Rapid characterization of the EHEC outbreak by “crowdsourcing”

Now we’ll be moving from papayas and fish to something a bit more sinister: EHEC O104:H4.  That is the name of the E. coli responsible for the recent German outbreak.  When a new outbreak begins sickening patients, researchers all around the world are mobilized to try and characterize the pathogen.  Since new strains often have similarity to well-understood strains, one of the critical first steps is to sequence parts the genome.  When SARS was first flaring up in Asia, I worked for a sizable biotech company focused on developing drugs for viral diseases.  Very early data suggested that the SARS virus may have a similar pathogenesis to related coronaviruses, particularly with regard to viral entry.  However, we couldn’t design drugs to combat SARS until we had the DNA sequence for that part of the genome.  Once that became available, I used our in-house analysis software to design the initial set of lead drugs and we were off and running.

                Sequencing the entire genome is extremely time consuming, but BGI (formally known as the Beijing Genomics Institute) is utilizing ‘crowdsourcing’ to help assemble the EHEC genome faster (here’s the press release).  Using open source software, Twitter feeds (@BGI_Events), and several sites for uploading data, they hope to pull together data from researchers around the world in an organized, efficient manner.   Here’s the bioproject link for this work at NCBI (link).  This exchange of data is great for biopunks because one can analyze the data almost in real time and there is a significant potential for finding interesting and important aspects of the EHEC strain, based on sequence similarities/differences with other strains.  Mike the Mad Biologist had a blog post a couple days ago that offers a glimpse of the type of analysis people are doing (link).  The more eyes there are on the data, the quicker the strain can be characterized and as I have mentioned before, the potential of using ‘citizen scientists’ or ‘crowdsourcing’ for efforts of this type are enormous.  With the advent of rapidly accessible data, and the power of on-line DNA analysis tools, the gap between the scientist and everybody else has never been smaller.