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

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Page 30 of 51 November/December 2018 Clinical OMICs 29 of the Collaborative Mass Spectrometry Innovation Center at University of California San Diego. "I got really frustrated with databases where you just deposit data, and then you can't do anything with it. We wanted to create a system where people actually upload data as they start to do the analysis, so you don't have to redo it at the end when you go publish." Unlike platforms like XCMS and METLIN, crowdsourced tools allow any user to contribute and provide input. "Par- ticularly in the natural products world, [allowing anyone to contribute] opens up a vast trove of authentic and purified compounds that are frequently not commercially available at all," said Broeckling. "As such, crowdsourced databases are likely to have content that simply isn't anywhere else." The GNPS platform allows users too freely annotate any piece of uploaded information and has a system much like Yelp where annotations are assigned a star ranking based on accuracy of identification. "What we're seeing is actually continuous improvement of the knowledge that exists within the infrastructure," said Dorrestein. "We also had an instance where people were going back and forth, correcting data points within the infrastructure, and it turns out that they were just using different names for the molecule. That only became visible once the dialogue started to happen." Although not a proponent of crowdsourcing, Siuzdak explained that cost is a big reason why some labs turn to crowdsourcing. "To buy these molecules can quickly lead to astronomical costs. It is completely impractical for most to pursue the analysis of standards. However, the human cost of using data from questionable sources is much higher." Because anyone can upload their data from virtually any source, critics of crowdsourced platforms are concerned that quality of data is impaired and confidence of accurate metab- olite identification is weakened. "The crowdsourcing is only good if there is a very strong filter for quality," explained Barnes. "Otherwise you're going to get drowned in noise of things that aren't interesting." If the data quality isn't up to par, he warned, "people will chase shadows." Although crowdsourced tools may lack desired standard- ization to confidently identify one's molecule, they have a place in the field. "It's going to take a village to solve some of these grand challenges that we face, and to do that, we're going to have to use whatever mechanisms that we have available," Broeckling noted. "So I'm not opposed to crowd- sourcing. If people are sharing their data, then you don't need to crowdsource, and truthfully I think maybe 10% of people share their data." Setting Standards Lack of standardization among incoming data extends well beyond just crowdsourced tools. It plagues all databases, data repositories, and comparative analysis tools in metabo- lomics because every lab has their own home-brew recipe for metabolomic experiments. Each lab has a different extraction protocol, profiling method, mass spectrometer, and the list goes on. This lack of standardization makes it difficult, if not impossible at times, to identify and confidently compare compounds. "The methods are never going to be as standard- ized as some of the other omics," said Broeckling. "Standard- ization is much more difficult with metabolomics than, say, genomics, and the reason is metabolites are way more diverse than genes are, chemically speaking." Although a set of rigorous standards may seem like a logical next step, the field of metabolomics may not yet be ready. "It's not a good idea yet to mandate that everybody do it the same at this point, because the technology is con- stantly evolving," Sumner pointed out. "But if you want to be able to compare things, then it is critical that people do try to work together to adopt some commonality. Right now, we're just trying to get people to report the fundamen- tal information of how they generated the data so it can be reused appropriately, but many people do not even do that." Nearly a decade has passed since Barnes' lab observed the dreaded "mystery peak." Like the rest of the metabolomics community, he now has numerous database options on hand, with his preference being METLIN. However, "if I don't go to METLIN, I just put the mass into Google, and sometimes it's in Google," he said. "I will use whatever resource I can find because none of the resources are complete. They can be enormous but not complete—and I may just have a com- pound that nobody has studied before." Mass spectrometers are a vital tool for metabolomics research and today, thanks to the growing number of available databases, more and more compounds identified by this technique are now known and be- ing used to further understand the role of metabolites in human health and disease. Monty Rakusen / Getty Images

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