Patterns in Genome Organization May Partially Explain How Microbial Cells Work
Jacobs School of Engineering
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 [organisms that lack nuclei] genomes is a complete surprise, and this finding carries 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 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 individual bacterial cells. 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. Nonrandom 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 spatial patterns in the arrangement of sequenced microbial genomes. They related the degree of organization in each genome they studied based on various characteristics.
“Bacterial chromosomes may have something like ZIP codes that fix groups of genes to certain locations within the cell where they are most needed,” said
Palsson’s team included Allen, recent Ph.D. graduate Nathan D. Price, and Ph.D. candidate Andrew R. Joyce. They downloaded the sequences of the 151 prokaryotic genomes from the CBS Genome Atlas Database and analyzed regions of each genome for the relative amount of four basic building blocks of DNA, the density of genes and expression level of those genes, and other factors.
To detect patterns in those features, they used wavelet analysis, a statistical technique that also has been used to identify patterns in geophysical data, such as warming of the surface of the ocean off South America that causes El Niño climatic events. The wavelet analysis of bacterial genomes yielded “scalograms,” maps colored to elucidate the strength of a variety of periodicities associated with chromosome position. Just as the wavelet analysis has identified significant increases in sea surface temperatures in El Niño events, it also revealed nonrandom patterns in the genomes of most of the 151 microorganisms studied.
“The analysis generated diagrams of psychedelically colored islands of statistically significant patterns floating in a sea of insignificant patterns,” said Palsson, author of Systems Biology: Properties of Reconstructed Networks (Cambridge University Press, 2006). “Basically, it demonstrated that most bacterial genomes are highly organized. Our results demonstrate that there are significant evolutionary constraints that act upon genomes organization as well as upon genome content. That interplay between organization and function can’t be ignored if we want to gain a better fundamental understanding of how a microbial cell works.”
Jacobs School of Engineering