Mass action models versus the Hill model: an analysis of tetrameric human thymidine kinase 1 positive cooperativity

Reprogramming EF-hands for design of catalytically amplified lanthanide sensors

We recently reported that a computationally designed catalyst nicknamed AlleyCat facilitates C-H proton abstraction in Kemp elimination at neutral pH in a selective and calcium-dependent fashion by a factor of approximately 100,000 (Korendovych et al. in Proc. Natl. Acad. Sci. USA 108:6823, 2011). Kemp elimination produced a colored product that can be easily read out, thus making AlleyCat a catalytically amplified metal sensor for calcium. Here we report that metal-binding EF-hand motifs in AlleyCat could be redesigned to incorporate trivalent metal ions without significant loss of catalytic activity. Mutation of a single neutral residue at position 9 of each of the EF-hands to glutamate results in almost a two orders of magnitude improvement of selectivity for trivalent metal ions over calcium. Development of this new lanthanide-dependent switchable Kemp eliminase, named CuSeCat EE, provides the foundation for further selectivity improvement and broadening the scope of the repertoire of metals for sensing. A concerted effort in the design of switchable enzymes has many environmental, sensing, and metal ion tracking applications.

Using GeneReg to construct time delay gene regulatory networks

Background

Understanding gene expression and regulation is essential for understanding biological mechanisms. Because gene expression profiling has been widely used in basic biological research, especially in transcription regulation studies, we have developed GeneReg, an easy-to-use R package, to construct gene regulatory networks from time course gene expression profiling data; More importantly, this package can provide information about time delays between expression change in a regulator and that of its target genes.

Findings

The R package GeneReg is based on time delay linear regression, which can generate a model of the expression levels of regulators at a given time point against the expression levels of their target genes at a later time point. There are two parameters in the model, time delay and regulation coefficient. Time delay is the time lag during which expression change of the regulator is transmitted to change in target gene expression. Regulation coefficient expresses the regulation effect: a positive regulation coefficient indicates activation and negative indicates repression. GeneReg was implemented on a real Saccharomyces cerevisiae cell cycle dataset; more than thirty percent of the modeled regulations, based entirely on gene expression files, were found to be consistent with previous discoveries from known databases.

Conclusions

GeneReg is an easy-to-use, simple, fast R package for gene regulatory network construction from short time course gene expression data. It may be applied to study time-related biological processes such as cell cycle, cell differentiation, or causal inference.