Martin Wühr1,2, Robert M Freeman1, Marc Presler1, Marko E Horb3, Leonid Peshkin1, Steven Gygi2, Marc W Kirschner1. 1. Department of Systems Biology, Harvard Medical School, 02115 Boston, MA, USA. 2. Department of Cell Biology, Harvard Medical School, 02115 Boston, MA, USA. 3. Bell Center for Regenerative Biology and Tissue Engineering and National Xenopus Resource, Marine Biological Laboratory, Woods Hole, MA 02543, USA.
Abstract
BACKGROUND: Mass spectrometry-based proteomics enables the global identification and quantification of proteins and their posttranslational modifications in complex biological samples. However, proteomic analysis requires a complete and accurate reference set of proteins and is therefore largely restricted to model organisms with sequenced genomes. RESULTS: Here, we demonstrate the feasibility of deep genome-free proteomics by using a reference proteome derived from heterogeneous mRNA data. We identify more than 11,000 proteins with 99% confidence from the unfertilized Xenopus laevis egg and estimate protein abundance with approximately 2-fold precision. Our reference database outperforms the provisional gene models based on genomic DNA sequencing and references generated by other methods. Surprisingly, we find that many proteins in the egg lack mRNA support and that many of these proteins are found in blood or liver, suggesting that they are taken up from the blood plasma, together with yolk, during oocyte growth and maturation, potentially contributing to early embryogenesis. CONCLUSION: To facilitate proteomics in nonmodel organisms, we make our platform available as an online resource that converts heterogeneous mRNA data into a protein reference set. Thus, we demonstrate the feasibility and power of genome-free proteomics while shedding new light on embryogenesis in vertebrates.
BACKGROUND: Mass spectrometry-based proteomics enables the global identification and quantification of proteins and their posttranslational modifications in complex biological samples. However, proteomic analysis requires a complete and accurate reference set of proteins and is therefore largely restricted to model organisms with sequenced genomes. RESULTS: Here, we demonstrate the feasibility of deep genome-free proteomics by using a reference proteome derived from heterogeneous mRNA data. We identify more than 11,000 proteins with 99% confidence from the unfertilized Xenopus laevis egg and estimate protein abundance with approximately 2-fold precision. Our reference database outperforms the provisional gene models based on genomic DNA sequencing and references generated by other methods. Surprisingly, we find that many proteins in the egg lack mRNA support and that many of these proteins are found in blood or liver, suggesting that they are taken up from the blood plasma, together with yolk, during oocyte growth and maturation, potentially contributing to early embryogenesis. CONCLUSION: To facilitate proteomics in nonmodel organisms, we make our platform available as an online resource that converts heterogeneous mRNA data into a protein reference set. Thus, we demonstrate the feasibility and power of genome-free proteomics while shedding new light on embryogenesis in vertebrates.
Authors: A Goffeau; B G Barrell; H Bussey; R W Davis; B Dujon; H Feldmann; F Galibert; J D Hoheisel; C Jacq; M Johnston; E J Louis; H W Mewes; Y Murakami; P Philippsen; H Tettelin; S G Oliver Journal: Science Date: 1996-10-25 Impact factor: 47.728
Authors: Vanessa C Evans; Gary Barker; Kate J Heesom; Jun Fan; Conrad Bessant; David A Matthews Journal: Nat Methods Date: 2012-11-11 Impact factor: 28.547
Authors: Martin Beck; Alexander Schmidt; Johan Malmstroem; Manfred Claassen; Alessandro Ori; Anna Szymborska; Franz Herzog; Oliver Rinner; Jan Ellenberg; Ruedi Aebersold Journal: Mol Syst Biol Date: 2011-11-08 Impact factor: 11.429
Authors: Paul Mooney; Taylor Sulerud; James F Pelletier; Matthew R Dilsaver; Miroslav Tomschik; Christoph Geisler; Jesse C Gatlin Journal: Cytoskeleton (Hoboken) Date: 2017-05-22
Authors: Predrag Jevtić; Ana Milunović-Jevtić; Matthew R Dilsaver; Jesse C Gatlin; Daniel L Levy Journal: Int J Dev Biol Date: 2016 Impact factor: 2.203