Predicting the emergence of host-adapted bacterial phytopathogens
Lead Research Organisation:
University of Birmingham
Department Name: Sch of Biosciences
Abstract
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Technical Summary
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.
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.
Planned Impact
We seek to understand how epiphytic niche, agronomic management practice and the 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.
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.
Publications
Grace E
(2021)
Seeing the forest for the trees: Use of phages to treat bacterial tree diseases
in Plant Pathology
Hulin MT
(2023)
Genomic and functional analysis of phage-mediated horizontal gene transfer in Pseudomonas syringae on the plant surface.
in The New phytologist
Rabiey M
(2022)
Scaling-up to understand tree-pathogen interactions: A steep, tough climb or a walk in the park?
in Current Opinion in Plant Biology
Taylor TB
(2022)
Natural selection on crosstalk between gene regulatory networks facilitates bacterial adaptation to novel environments.
in Current opinion in microbiology
Thompson CMA
(2023)
Plasmids manipulate bacterial behaviour through translational regulatory crosstalk.
in PLoS biology
Description | We have discovered that a type of bacterial virus, called a prophage, sits within the chromosome of several plant-associated bacteria, some of which are pathogens and some are not pathogens. These prophages can carry types of genes (virulence genes) that bacteria can use to help cause disease in plants. We were able to show that a prophage could move from a pathogen to a non-pathogen and thus they could potentially influence the evolution of pathogens if they were to transport virulence factors with them. Importantly, we were able to demonstrate that UV light (which will be intense where the bacteria reside when on plant surfaces) could trigger the prophage movement, so there is a potential causal mechanism for how the pathogens can acquire mobile genetic elements, like prophages, in a field setting. We believe this is likely to be a general phenomenon and thus important for a range of plant pathogens. |
Exploitation Route | It would be helpful to examine how broad this mechanism is and whether this phenomenon is a common contributor to plant pathogens. It has potential applied usage as well, if it is possible to reduce UV conditions impacting plant surfaces and thus reduce prophage movement between bacteria. |
Sectors | Agriculture Food and Drink Environment |
Description | Conference talk |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Conference seminar to a broad range of national and international researchers. |
Year(s) Of Engagement Activity | 2023 |
URL | https://imppc2023.org/en/ |
Description | Conference talk |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Conference seminar to disseminate results from this project |
Year(s) Of Engagement Activity | 2023 |
URL | https://www.fems2023.org/symposia-9-16 |
Description | Research seminar |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Research seminar at Departamento de Protección de cultivos, Instituto de Hortofruticultura Subtropical y Mediterránea "La Mayora", Universidad de Málaga-Consejo Superior de Investigaciones Científicas, IHSM UMA-CSIC |
Year(s) Of Engagement Activity | 2023 |