research highlights

PROTEOMICS The human proteome takes the spotlight

Two papers report mass spectrometry– big data. “We then thought, include some surpris- based draft maps of the human proteome ‘What is a potentially good ing findings. For example, and provide broadly accessible resources. illustration for the utility Kuster’s team found protein For years, members of the proteomics of such a database?’” says evidence for 430 long inter- community have been trying to garner sup- Kuster. “We very quickly genic noncoding RNAs, port for a large-scale project to exhaustively got to the idea, ‘Why don’t which have been thought map the normal human proteome, including we try to put together the not to be translated into pro- identifying all post-translational modifica- human proteome?’” tein. Pandey’s team refined tions and protein-protein interactions and The two groups took the annotations of 808 genes providing targeted mass spectrometry assays slightly different strategies and also found evidence and antibodies for all human proteins. But a towards this common goal. for the translation of many Nik Spencer/Nature Publishing Group Publishing Nik Spencer/Nature lack of consensus on how to exactly define Pandey’s lab examined 30 noncoding RNAs and pseu- Two groups provide mass the proteome, how to carry out such a mis- normal tissues, including spectrometry evidence for dogenes. sion and whether the technology is ready has adult and fetal tissues, as ~90% of the human proteome. Obtaining evidence for not so far convinced any funding agencies to well as primary hematopoi- the last roughly 10% of pro- fund on such an ambitious project. etic cells, subjecting them to comprehensive, teins not detected in these studies, will not “I have been very impatient about this,” label-free quantitative mass spectrometry be easy. Pandey suggests that proteomics says Akhilesh Pandey of Johns Hopkins analysis and analyzing the data with a strin- researchers will need to look at highly spe- University School of Medicine in Baltimore, gent bioinformatics pipeline (Kim et al., cialized tissues, such as parts of the eye or the principal investigator of one of two recent 2014). In total, Pandey and colleagues detect- the nasal epithelium, to find the missing reports describing mass spectrometry–based ed about 84% of the roughly 20,000 annotat- proteins. Kuster believes that the lack of draft maps of the human proteome. While ed human protein-coding genes. They also mass spectrometry evidence for some pre-

Nature America, Inc. All rights reserved. America, Inc. © 201 4 Nature listening to the debate during a session created a biologist-friendly resource called dicted proteins suggests that these proteins about a possible Human Proteome Project the Human Proteome Map, which allows may have been recently “retired” by evolu- at a conference of the Human Proteome users to explore protein expression across tion; determining this with certainty will Organization several years ago, he realized tissues. require focused efforts. To facilitate this, npg that his lab was in a good position to perform Kuster’s team took a different tack ProteomicsDB has an “adopt-a-protein” one of the human proteome project’s goals: (Wilhelm et al., 2014). “In talking to col- feature to entice researchers to follow up on finding evidence for all human protein- leagues over the last few years, most people predicted proteins that still elude detection. coding genes using mass spectrometry. As agreed that we had collectively probably The Human Proteome Map and the founder of the Institute of Bioinformatics seen the human proteome already, just that ProteomicsDB will be valuable resources for in Bangalore, India, his team also had the we hadn’t put it together,” says Kuster. His the entire biological community. The fact resources and bioinformatics know-how to lab amalgamated publicly available raw that two independent data sets are available carry out such a study. data sets and those from colleagues, which also increases the impact of the work. “The Around the same time, at the Technische together made up about 60% of the data that community, they have cross-validation,” says Universität München in Germany, Bernhard they analyzed using their own rigorous bio- Pandey. “This is beautiful.” The two groups Kuster was realizing that existing tools for informatics pipeline. The other 40% of the were unaware of how far each other’s efforts managing proteomics data were not meet- data came from new quantitative mass spec- had progressed but were happily surprised to ing his laboratory’s needs for mining and trometry experiments, in which they profiled see that the papers were submitted to Nature cross-referencing. After reading an article 60 tissues, 13 body fluids and 147 cell lines. at roughly the same time and published about in-memory database computing, he In total they obtained mass spectrometry together. Now they are collaborating to ana- contacted the German business operations evidence for about 92% of predicted protein- lyze the collective data. software company SAP to see whether this coding genes. Allison Doerr might provide a solution for handling pro- Both groups found evidence for many pro- RESEARCH PAPERS Kim, M.-S. et al. A draft map of the human proteome. teomics data. This resulted in the creation teins that had not been previously observed Nature 509, 575–581 (2014). of ProteomicsDB, which contains useful, by mass spectrometry, complementing Wilhelm, M. et al. Mass-spectrometry-based draft of computationally efficient tools for analyzing genome annotation efforts. The data also the human proteome. Nature 509, 582–587 (2014).

nature methods | VOL.11 NO.7 | JULY 2014 | 709