Scientists Create Synthetic Life

Last Updated on Saturday, 17 July 2010 14:57 Written by Mehmet Ali ANIL Friday, 21 May 2010 00:02

I just had to write about this.

Today, a large group in J. Craig Venter Institute, US, seems to engineer their own DNA (or RNA, NA in which there is encoded information, eventually), synthesize it in laboratory, inject it into a bacteria cell. The encoded DNA is structured  so that the bacteria was able to reproduce itself, and the resultant bacterium do also have the reproductive ability, which are two of the key requirements to be a living organism.

Well, this might be one of the days that will go into the textbooks. Ever since I read "The Selfish Gene" by Richard Dawkins, I found the section about "The Replicators" totally mind boggling. The fact that it was self repetition or self organization that is key player of the whole process, a simple algorithm that probably was once in favor of minimizing the energy, or one of millions of such root algorithms, that turned out to result in such large dynamics, as we right now are looking through.

The idea that those key algorithms are being unfolded, piece by piece, that humans are deciphering the motivation, the great kinesis we are right now observing in awe, is enough to give chills. I feel that we're starting to understand organisms in a bottom to up approach, just like mastering the replicator in order to figure genes out, despite of the fact that this was not the approach in biology, and it is not perfectly still.

Right now, that seems to me, genetics is in a point that it will go into a change that should be emphasized, like the turning point that Electronics was once at on 60's, the time the saturation in the need and the theoretical background, resulted in a burst in engineering, an uncontrollable momentum, replication, integration and scaling, such that still even a minuscule amount of enhancement is considered to be an instant realization, even there is a high price to be paid. It didn't stop there, because electronics had this unique property of paving its own way, in other words, it created its own market and design tools by its research and development. Molecular biology seems to be climbing to this peak, once approached its problems with a chemists or a biologist's intuition, and now also with the help of statistical physics and computational advances, is armed with numerical methods and simulations. This saturation of know-how until recetly was encapsulated into the laboratory and reached the public comparably indirectly and under a watchful eye, with generally ethical concerns. But seeing that this breakthrough was achieved by a private institute, if the time of genetic engineering comes with opportunities of easy implementation and integration, the dam is going to fall down. My guess is that we'll see days that the inevitable momentum of engineerable organisms flooding every place the market is in need of, will be overwhelming to every single limiting factor known effective today, religion, ethics, human rights or environmental concerns.

This might seem to be an over-dramatic entry, like those PopSci news, that every small development is presented as great scientific breakthrough, those that make one wonder how come every single day there happens to be one, In fact one should know that I am not presenting this as a huge advance, but It is, in my opinion, a signal for the point that is reached in genetic manipulation, that it is not genetic imitation anymore, it is evolving into a process of encoding, and design, which surely will build its layers of production. There will be ones that will code, ones that will generate blocks of single tasks, ones that will try multitasking, ones that will try to create self-developing and adaptive structures and so on. One should remember that the golden age of Electronics was not the time that the bipolar juction transistor was realized in the lab, it was in contrast, the time that CMOS was perfectly implemented, because it gave the opportunity to divide the workload, segmentize it in a way that one could focus on different parts, the platform that gave the chance for one group to code, one group to write algorithms that the ones that code will use without getting into details of, one group that design the architecture, and others that get into the semiconductor physics. This segmentation did not only gave a chance to divide the labor, but also, speeded up the scaling process, because requirements of every single subunit was evident, which resulted in an environment that the asignee of the problem, remained focused into his expertise.

If molecular biology present similiar circumstances, it will enjoy the benefits of plug'n play, whereas I am still not sure whether we (well, even if we don't want we'll be users of it, it does not seem to be preferential) will enjoy, or will suffer the big step sideways from Darwinian track, exchanging a huge heuristic algorithm with no memory but big sample size, with a combination of scientific methodology and engineering voraciousness.

No matter what, here's something that I will mention years after, when the day will come.

For the ScienceExpress article: http://www.sciencemag.org/cgi/rapidpdf/science.1190719v1.pdf
For the BBC News Report: http://news.bbc.co.uk/2/hi/science/nature/8695862.stm