Shimadzu's Metabolomics Solution
Shimadzu's Metabolomics Solution
Shimadzu strongly supports metabolomics research. Tools for high resolution separation of compounds in various biological samples, a tool for online accurate mass measurement of these compounds, and tools for efficiently extracting the desired information from huge amounts of acquired data are all available. The instrumentation used for these are designed to make full use of leading edge technology to achieve high-accuracy and high-speed processing.
 What is metabolomics?
Metabolomics is one of the important elements of systems biology which includes the analysis of low molecular weight compounds such as organic acids and amino acids as metabolites (study of the metabolome). Thus, while genomics focuses on the study of DNA, transcriptomics the study of mRNA, and proteomics the study of proteins, metabolomics focuses on the study of metabolites overall.
DNA and proteins are subject to such environmental influences as food, medicines, movement, and a variety of stresses. The results of interaction with these influences are reflected in the metabolites that remain behind, so metabolomics can be said to measure the activities of the genome and proteins within the body as well as the sum total of the environmental influences. Since metabolomics can be used to garner valuable information about biological functions, its application has extended to wide-ranging fields of research, from biomarker discovery projects (drug metabolism and dynamics, drug safety, pharmacologic toxicity, etc.) to disease diagnosis, lifestyle habits and health.
 Metabolomics Analysis Project Flow
A rough flow might be as follows:
Step 1 Project idea
Step 2 Experiment design
Step 3 Discovery of changed metabolites
Step 4 Identification of changed metabolites
Step 5 Hypothesis, verification, conclusion
[Step 1 Project idea]
To start a project, there must be some sort of question to be addressed, such as a drug, food or environment-related question (for example, "why is this drug toxic, or why does this food show antihypertensive action"), or a disease-related question, or a genome / proteomics-related question (for example, "what is the function of this gene, or protein"). This question then becomes the project idea.
[Step 2 Experiment design]
A variety of approaches are possible in metabolomics, so it is important that the experiment be designed so that when the project is analyzed, meaningful results will have been obtained. For example, should cultured cells be used for the pre-clinical sample or should an animal disease model be used, and for the clinical sample, should a healthy human sample (Phase I) be used or a disease sample (Phase II and later), and should the sample itself consist of tissue and cells or a biological fluid such as plasma, serum or urine. In addition, it is necessary to decide the number of samples taking into consideration the biological variability of the system.
[Step 3 Discovery of changed metabolites]
The approaches for discovering changed metabolites can be broadly divided into two categories.
This refers to the search for changed metabolites among all of the compounds, and the emphasis on in-depth search techniques make this a strong approach. It involves relative quantitative analysis.
In this approach, known metabolites are selectively analyzed. Relative quantitative analysis is taken into consideration, and multiple sample concentration profile analysis is possible.
There are various technology-related approaches in metabolomics, including the use of chromatography - mass spectrometry, and NMR, etc.
When chromatography-mass spectrometry is used, the measurement data advances the analysis starting with retention time and mass. If retention time calibration and alignment are required, iterative measurement using the same sample is conducted. Finding the changed metabolites in the case of a drug, for example, will necessarily involve the generation of large quantities of data. This is due to the production of multiple data sets associated with acquisition at timed intervals after the drug is administered, as well as the possibility of biological variability and parent population variability. Because of the huge volume of data generated from so many samples submitted to analysis, analytical software becomes virtually indispensable.
Thus, metabolite discovery is normally conducted using specialized software applications to handle processing of acquired data, such as calibration of retention time and mass, alignment and normalization, as well as to perform such operations as statistical analysis and data mining.
[Step 4 Identification of changed metabolites]
To identify the metabolites discovered in step 3, the compounds are cross-checked with those registered in databases, and their structures are determined through compound information analysis. Various databases are in development both domestically and internationally, which contain MS/MS and other reference spectra, as well as compounds associated with metabolic maps.
Since it will take some time before identification of all metabolites will become possible through database referencing, structural identification is attempted based on the information on changed metabolites in addition to that obtained from analytical instrumentation like the MS and NMR.
[Step 5 Hypothesis, verification, conclusion]
After the changed metabolites are discovered and identified, the project idea is revisited, a hypothesis is framed and verified, and a conclusion is drawn. The framing of a meaningful hypothesis and drawing conclusions requires reproducible data, a means of separating each of the metabolites from complex samples (normally, a combination of mass resolution and chromatographic resolution), abundant data for ID verification (a combination of mass accuracy and MSn information), and software that can extract from huge amounts of data the information which fulfills the research objective.
 Shimadzu's Metabolomics Solution
The combination of chromatography and mass spectrometry is widely used in metabolomics because of the high compound resolution obtained with this technique.
The information that is most essential for discovering changed metabolites is retention time. Excellent retention time reproducibility is critical, and the Shimadzu HPLC Prominence Series which receives high acclaim for its exceptional performance is perfectly suited for metabolomics research. The combination of the Shimadzu LCMS-IT-TOF, with its ability to obtain MSn accurate mass via high-speed measurement, with the Prominence HPLC can provide the accurate information required to satisfy these objectives.
To efficiently extract the information required to fulfill research objectives from the huge quantities of data acquired with these instruments, a system comprising these in combination with the Profiling Solution Metabolomics Software , developed by Phenomenome Discoveries Inc. (Canada) with its widely recognized experience and expertise in metabolomics and bioinformatics, is offered as Shimadzu's Metabolomics Solution.
Making use the 0.1-second high-speed mass spectral measurement of the LCMS-IT-TOF, when this instrument is configured online with the HPLC, a single measurement is all that is required to obtain not only an MS spectrum, but MS/MS and MS/MS/MS spectra, as well. In addition, after pinpointing changed metabolites, the MSn accurate mass spectra can be measured by re-injecting the same sample. The LCMS-IT-TOF Composition Prediction Program (Patent Pending) effectively narrows the number of candidates using not only isotopic patterns, but also the MSn spectra accurate mass information. That's what makes this system extremely useful in tackling the most formidable of tasks in metabolomics, the identification of discovered metabolites, and to powerfully support the success of projects using metabolomics, such as the search for biomarkers.
High throughput metabolite analysis is also required during lead compound optimization which occurs in the depth search stage of drug discovery research. A system which includes the metabolite structural analysis software MetID Solution is offered for efficient search and identification of both expected and unknown metabolites.
Through comparison of pre- and post-metabolic XIC (accurate mass) chromatograms, and the application of multivariate analysis to the MSn spectra of parent and metabolite compounds, this system allows even those analysts with limited familiarity in metabolic research to automatically extract metabolite candidates, supporting improvement of overall productivity in the lab.
On the other hand, with respect to identification of discovered metabolites, attention is currently being refocused on GCMS as a method for easily analyzing small molecule compounds like amino acids, organic acids and fatty acids with high sensitivity and high resolution.
Shimadzu offers the GCMS system comprising the GCMS-QP2010 Plus, for certain analysis and identification of amino acids, organic acids and fatty acids, the GCMSsolution software (Ver. 2.5 and later), featuring automatic retention time correction, in addition to a GCMS metabolite database. Using the metabolite database equipped with retention indices, candidate compounds can be greatly narrowed to enable highly reliable identification.
The ion trap-equipped LCMS-IT-TOF in the online configuration with HPLC achieves accurate mass spectral measurement to the nth power of MS.
the Profiling Solution Metabolomics Software the efficient search of target candidate compounds, dramatically improving research productivity.
The metabolite structural analysis software MetID Solution compares pre- and post-metabolic data to search for expected and unknown metabolites.
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