The DNA sequence information in the human genome is read and interpreted by proteins. Without interactions between proteins and DNA, life would not exist. My laboratory studies how proteins are directed to specific parts of the genome, so that they can do their specific jobs. Using a tool called the DNA microarray, we can determine the location of thousands of protein-DNA interactions in a single experiment. Then, we use this data to reconstruct the rules that the protein used to find out where it was supposed to go. Our studies may lead to better predictions of where defective proteins that cause cancer bind to the genome.

The Lieb laboratory was established in the summer of 2002 at the University of North Carolina in Chapel Hill. We aim to understand a very basic unsolved problem in biology: How do proteins that interact with DNA find their proper targets in living cells? We study this problem in yeast, a single-celled fungus, and C. elegans, a very simple roundworm that lives in the soil. C. elegans is not the kind of worm you may have in mind: it is transparent, about the size of a piece of lint, and is barely visible with the naked eye.

Researchers often use simpler organisms, like yeast, to figure out the details of processes that are fundamental to all living things. Then these discoveries are tested in more complicated systems, where the knowledge can be used as the basis for creating drugs or other therapies to cure disease. The advantage is that yeast cells grow very quickly and are easy to manipulate in the lab, allowing discoveries to be made much more rapidly than they would be if human cells were studied first.

We use yeast and worms to study how DNA-binding proteins called transcription factors find their proper targets in living cells. Transcription factors control which genes get turned on and off, when those genes get turned on and off, and in what tissues they get turned on and off. Using a new research tool called the DNA microarray (see below), we are able to map all of the sites of interaction between any given transcription factor and the entire yeast genome (a "genome" is simply all of the DNA that makes up the chromosomes that are in a cell). We have begun to uncover some of the rules that proteins use to find their targets in yeast. For example, we were able to provide conclusive genome-wide evidence that DNA sequence information alone is not sufficient to direct a binding event. Even though many regions of the genome may contain a DNA sequence a transcription factor likes to bind, only sequences that are in particular parts of the genome are actually bound. We would also like to test whether the rules that proteins use in yeast also are used in a much more complicated system, C. elegans (these are the worms). Worms are simple compared to humans, but are much more complicated than a yeast cell. For example, worms have muscle, a nervous system, and a gut, all things yeast don't have. Therefore, worms are an important stepping stone in determining whether the way transcription factors behave in yeast is similar to the way they behave in humans.

In humans, cancers occur when mutations in DNA lead to improper regulation of genes that control cell growth. It is likely that in all cancers, alterations in the abundance or binding specificity of at least one transcription factor contributes directly to uncontrolled cell proliferation. As one example, Burkitt's lymphoma is caused when a transcription factor called c-myc is turned on in improperly in immune cells, which in turn leads to inappropriate gene regulation and cancer. Another example is a protein called CTCF, which is involved in the occurrence of breast, prostate, and kidney tumors. When CTCF is mutated, the DNA binding spectrum of CTCF changes such that it no longer bind to its proper targets involved in regulating cell proliferation, but instead binds other targets. In both examples, which serve as general illustrations for numerous other cancers, alterations in the natural range of a transcription factor's gene targets are likely major factors in the development of cancer. We anticipate that our studies of DNA-binding specificity will lead to better predictions of the targets of human transcription factors that have the potential to cause cancer, which may ultimately lead to new therapies based on inhibiting binding to inappropriate targets. Our work may also lay the groundwork for experiments in mammalian systems to examine how any cancerous state affects the distribution of DNA-binding proteins, and how that altered distribution contributes to progression towards malignancy.

Traditionally, biologists have studied one gene at a time, often focusing on a single gene for their entire career. DNA microarrays allow a single investigator to study all of the genes in an organism in parallel, in a single experiment. Microarrays have therefore greatly accelerated the pace of biological discovery. Even more important than the increase in throughput is our ability to for the first time obtain a complete picture of how genes act to together, in groups, to specify biological function. This was impossible before; the analogy would be trying to understand how a battle was won by studying the behavior and fate of an individual soldier. Now, we can zoom out and see the movement and behavior of entire regiments, while retaining the resolution to focus in on particular soldiers of interest, who may have performed critical functions.

DNA microarrays are simply arrays of thousands of discrete DNA sequences, for example PCR products or oligonucleotides, representing all 6,200 genes in Saccharomyces cerevisiae (baker's yeast), printed at high density onto a glass slide. A typical DNA microarray fabricated in our laboratory contains about 20,000 spots of DNA, which represent all of the genes and regulatory DNA in Saccharomyces cerevisiae. The spots are about 100 microns in diameter and are spaced at a center-to-center distance of 175 microns. A home-made robotic machine produces the DNA microarrays we use. It is housed in Fordham hall, and was produced from off-the-shelf electronics, motors, and motion-control software that are used in the semiconductor industry.

Because of the property of DNA that allows complementary DNA fragments to hybridize to each other, we can use these arrays to measure the relative levels of specific nucleic acids in biological samples. For example, we can separately grow yeast under two different conditions (for example cold and hot), and then extract mRNA from both yeast cultures. The RNA from each of the cultures can be labeled with a different fluorescent dye (for example red and green). The labeled RNAs are then mixed together and hybridized to the array. By the ratio of fluorescent signal coming from each spot, we can monitor the relative levels of every mRNA expressed by an organism under any given condition. The same can be applied to human cells, for example comparing gene expression from cancerous and non-cancerous tissue. There are many other uses for microarrays. My primary use of them is for mapping the position of protein-DNA interactions in the genome.