- Effect of biodiversity on fate of resistance plasmids: are there preferential transfer paths? How would that affect risk analysis?
- Can we predict persistence of resistance based on transfer rates and fitness costs? Or do we need to include co-evolution of plasmids and hosts?
- Is inhibition of plasmid transfer the most effective way to reduce resistance?
The widespread use of antibiotics in human and veterinary medicine and as growth promoters in agriculture has not only selected for resistance genes but also for plasmids carrying resistance genes. As a result, plasmids as vectors of resistance genes have become prevalent, enhancing the rate of aquisition and dissemination of any new resistance genes as soon as new antimicrobials are introduced. Likewise, the simultaneous or alternating presence of several antimicrobials has selected for insertion sequence elements (IS) and other mobilizers of genes as they facilitate the accumulation of multiple resistances on single plasmids. Together, this has increased the potential for pathogens to aquire new resistances and new combinations of resistances. Multidrug resistant pathogens have brought us back to the pre-antibiotic era.
Hotspots of resistance genes in the environment are wastewater treatment plants and animal manures and slurrys on farms, which are being spread on arable land. Runoff from these fields and effluent from wasterwater treatment enter rivers and river sediments, also untreated sewage is discharged into rivers through storm overflow drains.
The group of Prof Wellington has isolated numerous Escherichia coli strains from river sediments. They carry a range of different types (IncF, IncA/C, IncQ) of plasmids with various resistance genes, eg the extended spectrum beta-lactamase blaCTX-M-15. Most of these strains are commensals but more than 10% carry virulence genes and resistance plasmids and are well known pathogens such as ST131, a common cause of urinary tract infections in hospitals, clearly linking human pathogens to environmental reservoirs.
We will use simple mass-action and more powerfull individual-based models to understand and predict the fate of resistance plasmids in mixed communities of several E. coli strains. The models will be based on plasmid transfer rates and fitness costs measured by a MIBTP PhD student in the Wellington lab (Victoria Clark) who has just started to investigate plasmid dynamics in chemostats and is co-supervised by Dr Kreft. She will be one year ahead of this joint modelling project, which will enable the modelling to feed into the experiments and the data to feed into the modelling.
The modelling will be based on our investigation of the competition of Narrow Host Range (NHR) and Broad Host Range (BHR) plasmids both with mass-action and individual-based models. We find that BHR plasmids have an advantage in multi-species communities despite their higher fitness costs but that they help the persistence of NHR plasmids by infecting the strains competing with the strains that the NHR plasmid can infect (Figure 1).
Individual-based models have a number of advantages, most importantly for this study they can encompass the presence of an indiviual plasmid in an individual host cell facilitating the modelling of co-evolution of plasmid and host, as well as transfer to another particular host.
The data will come from chemostats, where cells can be grown at lower growth rates relevant to river sediments and the gut. Growth rates in typical batch cultures are far too high to be relevant for the environment.
Training and Skills
CENTA students are required to complete 45 days training throughout their PhD including a 10 day placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to the student's projects and themes.
The Doctoral Researcher (DR) will acquire a broad set of mathematical modelling and statistical data analysis skills within an interdisciplinary project. The DR will learn to communicate and collaborate with an experimental DR, where the modelling will require certain data and generate predictions to be tested in the lab. The modelling will also guide experimental effort by identifying the most important parameters and processes.
Moreover, the DR will have the opportunity for public outreach activities to inform the AMR debate with the results of our project. Programming (Java, Matlab, Python, R), project management and communication skills will also be gained.
Year 1: Learn modelling of plasmid dynamics by expanding the existing model with co-evolution of plasmid and host reducing the fitness cost of the plasmid over time. Learn the possibilities and limitations of the experimental work so that the modelling reflects what can be measured. Use data already available to parameterize the model and learn how to do this. Perform sensitivity analysis to identify most important parameters and processes feeding into the lab work.
Year 2: Use and further develop the models to investigate the effect of increasing diversity on the persistence of plasmids in the absence of selection. Investigate the effect of growth rate (which can be controlled in the chemostats) on plasmid dynamics. Select some of the model predictions for experimental testing.
Year 3: Investigate the effect of co-evolution and antibiotic selection on the spread and persistence of plasmids. Investigate potential mitigation mechanisms such as reducing antibiotic concentrations during sewage treatment, inhibiting horizontal transfer of plasmids or using CRISPR or other mechanisms to get rid of plasmids, avoiding co-selection by mixtures of antibiotics and/or heavy metals. Inform risk analysis – how likely is it that pathogens aquire resistance genes in the environment? Is it more or less likely at lower growth rates?
Partners and collaboration (including CASE)
The Kreft group has >15 years’ experience in individual-based and other kinds of mathematical modelling. Current research includes modelling plasmid dynamics (Zhang et al., in preparation) and investigating the fate of resistance on a dairy farm (Kreft is Co-I on the NERC AMR-in-the-real-world grant “EVAL-FARMS”).
The Wellington lab has isolated a host of E. coli strains with various plasmids and resistance genes from river sediments. These genome sequenced strains are currently being investigated in chemostats by the joint PhD student Victoria Clark.
There is strong potential for conversion to CASE that will be pursued before project start.
Dr Jan-Ulrich Kreft
School of Biosciences & Institute of Microbiology and Infection & Centre for Computational Biology
The University of Birmingham
Edgbaston, Birmingham, B15 2TT, UK
Tel: +44 (0)121 41-48851
Professor E M H Wellington
School of Life Sciences
The University of Warwick
Coventry CV4 7AL, UK
Tel: +44 (0)2476 523184