Biology subjects

Trzaskoma, P.

Publications and source records attributed to Trzaskoma, P..

4 recordsLinked to original sources

bioRxiv2026

Highly Constrained Kinetic Models for Single-Cell Gene Expression Analysis

Advances in single-cell RNA sequencing (scRNA-seq) and high-resolution imaging techniques, such as single-molecule tracking (SMT) of RNA and transcription factors, allow researchers to quantitatively explore dynamics and variation but have never been integrated into a single coherent model. In this study, we propose a kinetic model that intakes multiple data types, including steady-state and time-resolved datasets, to simulate and fit stochastic models of gene transcription to experimental data. We find that 3-state models provide an essential improvement over the widely used 2-state model for most genes and have the property of kinetic proofreading, which we argue is advantageous in the cellular context. We further identify two dimensionless quantities derived from the rate equations which are broadly conserved across genes. Finally, we extend this model to scRNA-seq datasets to infer kinetic rates under defined perturbations and reveal biochemical insight into the mechanism of action of transcription factors.

bioinformatics↗

bioRxiv2024

Neuronal activation affects the organization and protein composition of the nuclear speckles

Nuclear speckles, also known as interchromatin granule clusters (IGCs), are subnuclear domains highly enriched in proteins involved in transcription and mRNA metabolism and, until recently, have been regarded primarily as their storage and modification hubs. However, several recent studies on non-neuronal cell types indicate that nuclear speckles may directly contribute to gene expression as some of the active genes have been shown to associate with these structures. Neuronal activity is one of the key transcriptional regulators and may lead to the rearrangement of some nuclear bodies. Notably, the impact of neuronal activation on IGC/nuclear speckles organization and function remains unexplored. To address this research gap, we examined whether and how neuronal stimulation affects the organization of these bodies in granular neurons from the rat hippocampal formation. Our findings demonstrate that neuronal stimulation induces morphological and proteomic remodelling of the nuclear speckles under both in vitro and in vivo conditions. Importantly, these changes are not associated with cellular stress or cell death but are dependent on transcription and splicing.

cell biology↗

bioRxiv2020

PartSeg, a Tool for Quantitative Feature Extraction From 3D Microscopy Images for Dummies

BackgroundBioimaging 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 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 limited technical background. This is especially apparent in bulk processing of image sets, which requires the use of some form of programming notation. ResultsIn this paper, we present PartSeg, a tool for segmentation and reconstruction of 3D microscopy images, optimised for the study of 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 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. ConclusionsIn 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 multiscale segmentation algorithms best-suited for this task. PartSeg can also be used for bulk processing of multiple images and its components can be reused in other systems or computational experiments. Contact g.bokota@cent.uw.edu.pl, a.magalska@nencki.edu.pl, d.plewczynski@cent.uw.edu.pl

bioinformatics↗

bioRxiv2020

Ultrastructural Visualization of 3D Chromatin Folding Using Serial Block-Face Scanning Electron Microscopy and In Situ Hybridization (3D-EMISH)

The human genome is extensively folded into 3-dimensional organization, yet 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 a novel 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 (5x5x30 nm in xyz dimensions, respectively). We applied 3D-EMISH to human lymphoblastoid cells at a 1.7 Mb segment of the genome and visualized a large number of distinctive 3D chromatin folding structures in high ultra-resolution. We further quantitatively characterized the reconstituted chromatin folding structures by identifying sub-domains, and uncovered a high level of heterogeneity in chromatin folding ultrastructures, suggestive of extensive dynamic fluidity in 3D chromatin states.

genomics↗