Susanna Manrubia
Group Leader
The main interest of our group is the theoretical study of evolutionary systems of different kinds. We develop models inspired by the phenomenology observed in natural systems, chiefly molecular populations, viruses, and interacting agents at the cellular level and up.
Publications
Aguirre J, Catalán P, Cuesta JA, Manrubia, S On the networked architecture of genotype spaces and its critical effects on molecular evolution. Open Biol 2018; 8: 180069.
Lucía-Sanz A, Aguirre J, Manrubia STheoretical approaches to disclosing the emergence and adaptive advantages of multipartite viruses. Curr Opin Virol 2018; 33: 89-95.
Iranzo J, Cuesta JA, Manrubia S, Katsnelson M, Koonin EV.Disentangling the effects of selection and loss bias on gene dynamics. Proc Natl Acad Sci USA 2017; 114: E5616-E5624
Yubero P, Manrubia S, Aguirre J. The space of genotypes is a network of networks: implications for evolutionary and extinction dynamics. Sci Rep 2017; 7: 13813.
Lucía-Sanz A, Manrubia S. Multipartite viruses: adaptive trick or evolutionary treat?. NPJ Syst Biol Appl 2017; 3: 34
The main interest of the group is the theoretical investigation of evolutionary systems of different kinds. We develop models inspired by the phenomenology observed in natural systems, chiefly molecular populations, viruses, and interacting agents from the cellular level and up. Our approach addresses either the study of fundamental properties of adapting systems –with a strong emphasis on their evolutionary origin-- or, at a more specific level, tries to reproduce and eventually predict the response of such populations to endogenous and exogenous change. In this context, we investigate the properties of the genotype-phenotype map through models such as the folded state of RNA sequences, focusing on the topological structure of neutral networks of genotypes and its relevance in adaptation and molecular innovation. Another main subject is the understanding of the survival strategies of viruses, among others the relevance of multipartite genomes or the ecological effect of viral satellites.
At a higher organisational level, we are also interested in the modelisation of the interaction between agents organised in networks that vie e.g. for resources, food, or mates, as competitive interactions represent one of the driving forces behind evolution and natural selection in biological systems. Finally, we explore the application of complex systems to biotechnology through the development of analysis techniques with environmental and health purposes. We have applied graph theory to antibody microarrays in order to improve the characterisation of experimental samples, with direct application to allergy control, toxin detection in fresh water ecosystems and planetary sciences. Our studies of viral response to antiviral treatments have determined optimal modes of drug administration to minimise viral load and mutant escape.
Slow environmental change, fast biological response. The genomic composition of populations (top) can undergo sudden shifts in response to smooth environmental changes (bottom) (modified from Aguirre & Manrubia, 2015)
The power of the weak. Cooperative interactions between two a priori weak populations can provide a collective advantage superior to direct alliances with a strong population (modified from Iranzo et al., 2016).
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