Current research interests of the Stan Cohen lab:

Certain of our investigations are aimed at elucidating the signals that govern RNA decay. We use E. coli to investigate the mechanism of action of specific ribonucleases and related proteins, and to identify RNA substrate signals that govern stability. We are also interested in the developmental aspects of RNA stability, and study mechanisms that lead to changes in decay during morphological and biochemical differentiation in the developmentally complex bacterial genus, Streptomyces. Recently, we have begun to use a novel approach, random homozygous knockout (RHKO; see below), to identify components of RNA decay pathways in eukaryotic cells.

Our lab has long been interested in the mechanisms that lead to the evolution and dissemination of antibiotic resistance, and currently, we continue to pursue these interests by investigating the biology of linear plasmids of Streptomyces. In particular, we are interested in the mechanisms by which these plasmids interact with chromosomes to acquire and transfer genes, how plasmids evolve and undergo alterations in structure and how their telomeres function to facilitate these events and propagate plasmid DNA. Studies using DNA microarrays are aimed directly at understanding genetic pathways that regulate antibiotic production and resistance.

Some members of our lab use RHKO (random homozygous knockout) and related approaches, together with DNA microarray analysis, to investigate processes that limit the growth of mammalian cells. RHKO, a genetic method we developed to inactivate mammalian cell genes randomly and homozygously, enables the identification of genes whose loss of function leads to altered growth properties. The TSG101 gene, which was the first gene we identified using RHKO, has now been found to affect endocytic processes as well as established pathways that regulate cell division, and remains an important subject of study in our lab.

A small bioinformatics team within our research group has developed and implemented GABRIEL to aid our microarray analyses. GABRIEL (Genetic Analysis By Rules Incorporating Expert Logic) is a novel system of computer programs that incorporates expert knowledge into rules and statistical algorithms used for analysis of genetic data.

Example Search Keywords for PubMed: RNA decay, RNA-binding proteins, ribonucleases, polyadenylation, telomeres, plasmids, linear replicons, DNA partitioning, RHKO, tumor suppressor, cancer biology, cell growth arrest, cell senescence, gene expression, GABRIEL, DNA microarray, bioinformatics, TSG101, MDM2