New insights into functional regulation in MS-based drug profiling
Data(s) |
24/05/2016
24/05/2016
08/01/2016
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Resumo |
We present a novel data analysis strategy which combined with subcellular fractionation and liquid chromatography-mass spectrometry (LC-MS) based proteomics provides a simple and effective workflow for global drug profiling. Five subcellular fractions were obtained by differential centrifugation followed by high resolution LC-MS and complete functional regulation analysis. The methodology combines functional regulation and enrichment analysis into a single visual summary. The workflow enables improved insight into perturbations caused by drugs. We provide a statistical argument to demonstrate that even crude subcellular fractions leads to improved functional characterization. We demonstrate this data analysis strategy on data obtained in a MS-based global drug profiling study. However, this strategy can also be performed on other types of large scale biological data. We thank Dr. Fridtjof Lund-Johansen for critical comments on the manuscript text. The Proteomics Resource Center at The Rockefeller University acknowledges funding from the Leona M. and Harry B. Helmsley Charitable Trust for mass spectrometer instrumentation. Cost of all experiments including MS analysis were supported by the Portuguese Foundation for Science and Technology (EXPL/DTP-PIC/0616/2013). R.M. is supported FCT investigator program 2012. A.S.C. is supported by the Portuguese Foundation for Science and Technology (FCT), financed by the European Social Funds (COMPETE-FEDER) and national funds of the Portuguese Ministry of Education and Science (POPH-QREN) fellowship SFRH/85569/2012. |
Identificador |
Sci Rep. 2016 Jan 8;6:18826. doi: 10.1038/srep18826 2045-2322 http://hdl.handle.net/10400.18/3818 doi: 10.1038/srep18826. |
Idioma(s) |
eng |
Publicador |
Nature Publishing Group |
Relação |
info:eu-repo/grantAgreement/FCT/3599-PPCDT/133638/PT http://www.nature.com/articles/srep18826 |
Direitos |
openAccess http://creativecommons.org/licenses/by-nc/4.0/ |
Palavras-Chave | #LC-MS #Proteomics #Biochemistry #Cell Biology #Cancer #Computational biology and bioinformatics #Chromatography–mass Spectrometry #Genomica Funcional #Genómica Funcional e Estrutural |
Tipo |
article |