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Shawn Levy, Director, Vanderbilt Shared Microarray Resource


Received his PhD in biochemistry from Emory University in 2000. Worked on mouse models studying mitochondrial genetics for human metabolic diseases and developed a 700-gene mitochondrial mouse microarray.

Set up micorarray facility in 1998 at Emory Center for Molecular Medicine, then set up the Vanderbilt facility in 2000.

Also serves as research assistant professor in the Vanderbilt department of molecular physiology and biophysics.

Outside of the microarray lab, his main recreational interest is hockey, which he played growing up in New England and still plays.

QHow is the Vanderbilt Shared Microarray Resource set up within the university?

AIt is a core facility accessible to anyone at the university. We sell microarrays at cost. The majority of the salaries are covered by center grants or program project grants. This enables us to keep the microarray costs low and be able to provide a high level of support for the data they generate.

QHow much of the microarray experiment do you handle?

AWe ask that the researchers provide us with purified RNA and we go from there. We do a small amount of RNA amplification, but the vast majority of our projects start with RNA ready to be labeled. The researchers get their raw data file back as well as the first-pass normalized data file.

QWhat types of data analysis programs do you use?

AWe use GeneSpring, and have found that product to be very nice. We also have a suite of BioDiscovery products. However, we are very wary of plugging numbers into a piece of software, then [having it] spit back numbers that are different [for the same sample] and not knowing why. But GeneSpring is very forthright about their algorithms. We also work with biostatisticians who are developing new algorithms.

QWhat sort of arraying and scanning equipment do you use?

AWe use a Hitachi Genetic Systems SP Bio Robot. We have been working pretty closely with Hitachi for the past six or seven months on optimizing the scanner for humidity and temperature control. We also have a device for plate handling and accessories that allows us to have a zero loss to humidity. The robot uses a solid type of pin for printing. Every slide it prints, it dips into the source plate. The print speed is a little slower than the quillpin printers, but we have found that print quality is high and reproducibility is higher than with quill pins. The spot-to-spot variation is down by a factor of five or six. The machine’s integrated plate stacker can load in ten 384-well plates and allow you to walk away. It runs five days a week. You are able to print about 300 arrays a week at a density of 5,000 to 10,000 spots.

QWhat kinds of arrays do you print?

AWe print mouse and human high-density arrays using Research Genetics clone sets as well as an NIA (National Institute on Aging) clone set for mouse. We also do yeast full-genome arrays and oligo-based arrays for Helicobacter pylori.

QWhat’s the biggest bottleneck in the arraying process?

AIn our process it’s verifying gene content. We use a ton of cDNA arrays, and there’s always the concern that what you are spotting down is not what you think it is.

QHave you developed any special arraying protocols or tricks to deal with these bottlenecks?

AYes, we have optimized print buffers to eliminate evaporative loss. We’ve found that the printing buffer can make a huge difference. With a print buffer that performs very well, the next step in the process, slide chemistry, became less important. We could use an inexpensive and easy-to-come-by chemical, polylysine.

QIf prefabricated arrays were to come down in price, would you use them?

AWe would switch to a prefabricated array with an open-source platform where there is really no question as to what the sequences are. For example, Affymetrix has not released the specific sequences that make up the oligos. With the Incyte arrays, you have to have access to an additional private database to have access to the sequences. These [restrictions] limit the usefulness of the arrays and limit the creativity of a researcher and how they analyze the data.

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