Chemists at New York University have developed a device that allows for the translation of DNA sequences, thereby serving as a factory for assembling the building blocks of new materials. The invention, described in the latest issue of Science magazine, has the potential to develop new synthetic fibers, advance the encryption of information, and improve DNA-based computation.
The device, developed by NYU Chemistry graduate student Shiping Liao and Professor Nadrian C. Seeman, emulates the process by which RNA replicas of DNA sequences are translated to create protein sequences. However, the signals that control the nanomechanical tool are DNA rather than RNA. The dimensions of the machine are approximately 110 x 30 x 2 nm.
"The device is a machine to make specific DNA sequences by imitating the ribosome's translational capabilities," said Seeman, who developed the machine with Liao over the last year.
The machine may be set to four different structural settings and allows researchers to determine which elements of a DNA strand are to be used to construct a product sequence. Liao and Seeman employed a pair of PX-JX2 devices--an existing DNA machine developed a few years ago in Seeman's laboratory--in selecting the DNA molecules and used another DNA motif, known as DX molecules, as an adapter between the strands they carry and the device. The researchers tested the device experimentally by adding a complete set of DX molecules to a solution. The intended DX molecules, which included strands from the target product attached to the device, and the target strands were bonded together, thereby emulating the way RNA molecules code for proteins.
The researchers emphasized that their device does not transcribe the traditional genetic code, but rather, uses an arbitrary code that they made up. However, they noted, its encryption abilities have the potential to construct new types of polymers, which could be used in the production of new synthetic polymer materials. In addition, the machine operation may be used to advance DNA-based computational methods.
Source: Eurekalert & othersLast reviewed: By John M. Grohol, Psy.D. on 21 Feb 2009
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