How genetic, social, and evolutionary interactions shape the many levels of biological complexity
Author
Moreno Fenoll, ClaraAdvisor
Poyatos Adeva, Juan FernandoEntity
UAM. Departamento de Biología MolecularDate
2017-11-14Subjects
Biología molecular - Tesis doctorales; Biología y Biomedicina / BiologíaNote
Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Biología Molecular. Fecha de lectura: 14-11-2017Esta tesis tiene embargado el acceso al texto completo hasta el 14-05-2019
Esta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional.
Abstract
Interactions between genes, between social individuals, and between the results of
alternative evolutionary histories reflect the organization and context-dependent
properties of each respective level of biological complexity. Genetic interactions
modify the combined effect of two genes on the characteristics of an organism. Social
interactions develop when some individuals of a population contribute to a common
resource at a personal cost. Evolutionary interactions result when adaptation to a
particular environment changes survival in unrelated conditions. We studied these
three types of interactions with a combination of computational and experimental
approaches using microbes. First, we evaluate the stability of interactions between
metabolic genes upon changes in the genetic background. We compared the genetic
interaction networks of an in silico model of Saccharomyces cerevisiae in two types
of backgrounds: single deletions and accumulation of neutral mutations. Network
rewiring was strongly associated to catabolic genes, revealing that they can add to an
organism’s growth in different configurations thus buffering genetic perturbations.
Neutral deletion backgrounds greatly reduced both this genetic buffering and the
ability to grow on alternative nutrients, connecting both environmental and genomic
robustness. Second, we tracked the sustainability of a microbial community where a
social cooperative interaction is essential for survival. Non-cooperative individuals
tend to appear and threaten the collective effect by exploting cooperators. Using an
engineered interaction between two strains of Escherichia coli we show how feedback
between population and evolutionary dynamics, combined with spatial structure,
can create a context where invasion by non-cooperators instead preserves the social
behavior. We further analyze how the molecular implementation of a social interaction
can modify such dynamics, on the synthetic E. coli system and in the natural
production of an iron-scavenging molecule by Pseudomonas fluorescens. Third, we
assessed the predictability of the effect of an organism’s prior history on its reaction
to a novel environment. We contrasted the evolutionary interaction networks
associated to the adaptation of a laboratory strain of E. coli to different antibiotic
classes. Acquiring resistance to the same drug could nevertheless result in different
responses to an alternative compound, including opposite effects on survival. We
discuss how a combination of genomic architecture and historical contingency can
produce these contrasting outcomes.
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