PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling

被引:59
|
作者
Letort, Gaelle [1 ,2 ,3 ,9 ]
Montagud, Arnau [1 ,2 ,3 ]
Stoll, Gautier [4 ,5 ,6 ,7 ]
Heiland, Randy [8 ]
Barillot, Emmanuel [1 ,2 ,3 ]
Macklin, Paul [8 ]
Zinovyev, Andrei [1 ,2 ,3 ]
Calzone, Laurence [1 ,2 ,3 ]
机构
[1] PSL Res Univ, Inst Curie, F-75005 Paris, France
[2] INSERM, U900, F-75005 Paris, France
[3] PSL Res Univ, MINES ParisTech, CBIO Ctr Computat Biol, F-75006 Paris, France
[4] Univ Paris Descartes Paris V, Sorbonne Paris Cite, F-75006 Paris, France
[5] Gustave Roussy Canc Campus, F-94800 Villejuif, France
[6] INSERM, U1138, F-75006 Paris, France
[7] Ctr Rech Cordeliers, Equipe Labellisee Ligue Natl Canc 11, F-75006 Paris, France
[8] Indiana Univ, Intelligent Syst Engn, Bloomington, IN 47408 USA
[9] Coll France, CIRB, F-75231 Paris, France
基金
欧盟地平线“2020”;
关键词
TUMOR-GROWTH; GENETIC-CONTROL; SPHEROIDS; EVOLUTION; BIOLOGY; ORGANIZATION; MORPHOLOGY; EXPRESSION; MIGRATION; STRATEGY;
D O I
10.1093/bioinformatics/bty766
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation Due to the complexity and heterogeneity of multicellular biological systems, mathematical models that take into account cell signalling, cell population behaviour and the extracellular environment are particularly helpful. We present PhysiBoSS, an open source software which combines intracellular signalling using Boolean modelling (MaBoSS) and multicellular behaviour using agent-based modelling (PhysiCell). Results PhysiBoSS provides a flexible and computationally efficient framework to explore the effect of environmental and genetic alterations of individual cells at the population level, bridging the critical gap from single-cell genotype to single-cell phenotype and emergent multicellular behaviour. PhysiBoSS thus becomes very useful when studying heterogeneous population response to treatment, mutation effects, different modes of invasion or isomorphic morphogenesis events. To concretely illustrate a potential use of PhysiBoSS, we studied heterogeneous cell fate decisions in response to TNF treatment. We explored the effect of different treatments and the behaviour of several resistant mutants. We highlighted the importance of spatial information on the population dynamics by considering the effect of competition for resources like oxygen. Availability and implementation PhysiBoSS is freely available on GitHub (https://github.com/sysbio-curie/PhysiBoSS), with a Docker image (https://hub.docker.com/r/gletort/physiboss/). It is distributed as open source under the BSD 3-clause license. Supplementary information Supplementary data are available at Bioinformatics online.
引用
收藏
页码:1188 / 1196
页数:9
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