Chris Knight

Experimenting with Evolution

We want to understand the mechanics of evolution. Exactly what molecules change? In what ways are these changes beneficial (or not) to the organism? How does this relate to what happens in populations of organisms? We mostly answer these questions using microbes. This means that our work relates to issues from the rise of antimicrobial resistance (AMR) to the roles of microbiomes – the mixed populations of microbes in particular places, from soil to our guts. Microbes reproduce fast enough that we can watch evolution happening in real time on the lab bench. To make sense of what’s going on we use computational models. Our mixture of wet-lab and computational approaches means that we collaborate both with other biologists, contributing quantitative approaches, as well as computer scientists and theoreticians.

Mechanisms of evolution

To understand evolution we use a range of tools, from computer models to model organisms, with a focus on experimental evolution. With these tools we ask questions at a range of scales, from single mutations to comparisons among species.

Microbiome evolution

How the diversity of microbes living together in one place changes over time is an example of evolution. We want to understand the impact of environmental change on microbial communities. This has the potential for insight in systems as diverse as soil and the mammalian gut.

Key current people: Ellen Fry, Deepanshi Karwall, Deon Lum

Key Collaborators: Franciska de Vries, Sheena Cruickshank, Kat Coyte, Richard Bardgett, Sophie Nixon, Mike Brockhurst

Key Papers: Knight, C.G., Nicolitch, O. et al & de Vries, F.T. (2024) Soil microbiomes show consistent and predictable responses to extreme events. Nature. https://doi.org/ntzk

Press release: Climate impacts on European soils predicted by scientists

Ramirez KS, Knight CG et al. (2017) Detecting macroecological patterns in bacterial communities across independent studies of global soils. http://doi.org/cgf2

Environmental effects on mutation rates

The probability that an organism’s offspring carry spontaneous changes to their DNA sequence depends on many things, including that organism’s environment. We are looking at environmentally dependent changes in mutation rate, or ‘mutation rate plasticity’. We discovered that microbes in dense populations tend to have lower mutation rates than microbes in spread out populations; that is, DAMP: density-associated mutation-rate plasticity. We want to understand DAMP from its mechanisms via how it evolves to the evolutionary effects that it has, particularly for grand challenges like antimicrobial resistance.

Key current people: Rowan Green, Sara Alghatani

Key collaborators: Rok Krašovec, Roman Belavkin, Alastair Channon, Andrew McBain

Key papers: Green, R. et al. (2024) Collective peroxide detoxification determines microbial mutation rate plasticity in E. coli. PLoS Biology, 22, e3002711. https://doi.org/m8zt

Press release: Scientists control bacterial mutation rates to preserve antibiotic effectiveness

Krašovec, R. et al. (2019) Measuring microbial mutation rates with the fluctuation assay. Journal of Visualised Experiments, 153, e60406 http://doi.org/dj9n

Krašovec, R., Richards, H. et al. (2017) Spontaneous Mutation Rate Is a Plastic Trait Associated with Population Density across Domains of Life. PLOS Biology, 15, e2002731. http://doi.org/cb9s

Antimicrobial Resistance

Organisms that are resistant to antibiotics and other antimicrobials are a major and growing issue in medicine and agriculture. How this comes about is a question of evolution and we are looking for evolutionary answers.

Key current people: Rosie Clover, Sophie, Somerville

Key collaborators: Danna Gifford, Curtis Dobson

Key Papers: Gifford, D.R. et al. (2023). Mutators can drive the evolution of multi-resistance to antibiotics. PLOS Genetics 19, e1010791, https://doi.org/kfnx

Gifford, D.R. et al. (2018) Environmental pleiotropy and demographic history direct adaptation under antibiotic selection. Heredity, 121, 438-448. http://doi.org/ctm6

2017 – present

University of Manchester, Faculty of Science and Engineering, Senior Lecturer

2012 – 2017
University of Manchester, Faculty of Life Sciences, Lecturer

2008 – 2013 University of Manchester, Faculty of Life Sciences, Wellcome Trust Research Career Development Fellow

2005 – 2007
University of Manchester, Manchester Interdisciplinary Biocentre, BBSRC Postdoc with Douglas Kell

2002 – 2005
University of Oxford, department of Plant Sciences, NERC Postdoc on the molecular basis of evolution in the bacterium Pseudomonas fluorescens with Paul Rainey and the proteomics lab in the department of Biochemistry.

1997 – 2001
Imperial College London at Silwood Park, PhD on ‘The genetics and evolution of body size in the nematode Caenorhabditis elegans’ funded by NERC, supervised by Armand Leroi

1994 – 1996
Christ's College Cambridge, MA Natural Sciences, finalising in genetics

We are always looking for people interested in joining the lab. In the first instance, please send me an email and CV outlining your interests and experience.

PhD opportunities

Current opportunities I’m involved with, advertised at findaPhD.com, should be listed below. These are mostly via the University of Manchester’s BBSRC, MRC and NERC doctoral training partnerships. If you have access to other sources of funding, get in touch and/or consider the available project outlined below.

Fellowship and postdoc opportunities

If you're interested in applying for a fellowship to work with us, there is a range of possible funding sources, both external (e.g. Wellcome Trust, Royal Society, BBSRC, NERC, HFSP and EU) and internal (e.g. look out for repeats of this).

PhD project: Mutations in space

Spontaneous mutation supplies the raw material for evolution, but we find that the rate at which it occurs can vary with the environment in non-obvious ways. Most of what we know about variation in mutation rates comes from microbes growing in shaken liquid cultures. These environments have little spatial structure. However, in many, ‘real’ environments, from soil to skin, spatial structure really matters. Using a range of techniques for estimating and modifying mutation rates in model microbes, the student will determine how space matters for that fundamental first step of evolution – does mutation rate change with the degree of spatial structure? Does the association of mutation rate with population density hold for spatially structured environments? What genes are required? Training will be provided in necessary skills, but the student would ideally have a background in biology or genetics with computational skills and a keen interest in evolution.