(BBSRC DTP) Modelling mechanisms of mutation rate plasticity

A BBSRC ENWW goal is “for researchers to routinely apply computational and mathematical techniques” to “enable a deeper and more rapid understanding of complex biological problems”. This is a primary goal of this PhD project. This project will couple computational simulations with wet lab studies, allowing them to inform one another. The proposal also fits within the integrative and systems biology priority area in that it will work between a computational model and wet-lab techniques to gain insight into the evolution of biological systems at different temporal and mechanistic scales.

The chance that an organism mutates, for instance that a microbe mutates to resist an antibiotic, can depend on that organism’s environment. We have recently discovered that the density of the population that an organism belongs to is closely associated with this mutation rate – high density populations of a wide range of organisms have roughly ten-fold lower mutation rates than sparser populations [1]. Genetic experiments give some clues as to how this comes about. It involves both proteins dealing with oxidatively damaged nucleotides in the cell [1] and, in the bacterium E. coli, cell-cell signalling and a gene involved in the activated methyl cycle [2]. The point of this project is to take these clues and put them together with known information about the processes involved, to create quantitative, dynamic models of mutational processes, and then to test them in the lab.

Density-associated mutation-rate plasticity (DAMP), as this phenomenon is known, has huge potential interest, for instance as a route to producing antibiotic adjuvants able to reduce the probability that organisms develop antibiotic resistance. But this will only become possible if we can determine the mechanism(s) by which it occurs. Focused experiments, for instance using alternative approaches to mutation rate estimation (e.g. [3]) will make it possible to test predictions from dynamic models and feed back into improving those models.

This interdisciplinary combination of in-silico and lab-based study of evolution, can provide new insights into how evolution works. This represents a unique opportunity for applicants interested in both computational biology approaches and lab work, and will allow the student to address fundamental questions of evolutionary biology, while training in computational and wet-lab techniques: a combination which will lend itself to multiple future career paths.

https://www.research.manchester.ac.uk/portal/Chris.Knight.html
https://www.research.manchester.ac.uk/portal/pawel.paszek.html
Project Outline
Mutation rate has long been appreciated as a fundamental factor in evolutionary genetics. In microbial pathogens, the issue of the evolution of antibiotic resistance has become a grand challenge. The de novo appearance of resistance mutations can play an important part in this process. Rates of spontaneous mutation can vary, both between and locally within genotypes. Variation of mutation rate at a particular site within a single genotype, i.e. mutation rate plasticity (MRP) is of particular interest, not least to evolutionary theory. MRP is known from stress-induced mutagenesis. However, its control by other factors is less well characterised. We have found that in diverse organisms (both bacteria and eukaryotes), the mutation rate to antibiotic resistance is plastic and inversely related to population density: lowering the density can increase the mutation rate by an order of magnitude. This plasticity is genetically switchable, dependent on the several genes we have identified in the lab and acts socially, via cell-cell interactions.

We are developing genetic insights into these processes, opening the possibility of putting the pieces together into systems biology models. Creating and then testing these models will be the role of this studentship.

The student will be able to ask:

• Are plastic mutation rates borne out by multiple empirical approaches? • Which networks are necessary and sufficient to generate the observed plastic mutation rates? • What testable predictions are made by these models?

These questions will be asked via a series of specific objectives: • Develop dynamic computational models of mutation generation • Measure mutation rates in microbial populations using sequence-based approaches • Test specific knock-out strains to test predictions of empirical models.

This project involves both computational (dry-lab) and wet-lab aspects. The expectation is roughly a 70:30 split between the two. However, the ratio may readily be adapted to the skills and interests of the student. The training provided will be multi-disciplinary, as reflected in the wet-dry and crossfaculty supervision arrangements:

Multidisciplinary training: Computational modelling (Paszek and Knight) Wet-lab microbiology skills (Krašovec and Knight) Statistics and mutation rate estimation (Knight)

Chris Knight has a group focused on Evolutionary Systems Biology, including both wet-lab (mostly microbial) experimental work and computational aspects. This is currently funded primarily by the BBSRC. Rok Krašovec Is the lead author on the publications initially identifying density associated mutationrate plasticity. He currently holds an independent position within FBMH. Pawel Paszek Having held a BBSRC David Philips fellowship, now leads a group concerned with systems biology modeling of cellular systems.