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预测复杂表型-基因型相互作用以实现酵母工程:以酿酒酵母为模式生物和细胞工厂。

Predicting complex phenotype-genotype interactions to enable yeast engineering: Saccharomyces cerevisiae as a model organism and a cell factory.

机构信息

Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, CB2 1GA, Cambridge, UK.

出版信息

Biotechnol J. 2013 Sep;8(9):1017-34. doi: 10.1002/biot.201300138. Epub 2013 Aug 23.

Abstract

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.

摘要

为了能够实现医学、药物和工业应用,系统生物学方法在“红色”和“白色”生物技术中得到了越来越多的应用。通过使用系统生物学、合成生物学和进化工程中开发的工具,可以解释基因型和表型之间错综复杂的联系。生物医学和生物技术研究是最能受益于阐明这种复杂关系的领域之一。研究人员已经广泛研究了适合度,以解释遗传变异对表型的影响。如此揭示的这个复杂的依赖关系网络,由于环境影响的影响而变得更加复杂,这给我们理解导致健康或患病表型或优化生产产量的细胞机制带来了重大挑战。对复杂的基因型-表型相互作用及其准确预测的深入了解,应该使我们能够更有效地将酵母工程化为细胞工厂,并将其用作人类或病原体细胞的活体模型,以进行新药物的智能筛选。本文综述了不同的方法和途径,旨在提高我们对酵母酿酒酵母生长表型的理解和预测,作为模型和生产生物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33f5/3910164/f208b053b431/biot0008-1017-f1.jpg

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