MaSTR™: an effective probabilistic genotyping tool for interpretation of STR mixtures associated with differentially degraded DNA.

The recently developed probabilistic genotyping software package MaSTR™ (SoftGenetics LLC) was used to develop statistical weight estimates for a variety of two-person STR mixture profiles with differentially degraded sources of DNA. A total of 864 analyses, on 144 two-person profiles, were performed. Mixture ratios ranged from 1:1 to 1:10, including pristine sources of DNA and various combinations of artificially degraded DNA (average size fragments of 150 or 250 bps). Quantities of DNA template were varied (0.1 to 0.5 ngs of total input) and MaSTR™ analysis was performed with eight chains of 10,000 or 40,000 iterations, with or without a conditioning profile to generate likelihood ratio (LR) values. Overall, the software performed as expected. The resulting log(LR) values for pristine mixture profiles were typically greater than 1030. Lower-quality mixture data associated with sources of DNA at ~ 0.05 ngs for each contributor resulted in peak imbalance and allelic dropout which reduced the weight in support of a contributor. This was exacerbated by higher levels of degradation, with some instances resulting in log(LR) values in support of an exclusion. These studies provide additional support for the use of probabilistic genotyping software solutions in forensic investigations, addressing concerns raised by the President's Council of Advisors on Science and Technology (PCAST).

Targeting the epigenome: Screening bioactive compounds that regulate histone deacetylase activity.

SCOPE: Nutrigenomics is a rapidly expanding field that elucidates the link between diet-genome interactions. Recent evidence demonstrates that regulation of the epigenome, and in particular inhibition of histone deacetylases (HDACs), impact pathogenetic mechanisms involved in chronic disease. Few studies, to date, have screened libraries of bioactive compounds that act as epigenetic modifiers. This study screened a library of 131 natural compounds to determine bioactive compounds that inhibit Zn-dependent HDAC activity. METHODS AND RESULTS: Using class-specific HDAC substrates, we screened 131 natural compounds for HDAC activity in bovine cardiac tissue. From this screen, we identified 18 bioactive compound HDAC inhibitors. Using our class-specific HDAC substrates, we next screened these 18 bioactive compounds against recombinant HDAC proteins. Consistent with inhibition of HDAC activity, these compounds were capable of inhibiting activity of individual HDAC isoforms. Lastly, we report that treatment of H9c2 cardiac myoblasts with bioactive HDAC inhibitors was sufficient to increase lysine acetylation as assessed via immunoblot. CONCLUSION: This study provided the first step in identifying multiple bioactive compound HDAC inhibitors. Taken together, this report sets the stage for future exploration of these bioactive compounds as epigenetic regulators to potentially ameliorate chronic disease.