Biology by the numbers
July 20, 2010 § 2 Comments
Ron Milo and colleagues recently published a “Snapshot” article in Cell about key numbers in biology (Moran U, Phillips R, Milo R. 2010 SnapShot: key numbers in biology. Cell 141 1262-1262). This is a handy sampling of the most essential information in the BioNumbers database, which attempts to gather together credible, concrete numbers for biological properties in one easily searchable place. The overall goal is to enable “back of the envelope” calculations to be made in biology. This particular sampling includes key items such as cell volumes for E. coli, yeast and mammalian cells, measurements of size for the average protein molecule, cell membrane and nucleus, and rates of replication, translation, diffusion and degradation.
One back of the envelope calculation Ron and colleagues have already done using these numbers is: how long should it take E. coli to replicate its genome? The genome size is roughly 5 million bp and the replication rate is in the range of 200–1000 bp/s. So with two replisomes, it should take at least 2500 seconds (42 minutes) to replicate the genome. But E. coli can double faster than that — under ideal conditions it can divide once every 20 min. How is this possible? It turns out that when E. coli is very happy and growing fast, it doesn’t wait for the first DNA replication cycle to be completed before starting the next one. So there are actually more than 2 replisomes active per cell — around 4 — and this is what explains the apparently too-fast growth rate.
Ron would like to put together a larger set of “canonical” numbers in biology for use in both research and teaching. What are the most important numbers in your field? Can you find them in BioNumbers? (If not, can you please deposit them?) Are they broadly useful, and should they be included in Ron’s handy handbook? You can answer in the comments, or e-mail Ron directly.
Wonderful initiative. But I am concerned about the qualifications for an entry. I wouldn’t want to dilute the diversity of the database by including gene lengths of every gene from E. coli ! (for which we have better resources). Nonetheless, a handy source of practical information.
Can I add this blog my blogroll ?
Nagendra ~ (http://metabolicengineering.wordpress.com)
Indeed large scale data sets are usually deposited at dedicated websites. What we then do in BioNumbers is create a single “meta” BioNumber that points to this dataset (e.g. BNID 100597 database of chromosome sizes or 104390 rrna database). You can then search for gene length in E.coli and it will guide you to the relevant data set. In such cases BioNumbers serves as a portal to other biological databases without diluting its diversity just as you point out.