The ESF meeting on Systems Biology, organized by Luis Serrano and Ruedi Aebersold, took place last week in Sant Feliu de Guixols, Spain. A lovely location (I took this picture with my iSight directly from my room...) for a small conference with a list of outstanding speakers. Together with the influence of the Mediterranean-Latin 'cultural jet lag' (understand: go to bed very very very very late), the stage was set for intense networking among the participants.
The meeting had a broad scope, and I think that the organizers did a very good job in covering the diversity of the field, form quantitative biology and mathematical modeling to network biology, large-scale phenotyping and synthetic biology. Even if I cannot summarize all the talks, here are some general impressions on some of the directions.
First, the 'systematic' branch of systems biology appears to be extending progressively to the cellular level, thanks to progresses in high-throughput imaging techniques and expression systems applied to mammalian systems. For example, large-scale sub-cellular (co-)localization of proteins are used to help deduce extensive maps of molecular interactions that underly the biological function of an organelle (Anthony Hyman), while the analysis of cell-to-cell variability in morphological or other cellular-level features reveals effects that would otherwise be undetectable (Lucas Pelkmans).
At the molecular level, the analysis of large biological networks (transcriptional, Luis Serrano; protein-protein interactions, Marc Vidal) is now progressing towards a large-scale analysis of the impact of perturbations of specific interactions ('edges') rather than the more conventional approach of looking at the absence/presence of individual 'nodes'. This emphasis on 'edges' is further illustrated by efforts in increasing the resolution of protein-protein interaction networks to the level of individual protein domains (Anthony Hyman, Marc Vidal).
The roles and consequences of biochemical interactions are seen somewhat differently by those who study quantitatively signal transduction mechanisms. There, great emphasis was put on the fact that seemingly simple biochemical interactions can result in surprisingly rich spatial and temporal behaviors (Boris Kholodenko) and that considerations of these dynamical aspects are crucial to provide fundamental mechanistic insights into the functions performed by signaling systems. As an example, the quantitative analysis of NF-kappaB signaling dynamics reveals that a sophisticated temporal code is used to discriminate between a variety of stimuli to achieve a stimulus-specific transcriptional response (Alexander Hoffmann).
Clearly, significant efforts remain to bridge large-scale 'systematic' systems biology to its small-scale 'quantitative' branch and one may at first wonder whether these two visions belong to the same field. A recurrent and potentially unifying theme was however that both approaches attempt to understand the relationship linking a biological function to the components of the system that performs this function. As nicely formulated by Tony Hyman, one of the key problems in (systems) biology is to understand how 'individuals' contribute to a 'collective behaviour' (Denis Noble also notes that the 'collective behaviour' can impact on the properties of 'individuals'). This view of systems biology has the advantage that it provides a similar objective for research applied at various scales (eg a cell, an organelle, a signaling pathway, a protein complex) without imposing arbitrary constraints in terms of experimental or computational approaches.
Engineering of biological systems able to perform a human-specified function is intimately related to advances in systems biology. An example of how system-level engineering is pushed to the limits was illustrated by Ron Weiss, who is progressively implementing cell-cell communication, information processing, and cell differentiation control circuits into mammalian stem-cells to ultimately enable rational 'programmed tissue engineering'. But these types of extremely complex circuits currently require enormous efforts and a major emphasis is to develop tools that allow proper engineering practice in biology. Such efforts are the most advanced for systems hosted in bacteria and Adam Arkin provided some spectacular examples of modular design and illustrated how well designed circuits (eg oxygen sensing module from a tumour-invading bacteria) can be rapidly re-used to enormously shorten the development time required to engineer new functions (eg artificial blood cell), without eternal tweaking and tuning.
On a more frivolous note, it did not take us too many glasses of wine at dinner, to start speculating with Hiroaki Kitano about mixing the Robocup and iGEM competitions to create a new 'bio vs nanomachine' league that would let nano-robots play against engineered microorganisms. As I said, we may not have had always enough sleep...
Gene duplications and mutations are central driving forces in the evolution of genomes. Genomes must be robust to such changes in order to be evolvable, and many studies have probed genome robustness using systematic gene knockouts or overexpression experiments. In a recent paper, Isalan et al. (2008) took a new approach to test the robustness of Escherichia coli gene circuitry by reconstructing gene duplication events by shuffling the promoter-ORF pairs for about 300 transcription factors and introducing 598 recombined pairs one-by-one into E. coli to rewire its transcriptional network. Surprisingly, ~95% of such additions are robustly tolerated, and some networks even exhibit greater fitness under various selection pressures. Moreover, the study shows that, in contrast to naive expectations, the introduction of positive or negative feedback loops has little effect on the protein expression levels of regulated ORFs.