Clinical OMICS

NOV-DEC 2018

Healthcare magazine for research scientists, labs, pathologists, hospitals, cancer centers, physicians and biopharma companies providing news articles, expert interviews and videos about molecular diagnostics in precision medicine

Issue link: https://clinicalomics.epubxp.com/i/1040438

Contents of this Issue

Navigation

Page 28 of 51

www.clinicalomics.com November/December 2018 Clinical OMICs 27 Research that is freely available and lives in the cloud, making it accessible to virtually any researchers and requiring a relatively simple setup. "The METLIN database is actually incredibly unique right now in terms of its size," said Gary Siuzdak, Ph.D., senior director of the Scripps Center for Metabolomics and co-developer of METLIN. First launched online in 2005, METLIN has grown rap- idly over the course of the last year from about 15,000 com- pounds to 150,000 compounds—and spanning more than 350 chemical classes—for which relevant fragmentation information is available. "This has been the result of a lot of things coming together over the last year to allow us to perform high-throughput analyses on a variety of different types of molecules that we've been able to get our hands on," Siuzdak noted. By comparison, he said, the database from the government-funded National Institute of Stan- dards and Technology, or NIST, is one order smaller, in the tens of thousands. Although METLIN may be one of the largest available metabolomics databases, it is far from complete. "We don't have any comprehensive spectral databases out there," said Lloyd Sumner, Ph.D., director of the Metabolomics Center at the University of Missouri. "We don't even know what the size of the metabolome is." Data repositories and analytical tools that allow research- ers to perform comparative analyses of their spectra are becoming more sophisticated and may interface with spec- tral databases. For example, METLIN is integrated with comparative analysis tool XCMS online. Released online in 2012, XCMS online was the first technology that allowed for nonlinear alignment of data from untargeted mass spectrometry experiments. "It really changed how we do untargeted metabolomics," said Siuzdak. In untargeted metabolomic experiments, researchers can cast the widest net possible and don't need to specify which metabolites they are looking for. "That's why [XCMS online] has on the order of twenty-two hundred citations so far," he asserted. Conversely, the Scripps suite of tools added another freely accessible, cloud-based platform in August: XCMS MRM and METLIN MRM. Unlike XCMS online and METLIN, this new platform is for targeted mass spectrometry. Targeted mass spectrometry is highly sensitive and is used when researchers know which metabolites they are looking for. "Almost every area of biological science uses this targeted technology to look at specific molecules that we're inter- ested in," Siuzdak said. For example, when an Olympian is suspected of doping, targeted mass spectrometry is used to screen for the compound of interest. "What we wanted to do was create something that would allow you to use XCMS and also METLIN for these types of [targeted] analyses across all of these different applications." Despite the relative success of the Scripps suite of tools, (continued on next page) Stephen Barnes, Ph.D., and colleague Janusz Kabarowski, Ph.D., in the UAB Targeted Metabolomics and Proteomics Laboratory.

Articles in this issue

Links on this page

Archives of this issue

view archives of Clinical OMICS - NOV-DEC 2018