Looking to bolster its microarray offerings beyond traditional gene expression, Agilent Technologies last week acquired Computational Biology, a developer of ChIP-on-chip technology, which uses chromatin immunoprecipitation to discover how regulatory proteins control gene activity.
"This acquisition is strategically important to the expansion of Agilent's microarray platform into new array-based genomics applications," said Fran DiNuzzo, vice president and general manager of Agilent's Integrated Biology Solutions business, in a company statement. He estimated that applications for the technology in disease research, drug discovery, and drug development will become roughly 10 percent, or at least $100 million, of the microarray market by 2007.
Computational Biology's technology platform includes "not only the protocol to run these experiments but also the software to analyze the data," said Kevin Meldrum, general manager of the ChIP-on-chip business and a former director of business development in the firm's Life Sciences and Chemical Analysis unit. "That software really comprises applications-based tools that allow you to basically plot the binding behavior of various transcription factors to different regions of the genome and statistical algorithms associated with the confidence you can have in those binding events, and some visualization tools that allow you to look at that data across the genome."
He told BioArray News, "We thought this was pretty interesting because the intellectual property is very strong, [and] they've worked hard on development and improving the robustness of the protocols that are required to run the experiments."
Meldrum said that the patents held by Computational Biology were a key to the purchase -- in particular, US Patent 6,410,243, which was issued to the Whitehead Institute in June 2002.
"This is really the key patent for conducting these experiments in an array-based format. So, I should say, just as people have used Northerns to do gene expression on a gene-by-gene basis, people have done immunoprecipitated transcription-factor-binding experiments on particular genes, one-off," he said. "But now [researchers can] use the ChIP technology in a massively parallel way -- and that's really the key invention that [they have]."
He cited NimbleGen and Affymetrix as potential competitors to the ChIP-on-chip technology, due to their contracts with the National Human Genome Research Institute to make tiling arrays based on the ENCODE (Encyclopedia of Complete DNA Elements) project. In fact, Affymetrix has said that its new tiling arrays, among other applications, would allow researchers to study transcription-factor-binding sites in greater detail (see BAN 10/27/2004).
But, Meldrum also said, "We do feel that this intellectual property is a pretty strong leg to stand on, and we feel clearly enabled having access to that."
Privately held Computational Biology was co-founded in 2003 by Richard Young and David Gifford of the Massachusetts Institute of Technology, and biotech executive Heidi Wyle. Young, who is a professor at the Whitehead Institute for Biomedical Research and primary inventor of the ChIP-on-chip technique, and Gifford will remain in their academic positions while consulting for Agilent on further development of ChIP-on-chip for commercial applications.
"Rick and Dave are really smart guys and are well connected in the academic world," Meldrum said, "and we are hoping that we'll be able to continue working with them on new technology development."
He noted that the two researchers had been collaborating with others in the field and the technology is already being used by some researchers. For example, Young had published a paper on mapping the "regulome" -- the promoter region activity associated with the yeast genome. As a result, there are now "a number of people working in the yeast field as a model organism, and they're very interested in getting access to yeast arrays so they can do their own experiments looking at transcription-factor-binding activity in the genome," Meldrum said.
Although the technology has been used almost exclusively in certain academic settings, Agilent intends to commercialize it more broadly in both the academic and industry markets. "We'll start with yeast, based on what [they] had, but we're developing arrays for human, rat, mouse, drosophila, and C. elegans -- all the classic organisms people study," Meldrum said.
Agilent sees a relatively easy integration process for the technology. Meldrum said that the ChIP-on-chip technology "plugs right into" the firm's ink jet platform for printing arrays. "What's unique about ChIP-chip is the probe design up front," said Meldrum.
"So, as we look at any particular model organism -- let's say human for instance -- we have the design and appropriate set of probes across the genome, and then those go into our database." From there, Agilent will be able to make either whole-genome scanning sets of chips or particular custom chips, where researchers will pick from that database.
Agilent hopes to roll out the first standard ChIP-on-chip arrays within the next three to six months. The firm already had been making custom chips for Computational Biology and will now make such chips more broadly available, but the acquisition is particularly expected to help drive its catalog business.
The firm currently is working on transferring the protocols out of Young's lab, examining them, and making sure they are "sufficiently robust and reproducible in the general customers' hands," he said. "For this technology, there are some unique things you need to do up-front in the sample prep to make sure that you properly immunoprecipitate your sample, and there are some modifications that are required to the hybridization conditions," Meldrum said. "Obviously, on the back end, once the data is read by a scanner, the application software is something unique as well. That's basically where we are going to be focusing our efforts over the next few months."
Meldrum expects there will be a lot of interest from the basic research community in using the technology for pathway-oriented types of experiments, understanding basic mechanisms associated with differential gene expression in healthy versus diseased tissue, and research into the toxicology set of pathways.
"In addition, we see some really big possibilities for mechanism-of-action studies associated with various drugs," Meldrum said. "In particular, lots of people are working on transcription-factor-based targets right now, and for an inhibitor or something like that, you could use this technology to find out how effective your inhibitor is in preventing a transcription-factor-binding event against a promoter region of a gene."
Agilent also said that within six months it would open a collaborative research center in Cambridge, Mass., where Computational Biology is located. The location of the research center, which will include an Agilent demonstration center for genomics, proteomics, and informatics, will enable close collaboration with Computational Biology's founders as well as researchers from MIT and the Whitehead Institute.
Meldrum said that Agilent intends to start hiring staff immediately upon identifying an appropriate site for the new center. He said that the center would start off with roughly 12 to 15 employees, and that the staff from its Beverly, Mass.-based demonstration center would move to the new facility.
Although Agilent has taken great strides over the past year to broaden its pipeline of products and offer customers integrated packages for genomics research, it has maintained that microarrays remain a key part of its growth strategy (see BAN 12/22/2004). Speaking recently at its annual analyst meeting in New York, Chris van Ingen, the head of Agilent's LSCA unit, said, "The microarray market for gene-expression profiling and genotyping is still fluctuating in growth, but the new applications will fuel growth in gene expression higher than 8 to 12 percent" -- and it appears that the ChIP-on-chip technology is a key part of that growth for Agilent.
The purchase of Computational Biology follows the November launch of the firm's fully automated lab-on-a-chip system, an advanced version of the firm's earlier-generation 2100 bioanalyzer, and the purchase of bioinformatics firm Silicon Genetics in August.