Marie France Sagot, Universitè de Lyon and INRIA Rhone Alpes, France

Metabolic Networks and Their Structural Analysis
The literature on metabolism, more specifically the computational biology and bioinformatics literature has been increasing dramatically in the last few years, although not yet reaching the levels observed for the modelling and inference of regulatory networks. Metabolism appears to lack somewhat in sexyness in relation to regulation – after all much of it seems to be about chemistry rather than life, yet metabolism offers a particularly interesting perspective on the relation genotype-phenotype as well as on the relation living organisms have with their environment, which includes other living organisms.

The set of three lectures on metabolism that will be given at the 2010 School will focus on one aspect only of metabolism, namely on the structure of metabolic networks, and on the analysis of such structure to understand function and specially evolution.

The first lecture will concentrate on presenting the mathematical models that are used to represent metabolic networks, and how these models are built from, usually, genomic data. The latter will have as main purpose to illustrate the problems associated with such reconstruction from often partial or erroneous data. The lecture will also comment on some general, high-level analyses that have been done on the increasingly more numerous reconstructed metabolic networks. The main references for this first lecture will be Lacroix et al. [9] as well as parts of Heath and Kavraki [7], and of Knight and Pinney [8].

In the second lecture, we discuss the relation between metabolism and habitat, how this has been explored computationally in particular through the concepts of scope and precursor sets [3, 5, 6, 10], and what are the main biological results that the exploration has led to so far [1, 2, 4, 5]. Particular stress will be put on the case where the habitat is another living organism as happens in an endosymbiotic relationship (this refers to a relation between two organisms where one lives inside the other, sometimes even inside the cells of the other organism. We speak in the latter case of an intracellular endosymbiotic relationship. 

Finally, in the third lecture, we shall explore different ways of comparing metabolic networks that have been used in the literature. These include comparing general indexes, inferring conserved motifs, aligning networks, or measuring and comparing capacities (references to all of these may be found in the text and bibliography of [9]; the papers that will no doubt continue to appear in the meantime will also be covered as possible). All of these will be briefly surveyed, and some results presented and commented. We shall in particular discuss the notion of a minimal network, and whether this makes sense in light of some of the relationships observed between an organism and its inanimate or living environment.

All through the lectures, the issue of ascertaining whether an observed result is "unexpected" from a statistical point of view, and therefore potentially interesting for biology, will also be raised. We shall in particular see that the question of a good random model for metabolic network analysis remains largely open as of today.  

Main references

  1. E. Borenstein, M.W. Feldman (2009). Topological signatures of species interactions in metabolic networks. J Comput Biol. 16(2):191-200.

  2. N. Christian, T. Handorf, O. Ebenhöh (2007). Metabolic synergy: increasing biosynthetic capabilities by network cooperation. Genome Inform. 18:320-329.

  3. L. Cottret, P. Milreu, V. Acuña, A. Marchetti-Spaccamela, F. Martinez, M.-F. Sagot, L. Stougie (2008). Enumerating Precursor Sets of Target Metabolites in a Metabolic Network. In WABI 2008, Lecture Notes in Computer Science, vol. 5251, pages 233-244.

  4. S. Freilich, A. Kreimer, E. Borenstein, N. Yosef, R. Sharan, U. Gopha, E. Ruppin (2009). Metabolic-network-driven analysis of bacterial ecological strategies. Genome Biol. 10(6):R61.

  5. T. Handorf, N. Christian, O. Ebenhöh, D. Kahn (2008). An environmental perspective on metabolism. J Theor Biol. 252(3):530-537.

  6. T. Handorf, O. Ebenhöh, R. Heinrich (2005). Expanding metabolic networks: scopes of compounds, robustness, and evolution. J Mol Evol. 61(4):498-512.

  7. A. P. Heath, L. E. Kavraki (2009). Computational challenges in systems biology. Computer Science Review 3(1):1-17.

  8. C. G. Knight, J. W. Pinney (2009). Making the right connections: biological networks in the light of evolution. Bioessays. 31(10):1080-1090.

  9. V. Lacroix, L. Cottret, P. Thébault, M.-F. Sagot (2008). An introduction to metabolic networks and their structural analysis. IEEE/ACM Trans Comput Biol Bioinform. 5(4):594-617.

  10. P. R. Romero, P. Karp (2001). Nutrient-related analysis of pathway/genome databases.Pac Symp Biocomput, pages 471-482.