Global presentation

The software, GenoTHREAT takes a DNA sequence on input, and in return told the user if it's a dangerous sequence which need further investigation or if the sequence can be synthetised. It follows the algorithm given by the federal guidelines, and so uses the Blast software for sequence alignement. For managing the sequence (six-frame translation, reversed frame, extracting sub-sequence), we use Biojava, a bio-informatics toolbox (1). GenoTHREAT has been coded in Java, and is working on both Windows and Linux distribution. We have developped different versions in order to optimize the time execution or the cpus' utilisation according to the use (#Different implementations).

General algorithm

Following the federal guideline, the first step is to do the six frame translation (See More) in order to have the corresponding amino-acid strands. We also keep the initial nucleotid strand and its reversed DNA sequence (/Why?). So we have now 8 sequences to screen (6 amino-acid, 2 nucleotides). Then, we divide each sequence in 200bps nucleotide or 66 amino-acid subsequences.
Each sub-sequence is then blasted, and we extract the relevant information from the blast output. For each sub-sequence, we have to decide if it's a hit or not (See More).

If one sub-sequence is a hit for our algorithm, then it means that a 200bps sequence potentially dangerous has been detected. The sequence will be so flagged, and a result file containing all the select agent found and some more information will be created.

Different options

Around this algorithm, we have developed different options to use the sequence screening. We can use it to just screen one sequence, or a group of sequence from our test database, or screen sequence from the iGEM registry or GenoCAD database. The parameter on some versions can also be changed in creating a new set of parameters.

Different implementations

Our main issue in implementing the software is the ressources-consuming(time and computational ressources) of blast. In order to get rid of it, we have tried different implementation of our algorithm.

1. OnlineBlast

   In this version we use the ncbi remote blast (1). Our software send the subsequences to be blasted to the website, wait for the result and extract it.

   * Advantages: not computational intensive (just need a connection), fast for one blast alone (20s for 200 bps).

   * Drawbacks: can't be fasten (e.g. by parallelisation) due to ncbi's restrictions (not more than three request by second and result file need to be access before send a new one), server error happening sometimes, and the lack of privacy by sending informations via the Internet.

   The last drawback (privacy issue) is a big concern for us, as the gene synthesis companies won't want to send customer data on the Internet. That's mainly why we had to create other implementations.

1. LocalBlast

   The ncbi website offers a local version of blast (download page). The databases (nt and nr especially) have to be download too. The software call this program via the bash.

   * Advantages: privacy, don't risk server error.

   * Drawbacks: requiers a lot of memory (nt and nr databases are 30Gb together), very slow (2.5min for 200 bps).

   To fasten the software with this version, we created in version in which the call to blast is done parallely.

1. LocalBlast Parallel

   using the java thread system, we make the call to blast in parallel for the subsequence. The number of blast called at the same time can be modified according to the computer power in which the software is launched. We use wages of 100 blast most of the time (compromise between time and ressources use).

   * Advantages: same as LocalBlast + speed (6 min for 80 blast of 200 bps)

   * Drawbacks: need memory, very computational intensive (100 blast at a time implies 100% of CPUs taken).

   In order to make it even better, we have then make a similar version of the LocalBlast Parallel in other system.

1. Sirion

   Sirion is a private server of Virginia Bioinformatic Institut.

   * Advantages: very fast

   * Drawbacks: expensive