Biology subjects

Pujadas, E.

Publications and source records attributed to Pujadas, E..

3 recordsLinked to original sources

bioRxiv2024

Deep Learning-driven Automatic Nuclei Segmentation of Label-free Live Cell Chromatin-sensitive Partial Wave Spectroscopic Microscopy Imaging

Chromatin-sensitive Partial Wave Spectroscopic (csPWS) microscopy offers a non-invasive glimpse into the mass density distribution of cellular structures at the nanoscale, leveraging the spectroscopic information. Such capability allows us to analyze the chromatin structure and organization and the global transcriptional state of the cell nuclei for the study of its role in carcinogenesis. Accurate segmentation of the nuclei in csPWS microscopy images is an essential step in isolating them for further analysis. However, manual segmentation is error-prone, biased, time-consuming, and laborious, resulting in disrupted nuclear boundaries with partial or over-segmentation. Here, we present an innovative deep-learning-driven approach to automate the accurate nuclei segmentation of label-free live cell csPWS microscopy imaging data. Our approach, csPWS-seg, harnesses the Convolutional Neural Networks-based U-Net model with an attention mechanism to automate the accurate cell nuclei segmentation of csPWS microscopy images. We leveraged the structural, physical, and biological differences between the cytoplasm, nucleus, and nuclear periphery to construct three distinct csPWS feature images for nucleus segmentation. Using these images of HCT116 cells, csPWS-seg achieved superior performance with a median Intersection over Union (IoU) of 0.80 and a Dice Similarity Coefficient (DSC) score of 0.88. The csPWS-seg overcame the segmentation performance over the baseline U-Net model and another attention-based model, SE-U-Net, marking a significant improvement in segmentation accuracy. Further, we analyzed the performance of our proposed model with four loss functions: binary cross-entropy loss, focal loss, dice loss, and Jaccard loss. The csPWS-seg with focal loss provided the best results compared to other loss functions. The automatic and accurate nuclei segmentation offered by the csPWS-seg not only automates, accelerates, and streamlines csPWS data analysis but also enhances the reliability of subsequent chromatin analysis research, paving the way for more accurate diagnostics, treatment, and understanding of cellular mechanisms for carcinogenesis.

bioengineering↗

bioRxiv2023

Active Transcription and Epigenetic Reactions Synergistically RegulateMeso-Scale Genomic Organization

In interphase nuclei, chromatin is organized into interspersed dense domains with characteristic sizes, both in the nuclear interior and periphery. However, the quantitative impact of transcription and histone modifications on the size and distribution of these domains remains unclear. Here, we introduce a mesoscale theoretical model that investigates the relationship between heterochromatic domain sizes and loop extrusion rates from these domains. The model considers chromatin-chromatin and chromatin-lamina interactions, methylation and acetylation kinetics, and diffusion of epigenetic marks and nucleoplasm. Our model generates testable predictions that help reveal the biophysics underlying chromatin organization in the presence of transcription-driven loop extrusion. This process is kinetically captured through the conversion of heterochromatin to euchromatin in response to RNAPII activity. We discovered that a balance between diffusive and reactive fluxes governs the steady-state sizes of heterochromatin domains. Using theory and simulations, we predicted that a loss of transcription results in increased chromatin compaction and larger heterochromatin domain sizes. To validate our predictions, we employed complementary super-resolution and nano-imaging techniques on five different cell lines with impaired transcription. We quantitatively assessed how domain sizes scale with loop extrusion rates at the hetero-euchromatin interfaces. Our analysis of previously obtained super-resolution images of nuclei revealed that excessive loop extrusion leads to smaller heterochromatin domains. The model successfully recapitulated these observations, explaining how transcription loss can counteract the effects of cohesin overloading. As the general biophysical mechanisms regulating heterochromatin domain sizes are independent of cell type, our findings have significant implications for understanding the role of transcription in global genome organization.

biophysics↗

bioRxiv2020

Nanoscale Chromatin Imaging and Analysis (nano-ChIA) platform bridges 4-D chromatin organization with molecular function

In eukaryotic cells, chromatin structure is linked to transcription processes through the regulation of genome organization. Extending across multiple length-scales - from the nucleosome to higher-order three-dimensional structures - chromatin is a dynamic system which evolves throughout the lifetime of a cell. However, no individual technique can fully elucidate the behavior of chromatin organization and its relation to molecular function at all length- and timescales at both a single-cell and a cell population level. Herein, we present a multi-technique nanoscale Chromatin Imaging and Analysis (nano-ChIA) platform that bridges electron tomography and optical superresolution imaging of chromatin conformation and transcriptional processes, with resolution down to the level of individual nucleosomes, with high-throughput, label-free analysis of chromatin packing and its dynamics in live cells. Utilizing nano-ChIA, we observed that chromatin is localized into spatially separable packing domains, with an average diameter of around 200 nm, sub-Mb genomic size, and an internal fractal structure. The chromatin packing behavior of these domains is directly influenced by active gene transcription. Furthermore, we demonstrated that the chromatin packing domain structure is correlated among progenitor cells and all their progeny, indicating that the organization of chromatin into fractal packing domains is heritable across cell division. Further studies employing the nano-ChIA platform have the potential to provide a more coherent picture of chromatin structure and its relation to molecular function.

genomics↗