Biology subjects

Steadman, C. R.

Publications and source records attributed to Steadman, C. R..

8 recordsLinked to original sources

bioRxiv2026

Resolving in vitro heterogeneity of host functional responses to HCoV-229E via single-cell analyses

Understanding host-pathogen interactions at the molecular level is essential to elucidating the mechanisms that govern immunity and pathogenesis. While diverse responses to viral infection have been documented, it remains unclear if this variability arises from the complex host milieu or represents an intrinsic property of the infection itself. To investigate this, we performed single-cell (sc) RNA sequencing analysis of infected MRC-5 fibroblast cells with human coronavirus 229E (HCoV-229E), which revealed pronounced variation in viral load across time points and biological replicates. While viral sequences were higher at 24 hours post-infection (hpi), more host genes were differentially expressed at 48 hpi, indicating dynamic responses during infection progression. Cells with higher viral load upregulated expression of unfolded protein response genes and NF-{kappa}B regulators, and downregulated expression of fibroblast identity and cell cycle genes, reflecting a shift toward a stress-adaptive, antiviral state. Network analyses identified NF-{kappa}B signaling as a central regulatory axis, with negative regulators overexpressed in high-viral-load clusters. Additionally, ATAC-seq analysis showed that regions of increased chromatin accessibility were enriched for NF-{kappa}B subunits, further supporting its role in transcriptional control. These findings demonstrate that even within ostensibly uniform cell cultures, viral infection induces distinct heterogeneous transcriptional and regulatory responses.

microbiology↗

bioRxiv2025

AI-Assisted Cryo-ET Workflow for 3D Visualization of Chromatin during Cellular Differentiation

Understanding how chromatin architecture changes during cellular differentiation requires structural methods that can resolve native genomic organization at high resolution. Here, we present an AI-assisted cryo-electron tomography (cryo-ET) and segmentation workflow to quantify chromatin compaction across various stages of motor neuron differentiation from induced pluripotent stem cells (iPSC). By directly imaging extracted and vitrified chromatin, we preserve native structure and avoid artifacts from heavy metal staining and resin embedding. Using three-dimensional (3D) density analysis, we measure chromatin density and capture the progressive increase in chromatin compaction with lineage commitment. This is then correlated with population-averaged Hi-C experiments, observing consistency between the microscale higher order structure of chromatin and global contact patterns. Our approach enables direct visualization of chromatin organization under near-physiological conditions, bridging the gap between structural imaging and genome-wide contact mapping. This platform therefore establishes an AI-assisted experimental framework for linking chromatin architecture to regulatory mechanisms during differentiation.

genomics↗

bioRxiv2025

From 2D to 4D: a Containerized Workflow and Browser to Explore Dynamic Chromatin Architecture

BackgroundCharacterizing the physical organization of the genome is essential for understanding long-range gene reg- ulation, chromatin compartmentalization, and epigenetic accessibility. Hi-C experiments generate two- dimensional (2D) genome-wide contact maps of chromatin interactions by capturing the spatial proximity between genomic loci, which reveal interaction frequencies but lack the spatial resolution needed to interpret the three-dimensional (3D) genome structure(s). Emerging evidence suggests that epigenetic regulation is closely linked to 3D genome architecture, and that structural changes over time (4D) drive key biological pro- cesses in development, disease, and environmental response. Thus, integrating 3D structure with functional data is critical for a more complete understanding of genome regulation. Previous work, most notably the 4DHiC chromosome modeling framework, has shown that physical multi-dimensional modeling approaches rooted in polymer physics and molecular dynamics can resolve these structures at biologically meaningful resolutions by integrating temporal Hi-C data with physical constraints to uncover dynamic chromosome reorganization. Thus, molecular dynamics simulations, constrained by Hi-C contact matrices, can resolve fine-scale structural changes and reveal functionally significant transitions in chromatin conformation. ResultsHerein, we present the 4D Genome Browser Workflow (4DGBWorkflow) and the 4D Genome Browser (4DGB). The algorithm is based on the 4DHiC method and the containerized tool is an end-to-end workflow that can transform, filter, and view 4D epigenomics and chromatin datasets, allowing non-specialists to apply three-dimensional modeling principles to diverse datasets and experimental conditions. The software executes on a laptop running macOS, Linux or Windows. From input Hi-C files (.hic), the 4DGBWorkflow produces 3D reconstructions of chromosomes, integrates the reconstruction with track data (e.g., epigenetic marks, transcriptome profiles), and provides comparative visualization of the results in a single workflow. ConclusionsThe 4DGBWorkflow and 4D Genome Browser are open-source tools for comparative analysis and visual- ization of 4D chromosome datasets, including chromatin architecture and epigenomic signals. Automatic integration of Hi-C data with molecular dynamics democratizes the construction of time resolved 3D genome structures, simplifying complex simulations and data integration schemes.

bioinformatics↗

bioRxiv2024

PERCEPTIVE: an R Shiny pipeline for the prediction of epigenetic modulators in novel species

Epigenetic processes play key roles in regulating gene expression, genome stability, and metabolic output in organisms across the tree of life. Yet, the role epigenetics plays in regulating genomes and behaviors remains underdeveloped for microalgae, particularly as new species are identified and characterized. This is likely due to the cumbersome nature and species-dependent attributes of epigenetic wet-lab methodologies, which preclude the rapid identification of epigenetic modifications and modulators. However, there is extraordinary conservation of epigenetic processes from budding yeast to humans; in many cases, one may infer how behavior and function are epigenetically regulated in novel species by simply identifying epigenetic modulators, or the proteins responsible for conferring epigenetic modifications. To this end, we have developed a graphical software package, titled PERCEPTIVE (pipeline for the prediction of epigenetic modulators in novel species). This novel platform solely uses the genomic sequence of an organism, and preexisting information from model species, to predict the epigenetic modulators and associated modifications in a novel species. Predictions are presented to the user in a graphical interface, which provides literature-based interpretation of results, enabling users to quickly understand potential epigenetic processes in their species of interest and plan follow-up experiments. To test PERCEPTIVE, we predicted epigenetic modulators in several feedstock candidate algae species. To validate these predictions, wet-lab studies were performed, including mass spectrometry; these results underscore the high accuracy of PERCEPTIVE predictions. Overall, PERCEPTIVE represents a powerful tool for the research and manipulation of algal species, which does not require a priori knowledge of epigenetics and is accessible to a broad set of investigators.

genomics↗

bioRxiv2024

Statistical relationships across epigenomes using large-scale hierarchical clustering

Environmental toxins and pathogens can influence epigenetic modifications on chromosomes, thereby leaving trace evidence of exposures. However, the avalanche of epigenomic data is difficult to parse for biological interpretation given non-linear complex patterns and relationships. This attractive challenge in epigenomic data lends itself to machine learning for discerning infectivity and susceptibility. In this study, we explore over 3,000 epigenomes of uninfected individuals and provide a comprehensive characterization of the relationships among epigenetic modifiers, their modifiers, and specific immune cell types across all chromosomes using hierarchical clustering.

genetics↗

bioRxiv2024

Epigenomic manipulation reveals the relationship between locus specific chromatin dynamics and gene expression

Dysregulation of epigenetic processes leads to a plethora of abnormalities including disease states such as cancer. Therapies focused on epigenetic modulation alter gene expression to correct dysfunction, though the mechanisms and perpetuation of these states is unknown. Here, we use integrated epigenomics and three-dimensional chromatin structure-function analyses after acute histone deacetylase inhibitor cancer drug treatment (suberoylanilide hydroxamic acid in lung cancer cells). Treatment induced substantial (13%) genomic rearrangement that rebounds despite persistent gene expression changes and spreading of acetylation. The chromatin functional landscape (accessibility, active transcription modification, and gene expression) is controlled and locus-specific, while chromatin contacts are globally altered resulting in a moderate weakening of topologically associating domains. Chromatin states are more dynamic at transcriptionally active loci while genes with reduced expression are epigenetically stable suggesting chromatin architectural turnover and nucleosome remodeling is locus-specific and underlies the bidirectional expression changes. Thus, local 3D chromatin and genome structural dynamics is integral for loci regulation in response to epigenomic perturbation. The partial persistence of these altered features may have larger implications for efficacy of epigenetic drugs in amelioration of disease states.

cancer biology↗

bioRxiv2023

Vaccinia virus infection induces concurrent alterations in host chromatin architecture, accessibility, and gene expression

Genomic DNA folds into complex configurations that produce particular local and global structures thought to profoundly impact genome function. To understand the dynamic nature of this relationship, we investigated the extent of host chromatin structural and functional changes in response to a viral agent. We performed comprehensive assessments of host architecture (Hi-C), accessibility (ATAC-seq), and gene expression (RNA-seq) in a paired manner in response to attenuated vaccinia (smallpox) virus. Over time, infection significantly increased long-range intra-chromosomal interactions and decreased chromatin accessibility. Fine-scale accessibility changes were independent of broad-scale chromatin compartment exchange, which increased (up to 12% of the genome) over time, underscoring potential independent mechanisms for global and local chromatin reorganization. The majority of differentially expressed genes, including those downregulated in immune responses, had concurrent alterations in local accessibility and loop domain restructuring. Increased B compartmentalization, intra-chromosomal interactions, and decreased inter-chromosomal interactions and chromatin accessibility together indicate that infection converts the host genome into a more condensed state with nearly equal bidirectional differential gene expression. These changes in host chromatin features may have implications for developing efficacious anti-viral countermeasures. Overall, our empirical data provides evidence of orchestrated concurrent alterations in chromatin architecture, accessibility, and gene expression in response to infection, further reinforcing the notion of coordinated structure-function dynamics of the genome.

genomics↗

bioRxiv2023

Improved Quality Metrics for Association and Reproducibility in Chromatin Accessibility Data Using Mutual Information

BackgroundCorrelation metrics are widely utilized in genomics analysis and often implemented with little regard to assumptions of normality, homoscedasticity, and independence of values. This is especially true when comparing values between replicated sequencing experiments that probe chromatin accessibility, such as assays for transposase-accessible chromatin via sequencing (ATAC-seq). Such data can possess several regions across the human genome with little to no sequencing depth and are thus non-normal with a large portion of zero values. Despite distributed use in the epigenomics field, few studies have evaluated and benchmarked how correlation and association statistics behave across ATAC-seq experiments with known differences or the effects of removing specific outliers from the data. Here, we developed a computational simulation of ATAC-seq data to elucidate the behavior of correlation statistics and to compare their accuracy under set conditions of reproducibility. ResultsUsing these simulations, we monitored the behavior of several correlation statistics, including the Pearsons R and Spearmans{rho} coefficients as well as Kendalls{tau} and Top-Down correlation. We also test the behavior of association measures, including the coefficient of determination R2, Kendalls W, and normalized mutual information. Our experiments reveal an insensitivity of most statistics, including Spearmans{rho} , Kendalls{tau} , and Kendalls W, to increasing differences between simulated ATAC-seq replicates. The removal of co-zeros (regions lacking mapped sequenced reads) between simulated experiments greatly improves the estimates of correlation and association. After removing co-zeros, the R2 coefficient and normalized mutual information display the best performance, having a closer one-to-one relationship with the known portion of shared, enhanced loci between simulated replicates. When comparing values between experimental ATAC-seq data using a random forest model, mutual information best predicts ATAC-seq replicate relationships. ConclusionsCollectively, this study demonstrates how measures of correlation and association can behave in epigenomics experiments. We provide improved strategies for quantifying relationships in these increasingly prevalent and important chromatin accessibility assays.

bioinformatics↗