Understanding and predicting PATHOgen COMmunities

Projektinformationen

PATHOCOM

ID Finanzhilfevereinbarung: 951444

DOI

10.3030/951444

EK-Unterschriftsdatum 30 Juni 2021

Startdatum 1 Juli 2021

Enddatum 30 Juni 2028

Finanziert unter

• EXCELLENT SCIENCE - European Research Council (ERC)

Gesamtkosten

€ 9 945 744,00

EU-Beitrag

€ 9 945 744,00

Koordiniert durch

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Germany

Periodic Reporting for period 3 - PATHOCOM (Understanding and predicting PATHOgen COMmunities)

Berichtszeitraum: 2024-07-01 bis 2025-12-31

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

Infectious disease is often the major selective agent in nature, and we cannot understand how populations evolve without understanding their pathogenic microbes. Beyond host immunity, an important factor determining the ability of pathogens to invade a host is how pathogens interact with other pathogens as well as background microbiota. This project investigates these questions in plants. Previous work has largely focused on pairwise interactions between one plant host and one pathogen, leaving a large gap in our understanding of how different types of interactions between microbes, and especially pathogens, determine the outcome of host-pathogen interactions in the real world. This project integrates large-scale field observations of microbes in the plant Arabidopsis thaliana with ultra-high-throughput experimental tests of host-dependent interactions among microbes, allowing experiment-informed modeling of pathogenic microbe-microbe interactions. These models, which will be improved through an iterative process of data collection with synthetic communities, will illuminate how interactions, from pairwise to higher-order, shape microbial community composition and structure. In the final step, the resulting models will be tested against and refined with field data. Together, these efforts will transform the study of plant pathogens by applying deep analyses of microbial interactions in an ecological context to explain patterns in nature. The ultimate goal is to refashion plant-pathogen-microbiome studies into a predictive science.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

Natural populations of the plant Arabidopsis thaliana have been extensively characterized for ecological variables across two plant life cycles from fall 2021 to spring 2023. The microbiota and pathobiota in and on these plants as well as on companion species and soil is well advanced, as is the genetic characterization of the plants. A subset of plants has been processed for gene expression analyses, to determine the effects of microbial colonization on the immune status of wild plants. The analysis of these data is also well advanced.

Both plant and microbe strains have been barcoded, and sequencing methods for ultra-high-throughput analyses of barcodes from infected plants are being refined. Instrumentation for massively parallel bacterial infections by spraying has been developed. Large-scale infection trials are currently ongoing.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

Previous work has largely ignored the impact of interactions between pathogens, the pathobiota. This project will provide the first large-scale experimental data set accurately describing the range of interactions, including higher-order interactions, that drive complex microbial communities in the plant phyllosphere.

Pseudomonas bacteria invading a plant leaf through stomata (Copyright: Sonja Kersten, Detlef Weigel)