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In Their Own Words: Researchers Gaze in the Future of Microarrays


Every week, BioArray News interviews leading researchers to learn what they are doing with microarrays and to get their opinions on the future. Following are edited highlights from the 50 Lab Report conversations of 2002:

Prognosticating the future of microarrays.

Martin Bilban, research assistant, University of Vienna:

(Aug. 30, 2002) — I hope that [the microarray] will find its way as a standard diagnostics tool for many kinds of disease analysis and diagnosis. I think that if you have a small subset of genes that you know is involved in…disease progression, then you can for example spot many replicates of that gene, so you have high statistical power of your microarray data.

[With regard to technical issues], I would like to see improvements in terms of being able to design probes … that are equally efficient in terms of hybridization efficiency. Because many times, for example if you have oligo arrays, if you have a low signal, it doesn’t necessarily mean that you have no mRNA in your sample, that the gene is not expressed: it might actually come from low hybridization efficiency. So, if you can develop software or strategies to efficiently and quickly design oligos to genes, that would be a great improvement. The other one would be to be able to design probes for splice variants efficiently - obviously you can’t do that with cDNA microarrays - but to be able to do that with short oligos.


What’s next?

Daniel Gerschwind, assistant professor of neurology, UCLA School of Medicine:

(Aug. 2, 2002) — Probably the advance that’s closest around the corner is using arrays in the clinic for tumor prognosis and treatment protocols. But beyond that, in neurology, it certainly might help you understand who is going to be a responder and non-responder to a particular treatment. It may help you decide who is going have side effects to a particular medicine or not.

Some medications have been taken off the market that are very good anti-seizure drugs. If we could just identify those people who we shouldn’t give [a drug] to, and those it would save, that would be quite helpful, because the medicines are quite effective.


Joel Credle, former Director of UC Berkeley DNA Analysis Center:

(April 19, 2002) — I really see microarray labs being like the large automated sequencing machines. Sequencing is never going to be a dead science, but there is not really a need for these really large sequencing centers. Similarly, microarrays are going to be a more individual science where individual labs have microarray capabilities all up and down the halls of a science lab, once the prices come down. Instead of looking at the entire genome of the mouse or rat or human, people will have a personal microarray machine and look at a subset of genes. That’s cost-effective.


Opportunities for improvement

Gary Churchill, staff scientist, Jackson Laboratories, Bar Harbor, Ma.:

(Jan. 4, 2002) — Dyes are a good place to start. New dyes would be okay, but a deep understanding of the physics of the dyes would be more helpful, as sometimes the dyes interact with the specific clones. We see spots that are always green no matter what. Dye flipping is sort of a stopgap to help us patch up this technical issue with microarrays. The two dyes Cy3 and Cy5 behave differently. Dye flipping corrects for the dye bias. I can think of several experiments where an investigator is looking at samples over time. We do multiple dye flips at each time point, and we make sure we get several different time points


Buy or print?

Ralph Dean, Plant Pathology, Director, Fungal Genomics Laboratory, North Carolina State University:

(Oct. 18, 2002) — Right now, my goal is not in technology development; it’s to use technology to answer important questions. If I feel that the technology has reached a point where I’m better served by buying it than making it myself, then I need to look at the option. We are very close to that with microarrays.

I still think there is going to be a shakeout coming. In this, it’s like computers and big screen TVs, once it reaches a certain price, everyone will start buying them. Once computers got below $1000, everybody went out and bought them. It’s the same thing for microarrays. When the prices come down, we’ll see a lot more use of the microarrays and a lot more companies producing them.


Do you think this technology will converge on one platform?

Mark Schena, visiting scholar, TeleChem/Arrayit, Sunnyvale, Calif.:

(Nov. 8, 2002) — I think that what we are seeing right now is kind of interesting. We are trying to find a two-part emphasis in terms of the technology platform. There are proprietary or closed platforms from people like Affymetrix and a proliferation of open platforms, nominally, in the microscope slide format. Companies and researchers are publishing and inventing in each of those two categories. We have seen very little consolidation and dramatic expansion in terms of different technologies, surfaces, assays - DNA, proteins, antibodies, carbohydrates, small molecules. We have also seen a rapid proliferation of instruments to read the devices. In five to 10 years, I’m not sure I have an idea of what that landscape would look like. It could become increasingly complex, or a really large player like a Microsoft, an Oracle, or an Agilent would purchase the technologies and develop a universal use platform. An exponential expansion in terms of tools is likely to continue for a number of years.


Please prognosticate on the future of protein chips and off-the-shelf products.

Michael Snyder, Yale professor and chair of molecular, cellular and developmental biology:

(May 31, 2002) — Ultimately there will be protein chips for every single organism. I think the first step will be sets of classes of proteins, then there will be uni-proteomes, where you have one representative of every single gene.

The criticism that everybody used to raise, and they still do, [is that] there are probably millions of proteins in humans when you consider alternative splicing. I would say just having representatives is not going to have all the information but will be very valuable for lots of things. Another thing that would be very valuable is the uni-domain set. And the combination of the two would be a great first start for biology.

Ultimately you’ll buy these things from companies. I think the protein chip field will move faster [than the DNA chip field] because I think the market place is more aggressive, and we obviously would like to see Protometrix be a big player in this area.


On Microarray Data

Jörg Hoheisel, Head of DKFZ Functional Genome Analysis Division:

(March 29, 2002) — I don’t think there is a data analysis issue. Part of what has been the problem is people seeking the single analytical answer to all queries related to microarrays and not giving enough thought to the nature of the question. Different questions might require completely different analytical methods. It’s important to choose the right analytical approach for the right applications. This is not a matter of a contest between supervised and unsupervised learning methods. They have very different roles.


What advice would you give to a colleague who is just starting to use microarrays?

Desmond Smith, researcher, department of molecular and medical pharmacology, UCLA:

(May 3, 2002) — If you can find a friendly person who has a lot of experience in mathematical analysis of the data, it would be a tremendous help. Unfortunately, now these individuals are like gold dust.

. . . The main breakthrough for us [in microarray experimentation] was teaming up with a set of mathematically sophisticated engineers at USC. We were really quite naïve about how noisy and how variable the data is.


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