325 research outputs found
Soluble oligomerization provides a beneficial fitness effect on destabilizing mutations.
Protein stability is widely recognized as a major evolutionary constraint. However, the relation between mutation-induced perturbations of protein stability and biological fitness has remained elusive. Here we explore this relation by introducing a selected set of mostly destabilizing mutations into an essential chromosomal gene of E.coli encoding dihydrofolate reductase (DHFR) to determine how changes in protein stability, activity and abundance affect fitness. Several mutant strains showed no growth while many exhibited fitness higher than wild type. Overexpression of chaperonins (GroEL/ES) buffered the effect of mutations by rescuing the lethal phenotypes and worsening better-fit strains. Changes in stability affect fitness by mediating the abundance of active and soluble proteins; DHFR of lethal strains aggregates, while destabilized DHFR of high fitness strains remains monomeric and soluble at 30oC and forms soluble oligomers at 42oC. These results suggest an evolutionary path where mutational destabilization is counterbalanced by specific oligomerization protecting proteins from aggregation
Lethal Mutagenesis in Viruses and Bacteria
Here we study how mutations which change physical properties of cell proteins
(stability) impact population survival and growth. In our model the genotype is
presented as a set of N numbers, folding free energies of cells N proteins.
Mutations occur upon replications so that stabilities of some proteins in
daughter cells differ from those in parent cell by random amounts drawn from
experimental distribution of mutational effects on protein stability. The
genotype-phenotype relationship posits that unstable proteins confer lethal
phenotype to a cell and in addition the cells fitness (duplication rate) is
proportional to the concentration of its folded proteins. Simulations reveal
that lethal mutagenesis occurs at mutation rates close to 7 mutations per
genome per replications for RNA viruses and about half of that for DNA based
organisms, in accord with earlier predictions from analytical theory and
experiment. This number appears somewhat dependent on the number of genes in
the organisms and natural death rate. Further, our model reproduces the
distribution of stabilities of natural proteins in excellent agreement with
experiment. Our model predicts that species with high mutation rates, tend to
have less stable proteins compared to species with low mutation rate
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