Scientists at the U.S. Department of Energy's Brookhaven National Laboratory have developed a new, high-throughput technique for identifying the many species of microorganisms living in an unknown "microbial community."
The method, described in the March 2006 issue of Applied Environmental Microbiology, has many applications -- from assessing the microbes present in environmental samples and identifying species useful for cleaning up contamination to identifying pathogens and distinguishing harmless bacteria from potential bioterror weapons.
"Microbial communities are enormously diverse and complex, with hundreds of species per milliliter of water or thousands per gram of soil," said Brookhaven biologist Daniel (Niels) van der Lelie, lead author of the study. "Elucidating this complexity is essential if we want to fully understand the roles microbes play in global cycles, make use of their enormous metabolic capabilities, or easily identify potential threats to human health."
Growing cultures of microbes to identify species is slow and error prone as the culture conditions often screen out important members of the community. Sequencing entire genomes, while highly specific and informative, would be too labor intensive and costly. So scientists have been searching for ways to identify key segments of genetic code that are short enough to be sequenced rapidly and can readily distinguish among species.
The Brookhaven team has developed just such a technique, which they call "single point genome signature tagging." Using enzymes that recognize specific sequences in the genetic code, they chop the microbial genomes into small segments that contain identifier genes common to all microbial species, plus enough unique genetic information to tell the microbes apart.
In one example, the scientists cut and splice pieces of DNA to produce "tags" that contain 16 "letters" of genetic code somewhat "upstream" from the beginning of the gene that codes for a piece of the ribosome -- the highly conserved "single point" reference gene. By sequencing these tags and comparing the sequenced code with databases of known bacterial genomes, the Brookhaven team determined that this specific 16-letter region contains enough unique genetic information to successfully identify all community members down to the genus level, and most to the species level as well.