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GnuBio Licenses Microfluidics, Emulsion Methods for DNA Sequencing from Harvard


This article was originally published Aug. 25.

GnuBio has exclusively licensed microfluidics and emulsion methodologies from Harvard University for worldwide use in nucleic acid analysis, the company said last week.

The company, founded on technology developed by David Weitz, a professor of physics and applied physics at Harvard, aims to develop a scalable DNA sequencer that can analyze a human genome at 30-fold coverage for less than $100 in sequencing reagent costs, and small candidate gene regions at 100-fold coverage for less than $2 per sample. Weitz presented an outline of the technology, where the sequencing reactions take place in picoliter-sized droplets, earlier this year at the Consumer Genetics conference (IS 6/8/2010).

The license agreement, which was signed in early June but was not announced until now, comprises a suite of patents and patent applications for technologies developed in the Weitz lab, co-founder John Boyce told In Sequence.

GnuBio said in a statement that it wants to distinguish itself from other sequencing platforms by being able to adjust the amount of DNA sequence produced in a run to the requirements of the experiment.

“Current methodologies utilize a 2D matrix, such as a chip or bead, and therefore large sample numbers, and broad genomic regions, must be analyzed in order to amortize the cost of the run,” said Weitz. GnuBio claims that will not the case with its platform, where a run is expected to be able to analyze small or large numbers of samples at the same cost per sample.

The system will "enable clinicians and diagnostic labs to cost-effectively analyze smaller batches of samples across a genomic region at a cost per patient that is an order of magnitude lower than with current and emerging technology," according to the company.

In addition to DNA sequencing, GnuBio's system will be capable of running other types of assays, carrying out "both the reaction and detection at a throughput orders of magnitude faster and cheaper than with current methodologies," the firm said.

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