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Predicting of Prokaryotic Defence Distributions

Periodic Reporting for period 2 - PredProkDef (Predicting of Prokaryotic Defence Distributions)

Reporting period: 2022-02-01 to 2023-01-31

The action “Predicting Prokaryotic Defences” aims to identify the ecological conditions that favour different forms of bacterial immunity. Just like higher-organisms, bacteria possess a wealth of immune mechanisms with which to survive infection from their own viruses: the bacteriophages (phages). Although the genetics and functions of these immune systems are incredibly diverse, they can broadly be categorised into two groups regarding their effects on the bacterial population. The first group can be considered ‘selfish’ immune systems, which benefits the individual bacterial cell by resisting infection and allowing the cell to survive. The second group can be considered ‘altruistic’ as these systems detect phage infection and kill the cell, therefore preventing the proliferation of the virus and subsequent infection of neighbouring cells. The evolutionary predictions regarding when each of these forms of immunity should be favoured are clear, yet empirical work that directly competes these immune systems is lacking. Still less is known regarding how these systems are distributed in natural microbial communities across environments. This action seeks to address this gap in the knowledge by developing a model system with which to directly compare these two forms of immunity. In parallel, the action aims to use metagenomic data from a range of environments to assess the distribution of the systems in nature. In both cases, I will use an abortive infection system as a model of an altruistic system and a CRISPR system as a model of a selfish immune system. A key prediction is that high-spatial structure, where populations mix less freely, will favour the evolution or maintenance of altruistic systems as neighbouring cells are more likely to be related to one another. By contrast, environments with low spatial structure are expected to favour selfish immune systems, as the protection provided is less likely to directly benefit neighbouring cells. Once these predictions have been tested, we can use them to categorise immune systems that have been recently identified, but where little is known regarding their function.

Bacteria are one of the most highly abundant organisms on earth, and are crucial for global geochemical cycling. Phages are estimated to outnumber bacteria by 10-100 : 1, depending on the environment. Therefore the scale alone of these interactions warrants the need for a deep understanding of their evolution and ecology. Moreover, phage biology has a long history of contributing to biotechnology advances, and in recent years the study of bacterial immune systems has continued this trend. For example, the discovery and use of CRISPR has led to advances in genome editing, gene-drives and diagnostic technologies. Newly discovered phage immune defence systems may provide similar advances. Overall, a better understanding of the role of ecology in shaping these systems may provide unique insights.

There are 3 major objectives of this action, with the steps involved divided into work packages (WP). Objective I aims to study the impact of spatial structure on bacterial defence in a model system. This system is the environmental bacterium Serratia sp. ATCC39006 and will contrast the abortive infection system, toxIN, and a selfish immune system, CRISPR, by manipulating spatial structure and quantifying the relative benefits to each system during phage infections Objective II uses metagenomic data and newly developed models to identify these forms of immune system in natural environments. Objective III uses the insights gathered from objectives I and II to classify a newly discovered immune system as other selfish or altruistic, and characterise the mechanism of this system experimentally.
The first steps of this action were to develop a model system with which to directly compare the two forms of immunity. I identified a suitable phage that infects the bacterium Serratia sp. ATCC39006 and introduced a fluorescent marker for high-throughput assays. I then tested the effectiveness of a selfish immune system (CRISPR) and an altruistic system (toxIN) at providing immunity against this phage. Lastly, I developed an experimental system with which to manipulate spatial structure and conducted preliminary experiments. Experiments and analysis that directly compare these systems are ongoing. For objective II, I developed models to identify altruistic defences and contributed these to a tool that identifies all forms of phage defence. I then collected soil samples from a wetland ecosystem that contains habitats spanning a gradient of spatial structure. I conducted preliminary metagenomic data collection and analysis and identified > 1000 viruses. I also used new sequencing technologies to better identify host bacteria and analysed their genomes for phage defence systems. Further samples have been collected from the remaining habitats and await DNA sequencing. I have also used publicly available data from a range of environments to describe the distribution of selfish immunity (CRISPR) and this work was recently published (Meaden and Biswas et al. 2022, Current Biology). Lastly, I have been experimentally characterising newly described phage defences in an Escherichia coli system and this work is ongoing.

In addition to research results, the action has achieved the auxiliary objectives of developing technical skills and independence via training and conference attendance. I presented the paper mentioned above at CRISPR 2021, Paris and FAOBMB, Christchurch, and delivered a research seminar to my host institution (Dept. of Microbiology and Immunology, University of Otago). I also attended training for computational biology at the Research Bazaar events at the University of Otago. Lastly, an outreach workshop was held at the end of the fellowship using nanopore sequencing to profile microbial communities in a popular UK botanical garden (The Eden Project).
One aspect of the action that has developed beyond the state of the art is through the use of new DNA sequencing technologies for metagenomic analysis. Notably, combining advances in Nanopore sequencing with HiC sequencing represent an advance in this field which I explored through a grant from the University of Otago. This grant allowed me to use these new technologies to address the questions in objective II. Impacts of the work include a high-impact publication (Meaden and Biswas et al. 2022, Current Biology) and the opportunity to contribute a perspective piece to the journal, Science (Meaden and Fineran, 2021). Other impacts beyond research includes public outreach via presenting results to the board of Trustees at the field site, and the opportunity to contribute to the Phages for Global Health online programme and discuss the methodologies used in the action. Further expected outcomes include high-impact research papers and using these results to develop research grants for UK funding bodies.
Lab group photo at the University of Otago