Biology subjects

Crampin, E. J.

Publications and source records attributed to Crampin, E. J..

9 recordsLinked to original sources

bioRxiv2026

A general thermodynamic approach for model reduction of enzyme cycles and electrogenic transporters

Mathematical models of enzyme cycles form the basis of quantifying key features of metabolism and membrane transport. These models are often integrated into more comprehensive models such as whole-cell models to understand emergent behaviours between interacting components. However, it is currently computationally infeasible to simulate the full dynamical behaviour of every enzyme at a network scale. Model reduction is frequently used to improve computational efficiency, but in general, these approaches do not preserve physical and thermodynamic consistency. Here, we outline a general method for simplifying enzyme kinetics models while retaining mass, charge and energy balance. We base our approach on the bond graph, which is a general methodology for modelling biological systems from fundamental physical laws. This approach ensures that key physical constraints are enforced in every model, regardless of their complexity. Our thermodynamic model reduction framework is readily extended to electrogenic transporters through the coupling of chemical and electrical processes. Through the application of our approach to both hypothetical enzyme cycles and real data from the Na+/K+ ATPase, we show that it can rapidly screen for plausible network structures in circumstances where enzyme catalytic mechanisms may not be fully characterised, facilitating biological discovery and drug development.

systems biology↗

bioRxiv2024

TRPV4 is expressed by enteric glia and muscularis macrophages of the colon but does not play a prominent role in colonic motility

BackgroundMechanosensation is an important trigger of physiological processes in the gastrointestinal tract. Aberrant responses to mechanical input are associated with digestive disorders, including visceral hypersensitivity. Transient Receptor Potential Vanilloid 4 (TRPV4) is a mechanosensory ion channel with proposed roles in visceral afferent signaling, intestinal inflammation, and gut motility. While TRPV4 is a potential therapeutic target for digestive disease, current mechanistic understanding of how TRPV4 may influence gut function is limited by inconsistent reports of TRPV4 expression and distribution. MethodsIn this study we profiled functional expression of TRPV4 using Ca2+ imaging of wholemount preparations of the mouse, monkey, and human intestine in combination with immunofluorescent labeling for established cellular markers. The involvement of TRPV4 in colonic motility was assessed in vitro using videomapping and contraction assays. ResultsThe TRPV4 agonist GSK1016790A evoked Ca2+ signaling in muscularis macrophages, enteric glia, and endothelial cells. TRPV4 specificity was confirmed using TRPV4 KO mouse tissue or antagonist pre-treatment. Calcium responses were not detected in other cell types required for neuromuscular signaling including enteric neurons, interstitial cells of Cajal, PDGFR+ cells, and intestinal smooth muscle. TRPV4 activation led to rapid Ca2+ responses by a subpopulation of glial cells, followed by sustained Ca2+ signaling throughout the enteric glial network. Propagation of these waves was suppressed by inhibition of gap junctions or Ca2+ release from intracellular stores. Coordinated glial signaling in response to GSK1016790A was also disrupted in acute TNBS colitis. The involvement of TRPV4 in the initiation and propagation of colonic motility patterns was examined in vitro. ConclusionsWe reveal a previously unappreciated role for TRPV4 in the initiation of distension-evoked colonic motility. These observations provide new insights into the functional role of TRPV4 activation in the gut, with important implications for how TRPV4 may influence critical processes including inflammatory signaling and motility. SummaryO_LITRPV4 is expressed by equivalent cell types in the rodent and primate (monkey and human) colon. This mechanosensitive ion channel has proposed roles in inflammation, visceral afferent signaling, and colonic motility. C_LIO_LINew analysis methods were developed to examine cellular communication in the enteric glial network. This approach revealed new insights into inflammation-associated changes in glial connectivity. C_LIO_LINew roles for TRPV4 in transduction of distension-evoked responses in the colon and colonic motility were identified. C_LI Key findingsWe have defined the cell types that functionally express TRPV4 in the gut wall. These include enteric glia, endothelia of blood and lymphatic vessels, mMac, and extrinsic afferent nerves. TRPV4- dependent Ca2+ signaling was not detected in enteric neurons, PDGFR cells, interstitial cells of Cajal and smooth muscle cells, which are important drivers of gut motility. These observations align with our experimental evidence for limited involvement of TRPV4 in neuromuscular transmission and propagating colonic motility. New and NoteworthyO_LINovel cellular sites of functional TRPV4 expression in the GI tract were identified and compared across multiple vertebrate species. New analytical approaches to characterize enteric glial communication in a spatiotemporal manner were developed. C_LIO_LIA supporting role for TRPV4 in the initiation of propagating colonic contractions in response to distension was demonstrated. Potential mechanisms that contribute to TRPV4-mediated effects on GI function were identified. C_LIO_LITRPV4-dependent activity in enteric glia is enhanced in inflammation, consistent with current evidence for inflammation-associated sensitization of TRPV4 on visceral afferents and a major role in mechanically evoked nociceptive signaling. C_LIO_LIPair correlation analysis was used to examine spatial connectivity of Ca2+ signaling, enabling demonstration of dysregulated glial communication in acute inflammation. C_LI

physiology↗

bioRxiv2021

Spatial-temporal analysis of nanoparticles in live tumor spheroids impacted by cell origin and density

Nanoparticles hold great preclinical promise in cancer therapy but continue to suffer attrition through clinical trials. Advanced, three dimensional (3D) cellular models such as tumor spheroids can recapitulate elements of the tumor environment and are considered the superior model to evaluate nanoparticle designs. However, there is an important need to better understand nanoparticle penetration kinetics and determine how different cell characteristics may influence this nanoparticle uptake. A key challenge with current approaches for measuring nanoparticle accumulation in spheroids is that they are often static, losing spatial and temporal information which may be necessary for effective nanoparticle evaluation in 3D cell models. To overcome this challenge, we developed an analysis platform, termed the Determination of Nanoparticle Uptake in Tumor Spheroids (DONUTS), which retains spatial and temporal information during quantification, enabling evaluation of nanoparticle uptake in 3D tumor spheroids. Outperforming linear profiling methods, DONUTS was able to measure silica nanoparticle uptake to 10 {micro}m accuracy in both isotropic and irregularly shaped cancer cell spheroids. This was then extended to determine penetration kinetics, first by a forward-in-time, center-in-space model, and then by mathematical modelling, which enabled the direct evaluation of nanoparticle penetration kinetics in different spheroid models. Nanoparticle uptake was shown to inversely relate to particle size and varied depending on the cell type, cell stiffness and density of the spheroid model. The automated analysis method we have developed can be applied to live spheroids in situ, for the advanced evaluation of nanoparticles as delivery agents in cancer therapy.

bioengineering↗

bioRxiv2021

Analysing and simulating energy-based models in biology using BondGraphTools

Like all physical systems, biological systems are constrained by the laws of physics. However, mathematical models of biochemistry frequently neglect the conservation of energy, leading to unrealistic behaviour. Energy-based models that are consistent with conservation of mass, charge and energy have the potential to aid the understanding of complex interactions between biological components, and are becoming easier to develop with recent advances in experimental measurements and databases. In this paper, we motivate the use of bond graphs (a modelling tool from engineering) for energy-based modelling and introduce, BondGraphTools, a Python library for constructing and analysing bond graph models. We use examples from biochemistry to illustrate how BondGraphTools can be used to automate model construction in systems biology while maintaining consistency with the laws of physics.

systems biology↗

bioRxiv2021

Hierarchical semantic composition of biosimulation models using bond graphs

Simulating complex biological and physiological systems and predicting their behaviours under different conditions remains challenging. Breaking systems into smaller and more manageable modules can address this challenge, assisting both model development and simulation. Nevertheless, existing computational models in biology and physiology are often not modular and therefore difficult to assemble into larger models. Even when this is possible, the resulting model may not be useful due to inconsistencies either with the laws of physics or the physiological behaviour of the system. Here, we propose a general methodology for composing models, combining the energy-based bond graph approach with semantics-based annotations. This approach improves model composition and ensures that a composite model is physically plausible. As an example, we demonstrate this approach to automated model composition using a model of human arterial circulation. The major benefit is that modellers can spend more time on understanding the behaviour of complex biological and physiological systems and less time wrangling with model composition. Author summaryBiological and physiological systems usually involve multiple underlying processes, mechanisms, structures, and phenomena, referred to here as sub-systems. Modelling the whole system every time from scratch requires a huge amount of effort. An alternative is to model each sub-system in a modular fashion, i.e., containing meaningful interfaces for connecting to other modules. Such modules are readily combined to produce a whole-system model. For the combined model to be consistent, modules must be described using the same modelling scheme. One way to achieve this is to use energy-based models that are consistent with the conservation laws of physics. Here, we present an approach that achieves this using bond graphs, which allows modules to be combined faster and more efficiently. First, physically plausible modules are generated using a small number of template modules. Then a meaningful interface is added to each module to automate connection. This approach is illustrated by applying this method to an existing model of the circulatory system and verifying the results against the reference model.

bioengineering↗

bioRxiv2020

Ca2+ release via IP3Rs increases RyR mediated Ca2+ spark frequency in ventricular cardiomyocytes without altering spark amplitude and duration

Calcium (Ca2+) plays a critical role in the excitation contraction coupling (ECC) process that governs the contraction of cardiomyocytes during each heartbeat. While ryanodine receptors (RyRs) are the primary Ca2+ channels responsible for mediating cell-wide Ca2+ transients during ECC, Ca2+ release via inositol 1,4,5-trisphosphate (IP3) receptors (IP3Rs) have been reported to elicit ECC-modulating effects. Recent studies suggest that the proximal localization of IP3Rs at dyads grants their ability to modify the occurrence of Ca2+ sparks (elementary Ca2+ release events that constitute ECC-associated Ca2+ transients) which may underlie the modulatory effects on ECC. Here, we aim to uncover the mechanism by which IP3Rs affect Ca2+ spark dynamics. To this end, we developed a mathematical model of the dyad that incorporates IP3Rs to reveal their impact on local Ca2+ handling and corresponding Ca2+ spark formation. Consistent with published experimental data, our model predicts that the propensity for Ca2+ spark formation increases with IP3R activity. Our simulations support the hypothesis that IP3R activity elevates Ca2+ within the dyad, sensitizing proximal RyRs for future release. However, this lowers Ca2+ in the JSR available for release and thus results in Ca2+ sparks with the same duration but lower amplitudes.

biophysics↗

bioRxiv2019

Isolating the sources of heterogeneity in nanoparticle-cell interactions

Nanoparticles have the potential to enhance therapeutic success and reduce toxicity-based treatment side effects via the targeted delivery of drugs to cells. This delivery relies on complex interactions between numerous biological, chemical and physical processes. The intertwined nature of these processes has thus far hindered attempts to understand their individual impact. Variation in experimental data, such as the number of nanoparticles inside each cell, further inhibits understanding. Here we present a mathematical framework that is capable of examining the impact of individual processes during nanoparticle delivery. We demonstrate that variation in experimental nanoparticle uptake data can be explained by three factors: random nanoparticle motion; variation in nanoparticle-cell interactions; and variation in the maximum nanoparticle uptake per cell. Without all three factors, the experimental data cannot be explained. This work provides insight into biological mecha-nisms that cause heterogeneous responses to treatment, and enables precise identification of treatment-resistant cell subpopulations.

biophysics↗

bioRxiv2018

Insights on the impact of mitochondrial organisation on bioenergetics in high-resolution computational models of cardiac cell architecture

Recent electron microscopy data have revealed that cardiac mitochondria are not arranged in crystalline columns, but are organised with several mitochondria aggregated into columns of varying sizes often spanning the cell cross-section. This raises the question - how does the mitochondrial arrangement affect the metabolite distributions within cardiomyocytes and their impact on force dynamics? Here we employed finite element modelling of cardiac bioenergetics, using computational meshes derived from electron microscope images, to address this question. Our results indicate that heterogeneous mitochondrial distributions can lead to significant spatial variation across the cell in concentrations of inorganic phosphate, creatine (Cr) and creatine phosphate (PCr). However, our model predicts that sufficient activity of the creatine kinase (CK) system, coupled with rapid diffusion of Cr and PCr, maintains near uniform ATP and ADP ratios across the cell cross sections. This homogenous distribution of ATP and ADP should also evenly distribute force production and twitch duration with contraction. These results suggest that the PCr shuttle, and associated enzymatic reactions, act to maintain uniform force dynamics in the cell despite the heterogeneous mitochondrial organization. However, our model also predicts that under hypoxia - activity of mitochondrial CK enzyme and diffusion of high-energy phosphate compounds may be insufficient to sustain uniform ATP/ADP distribution and hence force generation.

systems biology↗

bioRxiv2017

Post-Transcriptional Control Of EMT Is Coordinated Through Combinatorial Targeting By Multiple microRNAs

Epithelial-mesenchymal transition (EMT) is a process whereby cells undergo reversible phenotypic change, losing epithelial characteristics and acquiring mesenchymal attributes. While EMT underlies normal, physiological programs in embryonic tissue development and adult wound healing, it also contributes to cancer progression by facilitating metastasis and altering drug sensitivity. Using a cell model of EMT (human mammary epithelial (HMLE) cells), we show that miRNAs act as an additional regulatory layer over and above the activity of the transcription factors with which they are closely associated. In this context, miRNAs serve to both enhance expression changes for genes with EMT function, whilst simultaneously reducing transcriptional noise in non-EMT genes. We find that members of the polycistronic miR-200c~141 and miR-183~182 clusters (which are decreased during HMLE cell EMT and are associated with epithelial gene expression in breast cancer patients) co-regulate common targets and pathways to enforce an epithelial phenotype. We demonstrate their combinatorial effects are apparent much closer to endogenous expression levels (and orders of magnitude lower than used in most studies). Importantly, the low levels of combinatorial miRNAs that are required to exert biological function ameliorate the \"off-target\" effects on gene expression that are a characteristic of supra-physiologic miRNA manipulation. We argue that high levels of over-expression characteristic of many miRNA functional studies have led to an over-estimation of the effect of many miRNAs in EMT regulation, with over 130 individual miRNAs directly implicated as drivers of EMT. We propose that the functional effects of co-regulated miRNAs that we demonstrate here more-accurately reflects the endogenous post-transcriptional regulation of pathways, networks and processes, and illustrates that the post-transcriptional miRNA regulatory network is fundamentally cooperative.

molecular biology↗