance compounds. Using this method, over 400 lipid compounds targeted in this research were detected and identified from a sample of mouse plasma. This result indicates that the LC/MS method in the present study enables efficient lipid profiling.

Practical non-targeted gas chromatography/mass spectrometry-based metabolomics platform for metabolic phenotype analysis.

Gas chromatography coupled to mass spectrometry (GC/MS) is a core analytical method for metabolomics and has been used as a platform in non-targeted analysis, especially for hydrophilic metabolites. Non-targeted GC/MS-based metabolomics generally requires a high-throughput technology to handle a large volume of samples and an accumulated database (reference library) of the retention times and mass spectra of standard compounds for accurate peak identification. In this study, we provide a practical GC/MS platform and an auto peak identification technique that is not restricted to certain types of mass spectrometers. The platform utilizes a quadrupole mass spectrometer capable of high-speed scanning, resulting in greater output compared with Pegasus GC-time of flight (TOF)/MS, which has been an essential instrument for high-throughput experiments. Moreover, we show that our reference library is broadly applicable to other instruments; peak identification can be readily performed using the library without constructing a reference resource. The usefulness and versatility of our system are demonstrated by the analyses of three experimental metabolomics data sets, including standard mixtures and real biological samples.

Supercritical fluid chromatography/Orbitrap mass spectrometry based lipidomics platform coupled with automated lipid identification software for accurate lipid profiling.

We developed a practical analytical system for high-throughput and comprehensive lipid profiling using a supercritical fluid chromatography (SFC) system coupled to an Orbitrap Fourier transform mass spectrometer (Orbitrap FT-MS). Using our SFC method, polar lipid molecular species were separated based on not only their fatty acyl moieties but also their polar head groups, using a single octadecylsilyl (ODS) column. In addition, because automatic data processing software was used for the identification of lipid molecular species, the analysis time including data processing was about a half an hour per sample. A variety of lipid molecular species were detected in mouse plasma, and isomers which often co-elute in reverse phase separation were identified accurately and quantified individually. To the best of our knowledge, this is the first report describing the chromatographic separation of lipids based on both fatty acyl moieties and polar head groups, using a single ODS column. Our results demonstrate that SFC/MS is a powerful tool for the simultaneous analysis of diverse lipid molecular species.

Application of supercritical fluid chromatography/mass spectrometry to lipid profiling of soybean.

A metabolomics technology for lipid profiling based on supercritical fluid chromatography (SFC) coupled with mass spectrometry (MS) was applied to analyze lipids of soybean. Principal component analysis (PCA) was used to discriminate twelve soybean cultivars according to their suitability for different processed foods such as natto, tofu, edamame, and nimame. By PCA assay, triacylglycerol (TAG) was found as the main variable for discrimination of soybean cultivars. Therefore, a high-throughput and high-resolution TAG profiling method by SFC/MS was developed to more effective discrimination. By investigating several columns, three Chromolith Performance RP-18e columns connected in series were chosen as the most effective column for TAG profiling. Diverse TAGs were separated effectively for 8 min without purification. Additionally, each TAG was identified successfully by the programmed cone voltage fragmentation even without MS/MS analysis and any standard sample.