Understanding patterns and drivers of long-term change in biological communities is essential to understand the impact of human activity on the ecosystems we inhabit. However, long-term ecological datasets are rare, even for well-studied groups of organisms such as vertebrates and plants, and are absent for the ‘hidden majority’ of biodiversity that exists within prokaryotic communities. One approach to understand how these communities have responded to change over long time periods is the analysis of DNA preserved in sediments. Recent studies have shown that such records can go back many thousands of years, and give an insight into the composition and function of ancient biological communities, as well as the environmental and climatic conditions that shaped them. By relating these long-term datasets to known periods of environmental change, community response can be identified and used to inform future management strategies.

Before these approaches can be applied to answer fundamental ecological questions regarding the change in the composition and function of microbes over long time periods, a number of methodological questions need to be addressed. These include a) understanding the origin of microbial DNA in sediments (i.e. how does this reflect sediment, pelagic or terrestrial communities?); and b) identifying the form of microbial DNA (i.e. is the DNA found in intact cells, are these cells live or dead, or is the DNA extracellular?).

This project will seek to develop and optimise methods to analyse past communities of microbes through high throughout sequencing of lake sediment cores, and apply them to understand change in microbial communities over the past 200 to 300 years. Bioinformatic and statistical approaches will be used to investigate the turnover, stability and changing function of bacterial communities over time, and use this to inform predictions of future change.

Figure 1: Lake sediment core and example high throughput sequencing data showing changes in lake sediment communities over 100 years.


Sources of DNA: DNA extracted from sediment cores collected from the Cumbrian lakes and the surrounding environment will be analysed via high throughput sequencing. Bayesian approaches (SourceTracker) will be used to partition sedDNA and to identify the source of microbial DNA in sediment cores.

Understanding the form of sediment DNA: Sediment horizons will be processed to analyse the source and identity of DNA via the application of a range of approaches to identify extracellular DNA, intact and active cells. These include the use of Propodium Monoazide Sequencing (PMA-Seq) to remove extracellular DNA, flow cytometry using physiological stains to identify live intact cells, Raman microscopy paired with stable isotope labelling to identify metabolically active cells, and culturing to determine viability.

Identifying palaeoecological trends in microbes: Sediment core time series will be interrogated using the methods developed earlier in the project, to develop long term time series of microbial communities in anthropogenically impacted lakes.

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 CENTA research themes.

Project specific training will include field and limnology sampling techniques, including sampling from boats, as well field first aid training. Comprehensive training in molecular biology and DNA sequencing will be provided in within the CEH Molecular Ecology research group, which includes access to in-house DNA sequencers, flow cytometry and biological spectroscopy facilities. In addition, the student will receive training in bioinformatics, and the interpretation of large ecological datasets.

In addition to the CENTA2 training, the student will have access to CEH’s postgraduate training programme, including training in presentation skills, writing, conducting research and courses focussed on data analysis and programming skills.


The project will be divided into two phases; 1. Developing approaches to understand the form, identity and sources of microbial DNA in the sediment record, and 2. Examining long-term changes in microbial communities across a range of lake ecosystems.

Year 1 (2019-20) Focus on developing core skills in lake sampling, molecular biology and bioinformatics. Test approaches for sterile core sampling and sample processing. Collect lake cores and lake and catchment samples.

Year 2 (2020-21) Core horizons will be analysed via the application of high throughput sequencing (16S amplicon and metagenomics) on sediment fractions, and utilising a range of approaches to identify extracellular DNA, intact and active cells, including the use of Propodium Monoazide Sequencing (PMA-Seq), flow cytometry and Raman microscopy paired with stable isotope labelling.

Year 3 - 3.5 (2021-23) Up to three cores from contrasting lake ecosystems will be sampled and subjected to detailed analysis using sedDNA to develop long-term time series of microbial community dynamics. Data analysis and paper/chapter write-up.

Partners and collaboration (including CASE)

The supervisory team bring together expertise in molecular biology and the analysis of ecological datasets (Read) with high-resolution palaeoclimatology, molecular organic geochemistry and biomarker proxy development (Bendle), and molecular microbiology and sedDNA experience (Rhodes). All supervisors have a track record of collaborative PhD supervision and Read and Bendle currently co-supervise a PhD student. In addition, project partners Prof Suzanne McGowan (University of Nottingham) and Dirk Sachse (GFZ Potsdam) will provide additional input and advice on fieldwork, palaeoclimatology and data analysis.

Further Details

Please email Dr Daniel Read dasr@ceh.ac.uk for further information.