HAMMING CHROMATOGRAPHY

Selection of molecules with desired properties from random pools of bi opolymers has become a powerful tool in biotechnology. On designing an evolution experiment, a certain knowledge of the concomitant fitness landscape is clearly helpful to set up the optimal experimental condit ions. The correlation function is a useful means of characterizing a g iven landscape, since it can be efficiently measured if one has a meth od of separating a pool of random sequences according to their Hamming distance from a moderately small number of test sequences. In this pa per we describe a special type of hybridization chromatography, where a mixture of oligomers (partially) complementary to a given test-seque nce is hybridized to the test sequence, covalently bound to a matrix. DNA oligomers are eluted in an 'effective temperature gradient' using conditions that minimize the differences of effects of GC versus AT pa irs on the melting temperatures. This method should be a means to quic kly separate error classes and thus be the crucial step in characteriz ing fitness landscapes of biopolymers through an experimental approach , It would also be a useful tool to design sequence pools with a bias towards desired mutant spectra.