The MIRI project is funded by the French National
Research Agency (l'Agence Nationale de la Recherche), the ANR, a
public institution for the management of administrative issues, that
was created on January 01, 2007, and is a funding agency for
research projects. MIRI is funded for 4 years starting from Jan. 1st
2009. It has a single partner, the
BAMBOO Team, headed by
Marie-France Sagot, also coordinator of MIRI.
The huge variety in the types of close and long-term relations observed between
different species, the so-called symbiotic relations that involve a
symbiont and its host, is mirrored
by a huge variety of genomic and biochemical landscapes inside the
symbiont world, and at the interface between symbionts and hosts. The
purpose of this project is to combinatorially explore those landscapes
at the molecular
level, that is at the level of the genome and of two of the main types of
biochemical networks that may be reconstructed from the sequenced
genomes of symbionts and hosts. Such networks are the metabolic
and protein-protein interaction (PPI) networks. The final objective is
to try to relate the contours of the landscapes to the modus operandi of the
symbiotic relation, thereby offering a hope of better understanding the
latter, in particular its evolution.
The symbiosis issue is vast and complex. The MIRI project will focus
first on two questions concerning the evolution of symbionts,
one at the genome level, namely the studies of rearrangements, and one
at the biochemical network level and interface between genome
and network. The evolution of symbionts may be largely dependent on
the evolution of their hosts. In a third part of the project, we
therefore address the question of the evolution of the
intimate relations themselves by studying the co-cladogenesis
(co-speciation) of hosts and symbionts, and more generally their
co-evolution, that is the mutual evolutionary influence they exert on
each other.
Graph (tree) combinatorics and algorithmics underlie each of these
problems, as well as issues related to random graph enumeration under
certain models to improve confidence in the evolution and co-evolution
scenarii inferred.
