It is widely assumed that a General Election will be called for early May (and must in any event be called by early June), and one consequence is that all parts of Government, including ‘arms length bodies’ such as BBSRC, will, during the election period, have to follow strict rules to ensure they do not do anything that could be perceived as party political e.g. announcing new initiatives, commenting on activities etc.

In Whitehall this period is known as Purdah, and this means that my BBSRC blog will be suspended between the announcement of the General Election and the formation of a new Government. This would include any period involving negotiations with minority Parties should no individual Party have an overall majority (i.e. a hung Parliament). I have not yet decided whether to blog on non-BBSRC topics in my role as a member of the University of Manchester elsewhere during this time, but if I do this blog will record that fact.

My first visit this week was a most interesting visit to the University of Durham, where we heard about a variety of research initiatives, including their Biophysical Sciences Institute and their Centre for Crop Improvement Technology. Subsequent meetings tended to cluster, as usual, around the issues of Food Security, Bioenergy/Industrial Biotechnology, Bioscience Underpinning Health, and Big Data – as parts of our Strategic Plan.

Food Security meetings included one of our biannual meetings with the Gatsby Foundation, the main funders of the Sainsbury Laboratory in Norwich, and a meeting with Dame Suzi Leather, present Head of the Council of Food Policy Advisers.

I am still thinking further about the recognition that one of the most effective ways to capture and sequester atmospheric CO2 is in long-rooted plants that additionally improve soil structure and aeration, and a timely meeting with Brian Collins (Chief Scientific Adviser at the Department for Transport and at BBSRC’s sponsor department the Department for Business, Innovation and Skills) (inter alia)) reinforced the potential importance of this area.

Biofuels are a complex area, but it is becoming clear that they can make a substantial contribution to UK transport fuel needs, not least because we have an existing infrastructure for purveying them. Bio-butanol holds interest for a variety of reasons.

We also recognized that manmade infrastructure-type networks were brittle as they tended to have been optimized for (short-term) effectiveness but not for resilience, whereas biological evolution with natural selection has led to network motifs that tended to favour resilience over speed and efficiency (an organism that is killed by a single mutation or point of failure has little chance of surviving – and there are plenty of mutations). Biology has much to teach to engineering design – albeit this is not a new concept.

As part of our concerns about how to transfer and analyse PetaBytes of genomics data, we had a useful meeting with JISC, who look after the SuperJanet network. It may be that transmitting data by using extra wavelengths down existing fibres can give us something closer to the kinds of bandwidth we shall need, and if this is true it may make these problems far more tractable (both financially and technically) than I had feared. We shall be initiating some experiments to find out.

We also had useful meetings with the Association of British Pharmaceutical Industries, where many of our scientific interests overlap, and I was pleased to attend the launch of the Society of Biology, with talks by Paul Nurse, David Attenborough and Ceri Harrop.

It is very important that Biology has a coherent voice, and the emergence of the Society will assist this considerably in demonstrating how the biosciences underpin the solutions to key global challenges such as food security. One area of interest lies in the accreditation of degrees, not least for an adequacy of mathematical content to prepare biologists for the Systems Biology agenda. That the voices of biology can have impact was exemplified by the announcement last week of £250M for the UK Centre for Medical Research and Innovation. I was also pleased to be invited to this year’s Science Foo camp, since last year I learnt a great deal and met many pioneering thinkers.

Last week also saw (wearing an academic hat) the sending off of a couple of papers I have co-authored: Systematic integration of experimental data and models in systems biology and Predictive models for population performance on real biological fitness landscapes.

The first involves Taverna workflows for effecting the automated construction of biochemical networks, and their parametrisation and testing using experimental kinetic data. (Considerable progress can still be made in the absence of experimental kinetic data.)  

The second involves the use of a kind of finite state machine (that we have previously called a Landscape State Machine) to model fitness landscapes and directed biological evolution. Analysing and navigating the model of the landscape is much more efficient than navigating the ‘real’ (in silico) one. And what can be evolved continues to impress and surprise – a wonderful recent example is the stunning work of Jason Chin and colleagues on the development and evolution of quadruplet-decoding ribosomes that can encode multiple unnatural amino acids, a feat that opens up many novel possibilities for bioengineering.

Alon U: An introduction to systems biology: design principles of biological circuits. London: Chapman and Hall/CRC, 2006.

Corne, D. W., Oates, M. J. & Kell, D. B. (2003) Landscape State Machines: tools for evolutionary algorithm performance analyses and landscape/algorithm mapping. In Evoworkshops 2003, vol. LNCS 2611 (ed. S. Cagnoni, et al.), pp. 187-198. Springer, Berlin.

Kell DB: Metabolomics, modelling and machine learning in systems biology: towards an understanding of the languages of cells. The 2005 Theodor Bücher lecture. FEBS J 2006; 273:873-894.

Lee SY, Park JH, Jang SH, Nielsen LK, Kim J, Jung KS: Fermentative butanol production by clostridia. Biotechnol Bioeng 2008; 101:209-228.

Neumann, H., Wang, K., Davis, L., Garcia-Alai, M. and Chin, J.W. (2010) Encoding multiple unnatural amino acids via evolution of a quadruplet-decoding ribosome, Nature, 464, 441-444.

Smallbone, K., Simeonidis, E., Swainston, N. and Mendes, P. (2010) Towards a genome-scale kinetic model of cellular metabolism, BMC Syst Biol, 4, 6. Full free pdf.

Vijg, J. and Dollé, M.E. (2002) Large genome rearrangements as a primary cause of aging, Mech Ageing Dev, 123, 907-915.

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