Molecular differentiation of cattle Sarcocystis spp. by multiplex PCR targeting 18S and COI genes following identification of Sarcocystis hominis in human stool samples.

Sarcocystis spp. are protozoan parasites which can infect a wide range of vertebrates, including humans; the latter can act as definitive hosts for two cattle Sarcocystis spp.: Sarcocystis hominis and Sarcocystis heydorni. Reports of intestinal sarcocystosis are well documented in the literature, but PCR-based methods have been scarcely used to identify Sarcocystis species in human stools, and have been limited to the molecular analysis of 18S ribosomal RNA (18S rRNA) gene sequences. Since the mitochondrial cytochrome c oxidase subunit I (COI) gene is one of the most promising tools for distinguishing between closely related Sarcocystis spp., and taking into account the lack of publicly available S. hominis COI sequences, in the present study we obtained the first partial COI sequence of S. hominis from human stool samples of patient with gastrointestinal symptoms. We designed specific COI primers to develop a multiplex PCR method for the identification of Sarcocystis spp. in cattle. The submission of the COI sequence described herein and the unambiguous identification of S. hominis through the application of the new multiplex PCR is important for determining the prevalence of this zoonotic Sarcocystis spp. in meat and the risk for consumers.

Structure-activity relationship of Ca2+ channel blockers: a study using conformational analysis and chemometric methods.

A structure-activity relationship study has been done on 8 compounds with the activity known as 'Ca2+ channel blockers'. Conformational analysis was carried out using a molecular mechanics method. The 3D-QSAR approach was used and the most polar functional groups present in all the molecules were considered. Eight interatomic distances are necessary to define the relative spatial disposition of these relevant molecular fragments. The structure-activity relationship between interatomic distances and biological activity was performed using statistic and chemometric methods. In particular, with Principal Component Analysis, it was possible to reduce the number of interatomic distances: only six of the eight distances are sufficient to describe the system in a useful way. A classification method was iteratively used to select the most probable conformations linked to the biological activity and to build a model able to classify conformations according to their biological behaviour. Cluster analysis on the active selected conformations subsequently allowed the identification of two different geometrical patterns for the active compounds. Finally the validity of the model was verified by correctly predicting the activity of other molecules not used in the construction of the model but possessing known activity.