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Chemical ecology and the chemical trait space of oak leaves

Development of an optimized untargeted eco-metabolomics protocol for liquid chromatography high-resolution mass spectrometry and data dependent acquisition (UPLC-QTOF-DDA-MS) to assess the chemical trait space of small molecules (20-1000 Da) in oak leaves (Quercus robur). Analysing ecological influences on the chemical composition of different types of oak leaves in space (different individual trees, environmental and biotic stress) and time (different seasonal stages). Calculation of phenotypic and molecular traits and elucidation of the ecologically most relevant impact factors on leaf chemistry.

Background

European oaks are under stress. The combined effects of climate change and pathogenic insects like the oak processionary are not well understood, especially at the chemical level. In the LOEWE-Schwerpunkt TreeM project we are investigating the bacterial functions that drive the accumulation of carbon and nitrogen resources in oak leaves and the underlying molecular mechanisms at different spatial and temporal scales.

In the context of the TreeM project, we want to establish a reliable and efficient eco-metabolomics protocol. As the leaf economics spectrum highly depends on environmental conditions, the leaf microbiome and pathogenic pressure, an optimised method to assess the chemical trait space is needed to link the complex mechanistic processes at the molecular level with ecological factors.

As part of the sampling campaign, different types of oak leaves (3 oak tree individuals, 3 seasons, sun and shade leaves, leaves with feeding) need to be analysed regarding the impact of different ecological factors. It is still unresolved which and how ecological factors like environmental or biotic changes affect the leaf chemistry. To address these questions, the chemical trait space can be characterised by a multitude of small specialised molecules (20-1000 Da) whose abundance and composition can reveal molecular interactions with the environment and the microbiome, hence, linking molecules to the leaf economics spectrum and ecological processes and traits.

General Aim of the study

Establishing an efficient eco-metabolomics protocol to produce reliable methanolic extracts of oak leaves. Using the developed protocol to analyse the chemical trait space (revealing specialised metabolites) of oak leaf discs of different conditions and types and linking the chemical diversity and molecular traits to ecological factors.

Hypotheses

1. An efficient and reliable extraction protocol can be established that allows to analyse the majority of polar small molecules (20-1000 Da) constituting specialised metabolites in oak leaves excluding the polar wax-like cuticle.

2. There is a considerable difference in molecular/chemical features between leaves, where there is the largest difference between sun/shade and healthy/exposed leaves. Compound classes showing the largest differences are flavonoids and glycosides (sun/shade) and terpenoids (defence). 

3. There is further a link of molecular-chemical traits to phenotypic leaf traits defining the leaf economics spectrum and the ecological response of oak leaves.

Material & Methods

1. Testing and optimising different protocols of methanolic metabolite extraction methods.

2. Metabolomics analyses using liquid chromatography high-resolution mass-spectrometry (UPLC/ESI-QTOF-MS) with data-dependent acquisition (DDA-MS).

3. Data pre-processing according to Peters et al. (2018), in silico annotation and classification of molecules using SIRIUS and the iESTIMATE computational framework (Peters et al. 2024, unplublished)

4. Calculation of chemical diversity measures using chemodiv R package.

5. Comparison of metabolite profiles of leaves using multivariate statistics (PCA, PLS-DA) and variable selection (e.g. Random Forest, Heatmaps, clustering).

6. Ordination analysis (e.g. variance partitioning, RDA) to find links between leaf physiology (leaf economics spectrum) and ecological traits (environmental factors, leaf traits, life stage, chemical diversity, pathogens).

Rough schedule

· Plant material (leaf discs) stored in -80°C freezer and readily available.

· Protocol establishment (2-3 weeks)

· Metabolite extractions (2 days), metabolomics measurements (4 days)

· Data pre-processing and in silico annotation (approx. 2 weeks)

· Data analysis including statistics, chemodiversity, interpretation of annotations and classifications (2 months).

· Interpreting the results in the light of ecological hypotheses and plant physiology (1 month). Literature research.

· Writing of the thesis (1-2 months).

Important reading

1. BERTIC 2021 European oak chemical diversity – from ecotypes to herbivore resistance

2. PETERS 2018 Seasonal variation of secondary metabolites in nine different bryophytes

3. BLATT-JANMAAT 2023 Host Tree and Geography Induce Metabolic Shifts in the Epiphytic Liverwort Radula complanata

4. WRIGHT 2004 The worldwide leaf economics spectrum

Publication potential

· Publication in Journal of Chemical Ecology (Springer), or Ecology and Evolution (Wiley)

Supervision

· Kristian Peters, Nicole Paczia, Lars Opgenoorth