An integrative approach for modeling and simulation of heterocyst pattern formation in cyanobacteria filaments
Resumen: Heterocyst differentiation in cyanobacteria filaments is one of the simplest examples of cellular differentiation and pattern formation in multicellular organisms. Despite of the many experimental studies addressing the evolution and sustainment of heterocyst patterns and the knowledge of the genetic circuit underlying the behavior of single cyanobacterium under nitrogen deprivation, there is still a theoretical gap connecting these two macroscopic and microscopic processes. As an attempt to shed light on this issue, here we explore heterocyst differentiation under the paradigm of systems biology. This framework allows us to formulate the essential dynamical ingredients of the genetic circuit of a single cyanobacterium into a set of differential equations describing the time evolution of the concentrations of the relevant molecular products. As a result, we are able to study the behavior of a single cyanobacterium under different external conditions, emulating nitrogen deprivation, and simulate the dynamics of cyanobacteria filaments by coupling their respective genetic circuits via molecular diffusion. These two ingredients allow us to understand the principles by which heterocyst patterns can be generated and sustained. In particular, our results point out that, by including both diffusion and noisy external conditions in the computational model, it is possible to reproduce the main features of the formation and sustainment of heterocyst patterns in cyanobacteria filaments as observed experimentally. Finally, we discuss the validity and possible improvements of the model.
Idioma: Inglés
DOI: 10.1371/journal.pcbi.1004129
Año: 2015
Publicado en: PLoS computational biology 11, 3 (2015), [18 pp.]
ISSN: 1553-734X

Factor impacto JCR: 4.587 (2015)
Categ. JCR: MATHEMATICAL & COMPUTATIONAL BIOLOGY rank: 5 / 56 = 0.089 (2015) - Q1 - T1
Categ. JCR: BIOCHEMICAL RESEARCH METHODS rank: 9 / 77 = 0.117 (2015) - Q1 - T1

Factor impacto SCIMAGO: 3.476 - Cellular and Molecular Neuroscience (Q1) - Computational Theory and Mathematics (Q1) - Ecology (Q1) - Molecular Biology (Q1) - Genetics (Q1) - Modeling and Simulation (Q1) - Ecology, Evolution, Behavior and Systematics (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/FIS2011-25167
Financiación: info:eu-repo/grantAgreement/ES/MINECO/FIS2012-38266-C02-01
Tipo y forma: Article (Published version)
Área (Departamento): Área Física Materia Condensada (Dpto. Física Materia Condensa.)

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