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Abstract MotivationStochastic gene expression and cell-to-cell heterogeneity have attracted increased interest in recent years, enabled by advances in single-cell measurement technologies. These studies are also increasingly complemented by quantitative biophysical modeling, often using the framework of stochastic biochemical kinetic models. However, inferring parameters for such models (i.e., the kinetic rates of biochemical reactions) remains a technical and computational challenge, particularly doing so in a manner that can leverage high-throughput single-cell sequencing data. ResultsIn this work, we develop a chemical master equation model reference library-based computational pipeline to infer kinetic parameters describing noisy mRNA distributions from single-cell RNA sequencing data, using the commonly applied stochastic telegraph model. The approach fits kinetic parameters via steady-state distributions, as measured across a population of cells in snapshot data. Our pipeline also serves as a tool for comprehensive analysis of parameter identifiability, in both a priori (studying model properties in the absence of data) and a posteriori (in the context of a particular dataset) use-cases. The pipeline can perform both of these tasks, i.e. inference and identifiability analysis, in an efficient and scalable manner, and also serves to disentangle contributions to uncertainty in inferred parameters from experimental noise versus structural properties of the model. We found that for the telegraph model, the majority of the parameter space is not practically identifiable from single-cell RNA sequencing data, and low experimental capture rates worsen the identifiability. Our methodological framework could be extended to other data types in the fitting of small biochemical network models. Availability and implementationAll code relevant to this work is available at https://github.com/Read-Lab-UCI/TelegraphLikelihoodInfer, archival DOI: https://doi.org/10.5281/zenodo.16915450. 

Abstract The 3D organization of the genome—in particular, which two regions of DNA are in contact with each other—plays a role in regulating gene expression. Several factors influence genome 3D organization. Nucleosomes (where ∼100 base pairs of DNA wrap around histone proteins) bend, twist, and compactify chromosomal DNA, altering its polymer mechanics. How much does the positioning of nucleosomes between gene loci influence contacts between those gene loci? And to what extent are polymer mechanics responsible for this? To address this question, we combine a stochastic polymer mechanics model of chromosomal DNA including twists and wrapping induced by nucleosomes with two data-driven pipelines. The first estimates nucleosome positioning from ATAC-seq data in regions of high accessibility. Most of the genome is low accessibility, so we combine this with a novel image analysis method that estimates the distribution of nucleosome spacing from electron microscopy data. There are no fit parameters in the biophysical model. We apply this method to IL-6, IL-15, CXCL9, and CXCL10, inflammatory marker genes in macrophages, before and after inflammatory stimulation, and compare the predictions with contacts measured by conformation capture experiments (4C-seq). We find that within a 500-kb genomic region, polymer mechanics with nucleosomes can explain 71% of close contacts. These results suggest that, while genome contacts on 100 kb scales are multifactorial, they may be amenable to mechanistic, physical explanation. Our work also highlights the role of nucleosomes, not just at the loci of interest, but between them, and not just the total number of nucleosomes, but their specific placement. The method generalizes to other genes, and can be used to address whether a contact is under active regulation by the cell (e.g. a macrophage during inflammatory stimulation). 

Innate immune cells are responsible for eliminating foreign infectious agents and cellular debris, and their ability to perceive, respond to, and integrate biochemical and mechanical cues from their microenvironment eventually determines their behavior. In response to tissue injury, pathogen invasion, or a biomaterial implant, immune cells activate many pathways to initiate inflammation in the tissue. In addition to common inflammatory pathways, studies have demonstrated the role of the mechanosensitive proteins and transcriptional coactivators YAP and TAZ (YAP/TAZ) in inflammation and immunity. We review our knowledge of YAP/TAZ in controlling inflammation and immunity in innate immune cells. Furthermore, we discuss the roles of YAP/TAZ in inflammatory diseases, wound healing, and tissue regeneration and how they integrate mechanical cues with biochemical signaling during disease progression. Last, we comment on possible approaches that can be exploited to harness the therapeutic potential of YAP/TAZ in inflammatory diseases. 

We investigate how matrix stiffness regulates chromatin reorganization and cell reprogramming and find that matrix stiffness acts as a biphasic regulator of epigenetic state and fibroblast-to-neuron conversion efficiency, maximized at an intermediate stiffness of 20 kPa. ATAC sequencing analysis shows the same trend of chromatin accessibility to neuronal genes at these stiffness levels. Concurrently, we observe peak levels of histone acetylation and histone acetyltransferase (HAT) activity in the nucleus on 20 kPa matrices, and inhibiting HAT activity abolishes matrix stiffness effects. G-actin and cofilin, the cotransporters shuttling HAT into the nucleus, rises with decreasing matrix stiffness; however, reduced importin-9 on soft matrices limits nuclear transport. These two factors result in a biphasic regulation of HAT transport into nucleus, which is directly demonstrated on matrices with dynamically tunable stiffness. Our findings unravel a mechanism of the mechano-epigenetic regulation that is valuable for cell engineering in disease modeling and regenerative medicine applications. 

DNA methylation occurs predominantly on cytosine-phosphate-guanine (CpG) dinucleotides in the mammalian genome, and the methylation landscape is maintained over mitotic cell division. It has been posited that coupling of maintenance methylation activity among neighbouring CpGs is critical to stability over cellular generations; however, the mechanism is unclear. We used mathematical models and stochastic simulation to analyse data from experiments that probe genome-wide methylation of nascent DNA post-replication in cells. We find that DNA methylation maintenance rates on individual CpGs are locally correlated, and the degree of this correlation varies by genomic regional context. By using theory of protein diffusion along DNA, we show that exponential decay of methylation rate correlation with genomic distance is consistent with enzyme processivity. Our results provide quantitative evidence of genome-wide methyltransferase processivity in vivo . We further developed a method to disentangle different mechanistic sources of kinetic correlations. From the experimental data, we estimate that an individual methyltransferase methylates neighbour CpGs processively if they are 36 basepairs apart, on average. But other mechanisms of coupling dominate for longer inter-CpG distances. Our study demonstrates that quantitative insights into enzymatic mechanisms can be obtained from replication-associated, cell-based genome-wide measurements, by combining data-driven statistical analyses with hypothesis-driven mathematical modelling. 

Macrophages are innate immune cells that help wounds heal. Here, we study the potential immunomodulatory effects of negative-pressure wound therapy (NPWT) materials on the macrophage inflammatory response. We compared the effects of two materials, Granufoam™ (GF) and Veraflo Cleanse™ (VC), on macrophage function in vitro. We find that both materials cause reduced expression of inflammatory genes, such as TNF and IL1B, in human macrophages stimulated with bacterial lipopolysaccharide (LPS) and interferon-gamma (IFNγ). Relative to adherent glass control surfaces, VC discourages macrophage adhesion and spreading, and may potentially sequester LPS/IFNγ and cytokines that the cells produce. GF, on the other hand, was less suppressive of inflammation, supported macrophage adhesion and spreading better than VC, and sequestered lesser quantities of LPS/IFNγ in comparison to VC. The control dressing material cotton gauze (CT) was also immunosuppressive, capable of TNF-α retention and LPS/IFNγ sequestration. Our findings suggest that NPWT material interactions with cells, as well as soluble factors including cytokines and LPS, can modulate the immune response, independent of vacuum application. We have also established methodological strategies for studying NPWT materials and reveal the potential utility of cell-based in vitro studies for elucidating biological effects of NPWT materials. 

Abstract Background Mutations in LMNA , encoding lamin A/C, lead to a variety of diseases known as laminopathies including dilated cardiomyopathy (DCM) and skeletal abnormalities. Though previous studies have investigated the dysregulation of gene expression in cells from patients with DCM, the role of epigenetic (gene regulatory) mechanisms, such as DNA methylation, has not been thoroughly investigated. Furthermore, the impact of family-specific LMNA mutations on DNA methylation is unknown. Here, we performed reduced representation bisulfite sequencing on ten pairs of fibroblasts and their induced pluripotent stem cell (iPSC) derivatives from two families with DCM due to distinct LMNA mutations, one of which also induces brachydactyly. Results Family-specific differentially methylated regions (DMRs) were identified by comparing the DNA methylation landscape of patient and control samples. Fibroblast DMRs were found to enrich for distal regulatory features and transcriptionally repressed chromatin and to associate with genes related to phenotypes found in tissues affected by laminopathies. These DMRs, in combination with transcriptome-wide expression data and lamina-associated domain (LAD) organization, revealed the presence of inter-family epimutation hotspots near differentially expressed genes, most of which were located outside LADs redistributed in LMNA -related DCM. Comparison of DMRs found in fibroblasts and iPSCs identified regions where epimutations were persistent across both cell types. Finally, a network of aberrantly methylated disease-associated genes revealed a potential molecular link between pathways involved in bone and heart development. Conclusions Our results identified both shared and mutation-specific laminopathy epimutation landscapes that were consistent with lamin A/C mutation-mediated epigenetic aberrancies that arose in somatic and early developmental cell stages.