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Title : Digital Movies In Bacterial DNA
link : Digital Movies In Bacterial DNA

Digital Movies In Bacterial DNA

By Credit: Rocky Mountain Laboratories, NIAID, NIH - NIAID: These high-resolution (300 dpi) images may be downloaded directly from this site. All the images, except specified ones from the World Health Organization (WHO), are in the public domain. For the public domain images, there is no copyright, no permission required, and no charge for their use., Public Domain, http://ift.tt/1WGO3dW

Here is a fascinating piece of basic science, in which the gene editing CRISPR system is used to add digital black and white images and a short digital movie into the genome of a bacteria. There are implications here of using live organisms for information storage (bacteria instead of a USB drive?) and the possibilities of using the same principles for gene therapy purposes (e.g., adjusting disease-causing genes). Abstract:

DNA is an excellent medium for archiving data. Recent efforts have illustrated the potential for information storage in DNA using synthesized oligonucleotides assembled in vitro. A relatively unexplored avenue of information storage in DNA is the ability to write information into the genome of a living cell by the addition of nucleotides over time. Using the Cas1-Cas2 integrase, the CRISPR-Cas microbial immune system stores the nucleotide content of invading viruses to confer adaptive immunity. When harnessed, this system has the potential to write arbitrary information into the genome. Here we use the CRISPR-Cas system to encode the pixel values of black and white images and a short movie into the genomes of a population of living bacteria. In doing so, we push the technical limits of this information storage system and optimize strategies to minimize those limitations. We also uncover underlying principles of the CRISPR-Cas adaptation system, including sequence determinants of spacer acquisition that are relevant for understanding both the basic biology of bacterial adaptation and its technological applications. This work demonstrates that this system can capture and stably store practical amounts of real data within the genomes of populations of living cells.

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