Genomic sequencing methods have revolutionized the way we understand biology. Comparing the genomes of different organisms allows us to understand what distinguishes each species, its adaptation to the environment, and even its interaction with other organisms. However, given the enormous amount of data derived from genome sequencing, this type of comparisons is only possible through the use of computational methods (bioinformatics or computational biology). Morover, the recent application of massive sequencing techniques to the study of complete microbial ecosystems (metagenomics), has revealed an enormous diversity of unknown microorganisms, as well as a huge amount of uncharacterized genetic material.
Our laboratory pursues, precisely, to characterize the gene functions, evolution and ecological implications, of microbial communities (microbiomes). In particular, we use phylogenomic techniques to study processes such as the sub/neo-functionalization of genes, duplication, horizontal transfer, domain conservation and orthology detection.
At the metagenomic scale, we are interested in the functional characterization of microbial communities as a whole, in order to identify functional modules associated with specific environmental conditions. To do so, we combine evolutionary biology techniques, massive sequencing data and high performance computational resources.
Our current research lines are:
We analyze shotgun metagenomics data (soil, ocean, gut, etc.) to identify functional modules within microbial communities that might differentiate sample or environmental conditions. We are particularly interested in exploring the unknown fraction of those data (i.e. sequences with no homologs), currently accounting for 20-50% of the observed unigenes. Our ultimate goals are i) understanding the interactions of microbial communities with their environment, ii) identifying functional modules that can work as markers for specific environmental conditions, and iii) discovering novel gene functions with potential applications in biotechnology (i.e. novel enzymes).
Phylogenetic diversity within microbial communities
Metagenomics data are incomplete, noisy and quite challenging for classic evolutionary analysis. Our goal is to explore and characterize microbial (prok- and eukaryotic) biodiversity using bioinformatic methods. To this end, we work on the implementation and application of phylogenetic methods for taxonomic identification of metagenomic species, the integration of pan-genomic data, and strain resolution.
Evolution at the gene family level
We are interested in different aspects of gene family evolution, such as dating the emergence of specific functions, studying gene duplication, identifying horizontal gene transfers, or characterizing gene fusion events. We are specialized in large scale phylogenomic analysis, where hundreds of genomes can be compared at once. We apply those techniques to gain insights about the evolution of gene function and its relationships with ecological factors.
Phylogenomic methods and tools
We develop functional prediction methods, metagenomic frameworks, orthology resources and genomic databases. Many of those tools are the result of our own needs, but we also work on providing open source implementations that are useful to other researchers in the field.