Neuronal Nogo-A negatively regulates dendritic morphology and synaptic transmission in the cerebellum.

Neuronal signal integration as well as synaptic transmission and plasticity highly depend on the morphology of dendrites and their spines. Nogo-A is a membrane protein enriched in the adult central nervous system (CNS) myelin, where it restricts the capacity of axons to grow and regenerate after injury. Nogo-A is also expressed by certain neurons, in particular during development, but its physiological function in this cell type is less well understood. We addressed this question in the cerebellum, where Nogo-A is transitorily highly expressed in the Purkinje cells (PCs) during early postnatal development. We used general genetic ablation (KO) as well as selective overexpression of Nogo-A in PCs to analyze its effect on dendritogenesis and on the formation of their main input synapses from parallel (PFs) and climbing fibers (CFs). PC dendritic trees were larger and more complex in Nogo-A KO mice and smaller than in wild-type in Nogo-A overexpressing PCs. Nogo-A KO resulted in premature soma-to-dendrite translocation of CFs and an enlargement of the CF territory in the molecular layer during development. Although spine density was not influenced by Nogo-A, the size of postsynaptic densities of PF-PC synapses was negatively correlated with the Nogo-A expression level. Electrophysiological studies revealed that Nogo-A negatively regulates the strength of synaptic transmission at the PF-PC synapse. Thus, Nogo-A appears as a negative regulator of PC input synapses, which orchestrates cerebellar connectivity through regulation of synapse morphology and the size of the PC dendritic tree.

Dynamic histone marks in the hippocampus and cortex facilitate memory consolidation.

Memory consolidation requires a timely controlled interplay between the hippocampus, a brain region important for memory formation, and the cortex, a region recruited for memory storage. Here we show that memory consolidation is associated with specific epigenetic modifications on histone proteins that have a distinct dynamic in these brain areas. While in the hippocampus, histone post-translational modifications (PTMs) are rapidly and transiently activated after learning, in the cortex they are induced with delay but persist over time. When these histone PTMs are increased in vivo by transgenic intervention or intense training, they facilitate memory consolidation. Conversely, when they are pharmacologically blocked, memory consolidation is impaired. These histone PTMs are further associated with the expression of the immediate early gene zif268, a transcription factor that favours memory consolidation. These findings reveal the spatiotemporal dynamics of histone marks during memory consolidation, and demonstrate their inherent 'mnemonic' property.

Tapping the potential of intact cell mass spectrometry with a combined data analytical approach applied to Yersinia spp.: detection, differentiation and identification of Y. pestis.

In the everyday routine of an analytic lab, one is often confronted with the challenge to identify an unknown microbial sample lacking prior information to set the search limits. In the present work, we propose a workflow, which uses the spectral diversity of a commercial database (SARAMIS) to narrow down the search field at a certain taxonomic level, followed by a refined classification by supervised modelling. As supervised learning algorithm, we have chosen a shrinkage discriminant analysis approach, which takes collinearity of the data into account and provides a scoring system for biomarker ranking. This ranking can be used to tailor specific biomarker subsets, which optimize discrimination between subgroups, allowing a weighting of misclassification. The suitability of the approach was verified based on a dataset containing the mass spectra of three Yersinia species Yersinia enterocolitica, Y. pseudotuberculosis and Yersinia pestis. Thereby, we laid the emphasis on the discrimination between the highly related species Yersinia pseudotuberculosis and Y. pestis. All three species were correctly identified at the genus level by the commercial database. Whereas Y. enterocolitica was correctly identified at the species level, discrimination between the highly related Y. pseudotuberculosis and Y. pestis strains was ambiguous. With the use of the supervised modelling approach, we were able to accurately discriminate all the species even when grown under different culture conditions.