Computational tools prove value in detecting rogue bacteria
Three LLNL scientists have shown that computational tools could become an important resource in detecting rogue genetically engineered bacteria in environmental samples.
Computational biologists Jonathan Allen, Shea Gardner and Tom Slezak have designed new computational tools that identify a set of DNA markers that can distinguish between artificial vector sequences and natural DNA sequences. Vector sequences are used for bacterial genetic engineering to insert foreign genetic material into bacteria. Natural plasmids and artificial vector sequences have much in common, but the new computational tools show the potential to achieve high sensitivity and specificity in microarray-based bioassays, even when detecting previously unsequenced vectors.
A new computational genomics tool was developed to compare all available sequenced artificial vectors with available natural sequences, including plasmids and chromosomes, from bacteria and viruses. The tool clusters the artificial vector sequences into different subgroups based on shared sequences; these shared sequences are then compared with the natural plasmid and chromosomal sequence information so as to find regions that are unique to the artificial vectors.
Nearly all the artificial vector sequences had one or more unique regions. Short stretches of these unique regions are termed "candidate DNA signatures" and can be used as probes for detecting an artificial vector sequence in the presence of natural sequences. Further tests showed that subgroups of candidate DNA signatures are far more likely to match unseen artificial sequences than natural sequences.
The scientists say that the next step is to see whether a bioassay design using DNA signatures on microarrays can spot genetically modified DNA in a sample containing a mixture of natural and modified bacteria. If DNA signatures are to be used successfully to support detection and deterrence against malicious genetic engineering applications, the scientific community will need to work with computational experts to sequence and track available vector sequences. The scientists also will need to maintain an expanding database of DNA signatures to track all sequenced vectors.
"As with any attempt to counter malicious use of technology, detecting genetic engineering in microbes will be an immense challenge that requires many different tools and continual effort," Allen said.
For more information, contact wampler1 [at] llnl.gov ( Stephen Wampler. )
