1,720,992 research outputs found
Quantitative modelling in stem cell biology and beyond: how to make best use of it
No full textPurpose of review: this article gives a broad overview of quantitative modelling approaches in biology and provides guidance on how to employ them to boost stem cell research, by helping to answer biological questions and to predict the outcome of biological processes.Recent findings: the twenty-first century has seen a steady increase in the proportion of cell biology publications employing mathematical modelling to aid experimental research. However, quantitative modelling is often used as a rather decorative element to confirm experimental findings, an approach which often yields only marginal added value, and is in many cases scientifically questionable.Summary: quantitative modelling can boost biological research in manifold ways, but one has to take some careful considerations before embarking on a modelling campaign, in order to maximise its added value, to avoid pitfalls that may lead to wrong results, and to be aware of its fundamental limitations, imposed by the risks of over-fitting and “universality”
Cooperative SIR dynamics as a model for spontaneous blood clot initiation
No full textBlood clotting is an important physiological process to suppress bleeding upon injury, but when it occurs inadvertently, it can cause thrombosis, which can lead to life threatening conditions. Hence, understanding the microscopic mechanistic factors for inadvertent, spontaneous blood clotting, in absence of a vessel breach, can help in predicting and averting such conditions. Here, we present a minimal model – reminiscent of the SIR model – for the initiating stage of spontaneous blood clotting, the collective activation of blood platelets. This model predicts that in the presence of very small initial activation signals, collective activation of the platelet population is possible, but requires a sufficient degree of heterogeneity of platelet sensitivity. To propagate the activation signal and achieve collective activation of the bulk platelet population, it requires the presence of, possibly only few, hyper-sensitive platelets, but also a sufficient proportion of platelets with intermediate, yet higher than-average sensitivity. A comparison with experimental results demonstrates a qualitative agreement for high platelet signalling activity
Emergent order in epithelial sheets by interplay of cell divisions and cell fate regulation
No full textThe fate choices of stem cells between self-renewal and differentiation are often tightly regulated by juxtacrine (cell-cell contact) signalling. Here, we assess how the interplay between cell division, cell fate choices, and juxtacrine signalling can affect the macroscopic ordering of cell types in self-renewing epithelial sheets, by studying a simple spatial cell fate model with cells being arranged on a 2D lattice. We show in this model that ifcells commit to their fate directly upon cell division, macroscopic patches of cells of the same type emerge, if at least a small proportion of divisions are symmetric, except if signalling interactions are laterally inhibiting. In contrast, if cells are first 'licensed' to differentiate, yet retaining the possibility to return to their naive state, macroscopic order only emerges if the signalling strength exceeds a critical threshold: if then the signalling interactions are laterally inducing, macroscopic patches emerge as well. Lateral inhibition, on the other hand, can in that case generate periodic patterns of alternating cell types (checkerboard pattern), yet only if the proportion of symmetric divisions is sufficiently low. These results can be understood theoretically by an analogy to phase transitions in spin systems known from statistical physics
Boundary-induced orientation of dynamic filament networks and vesicle agglomerations
No full textWe find a statistical mechanism that can adjust orientations of intracellular filaments to cell geometry inthe absence of organizing centers. The effect is based on random and isotropic filament (de-)polymerizationdynamics and is independent of filament interactions and explicit regulation. It can be understood by an analogyto electrostatics and appears to be induced by the confining boundaries; for periodic boundary conditions, noorientational bias emerges. Including active transport of particles, the model reproduces experimental observationsof vesicle accumulations in transected axons
Disordered driven lattice gases with boundary reservoirs and Langmuir kinetics
No full textThe asymmetric simple exclusion process with additional Langmuir kinetics, i.e., attachment and detachment in the bulk, is a paradigmatic model for intracellular transport. Here we study this model in the presence of randomly distributed inhomogeneities ("defects"). Using Monte Carlo simulations, we find a multitude of coexisting high- and low-density domains. The results are generic for one-dimensional driven diffusive systems with short-range interactions and can be understood in terms of a local extremal principle for the current profile. This principle is used to determine current profiles and phase diagrams as well as statistical properties of ensembles of defect samples
Mathematical modelling of clonal stem cell dynamics
No full textStudying cell fate dynamics is complicated by the fact that direct in vivo observation of individual cell fate outcomes is usually not possible and only multicellular data of cell clones can be obtained. In this situation, experimental data alone is not sufficient to validate biological models because the hypotheses and the data cannot be directly compared and thus standard statistical tests cannot be leveraged. On the other hand, mathematical modelling can bridge the scales between a hypothesis and measured data via quantitative predictions from a mathematical model. Here, we describe how to implement the rules behind a hypothesis (cell fate outcomes) one-to-one as a stochastic model, how to evaluate such a rule-based model mathematically via analytical calculation or stochastic simulations of the model's Master equation, and to predict the outcomes of clonal statistics for respective hypotheses. We also illustrate two approaches to compare these predictions directly with the clonal data to assess the models.</p
Homeostatic regulation of renewing tissue cell populations via crowding control: stability, robustness and quasi-dedifferentiation
No full textTo maintain renewing epithelial tissues in a healthy, homeostatic state, cell divisions and differentiation need to be tightly regulated. Mechanisms of homeostatic regulation often rely on crowding feedback control: cells are able to sense the cell density in their environment, via various molecular and mechanosensing pathways, and respond by adjusting division, differentiation, and cell state transitions appropriately. Here, we determine, via a mathematically rigorous framework, which general conditions for the crowding feedback regulation (i) must be minimally met, and (ii) are sufficient, to allow the maintenance of homeostasis in renewing tissues. We show that those conditions naturally allow for a degree of robustness toward disruption of regulation. Furthermore, intrinsic to this feedback regulation is that stem cell identity is established collectively by the cell population, not by individual cells, which implies the possibility of ‘quasi-dedifferentiation’, in which cells committed to differentiation may reacquire stem cell properties upon depletion of the stem cell pool. These findings can guide future experimental campaigns to identify specific crowding feedback mechanisms.</p
Extreme value statistics of mutation accumulation in renewing cell populations
Full text linkThe emergence of a predominant phenotype within a cell population is often triggered by the chance accumulation of a sequence of rare genomic DNA mutations within a single cell. For example, tumors may be initiated by a single cell in which multiple mutations cooperate to bypass their natural defense mechanism. The risk of such an event is thus determined by the extremal accumulation of mutations across tissue cells. To address this risk, here we study the statistics of the maximum mutation numbers in a generic, but tested, model of a renewing cell population. By drawing an analogy between the genealogy of a cell population and the theory of branching random walks, we obtain analytical estimates for the probability of exceeding a threshold number of mutations to trigger a proliferative advantage of a cell over its neighbors, and determine how the statistical distribution of maximum mutation numbers scales with age and cell population size
Dynamic heterogeneity as a strategy of stem cell self-renewal.
Full text linkTo maintain cycling adult tissue in homeostasis the balance between proliferation and differentiation of stem cells needs to be precisely regulated. To investigate how stem cells achieve perfect self-renewal, emphasis has been placed on models in which stem cells progress sequentially through a one-way proliferative hierarchy. However, investigations of tissue regeneration have revealed a surprising degree of flexibility, with cells normally committed to differentiation able to recover stem cell competence following injury. Here, we investigate whether the reversible transfer of cells between states poised for proliferation or differentiation may provide a viable mechanism for a heterogeneous stem cell population to maintain homeostasis even under normal physiological conditions. By addressing the clonal dynamics, we show that such models of "dynamic heterogeneity" may be equally capable of describing the results of recent lineage tracing assays involving epithelial tissues. Moreover, together with competition for limited niche access, such models may provide a mechanism to render tissue homeostasis robust. In particular, in 2D epithelial layers, we show that the mechanism of dynamic heterogeneity avoids some pathological dependencies that undermine models based on a hierarchical stem/progenitor organization
Self-renewal without niche instruction, feedback or fine-tuning
No full textTo self-renew, stem cells must precisely balance proliferation and differentiation. Typically, this is achieved under feedback from the niche; yet many stem cells also possess an intrinsic self-renewal program that allows them to do so autonomously, as required. However, because self-renewal implies a stable equilibrium -- in which the expected stem cell number neither increases nor decreases over time -- this seems to require fine-tuning to a critical point. Here, we show that this is not the case: self-renewal can, in principle, be easily achieved without the need for extrinsic instruction, feedback or fine-tuning, by a simple 'dimerization cycle' that uses partitioning errors at cell division to reliably establish asymmetric divisions and perfectly balance symmetric divisions
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