PROJECT HIGHLIGHTS
- Current approaches to detect selection for resistance in the environment are flawed
- Our new approach is to use mathematical models to mimic the complex environment by building the complexity from simple laboratory-based parts
- And validate model predictions experimentally, in flume mesocosms and in rivers
Overview
Antimicrobial resistance (AMR) is a major public health threat. The environment plays an important role as resistant microorganisms are transmitted between people and animals through the environment; they also survive or thrive there and exchange genes.
One of the big debates is whether the low concentrations of antibiotics in the environment are selecting for resistance.
One approach to experimentally test this is to compete a ‘special pair’ of sensitive and resistant bacteria at a range of antibiotic concentrations in the lab, where their only difference is resistance so they share the same ecological niche. This is an accurate and sensitive method, but the conditions in the lab do not mimic the environment.
An alternative approach is to bring a complex sample from the environment into the lab and measure whether resistance genes are increasing at different antibiotic concentrations. This would seem to mimic the environment as a diverse community of bacteria is used, but the inevitable shifts in microbial community composition when incubating in rich media can result in increased resistance levels in the absence of selection.
We have a different idea, to use mathematical models based on results from simple lab experiments and then create the complexity in the model by including the effects of diversity, predation, low substrate concentrations etc, ultimately predicting at which concentration selection happens in the environment and also understanding the effects of the complications. This will be coupled with experiments under natural conditions to test and validate the model, in flume mesocosms that can mimic river conditions in the lab at UKCEH Wallingford and also in situ in rivers. For this, we will put the special pair in ‘cages’ (dialysis bags) so they cannot escape but are immersed in the environment and experience the same nutrient concentrations etc. as the other bacteria in the surrounding environment.
Such a validated mathematical model that can predict the risk of selection under environmental conditions is hugely important because it is impossible to expose thousands of different pathogenic and environmental bacteria with various (combinations) of resistances to many levels of hundreds of potentially selective antibiotics and other compounds under a variety of relevant environmental conditions.
Figure 1: (A, B) The AQUA-REP mesocosm facility at UKCEH Wallingford. (C) Dialysis bag ‘cages’ physically separate bacteria from the environment but allowing nutrients and antibiotics to equilibrate. (D) Schematic of dialysis bag setup in aquarium mesocosm including (1) floats, (2) wire mesh platform, (3) dialysis bags, (4) pump to chiller unit, (5) insulation/shading, (6) temperature & light logger and (7) pump for mixing. (E) Immersing dialysis bag racks in a river, floating and submerged.
Case Projects
This project does not offer a CASE studentship
Host
- University of Birmingham
Theme
- Climate and Environmental Sustainability, Organisms and Ecosystems
Supervisors
Project investigator
- Jan-Ulrich Kreft, j.kreft@bham.ac.uk
Co-investigators
- Susheel Bhanu Busi, SusBus@ceh.ac.uk; Mike Bowes, mibo@ceh.ac.uk; Daniel Read, daniel.read@ceh.ac.uk (all at UKCEH Wallingford)
How to apply
Each host has a slightly different application process.
Find out how to apply for this studentship.
All applications must include the CENTA application form.
Methodology
Guided by our experience with modelling selection for resistance in wastewater treatment plants, the doctoral researcher (DR) will build mathematical models simulating the fate of sensitive and resistant bacteria in rivers, including competition with a background microbial community, predation and other relevant processes, based on mechanisms and parameters from simple lab experiments. The DR will initially use differential equation models and then individual-based models that are better suited to understand the effect of biodiversity and stochasticity on outcomes.
The experimental part will be mostly based at UKCEH, where the DR will compete resistant with sensitive bacteria in dialysis bags to physically separate them from the background microbial community and enable their recovery for analysis, while exposing them to the same environment. In the UKCEH mesocosm facility, bacteria in the dialysis bags can be exposed to antibiotics and background community under environmentally relevant conditions. A similar dialysis bag set up can be immersed in natural rivers to match environmental conditions better but loosing experimental control over them (Figure 1).
Training and skills
Partners and collaboration
Possible timeline
Further reading
Further details and How to Apply
Any queries welcome, please contact Jan on j.kreft@bham.ac.uk
Dr Jan-Ulrich Kreft
School of Biosciences & Institute of Microbiology and Infection
The University of Birmingham
Edgbaston, Birmingham, B15 2TT, UK
Tel: +44 (0)7947812897
Email: j.kreft@bham.ac.uk
Web pages:
https://www.birmingham.ac.uk/research/centres-institutes/kreft-lab
https://more.bham.ac.uk/amrflows/
https://scholar.google.com/citations?user=hLRsYpsAAAAJ&hl=en&oi=ao
Dr Susheel Bhanu Busi
Head of Molecular Ecology
UK Centre for Ecology & Hydrology
Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
P: +44 (0)7407405176
Professor Mike J Bowes
Head of River Water Quality & Ecology
UK Centre for Ecology & Hydrology
Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
P: +44 (0)1491 692255
Dr Daniel Read
Science Director for the Environmental Pressures & Responses
UK Centre for Ecology & Hydrology
Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
P: +44 (0)1491 692644
To apply to this project:
- You must include a CENTA studentship application form, downloadable from: CENTA Studentship Application Form 2027
- You must include a CV with the names of at least two referees (preferably three) who can comment on your academic abilities.
- Please submit your application and complete the host institution application process via: https://admissions.bham.ac.uk/course-finder-landing-page/?code=LES068 Please select the PhD in School of Biosciences (CENTA) 2027 entry year Apply Now button. The CENTA Studentship Application Form 2027 and CV can both be uploaded to the Personal Statement section of the online form. In the funding section of the online form please select Research Council Funding and then choose Natural Environment Research Council (NERC). Please quote CENTA 2027-B05 when completing the application form.
