Search

The ability to design and engineer organisms demands the ability to predict kinetic responses of novel regulatory networks built from well-characterized biological components. Surprisingly, few validated kinetic models of complex regulatory networks have been derived by combining models of the network components. A major bottleneck in producing such models is the difficulty of measuring in vivo rate constants for components of complex networks. We demonstrate that a simple, genetic approach to measuring rate constants in vivo produces an accurate kinetic model of the complex network that Saccharomyces cerevisiae employs to regulate the expression of genes encoding glucose transporters. The model predicts a transient pulse of transcription of HXT4 (but not HXT2 or HXT3) in response to addition of a small amount of glucose to cells, an outcome we observed experimentally. Our model also provides a mechanistic explanation for this result: HXT2-4 are governed by a type 2, incoherent feed forward regulatory loop involving the Rgt1 and Mig2 transcriptional repressors. The efficiency with which Rgt1 and Mig2 repress expression of each HXTgene determines which of them have a pulse of transcription in response to glucose. Finally, the model correctly predicts how lesions in the feed forward loop change the kinetics of induction of HXT4 expression. gene--regulatory networks | glucose transport | kinetic model | Saccharomyces cerevisiae | systems biology doi/ 10.1073/pnas.0912483107

A primary motivation for sequencing the mouse genome was to accelerate the discovery of mammalian genes by using sequence conservation between mouse and human to identify coding exons. Achieving this goal proved challenging because of the large proportion of the mouse and human genomes that is apparently conserved but apparently does not code for protein. We developed a two-stage procedure that exploits the mouse and human genome sequences to produce a set of genes with a much higher rate of experimental verification than previously reported prediction methods. RT-PCR amplification and direct sequencing applied to an initial sample of mouse predictions that do not overlap previously known genes verified the regions flanking one intron in 139 predictions, with verification rates reaching 76%. On average, the confirmed predictions show more restricted expression patterns than the mouse orthologs of known human genes, and two-thirds lack homologs in fish genomes, demonstrating the sensitivity of this dual-genome approach to hard-to-find genes. We verified 112 previously unknown homologs of known proteins, including two homeobox proteins relevant to developmental biology, an aquaporin, and a homolog of dystrophin. We estimate that transcription and splicing can be verified for >1,000 gene predictions identified by this method that do not overlap known genes. This is likely to constitute a significant fraction of the previously unknown, multiexon mammalian genes.

The ability to rationally manipulate the transcriptional states of cells would be of great use in medicine and bioengineering. We have developed an algorithm, NetSurgeon, which uses genomewide gene-regulatory networks to identify interventions that force a cell toward a desired expression state. We first validated NetSurgeon extensively on existing datasets. Next, we used Net-Surgeon to select transcription factor deletions aimed at improving ethanol production in Saccharomyces cerevisiae cultures that are catabolizing xylose. We reasoned that interventions that move the transcriptional state of cells using xylose toward that of cells producing large amounts of ethanol from glucose might improve xylose fermentation. Some of the interventions selected by NetSurgeon successfully promoted a fermentative transcriptional state in the absence of glucose, resulting in strainswith a 2.7-fold increase in xylose import rates, a 4-fold improvement in xylose integration into central carbon metabolism, or a 1.3-fold increase in ethanol production rate. We conclude by presenting an integrated model of transcriptional regulation and metabolic flux that will enable future efforts aimed at improving xylose fermentation to prioritize functional regulators of central carbon metabolism. [ABSTRACT FROM AUTHOR]