Bench Press

Here at Bench Press we’re fans of PLoS because they strive to expand access to the world’s scientific and medical literature with their open access stance as well as other experimental endeavors such as PLoS Currents: Influenza. That’s why when I checked in on PLoS Biology I was intrigued by a new collection titled Genomics of Emerging Infectious Diseases.

The collection is a series of essays, perspectives, and reviews discussing the potential genomics research holds in understanding emerging infectious diseases. While I haven’t had a chance to read through very much of the collection yet, one perspective written by Rajesh Gupta, Mark H. Michalski, and Frank R. Rijsberman suggests an interesting plan for infectious disease research. They suggest beginning an Infectious Disease Genomics Project (IDGP), much like the Human Genome Project.

The IDGP would be:

a coordinated, large-scale, international effort focused on the genomes of pathogens, vectors, hosts, and reservoirs and linked to end-point surveillance and response systems. Such a project could coordinate activities in four specific areas: generating data, linking data, analyzing data, and applying data.

The figure above illustrates some of the specific things the authors envision the IDGP being able to coordinate. Ideally the IDGP provides:

• A “roadmap” for researchers to follow in sequencing and monitoring emerging pathogens that allow researchers worldwide to aid in global efforts while continuing critical research on local diseases.
• Advanced data management in an easy to use, open-source, real-time interface. With an emphasis on linking as much data with relevant details (e.g. literature references).
• A centralized analytical toolbox with dynamic databases allowing for collaboration worldwide in addition to improved access for researchers in resource-limited settings.
• Ability to incorporate emerging technologies and provide access (e.g. new assay methods, next generation sequencers).

Personally I find the IDGP very intriguing simply from the standpoint of developing a framework for worldwide scientific collaboration. If this were successful it could provide a model for future projects. On a practical level, providing a network of this sort for scientists to rely on could at least increase the speed at which emerging diseases are detected. Increasing the speed of detection is always a good thing when dealing with novel pathogens with pandemic potential. It’ll be interesting to see what the scientific community thinks about beginning an IDGP.

Readers any thoughts?

(Source – PLoS Biology: Can an Infectious Disease Genomics Project Predict and Prevent the Next Pandemic?)

Berkeley researchers are on the heels of settling debates over taxonomy using innovative computing methods.

Apparently, whoever came up with the saying “nothing good ever comes from cheating” didn’t go to Berkeley. Recently, a team of researchers at the University of California, Berkeley took a little bit of inspiration from plagiarism-detecting software and created a program which can compare the entire genomes of two distinct organisms. Using what are known as feature frequency profiles (FFP), professor of chemistry Sung-Hou Kim and his team were able to successfully compare the genomes of several different organisms, and in a sense, “map” the organisms’ evolutionary family tree.

Traditionally, methods of determining how closely related two species are focus on a very specific subset of genes that the organisms have in common. The differences and similarities in the genetic code are then counted up and a computer program constructs the family tree. The more differences in the genes, the more distantly related the organisms are. However, the drawback of this technique is that it relies on organisms having these specific genes in common. What may end up happening is that an organism may not have a “homologous” gene to compare it with. Additionally, two genes that are used for comparison oftentimes conflict with each other; one gene says two organisms should be closely related while another one says they shouldn’t. With this innovative new approach of using FFP’s, the entire genome is sequenced and compared, as opposed to several different genes, allowing scientists to view differences in a larger scope.

Maybe even more surprising, this idea of using FFP’s as a means of comparison transcends the realm of genetics. When applied to literary works, this algorithm was able to better detect similarities between texts by the same author, of the same genre, and of the same historical era, than other conventional methods.

I was just stunned when I saw this,” Kim said. One of the reasons this method works better, he said, may be that, while word frequency analysis treats each word independently, feature frequency analysis picks up syntax.

Armed with this technique, these researchers have successfully segregated the proteomes of bacteria, Archaea, and eukaryotes with genomes of varying complexity into distinct groups and domains. Whenever disagreement occurred between their findings and common scientific belief, there was generally some kind of ongoing debate over that particular organism’s taxonomy. Professor Kim and the rest of his colleagues hope that they can use this algorithm to classify some enigmatic viral genomes and possibly utilize it in other fronts, such as literature and electronic encoding.

To me, this breakthrough in comparative genomics is a chance to reflect on how marvelous and miraculous life and evolution are. To think that the entire human civilization arose from single celled organisms, and that the building blocks and impulses which act upon bacteria and micro-organisms to keep them alive are the very same mechanisms that we live on.