( The location of a piece of real estate ...)Patterns in genome organization may partially explain how microbial cells work

The location of a piece of real estate may be its most important feature to many Realtors, and bioengineering researchers at the University of California, San Diego (UCSD) and the University of Virginia have reported that the location of genes and other features distributed along the chromosomes of bacteria and simpler organisms also is fundamentally important to how microbial cells operate.

In a paper published Jan. 13 online in PLoS Computational Biology, the researchers reported large- and small-scale organizational patterns in the genomes of 135 bacteria ranging from those that cause typhoid fever and various other human infections to organisms that enrich the nitrogen content of soil. In addition, 16 more primitive microorganisms, including one that thrives in boiling hot springs, also exhibit patterns in their genomes that are highly nonrandom.

"This high degree of organization of prokaryotic genomes is a complete surprise, and this finding carried many implications that biologists might not have considered before," said Bernhard Palsson, a professor of bioengineering at UCSD's Jacobs School of Engineering and adjunct professor of medicine and co-author of the analysis. "These findings show that evolution of prokaryotes [organisms that lack nuclei] is constrained not just by variations in the content of genes, but also by the intricate ways in which those genes are arranged on chromosomes."

A bacterial cell usually operates with one copy of its genome. Until 2002, there had been no way to determine if a particular gene or area of the chromosome was segregated in any particular way inside the cell. New techniques that attach fluorescent "reporter" markers to predetermined spots on chromosomes have indicated that many bacterial genes tend to be found at specific cellular locations. Patterns are not obvious in the sequences of prokaryotic genomes, which led the team led by Palsson to use signal-processing methods to identify long-range spat
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Source:University of California - San Diego

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