1. |
- Scott, Jacob G, et al.
(författare)
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A filter-flow perspective of haematogenous metastasis offers a non-genetic paradigm for personalised cancer therapy
- 2014
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Ingår i: European Journal of Cancer. - : Elsevier BV. - 0959-8049. ; 50:17, s. 3068-3075
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Tidskriftsartikel (refereegranskat)abstract
- Research into mechanisms of haematogenous metastasis has largely become genetic in focus, attempting to understand the molecular basis of ‘seed–soil’ relationships. Preceding this biological mechanism is the physical process of dissemination of circulating tumour cells (CTCs) in the circulation. Patterns of metastatic spread have been previously quantified using the metastatic efficiency index, a measure quantifying metastatic incidence for a given primary-target organ pair and the relative blood flow between them. We extend this concept to take into account the reduction in CTCs which occurs in organ capillary beds connected by a realistic vascular network topology. Application to a dataset of metastatic incidence reveals that metastatic patterns depend strongly on assumptions about the existence and location of micrometastatic disease which governs CTC dynamics on the network, something which has heretofore not been considered – an oversight which precludes our ability to predict metastatic patterns in individual patients.
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2. |
- Anderson, Alexander, et al.
(författare)
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Evolution, regulation and disruption of homeostasis and its role in carcinogenesis
- 2010
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Ingår i: Multiscale Cancer Modeling. - : CRC Press. - 9781439814406 ; , s. 1-30
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Homeostasis is a critical property of living beings that involves the ability to self-regulate in response to changes in the environment in order to maintain a certain dynamic balance aecting form and/or function. Homeostasis is of particular importance in multicellular organisms, where it is intertwined with development [2,3]. Organisms have evolved intricate control mechanisms that ensure developmental processes achieve their end points and stabilize (e.g., dierentiate) as well as allow for a degree of adaptability to a range of conditions (e.g., stress or damage induced by wounding). is allows for the emergence of a more robust system that can tolerate both external and internal perturbations [4]. However, there are limitations to this tolerance, and oen it is the rare events that cause the most disruption [5]; think of the extinction of dinosaurs for an example. From an evolutionary point of view, this is a viable trade-o between the energetic cost of homeostasis versus the tness benet it would provide. In practical terms, homeostasis of living multicellular organisms is constrained in terms of the amount of disruption they can cope with and in terms of the amount of time they will remain homeostatic.
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3. |
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4. |
- Bengmark, Samuel, 1965, et al.
(författare)
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Combining engineering and teacher education – ideas and experiences from Chalmers University of Technology
- 2021
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Ingår i: Bidrag från 8:e Utvecklingskonferensen för Sveriges ingenjörsutbildningar. - 9789178672714
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Konferensbidrag (refereegranskat)abstract
- In response to the lack of STEM teachers in Sweden, Chalmers University of Technology offers a double degree program in engineering and education. This article investigates which ideas behind the program’s design have been of particular value in implementing the program and their added value. The five main ideas are: involve skilled schoolteachers called master teachers in the education, having many entrances to the program but only one exit, using interviews as part of the admission process, using a competency model to ensure coherence in the education, focusing on concrete work skills at the beginning of the education and later move on to theory and further development. We invite other universities to consider double degree programs in engineering and education and be inspired by these five ideas in their implementation.
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5. |
- Bernhardsson, Sebastian, et al.
(författare)
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Structural correlations in bacterial metabolic networks
- 2011
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Ingår i: BMC Evolutionary Biology. - : Springer Science and Business Media LLC. - 1471-2148. ; 11:20
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Tidskriftsartikel (refereegranskat)abstract
- Background Evolution of metabolism occurs through the acquisition and loss of genes whose products acts as enzymes in metabolic reactions, and from a presumably simple primordial metabolism the organisms living today have evolved complex and highly variable metabolisms. We have studied this phenomenon by comparing the metabolic networks of 134 bacterial species with known phylogenetic relationships, and by studying a neutral model of metabolic network evolution. Results We consider the 'union-network' of 134 bacterial metabolisms, and also the union of two smaller subsets of closely related species. Each reaction-node is tagged with the number of organisms it belongs to, which we denote organism degree (OD), a key concept in our study. Network analysis shows that common reactions are found at the centre of the network and that the average OD decreases as we move to the periphery. Nodes of the same OD are also more likely to be connected to each other compared to a random OD relabelling based on their occurrence in the real data. This trend persists up to a distance of around five reactions. A simple growth model of metabolic networks is used to investigate the biochemical constraints put on metabolic-network evolution. Despite this seemingly drastic simplification, a 'union-network' of a collection of unrelated model networks, free of any selective pressure, still exhibit similar structural features as their bacterial counterpart. Conclusions The OD distribution quantifies topological properties of the evolutionary history of bacterial metabolic networks, and lends additional support to the importance of horizontal gene transfer during bacterial metabolic evolution where new reactions are attached at the periphery of the network. The neutral model of metabolic network growth can reproduce the main features of real networks, but we observe that the real networks contain a smaller common core, while they are more similar at the periphery of the network. This suggests that natural selection and biochemical correlations can act both to diversify and to narrow down metabolic evolution.
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6. |
- Borgqvist, Johannes, 1990, et al.
(författare)
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Cell polarisation in a bulk-surface model can be driven by both classic and non-classic Turing instability
- 2021
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Ingår i: Npj Systems Biology and Applications. - : Springer Science and Business Media LLC. - 2056-7189. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- The GTPase Cdc42 is the master regulator of eukaryotic cell polarisation. During this process, the active form of Cdc42 is accumulated at a particular site on the cell membrane called the pole. It is believed that the accumulation of the active Cdc42 resulting in a pole is driven by a combination of activation-inactivation reactions and diffusion. It has been proposed using mathematical modelling that this is the result of diffusion-driven instability, originally proposed by Alan Turing. In this study, we developed, analysed and validated a 3D bulk-surface model of the dynamics of Cdc42. We show that the model can undergo both classic and non-classic Turing instability by deriving necessary conditions for which this occurs and conclude that the non-classic case can be viewed as a limit case of the classic case of diffusion-driven instability. Using three-dimensional Spatio-temporal simulation we predicted pole size and time to polarisation, suggesting that cell polarisation is mainly driven by the reaction strength parameter and that the size of the pole is determined by the relative diffusion.
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7. |
- Borgqvist, Johannes, 1990, et al.
(författare)
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Turing pattern formation on the sphere is robust to the removal of a hole
- 2024
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Ingår i: JOURNAL OF MATHEMATICAL BIOLOGY. - : Springer Science+Business Media B.V.. - 0303-6812 .- 1432-1416. ; 88:2
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Tidskriftsartikel (refereegranskat)abstract
- The formation of buds on the cell membrane of budding yeast cells is thought to be driven by reactions and diffusion involving the protein Cdc42. These processes can be described by a coupled system of partial differential equations known as the Schnakenberg system. The Schnakenberg system is known to exhibit diffusion-driven pattern formation, thus providing a mechanism for bud formation. However, it is not known how the accumulation of bud scars on the cell membrane affect the ability of the Schnakenberg system to form patterns. We have approached this problem by modelling a bud scar on the cell membrane with a hole on the sphere. We have studied how the spectrum of the Laplace-Beltrami operator, which determines the resulting pattern, is affected by the size of the hole, and by numerically solving the Schnakenberg system on a sphere with a hole using the finite element method. Both theoretical predictions and numerical solutions show that pattern formation is robust to the introduction of a bud scar of considerable size, which lends credence to the hypothesis that bud formation is driven by diffusion-driven instability.
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8. |
- Gerlee, Philip, 1980, et al.
(författare)
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Autocrine signaling can explain the emergence of Allee effects in cancer cell populations
- 2022
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Ingår i: Plos Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 18:3
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Tidskriftsartikel (refereegranskat)abstract
- In many human cancers, the rate of cell growth depends crucially on the size of the tumour cell population. Low, zero, or negative growth at low population densities is known as the Allee effect; this effect has been studied extensively in ecology, but so far lacks a good explanation in the cancer setting. Here, we formulate and analyze an individual-based model of cancer, in which cell division rates are increased by the local concentration of an autocrine growth factor produced by the cancer cells themselves. We show, analytically and by simulation, that autocrine signaling suffices to cause both strong and weak Allee effects. Whether low cell densities lead to negative (strong effect) or reduced (weak effect) growth rate depends directly on the ratio of cell death to proliferation, and indirectly on cellular dispersal. Our model is consistent with experimental observations from three patient-derived brain tumor cell lines grown at different densities. We propose that further studying and quantifying population-wide feedback, impacting cell growth, will be central for advancing our understanding of cancer dynamics and treatment, potentially exploiting Allee effects for therapy.
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9. |
- Gerlee, Philip, 1980, et al.
(författare)
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Bridging scales in cancer progression: Mapping genotype to phenotype using neural networks
- 2015
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Ingår i: Seminars in Cancer Biology. - : Elsevier BV. - 1096-3650 .- 1044-579X. ; 30, s. 30-41
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Tidskriftsartikel (refereegranskat)abstract
- In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions.
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10. |
- Gerlee, Philip, 1980, et al.
(författare)
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Complexity and stability in growing cancer cell populations
- 2015
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 112:21
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Evolutionary game theory (EGT) describes dynamics in populations in which individual fitness can change because of the interactions with others, called frequency-dependent selection (1). Interactions are driven by differences in phenotype. EGT has been proposed as a framework for evolutionary dynamics of tumors (2). An underlying assumption is that different cancer cell types within a tumor engage in different heritable behavior; thus, frequency-dependent selection acts. Until now there has been little direct empirical evidence for this. The study by Archetti et al. (3) demonstrates frequency-dependent growth rates of two phenotypically distinct cancer subclones. One clone produced the insulin-like growth factor (IGF)-II, the other did not. In a mix of producers and nonproducers, the growth rates of both clones varied with the frequency of producers. Because a similar effect was shown when varying the concentration of serum, the production of IGF-II could be viewed as a public goods game.
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11. |
- Gerlee, Philip, 1980, et al.
(författare)
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Computational models predicting the early development of the COVID-19 pandemic in Sweden: systematic review, data synthesis, and secondary validation of accuracy
- 2022
-
Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Computational models for predicting the early course of the COVID-19 pandemic played a central role in policy-making at regional and national levels. We performed a systematic review, data synthesis, and secondary validation of studies that reported on prediction models addressing the early stages of the COVID-19 pandemic in Sweden. A literature search in January 2021 based on the search triangle model identified 1672 peer-reviewed articles, preprints and reports. After applying inclusion criteria 52 studies remained out of which 12 passed a Risk of Bias Opinion Tool. When comparing model predictions with actual outcomes only 4 studies exhibited an acceptable forecast (mean absolute percentage error, MAPE < 20%). Models that predicted disease incidence could not be assessed due to the lack of reliable data during 2020. Drawing conclusions about the accuracy of the models with acceptable methodological quality was challenging because some models were published before the time period for the prediction, while other models were published during the prediction period or even afterwards. We conclude that the forecasting models involving Sweden developed during the early stages of the COVID-19 pandemic in 2020 had limited accuracy. The knowledge attained in this study can be used to improve the preparedness for coming pandemics.
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12. |
- Gerlee, Philip, 1980
(författare)
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Derivation of a Generalised Replicator Equation in the Limit of Weak Selection
- 2023
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Ingår i: Springer Proceedings in Mathematics and Statistics. - 2194-1009 .- 2194-1017. ; 429, s. 249-260
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Konferensbidrag (refereegranskat)abstract
- The replicator equation is often applied for describing the change in frequency of competing subpopulations, but has only been formally derived under strong limitations on the dynamics of the total population size. We show that a generalised replicator equation can be derived from a wide class of population dynamical models that allow for a factorisation into density-dependent and frequency-dependent birth and death rates. The method relies on weak selection (i.e. small fitness differences) and the generalised replicator equation is obtained as the zeroth order approximation in a perturbation expansion. We apply our theoretical results to a specific model with linear frequency-dependence and logistic dynamics for the population size, and show that the error introduced by considering a zeroth order composite solution scales as the fitness difference.
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13. |
- Gerlee, Philip, 1980, et al.
(författare)
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Diffusion-limited tumour growth: Simulations and analysis.
- 2010
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Ingår i: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences (AIMS). - 1551-0018 .- 1547-1063. ; 7:2, s. 385-400
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Tidskriftsartikel (refereegranskat)abstract
- The morphology of solid tumours is known to be affected by the background oxygen concentration of the tissue in which the tumour grows, and both computational and experimental studies have suggested that branched tumour morphology in low oxygen concentration is caused by diffusion-limited growth. In this paper we present a simple hybrid cellular automaton model of solid tumour growth aimed at investigating this phenomenon. Simulation results show that for high consumption rates (or equivalently low oxygen concentrations) the tumours exhibit branched morphologies, but more importantly the simplicity of the model allows for an analytic approach to the problem. By applying a steady-state assumption we derive an approximate solution of the oxygen equation, which closely matches the simulation results. Further, we derive a dispersion relation which reveals that the average branch width in the tumour depends on the width of the active rim, and that a smaller active rim gives rise to thinner branches. Comparison between the prediction of the stability analysis and the results from the simulations shows good agreement between theory and simulation.
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14. |
- Gerlee, Philip, 1980, et al.
(författare)
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Effect of space in the game “war of attrition”
- 2012
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Ingår i: Physical Review E. - 1539-3755 .- 2470-0045 .- 2470-0053. ; 85:4
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Tidskriftsartikel (refereegranskat)abstract
- Spatial dynamics has in many cases been invoked as a mechanism that can promote the evolution of coexistence and cooperation, although the precise conditions for this to occur have not yet been characterised. In an effort to address this question we have analyzed an alternative version of the theoretical game “war of attrition,” which exhibits unusual behavior: The well-mixed system exhibits quasistationary coexistence and a relaxation time that scales exponentially with the system size, while the spatial system shows a relaxation time that is considerably smaller and scales with a power α≈1.4 of the system size. Further, the spatial system exhibits a first-order phase transition in the strategy distribution at a consolation prize of k≈1/3. Close to this point the relaxation time diverges with an exponent γ≈1.2. This analysis shows that the effect of space is highly dependent on the type of game considered.
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15. |
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16. |
- Gerlee, Philip, 1980, et al.
(författare)
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Evolving homeostatic tissue using genetic algorithms
- 2011
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Ingår i: Progress in Biophysics & Molecular Biology. - : Elsevier BV. - 0079-6107. ; 106:2, s. 414-425
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Tidskriftsartikel (refereegranskat)abstract
- Multicellular organisms maintain form and function through a multitude of homeostatic mechanisms. The details of these mechanisms are in many cases unknown, and so are their evolutionary origin and their link to development. In order to illuminate these issues we have investigated the evolution of structural homeostasis in the simplest of cases, a tissue formed by a mono-layer of cells. To this end, we made use of a 3-dimensional hybrid cellular automaton, an individual-based model in which the behaviour of each cell depends on its local environment. Using an evolutionary algorithm (EA) we evolved cell signalling networks, both with a fixed and an incremental fitness evaluation, which give rise to and maintain a mono-layer tissue structure. Analysis of the solutions provided by the EA shows that the two evaluation methods gives rise to different types of solutions to the problem of homeostasis. The fixed method leads to almost optimal solutions, where the tissue relies on a high rate of cell turnover, while the solutions from the incremental scheme behave in a more conservative manner, only dividing when necessary. In order to test the robustness of the solutions we subjected them to environmental stress, by wounding the tissue, and to genetic stress, by introducing mutations. The results show that the robustness very much depends on the mechanism responsible for maintaining homeostasis. The two evolved cell types analysed present contrasting mechanisms by which tissue homeostasis can be maintained. This compares well to different tissue types found in multicellular organisms. For example the epithelial cells lining the colon in humans are shed at a considerable rate, while in other tissue types, which are not as exposed, the conservative type of homeostatic mechanism is normally found. These results will hopefully shed light on how multicellular organisms have evolved homeostatic mechanisms and what might occur when these mechanisms fail, as in the case of cancer. (C) 2011 Published by Elsevier Ltd.
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17. |
- Gerlee, Philip, 1980, et al.
(författare)
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Extinction rates in tumour public goods games
- 2017
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Ingår i: Journal of the Royal Society Interface. - : The Royal Society. - 1742-5689 .- 1742-5662. ; 14:134
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Tidskriftsartikel (refereegranskat)abstract
- Cancer evolution and progression are shaped by cellular interactions and Darwinian selection. Evolutionary game theory incorporates both of these principles, and has been proposed as a framework to understand tumour cell population dynamics. A cornerstone of evolutionary dynamics is the replicator equation, which describes changes in the relative abundance of different cell types, and is able to predict evolutionary equilibria. Typically, the replicator equation focuses on differences in relative fitness. We here showthat this framework might not be sufficient under all circumstances, as it neglects important aspects of population growth. Standard replicator dynamics might miss critical differences in the time it takes to reach an equilibrium, as this time also depends on cellular turnover in growing but bounded populations. As the system reaches a stable manifold, the time to reach equilibrium depends on cellular death and birth rates. These rates shape the time scales, in particular, in coevolutionary dynamics of growth factor producers and free-riders. Replicator dynamics might be an appropriate framework only when birth and death rates are of similar magnitude. Otherwise, population growth effects cannot be neglected when predicting the time to reach an equilibrium, and cell-type-specific rates have to be accounted for explicitly.
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18. |
- Gerlee, Philip, 1980, et al.
(författare)
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Gene divergence and pathway duplication in the metabolic network of yeast and digital organisms
- 2009
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Ingår i: Journal of the Royal Society Interface. - : The Royal Society. - 1742-5689 .- 1742-5662. ; 6, s. 1233-1245
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Tidskriftsartikel (refereegranskat)abstract
- We have studied the metabolic gene–function network in yeast and digital organisms evolved in the artificial life platform Avida. The gene–function network is a bipartite network in which a link exists between a gene and a function (pathway) if that function depends on that gene, and can also be viewed as a decomposition of the more traditional functional gene networks, where two genes are linked if they share any function. We show that the gene–function network exhibits two distinct degree distributions: the gene degree distribution is scale-free while the pathway distribution is exponential. This is true for both yeast and digital organisms, which suggests that this is a general property of evolving systems, and we propose that the scale-free gene degree distribution is due to pathway duplication, i.e. the development of a new pathway where the original function is still retained. Pathway duplication would serve as preferential attachment for the genes, and the experiments with Avida revealed precisely this; genes involved in many pathways are more likely to increase their connectivity. Measuring the overlap between different pathways, in terms of the genes that constitute them, showed that pathway duplication also is a likely mechanism in yeast evolution. This analysis sheds new light on the evolution of genes and functionality, and suggests that function duplication could be an important mechanism in evolution.
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19. |
- Gerlee, Philip, 1980, et al.
(författare)
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Impact of anticipation in dynamical systems
- 2017
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Ingår i: Physical Review E. - 2470-0045 .- 2470-0053. ; 96:6
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Tidskriftsartikel (refereegranskat)abstract
- Many animals, including humans, have predictive capabilities and, presumably, base their behavioral decisions-at least partially-upon an anticipated state of their environment. We explore a minimal version of this idea in the context of particles that interact according to a pairwise potential. Anticipation enters the picture by calculating the interparticle forces from linear extrapolations of the particle positions some time tau in the future. Simulations show that for intermediate values of t, compared to a transient time scale defined by the potential and the initial conditions, the particles form rotating clusters in which the particles are arranged in a hexagonal pattern. Analysis of the system shows that anticipation induces energy dissipation and we show that the kinetic energy asymptotically decays as 1/t. Furthermore, we show that the angular momentum is not necessarily conserved for tau > 0, and that asymmetries in the initial condition therefore can cause rotational movement. These results suggest that anticipation could play an important role in collective behavior, since it may induce pattern formation and stabilizes the dynamics of the system.
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20. |
- Gerlee, Philip, 1980, et al.
(författare)
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Inferring rates of metastatic dissemination using stochastic network models
- 2019
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Ingår i: Plos Computational Biology. - : Public Library of Science (PLoS). - 1553-7358 .- 1553-734X. ; 15:4
-
Tidskriftsartikel (refereegranskat)abstract
- The formation of metastases is driven by the ability of cancer cells to disseminate from the site of the primary tumour to target organs. The process of dissemination is constrained by anatomical features such as the flow of blood and lymph in the circulatory system. We exploit this fact in a stochastic network model of metastasis formation, in which only anatomically feasible routes of dissemination are considered. By fitting this model to two different clinical datasets (tongue & ovarian cancer) we show that incidence data can be modelled using a small number of biologically meaningful parameters. The fitted models reveal site specific relative rates of dissemination and also allow for patient-specific predictions of metastatic involvement based on primary tumour location and stage. Applied to other data sets this type of model could yield insight about seed-soil effects, and could also be used in a clinical setting to provide personalised predictions about the extent of metastatic spread. Author summary For most cancer patients the occurrence of metastases equals incurable disease. Despite this fact our quantitative knowledge about the process of metastatic dissemination is limited. In this manuscript we improve on a previously published mathematical model by incorporating known biological facts about metastatic spread and also consider the temporal dimension of dissemination. The model is fit to two different cancer types with very different patterns of spread, which highlights the versatility of our framework. Properly parametrised this type of model can be used for making personalised predictions about metastatic burden.
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21. |
- Gerlee, Philip, 1980, et al.
(författare)
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Persistence of cooperation in diffusive public goods games
- 2019
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Ingår i: Physical Review E. - 2470-0045 .- 2470-0053. ; 99:6
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Tidskriftsartikel (refereegranskat)abstract
- Diffusive public goods (PG) games are difficult to analyze due to population assortment affecting growth rates of cooperators (producers) and free-riders. We study these growth rates using spectral decomposition of cellular densities and derive a finite cell-size correction of the growth rate advantage which exactly describes the dynamics of a randomly assorted population and approximates the dynamics under limited dispersal. The resulting effective benefit-to-cost ratio relates the physical parameters of PG dynamics to the persistence of cooperation, and our findings provide a powerful tool for the analysis of diffusive PG games, explaining commonly observed patterns of cooperation. © 2019 American Physical Society.
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22. |
- Gerlee, Philip, 1980, et al.
(författare)
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Predicting regional COVID-19 hospital admissions in Sweden using mobility data.
- 2021
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- The transmission of COVID-19 is dependent on social mixing, the basic rate of which varies with sociodemographic, cultural, and geographic factors. Alterations in social mixing and subsequent changes in transmission dynamics eventually affect hospital admissions. We employ these observations to model and predict regional hospital admissions in Sweden during the COVID-19 pandemic. We use an SEIR-model for each region in Sweden in which the social mixing is assumed to depend on mobility data from public transport utilisation and locations for mobile phone usage. The results show that the model could capture the timing of the first and beginning of the second wave of the pandemic 3weeks in advance without any additional assumptions about seasonality. Further, we show that for two major regions of Sweden, models with public transport data outperform models using mobile phone usage. We conclude that a model based on routinely collected mobility data makes it possible to predict future hospital admissions for COVID-19 3weeks in advance.
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23. |
- Gerlee, Philip, 1980, et al.
(författare)
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Productivity and diversity in a cross-feeding population of digital organisms
- 2010
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Ingår i: Evolution. - : Wiley. - 0014-3820 .- 1558-5646. ; 64:9, s. 2716-2730
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Tidskriftsartikel (refereegranskat)abstract
- Cross-feeding interactions are a common feature of many microbial systems, such as colonies of Escherichia coli grown on a single limiting resource, and microbial consortia cooperatively degrading complex compounds. We have studied this phenomenon from an abstract point of view by considering artificial organisms that metabolize binary strings from a shared environment. The organisms are represented as simple cellular automaton rules and the analog of energy in the system is an approximation of the Shannon entropy of the binary strings. Only organisms that increase the entropy of the transformed strings are allowed to replicate. This system exhibits a large degree of species diversity, which increases when the flow of binary strings into the system is reduced. Investigating the relation between ecosystem productivity and diversity we find that diversity is negatively correlated with biomass production and energy uptake, while it correlates positively with energy-uptake efficiency. By performing invasion experiments, we show that the source of diversity is negative frequency-dependent selection acting among the different species, and that some of these interactions are intransitive, another mechanism known to promote diversity.
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24. |
- Gerlee, Philip, 1980, et al.
(författare)
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Rock-scissor-paper dynamics in a digital ecology
- 2010
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Ingår i: 12th International Conference on the Synthesis and Simulation of Living Systems: Artificial Life XII, ALIFE 2010; Odense; Denmark; 19 August 2010 through 23 August 2010. - 9780262290753 ; , s. 285-295
-
Konferensbidrag (refereegranskat)abstract
- In this paper we present an Alife-platform named Urdar aimed at investigating dynamics of ecosystems where species engage in cross-feeding, i.e. where metabolites are passed from one species to the next in a process of sequential degra- dation. This type of interactions are commonly found in microbial ecosystems such as bacterial consortia degrading complex compounds. We have studied this phenomenon from an abstract point of view by considering artificial organisms which metabolise binary strings from a shared environment. The organisms are represented as simple cellular automaton rules and the analogue of energy in the system is an approxi- mation of the Shannon entropy of the binary strings. Only or- ganisms which increase the entropy of the transformed strings are allowed to replicate. We find that the system exhibits a large degree of biodiversity and a non-stationary species dis- tribution, especially during low rates of energy inflow, and that the time spent in each species configuration exhibits a broad distribution. Investigating the interaction between dif- ferent species in the system by invasion experiments we ob- serve that co-existence is a common feature and that some triplets of species exhibit intransitive, i.e. rock-paper-scissors like, interactions.
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25. |
- Gerlee, Philip, 1980, et al.
(författare)
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Scientific Models : Red Atoms, White Lies and Black Boxes in a Yellow Book
- 2016
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Bok (övrigt vetenskapligt/konstnärligt)abstract
- A zebrafish, the hull of a miniature ship, a mathematical equation and a food chain - what do these things have in common? They are examples of models used by scientists to isolate and study particular aspects of the world around us. This book begins by introducing the concept of a scientific model from an intuitive perspective, drawing parallels to mental models and artistic representations. It then recounts the history of modelling from the 16th century up until the present day. The iterative process of model building is described and discussed in the context of complex models with high predictive accuracy versus simpler models that provide more of a conceptual understanding. To illustrate the diversity of opinions within the scientific community, we also present the results of an interview study, in which ten scientists from different disciplines describe their views on modelling and how models feature in their work. Lastly, it includes a number of worked examples that span different modelling approaches and techniques. It provides a comprehensive introduction to scientific models and shows how models are constructed and used in modern science. It also addresses the approach to, and the culture surrounding modelling in different scientific disciplines. It serves as an inspiration for model building and also facilitates interdisciplinary collaborations by showing how models are used in different scientific fields. The book is aimed primarily at students in the sciences and engineering, as well as students at teacher training colleges but will also appeal to interested readers wanting to get an overview of scientific modelling in general and different modelling approaches in particular.
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26. |
- Gerlee, Philip, 1980, et al.
(författare)
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Scientific Models
- 2016
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Bok (övrigt vetenskapligt/konstnärligt)abstract
- A zebrafish, the hull of a miniature ship, a mathematical equation and a food chain - what do these things have in common? They are examples of models used by scientists to isolate and study particular aspects of the world around us. This book begins by introducing the concept of a scientific model from an intuitive perspective, drawing parallels to mental models and artistic representations. It then recounts the history of modelling from the 16th century up until the present day. The iterative process of model building is described and discussed in the context of complex models with high predictive accuracy versus simpler models that provide more of a conceptual understanding. To illustrate the diversity of opinions within the scientific community, we also present the results of an interview study, in which ten scientists from different disciplines describe their views on modelling and how models feature in their work. Lastly, it includes a number of worked examples that span different modelling approaches and techniques. It provides a comprehensive introduction to scientific models and shows how models are constructed and used in modern science. It also addresses the approach to, and the culture surrounding modelling in different scientific disciplines. It serves as an inspiration for model building and also facilitates interdisciplinary collaborations by showing how models are used in different scientific fields. The book is aimed primarily at students in the sciences and engineering, as well as students at teacher training colleges but will also appeal to interested readers wanting to get an overview of scientific modelling in general and different modelling approaches in particular.
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27. |
- Gerlee, Philip, 1980, et al.
(författare)
-
Searching for Synergies: Matrix Algebraic Approaches for Efficient Pair Screening
- 2013
-
Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:7
-
Tidskriftsartikel (refereegranskat)abstract
- Functionally interacting perturbations, such as synergistic drugs pairs or synthetic lethal gene pairs, are of key interest in both pharmacology and functional genomics. However, to find such pairs by traditional screening methods is both time consuming and costly. We present a novel computational-experimental framework for efficient identification of synergistic target pairs, applicable for screening of systems with sizes on the order of current drug, small RNA or SGA (Synthetic Genetic Array) libraries (>1000 targets). This framework exploits the fact that the response of a drug pair in a given system, or a pair of genes' propensity to interact functionally, can be partly predicted by computational means from (i) a small set of experimentally determined target pairs, and (ii) pre-existing data (e.g. gene ontology, PPI) on the similarities between targets. Predictions are obtained by a novel matrix algebraic technique, based on cyclical projections onto convex sets. We demonstrate the efficiency of the proposed method using drug-drug interaction data from seven cancer cell lines and gene-gene interaction data from yeast SGA screens. Our protocol increases the rate of synergism discovery significantly over traditional screening, by up to 7-fold. Our method is easy to implement and could be applied to accelerate pair screening for both animal and microbial systems.
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28. |
- Gerlee, Philip, 1980, et al.
(författare)
-
The Emergence of Overlapping Scale-free Genetic Architecture in
- 2008
-
Ingår i: Artificial Life. - 1064-5462 .- 1530-9185. ; 14:3, s. 265-275
-
Tidskriftsartikel (refereegranskat)abstract
- We have studied the evolution of genetic architecture in digital organisms and found that the gene overlap follows a scale-free distribution, which is commonly found in metabolic networks of many organisms. Our results show that the slope of the scale-free distribution depends on the mutation rate and that the gene development is driven by expansion of already existing genes, which is in direct correspondence to the preferential growth algorithm that gives rise to scale-free networks. To further validate our results we have constructed a simple model of gene development, which recapitulates the results from the evolutionary process and shows that the mutation rate affects the tendency of genes to cluster. In addition we could relate the slope of the scale-free distribution to the genetic complexity of the organisms and show that a high mutation rate gives rise to a more complex genetic architecture.
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29. |
- Gerlee, Philip, 1980, et al.
(författare)
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The evolution of carrying capacity in constrained and expanding tumour cell populations
- 2015
-
Ingår i: Physical Biology. - : IOP Publishing. - 1478-3967 .- 1478-3975. ; 12:5, s. artikel nr 056001-
-
Tidskriftsartikel (refereegranskat)abstract
- Cancer cells are known to modify their micro-environment such that it can sustain a larger population, or, in ecological terms, they construct a niche which increases the carrying capacity of the population. It has however been argued that niche construction, which benefits all cells in the tumour, would be selected against since cheaters could reap the benefits without paying the cost. We have investigated the impact of niche specificity on tumour evolution using an individual based model of breast tumour growth, in which the carrying capacity of each cell consists of two components: an intrinsic, subclone-specific part and a contribution from all neighbouring cells. Analysis of the model shows that the ability of a mutant to invade a resident population depends strongly on the specificity. When specificity is low selection is mostly on growth rate, while high specificity shifts selection towards increased carrying capacity. Further, we show that the long-term evolution of the system can be predicted using adaptive dynamics. By comparing the results from a spatially structured versus well-mixed population we show that spatial structure restores selection for carrying capacity even at zero specificity, which poses a solution to the niche construction dilemma. Lastly, we show that an expanding population exhibits spatially variable selection pressure, where cells at the leading edge exhibit higher growth rate and lower carrying capacity than those at the centre of the tumour.
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30. |
- Gerlee, Philip, 1980, et al.
(författare)
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The Genetic coding style of digital organisms
- 2005
-
Ingår i: Lecture Notes in Computer Science - Advances in Artificial Life, Sept. 2005, Canterbury, UK, M.S. Capcarrere et al.. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 0302-9743 .- 1611-3349. - 3540288481 ; 3630, s. 854-863
-
Konferensbidrag (refereegranskat)abstract
- Recently, all the human genes were identified. But understanding the functions coded in the genes is of course a much harder problem. We are used to view DNA as some sort of a computer code, but there are striking differences. For example, by using entropy, it has been shown that the DNA code is much closer to random code than written text, which in turn is less ordered than ordinary computer code. Instead of saying that the DNA is badly written, using common programming standards, we might say that it is written in a different style − an evolutionary style. In this paper the coding style of creatures from the artificial life platform Avida has been studied. Avida creatures that have evolved under different size merit methods and mutation rates have been analysed using the notion of stylistic measures. The analysis has shown that the evolutionary coding style depends on the environment in which the code evolved, and that the choice of size merit method and mutation probabilities affect different stylistic properties of the genome. A better understanding of Avidas coding style, might eventually lead to insights of evolutionary codes in general.
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31. |
- Gerlee, Philip, 1980, et al.
(författare)
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The Impact of Phenotypic Switching on Glioblastoma Growth and Invasion
- 2012
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Ingår i: PLoS Computational Biology. - : Public Library of Science (PLoS). - 1553-7358 .- 1553-734X. ; 8:6
-
Tidskriftsartikel (refereegranskat)abstract
- The brain tumour glioblastoma is characterised by diffuse and infiltrative growth into surrounding brain tissue. At the macroscopic level, the progression speed of a glioblastoma tumour is determined by two key factors: the cell proliferation rate and the cell migration speed. At the microscopic level, however, proliferation and migration appear to be mutually exclusive phenotypes, as indicated by recent in vivo imaging data. Here, we develop a mathematical model to analyse how the phenotypic switching between proliferative and migratory states of individual cells affects the macroscopic growth of the tumour. For this, we propose an individual-based stochastic model in which glioblastoma cells are either in a proliferative state, where they are stationary and divide, or in motile state in which they are subject to random motion. From the model we derive a continuum approximation in the form of two coupled reaction-diffusion equations, which exhibit travelling wave solutions whose speed of invasion depends on the model parameters. We propose a simple analytical method to predict progression rate from the cell-specific parameters and demonstrate that optimal glioblastoma growth depends on a non-trivial trade-off between the phenotypic switching rates. By linking cellular properties to an in vivo outcome, the model should be applicable to designing relevant cell screens for glioblastoma and cytometry-based patient prognostics.
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32. |
- Gerlee, Philip, 1980, et al.
(författare)
-
The Influence of Cellular Characteristics on the Evolution of Shape Homeostasis
- 2017
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Ingår i: Artificial Life. - 1530-9185 .- 1064-5462. ; 23:3, s. 424-448
-
Tidskriftsartikel (refereegranskat)abstract
- The importance of individual cells in a developing multicellular organism is well known, but precisely how the individual cellular characteristics of those cells collectively drive the emergence of robust, homeostatic structures is less well understood. For example, cell communication via a diffusible factor allows for information to travel across large distances within the population, and cell polarization makes it possible to form structures with a particular orientation, but how do these processes interact to produce a more robust and regulated structure? In this study we investigate the ability of cells with different cellular characteristics to grow and maintain homeostatic structures. We do this in the context of an individual-based model where cell behavior is driven by an intracellular network that determines the cell phenotype. More precisely, we investigated evolution with 96 different permutations of our model, where cell motility, cell death, long-range growth factor (LGF), short-range growth factor (SGF), and cell polarization were either present or absent. The results show that LGF has the largest positive influence on the fitness of the evolved solutions. SGF and polarization also contribute, but all other capabilities essentially increase the search space, effectively making it more difficult to achieve a solution. By perturbing the evolved solutions, we found that they are highly robust to both mutations and wounding. In addition, we observed that by evolving solutions in more unstable environments they produce structures that were more robust and adaptive. In conclusion, our results suggest that robust collective behavior is most likely to evolve when cells are endowed with long-range communication, cell polarisation, and selection pressure from an unstable environment.
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33. |
- Gerlee, Philip, 1980
(författare)
-
The Model Muddle: In Search of Tumor Growth Laws
- 2013
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Ingår i: Cancer Research. - : American Association for Cancer Research (AACR). - 0008-5472 .- 1538-7445. ; 73:8, s. 2407-2411
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we will trace the historical development of tumor growth laws, which in a quantitative fashion describe the increase in tumor mass/volume over time. These models are usually formulated in terms of differential equations that relate the growth rate of the tumor to its current state and range from the simple one-parameter exponential growth model to more advanced models that contain a large number of parameters. Understanding the assumptions and consequences of such models is important, as they often underpin more complex models of tumor growth. The conclusion of this brief survey is that although much improvement has occurred over the last century, more effort and new models are required if we are to understand the intricacies of tumor growth.
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34. |
- Gerlee, Philip, 1980, et al.
(författare)
-
Travelling wave analysis of a mathematical model of glioblastoma growth
- 2016
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Ingår i: Mathematical Biosciences. - : Elsevier BV. - 0025-5564 .- 1879-3134. ; 276, s. 75-81
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper we analyse a previously proposed cell-based model of glioblastoma (brain tumour) growth, which is based on the assumption that the cancer cells switch phenotypes between a proliferative and motile state (Gerlee and Nelander, PLoS Comp. Bio., 8(6) 2012). The dynamics of this model can be described by a system of partial differential equations, which exhibits travelling wave solutions whose wave speed depends crucially on the rates of phenotypic switching. We show that under certain conditions on the model parameters, a closed form expression of the wave speed can be obtained, and using singular perturbation methods we also derive an approximate expression of the wave front shape. These new analytical results agree with simulations of the cell-based model, and importantly show that the inverse relationship between wave front steepness and speed observed for the Fisher equation no longer holds when phenotypic switching is considered.
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35. |
- Gerlee, Philip, 1980, et al.
(författare)
-
Urdar - an artificial ecology platform
- 2011
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Ingår i: ECAL 2011: The 11th European Conference on Artificial Life.
-
Konferensbidrag (refereegranskat)abstract
- Cross-feeding interactions are a common feature of many microbial systems, such as colonies of E. coli grown on a single limiting resource. We have studied this phenomenon in Gerlee and Lundh (2010) from an abstract point of view by considering artificial organisms which metabolise binary strings from a shared environment. The organisms are represented as simple cellular automaton rules and the analog of energy in the system is an approximation of the Shannon entropy of the binary strings. Only organisms which increase the entropy of the transformed strings are allowed to replicate. This system exhibits a large degree of species diversity, which increases when the flow of binary strings into the system is reduced.
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36. |
- Gerlee, Philip, 1980, et al.
(författare)
-
Vetenskapliga modeller : Svarta lådor, röda atomer och vita lögner
- 2012
-
Bok (övrigt vetenskapligt/konstnärligt)abstract
- Vad har en zebrafisk, ett fartygsskrov i miniatyr, en matematisk ekvation och en näringskedja gemensamt? De är alla exempel på vetenskapliga modeller som används inom dagens forskning för att beskriva vår omvärld och gör det möjligt för forskare att isolera och i detalj studera ett visst fenomen. Boken inleds med att introducera begreppet på ett intuitivt plan, genom att dra paralleller till mentala modeller och konstnärliga representationer, och fortsätter med en historisk tillbakablick som sträcker sig från 1600-talet till nutid. Vi diskuterar också den iterativa konstruktionsprocessen och balansen mellan enkelhet och komplexitet som den innebär, vilket i sin tur är kopplat till avvägningen mellan en förklarande modell och en förutsägande. För att belysa skillnader mellan olika synsätt på modeller presenteras också en intervjustudie där forskare från tio stycken forskningsfält beskriver sin relation till modeller. Avslutningsvis innehåller boken ett kapitel där typiska modeller från flera discipliner beskrivs i detalj. Syftet med denna bok är att ge en övergripande introduktion till vetenskapliga modeller och visa hur modeller är uppbyggda samt hur de används inom vetenskapligt arbete. Vi hoppas också att den kan tjäna som inspiration till nya modeller och även underlätta det interdisciplinära samtalet. Boken vänder sig i första hand till studenter på landets ingenjörs- och naturvetarprogram samt till studenter på lärarhögskolorna, men även till dig som har ett vetenskapligt intresse och vill få en översikt av modellering i stort och olika modelleringstraditioner i synnerhet.
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37. |
- Gerlee, Philip, 1980, et al.
(författare)
-
Vetenskapliga modeller
- 2012
-
Bok (övrigt vetenskapligt/konstnärligt)abstract
- Vad har en zebrafisk, ett fartygsskrov i miniatyr, en matematisk ekvation och en näringskedja gemensamt? De är alla exempel på vetenskapliga modeller som används inom dagens forskning för att beskriva vår omvärld och gör det möjligt för forskare att isolera och i detalj studera ett visst fenomen.Boken inleds med att introducera begreppet på ett intuitivt plan, genom att dra paralleller till mentala modeller och konstnärliga representationer, och fortsätter med en historisk tillbakablick som sträcker sig från 1600-talet till nutid. Vi diskuterar också den iterativa konstruktionsprocessen och balansen mellan enkelhet och komplexitet som den innebär, vilket i sin tur är kopplat till avvägningen mellan en förklarande modell och en förutsägande. För att belysa skillnader mellan olika synsätt på modeller presenteras också en intervjustudie där forskare från tio stycken forskningsfält beskriver sin relation till modeller. Avslutningsvis innehåller boken ett kapitel där typiska modeller från flera discipliner beskrivs i detalj.Syftet med denna bok är att ge en övergripande introduktion till vetenskapliga modeller och visa hur modeller är uppbyggda samt hur de används inom vetenskapligt arbete. Vi hoppas också att den kan tjäna som inspiration till nya modeller och även underlätta det interdisciplinära samtalet.Boken vänder sig i första hand till studenter på landets ingenjörs- och naturvetarprogram samt till studenter på lärarhögskolorna, men även till dig som har ett vetenskapligt intresse och vill få en översikt av modellering i stort och olika modelleringstraditioner i synnerhet.
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38. |
- Gerlee, Philip, 1980
(författare)
-
Weak Selection and the Separation of Eco-evo Time Scales using Perturbation Analysis
- 2022
-
Ingår i: Bulletin of Mathematical Biology. - : Springer Science and Business Media LLC. - 0092-8240 .- 1522-9602. ; 84:5
-
Tidskriftsartikel (refereegranskat)abstract
- We show that under the assumption of weak frequency-dependent selection a wide class of population dynamical models can be analysed using perturbation theory. The inner solution corresponds to the ecological dynamics, where to zeroth order, the genotype frequencies remain constant. The outer solution provides the evolutionary dynamics and corresponds, to zeroth order, to a generalisation of the replicator equation. We apply this method to a model of public goods dynamics and construct, using matched asymptotic expansions, a composite solution valid for all times. We also analyse a Lotka-Volterra model of predator competition and show that to zeroth order the fraction of wild-type predators follows a replicator equation with a constant selection coefficient given by the predator death rate. For both models, we investigate how the error between approximate solutions and the solution to the full model depend on the order of the approximation and show using numerical comparison, for k = 1 and 2, that the error scales according to epsilon(k+1), where s is the strength of selection and k is the order of the approximation.
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39. |
- Hamis, S., et al.
(författare)
-
Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems
- 2023
-
Ingår i: Journal of Mathematical Biology. - : Springer Nature. - 0303-6812 .- 1432-1416. ; 86:5
-
Tidskriftsartikel (refereegranskat)abstract
- Theoretical and applied cancer studies that use individual-based models (IBMs) have been limited by the lack of a mathematical formulation that enables rigorous analysis of these models. However, spatial cumulant models (SCMs), which have arisen from theoretical ecology, describe population dynamics generated by a specific family of IBMs, namely spatio-temporal point processes (STPPs). SCMs are spatially resolved population models formulated by a system of differential equations that approximate the dynamics of two STPP-generated summary statistics: first-order spatial cumulants (densities), and second-order spatial cumulants (spatial covariances). We exemplify how SCMs can be used in mathematical oncology by modelling theoretical cancer cell populations comprising interacting growth factor-producing and non-producing cells. To formulate model equations, we use computational tools that enable the generation of STPPs, SCMs and mean-field population models (MFPMs) from user-defined model descriptions (Cornell et al. Nat Commun 10:4716, 2019). To calculate and compare STPP, SCM and MFPM-generated summary statistics, we develop an application-agnostic computational pipeline. Our results demonstrate that SCMs can capture STPP-generated population density dynamics, even when MFPMs fail to do so. From both MFPM and SCM equations, we derive treatment-induced death rates required to achieve non-growing cell populations. When testing these treatment strategies in STPP-generated cell populations, our results demonstrate that SCM-informed strategies outperform MFPM-informed strategies in terms of inhibiting population growths. We thus demonstrate that SCMs provide a new framework in which to study cell-cell interactions, and can be used to describe and perturb STPP-generated cell population dynamics. We, therefore, argue that SCMs can be used to increase IBMs' applicability in cancer research.
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40. |
- Kimmel, G. J., et al.
(författare)
-
Neighborhood size-effects shape growing population dynamics in evolutionary public goods games
- 2019
-
Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 2:AAC RM, 1994, JOURNAL OF PUBLIC ECONOMICS, V54, P1
-
Tidskriftsartikel (refereegranskat)abstract
- An evolutionary game emerges when a subset of individuals incur costs to provide benefits to all individuals. Public goods games (PGG) cover the essence of such dilemmas in which cooperators are prone to exploitation by defectors. We model the population dynamics of a non-linear PGG and consider density-dependence on the global level, while the game occurs within local neighborhoods. At low cooperation, increases in the public good provide increasing returns. At high cooperation, increases provide diminishing returns. This mechanism leads to diverse evolutionarily stable strategies, including monomorphic and polymorphic populations, and neighborhood-size-driven state changes, resulting in hysteresis between equilibria. Stochastic or strategy-dependent variations in neighborhood sizes favor coexistence by destabilizing monomorphic states. We integrate our model with experiments of cancer cell growth and confirm that our framework describes PGG dynamics observed in cellular populations. Our findings advance the understanding of how neighborhood-size effects in PGG shape the dynamics of growing populations.
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41. |
- Kimmel, G. J., et al.
(författare)
-
Time scales and wave formation in non-linear spatial public goods games
- 2019
-
Ingår i: PLoS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 15:9
-
Tidskriftsartikel (refereegranskat)abstract
- The co-evolutionary dynamics of competing populations can be strongly affected by frequency- dependent selection and spatial population structure. As co-evolving populations grow into a spatial domain, their initial spatial arrangement and their growth rate differences are important factors that determine the long-term outcome. We here model producer and free-rider co-evolution in the context of a diffusive public good (PG) that is produced by the producers at a cost but evokes local concentration-dependent growth benefits to all. The benefit of the PG can be non-linearly dependent on public good concentration. We consider the spatial growth dynamics of producers and free-riders in one, two and three dimensions by modeling producer cell, free-rider cell and public good densities in space, driven by the processes of birth, death and diffusion (cell movement and public good distribution). Typically, one population goes extinct, but the time-scale of this process varies with initial conditions and the growth rate functions. We establish that spatial variation is transient regardless of dimensionality, and that structured initial conditions lead to increasing times to get close to an extinction state, called ∈-extinction time. Further, we find that uncorrelated initial spatial structures do not influence this ∈-extinction time in comparison to a corresponding well-mixed (non-spatial) system. In order to estimate the ∈-extinction time of either free-riders or producers we derive a slow manifold solution. For invading populations, i.e. for populations that are initially highly segregated, we observe a traveling wave, whose speed can be calculated. Our results provide quantitative predictions for the transient spatial dynamics of cooperative traits under pressure of extinction. © 2019 Kimmel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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42. |
- Lindwall, Gustav, 1992, et al.
(författare)
-
Bayesian inference on the Allee effect in cancer cell line populations using time-lapse microscopy images
- 2023
-
Ingår i: Journal of Theoretical Biology. - 0022-5193 .- 1095-8541. ; 574
-
Tidskriftsartikel (refereegranskat)abstract
- The Allee effect describes the phenomenon that the per capita reproduction rate increases along with the population density at low densities. Allee effects have been observed at all scales, including in microscopic environments where individual cells are taken into account. This is great interest to cancer research, as understanding critical tumour density thresholds can inform treatment plans for patients. In this paper, we introduce a simple model for cell division in the case where the cancer cell population is modelled as an interacting particle system. The rate of the cell division is dependent on the local cell density, introducing an Allee effect. We perform parameter inference of the key model parameters through Markov Chain Monte Carlo, and apply our procedure to two image sequences from a cervical cancer cell line. The inference method is verified on in silico data to accurately identify the key parameters, and results on the in vitro data strongly suggest an Allee effect
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43. |
- Lindwall, Gustav, 1992, et al.
(författare)
-
Bayesian inference on the Allee effect in cancer cell populations using time-lapse microscopy images
- 2023
-
Ingår i: Journal of Theoretical Biology. - 1095-8541 .- 0022-5193. ; 574
-
Tidskriftsartikel (refereegranskat)abstract
- The Allee effect describes the phenomenon that the per capita reproduction rate increases along with the population density at low densities. Allee effects have been observed at all scales, including in microscopic environments where individual cells are taken into account. This is great interest to cancer research, as understanding critical tumour density thresholds can inform treatment plans for patients. In this paper, we introduce a simple model for cell division in the case where the cancer cell population is modelled as an interacting particle system. The rate of the cell division is dependent on the local cell density, introducing an Allee effect. We perform parameter inference of the key model parameters through Markov Chain Monte Carlo, and apply our procedure to two image sequences from a cervical cancer cell line. The inference method is verified on in silico data to accurately identify the key parameters, and results on the in vitro data strongly suggest an Allee effect.
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44. |
- Lindwall, Gustav, 1992, et al.
(författare)
-
Fast and precise inference on diffusivity in interacting particle systems
- 2023
-
Ingår i: Journal of Mathematical Biology. - : Springer Science and Business Media LLC. - 1432-1416 .- 0303-6812. ; 86:5
-
Tidskriftsartikel (refereegranskat)abstract
- Particle systems made up of interacting agents is a popular model used in a vast array of applications, not the least in biology where the agents can represent everything from single cells to animals in a herd. Usually, the particles are assumed to undergo some type of random movements, and a popular way to model this is by using Brownian motion. The magnitude of random motion is often quantified using mean squared displacement, which provides a simple estimate of the diffusion coefficient. However, this method often fails when data is sparse or interactions between agents frequent. In order to address this, we derive a conjugate relationship in the diffusion term for large interacting particle systems undergoing isotropic diffusion, giving us an efficient inference method. The method accurately accounts for emerging effects such as anomalous diffusion stemming from mechanical interactions. We apply our method to an agent-based model with a large number of interacting particles, and the results are contrasted with a naive mean square displacement-based approach. We find a significant improvement in performance when using the higher-order method over the naive approach. This method can be applied to any system where agents undergo Brownian motion and will lead to improved estimates of diffusion coefficients compared to existing methods.
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45. |
- Liu, Y., et al.
(författare)
-
Ladderpath Approach: How Tinkering and Reuse Increase Complexity and Information
- 2022
-
Ingår i: Entropy. - : MDPI AG. - 1099-4300. ; 24:8
-
Tidskriftsartikel (refereegranskat)abstract
- The notion of information and complexity are important concepts in many scientific fields such as molecular biology, evolutionary theory and exobiology. Many measures of these quantities are either difficult to compute, rely on the statistical notion of information, or can only be applied to strings. Based on assembly theory, we propose the notion of a ladderpath, which describes how an object can be decomposed into hierarchical structures using repetitive elements. From the ladderpath, two measures naturally emerge: the ladderpath-index and the order-index, which represent two axes of complexity. We show how the ladderpath approach can be applied to both strings and spatial patterns and argue that all systems that undergo evolution can be described as ladderpaths. Further, we discuss possible applications to human language and the origin of life. The ladderpath approach provides an alternative characterization of the information that is contained in a single object (or a system) and could aid in our understanding of evolving systems and the origin of life in particular.
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46. |
- Lundh, Torbjörn, 1965, et al.
(författare)
-
Cross-Feeding Dynamics Described by a Series Expansion of the Replicator Equation
- 2013
-
Ingår i: Bulletin of Mathematical Biology. - : Springer Science and Business Media LLC. - 0092-8240 .- 1522-9602. ; 75:5, s. 709-724
-
Tidskriftsartikel (refereegranskat)abstract
- Understanding how ecosystems evolve and how they respond to external perturbations is critical if we are to predict the effects of human intervention. A particular class of ecosystems whose dynamics are poorly understood are those in which the species are related via cross-feeding. In these ecosystems the metabolic output of one species is being used as a nutrient or energy source by another species. In this paper we derive a mathematical description of cross-feeding dynamics based on the replicator equation. We show that under certain assumptions about the system (e.g., high flow of nutrients and time scale separation), the governing equations reduce to a second-order series expansion of the replicator equation. By analysing the case of two and three species we derive conditions for co-existence and show under which parameter conditions one can expect an increase in mean fitness. Finally, we discuss how the model can be parameterised from experimental data.
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47. |
- Malik, Adam, 1991, et al.
(författare)
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Mathematical modelling of cell migration: stiffness dependent jump rates result in durotaxis
- 2019
-
Ingår i: Journal of Mathematical Biology. - : Springer Science and Business Media LLC. - 0303-6812 .- 1432-1416. ; 78:7, s. 2289-2315
-
Tidskriftsartikel (refereegranskat)abstract
- Durotaxis, the phenomena where cells migrate up a gradient in substrate stiffness, remains poorly understood. It has been proposed that durotaxis results from the reinforcement of focal adhesions on stiff substrates. In this paper we formulate a mathematical model of single cell migration on elastic substrates with spatially varying stiffness. We develop a stochastic model where the cell moves by updating the position of its adhesion sites at random times, and the rate of updates is determined by the local stiffness of the substrate. We investigate two physiologically motivated mechanisms of stiffness sensing. From the stochastic model of single cell migration we derive a population level description in the form of a partial differential equation for the time evolution of the density of cells. The equation is an advection-diffusion equation, where the advective velocity is proportional to the stiffness gradient. The model shows quantitative agreement with experimental results in which cells tend to cluster when seeded on a matrix with periodically varying stiffness.
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48. |
- Malik, Adam, 1991, et al.
(författare)
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The Impact of Elastic Deformations of the Extracellular Matrix on Cell Migration
- 2020
-
Ingår i: Bulletin of Mathematical Biology. - : Springer Science and Business Media LLC. - 0092-8240 .- 1522-9602. ; 82:4
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Tidskriftsartikel (refereegranskat)abstract
- The mechanical properties of the extracellular matrix, in particular its stiffness, are known to impact cell migration. In this paper, we develop a mathematical model of a single cell migrating on an elastic matrix, which accounts for the deformation of the matrix induced by forces exerted by the cell, and investigate how the stiffness impacts the direction and speed of migration. We model a cell in 1D as a nucleus connected to a number of adhesion sites through elastic springs. The cell migrates by randomly updating the position of its adhesion sites. We start by investigating the case where the cell springs are constant, and then go on to assuming that they depend on the matrix stiffness, on matrices of both uniform stiffness as well as those with a stiffness gradient. We find that the assumption that cell springs depend on the substrate stiffness is necessary and sufficient for an efficient durotactic response. We compare simulations to recent experimental observations of human cancer cells exhibiting durotaxis, which show good qualitative agreement. © 2020, The Author(s).
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49. |
- Rosén, Emil, et al.
(författare)
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Inference of glioblastoma migration and proliferation rates using single time-point images
- 2023
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Ingår i: Communications Biology. - : Springer Nature. - 2399-3642. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Cancer cell migration is a driving mechanism of invasion in solid malignant tumors. Anti-migratory treatments provide an alternative approach for managing disease progression. However, we currently lack scalable screening methods for identifying novel anti-migratory drugs. To this end, we develop a method that can estimate cell motility from single end-point images in vitro by estimating differences in the spatial distribution of cells and inferring proliferation and diffusion parameters using agent-based modeling and approximate Bayesian computation. To test the power of our method, we use it to investigate drug responses in a collection of 41 patient-derived glioblastoma cell cultures, identifying migration-associated pathways and drugs with potent anti-migratory effects. We validate our method and result in both in silico and in vitro using time-lapse imaging. Our proposed method applies to standard drug screen experiments, with no change needed, and emerges as a scalable approach to screen for anti-migratory drugs. The spatial positioning of cultured glioblastoma cells is used to estimate cell motility and drug effects from single end-point images in vitro.
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50. |
- Schmidt, L., et al.
(författare)
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Comparative drug pair screening across multiple glioblastoma cell lines reveals novel drug-drug interactions
- 2013
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Ingår i: Neuro-Oncology. - : Oxford University Press (OUP). - 1522-8517 .- 1523-5866. ; 15:11, s. 1469-1478
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Tidskriftsartikel (refereegranskat)abstract
- Glioblastoma multiforme (GBM) is the most aggressive brain tumor in adults, and despite state-of-the-art treatment, survival remains poor and novel therapeutics are sorely needed. The aim of the present study was to identify new synergistic drug pairs for GBM. In addition, we aimed to explore differences in drug-drug interactions across multiple GBM-derived cell cultures and predict such differences by use of transcriptional biomarkers. We performed a screen in which we quantified drug-drug interactions for 465 drug pairs in each of the 5 GBM cell lines U87MG, U343MG, U373MG, A172, and T98G. Selected interactions were further tested using isobole-based analysis and validated in 5 glioma-initiating cell cultures. Furthermore, drug interactions were predicted using microarray-based transcriptional profiling in combination with statistical modeling. Of the 5 465 drug pairs, we could define a subset of drug pairs with strong interaction in both standard cell lines and glioma-initiating cell cultures. In particular, a subset of pairs involving the pharmaceutical compounds rimcazole, sertraline, pterostilbene, and gefitinib showed a strong interaction in a majority of the cell cultures tested. Statistical modeling of microarray and interaction data using sparse canonical correlation analysis revealed several predictive biomarkers, which we propose could be of importance in regulating drug pair responses. We identify novel candidate drug pairs for GBM and suggest possibilities to prospectively use transcriptional biomarkers to predict drug interactions in individual cases.
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