SANDPIT: Multi-scale dynamics and gene communities

Lead Research Organisation: University of Manchester
Department Name: Physics and Astronomy


Evolution has mostly been studied in the context of the higher organisms, where the transfer of genetic material is almost always from parents to offspring. However some years ago it was discovered that bacteria, by contrast, are able to transfer genetic material directly between individuals. The first type of transfer is called vertical and the second type horizontal. So when we talk about bacteria evolving, we are referring to the genes which they contain, and horizontal transfer is a way of changing this content. From the point of view of the genes, the bacteria are habitats where the genes can reside, just like an ecosystem such as a forest or lake is a habitat where plants and animals can reside. So while the survival and reproduction of genes and the bacteria they live in are related, the fact that genes are not bound to a specific organism means that their interests are not identical. So genetic material transferred between bacteria can evolve strategies that can either help or hurt the bacteria. These are referred to as mutualism and parasitism respectively. This means that the mechanism of natural selection may take place at two levels: at the genetic level and at the level of the organism, and that these may be in conflict with each other. This conflict is played out in the ways that the genes interact with each other, and how these interactions determine the properties of the bacterium in which they are found. Evolution is a process which is random, and there is evidence that randomness is important in the horizontal transfer of genes. The analysis of systems made up of a large number of interacting objects, which have a degree of randomness, is an important area of applied mathematics. So far, however, progress in analysing these systems mathematically has lagged behind their study using computer simulations. We propose to develop an appropriate mathematical analysis of horizontal gene transfer in bacteria. We will be guided by computer simulations and also by databases of the distribution of genes in a wide range of different organisms. The final theory, although developed for a specific biological situation, can provide a model for mathematical treatments of other interacting random systems, which are found widely in physical, biological, and social contexts. It will also address an important theoretical problem in biology. We have already referred to the fact that selection can happen at the lower (genetic) level and the higher (organism) level. There could in principle be more than two levels, leading to what is called multi-level selection. In this case entities (genes, bacteria,...) at each level can reproduce, mutate and compete with each other. We will also gain greater understanding of the way that genes in bacteria move around, and so gain some insight into the current diversity of bacteria which is observed. This should allow for the monitoring and managing of new infections and antibiotic resistance.

Planned Impact

One of the major challenges of the 21st century is to develop a more quantitative theory of the biological and social sciences. The physical sciences have been formulated in a mathematical way for centuries, but the nature of the biological and social sciences has made this process far more difficult. However, the development of computer simulations has pointed the way forward. The interaction of a large number of entities, interacting with each other at given rates - which is typical of problems in these fields - can be effectively simulated. This has yielded many useful insights, but in order to draw general conclusions, understand governing principles and generally make statements with some kind of universal applicability, the development of novel mathematical frameworks and calculational schemes is required. In fact, the majority of computer simulations can be reformulated in mathematical form: they are Markov processes (in a perhaps extended state space) in which a large number of agents interact according to specified reaction schemes. Thus a large class of problems may be reduced to the analysis of such systems. Of course, the generic problem is very complex and intractable, but the project we are putting forward covers a large sub-class of such problems, namely those where several levels or stages are involved. Typical of these systems are entities which cluster together in groups, with a dynamic assumed for both the individual entities and the groups. Moreover, there are feedbacks between the two levels. We believe that the work suggested in this project will enable us to develop mathematical techniques to study systems of this type, and thus lead to methods to analyse general multi-level systems. This should lead to insights, and have application to, a large number of biological and social systems that have a hierarchical structure. Evolution is at the heart of all biology, so improving our understanding of evolution has the potential to contribute to advancing almost every fundamental biological field: development, disease, immunity, healing, ageing, populations, ecosystems, etc. Many of the fundamental principles and theoretical constructs of evolution are based on studies of higher eukaryotes, where lineages and species are relatively well defined, and horizontal transfer is the exception, and representations of related families of organisms are appropriately represented by phylogenetic trees. Higher eukaryotes, however, represent only a miniscule fraction of life on earth. The tools and approaches that often are used to study the vast bulk of life may be inappropriate. For example, the observation that there are species of bacteria cannot be understood with eukaryotic approaches such as reproductive isolation. Unfortunately, we have not generated a sufficiently advanced alternative conceptual framework. This project is directed towards the aspects of bacterial evolution that are central to its difference from eukaryotic evolution. Insights that we draw from our study of these aspects will help to create this alternative framework. More specifically, the properties of biological systems are the result of the evolutionary process. Features can arise through many different mechanisms, including adaptation, neutral drift, hitchhiking, or as consequences of the evolutionary dynamics or of other evolutionary changes. Unravelling how and why these features emerged, and what that implies about the functional and physiological significance of these features, is often best addressed with models that capture the necessary salient aspects of this evolutionary process. Conversely, evolution occurs through the changes in assemblies of biological macromolecules. The nature of the evolutionary process cannot be understood without understanding the constraints imposed by the properties of these evolving systems, by the molecular processes available to the organisms.


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Description Antagonistic coevolution between hosts and parasites can have a major impact on host population structures, and hence on the evolution of social traits. Using stochastic modelling techniques in the context of bacteria-virus interactions, we investigated the impact of coevolution, across a range of models, on population genetic structure, and on the social behaviour of the host. We found that in some cases the interaction can prevent defector invasion, and can even allow migrant cooperators to invade populations of defectors.

Another topic that was investigated was the repression of competition by mechanisms of policing. General models on the evolution of policing have focused on the interplay between individual competitiveness and mutual policing, demonstrating a positive relationship between within-group diversity and levels of policing. We expanded this perspective by investigating what is possibly the simplest example of reproductive policing: copy number control among non-conjugative plasmids, a class of extra-chromosomal vertically transmitted molecular symbionts of bacteria. Through the formulation and analysis of a multi-scale dynamical model, we showed that the establishment of stable reproductive restraint among plasmids requires the co-evolution of two fundamental plasmid traits. Increasing levels of policing and obedience lead to improvements in group performance due to tighter control of local population size (plasmid copy number), delivering benefits both to plasmids, by reducing the risk of segregational loss and to the plasmid-host partnership, by increasing the rate of cell reproduction, and therefore plasmid vertical transmission.

Plasmids carry a wide range of genes that are often involved in bacterial social behaviour. The question of why such genes are frequently mobile has received increasing attention. We used an explicit population genetic approach to model the evolution of plasmid-borne bacterial public goods production. Our findings highlighted the importance of both transmission and relatedness as factors driving the evolution of plasmid-borne public goods production.
Exploitation Route This is a very active area of research. We have made a start in the modelling of several phenomena, but there are many extensions and improvements in the models then can, and we are sure will, be made.
Sectors Agriculture, Food and Drink,Healthcare

Description Our findings have not yet been used in an essential way, but plasmids remain important vectors for the spread of social genes involved in bacterial virulence thus an understanding of their dynamics is highly relevant from a public health perspective.
Description Self policing among non-conjugative plasmids: The evolution of copy number control 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? Yes
Geographic Reach International
Primary Audience Participants in your research or patient groups
Results and Impact Talk in Institute for Evolution and Biodiversity, School of Biol.Sciences, University of Muenster.
Year(s) Of Engagement Activity 2012