The transfer of biological and natural world phenomena via algorythms into computing and autopoietic systems is a core challenge for OPAALS. Here, some of those involved in this work report on key aspects and their approach to providing a common framework, largely inspired by systems theory, that will help organise the research of the project in both its social science and computer science domains.
1. Experimental work on the p53-mdm3 regulatory cycle
p53 is perhaps the most important and best characterised tumour suppressor protein. As such, its primary function is to stop proliferation and/or kill damaged cells. Hence, its levels and activity are tightly regulated through a negative feedback loop mechanism. p53 is known to induce the synthesis of its negative regulator mdm2. mdm2, which itself has a very short half-life, interacts with p53 and functions as an E3 ubiquitin ligase that promotes the conjugation of p53 to ubiquitin. This modification effectively targets p53 for degradation. Contributing to its 'anti-p53' function, mdm2 is also thought to impair the activity of p53 by masking its transactivation domain. In response to stresses (e.g. DNA damage) the interaction of p53 with mdm2 is impaired and p53 accumulates leading to a halt on cell proliferation or to the induction of cell death by apoptosis. Furthermore, p53 levels have been shown to oscillate in response to DNA damage. Whether these oscillations are digital is still a matter of debate.
We have identified a series of mdm2 mutants that are deficient at degrading p53. As mentioned above, mdm2 levels are increased through p53âs ability to increase Mdm2 gene expression. Additionally, mdm2 levels can be increased through the simple interaction of p53 with mdm2. Supporting this, small molecules that mimic p53 binding to mdm2 lead to an elevation in mdm2 levels. We observed that unlike the levels of wild type mdm2, the levels of the mdm2 mutants we study are not effectively increased by interaction with p53. This implies that the interaction of mdm2 with p53 causes a conformational change or modification on mdm2 that protects it from degradation and that this change cannot occur with the mdm2 mutants.
By expressing this new concept mathematically we have developed a set of equations that lead to an oscillatory behavior of p53 and mdm2 levels in response to stress. This oscillatory behavior is lost when we the term expressing the stabilization of mdm2 by its interaction with p53 is omitted.
|
 |
Image 1
Expressing increasing amounts of wild type mdm2 (wt mdm2) decreases p53 levels in cells. This decrease is significantly impaired when an mdm2 mutant (EVEmt) is used. Note that the levels of the mdm2 EVE mutant are lower than the levels of wild type mdm2. |
Image 2
mdm2 levels in cells are increased in the presence of nutlin-3, a small molecule that mimics the binding of p53 to mdm2. The levels of the mdm2 EVE mutant are less effectively induced by nutlin-3. b-gal is a control protein that does not respond to nulin-3 and is used to evaluate the quality of the procedure. |
2. SBML as a bridge between Systems Biology and Software Engineering
Biomimicry in engineering is a long established process, and probably started with Leonardo Da Vinciâs during the renaissance, with his flying machine designed around the anatomical structure of birds. Despite his genius it is still debated as to whether his flying machine would have flown, which provides a reminder that such research may not be a straight forward process.

Diagram showing the Biologically Inspired Design Process
Nature has been in the research business for 3.8 billion years and in that time has accumulated close to 30 million âwell adjustedâ?solutions to a plethora of design challenges that humankind struggles to address with mixed results. Biomimicry is an emerging discipline that seeks sustainable solutions by emulating natureâs designs and processes. There are some great opportunities to learn how Nature has designed elegant solutions for some tough human-made problems.
In the DBE project we researched using biomimicry in computing engineering to create the Evolutionary Environment Software Ecosystem, mimicking the processes of evolution and ecosystems to create an Ecosystem-Orientated Architecture (EOA). Despite its success, the key distinction between our software ecosystem (EvE) and a biological ecosystem could be stated succinctly as a lack of autopoiesis, which is a construct for self-organisation of biological ecosystems. To create a digital ecosystem that demonstrates autopoiesis, we will need to determine the design patterns of the autopoietic constructs and algorithms common to all biological ecosystems. "In software engineering, a design pattern is a general repeatable solution to a commonly occurring problem in software design. A design pattern is not a finished design that can be transformed directly into code. It is a description or template for how to solve a problem that can be used in many different situations. Object-oriented design patterns typically show relationships and interactions between classes or objects, without specifying the final application classes or objects that are involved. Algorithms are not thought of as design patterns, since they solve computational problems rather than design problems." Extending this concept, Biological Design Patterns (BDPs) will catalogue common interactions between biological structures using a Pattern-Orientated Modelling (POM) approach, which here will provide autopoiesos. These BDPs could eventually be applied to our software ecosystem to endow it with the same self-organising capabilities found in biological ecosystems, and one of the ways in which this will be evident will be the ability to apply the evolutionary process at a lower level of granularity than previously possible, i.e. the object and method level, instead of the service level as is currently done. We are currently focusing on intracellular behaviour for the BDPs of our interactive model of computing, because cells are fundamental to the autopoietic behaviour inherent in life, being the basic unit for the construction of all life and which operate almost entirely through the process of gene expression. Cells are the biological construct that most obviously show autopoietic behaviour, which is a process working similarly a multiple levels of scale, and so an understanding of cellular operations is a critical first step in providing an tangible understanding of autopeiosis. To this end we will develop a modelling framework based on the Systems Biology Modelling Language (SBML), which utilises a domain modelling methodology based on UML to represent biochemical pathways.
"This UML-based definition in turn is used to define an XML Schema (Fallside, 2000; Thompson et al., 2000; Biron and Malhotra, 2000) for SBML. There are three main advantages to using UML as a basis for defining SBML data structures. First, compared to using other notations or a programming language, the UML visual representations are generally easier to grasp by readers who are not computer scientists. Second, the visual notation is implementation-neutral: the defined structures can be encoded in any concrete implementation languageânot just XML, but C, Java and other languages as well. Third, UML is a de facto industry standard that is documented in many sources. Readers are therefore more likely to be familiar with it than other notations."
This framework includes a translator from the specified chemical reactions to the corresponding differential equations for the time-evolution of the concentrations of the reactants and products. Differential equation models can then be investigated in Mathematica and other similar packages. Whereas we hope that this approach will help UNIVDUNâs research in the modelling of cell regulatory cycles, the benefit arises mainly from the use of a domain modelling methodology that is based on UML. In other words, strengthening the formal and semi-formal language links between biology and software engineering.
3. Mathematical framework for interaction computing
We are examining some ideas related to the connections between cell biology and software security. This work is being done in collaboration with the BIONETS project ( www.bionets.org) where Daniel Schreckling, a researcher in software security from the University of Hamburg, is showing a similar interest to develop a biologically inspired mathematical framework for interaction computing. From the point of view of OPAALS, therefore, software security represents a potential field of application of the theory. The fact that Digital Ecosystems research is currently weak on security aspects makes this collaboration particularly welcome.
The bridge that we are in the process of building between these two very different fields relies on abstract algebra and logic and can be simplistically depicted as follows:
cell biology - algebra - logic - security
In this context security represents one of the possible applications of a formalism that we expect to be of wider relevance. When referring to biologically inspired computing, reliance on some kind of evolutionary framework tends to be assumed by default. Whereas biological evolution does represent an essential model for biologically inspired computing, in this work we are focussing on the âotherâ?function of DNA. By this we mean all the processes relating to the life of the individual organism, thus a better name could be âdevelopmentâ? or âmorphogenesisâ? or âgene expressionâ?
As noticed by Crick and Watson themselves, it appears that the DNA code has a non-trivial and non-random formal structure. In the last 20 years or so several models have been proposed, with the latest ones going beyond a Boolean algebra, to a Lie algebra. A Lie algebra is a vector space whose elements satisfy certain properties with respect to a binary operator called a âcommutatorâ? The DNA code of 64 codons is in fact a Galois field extension (and therefore a finite vector space) most of whose quotient fields provide taxonomies for well-known physico-chemical characteristics of the corresponding amino-acids. Foremost is hydrophobicity, which is directly related to protein folding structure, which in turn is related to protein function.
Our current activities are focussed on understanding the abstract algebra and its connections to non-standard logics. The objective is to reach a mathematical model that can formalise the stable interactive behaviour of the cell components into an organisationally closed system that represents the archetype autopoietic system (i.e. a stem cell). Because cell biology is fundamentally digital, our hope is that by formalising cell-biological structure and behaviour in this manner we will arrive at the Interaction Machine model of computation as the kernel of digital autopoietic systems.
4. In Principio Erat Verbum
In 1917, DâArcy Wentworth Thompson was appointed to the Chair of Natural History in St Andrews University. Thereafter, several times a day for the next 30 years, he passed through an archway which led both to the Bell Pettigrew Museum (where he worked) and to St Maryâs College. Above the archway are the words from the opening sentence of the gospel according to St Johnâs â?em>In Principio Erat VerbumââIn the beginning was the word.
We have to start with words because, otherwise, all will end in confusion. The OPAALS project brings together researchers and practitioners from a broad variety of disciplines. We all have our own specialist vocabularies: our discipline-specific words; our own specific meanings for words in common use. We each bring understanding of our own discipline and the potential to misunderstand, or entirely fail to comprehend, the disciplines of others. The clear definition of the terms used in biology, as it applies to the OPAALS project, has therefore been an important initial task for WP1 and the clear presentation of such definitions is an important component of our first deliverables (at Month 18).
Following the first review, the reviewers have asked for a paper that can serve a similar function to orient the project toward an overarching or we could even say archetypal model of an Autopoietic Digital Ecosystem. We expect this paper to lay the groundwork for a theory of autopoiesis in computing, which is likely to be based on some form of interaction computing. At the same time, the paper will also review and begin to assess the application of autopoiesis and systems theory to social science disciplines. Interestingly, such adoption by social science of concepts from second-order cybernetics has been strongest in the field of linguistics and philosophy of language. The strongly relativist philosophical stance upon which Maturana and Varela based their theory is in fact perfectly compatible with the inter-subjective construction of reality of social constructivism.
http://freethinkr.wordpress.com/2007/06/
http://en.wikipedia.org/wiki/Design_pattern_(computer_science)
http://sbml.org/specifications/sbml-level-2/version-1/html/sbml-level-2.html