- THIS ARTICLE
- Full Text
- Full Text (PDF)
-
All Versions of this Article:
genetics.109.106492v1
genetics.109.106492v2
183/2/639 most recent - Alert me when this article is cited
- Alert me if a correction is posted
- SERVICES
- Email this article to a friend
- Similar articles in this journal
- Similar articles in PubMed
- Alert me to new issues of the journal
- Download to citation manager
- Reprints & Permissions
- CITING ARTICLES
- Citing Articles via Google Scholar
- GOOGLE SCHOLAR
- Articles by Chen, P.
- Articles by Shakhnovich, E. I.
- Search for Related Content
- PUBMED
- PubMed Citation
- Articles by Chen, P.
- Articles by Shakhnovich, E. I.
Originally published as Genetics Published Articles Ahead of Print on July 20, 2009.
Genetics, Vol. 183, 639-650, October 2009, Copyright © 2009
doi:10.1534/genetics.109.106492
Lethal Mutagenesis in Viruses and Bacteria
Peiqiu Chen*,
and
Eugene I. Shakhnovich*,1
* Department of Chemistry and Chemical Biology and
Department of Physics, Harvard University, Cambridge, Massachusetts 02138
1 Corresponding author: Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford St., Cambridge, MA 02138.
E-mail: eugene{at}belok.harvard.edu
In this work we study how mutations that change physical properties of cell proteins (stability) affect population survival and growth. We present a model in which the genotype is presented as a set folding free energies of cell proteins. Mutations occur upon replication, so stabilities of some proteins in daughter cells differ from those in the parent cell by amounts deduced from the distribution of mutational effects on protein stability. The genotype–phenotype relationship posits that the cell's fitness (replication rate) is proportional to the concentration of its folded proteins and that unstable essential proteins result in lethality. Simulations reveal that lethal mutagenesis occurs at a mutation rate close to seven mutations in each replication of the genome for RNA viruses and at about half that rate for DNA-based organisms, in accord with earlier predictions from analytical theory and experimental results. This number appears somewhat dependent on the number of genes in the organisms and the organism's natural death rate. Further, our model reproduces the distribution of stabilities of natural proteins, in excellent agreement with experiments. We find that species with high mutation rates tend to have less stable proteins compared to species with low mutation rates.