Overview

I am a NERC Independent Research fellow and my research is broadly interested in understanding how microbial communities respond to environmental change. Specifically, my fellowship is exploring whether climate change will worsen the problem of antibiotic resistance. To do this, I use a variety of sequencing, experimental, and modelling approaches.

I am also committed to reproducible and open science. All of the code and data from my projects are freely available online through GitHub and archived on Zenodo.

I have been using R for >10 years and authored and maintain the R packages nls.multstart and rTPC and specialise in the wrangling and manipulation of large datasets and statistical analyses. I am also a bioinformatician, processing and analysing everything from 16S sequencing to de novo genome assembly, the latter using bash. Basically a bit of jack-of-all-trades master of none!

Qualifications

PhD., Biological Sciences 2013-2017 Environment & Sustainability Institute, University of Exeter, Cornwall, UK.

The direct and indirect effects of warming on aquatic metabolism

Combined ideas from metabolic theory with a variety of experimental approaches to further our understanding of how warming will impact photosynthesis and respiration across different temporal and organisational scales.

MBiolSci., Zoology 2008-2012 Animal & Plant Sciences Department, University of Sheffield, UK.

First class degree honours. Bergmann’s rule in fish in the North Sea: a snapshot from a single year and a temporal perspective

Career

2023 - present: NERC IRF fellow, University of Exeter, Cornwall Campus.

2021 - 2022: Postdoctoral Research Fellow with Michiel Vos, University of Exeter, Cornwall Campus.

2017 - 2020: Postdoctoral Research Fellow with Angus Buckling, University of Exeter, Cornwall Campus.

2012 - 2017: PhD in Biological Sciences with Gabriel Yvon-Durocher, University of Exeter, Cornwall Campus.

Throughout my research career, I have balanced work with caring for my partner.

Links

• My GitHub profile
• My lab website
• My Google Scholar

Research group links

• Microbial Evolutionary Ecology

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Research

Research interests

Climate change

Community ecology

Microbial ecology

Experimental evolution

Thermal adaptation

Open science

Research projects

My current research project

Understanding the effect of temperature on the ecology and evolution of antimicrobial resistance.

The evolution and spread of antimicrobial resistance (AMR) are major threats to global health. Recent correlational studies have shown that levels of AMR increase at higher temperatures in environmental and pathogenic bacteria. However, an almost complete lack of empirical evidence to explain the mechanisms of these broad scale-patterns limits our ability to quantify, understand, and ultimately control potential synergistic impacts of climate change and AMR. 

One of the major ways AMR spreads is through horizontal gene transfer (HGT), which allows bacteria to acquire DNA from individuals other than their immediate ancestors and is driven by mobile genetic elements, such as plasmids. This project’s key research question is whether the spread of plasmids and antimicrobial resistance increases at higher temperatures. If this is the case, then climate change may increase environmental reservoirs of AMR that can then spread into clinically relevant bacteria.

This project is made of 4 main objectives:

1. Explore variation in the response of environmental and human-associated bacteria to temperature.

Theory predicts that human-associated bacteria should have higher optimal temperatures and a narrower tolerance range than environmental bacteria.

2. Understand how plasmid transfer rate changes across temperatures in environmental and human-associated bacteria.

Plasmid transfer rate is linked to the growth rates of the donor and recipient bacteria. We therefore expect plasmid transfer across different bacteria to be highest close to their optimal temperatures. 

3. Understand how selection for resistance changes across temperatures.

We will measure the cost of plasmid carriage and the impact of environmentally-relevant antibiotic concentrations on susceptible bacteria across their full temperature range to understand how the selection for resistance changes with warming.

4. Understand how plasmid spread and dynamics of environmental and human-associated bacteria change across temperatures in natural sewage communities

We will use sequencing to test whether plasmids spread more at higher environmental temperatures in natural communities, and investigate whether human associated bacteria survive better in a warmer world.

Other things I have done and retain interest in!

Macroevolutionary dynamics in micro-organisms

Understanding the ecological and evolutionary forces that structure prokaryote diversity is a central objective in microbial ecology. In macro-organisms, a common approach to do this is to use comparative phylogenetics to look back through macroevolutionary time, but this approach is difficult to do bacteria due a lack of a fossil record and difficulties in actually sampling extant diversity! To tackle this in my most recent postdoc with Mick Vos, we used targeted deep sequencing of the protein coding gene rpoB to sample the phylum Myxococcota across >70 sites in Cornwall. I then did a lot of comparative phylogenetics - and I mean A LOT - and revealed that biome specialists very rarely transitioned to specialise in another biome. Instead, generalists mediated transitions between biome specialists.

Long-term coexistence of a model microbial community

Using microbes in experiments to test theory from community ecology requires having a highly stable community with species that coexist with each other. However, most synthetic communities do not actually test for long-term coexistence, or even check whether the species can coexist together. Together with Elze Hesse, Angus Buckling, Meaghan Castledine, and others, we created a model microbial community consisting of 5 species that (dis)assembled and have coexisted for hundreds (if not thousands) of generations.

These species have been sequenced using long and short-read technology and we have high quality reference genomes of each one. This community is now being utilised across many projects being used to understand how species interactions change through evolutionary time, how plasmids spread and are maintained in communities, and how species interactions change under environmental stress.

Temperature-dependent changes to host–parasite interactions 

Thermal performance curves (TPCs) are used to predict changes in species interactions, and hence, range shifts, disease dynamics and community composition, under forecasted climate change. Species interactions might in turn affect TPCs. We investigated how temperature-dependent changes in a microbial host–parasite interaction (the bacterium Pseudomonas fluorescens, and its lytic bacteriophage, SBWΦ2Φ2) changed the host TPC and uncovered the ecological and evolutionary mechanisms underlying these changes.

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Publications

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External Engagement and Impact

Administrative responsibilities

I am co-chair of the Cornwall Disability Network that aims to provide a support system for staff and students at the University of Exeter’s Penryn campus, to share experiences within a secure and confidential environment and to seek guidance and support regarding disability issues. We also aim to raise awareness of issues affecting those with disability and carers at the Penryn campus, and to help promote a culture that supports disabled and caring staff and students through all areas of campus life.

Other

Software

I developed and maintain two R packages that are useful to people fitting non-linear models and thermal performance curves.

nls.multstart is an R package that allows more robust and reproducible non-linear regression compared to nls() or nlsLM(). This package is designed to work with the tidyverse, harnessing the functions within broom, tidyr, dplyr and purrr to extract estimates and plot things easily with ggplot2.

rTPC is an R package that helps fit thermal performance curves (TPCs) in R. rTPC contains 26 model formulations previously used to fit TPCs and has helper functions to help set sensible start parameters, upper and lower parameter limits and estimate parameters useful in downstream analyses, such as cardinal temperatures, maximum rate and optimum temperature.

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