From drug to protein: using yeast genetics for high-throughput target discovery

The budding yeast Saccharomyces cerevisiae has long been an effective eukaryotic model system for understanding basic cellular processes. The genetic tractability and ease of manipulation in the laboratory make yeast well suited for large-scale chemical and genetic screens. Several recent studies describing the use of yeast genetics for high-throughput drug target identification are discussed in this review.     

Targeted disruption of the sheep MSTN gene by engineered zinc-finger nucleases

Prior to the development of zinc-finger nuclease technology, genetic manipulation by gene targeting achieved limited success in mammals, with the exception of mice and rat. Although ZFNs demonstrated highly effective gene targeted disruption in various model organisms, the activity of ZFNs in large domestic animals may be very low, and the probability of identifying ZFN-mediated positive targeted disruption events is small. In this paper, we used the context-dependent assembly method to synthesize two pairs of ZFNs targeted to the sheep MSTN gene. We verified the activity of these ZFNs using an mRFP-MBS-eGFP dual-fluorescence reporter system in HEK293T cells and, according to the expression level of eGFP, we obtained a pair of ZFNs that can recognize and cut the targeted MSTN site in the reporter vector. The activity of ZFN was increased by cold stimulation at 30 °C and by mutant the wildtype FokI in ZFN with its counterpart Sharkeys. Finally, the ZF-Sharkeys and reporter vector were cotransfected into sheep fetal fibroblasts and two MSTN mutant cell lines, identified by flow cytometry and sequencing, were obtained.     

Optimization of protein expression systems for modern drug discovery

The expression of high levels of stable and functional proteins remains a bottleneck in many scientific endeavors, including the determination of structures in a high-throughput fashion or the screening for novel active compounds in modern drug discovery. Recently, numerous developments have been made to improve the production of soluble and active proteins in heterologous expression systems. These include modifications to the expression constructs, the introduction of new and/or improved pro- and eukaryotic expression systems, and the development of improved cell-free protein synthesis systems. The introduction of robotics has enabled a massive parallelization of expression experiments, thereby vastly increasing the throughput and, hopefully, the output of such experiments. In addition, the big challenges of recombinant overexpression of membrane and secreted proteins are tackled, and some new methods are reviewed.     

Genetic inheritance of gene expression in human cell lines

Combining genetic inheritance information, for both molecular profiles and complex traits, is a promising strategy not only for detecting quantitative trait loci (QTLs) for complex traits but for understanding which genes, pathways, and biological processes are also under the influence of a given QTL. As a primary step in determining the feasibility of such an approach in humans, we present the largest survey to date, to our knowledge, of the heritability of gene-expression traits in segregating human populations. In particular, we measured expression for 23,499 genes in lymphoblastoid cell lines for members of 15 Centre d'Etude du Polymorphisme Humain (CEPH) families. Of the total set of genes, 2,340 were found to be expressed, of which 31% had significant heritability when a false-discovery rate of 0.05 was used. QTLs were detected for 33 genes on the basis of at least one P value <.000005. Of these, 13 genes possessed a QTL within 5 Mb of their physical location. Hierarchical clustering was performed on the basis of both Pearson correlation of gene expression and genetic correlation. Both reflected biologically relevant activity taking place in the lymphoblastoid cell lines, with greater coherency represented in Kyoto Encyclopedia of Genes and Genomes database (KEGG) pathways than in Gene Ontology database pathways. However, more pathway coherence was observed in KEGG pathways when clustering was based on genetic correlation than when clustering was based on Pearson correlation. As more expression data in segregating populations are generated, viewing clusters or networks based on genetic correlation measures and shared QTLs will offer potentially novel insights into the relationship among genes that may underlie complex traits.