University researchers have designed a suite of computer programs to analyze microbial genome sequences. The system is meant to help public health officials quickly characterize the pathogens that cause disease epidemics.
The system, called the Computational Genome Pipeline by its Georgia Tech developers, now does in 24 hours what once took months to achieve by conventional means.
It’s easy to see how such a system could be useful in identifying and characterizing agents responsible for a bio-terror attack.
“High-throughput experimental techniques for the characterization of genome sequences have evolved rapidly over the last decade,” said Georgia Tech biology professor King Jordan. Jordan told Homeland1 that it’s now possible to characterize the complete sequences of numerous bacterial genomes, in particular the genome sequences of microbial pathogens, in a single day.
Jordan said that the CG-Pipeline software provides an integrated and fully automated platform for the analysis of microbial genome sequences.
“Determining the order of DNA bases for an entire genome has become relatively cheap and easy in recent years because of technological advancements,” said Jordan.
“The hard part is figuring out what the genome sequence information means. Our software takes that next step. It analyzes the sequences, finds the genes and provides clues as to which genes are involved in making people sick. Manually, this process used to take weeks, months or a year.”
The CG-Pipeline software has already proved useful. It was used in 2011 to analyze the outbreak of severe Escherichia coli infections that originated in sprouts in Germany and eventually led to illnesses in 16 European countries, Canada and the United States. It was one of the largest E. coli outbreaks in history, with more than 4,000 cases worldwide, including 50 deaths.
The open source CG-Pipeline system was used to understand why the strain of bacteria that caused the 2011 E. coli outbreak was so virulent. The system determined that genetic material from two previously distinct strains of E. coli had combined in a hybrid, hyper-virulent strain, which seemed to be more lethal than either of the parent strains.
The CG-Pipeline system was also used to analyze the bacteria that caused last year’s outbreak of listeriosis in the United States. That outbreak was traced back to cantaloupes from a single farm in Colorado that were tainted with Listeria bacteria.
Over several months, there were 146 confirmed cases of listeriosis and 30 deaths, making it the deadliest outbreak of food-borne illness in the United States in 25 years. Using the CG-pipeline, officials were able to identify an important epidemiological genomic marker, helping track invasive strains of Listeria.