Rescue of odontogenesis in Dmp1-deficient mice by targeted re-expression of DMP1 reveals roles for DMP1 in early odontogenesis and dentin apposition in vivo

Dentin matrix protein 1 (DMP1) is expressed in both pulp and odontoblast cells and deletion of the Dmp1 gene leads to defects in odontogenesis and mineralization. The goals of this study were to examine how DMP1 controls dentin mineralization and odontogenesis in vivo. Fluorochrome labeling of dentin in Dmp1-null mice showed a diffuse labeling pattern with a 3-fold reduction in dentin appositional rate compared to controls. Deletion of DMP1 was also associated with abnormalities in the dentinal tubule system and delayed formation of the third molar. Unlike the mineralization defect in Vitamin D receptor-null mice, the mineralization defect in Dmp1-null mice was not rescued by a high calcium and phosphate diet, suggesting a different effect of DMP1 on mineralization. Re-expression of Dmp1 in early and late odontoblasts under control of the Col1a1 promoter rescued the defects in mineralization as well as the defects in the dentinal tubules and third molar development. In contrast, re-expression of Dmp1 in mature odontoblasts, using the Dspp promoter, produced only a partial rescue of the mineralization defects. These data suggest that DMP1 is a key regulator of odontoblast differentiation, formation of the dentin tubular system and mineralization and its expression is required in both early and late odontoblasts for normal odontogenesis to proceed.     

Residue-level prediction of DNA-binding sites and its application on DNA-binding protein predictions

Protein-DNA interactions are crucial to many cellular activities such as expression-control and DNA-repair. These interactions between amino acids and nucleotides are highly specific and any aberrance at the binding site can render the interaction completely incompetent. In this study, we have three aims focusing on DNA-binding residues on the protein surface: to develop an automated approach for fast and reliable recognition of DNA-binding sites; to improve the prediction by distance-dependent refinement; use these predictions to identify DNA-binding proteins. We use a support vector machines (SVM)-based approach to harness the features of the DNA-binding residues to distinguish them from non-binding residues. Features used for distinction include the residue's identity, charge, solvent accessibility, average potential, the secondary structure it is embedded in, neighboring residues, and location in a cationic patch. These features collected from 50 proteins are used to train SVM. Testing is then performed on another set of 37 proteins, much larger than any testing set used in previous studies. The testing set has no more than 20% sequence identity not only among its pairs, but also with the proteins in the training set, thus removing any undesired redundancy due to homology. This set also has proteins with an unseen DNA-binding structural class not present in the training set. With the above features, an accuracy of 66% with balanced sensitivity and specificity is achieved without relying on homology or evolutionary information. We then develop a post-processing scheme to improve the prediction using the relative location of the predicted residues. Balanced success is then achieved with average sensitivity, specificity and accuracy pegged at 71.3%, 69.3% and 70.5%, respectively. Average net prediction is also around 70%. Finally, we show that the number of predicted DNA-binding residues can be used to differentiate DNA-binding proteins from non-DNA-binding proteins with an accuracy of 78%. Results presented here demonstrate that machine-learning can be applied to automated identification of DNA-binding residues and that the success rate can be ameliorated as more features are added. Such functional site prediction protocols can be useful in guiding consequent works such as site-directed mutagenesis and macromolecular docking.     

Interleukin-1 (IL-1)-induced TAK1-dependent Versus MEKK3-dependent NFkappaB activation pathways bifurcate at IL-1 receptor-associated kinase modification

Interleukin-1 (IL-1) receptor-associated kinase (IRAK) is phosphorylated after it is recruited to the receptor, subsequently ubiquitinated, and eventually degraded upon IL-1 stimulation. Although a point mutation changing lysine 134 to arginine (K134R) in IRAK abolished IL-1-induced IRAK ubiquitination and degradation, mutations of serines and threonines adjacent to lysine 134 to alanines ((S/T)A (131-144)) reduced IL-1-induced IRAK phosphorylation and abolished IRAK ubiquitination. Through the study of these IRAK modification mutants, we uncovered two parallel IL-1-mediated signaling pathways for NFkappaB activation, TAK1-dependent and MEKK3-dependent, respectively. These two pathways bifurcate at the level of IRAK modification. The TAK1-dependent pathway leads to IKKalpha/beta phosphorylation and IKKbeta activation, resulting in classical NFkappaB activation through IkappaBalpha phosphorylation and degradation. The TAK1-independent MEKK3-dependent pathway involves IKKgamma phosphorylation and IKKalpha activation, resulting in NFkappaB activation through IkappaBalpha phosphorylation and subsequent dissociation from NFkappaB but without IkappaBalpha degradation. These results provide significant insight to our further understanding of NFkappaB activation pathways.     

Heat shock protein 70 interacts with aquaporin-2 and regulates its trafficking

The trafficking of aquaporin-2 (AQP2) involves multiple complex pathways, including regulated, cAMP-, and cGMP-mediated pathways, as well as a constitutive recycling pathway. Although several accessory proteins have been indirectly implicated in AQP2 recycling, the direct protein-protein interactions that regulate this process remain largely unknown. Using yeast two-hybrid screening of a human kidney cDNA library, we have identified the 70-kDa heat shock proteins as AQP2-interacting proteins. Interaction was confirmed by mass spectrometry of proteins pulled down from rat kidney papilla extract using a GST-AQP2 C-terminal fusion protein (GST-A2C) as a bait, by co-immunoprecipitation (IP) assays, and by direct binding assays using purified hsc70 and the GST-A2C. The direct interaction of AQP2 with hsc70 is partially inhibited by ATP, and the Ser-256 residue in the AQP2 C terminus is important for this direct interaction. Vasopressin stimulation in cells enhances the interaction of hsc70 with AQP2 in IP assays, and vasopressin stimulation in vivo induces an increased co-localization of hsc70 and AQP2 on the apical membrane of principal cells in rat kidney collecting ducts. Functional knockdown of hsc70 activity in AQP2 expressing cells results in membrane accumulation of AQP2 and reduced endocytosis of rhodamine-transferrin. Our data also show that AQP2 interacts with hsp70 in multiple in vitro binding assays. Finally, in addition to hsc70 and hsp70, AQP2 interacts with several other key components of the endocytotic machinery in co-IP assays, including clathrin, dynamin, and AP2. To summarize, we have identified the 70-kDa heat shock proteins as a AQP2 interactors and have shown for hsc70 that this interaction is involved in AQP2 trafficking.     

Stratigraphic record of U37K in Sanmen Bay: the effect of SST and EI Niño on life activity in macrobenthos communities

Sea surface temperature (SST) from 1916–2003 was estimated by using the index of U₃₇^K of organic compounds in Sanmen Bay (SMB) sediment. It fluctuated between 15.97°C and 18.00°C with an average of 17.03°C. The estimated SST was 3.52°C lower than the annual average temperature measured in the same year but was close to the temperature measured in fall. The research suggested that the climate events (EI Ni?o) on large scale in Sanmen Bay were affected by the climate, similar to that in the East Pacific Ocean (EPC). The change scale was also affected by geographical location and local climate such as monsoon. According to the chronological basis, the events in SMB corresponded to those in EPC, but the scale of variation is not so strong as that in EPC. By comparing the community, biomass, individual density and biodiversity of macrobenthos during EI Ni?o (between 2002 and 2003) and non-EI Ni?o (between 2005 and 2006) periods, it was indicated that certain macrobenthos communities in SMB responded to EI Ni?o events. During the EI Ni?o period, Taiwan warm current (TWC) is much stronger than that in normal years. The diversity of macrobenthos during 2002 and 2003 was relatively low owing to invasion of the warm current that caused salinity change. The macrobenthos and zooplankton in Sanmen Bay responded to EI Ni?o events significantly. The diversity of macrobenthos decreased significantly because TWC invaded into the shallow bay from the floor and thus changed the temperature and salinity in the bay. On the other hand, zooplankton species, biomass and abundance increased in the period of EI Ni?o since the invaded warm current brought abundant species of zooplankton.