| Literature DB >> 21266995 |
André B Canelas1, Nicola Harrison, Alessandro Fazio, Jie Zhang, Juha-Pekka Pitkänen, Joost van den Brink, Barbara M Bakker, Lara Bogner, Jildau Bouwman, Juan I Castrillo, Ayca Cankorur, Pramote Chumnanpuen, Pascale Daran-Lapujade, Duygu Dikicioglu, Karen van Eunen, Jennifer C Ewald, Joseph J Heijnen, Betul Kirdar, Ismo Mattila, Femke I C Mensonides, Anja Niebel, Merja Penttilä, Jack T Pronk, Matthias Reuss, Laura Salusjärvi, Uwe Sauer, David Sherman, Martin Siemann-Herzberg, Hans Westerhoff, Johannes de Winde, Dina Petranovic, Stephen G Oliver, Christopher T Workman, Nicola Zamboni, Jens Nielsen.
Abstract
The field of systems biology is often held back by difficulties in obtaining comprehensive, high-quality, quantitative data sets. In this paper, we undertook an interlaboratory effort to generate such a data set for a very large number of cellular components in the yeast Saccharomyces cerevisiae, a widely used model organism that is also used in the production of fuels, chemicals, food ingredients and pharmaceuticals. With the current focus on biofuels and sustainability, there is much interest in harnessing this species as a general cell factory. In this study, we characterized two yeast strains, under two standard growth conditions. We ensured the high quality of the experimental data by evaluating a wide range of sampling and analytical techniques. Here we show significant differences in the maximum specific growth rate and biomass yield between the two strains. On the basis of the integrated analysis of the high-throughput data, we hypothesize that differences in phenotype are due to differences in protein metabolism.Entities:
Mesh：
Year: 2010 PMID： 21266995 DOI： 10.1038/ncomms1150
Source DB: PubMed Journal: Nat Commun ISSN： 2041-1723 Impact factor: 14.919