Once again physicists have made the great biological leap. It took physicists to design and carry out the experiments that unlocked neurophysiology. Now a group of physicists, biophysicists and a pathologist have published a flux balance analysis of all the metabolic pathways in our favorite bacteria, E. coli.
In a time when genetic and protein data are being generated at a remarkable rate, few people in biology have been able to come out of reductionism and into systemic thinking. The sheer amount of data is daunting, and excluding the biophysicists, many biologists don’t use (or need) math harder than ANOVA or a two-tailed T test.
For those interested in more of the crunchy details, the abstract from PubMed is below.
Nature. 2004 Feb 26;427(6977):839-43.
Global organization of metabolic fluxes in the bacterium Escherichia coli.
Almaas E, Kovacs B, Vicsek T, Oltvai ZN, Barabasi AL.
Department of Physics, University of Notre Dame, Notre Dame, Indiana 46556, USA.
Cellular metabolism, the integrated interconversion of thousands of metabolic substrates through enzyme-catalysed biochemical reactions, is the most investigated complex intracellular web of molecular interactions. Although the topological organization of individual reactions into metabolic networks is well understood, the principles that govern their global functional use under different growth conditions raise many unanswered questions. By implementing a flux balance analysis of the metabolism of Escherichia coli strain MG1655, here we show that network use is highly uneven. Whereas most metabolic reactions have low fluxes, the overall activity of the metabolism is dominated by several reactions with very high fluxes. E. coli responds to changes in growth conditions by reorganizing the rates of selected fluxes predominantly within this high-flux backbone. This behaviour probably represents a universal feature of metabolic activity in all cells, with potential implications for metabolic engineering.
Flux Balance Analysis — well, I liked the article, and if Peg sez it’s significant then I know it’s significant, but basically I didn’t know what the hell it was saying. SO I asked google what Flux Balance Analysis, and google told me the answer (google knows everything).
Anyway you can ask google yourself, but here at any rate is
<a href=”http://www.icsb2001.org/Pos…
one article</a> that I thought interesting — note that its authors, who are writing about biological pathways, are in the Department of Chemical Engineering. . .
that link (damn nucleous software. . . won’t handle simple html. . .grrr. . .)
http://www.icsb2001.org/Pos…
And, since there is no “preview” function, let me here section the link, in case the above doesn’t work:
http://www.icsb2001.org/Pos…
/084_mahadevan.pdf
“The sheer amount of data is daunting, and excluding the biophysicists, many biologists don’t use (or need) math harder than ANOVA or a two-tailed T test.”
Indeed. That reminds me of the project (linked below) that tracked the expression of most of the genes of a malaria species. They actually did Fourier transforms of the gene chip data to show the cycles of gene expression. They also made pretty colored charts of gene expression (near the end of the web page) that clearly show the different metabolic phases of the life cycle. I was rather impressed to see bio folks doing actual signal processing.
http://www.pubmedcentral.ni…
As Daniel points out, the increasing need for bioinformatics is pushing biologists toward better use of quantitative analysis. In general, though, they find someone they trust with the chops to do the work.