Title | Predicting complex phenotype-genotype interactions to enable yeast engineering: Saccharomyces cerevisiae as a model organism and a cell factory. |
Publication Type | Journal Article |
Year of Publication | 2013 |
Authors | Dikicioglu, D, Pir, P, Oliver, SG |
Journal | Biotechnol J |
Volume | 8 |
Issue | 9 |
Pagination | 1017-34 |
Date Published | 2013 Sep |
ISSN | 1860-7314 |
Keywords | Biological Evolution, Biotechnology, Computational Biology, Fermentation, Gene Dosage, Genes, Essential, Genes, Fungal, Genetic Engineering, Genetic Fitness, Genotype, Humans, Models, Biological, Phenotype, Saccharomyces cerevisiae |
Abstract | <p>There is an increasing use of systems biology approaches in both "red" and "white" biotechnology in order to enable medical, medicinal, and industrial applications. The intricate links between genotype and phenotype may be explained through the use of the tools developed in systems biology, synthetic biology, and evolutionary engineering. Biomedical and biotechnological research are among the fields that could benefit most from the elucidation of this complex relationship. Researchers have studied fitness extensively to explain the phenotypic impacts of genetic variations. This elaborate network of dependencies and relationships so revealed are further complicated by the influence of environmental effects that present major challenges to our achieving an understanding of the cellular mechanisms leading to healthy or diseased phenotypes or optimized production yields. An improved comprehension of complex genotype-phenotype interactions and their accurate prediction should enable us to more effectively engineer yeast as a cell factory and to use it as a living model of human or pathogen cells in intelligent screens for new drugs. This review presents different methods and approaches undertaken toward improving our understanding and prediction of the growth phenotype of the yeast Saccharomyces cerevisiae as both a model and a production organism.</p> |
DOI | 10.1002/biot.201300138 |
Alternate Journal | Biotechnol J |
PubMed ID | 24031036 |
PubMed Central ID | PMC3910164 |
Grant List | BB/C505140/1 / / Biotechnology and Biological Sciences Research Council / United Kingdom |