Monday, September 19, 2011

Software aids in unraveling genetic code

The Craig Venter Institute, named after the scientist that published the full genetic code of the human genome, developed software that makes sequencing DNA a lot easier. Their method is especially useful for bacteria that can not be cultured in the lab: in order to unravel the genetic code with conventional means, billions of cells have to be grown before enough DNA is available to properly assess the genetic sequence. This means that scientists gain access to the possibility of elucidating the genetic code of countless bacterial species, giving us insight in how certain characteristics are stored in DNA, such as resistance against antibiotics and other bacterial behavior. Additionally, we may harness the genetic code we find to create new capabilities for genetically modified micro-organisms.

According to the scientists at the Craig Venter Institute, only one complete genome from a single bacterial cell is needed to unravel the genetic code with the newly developed software. Tests with the well-known strains Escherichia coli and Staphylococcus aureus show that the software captures 91 percent of the genes that are present in these bacteria. That is only a bit less than the 95 percent that conventional biological methods yield. Not only was the newly developed software tested on previously sequenced strains, the scientists also deployed the algorithm on a never-before sequenced bacteria, carrying the name SAR324, belonging to the family of Deltaproteobacteria. The genetic analysis proved to be successful, and showed that this particular bacterium is capable of movement induced by certain chemicals, called chemotaxis, and relies on oxygen to survive.

The sequencing method works by copying the genetic code of one bacterial cell with a certain copy technique, called MDA. After enough copies are produced, they are analyzed by the sequencing software. Copying DNA with MDA is a crude method, causing some pieces of genetic code to be copied more often than others. Additionally, the number of copy errors is relatively high. Previously, analyzing software was unable to handle the differences in copy numbers and the high number of errors, but the algorithm that was developed at the Craig Venter Institute is capable of correctly deriving the genetic code out of the copy machine; almost just as effective as conventional methods.

It is hard to say what kind of interesting bits we will find in the genetic code of bacteria. It is known that bacterial species have a wide variety of characteristics and can mutate to develop new capabilities. Resistance against antibiotics is perhaps the most well-known, and with the high incidence of multiple-resistant bacteria strains nowadays, certainly the most important. Unraveling how these bacteria build resistance into their genome could give us new insights in how to undo it.

Scientists estimate that 99,9 percent of the known bacterial strains can not be cultured. That means an enormous dataset of genetic information is waiting for us to be analyzed.

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