Spatio-temporal dynamics of mutation avoidance and antimicrobial resistance

Lead Research Organisation: University of Manchester
Department Name: School of Biological Sciences

Abstract

Spontaneous mutations are the basis of evolutionary innovation. They are also central to diseases in higher organisms and the root of some of the most pressing medical problems that we face: antimicrobial resistance and cancer.

Mutations are usually detrimental for microbial cells. Therefore, cells have evolved to control mutations very tightly and DNA mutation rates are remarkably low. Yet mutations can be beneficial, for instance, a single point mutation in the right gene helps a cell to gain antibiotic resistance. Cells thus need mutations but just not too many.

We need deep understanding of how the number of mutations fluctuate with the internal and external cellular environment. Addressing such dynamical aspects of mutations in the natural environment is vital for understanding the survival, adaptation and evolution of all cells.

My previous work found that the rate of mutations is regulated by the environment associated with the cell-density: mutation rates decrease in dense populations up to 20-fold. Specifically, I discovered that crucial effectors of this environmental dependence of mutations are enzymes that enable cells to avoid mutations.

In this Fellowship I shall observe mutations in individual microbes growing in their native environment, community. Only studying individual cells growing in a dense community will give us an understanding of mutation dynamics in the real-world.

To accomplish my aims, I will combine live fluorescence microscopy, microfluidics, statistical modelling and interact with outstanding researchers from other disciplines.

I shall use the Escherichia coli K-12 model system and observe mobility of DNA repair proteins, which will enable me to count mutations in individual cells. This will tell us about cell-to-cell variation in the number of mutations and how such a heterogeneity depends on micro-environments generated in the community.

I will also quantify the molecular diffusion of mutation avoidance protein MutT in these micro-environments. I will establish the potential link between MutT dynamics and downstream processes involved in the generation of mutations.

I will do all this not only in cells during normal community growth, but also in cells that survive the antibiotic treatment without obtaining the genetic resistance. These tolerant and persistent cells start to divide again, after the antibiotic is removed. My study will determine dynamics of mutations in these survivor cells and how micro-environments, generated in the aftermath of the antibiotic treatment, affect their fate.

Understanding factors that affect a cell's capability to avoid and repair mutations is essential to better predict the development of mutation-based resistance in microbial communities and to exploit that understanding to combat antimicrobial resistance.

Generated knowledge, in years 1-4, will be used in years 5-7 to test how various drug candidates impact the mutation dynamics and fate of cells that survive antibiotic treatment. I will also apply these developed experimental approach to more clinically relevant strains.

Planned Impact

Who will benefit from this research and how?

The Fellowship shall transform the way we see a fundamental process of life, spontaneous mutation, using a microbial model system. Mutations impact society at a range of levels, from the development of antimicrobial resistance in clinical or livestock settings to the adaptation of agricultural soil microbiota to environmental change. This work is transformative of our understanding of the interplay between single-cell dynamics and evolution, understanding mutation as a dynamic, environmentally plastic trait. Its findings will therefore be of wide importance, well beyond the academic fields of those involved.


In particular, the following non-academic groups will benefit:

Healthcare professionals: Awareness of the antimicrobial resistance crisis is broad, but understanding of its causes is currently very limited. Healthcare professionals will benefit from increased understanding of spontaneous antibiotic resistance, which may lead to potentially resistance-suppressing antibiotic adjuvants.

General public: Public have frequently personal interest in combating disease and antimicrobial resistance and they have a real fascination with videos of living cells. My work is an ideal subject to engage in dialogue about antimicrobial resistance, single-cell dynamics and evolution, reinforcing and feeding these interests, thus promoting an interest in science generally.

Biotechnology companies: I aimed to develop links with biotechnology companies to determine if there are commercial applications for Fellowship's results.
 
Description Interdisciplinary PhD studentships in Modelling, AI and Big Data
Amount £15,000 (GBP)
Organisation University of Manchester 
Sector Academic/University
Country United Kingdom
Start 09/2022 
End 02/2026
 
Description Sequence-specific tracking of double-stranded DNA molecules in live bacterial cells
Amount £9,631 (GBP)
Organisation University of Manchester 
Sector Academic/University
Country United Kingdom
Start 02/2022 
End 07/2022
 
Title Single-molecule fluorescence and microfluidics 
Description In a process of setting up my lab I purchased new equipment needed for manufacturing microfluidic devices, that included plasma cleaner, various pumps, oven and microfluidic wafers that were originally designed by my collaborators from ETH Zürich. I recruited a postdoctoral researcher Dr Raveen Tank, she started to work on 1 January 2021, and a technician Dr Andrew Angus-Whiteoak (his post started on 1 June 2021). We are now able to routinely manufacture PDMS microfluidic devices with chambers that have different shapes and opening sizes. The device is adhered to a microscope slide with a plasma cleaner, which is then combined with a Leica Total Internal Reflection Fluorescence (TIRF) microscope located in the Bioimaging facility. We managed to reduce the background noise by photobleaching the background before doing the experiment and adding small amount of fluorescence quencher TrueBlack into PDMS. We significantly increased the signal by acquiring a cutting-edge camera Hamamatsu Fusion BT. We also managed to significantly decrease the movement of cells within a chamber using Cell-Tak. We also found an efficient solution to the problem of confining cells in this very small chambers covered with Cell-Tak. We use a spinner with a custom designed elements on it, which applies a centrifugal force that push cells into chambers but not destroy the microscope slide. In 2021 we collected first single molecule tracks of the DNA repair protein MutS (labelled with photoactivatable PAmCherry) in Escherichia coli AB1157 strain. This MutS-PAmCherry strain was a kind gift of its creator Stephan Uphoff and it still contains a kanamycin resistance. This allowed us to use the P1 transduction protocol to transduce MutS-PAmCherry fusion into different E. coli strains, wild-type and single-gene knockouts, all relevant for the density-associated mutation rate plasticity (the phenomenon that FLF is focused on). We have so far collected >2Tb of images and videos from all these strains growing at low and high density within a microfluidic chamber. For now we analyse MutS tracks in individual cells using a software called SMTracker. However in March 2022 I started the collaboration with the IT research team (from the University of Manchester) that will result in a custom MatLab code that will enable us to do much more efficient image analysis (a marriage of a cutting-edge segmentation and single molecule tracking tools). 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? No  
Impact We are using single-molecule fluorescence and microfluidics to image DNA repair, which enable us to quantify mutations in individual cells growing in communities with different cell densities (allowing us to test Fellowship's hypotheses H1a and H1b).