A functional network of the tumor suppressors APC, hDlg, and PTEN, that relies on recognition of specific PDZ-domains

APC and PTEN are tumor suppressor proteins that bind through their C-termini to the PDZ domain containing-hDlg scaffolding protein. We have found that co-expression of PTEN and hDlg enhanced the negative regulation of the PI3K/Akt pathway by PTEN, indicating the physiologic importance of these interactions. APC and PTEN share other PDZ domain containing-interacting partners, including the MAGI scaffolding proteins and the MAST family of protein kinases. Mutational analysis revealed that the C-terminal PDZ-binding motifs from APC and PTEN were differentially recognized by distinct PDZ domains. APC bound to the three PDZ domains from hDlg, whereas PTEN mainly bound to PDZ-2/hDlg. This indicates the existence of overlapping, but distinct PDZ-domain recognition patterns by APC and PTEN. Furthermore, a ternary complex formed by APC, PTEN, and hDlg was detected, suggesting that hDlg may serve as a platform to bring in proximity APC and PTEN tumor suppressor activities. In line with this, tumor-related mutations targeting the PDZ-2/hDlg domain diminished its interaction with APC and PTEN. Our results expand the PDZ-domain counterparts for the tumor suppressor APC, show that APC and PTEN share PDZ-domain partners but have individual molecular determinants for specific recognition of PDZ domains, and suggest the participation of the tumor suppressors APC, PTEN, and hDlg in PDZ-domain interaction networks which may be relevant in oncogenesis.     

A comparative evaluation of presence-only methods for modelling species distribution

In spite of increasing application of presence-only models in ecology and conservation and the growing number of such models, little is known about the relative performance of different modelling methods, and some of the leading models (e.g. GARP and ENFA) have never been compared with one another. Here we compare the performance of six presence-only models that have been selected to represent an increasing level of model complexity [BIOCLIM, HABITAT, Mahalanobis distance (MD), DOMAIN, ENFA, and GARP] using data on the distribution of 42 species of land snails, nesting birds, and insectivorous bats in Israel. The models were calibrated using data from museum collections and observation databases, and their predictions were evaluated using Cohen's Kappa based on field data collected in a standardized sampling design covering most parts of Israel. Predictive accuracy varied between modelling methods with GARP and MD showing the highest accuracy, BIOCLIM and ENFA showing the lowest accuracy, and HABITAT and DOMAIN showing intermediate accuracy levels. Yet, differences between the various models were relatively small except for GARP and MD that were significantly more accurate than BIOCLIM and ENFA. In spite of large differences among species in prevalence and niche width, neither prevalence nor niche width interacted with the modelling method in determining predictive accuracy. However, species with relatively narrow niches were modelled more accurately than species with wider niches. Differences among species in predictive accuracy were highly consistent over all modelling methods, indicating the need for a better understanding of the ecological and geographical factors that influence the performance of species distribution models.