Your browser doesn't support javascript.
loading
Social network position is a major predictor of ant behavior, microbiota composition, and brain gene expression.
Kay, Tomas; Liberti, Joanito; Richardson, Thomas O; McKenzie, Sean K; Weitekamp, Chelsea A; La Mendola, Christine; Rüegg, Matthias; Kesner, Lucie; Szombathy, Natasha; McGregor, Sean; Romiguier, Jonathan; Engel, Philipp; Keller, Laurent.
Afiliação
  • Kay T; Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
  • Liberti J; Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
  • Richardson TO; Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland.
  • McKenzie SK; Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
  • Weitekamp CA; School of Biological Sciences, University of Bristol, Bristol, United Kingdom.
  • La Mendola C; Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
  • Rüegg M; Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
  • Kesner L; Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
  • Szombathy N; Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
  • McGregor S; Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland.
  • Romiguier J; Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
  • Engel P; Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
  • Keller L; Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
PLoS Biol ; 21(7): e3002203, 2023 07.
Article em En | MEDLINE | ID: mdl-37486940
ABSTRACT
The physiology and behavior of social organisms correlate with their social environments. However, because social environments are typically confounded by age and physical environments (i.e., spatial location and associated abiotic factors), these correlations are usually difficult to interpret. For example, associations between an individual's social environment and its gene expression patterns may result from both factors being driven by age or behavior. Simultaneous measurement of pertinent variables and quantification of the correlations between these variables can indicate whether relationships are direct (and possibly causal) or indirect. Here, we combine demographic and automated behavioral tracking with a multiomic approach to dissect the correlation structure among the social and physical environment, age, behavior, brain gene expression, and microbiota composition in the carpenter ant Camponotus fellah. Variations in physiology and behavior were most strongly correlated with the social environment. Moreover, seemingly strong correlations between brain gene expression and microbiota composition, physical environment, age, and behavior became weak when controlling for the social environment. Consistent with this, a machine learning analysis revealed that from brain gene expression data, an individual's social environment can be more accurately predicted than any other behavioral metric. These results indicate that social environment is a key regulator of behavior and physiology.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Formigas / Microbiota Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals Idioma: En Revista: PLoS Biol Assunto da revista: BIOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Formigas / Microbiota Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals Idioma: En Revista: PLoS Biol Assunto da revista: BIOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Suíça