Deciphering the Transcriptional Networks that Control Vertebrate Development
There is still a great deal to learn about the design principles that guide vertebrate development. Since all cells in an organism contain the same genes, transcribing different sets of genes is what confers a cell’s specialized role. Which genes get turned on or off to create a particular cell type at the right time, in the right place during the development of an organism? This is one of the pivotal questions in developmental biology. We have developed a technology, Transposon “Calling Cards,” to attack this question in a novel way, and we have shown that it works in yeast and mammalian cell culture. We will produce a record of gene activation at various stages of neural differentiation, watching as stem cells and their progeny specialize. These data will contribute to the field by providing a blueprint for the generation of many cell types, and could ultimately guide the reprogramming of embryonic or induced pluripotent stem cells to produce specific cell types.
Epigenetic modifications of DNA play an important role in mammalian development because they act to specify and maintain the expression state of different genes in different cell lineages. Epigenetic marks such as DNA methylation regulate the transcription of nearby genes. During development, different cell types establish different patterns of DNA methylation to ensure expression of the correct sets of genes needed for their specialized functions. There is still much that is not known about how epigenetic modifications are initiated, how they act to influence gene expressions and how their patterns change in disease. A deeper knowledge of the epigenetic code is needed if we are to fully understand development, tissue homeostasis, and cancer. We are developing methods to analyze methylation patterns in complex tissues. We are also actively investigating how patterns of DNA methylation are established in different tissues.
Our ability to detect and quantify proteins has lagged behind our ability to analyze nucleic acids. Closing this gap by developing more sensitive and quantitative protein analysis methods would greatly aid efforts to understand cellular processes and the search for protein biomarkers that reveal disease state. We are developing methods to unite the field of protein detection with single molecule counting, with the long-term goal of sequencing single peptide molecules. In collaboration with the Elbert lab, we have characterized two low background surfaces that are highly resistant to protein adsorption. Using these surfaces, we have demonstrated accurate and sensitive quantification of proteins in serum by single molecule counting on a solid surface. In these experiments, we were able to detect 80% of immobilized molecules by binding fluorescently labeled antibodies and single molecule counting.