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Combining microfluidics and mathematical modelling to study interactions between individual bacteria

Primary Supervisor: Dr Jan Kreft, School of Biosciences

Secondary supervisor: Daniele Vigolo, Chemical Engineering

PhD project title: Combining microfluidics and mathematical modelling to study interactions between individual bacteria

University of Registration: University of Birmingham

Project outline:

The rise of antimicrobial and antibiotic resistance threatens our ability to cure infections. If we do not tackle this crisis, we may return to the death toll of the pre-antibiotic era.

One important way to tackle the AMR crisis is to improve our understanding of the factors influencing the spread and evolution of resistance gene carrying plasmids in order to be able to predict and control this risk.

Another is to develop alternatives to antibiotics. We have been working with the bacterial predator Bdellovibrio bacteriovorus, which is an alternative to phage therapy with three important advantages: rather than being prey specific like a phage, Bdellovibrio can kill a broad range of Gram-negative bacterial prey. It can also kill non-growing prey. Also, prey do not become resistant via simple mutations.

What these two topics have in common is the methodology as we will be constructing microfluidic interaction arenas to study either plasmid transfer and fitness costs or predation on the level of individual bacteria under controlled conditions. We can observe and track many individual cells (as well as populations) in the channels or chambers of the microfluidic device under a microscope and then use image analysis to measure e.g. growth rates, plasmid transfer rates or predation rates. Using these measurements of many individual cells we will then construct individual-based mathematical models that are the best way to capture the observed interactions between bacteria. These models will then predict the effects of individual interactions on the population level, predictions which will be tested with dedicated experiments on the larger scale of populations or communities. We have dubbed this approach ┬ÁIBE for microbial Individual-Based Ecology. The key points are that no two bacteria are identical and that local interactions between unique individuals, spatial structure and stochastic events make the dynamics on the population or community level different from what you would get when all cells were identical and would encounter each other randomly.

For the plasmid work, our hypothesis is that fitness costs of plasmids and plasmid transfer rates are affected by the growth rate and physiology of individual cells and the diversity of the microbial community. With the microfluidic device and individual-based modelling we can study the cell-to-cell variation of fitness costs and plasmid transfer rates. Fitness costs are typically measured for populations growing under optimal conditions, that is, at high growth rates. We do not know whether fitness costs will be different when cells grow more slowly but this could have huge consequences. What we do know is that bacteria grow much more slowly in their natural environment than under optimal conditions: E. coli has a doubling time of about 24 hours in the gut. It may also be that individual cells with higher fitness costs have lower antibiotic sensitivity. There is a lot we do not know and the methodology in this project will be able to address many fundamentally important and clinically relevant questions.

For the predator work, our hypothesis is that Bdellovibrio has genetically encoded prey preferences that will have important consequences for applications in agriculture and aquaculture where the predator is facing a choice between different prey but we want it to kill the pathogen or antibiotic resistant cell we target. Giving the predator the choice to enter microfluidic chambers with different single or mixed prey will enable us to shed light on this question.

There is a host of opportunities to go beyond the state of the art. We have developed some prototype microfluidic devices with the help of project students and visiting scientists and the PhD student would have the opportunity to develop new designs and optimize them. The specific topic for the PhD will be decided in consultation with the student and consider progress on those topics in our labs until project start in Oct 2021.

References:

  1. Hellweger FL, Clegg RJ, Clark JR, Plugge CM, Kreft JU (2016). Advancing microbial sciences by individual-based modelling. Nature Reviews Microbiology 14: 461–471.
  2. Hol FJH, Dekker C (2014). Zooming in to see the bigger picture: Microfluidic and nanofabrication tools to study bacteria. Science 346: 1251821.

BBSRC Strategic Research Priority: Sustainable Agriculture and Food: Microbial Food Safety

Techniques that will be undertaken during the project:

  • Design, manufacture (i.e., soft-lithography) and operation of microfluidic devices.
  • Automated microscopic imaging (including fluorescence and phase contrast) and image analysis.
  • All optical velocimetry technique to evaluate the flow field within the microfluidic device (Ghost Particle Velocimetry).
  • General laboratory and microbiological methods.
  • Molecular microbiology and strain construction.
  • Individual-based modelling.
  • Statistics.

Contact: Dr Jan-Ulrich Kreft, University of Birmingham