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Antagonistic interactions are sufficient to explain self-assemblage of bacterial communities in a homogeneous environment: a computational modeling approach.
Zapién-Campos, Román; Olmedo-Álvarez, Gabriela; Santillán, Moisés.
Afiliación
  • Zapién-Campos R; Unidad Profesional Interdisciplinaria de Ingenierías Guanajuato, Instituto Politécnico Nacional Silao, Mexico.
  • Olmedo-Álvarez G; Departamento de Ingeniería Genética, Unidad Irapuato, Centro de Investigación y Estudios Avanzados del IPN Irapuato, Mexico.
  • Santillán M; Unidad Monterrey, Centro de Investigación y Estudios Avanzados del IPN Apodaca, Mexico.
Front Microbiol ; 6: 489, 2015.
Article en En | MEDLINE | ID: mdl-26052318
Most of the studies in Ecology have been devoted to analyzing the effects the environment has on individuals, populations, and communities, thus neglecting the effects of biotic interactions on the system dynamics. In the present work we study the structure of bacterial communities in the oligotrophic shallow water system of Churince, Cuatro Cienegas, Mexico. Since the physicochemical conditions of this water system are homogeneous and quite stable in time, it is an excellent candidate to study how biotic factors influence the structure of bacterial communities. In a previous study, the binary antagonistic interactions of 78 bacterial strains, isolated from Churince, were experimentally determined. We employ these data to develop a computer algorithm to simulate growth experiments in a cellular grid representing the pond. Remarkably, in our model, the dynamics of all the simulated bacterial populations is determined solely by antagonistic interactions. Our results indicate that all bacterial strains (even those that are antagonized by many other bacteria) survive in the long term, and that the underlying mechanism is the formation of bacterial community patches. Patches corresponding to less antagonistic and highly susceptible strains are consistently isolated from the highly-antagonistic bacterial colonies by patches of neutral strains. These results concur with the observed features of the bacterial community structure previously reported. Finally, we study how our findings depend on factors like initial population size, differential population growth rates, homogeneous population death rates, and enhanced bacterial diffusion.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Microbiol Año: 2015 Tipo del documento: Article País de afiliación: México Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Microbiol Año: 2015 Tipo del documento: Article País de afiliación: México Pais de publicación: Suiza