Publikationen Program Center MetaCom

Plant metabolism is profoundly affected by various abiotic stresses. Consequently, plants must reconfigure their metabolic networks to sustain homeostasis while synthesizing compounds that mitigate stress. This aspect, with the current intensified climate impact results in more frequent abiotic stresses on a global scale. Advances in metabolomics and systems biology in past decades have enabled both a comprehensive overview and a detailed analysis of key components involved in the plant metabolic response to abiotic stresses. This review addresses metabolic responses to altered atmospheric CO2 and O3, water deficit, temperature extremes, light intensity fluctuations including the importance of UV-B, ionic imbalance, and oxidative stress predicted to be caused by climate change, long-term shifts in temperatures, and weather patterns. It also assesses both the commonalities and specificities of metabolic responses to diverse abiotic stresses, drawing on data from the literature. Classical stress-related metabolites such as proline, and polyamines are revisited, with an emphasis on the critical role of branched-chain amino acid metabolism under stress conditions. Finally, where possible, mechanistic insights into the regulation of metabolic processes and further outlook on combinatory stresses are discussed.

Metabolomics, a rapidly evolving field, has revolutionized horticultural crop research by enabling comprehensive analysis of metabolites that influence plant yield, growth, quality and nutritional value. The integration of web-based resources, including databases, computational tools and analytical platforms has significantly enhanced metabolomics studies by facilitating data processing, metabolite identification and pathway analysis. Moreover, the application of machine learning algorithms to these web resources has further optimized data interpretation, enabling more accurate prediction of metabolic profiles. Publicly available reference libraries and bioinformatic tools support precision of breeding, postharvest quality assessment and ultimately improving crop yield and sustainability. In this mini-review, we explore the current status of the diverse range of plant metabolomics databases in horticultural crops, highlighting the synergy between machine learning and traditional bioinformatics methods, their applications, challenges and future prospects in advancing plant science and agricultural innovation.

Metabolomics is a rapidly evolving field focused on the comprehensive identification and quantification of small molecules in biological systems. As the final layer of the biological hierarchy following of the genome, transcriptome and proteome, it presents a dynamic snapshot of phenotype, influenced by genetic, environmental and physiological factors. Whilst the metabolome sits downstream of genes and proteins, there are multiple higher levels—tissues, organs, the entire organism, and interactions with other organisms, which need to be considered in order to fully comprehend organismal biology. Advances in metabolomics continue to expand its applications in plant biology, biotechnology, and natural product discovery unlocking many of nature’s most beneficial colors, tastes, nutrients and medicines. Flavonoids and other specialized metabolites are essential for plant defense against oxidative stress and function as key phytonutrients for human health. Recent advancements in gene-editing and metabolic engineering have significantly improved the nutritional value and flavor of crop plants. Here we highlight how advanced metabolic analysis is driving improvements in crops uncovering genes that influence nutrient and flavor profile and plant derived compounds with me-dicinal potential.

In recent years, several studies investigating multifactorial stresses have emerged. This shift has been driven by the recognition that one of the primary reasons for the inconsistency between laboratory-based results and field observations of plant responses is that, in natural environments, plants are routinely exposed to a combination of biotic and/or abiotic stresses, which they encounter either simultaneously or sequentially. Within this review, we address current advances in multifactorial studies focusing on metabol(om)ic changes in model as well as cereal crop species. The common consensus is that currently, studies on phenotypic and transcriptomics analysis are prevailing, while metabolic studies are scarce. Despite the need for further studies to validate the findings in this review, two clear biological messages emerge. First, and perhaps unsurprisingly, proline stands out as a universal stress metabolite, closely followed by branched-chain amino acids. Interestingly, while multifactorial stress responses are often considered non-additive and unpredictable, our findings reveal that many metabolic changes are both. Expanding the scope of studies to include more species and a wider range of stresses at the metabolic level will be essential for uncovering additional metabolic reprogramming in response to multifactorial stress. This will provide invaluable insights for developing breeding strategies aimed at future-proofing crops.