Biology subjects

Prasad, J.

Publications and source records attributed to Prasad, J..

10 recordsLinked to original sources

bioRxiv2026

Characterizing nascent readthrough transcripts in human cells

Termination of transcription by RNA polymerase II (RNAPII) is critical to appropriately define transcriptome and proteome identity; yet mechanisms of termination regulation are incompletely understood. Current models suggest critical roles for the exonuclease XRN2, which is posited to "torpedo" out RNAPII after degrading uncapped and RNAPII-tethered nascent transcripts and posit an allosteric model wherein elongating RNAPII loses its processivity downstream of the transcription end site (TES) via unknown mechanisms. Here, we used nascent RNA Bru-seq to interrogate transcription termination across 16 human cell lines of distinct lineages, as part of the ENCODE 4 project, to identify key regulatory modes. We find that > 75% of protein-coding genes engage in readthrough transcription under homeostatic conditions. Exposing human cells to oxidative stress or hyperosmotic conditions or splicing inhibitors cause an increase in readthrough transcripts globally. Using an auxin-inducible degradation approach we find that depletion of BRD4, MED14 or XRN2 increases the extent and pervasiveness of readthrough transcripts while depletion of SUPT16H results in shorter readthrough transcripts. Our study provides a comprehensive view of homeostatic readthrough transcripts in human cells and delineates key components regulating transcription termination.

molecular biology↗

bioRxiv2025

Analysing a Reported Experiment That May Demonstrate the Interplay of Fluid Velocity and Pore Pressure in Bone Adaptation

Current models propose that osteogenesis occurs in regions of high mechanical stimuli such as strain, fluid velocity, or pore pressure. However, in vivo experiments on mouse tibiae under cantilever loading revealed new bone formation exclusively on the anterolateral side, despite the opposite posteromedial surface experiencing comparable magnitudes of these stimuli. This indicates that individual stimulus magnitude is insufficient and suggests an interactive mechanism among them. To investigate this, a poroelastic finite element model was developed to quantify the combined effects of load-induced fluid velocity and pore pressure. Tensile loading generated negative pore pressure, stretching osteocyte processes, while compressive loading produced positive pore pressure, compressing them. Since fluid flow exerts drag forces that also stretch osteocytes, the combined effect of flow and negative pressure on the tensile side was hypothesized to enhance mechanotransduction and trigger osteogenesis. Four potential stimuli were evaluated: dissipation energy density arising from (i) pore pressure, (ii) fluid velocity, (iii) their non-interactive sum, and (iv) their interaction. Comparison with in vivo data showed that only the interactive dissipation energy density accurately predicted both the spatial pattern and rate of new bone formation under high, low, and rest-inserted loading regimes. These results establish that the interaction between fluid velocity and pore pressure, rather than their independent contributions, governs load-induced osteogenesis. The proposed framework advances the mechanistic understanding of bone adaptation and offers a predictive basis for optimizing mechanical and clinical interventions to promote bone formation and mitigate bone loss.

bioengineering↗

bioRxiv2025

A Mathematical Model to Predict Instantaneous Bone Formation Rate from Temporal Data of Cellular Biomarkers

Although several models have been proposed to predict spatial patterns of new bone formation across different regions of a bone, to our knowledge no model has predicted bone formation temporally from cellular biomarkers. In this article, we predict bone formation rate (BFR) temporally from Col1a1 gene expression data and compare our predictions with the average BFR reported in the literature. The proposed mathematical model identifies key parameters influencing BFR at the celluar level and quantifies how biomarkers encode mechanical loading information. This model serves as an excellent starting point to understand how BFR changes over time relative to a given regimen of exogenous loading. We report that the simplest mathematical model explaining this phenonmenon with reasonable accuracy is a second order linear critically-damped system with a delay time. Since BFR reported in the literature typically represents an average value over the interlabel period, we also propose a method to convert this measure into an instantaneous one, which is essential for constructing an "ideal" mathematical model. Finally, we present our results and discuss limitations of the model along with directions for future improvement.

bioengineering↗

bioRxiv2025

Derivation of a Time-Dependent Model for Long-Term Cortical Bone Adaptation

This work attempts to derive long-term, time-dependent cortical bone adaptation to mechanical loading. Linear control theory is used to model the adaptation process, with the stimulus defined in terms of dissipation energy density. The newly adapted area is expressed as a function of the stimulus in the form of a differential equation, which is analyzed to obtain closed-form solutions. The study explores different possibilities, such as varying the order of differential equations (including fractional order) and examining different types of responses, e.g., critically damped and overdamped. Such model diversity will help identify the most appropriate formulation that fits experimental data.

bioengineering↗

bioRxiv2025

Pathogenic strains of a gut commensal drive systemic platelet activation and thromboinflammation in lupus nephritis

Imbalances in the gut microbiome have been linked to increased intestinal permeability and disease flares in systemic lupus erythematosus (SLE). Our study revealed that patients with flares of lupus nephritis (LN) and intestinal expansions of the anaerobic commensal, Ruminococcus gnavus (RG), displayed whole blood transcriptome profiles indicative of platelet, neutrophil, and myeloid cell activation, a profile reminiscent of sepsis. Serum analysis confirmed elevated serum levels of Platelet Factor 4 and neutrophil extracellular traps, which significantly correlated with levels of IgG-antibody to a novel lipoglycan (LG) produced by pathogenic RG strains, which was also documented in an independent LN cohort. To test for causality, in vivo mouse models further demonstrated that gut colonization with LG-producing RG strains, as well as a single intraperitoneal challenge with an LG preparation, caused platelet activation and megakaryocytosis in bone marrow and spleen. Mice colonized with RG strains that produce LG developed cellular infiltration of the kidneys by neutrophils and monocytes. Hence, RG expansions during renal flares may identify a specific LN flare endotype driven by thromboinflammatory mechanisms. Antibodies that arise from immune exposure to the RG lipoglycan may serve as a surrogate biomarker, helping to elucidate the impact of the relationship between gut microbiota communities and clinical outcomes in patients afflicted by LN. [208] Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=164 SRC="FIGDIR/small/641288v1_ufig1.gif" ALT="Figure 1"> View larger version (74K): org.highwire.dtl.DTLVardef@1239f8eorg.highwire.dtl.DTLVardef@1c062caorg.highwire.dtl.DTLVardef@195ece2org.highwire.dtl.DTLVardef@1f3123f_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2023

Predicting Cortical Bone Resorption in Disuse Condition Caused by Transient Muscle Paralysis

Load removal from the load-bearing bone, such as in the case of extended space travel and prolonged bed rest, harms bone health and leads to severe bone loss. However, the constitutive idea relating the quantity of bone loss to the absence of physiological loading is poorly understood. This work attempts to develop a mathematical model that predicts cortical bone loss at three sections: distal, mid-section, and proximal along the length of a mouse tibia. Load-induced interstitial fluid flow-based dissipation energy density has been adopted as a stimulus to trigger mechanotransduction. The developed model takes the loss of stimulus due to the disuse of bone as an input and predicts the quantity of bone loss with spatial accuracy. We hypothesized that the bone loss site would be the site of maximum stimulus loss due to disuse. To test the hypothesis, we calculated stimulus loss, i.e., loss of dissipation energy density due to bone disuse, based on the poroelastic analysis of the bone using a finite element method. A novel mathematical model has been then developed that successfully relates this loss of stimulus to the in-vivo bone loss data in the literature. According to the developed model, the site-specific mineral rate is found to be proportional to the square root of the loss of dissipation energy density. To the authors best knowledge, this model is the first of its kind to compute site-specific bone loss. The developed model can be extended to predict bone loss due to other disuse conditions such as long space travel, prolonged bed rest, etc.

bioengineering↗

bioRxiv2023

Relating strain amplitude, strain threshold and bone formation rate to exogenous forcing frequency

The literature supports the existence of a strain threshold, above which cortical bone adapts to exogenous mechanical loading by forming new bone. This strain threshold, however, varies with loading conditions, locations, waveforms, frequency etc. and there is a need to mathematically express the strain threshold in terms of these parameters. There have been several parametric, mathematical or numerical models in the literature for the cortical bones adaptation to mechanical loading, which may be already fitting some of the experimental data; however, they may not be easily and confidently derived from the first principles. To fill the gap, this work has attempted to derive the corresponding bone formation rate (BFR) rather from the first principles, namely using the energy principles. The derived model has been compared to the existing parametric models and validated with respect to the diverse experimental data available in the literature. The developed model is able to not only predict the BFR, but also helps to understand the nature and possible mathematical form of the strain threshold for cortical bones adaptation to mechanical loading.

bioengineering↗

bioRxiv2023

Derivation, Validation, and Prediction of Loading-Induced Mineral Apposition Rates at Endocortical and Periosteal Bone Surfaces Based on Fluid Velocity and Pore Pressure

Bones adapt to mechanical forces driven by osteocytes in the lacunae canalicular network (LCN). Osteocytes sense signals such as strain, interstitial fluid flow, and pore pressure. Physiological tissue strain is insufficient to induce bone formation, and fluid flow-based models struggle to predict bone formation at both the periosteal and endocortical surfaces, simultaneously. This prompted the exploration of pore pressures role. The study introduces dissipation energy density as a more significant stimulus, combining various LCN parameters, including the waveforms of both fluid velocity and pore pressure and the number of loading cycles. A pivotal achievement is the mathematical derivation of the Mineral Apposition Rate (MAR), linked proportionally to the square root of the dissipation energy density minus its reference value. This hypothesis is subjected to testing/ validation for both endocortical and periosteal surfaces for an in-vivo study on mouse tibia available in the literature. Computational implementation of this mathematical model adopts a poroelastic finite element analysis approach, treating bone as a porous fluid-filled entity. Crucially, assumptions underpinning the model, such as the impermeability of the periosteum to fluid and the maintenance of a reference zero pressure at the endosteal surface, are corroborated by relevant experimental studies. As a bottom line, the resulting model is the first of its kind, as it has been able to predict MAR at both endocortical and periosteal surfaces, significantly advancing our understanding of cortical bone adaptation to exogenous mechanical loading.

bioengineering↗

bioRxiv2018

Diversification of retinoblastoma protein function associated with cis and trans adaptations

Retinoblastoma proteins are eukaryotic transcriptional co-repressors that play central roles in cell cycle control, among other functions. Although most metazoan genomes encode a single retinoblastoma protein, gene duplications have occurred at least twice: in the vertebrate lineage, leading to three genes encoding Rb, p107, and p130, while separately in the Drosophila lineage an ancestral Rbf1 gene and a derived Rbf2 gene. Structurally, Rbf1 resembles p107 and p130 most closely, and mutation of the gene is lethal, while Rbf2 is more divergent, and is not essential for development. Rbf1 has been demonstrated to be a potent repressor of canonical cell-cycle promoters, unlike Rbf2. The retention of Rbf2 over 60 million years in the entire Drosophila lineage points to essential functions, however. We show here that Rbf2 regulates a broad set of cell growth control related genes, and can antagonize Rbf1 on specific sets of promoters. Rbf2 null mutants exhibit abnormal development of the female reproductive tract, with reduced egg laying, while heterozygous null mutants exhibit an increased rate of egg deposition, suggesting that the normal function of this protein is critical for optimal control of fertility. The structural alterations found in conserved regions of the Rbf2 gene suggest that this gene was sub- or neofunctionalized to develop specific regulatory specificity and activity. We define cis regulatory features of Rbf2 target genes that allow preferential repression by this protein, indicating that it is not merely a weaker version of the ancestral protein. The specialization of retinoblastoma function in Drosophila may reflect a parallel evolution found in vertebrates, and raises the possibility that cell growth control is equally important to cell cycle function for this conserved family of transcriptional corepressors.

developmental biology↗

bioRxiv2018

Finding the difference between periosteal and endocortical bone adaptation by using Artificial Neural Networks

In silico models of bone adaptation successfully simulated in vivo periosteal bone apposition, however, there are instances where these models may have limited success in predicting the new bone formation at endocortical surface. In vivo studies have highlighted that cortical bone surfaces may have differences in their modeling or remodeling responses to mechanical loading. However, the principle which the two cortical surfaces follow in bone adaptation is not very clear. This work accordingly attempts to understand how periosteal and endocortical surfaces accommodate loading-induced new bone formation. A neural network model is used to serve the purpose. A relationship is established to compute new bone thickness as a function of mechanical parameters (normal and shear strains) and non-mechanical parameters (distances from the neutral axis and the centroid) at the two surfaces. Analytical results indicate that two cortical surfaces behave opposite to each other in order to achieve optimal distribution of newly formed bone. The outcomes may be useful in establishing a unifying principle to predict site-specific new bone formation.

bioengineering↗