Shimadzu Releases New Multi-Omic Data Analysis Package and Relevant Method Packages
Product News Mar 20, 2019
Screenshot from the Multi-Omics Analysis Package
Shimadzu Corporation (head office: Kyoto city; President and CEO: Teruhisa Ueda) announces the release of a Multi-Omic Data Analysis Package designed for metabolic engineering research applications. Using this package, measurement data from Shimadzu mass spectrometers can be loaded in the Garuda*1 open platform and automatically plotted on a metabolic map. The package can reduce the several hours of work previously required to only a few minutes and free researchers from tedious data analysis processes.
The proteomic,*2 metabolomic,*3 and flux analysis*4 data obtained from Shimadzu gas chromatograph mass spectrometers (GCMS) and liquid chromatograph mass spectrometers (LCMS) is essential for multi-omic*5 research. However, given the increasingly sophisticated instrument functionality available in recent years, the huge amounts of data generated by the systems can become a bottleneck for research, due to the significant time and trouble required for analyzing the data.
The Multi-Omic Data Analysis Package runs on the Garuda open platform. On the Garuda platform, the package uses data analysis programs called “gadgets,” including publicly released gadgets and Shimadzu’s independently developed gadgets. Some of the gadgets enable plotting the measurement data from Shimadzu mass spectrometers on a metabolic map and some are used as tools for statistical analysis or correlation analysis, for example. In 2017, Shimadzu jointly released a free version of the Multi-Omic Data Analysis Package in partnership with the Systems Biology Institute (represented by Hiroaki Kitano) and Professor Fumio Matsuda, Graduate School of Information Science and Technology, Osaka University.*6 This new product reflects the feedback received from users of the free version.
In addition to releasing the Multi-Omic Data Analysis Package, Shimadzu is releasing updated versions of the LC/MS/MS Method Package for Primary Metabolites (originally released in August 2014) and LC/MS/MS Method Package for Cell Culture Profiling (originally released April 2015). Using the Multi-Omic Data Analysis Package in combination with either of these packages can reduce the trouble required for pretreatment, reviewing analytical conditions, and configuring analytical parameter settings, and provide a total solution for everything from automatically creating metabolic maps and statistical analysis to post-processing. For quantitative analysis, which is essential for multi-omic research, the product offers support for a range of process steps from pretreatment to data analysis.
Shimadzu intends to continue contributing to research progress by offering a family of hardware products, such as the triple quadrupole LCMS-8060 and LCMS-8050, and the Q-TOF LCMS-9030, and a family of software products, including a variety of method packages for all sorts of analytical applications.
*1 Supplied by the Garuda Alliance since 2010, which is mainly operated by the Systems Biology Institute. Offering the ability to seamlessly transfer data between different software, metabolic engineering researchers can freely configure the open platform based on their own workflow from data acquisition to data analysis.
*2 Comprehensive research of protein structures and functions
*3 Comprehensive research of metabolites generated from cell activities
*4 Technique of precisely tracking the quantity of specific metabolites based on the difference between the quantities of the metabolite produced and consumed
*5 Cutting-edge life sciences research to identify biological activities in humans and cells based on an integrated analysis of genes, proteins, metabolites, and other such substances. Anticipated for use in a wide variety of research applications, such as drug discovery, medical diagnostics, or biofuels, multi-omics is categorized into proteomics, metabolomics, flux analysis, and other fields, depending on what is being analyzed.
*6 This package is the result of joint research with the Osaka University-Shimadzu Analytical Innovation Joint Research Workshop (established December 2014), the Graduate School of Information Science and Technology, and the Systems Biology Institute.