Award details

Predicting the emergence of host-adapted bacterial phytopathogens

Reference	BB/T010746/1
Principal Investigator / Supervisor	Professor Xiangming Xu
Co-Investigators / Co-Supervisors	Dr Richard Harrison, Dr Michelle Hulin, Dr Bo Li, Professor John Mansfield, Dr Eleftheria Stavridou
Institution	National Inst of Agricultural Botany
Department	Centre for Research
Funding type	Research
Value (£)	1,458,711
Status	Current
Type	Research Grant
Start date	01/09/2020
End date	31/03/2024
Duration	43 months

Abstract

Using low cost, high throughput genome sequencing we will ask how the population structures of Ps lineages on cultivated and wild cherry varies over time, and how much this is shaped by host genotype and local environment. Profiling absolute levels of abundance of bacterial and fungal species in the phylloplane we will ask how agronomic practice, specifically the application of nitrogen and the use of polytunnel covers affects epiphytic and pathogenic lineages in realistic field settings. Convergent effector gain has been identified in pathogens of cherry and we will examine if effector repertoire is also adapted to colonisation of the shoot surface. We will carry out controlled evolution experiments to study whether effector rich lineages are able to colonise increasingly phylogenetically distant hosts through and whether the adaptive potential of effector poor, toxin-rich Ps lineages to shift hosts is greater than effector-rich lineages. Using phage transfer experiments under different stress-inducing conditions we ask whether there is phage-mediated effector transfer between pathogens and epiphytes as is indicated by preliminary work. Utilising the abundance of Ps genomic data, coupled with supervised machine learning approaches, we will develop tools to predict bacterial host range from genome sequence alone. Developing a training set of genomes with well established host-pathogen association, then testing a range of feature classification techniques and machine learning method, we will evaluate predictions of host compatibility with Prunus and other plant species. Using 'deep learning' methods, we will discover further explanatory features associated with host range classification. We will validate predictions through pathogenicity tests on predicted compatible hosts.

Summary

Bacterial phytopathogens are hard to control and therefore pose a high risk to crop production and the wider natural environment. In order to mitigate that risk, we propose multidisciplinary research into the tempo at which and the mechanism by which bacteria adapt to hosts. Our findings will support new developments in disease management and control strategies. The host range of a pathogen encompasses all the species it can successfully infect and colonise. It is hypothesised that plant species outside this range mount an effective non-host resistance response, preventing colonisation. Plant pathologists traditionally define some pathogens as having a wide host range (generalists) whilst others are limited to one or a few hosts (specialists), although a continuum between these two life strategies probably exists. Our work focuses on the ubiquitous bacterial species complex Pseudomonas syringae (Ps), lineages of which are pathogens of over 300 different plant species. At least eight lineages of Ps are known to cause bacterial canker of cherry trees including the recognised pathogens Ps pv. morsprunorum and Ps pv. syringae. From our preliminary work, sampling from the leaf and shoot surface across cherry orchards around the UK, we have shown that there are large regional variations in Ps populations. We have found that, in addition to the known pathogens, many additional lineages of Pseudomonas (which have the potential to be pathogenic) are present on non-diseased cherry leaves and such strains are extremely widespread across orchards and regions. These epiphytic (surface) populations of pseudomonads may either be donors or repositories of bacterial genes predicted to have a key role in host adaptation to Prunus. We have shown that there is significant variation in resistance to canker within cherry cultivars and also between genotypes of wild cherry. What we do not know is whether or not the epiphytic populations of Ps are similar or variable between cultivated and wild cherry hosts, or if there is a flow of bacterial strains between wild and cultivated cherry. In this multidisciplinary research proposal, we will extend our initial experiments to study the ecological niches occupied by Ps. Using repeated sampling and genome sequencing of isolates from cultivated crops and surrounding plant species, we will determine if epiphytic Ps populations, some of which contain known pathogens, are stable over time and space. In controlled field experiments we will also ask whether agronomic interventions, such as nitrogen rates and polytunnel covering of crops also play a role in shaping bacterial populations. Our previous work has shown that key genes have been transferred between Pseudomonas lineages by phages and plasmids. In order to explore the molecular factors that may affect virulence and lead to new disease outbreaks, we will carry out tests to determine whether epiphytic lineages have 'pathogenic potential' and study the mechanisms of host range expansion through a range of directed evolution experiments. Our analysis will include controlled assessment of gene exchange between bacteria through phage infection. Finally, we will explore whether machine learning approaches can predict the host range of a Pseudomonas isolate with any degree of certainty from its genome sequence alone- a feat that is currently impossible with our current knowledge base, without direct pathogenicity testing upon a host. These predictions will be tested and validated using existing datasets but also on new datasets gathered as part of this work.

Impact Summary

We seek to understand how epiphytic niche, agronomic management practice and gene exchange between bacterial lineages modify population dynamics and adaptive potential using wild and cultivated cherry. Fulfilling these objectives will allow more effective, integrated control methods to be developed. Deploying machine-learning approaches on large datasets we also ask, whether host range can be predicted from genome sequence alone. These novel approaches will generate more powerful tools for management of bacterial diseases and the identification of invasive bacterial lineages that may pose a threat to natural species or cultivated crops. Taken together it is likely there will be significant impacts beyond this funded research project. Indicated in brackets is the indicative timescale of the potential benefits measured from the start of the project. Understanding movement of pathogens and potential pathogens (and pathogenicity genes) between crops and wild relatives (3-7 years)- Benefits, plant health agencies, policymakers, researchers, nurseries, growers, agroforestry schemes This work will inform where environmental reservoirs of potentially pathogenic Pseudomonas are, how stable they are over space and time and how variable they are between crops and their wild relatives. This is all important knowledge, as coupled with other developments (see below) they can inform management practices and provide a tool to monitor the role that different crops may play in harbouring diseases that affect natural populations and vice versa. This may then inform management decisions, for example the location and composition of new agroforestry plantings on farms and the wider environment. Development of machine learning approaches to predict host range and infection risk and precision diagnostics (4-8 years) - Benefits, plant health agencies, policymakers, researchers, nurseries, growers The purpose of developing models to identify host range, first for research purposes but later as a tool for risk management. The movement of diseases through global trade is having significant impacts across many crops. However being able to trace the source of disease outbreaks and their origin is often challenging. Developing precision diagnostics to provide early warnings and more detailed information about whether imported plants carry potential pathogens affecting them and other close or distantly related crops would be a powerful tool in shaping both rapid responses and plant movement policy. Development of precision control (6-12 years) (Benefits, researchers, nurseries, growers, general public) Once the stability of bacterial populations can be assessed more rational and informed approaches to biocontrol can be undertaken, through the study of synthetic communities targeted biocontrol agents, e.g. phages, synthetic community inoculation, modified microbes etc. Further work, underpinned by this research project would then allow the decision of precise controls, potentially even adapted to the local population of microbes and disease causing agents. While the approaches would be general to many pathogenic microbes, benefits could be first realised in disease scenarios involving Ps. This could have wide ranging benefits, both for cultivated and wild plant populations. Agronomic work (benefits 3-5 years) - Benefits growers This work establishes orchards for long-term study and the learnings from our experiments can be taken forward to inform agronomic practice, either through larger scale trials on grower holdings funded by producer organisations or the levy body or through implementation. As managing disease effectively contributes significantly to grower profitability and total factor productivity, through reduction in losses, the impact of this research outcome will be felt through the supply chain.

Committee	Not funded via Committee
Research Topics	Crop Science, Microbiology, Plant Science
Research Priority	X – Research Priority information not available
Research Initiative	Bacterial Plant Diseases [2019]
Funding Scheme	X – not Funded via a specific Funding Scheme

Associated awards:

BB/T010568/1 Predicting the emergence of host-adapted bacterial phytopathogens

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