Biology subjects

Guin, K.

Publications and source records attributed to Guin, K..

4 recordsLinked to original sources

bioRxiv2025

Orderly mitosis shapes interphase genome organization

Genomes assume a complex 3D architecture in the interphase cell nucleus. Yet the molecular mechanisms that determine global genome architecture are only poorly understood. To identify mechanisms of higher order genome organization, we performed high-throughput imaging-based CRISPR knockout screens targeting 1064 genes encoding nuclear proteins in multiple human cell lines. We assessed changes in the distribution of centromeres at single cell resolution as surrogate markers for global genome organization. The screens revealed multiple major regulators of spatial distribution of centromeres including components of the nucleolus, kinetochore, cohesins, condensins, and the nuclear pore complex. Alterations in centromere distribution required progression through the cell cycle and acute depletion of mitotic factors with distinct functions altered centromere distribution in the subsequent interphase. These results identify molecular determinants of spatial centromere organization, and they show that orderly progression through mitosis shapes interphase genome architecture.

cell biology↗

bioRxiv2025

Simulation and quantitative analysis of spatial centromere distributionpatterns

A prominent feature of eukaryotic chromosomes are centromeres, which are specialized regions of repetitive DNA required for faithful chromosome segregation during cell division. In interphase cells centromeres are non-randomly positioned in the three-dimensional space of the nucleus in a cell-type specific manner. The functional relevance and the cellular mechanisms underlying this observation are unknown, and quantitative methods to measure distribution patterns of centromeres in 3D space are needed. Here we have developed an analytical framework that combines robust clustering metrics and advanced modeling techniques for the quantitative analysis of centromere distributions at the single cell level. To identify a robust quantitative measure for centromere clustering, we benchmarked six metrics for their ability to sensitively detect changes in centromere distribution patterns from high-throughput imaging data of human cells, both under normal conditions and upon experimental perturbation of centromere distribution. We find that Ripleys K Score has the highest accuracy with minimal sensitivity to variations in centromeres number, making it the most suitable metric for measuring centromere distributions. As a complementary approach, we also developed and validated spatial models to replicate centromere distribution patterns, and we show that a radially shifted Gaussian distribution best represents the centromere patterns seen in human cells. Our approach creates tools for the quantitative characterization of spatial centromere distributions with applications in both targeted studies of centromere organization as well as in unbiased screening approaches.

genomics↗

bioRxiv2023

HiTIPS: High-Throughput Image Processing Software for the Study of Nuclear Architecture and Gene Expression

High-throughput imaging (HTI) generates complex imaging datasets from a large number of experimental perturbations. Commercial HTI software for image analysis workflows does not allow full customization and adoption of new image processing algorithms in the analysis modules. While open-source HTI analysis platforms provide individual modules in the workflow, like nuclei segmentation, spot detection, or cell tracking, they are often limited in integrating novel analysis modules or algorithms. Here, we introduce the High-Throughput Image Processing Software (HiTIPS) to expand the range and customization of existing HTI analysis capabilities. HiTIPS incorporates advanced image processing and machine learning algorithms for automated cell and nuclei segmentation, spot signal detection, nucleus tracking, spot tracking, and quantification of spot signal intensity. Furthermore, HiTIPS features a graphical user interface that is open to integration of new algorithms for existing analysis pipelines and to adding new analysis pipelines through separate plugins. To demonstrate the utility of HiTIPS, we present three examples of image analysis workflows for high-throughput DNA FISH, immunofluorescence (IF), and live-cell imaging of transcription in single cells. Altogether, we demonstrate that HiTIPS is a user-friendly, flexible, and open-source HTI analysis platform for a variety of cell biology applications.

bioinformatics↗

bioRxiv2020

Spatial proximity of homologous centromere DNA sequences facilitated karyotype diversity and seeding of evolutionary new centromeres

Centromeres of Candida albicans form on unique and different DNA sequences but a closely related species, Candida tropicalis, possesses homogenized inverted repeat (HIR)-associated centromeres. To investigate the mechanism of centromere-type transition, we improved the fragmented genome assembly and constructed a chromosome-level genome assembly of C. tropicalis by employing PacBio sequencing, chromosome conformation capture sequencing (3C-seq), chromoblot, and genetic analysis of engineered aneuploid strains. Further, we analyzed the 3D genome organization using 3C-seq data, which revealed spatial proximity among the centromeres as well as telomeres of seven chromosomes in C. tropicalis. Intriguingly, we observed evidence of inter-centromeric translocations in the common ancestor of C. albicans and C. tropicalis. Identification of putative centromeres in closely related Candida sojae, Candida viswanathii and Candida parapsilosis indicates loss of ancestral HIR-associated centromeres and establishment of evolutionary new centromeres (ENCs) in C. albicans. We propose that spatial proximity of the homologous centromere DNA sequences facilitated karyotype rearrangements and centromere type transitions in human pathogenic yeasts of the CUG-Ser1 clade.

genetics↗