Measuring adaptation to extreme environments with a multi-omic approach

During the past decade, more than 4000 organisms have been subjects of
genome-sequencing projects. This has enabled the retrieval of information such as evo-
lutionary relationships among all living organisms, and the understanding of complex
phenomena, including evolution, adaptation, and ecology. Bioinformatics tools have
allowed us to perform genome annotation, cross-comparison, and to understand the
metabolic potential of living organisms. In the last few years, research in bioinfor-
matics started to evolve from the analysis of genomic sequences and structural biology
problems, to the analysis of complex post-genomic interaction networks. The main out-
come of this effort has been the creation of: (i) databases and ontologies of protein
class and cell components; (ii) repositories of models of cell processes, through the def-
inition of common exchange formats such as the Systems Biology Markup Language
(SBML); (iii) simulation tools; (iv) Multi-scale modeling (micro-macro biology). How-
ever, the following questions remain open: what is the real functioning scheme of the
cell? What is the metabolic influence of changes in gene expression? How to understand
the metabolic interactions among living organisms in a ecosystem? How to understand
evolutionary mechanisms of adaptation? Here, we describe a pipeline that summarizes
the methodologies recently proposed to address these questions.