Interactions of pathological hallmark proteins: Tubulin polymerization promoting protein/p25, {beta}-amyloid and {alpha}-synuclein

The disordered tubulin polymerization promoting protein (TPPP/p25) was found to be co-enriched in neuronal and glial inclusions with α-synuclein in Parkinson disease and multiple system atrophy, respectively; however, co-occurrence of α-synuclein with β-amyloid (Aβ) in human brain inclusions has been recently reported, suggesting the existence of mixed type pathologies that could result in obstacles in the correct diagnosis and treatment. Here we identified TPPP/p25 as an interacting partner of the soluble Aβ oligomers as major risk factors for Alzheimer disease using ProtoArray human protein microarray. The interactions of oligomeric Aβ with proteins involved in the etiology of neurological disorders were characterized by ELISA, surface plasmon resonance, pelleting experiments, and tubulin polymerization assay. We showed that the Aβ(42) tightly bound to TPPP/p25 (K(d) = 85 nm) and caused aberrant protein aggregation by inhibiting the physiologically relevant TPPP/p25-derived microtubule assembly. The pair-wise interactions of Aβ(42), α-synuclein, and tubulin were found to be relatively weak; however, these three components formed soluble ternary complex exclusively in the absence of TPPP/p25. The aggregation-facilitating activity of TPPP/p25 and its interaction with Aβ was monitored by electron microscopy with purified proteins by pelleting experiments with cell-free extracts as well as by confocal microscopy with CHO cells expressing TPPP/p25 or amyloid. The finding that the interaction of TPPP/p25 with Aβ can produce pathological-like aggregates is tightly coupled with unusual pathology of the Alzheimer disease revealed previously; that is, partial co-localization of Aβ and TPPP/p25 in the case of diffuse Lewy body disease with Alzheimer disease

Vegetation-based landscape regions of Hungary.

he first version of the map of the Hungarian vegetation-based landscape regions were prepared at the scale of 1 : 200,000 (1 km or higher resolution). The primary goal of the map was to provide an exact background for the presentation and evaluation of the data of theMÉTA database. Secondly, we intended to give an up-to-date and detailed vegetation-based division of Hungary with a comprehensive nomenclature of the regions. Regions were primarily defined on the basis of their present zonal vegetation, or their dominant extrazonal or edaphic vegetation. Where this was not possible, abiotic factors that influence the potential vegetation, the flora were taken into consideration, thus, political and economical factors were ignored. All region borders were defined by local expert botanists, mainly based on their field knowledge. The map differs in many features from the currently used, country- wide, flora- or geography-based divisions in many features. We consider our map to be temporary (i.e. a work map), and we plan to refine and improve it after 5 years of testing

Vegetation-based landscape regions of Hungary

The first version of the map of the Hungarian vegetation-based landscape regions were prepared at the scale of 1: 200,000 (1 km or higher resolution). The primary goal of the map was to provide an exact background for the presentation and evaluation of the data of the MÉTA database. Secondly, we intended to give an up-to-date and detailed vegetation-based division of Hungary with a comprehensive nomenclature of the regions. Regions were primarily defined on the basis of their present zonal vegetation, or their dominant extrazonal or edaphic vegetation. Where this was not possible, abiotic factors that influence the potential vegetation, the flora were taken into consideration, thus, political and economical factors were ignored. All region borders were defined by local expert botanists, mainly based on their field knowledge. The map differs in many features from the currently used, country-wide, flora-or geography-based divisions in many features. We consider our map to be temporary (i.e. a work map), and we plan to refine and improve it after 5 years of testing