Ultrastructural visualization of 3D chromatin folding using volume electron microscopy and DNA in situ hybridization.

The human genome is extensively folded into 3-dimensional organization. However, the detailed 3D chromatin folding structures have not been fully visualized due to the lack of robust and ultra-resolution imaging capability. Here, we report the development of an electron microscopy method that combines serial block-face scanning electron microscopy with in situ hybridization (3D-EMISH) to visualize 3D chromatin folding at targeted genomic regions with ultra-resolution (5 × 5 × 30 nm in xyz dimensions) that is superior to the current super-resolution by fluorescence light microscopy. We apply 3D-EMISH to human lymphoblastoid cells at a 1.7 Mb segment of the genome and visualize a large number of distinctive 3D chromatin folding structures in ultra-resolution. We further quantitatively characterize the reconstituted chromatin folding structures by identifying sub-domains, and uncover a high level heterogeneity of chromatin folding ultrastructures in individual nuclei, suggestive of extensive dynamic fluidity in 3D chromatin states

DYNAMICAL CLUSTERING AS A GENERATOR OF COMPLEX SYSTEM DYNAMICS

The challenge to understand the dynamics of Complex Systems is attracting attention from a wide range of disciplines across the natural, biological and social sciences. Recent turmoil in the financial markets has brought this challenge into the public domain, with speculation rife as to the root cause of the observed fluctuations. At their heart, all Complex Systems share the common property of featuring many interacting objects from which the observed macroscopic dynamics emerge. Exactly how this happens cannot yet be specified in a generic way — however, an important milestone in this endeavor is to develop a quantitative understanding of any internal clustering dynamics within the population. Coalescence-fragmentation processes have been studied widely in conventional chemistry and physics — however, collective behavior in social systems is not limited by nearest-neighbor interactions, nor are the details of social coalescence or fragmentation processes necessarily the same as in physical and biological systems. Here we discuss the general phenomenon of coalescence and fragmentation problems with a focus on social systems in which a typical fragmentation process corresponds to an entire group breaking up, as opposed to the typical binary splitting studied in physical and biological systems. Having discussed situations under which power-laws for the group distribution size emerge from such internal clustering dynamics, we move on to look at the specific application to financial markets. We propose a new model for financial market dynamics based on the combination of internal clustering (i.e. herding) dynamics with human decision-making. The resulting fluctuation in price movements is closer to what is observed empirically, leading us to speculate that the combination of dynamical clustering and decision-making are key for developing quantitative models of social dynamical phenomena

Quantitative image analysis in the structural synaptic plasticity studies

Analiza obrazów mikroskopowych odgrywa obecnie dominującą rolę w badaniach nad strukturą mózgu. Wgląd w strukturalną plastyczność synaptyczną może być kluczem do zrozumienia podstaw wielu zaburzeń neurodegeneracyjnych. Prawie w każdym eksperymencie niezbędna jest ilościowa analiza obrazów tkanki mózgowej, wymagająca często wyspecjalizowanego oprogramowania komputerowego ze względu na złożoność struktur analizowanych obrazów. W niniejszym tekście dokonamy przeglądu najważniejszych problemów towarzyszących analizie obrazów zebranych mikroskopem konfokalnym. Każdy z tych problemów wymaga zastosowania dedykowanych algorytmów.The analysis of confocal microscopy images has started to play a significant role in the brain structure analysis. An insight into structural synaptic plasticity may be the key to elucidate the molecular basis of many neurodegenerative disorders. Almost every experiment demands a quantitative analysis of brain tissue images, which requires specialized software able to cope with the structural complexity of the data. In the following text we will review common issues arising while performing the confocal image analysis and dedicated algorithms designed to overcome those problems

The interplay of seizures-induced axonal sprouting and transcription-dependent Bdnf repositioning in the model of temporal lobe epilepsy.

The Brain-Derived Neurotrophic Factor is one of the most important trophic proteins in the brain. The role of this growth factor in neuronal plasticity, in health and disease, has been extensively studied. However, mechanisms of epigenetic regulation of Bdnf gene expression in epilepsy are still elusive. In our previous work, using a rat model of neuronal activation upon kainate-induced seizures, we observed a repositioning of Bdnf alleles from the nuclear periphery towards the nuclear center. This change of Bdnf intranuclear position was associated with transcriptional gene activity. In the present study, using the same neuronal activation model, we analyzed the relation between the percentage of the Bdnf allele at the nuclear periphery and clinical and morphological traits of epilepsy. We observed that the decrease of the percentage of the Bdnf allele at the nuclear periphery correlates with stronger mossy fiber sprouting-an aberrant form of excitatory circuits formation. Moreover, using in vitro hippocampal cultures we showed that Bdnf repositioning is a consequence of transcriptional activity. Inhibition of RNA polymerase II activity in primary cultured neurons with Actinomycin D completely blocked Bdnf gene transcription and repositioning occurring after neuronal excitation. Interestingly, we observed that histone deacetylases inhibition with Trichostatin A induced a slight increase of Bdnf gene transcription and its repositioning even in the absence of neuronal excitation. Presented results provide novel insight into the role of BDNF in epileptogenesis. Moreover, they strengthen the statement that this particular gene is a good candidate to search for a new generation of antiepileptic therapies