Journal Article10.1038/NMETH778
A streamlined platform for high-content functional proteomics of primary human specimens
Nadim Jessani,Nadim Jessani,Sherry Niessen,Binqing Wei,Monica Nicolau,Mark Humphrey,Youngran Ji,Wonshik Han,Dong-Young Noh,John R. Yates,Stefanie S. Jeffrey,Benjamin F. Cravatt +11 more
TL;DR: A functional proteomics strategy that unites the activity-based protein profiling and multidimensional protein identification technologies (ABPP-MudPIT) for the streamlined analysis of human samples and identified more than 50 enzyme activities in human breast tumors, nearly a third of which represent previously uncharacterized proteins.
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Abstract: Achieving information content of satisfactory breadth and depth remains a formidable challenge for proteomics. This problem is particularly relevant to the study of primary human specimens, such as tumor biopsies, which are heterogeneous and of finite quantity. Here we present a functional proteomics strategy that unites the activity-based protein profiling and multidimensional protein identification technologies (ABPP-MudPIT) for the streamlined analysis of human samples. This convergent platform involves a rapid initial phase, in which enzyme activity signatures are generated for functional classification of samples, followed by in-depth analysis of representative members from each class. Using this two-tiered approach, we identified more than 50 enzyme activities in human breast tumors, nearly a third of which represent previously uncharacterized proteins. Comparison with cDNA microarrays revealed enzymes whose activity, but not mRNA expression, depicted tumor class, underscoring the power of ABPP-MudPIT for the discovery of new markers of human disease that may evade detection by other molecular profiling methods.
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Citations
Activity-Based Protein Profiling: From Enzyme Chemistry to Proteomic Chemistry
TL;DR: Activity-based protein profiling (ABPP) has emerged as a powerful chemical proteomic strategy to characterize enzyme function directly in native biological systems on a global scale as mentioned in this paper, and the basic technology of ABPP, the enzyme classes addressable by this method, and the biological discoveries attributable to its application.
A Comprehensive Profile of Brain Enzymes that Hydrolyze the Endocannabinoid 2-Arachidonoylglycerol
TL;DR: It is revealed that approximately 85% of brain 2-AG hydrolase activity can be ascribed to MAGL, and that the remaining 15% is mostly catalyzed by two uncharacterized enzymes, ABHD6 and ABHD12.
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Monoacylglycerol Lipase Regulates a Fatty Acid Network that Promotes Cancer Pathogenesis
Daniel K. Nomura,Jonathan Z. Long,Sherry Niessen,Heather Hoover,Shu-Wing Ng,Benjamin F. Cravatt +5 more
TL;DR: Overexpression of MAGL in nonaggressive cancer cells recapitulates this fatty acid network and increases their pathogenicity-phenotypes that are reversed by an MAGL inhibitor, indicating that exogenous sources of fatty acids can contribute to malignancy in cancers lacking MAGL activity.
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Selective blockade of 2-arachidonoylglycerol hydrolysis produces cannabinoid behavioral effects
Jonathan Z. Long,Weiwei Li,Lamont Booker,James J. Burston,Steven G. Kinsey,Joel E. Schlosburg,Franciso J Pavón,Antonia Serrano,Dana E. Selley,Loren H. Parsons,Aron H. Lichtman,Benjamin F. Cravatt +11 more
TL;DR: 2-AG endogenously modulates several behavioral processes classically associated with the pharmacology of cannabinoids and point to overlapping and unique functions for 2-AG and anandamide in vivo, indicating a functional segregation of endocannabinoid signaling pathways in vivo.
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The biological impact of mass-spectrometry-based proteomics
TL;DR: It is clear that mass-spectrometry-based proteomics is now a powerful 'hypothesis-generating engine' that, when combined with complementary molecular, cellular and pharmacological techniques, provides a framework for translating large data sets into an understanding of complex biological processes.
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