Synthetic Biology: Scientists Engineer Memory In Yeast Cells
Scientists synthesize memory in yeast cells
Harvard Medical School researchers have successfully synthesized a DNA-based memory loop in yeast cells, an experiment that marks a significant step forward in the emerging field of synthetic biology.
After constructing genes from random bits of DNA, researchers in the lab of Pamela Silver, a faculty member in Harvard Medical School's Department of Systems Biology, not only reconstructed the dynamics of memory, but also created a mathematical model that predicted how such a memory "device" might work.
"Synthetic biology is an incredibly exciting field, with more possibilities than many of us can imagine," says Silver, lead author of the paper to be published in the Sept. 15 issue of the journal Genes and Development. "While this proof-of-concept experiment is simply one step forward, we've established a foundational technology that just might set the standard of what we should expect in subsequent work."
Like many emerging fields, there's still a bit of uncertainty over what, exactly, synthetic biology is. Ask any three scientists for a definition, and you'll probably get four answers.
Some see it as a means to boost the production of biotech products, such as proteins for pharmaceutical uses or other kinds of molecules for, say, environmental cleanup. Others see it as a means to creating computer platforms that may bypass many of the onerous stages of clinical trials. In such a scenario, a scientist would type the chemical structure of a drug candidate into a computer, and a program containing models of cellular metabolism could generate information on how people would react to that compound.
Either way, at its core, synthetic biology boils down to gleaning insights into how biological systems work by reconstructing them. If you can build it, it forces you to understand it.
The news articles on artificial life and synthetic biology are popping out of the ground like mushrooms.
This is a booming field, which holds enormous potentials.
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