Presentations

Denis Noble
The principles of systems biology

The systems approach has now penetrated all levels of biology, from genes to the whole organism. Are there principles that unite all these areas of application? Or is Systems Biology essentially different in each case? Is it the next step in a progressive development of biology or does it involve a paradigm shift? These questions will be illustrated using work on the heart.
References:
Noble (2006) The Music of Life, OUP
Noble (2008) Claude Bernard, the first Systems Biologist, and the future of Physiology. Experimental Physiology, 93, 16-26

Douglas Kell
The cellular uptake of pharmaceutical drugs: a problem not of biophysics but of systems biology

90-95% of candidate drugs fail to progress to market despite favourable indications when assayed initially, a difficulty that costs billions and is referred to as 'attrition'. Largely it is due to the fact that drugs are assayed on molecular targets but either fail to work or are toxic in complex physiological systems. This makes drug discovery a problem of systems biology.
The cellular uptake of pharmaceutical drugs is widely assumed to be determined mainly by lipophilicity (the octanol:water partition coefficient log P), and thus to occur mainly by diffusion through the phospholipid bilayer portion of cellular membranes. This is also assumed to be true for 'pure' bilayer ('black') lipid membranes and liposomes. In these cases, however, transfer is via pore defects that do not occur in real membranes.
I review the considerable evidence for (and predictive power that derives from) the view that drugs are taken up via carriers that normally serve in intermediary metabolism, and describe a system in yeast for determining whihc ones are used. Our understanding is improving significantly as a result of the availability of network models of cellular metabolism ('digital organisms'), but until we have a full model that includes drug transporters we shall not be able to predict either drug efficacy or toxicity.

Béla Novák
Systems-level feedback control cell cycle progression

During the cell division cycle, cells replicate their DNA, segregate their replicated chromosomes during mitosis, and then divide into two daughter cells, which have all the information and machinery necessary to repeat the process. Repetitive cell cycles, which are essential to the perpetuation of life, are orchestrated by an underlying biochemical reaction network centered around cyclin-dependent protein kinases (Cdks) and their regulatory subunits (cyclins). Oscillations of Cdk1/CycB activity between low and high levels during the cycle trigger DNA replication and mitosis in the correct order. Based on computational modeling, we proposed that the low and the high kinase activity states are alternative stable steady states of a bistable Cdk control system. Bistability is a consequence of system-level feedback (positive and double-negative feedback signals) in the underlying control system. We have also argued that bistability underlies irreversible transitions between low and high Cdk activity states and thereby ensures directionality of cell cycle progression. I will review experimental evidence for bistability in the Cdk control network of budding yeast. In particular, I will show that irreversibility of mitotic exit depends on system-level feedback rather than on degradation of the cyclin B subunit, as often claimed. Cyclin degradation per se is neither necessary nor sufficient for irreversible mitotic exit.

Hub Zwart
Nature is wont to hide herself: are we about to unveil the complexities of life?

The recent history of biology builds on a number of important highlights. The term biology was introduced in 1800 by Lamarck to replace the more traditional “natural history” approach. Biology was becoming a comprehensive and experimental science. Mid-way the 19th century, Darwin introduced his theory of evolution. The year 1900 was the year of genetics (the rediscovery of Mendel) and of biotechnology (Loeb). And mid-way the 20th century, molecular biology resulted in the discovery of the structure of DNA (Watson&Crick). Finally, the year 2000 was the year of genomics and of the human genome sequence. At last, so it seems, we are about to develop a comprehensive view on living nature, both on the micro-level of genes and molecules, as on the macro-level of organisms and ecosystems. As is indicated in the NCSB research programme, systems biology (SB) promises to do precisely that: to provide us with a comprehensive, even holistic understanding of living systems. SB is rapidly becoming a widely used scientific approach to understand biological complexity, the functioning of cells, organs and organisms. While genomics already entailed the use of immense collections of bioinformation, SB promises to take this development one quantum leap further, relying on computational and ICT strategies and technologies to collect, manage, screen and analyse enormous amounts of bioinformation. At present, however, SB is facing what the NCSB programme defines as the “complexity bottleneck”. Although the genomics era has resulted in an explosive growth of bioinformation, real breakthroughs in terms of applications are remarkably rare, in contrast to the high expectations initially raised, due to the extreme complexity of life. The amount of data is so overwhelming, and the complexities of living systems so bewildering, that the ability to really use these data collections in order to deepen our understanding and, from there, to employ these tools to address important scientific and societal issues are quite limited so far. Still, the new field triggers high expectations and, as a consequence of that, significant investments. In Germany alone, 230 million Euro has been invested in SB, on the basis of scenarios concerning its future value. In other words, SB is not only important in that it promotes a holistic, integrated view of life (including human life), but also insofar as it constitutes an experiment in science innovation and research management to live up to this promise.