ERC FUNDED PROJECTS

As evolutionary biologists we are of course motivated by the desire to gain further insight in to the evolution of natural populations. The main goals of this proposal are to (i) develop theory and methodology that will enable the identification of adaptively evolving genomic regions using polymorphism data, (ii) develop theory and methodology for the estimation of whole-genome rates of adaptive evolution, and (iii) apply the developed theory in two strategic collaborative applications. Capitalizing on recently available and soon-to-be available whole genome polymorphism data across multiple taxa, these approaches are expected to significantly improve the identification and localization of recent selective events, as well as provide long sought after information regarding the genomic distributions of selective effects. Additionally, through these on-going collaborations with empirical and experimental labs, this methodology will allow for specific hypothesis testing that will further illuminate classical examples of adaptation. Together, this proposal seeks to Describe Evolution with Theoretical, Empirical and Computational Tools (DETECT), seeking to accurately describe the very mode and tempo of Darwinian adaptation.

1 071 729 €

Start date: 2013-01-01, End date: 2017-08-31

Microbes play an important role in various aspects of our lives, from our own health to the health of our environment. In almost all of their natural habitats, microbes live in dense communities composed of different strains and species that interact with each other. As these microbes evolve, so do the interactions between them, which alters the functioning of the community as a whole. In this project, I propose to develop theoretical and experimental tools to study and control evolving interactions between cells and species living in microbial ecosystems. This will involve three main research objectives: first, we will couple theory and experiments to disentangle and characterise the social interactions between five bacterial species that make up an ecosystem used to degrade pollutants. Our second objective will be to use this knowledge to control this same ecosystem, by directing it toward increased productivity and stability. Finally, our third objective will be to “breed” novel communities from scratch using experimental evolution to promote cooperative interactions between community members and thereby increase productivity. This interdisciplinary and ambitious research will allow us to improve existing methods in pollution degradation, and to design new microbial communities for this and other purposes. More generally, our model system will provide an in-depth conceptual understanding of microbial ecosystems and their evolution, and the tools to investigate more complex microbial communities. My ultimate vision is to possess the technology to use microbial communities to degrade waste, generate efficient biofuels, and design customised treatments for intestinal diseases. This project promises to create the foundations needed to develop this technology, and open many exciting avenues for future research.

1 498 875 €

Start date: 2017-05-01, End date: 2022-04-30

With the advent of genome-scale sequencing, molecular phylogeny, which reconstructs gene trees from homologous sequences, has reached an impasse. Instead of answering open questions, new genomes have reignited old debates. The problem is clear, gene trees are not species trees, each is the unique result of series of evolutionary events. If, however, we model these differences in the context of a common species tree, we can access a wealth of information on genome evolution and the diversification of species that is not available to traditional methods. For example, as horizontal gene transfer (HGT) can only occur between coexisting species, HGTs provide information on the order of speciations. When HGT is rare, lineage sorting can generate incongruence between gene trees and the dating problem can be formulated in terms of biologically meaningful parameters (such as population size), that are informative on the rate of evolution and hence invaluable to molecular dating. My first goal is to develop methods that systematically extract information on the pattern and timing of genomic evolution by explaining differences between gene trees. This will allow us to, for the first time, reconstruct a dated tree of life from genome-scale data. We will use parallel programming to maximise the number of genomes analysed. My second goal is to apply these methods to open problems, e.g.: i) to resolve the timing of microbial evolution and its relationship to Earth history, where the extreme paucity of fossils limits the use of molecular dating methods, by using HGT events as “molecular fossils”; ii) to reconstruct rooted phylogenies from complete genomes and harness phylogenetic incongruence to answer long standing questions, such as the of diversification of animals or the position of eukaryotes among archaea; and iii) for eukaryotic groups such as Fungi, where evidence of significant amounts of HGT is emerging our methods will also allow the quantification of the extent of HGT.

1 453 542 €

Start date: 2017-07-01, End date: 2022-06-30

Animals harbor specialized bacterial communities in their guts, typically referred to as gut microbiomes. Despite the importance of gut microbiomes for host health, surprisingly little is known about their evolution. There is evidence that the complexity of the mammalian gut microbiome has emerged through the diversification of a few founder lineages. However, how lineages have diversified into discrete species and which underlying mechanisms maintain the diversity in the gut remains elusive. The current project will address these questions by studying the gut microbiome of honey bees. We have recently found that the eight dominant bacterial lineages in the honey bee gut have substantially diversified, which is a striking parallelism to the evolution of the mammalian gut microbiome. Moreover, we have established experiments to colonize microbiota-free bees with cultured isolates of divergent bee gut bacteria. This provides us with unique opportunities to study bacterial evolution in the gut in a simple and experimentally amenable system. The project is divided into four work packages addressing interconnected research questions of current biology: We will (i) determine the population genomic landscape of divergent gut bacteria, (ii) investigate whether bacterial diversification has resulted in competition or cooperation, (iii) discover novel mechanisms of bacterial interactions, and (iv) reveal how bacterial diversification impacts the symbiosis with the host. To this end, we will use a multidisciplinary approach combining comparative metagenomics, transcriptomics, metabolomics, bee colonization experiments, microscopy, bacterial genetics, and automated bee tracking. This project situated at the forefront of microbial symbiosis will provide groundbreaking insights into microbial evolution and ecology, gut microbiology, and honey bee health and biology.

1 499 462 €

Start date: 2017-03-01, End date: 2022-02-28