Specific cleavage of chromosomal and plasmid DNA strands in gram-positive and gram-negative bacteria can be detected with nucleotide resolution

A sensitive and precise in vitro technique for detecting DNA strand discontinuities produced in vivo has been developed. The procedure, a form of runoff DNA synthesis on molecules released from lysed bacterial cells, mapped precisely the position of cleavage of the plasmid pMV158 leading strand origin in Streptococcus pneumoniae and the site of strand scission, nic, at the transfer origins of F and the F-like plasmid R1 in Escherichia coli. When high frequency of recombination strains of E. coli were examined, DNA strand discontinuities at the nic positions of the chromosomally integrated fertility factors were also observed. Detection of DNA strand scission at the nic position of F DNA in the high frequency of recombination strains, as well as in the episomal factors, was dependent on sexual expression from the transmissable element, but was independent of mating. These results imply that not only the transfer origins of extrachromosomal F and F-like fertility factors, but also the origins of stably integrated copies of these plasmids, are subject to an equilibrium of cleavage and ligation in vivo in the absence of DNA transfer.

Computational method to reduce the search space for directed protein evolution

We introduce a computational method to optimize the in vitro evolution of proteins. Simulating evolution with a simple model that statistically describes the fitness landscape, we find that beneficial mutations tend to occur at amino acid positions that are tolerant to substitutions, in the limit of small libraries and low mutation rates. We transform this observation into a design strategy by applying mean-field theory to a structure-based computational model to calculate each residue's structural tolerance. Thermostabilizing and activity-increasing mutations accumulated during the experimental directed evolution of subtilisin E and T4 lysozyme are strongly directed to sites identified by using this computational approach. This method can be used to predict positions where mutations are likely to lead to improvement of specific protein properties.