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Proteomics Moves into the Fast Lane

2016; Elsevier BV; Volume: 2; Issue: 3 Linguagem: Inglês

10.1016/j.cels.2016.03.002

2639-5460

Nicholas M. Riley, Alexander S. Hebert, Joshua J. Coon,

Metabolomics and Mass Spectrometry Studies

Three studies demonstrate the potential of state-of-the-art mass spectrometry-based proteomics for rapid, deep characterization of proteomes. Three studies demonstrate the potential of state-of-the-art mass spectrometry-based proteomics for rapid, deep characterization of proteomes. For years, genomic technologies have driven systems biology, primarily because methods for measuring actual effector molecules, proteins and metabolites, could not offer comparable depth or throughput. Two decades of vigorous mass spectrometry development, including introduction of a new mass analyzer (i.e., the Orbitrap), are beginning to pay off. Today, it is possible to obtain relatively deep measurements of the proteome in a matter of tens of minutes to a few hours. Three manuscripts in this issue of Cell Systems showcase the promise of a new era in large-scale biology in which proteome analysis is the centerpiece. Together, these studies exemplify how proteomics is poised to deliver new insights in biomedical research at a breakneck pace. Two of the manuscripts in this issue of Cell Systems, Pozniak et al., 2016Pozniak Y. Balint-Lahat N. Rudolph J.D. Lindskog C. Katzir R. Avivi C. Pontén F. Ruppin E. Barshack I. Geiger T. Cell Syst. 2016; 2 (this issue): 172-184Google Scholar and Sacco et al., 2016Sacco F. Silvestri A. Posca D. Pirrò S. Gherardini P.F. Castagnoli L. Mann M. Cesareni G. Cell Syst. 2016; 2 (this issue): 159-171Google Scholar, use high-resolution mass spectrometry to investigate breast cancer in both cell lines and human tissues. Pozniak et al., 2016Pozniak Y. Balint-Lahat N. Rudolph J.D. Lindskog C. Katzir R. Avivi C. Pontén F. Ruppin E. Barshack I. Geiger T. Cell Syst. 2016; 2 (this issue): 172-184Google Scholar quantitatively profile >10,000 proteins to elucidate clinically relevant signatures of energetic demand in tumorigenesis and metastatic spread. Sacco et al., 2016Sacco F. Silvestri A. Posca D. Pirrò S. Gherardini P.F. Castagnoli L. Mann M. Cesareni G. Cell Syst. 2016; 2 (this issue): 159-171Google Scholar characterize the anti-cancer activity of the biguanide drug metformin, quantifying metformin-dependent changes across nearly 8,000 proteins and nearly 16,000 sites of protein phosphorylation that reflect complex rewiring of mTOR signaling pathways. They also integrate this information with transcriptomic data and describe a portable strategy for mapping experimental data onto literature-derived signaling networks. The third work in this issue of Cell Systems, Geyer et al., 2016Geyer P.E. Kulak N.A. Pichler G. Holdt L.M. Teupser D. Mann M. Cell Syst. 2016; 2 (this issue): 185-195Abstract Full Text Full Text PDF PubMed Scopus (382) Google Scholar, expands proteome analysis with an eye toward the clinic. Briefly, this exciting paper describes a streamlined approach for preparing and analyzing the plasma proteome. With only a half an hour of mass spectral analysis, and a total of 3 hr from start to finish, the group can quantitatively monitor nearly 300 proteins, 49 of which are known plasma biomarkers. These studies provide strong evidence of momentum toward rapid and deep proteome characterization. The prediction Mann and co-workers made a few years ago—the coming of age of "complete and ubiquitous" proteomes (Mann et al., 2013Mann M. Kulak N.A. Nagaraj N. Cox J. Mol. Cell. 2013; 49: 583-590Abstract Full Text Full Text PDF PubMed Scopus (285) Google Scholar)—has proven largely accurate with the publication of near-complete to complete proteome analysis in both simple (e.g., yeast) and complex (i.e., mammalian) systems. Two draft maps of the human proteome, published concurrently in 2014, stand as true tour de force case studies of what proteomics can accomplish. These studies measured direct evidence for protein translation of the majority of the ∼20,000 genes encoded in the human genome (Kim et al., 2014Kim M.S. Pinto S.M. Getnet D. Nirujogi R.S. Manda S.S. Chaerkady R. Madugundu A.K. Kelkar D.S. Isserlin R. Jain S. et al.Nature. 2014; 509: 575-581Crossref PubMed Scopus (1505) Google Scholar, Wilhelm et al., 2014Wilhelm M. Schlegl J. Hahne H. Moghaddas Gholami A. Lieberenz M. Savitski M.M. Ziegler E. Butzmann L. Gessulat S. Marx H. Mathieson T. Lemeer S. Schnatbaum K. Reimer U. Wenschuh H. Mollenhauer M. Slotta-Huspenina J. Boese J.H. Bantscheff M. Gerstmair A. Faerber F. Kuster B. Nature. 2014; 509: 582-587Crossref PubMed Scopus (1317) Google Scholar) and stimulated many productive discussions: whether all expressed proteins were detected, how to calculate false discovery rates on such large datasets, and how to accomplish similar feats on more practical timescales. Only 5 years ago, meaningful proteome analysis in 1 hr was simply beyond expectation. To fulfill the need for rapid and comprehensive proteome analysis, much attention has been devoted to maximizing proteomic depth per unit time. In 2013, Zubarev and co-workers identified nearly 5,000 proteins from cultured human cells following just 4 hr of analysis (Pirmoradian et al., 2013Pirmoradian M. Budamgunta H. Chingin K. Zhang B. Astorga-Wells J. Zubarev R.A. Mol. Cell. Proteomics. 2013; 12: 3330-3338Crossref PubMed Scopus (106) Google Scholar). In the following year, our group described technology for detection of 4,000 proteins (∼90% of the expressed proteome) from yeast in just over 1 hr (Hebert et al., 2014Hebert A.S. Richards A.L. Bailey D.J. Ulbrich A. Coughlin E.E. Westphall M.S. Coon J.J. Mol. Cell. Proteomics. 2014; 13: 339-347Crossref PubMed Scopus (411) Google Scholar). And now, just 2 years later, Geyer et al., 2016Geyer P.E. Kulak N.A. Pichler G. Holdt L.M. Teupser D. Mann M. Cell Syst. 2016; 2 (this issue): 185-195Abstract Full Text Full Text PDF PubMed Scopus (382) Google Scholar have further pushed these limits with a half-hour analysis of human plasma. All of these studies are enabled by the culmination of several cutting-edge proteomic technologies, including substantial improvements in mass spectrometry instrument acquisition speed, judiciously selected chromatographic conditions, and simple yet robust sample preparation methods. These new approaches, along with labeling technologies for multiplexed quantification, where several samples are compared simultaneously, continue to increase throughput in large-scale protein analysis (Erickson et al., 2015Erickson B.K. Jedrychowski M.P. McAlister G.C. Everley R.A. Kunz R. Gygi S.P. Anal. Chem. 2015; 87: 1241-1249Crossref PubMed Scopus (120) Google Scholar, Rauniyar and Yates, 2014Rauniyar N. Yates 3rd, J.R. J. Proteome Res. 2014; 13: 5293-5309Crossref PubMed Scopus (395) Google Scholar, Svinkina et al., 2015Svinkina T. Gu H. Silva J.C. Mertins P. Qiao J. Fereshetian S. Jaffe J.D. Kuhn E. Udeshi N.D. Carr S.A. Mol. Cell. Proteomics. 2015; 14: 2429-2440Crossref PubMed Scopus (120) Google Scholar). Figure 1 highlights the trend of consistent improvements in proteins characterized per hour over the past 5 years for both human and yeast proteomes. As mass spectrometer technologies steadily advance, we can anticipate continued progress toward whole human proteome analysis in just minutes or hours. Currently, instead of questioning the possibility of whole-proteome characterization, many investigators seek to balance sufficient proteomic depth with rapid throughput. Such balance enables large-scale experiments involving tens to hundreds of samples, with the goal of more thorough investigation of biological systems of interest. This concentration on pragmatic, if not complete, proteome analyses represents the concerted effort of the proteomic community to translate the technological gains of the past few years into tools with high utility for biological research. The payoff of this strategy is beginning to emerge through studies like Pozniak et al., 2016Pozniak Y. Balint-Lahat N. Rudolph J.D. Lindskog C. Katzir R. Avivi C. Pontén F. Ruppin E. Barshack I. Geiger T. Cell Syst. 2016; 2 (this issue): 172-184Google Scholar, Sacco et al., 2016Sacco F. Silvestri A. Posca D. Pirrò S. Gherardini P.F. Castagnoli L. Mann M. Cesareni G. Cell Syst. 2016; 2 (this issue): 159-171Google Scholar, and Geyer et al., 2016Geyer P.E. Kulak N.A. Pichler G. Holdt L.M. Teupser D. Mann M. Cell Syst. 2016; 2 (this issue): 185-195Abstract Full Text Full Text PDF PubMed Scopus (382) Google Scholar. What, then, does the future hold? Striking an ideal balance between the demand for complete proteome characterization and the practical limitations of proteomic technology will be key. Thankfully, necessary sacrifices in proteomic depth in the name of expediency are becoming less pronounced. The era of practical proteomics—that is, near-complete proteomes within hours rather than days—will focus on improved sample preparation, chromatographic conditions, and data-analysis methods to capitalize on the advances in sensitivity and speed of the newest generations of mass spectrometers. Practical proteomics is already gaining prevalence, as evidenced by Geyer et al., 2016Geyer P.E. Kulak N.A. Pichler G. Holdt L.M. Teupser D. Mann M. Cell Syst. 2016; 2 (this issue): 185-195Abstract Full Text Full Text PDF PubMed Scopus (382) Google Scholar, who process samples in parallel in a 96-well plate, and Pozniak et al., 2016Pozniak Y. Balint-Lahat N. Rudolph J.D. Lindskog C. Katzir R. Avivi C. Pontén F. Ruppin E. Barshack I. Geiger T. Cell Syst. 2016; 2 (this issue): 172-184Google Scholar and Sacco et al., 2016Sacco F. Silvestri A. Posca D. Pirrò S. Gherardini P.F. Castagnoli L. Mann M. Cesareni G. Cell Syst. 2016; 2 (this issue): 159-171Google Scholar, who handle small amounts in input material by performing fractionation and enrichment steps in a pipette tip. Additionally, the quantitative strategies used in these three studies, including both label and label-free quantitation, will continue to facilitate reproducible quantitative comparisons between many proteomes. These improvements will usher in more thorough experimental designs enabled by the ability to characterize each proteome quickly. Instead of comparisons among tens of samples, researchers will characterize hundreds of samples in realistic time frames, and new data acquisition strategies continue to promise reproducible proteome-wide characterization across many samples (Selevsek et al., 2015Selevsek N. Chang C.-Y. Gillet L.C. Navarro P. Bernhardt O.M. Reiter L. Cheng L.-Y. Vitek O. Aebersold R. Mol. Cell. Proteomics. 2015; 14: 739-749Crossref PubMed Scopus (134) Google Scholar). These capabilities will open many exciting avenues for multi-faceted comparisons, longitudinal studies, and even deeper and more expedient characterization of known systems, such as the human proteome. The next frontier will be robust analysis of post-translational modifications. Even as we approach routine whole-proteome characterization, confident reports of a complete catalog of any post-translational modification, much less all of them, have yet to emerge. Phosphoproteomics, or the global analysis of protein phosphorylation, is a challenging endeavor with broad implications in biological research and has especially benefited from recent developments in proteomic technology (Riley and Coon, 2016Riley N.M. Coon J.J. Anal. Chem. 2016; 88: 74-94Crossref Scopus (166) Google Scholar). Quantifying 15,813 dynamic phosphosites using single-shot ∼4 hr analyses per sample, the work of Sacco et al., 2016Sacco F. Silvestri A. Posca D. Pirrò S. Gherardini P.F. Castagnoli L. Mann M. Cesareni G. Cell Syst. 2016; 2 (this issue): 159-171Google Scholar highlights the progress the field has already made. Instead of profiling an entire phosphoproteome, which likely includes 105 phosphorylation sites, we anticipate technologies that permit quantification of ∼25,000 phosphosites in hours or minutes. Such capability is doubtless needed, and we are well on our way to this goal. Humphrey et al., 2015Humphrey S.J. Azimifar S.B. Mann M. Nat. Biotechnol. 2015; 33: 990-995Crossref PubMed Scopus (310) Google Scholar, for example, detect ∼10,000 phosphosites in dozens of cell and tissue samples following ∼1 hr of mass spectral analysis each. Similar capabilities seem imminent for other widely prevalent post-translational modifications (Doll and Burlingame, 2015Doll S. Burlingame A.L. ACS Chem. Biol. 2015; 10: 63-71Crossref PubMed Scopus (137) Google Scholar). In summary, the highlighted studies are the product of years of technological advances in mass spectrometry and provide a glimpse into the exciting future to come: a future of fast, comprehensive, and accessible proteome measurements. In this coming era, biomedical researchers will have access to broad, systems-level information on proteins and their post-translational modifications to drive their research in myriad, previously unnavigable directions. Plasma Proteome Profiling to Assess Human Health and DiseaseGeyer et al.Cell SystemsMarch 23, 2016In BriefA rapid and highly reproducible proteomic workflow delivers a systemic-view proteomic portrait of a person's health state from a single drop of blood. Full-Text PDF Open AccessDeep Proteomics of Breast Cancer Cells Reveals that Metformin Rewires Signaling Networks Away from a Pro-growth StateSacco et al.Cell SystemsMarch 3, 2016In BriefSacco et al. found that a new generally applicable method that combines deep proteomics with prior knowledge reveals detailed and global molecular mechanisms contributing to the unexpectedly complex anti-cancer activity of metformin. Full-Text PDF Open ArchiveSystem-wide Clinical Proteomics of Breast Cancer Reveals Global Remodeling of Tissue HomeostasisPozniak et al.Cell SystemsMarch 3, 2016In BriefDeep proteomic analysis of ER-positive clinical breast tumors points to key proteins and processes that are associated with tumorigenesis and metastatic spread. Full-Text PDF Open Archive