Microarrays enable scientists to chip away at genetic mysteries

When the chips are down, University of Florida scientists increasingly turn to an analytical tool called a microarray to solve genetic riddles.

Microarrays, often called DNA chips, usually consist of a piece of glass or nylon on which hundreds of pieces of DNA strands, known as probes, are arranged in a regular pattern. Analysis of those strands provides a picture of gene expression that takes place in a cell during a given moment.

This is the future, said UF Genetics Institute Director Kenneth Berns, Ph.D. Say you want to know the difference between a normal cell and a cancer cell. Until recently, scientists would say, maybe it's this gene, and they would investigate. But life is more complicated than that. What you really need is a good picture of the overall set of genes that are turned on in a cancer cell or not turned on in a normal cell, or turned off in a cancer cell as opposed to being turned on in a normal cell. That�s what the microarray allows you to do.

Basically, every cell of the body contains a full set of chromosomes and identical genes. However, less than 50 percent of these genes are turned on, and that's what gives a cell its unique properties, whether it's a nerve cell, liver cell or cancer cell. Scientists are interested in the subset of genes that are expressed.

Defining that subset is where the microarray enters the picture. Often called gene chips, scientists can buy them from manufacturers the actual name GeneChip is trademarked by Affymetrix, a company that's made them available since about 1996 or they can make their own.

Holding one of the unassuming chips up for inspection they're about half the size of a computer floppy disc Henry V. Baker, Ph.D., points to a small patch in the center.

That's a 1-square-inch surface, Baker said. It holds a half million features that represent 22,000 genes. The human genome is estimated to have between 24,000 to 33,000 genes, so two chips hold the human genome. With an array, you can essentially screen the whole genome to see which genes are expressed in a different way in a diseased cell as opposed to a normal cell. You can use that information for diagnostic or prognostic purposes, or perhaps more importantly, to identify genes that might be targets for intervention.

Baker, associate chairman of the UF Genetics Institute and interim chairman of molecular genetics and microbiology, investigates the fundamental problems of gene regulation. He also trains graduate students for careers as research scientists and gives future physicians rigorous training in experimental science. He's known as the UF Genetics Institute's chip expert, which opens the door to collaborations with a wide range of scientists.

The beautiful thing about genomics and microarray data analysis is once you acquire the chip image, then the principles of analysis in well-designed experiments are relatively similar, Baker said. I've really enjoyed the last few years working with these chips, because they've enabled me to work with a lot of people I normally wouldn't have. I've learned a lot as a result.

A microarray works because it exploits the ability of a given mRNA molecule to bind specifically to the DNA template from which it originated. By using an array containing many DNA probes, scientists can measure the amount of mRNA bound to each site on the array. The amount of mRNA bound to the spots on the microarray is measured with computers, generating a profile of gene expression in the cell.

What you're looking at when you look at the data from a microarray is a snapshot in time from whenever you pulled cells from culture or tissues from an animal, said Jo Velardo, Ph.D., an assistant professor of neuroscience at UF's McKnight Brain Institute, who is working with Baker on a research project. In doing the experiment, you immediately isolate the cell's messenger RNA, which tells you which proteins might be being made at that moment in time. Then, you use several chemical reactions to turn that RNA into a form that can be detected and loaded on the chip. The microarray chips have tiny spots on them in the case of the rat Affymetrix GeneChip, you have thousands of spots that represent the known rat genome. The RNA will bind with a differential affinity to each spot on the chip depending on how much of that gene is present. Then we put the chip into the scanner and the scanner reads the differences among the spots. By analyzing these differences, we are able to assess how the genes change their levels of expression in relationship to each other after we perturb a biological system. In terms of understanding injuries, the power of the technique lies in the fact that it enables us to monitor the activities of thousands of genes simultaneously in the complex injury environment. Ultimately this will give us detailed information that will allow us to do productive experiments and make rational choices as to what genes should be targeted for therapies.

Terence Flotte, M.D., the pediatrics chairman at the College of Medicine and former director of the Genetics Institute, said understanding gene expression is essential in his efforts to design gene therapies for patients with cystic fibrosis, an inherited disorder in which a defective gene causes the body to produce lung-clogging mucus.

In situations such as in cystic fibrosis a single gene can affect the functioning of many other genes, leading to a whole host of negative health effects. Microarrays allow us to characterize those effects at a molecular levels, Flotte said. In our recent studies, we looked at the differences between lung cells from a patient who had cystic fibrosis and normal cells. We saw how gene expression diverged even further when cells were exposed to bacteria. This mimics what goes on when our patients lungs become massively inflamed after exposure to a relatively small number of bacteria.

Genomics and analytical tools such as microarrays are changing the way science is done, not just in terms of technological advancements, but in philosophical approaches, said Mick Popp, Ph.D., who directs a microarray research core for the UF Shands Cancer Center and the Interdisciplinary Center for Biotechnology Research.

While the technology is extremely powerful, what's more powerful is the underlying mindset, Popp said. Traditionally, scientists were taught to generate very specific hypotheses and to test those hypotheses. They had to have presumptive knowledge of what they were looking for ahead of time. Then, they would test the hypothesis and get either a yes or no answer. Now, in order to use the technology to its potential, scientists have to change the paradigm in which they do science. Instead of a specific hypothesis, they have to have a very good question and a model system to test it. The data tell them what is important, rather than them deciding ahead of time.

Ironically, one of the reasons more scientists do not use microarrays is because the analysis generates an intimidating amount of data. Researchers say the learning curve is steep.

Most people understand the promise of the technology, but the uninitiated have no idea how to handle all the data, Baker said. Biologists who are used to working with a laboratory notebook using ink and paper you absolutely can't do that with these kinds of experiments. You need to go to database systems.

Analysis of the results is key to using the tool to its full advantage, Velardo said.

I went into the process with a lot of skepticism, Velardo said.

I'm coming out the other end blown away by the power of the technique.