Molecular markers reveal cryptic sex in the human pathogen Coccidioides immitis.

Coccidioides immitis, cause of a recent epidemic of "Valley fever" in California, is typical of many eukaryotic microbes in that mating and meiosis have yet to be reported, but it is not clear whether sex is truly absent or just cryptic. To find out, we have undertaken a population genetic study using PCR amplification, screening for single-strand conformation polymorphisms, and direct DNA sequencing to find molecular markers with nucleotide-level resolution. Both population genetic and phylogenetic analyses indicate that C. immitis is almost completely recombining. To our knowledge, this study is the first to find molecular evidence for recombination in a fungus for which no sexual stage has yet been described. These results motivate a directed search for mating and meiosis and illustrate the utility of single-strand conformation polymorphism and sequencing with arbitrary primer pairs in molecular population genetics.

Identification by representational difference analysis of a homozygous deletion in pancreatic carcinoma that lies within the BRCA2 region.

Homozygous deletions have been central to the discovery of several tumor-suppressor genes, but their finding has often been either serendipitous or the result of a directed search. A recently described technique [Lisitsyn, N., Lisitsyn, N. & Wigler, M. (1993) Science 259, 946-951] held out the potential to efficiently discover such events in an unbiased manner. Here we present the application of the representational difference analysis (RDA) to the study of cancer. We cloned two DNA fragments that identified a homozygous deletion in a human pancreatic adenocarcinoma, mapping to a 1-centimorgan region at chromosome 13q12.3 flanked by the markers D13S171 and D13S260. Interestingly, this lies within the 6-centimorgan region recently identified as the BRCA2 locus of heritable breast cancer susceptibility. This suggests that the same gene may be involved in multiple tumor types and that its function is that of a tumor suppressor rather than that of a dominant oncogene.

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.