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Slug Feeding Triggers Dynamic Metabolomic and Transcriptomic Responses Leading to Induced Resistance inSolanum dulcamara
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Current Challenges in Plant Eco-Metabolomics
The relatively new research discipline of Eco-Metabolomics is the application of
metabolomics techniques to ecology with the aim to characterise biochemical interactions of
organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical
approach to measure many thousands of metabolites in different species, including plants and animals.
Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes
that are relevant at ecological scales. These include physiological, phenotypic and morphological
responses of plants and communities to environmental changes and also interactions with other
organisms. Traditionally, research in biochemistry and ecology comes from two different directions
and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic
processes in individuals at physiological and cellular scales. Generally, they take a bottom-up
approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies
usually focus on extrinsic processes acting upon organisms at population and community scales
and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a
transdisciplinary research discipline that links biochemistry and ecology and connects the distinct
spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical
interactions of plants at various ecological levels, mainly plant–organismal interactions, and discuss
related examples from other domains. We present recent developments and highlight advancements
in Eco-Metabolomics over the last decade from various angles. We further address the five key
challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature
extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools
and workflows. The presented solutions to these challenges will advance connecting the distinct
spatiotemporal scales and bridging biochemistry and ecology
Current Challenges in Plant Eco-Metabolomics
The relatively new research discipline of Eco-Metabolomics is the application of
metabolomics techniques to ecology with the aim to characterise biochemical interactions of
organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical
approach to measure many thousands of metabolites in different species, including plants and animals.
Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes
that are relevant at ecological scales. These include physiological, phenotypic and morphological
responses of plants and communities to environmental changes and also interactions with other
organisms. Traditionally, research in biochemistry and ecology comes from two different directions
and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic
processes in individuals at physiological and cellular scales. Generally, they take a bottom-up
approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies
usually focus on extrinsic processes acting upon organisms at population and community scales
and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a
transdisciplinary research discipline that links biochemistry and ecology and connects the distinct
spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical
interactions of plants at various ecological levels, mainly plant–organismal interactions, and discuss
related examples from other domains. We present recent developments and highlight advancements
in Eco-Metabolomics over the last decade from various angles. We further address the five key
challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature
extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools
and workflows. The presented solutions to these challenges will advance connecting the distinct
spatiotemporal scales and bridging biochemistry and ecology