Phd Studentship: Elucidating the transmission and persistence of antimicrobial resistance genes in

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 them. Mixtures of antimicrobials select for insertion sequence elements as they facilitate the accumulation of multiple resistances, increasing the potential for pathogens to acquire 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 slurries on farms, which are being spread on arable land. Runoff from these fields and effluent from wastewater treatment enter rivers and river sediments, also untreated sewage is discharged into rivers through storm overflow drains.
As partner of an international JPIAMR-funded consortium, we developed a mathematical model of AMR dynamics in wastewater treatment that makes a number of important predictions (Fig. 1). Our partner at Newcastle University (Prof Graham) is testing these predictions. We will be developing this single compartment model into a model of multiple compartments to understand AMR transmission from residential or hospital sewage via wastewater treatment into receiving rivers. Other partners are making measurements in Denmark, Spain and the UK. We are also partner in a NERC-funded project investigating AMR dynamics in dairy farms that can provide further data on slurries as a source of AMR genes.
The group of Prof Wellington in collaboration with CEH and Thames Water has been sampling 69 river sites along the Thames including tributaries to do qPCR and 16S rRNA amplicon and metagenome sequencing. The sequence data is being analysed in collaboration with Dr Quince. Both will be co-supervisors of the student. Amos et al. (2015) fitted a mostly statistical model to the data. Our aim is to use a mechanistic, mathematical model instead. Also, there are now a lot more data available.
In the project, the student will further develop our mathematical model to include AMR dynamics in rivers to generate a more complete catchment scale model and use a Bayesian framework to select appropriate model variants and infer parameters including their uncertainty. This can then inform risk analysis.
The Kreft group has >15 years' experience in mathematical modelling, including modelling plasmid dynamics, investigating the fate of resistance on a dairy farm and in urban waters in Denmark, Spain and the UK.
The Wellington lab has for many years driven forward the research on AMR dynamics in the Thames catchment with collaborators from CEH, Thames Water and others.
The Quince group is at the forefront of developing more rigorous statistical and bioinformatic algorithms e.g. for reconstructing genomes from metagenomes.
There is strong potential for conversion to CASE that will be pursued before project start (Thames Water, Environment Agency or DEFRA, AstraZeneca).
For further details, contact Dr Jan-Ulrich Kreft - j.kreft@bham.ac.uk

Funding Notes

CENTA studentships are for 3.5 years and are funded by NERC. In addition to the full payment of their tuition fees, successful candidates will receive the following financial support:

Annual stipend, set at £14,777 for 2018/19
Research training support grant (RTSG) of £8,000

 

References

Merkey BV, Lardon LA, Seoane JM, Kreft J-U, Smets BF (2011). Growth dependence of conjugation explains limited plasmid invasion in biofilms: an individual-based modelling study. Environmental Microbiology 13: 2435-2452

Hellweger FL, Clegg RJ, Clark JR, Plugge CM, Kreft J-U (2016). Advancing microbial sciences by individual-based modelling. Nature Reviews Microbiology 14: 461-471

Kreft J-U (2014). Mathematical modelling of plasmid dynamics. In: Bell E, Bond J, Klinman J, Masters B, Wells R (eds), Molecular Life Sciences: An Encyclopedic Reference. Springer-Verlag, Berlin Heidelberg

Kreft J-U, Plugge CM, Prats C, Leveau JHJ, Zhang W, Hellweger FL (2017). From Genes to Ecosystems in Microbiology: Modeling Approaches and the Importance of Individuality. Frontiers in Microbiology 8: 2299

Schmidt SI, Kreft J-U, Mackay R, Picioreanu C, Thullner M (2018). Elucidating the impact of micro-scale heterogeneous bacterial distribution on biodegradation. Advances in Water Resources 116: 67-76

Amos GCA, Hawkey PM, Gaze WH, Wellington EM (2014). Waste water effluent contributes to the dissemination of CTX-M-15 in the natural environment. The Journal of Antimicrobial Chemotherapy 69: 1785-1791

Amos GCA, Zhang L, Hawkey PM, Gaze WH, Wellington EM (2014). Functional metagenomic analysis reveals rivers are a reservoir for diverse antibiotic resistance genes. Veterinary Microbiology 171: 441-447

Amos GCA, Gozzard E, Carter CE, Mead A, Bowes MJ, Hawkey PM, Zhang L, Singer AC, Gaze WH, Wellington EMH (2015). Validated predictive modelling of the environmental resistome. ISME Journal 9: 1467-1476

Lehmann K, Bell T, Bowes MJ, Amos GCA, Gaze WH, Wellington EMH, Singer AC (2016). Trace levels of sewage effluent are sufficient to increase class 1 integron prevalence in freshwater biofilms without changing the core community. Water Research 106: 163-170