PredProkDef · Predicting of Prokaryotic Defence Distributions

Predicting of Prokaryotic Defence Distributions

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.

Data: CORDIS, © European Union