PartSeg: a tool for quantitative feature extraction from 3D microscopy images for dummies.

BACKGROUND: Bioimaging techniques offer a robust tool for studying molecular pathways and morphological phenotypes of cell populations subjected to various conditions. As modern high-resolution 3D microscopy provides access to an ever-increasing amount of high-quality images, there arises a need for their analysis in an automated, unbiased, and simple way. Segmentation of structures within the cell nucleus, which is the focus of this paper, presents a new layer of complexity in the form of dense packing and significant signal overlap. At the same time, the available segmentation tools provide a steep learning curve for new users with a limited technical background. This is especially apparent in the bulk processing of image sets, which requires the use of some form of programming notation. RESULTS: In this paper, we present PartSeg, a tool for segmentation and reconstruction of 3D microscopy images, optimised for the study of the cell nucleus. PartSeg integrates refined versions of several state-of-the-art algorithms, including a new multi-scale approach for segmentation and quantitative analysis of 3D microscopy images. The features and user-friendly interface of PartSeg were carefully planned with biologists in mind, based on analysis of multiple use cases and difficulties encountered with other tools, to offer an ergonomic interface with a minimal entry barrier. Bulk processing in an ad-hoc manner is possible without the need for programmer support. As the size of datasets of interest grows, such bulk processing solutions become essential for proper statistical analysis of results. Advanced users can use PartSeg components as a library within Python data processing and visualisation pipelines, for example within Jupyter notebooks. The tool is extensible so that new functionality and algorithms can be added by the use of plugins. For biologists, the utility of PartSeg is presented in several scenarios, showing the quantitative analysis of nuclear structures. CONCLUSIONS: In this paper, we have presented PartSeg which is a tool for precise and verifiable segmentation and reconstruction of 3D microscopy images. PartSeg is optimised for cell nucleus analysis and offers multi-scale segmentation algorithms best-suited for this task. PartSeg can also be used for the bulk processing of multiple images and its components can be reused in other systems or computational experiments.

Activation-induced chromatin reorganization in neurons depends on HDAC1 activity.

Spatial chromatin organization is crucial for transcriptional regulation and might be particularly important in neurons since they dramatically change their transcriptome in response to external stimuli. We show that stimulation of neurons causes condensation of large chromatin domains. This phenomenon can be observed in vitro in cultured rat hippocampal neurons as well as in vivo in the amygdala and hippocampal neurons. Activity-induced chromatin condensation is an active, rapid, energy-dependent, and reversible process. It involves calcium-dependent pathways but is independent of active transcription. It is accompanied by the redistribution of posttranslational histone modifications and rearrangements in the spatial organization of chromosome territories. Moreover, it leads to the reorganization of nuclear speckles and active domains located in their proximity. Finally, we find that the histone deacetylase HDAC1 is the key regulator of this process. Our results suggest that HDAC1-dependent chromatin reorganization constitutes an important level of transcriptional regulation in neurons.