New Microarray Equipment Advances Genetic Research in KC Area

DNA microarrays or DNA chips have given us a larger and more complex picture than we have ever had of both healthy and diseased cells. As of yet, scientists have barely tapped the technology's potential to detect and predict disease and to improve drug treatment. Only slightly larger than a computer keyboard key, each chip contains thousands of single-stranded DNA molecules that can interact with either the complementary DNA or RNA in a tissue sample to reveal genetic abnormalities.

Until recently, researchers at the Higuchi Biosciences Center and fellow Kansas City-area educational, research, and medical institutions could only stand aside and watch others benefit from the technology. That has all changed. As early as this summer, the computer equipment and scanners needed to process the information from these tiny microarrays will be up and running at the Higuchi Biosciences Center.

Microarrays make direct use of a very fundamental principle in genetics: Single strands of DNA or RNA can form a double helix with single-stranded DNA. Single strands of DNA covalently attached to the chip can bind in a complementary fashion to the DNA or RNA in a tissue sample, which can then allows the sample to be read for genetic abnormalities.

In the first step, a computer scanner reads the microarray chip. The scanner notes what gene each tiny position represents, storing that information on the computer's mem-ory. Next, scientists tag with fluorescent compounds those DNA strands in a tissue sample that they predict will hybridize to the strands on the microarray. The scanner's lens then magnifies sections of the sample to record the location of the fluorescent tags within it. This information is stored in the computer's memory. Finally, the sample is read against the microarray. The computer records each position on the microarray where a fluorescent compound is concentrated. The computer then combines the information and provides a reading of the genetic information the tissue sample has revealed.

"You can't get a reliable reading with just one tissue sample," said Elias Michaelis, director of the Higuchi Biosciences Center and the Center for Neurobiology and Immunology Research. "Let's say we took a piece of tissue from somebody with a neurological disease. It doesn't do any good to look just at diseased tissue; we also have to examine a healthy tissue sample from the same region of the brain, a control." From the diseased tissue sample, the RNA extracted will be labeled with a blue fluorescent probe, and the RNA extracted from the control will be yellow. The scanner will superimpose the two readings. Just as when you mix paint, when you superimpose yellow over blue fluorescence, you're going to come up with green. If the blue and yellow are equal in intensity in both the control and the diseased tissue sample then the resulting green color indicates that that particular strand of DNA is equally expressed in both samples. However, if the signal from the control is much higher or stronger you will get primarily yellow, and if the signal is higher from the diseased tissue you'll get blue. What a researcher is really looking for is all the non-green spots, anything that may be blue or yellow. Those are indicators that the disease is causing a particular gene to be either over-expressed or under-expressed.

The question each researcher will have to answer when they undertake a microarray project is what genetic differences are sufficiently large enough to pursue. Every little deviation from the perfect green could be significant but it might also be just a technical error resulting from improper preparation of the tissue, for example.The researcher will have to set a particular criterion to determine if under- or overexpressed genes signal a significant finding or not.

Though the computer equipment used to analyze the microarrays is expensive, it is the microarrays themselves that can quickly deplete a traditional research budget. Each microarray can cost anywhere from $800 to $1,400. If, for example, you wanted to study breast cancer occurences that you suspect involve a certain group of genes, you need to examine more than just one tissue sample to have confidence in the results. For the sake of comparison you would need several arrays for the healthy or control tissue and several for the diseased tissue.

"That can run up to about $10,000," Michaelis said. "And that is the supply budget for an average-to-small NIH or NSF grant and all you've done is bought the arrays. You haven't even studied them. After labeling the DNA you have to run the microarray, assemble the data and analyze it. You then have to determine statistically relevant changes vs. statistically insignificant changes. Once you've done all of that, if you're lucky, you have identified genes for investigation. But you can't just sit there and admire them, you have to do something with them. Chances are some of the genes are going to be brand new ones that no one has ever studied before. That's when the really hard work begins."

Microarray technology can be used by researchers from a number of fields-biotechnologists, veterinarians, and even botanist. A botanist could study plants in one stage of growth vs. another stage of growth and determine in these stages which genes have been turned on and which have been turned off. Interesting to the HBC in particular are the possibilities microarrays offer in the area of drug discovery. For example, if a drug with great therapeutic potential damages the liver, it has to be taken off the market immediately. However if researchers could use microarrays to identify 40 or 50 genes in the liver that are impacted adversely by the drug, there is potential for eliminating its damaging influence, and it could again become a useful drug.

While using microarrays as research tools, researchers are never certain what their results are going to be, but Michaelis said that's the beauty of them. Initially most people in the sciences recoiled at the notion of such "hit-and-miss" technology. Especially organizations like the NIH. "When we sent out early proposals to NIH, the review panels kept saying, 'This has no hypothesis, no data, what are you going to do with this information?' What they were really saying was, 'This is worse than a fishing expedition.'"

Michaelis says it has finally dawned on everyone, including the NIH, that traditional hypothesis-driven research is frequently biased research. People who have already made up their mind might miss something that hadn't even occurred to them.

"I might like a particular group of proteins and genes," he said, "so what are the chances that I would look at another gene that is totally unrelated? Not one in a million. In the past, I would have gone to NIH with this wonderful construct and argument and said, 'I think this gene and that gene will do thus and so. I have very clear data to substantiate my hypothesis.' This data might be true, but it also might be totally fallacious. I might be missing everything. With microarrays you're completely unbiased. You're just asking the tissue to reveal its secrets."

Michaelis said that all the researchers who use this technology actually do have one hypothesis: When a cell moves from one stage to another-whether from normal to treated or healthy to diseased-some genes are going to be turned on and some are going to be turned off.

"That's it. That's all we can assume," said Michaelis. The rest is search and find. This is where the entire world is heading now. Not only is NIH now supporting this kind of research, but they are also sponsoring proposals for study into specific conditions using this technology. Microarrays have split genetic research wide open."