High-quality data preprocessing is essential for untargeted metabolomics experiments, where increasing dataset scale and complexity demand adaptable, robust, and reproducible software solutions. Modern preprocessing tools must evolve to integrate seamlessly with downstream analysis platforms, ensuring efficient and streamlined workflows. Since its introduction in 2005, the xcms R package has become one of the most widely used tools for LC-MS data preprocessing. Developed through an open-source, community-driven approach, xcms has maintained long-term stability while continuously expanding its capabilities and accessibility. We present recent advancements that position xcms as a central component of a modular and interoperable software ecosystem for metabolomics data analysis. Key improvements include enhanced scalability, enabling the processing of large-scale experiments with thousands of samples on standard computing hardware. These developments empower users to build comprehensive, customizable, and reproducible workflows tailored to diverse experimental designs and analytical needs. An expanding collection of tutorials, documentation, and teaching materials further supports both new and experienced users in leveraging the broader R and Bioconductor ecosystems. These resources facilitate the integration of statistical modeling, visualization tools, and domain-specific packages, extending the reach and impact of xcms workflows. Together, these enhancements solidify xcms as a cornerstone of modern metabolomics research.

The transition to flowering is governed by different pathways integrating endogenous and exogenous signals. Here, we evaluated the role of the phytohormone cytokinin (CK) in regulating Arabidopsis thaliana flowering time. By analyzing key mutants in CK metabolism, transport and signalling, we found that the hormone promotes flowering under both long-day (LD) and short-day (SD) conditions, with a stronger impact on flowering under SDs. Genetic analyses indicated that both trans- and cis-zeatin regulate the floral transition, while isopentenyladenine plays a minor role. Blocking CK export from roots and reciprocal grafting experiments revealed that root-derived CK is an important flowering signal. Perception and transmission of the CK flowering signal depended on distinct CK receptors, phosphotransmitter proteins and several B-type response regulators. Further, CK functioned through floral integrators such as OVEREXPRESSION OF CONSTANS1 (SOC1) and components of the age pathway. The CK status of plants affected the levels of the age pathway microRNAs miR156 and miR172. Cytokinin-promoted flowering required the miR156-target SQUAMOSA PROMOTER BINDING PROTEIN-LIKE15 (SPL15) and miR172, and the late-flowering phenotype of LD-grown CK-deficient plants depended on miR172-targeted APETALA2 (AP2)-like genes encoding floral repressors. Collectively, this study shows that CK regulates flowering time through the two-component signaling system and components of the age pathway, providing a genetic framework for future investigations.

Sulfur (S) metabolism has played a critical role in the evolution of life, serving as an energy source for early biochemical pathways like dissimilatory S reduction and anoxygenic photosynthesis. Across kingdoms, S metabolism displays remarkable diversity. S-containing metabolites like glucosinolates (GLSs) in Brassicaceae and S-alk(en)ylcysteine sulfoxides in Allium species illustrate the ecological and evolutionary significance of Scontaining compounds. These metabolites contribute to defense, homeostasis, and ecological interactions, with mechanisms like enzymatic hydrolysis releasing bioactive molecules such as allicin. Further, advances in transcriptomics and biochemical studies have revealed the genetic underpinnings of S metabolism and specialized pathways in bulb-forming Allium species. The role extends to ecological interactions by modulating S-associated defense pathways. This integrative understanding of S metabolism underscores its evolutionary, physiological, and ecological importance.

Genome engineering technologies allow the generation of crops with increased disease resistance, though selecting suitable targets remains challenging. Our team has published two recent studies that highlight the potential of engineering plant immune proteases as an alternative approach to generating disease resistant plants.

Background and Aims We have abundant knowledge on drought responses of plants or soil microorganisms individually. However, there is a severe lack of knowledge regarding interactions in the plant-soil-microbiome continuum, and specifically root-soil interface traits including the role of root hairs. Here, we investigated how water limitation propagates in a plant-soil-microbiome system upon stopping irrigation. We used two Zea mays genotypes (rth3 and its isogenic wildtype B73), differing in root hair formation, to elucidate the effect of rhizosphere extension under water limitation. Methods For 22 days, WT and rth3 were grown in a climate chamber, with irrigation stopped for drought treatment during the last 7 days. Daily measurements included soil water status, plant evapotranspiration and gas exchange. At harvest, root exudates, shoot relative water content, osmolality and nutrients, root morphological traits and transcriptomics, and soil microbial β-diversity and enzyme activity were determined. Key Results In line with a larger plant size, drought stress developed more rapidly and the number of differentially expressed genes was higher in the WT compared to rth3. Under water limitation, root exudation rates increased and soil enzyme activities decreased more strongly in the WT rhizosphere. In both genotypes, water level significantly altered microbial β-diversity in the bulk soil, particularly affecting fungi more than bacteria/archaea. The genotype affected only bacteria/archaea and was more pronounced in rhizosphere than in bulk soil.Conclusions This interdisciplinary study assessed how a short drought stress manifested in a plant-soil-microbiome system. Water limitation altered microbial (fungal) diversity more distant from the root surface. Genotype-specific stress-induced increases in exudation rates modified microbial activity in root proximity, possibly pointing to root hair functions under water limitation. Less intense drought responses of rth3 were confirmed at all levels of investigation and may be due at least in part to its smaller plant size.

Objective: In this study, 25 synthetic cyclic lipopeptides (CLPs) were investigated for their anticancer potential against mouse melanoma (B16F10) cells, human prostate cancer (PC-3), human colorectal adenocarcinoma (HT-29) and mouse embryonic fibroblast (NIH3T3) cells. Methods: The cytotoxic activity of investigated compounds was evaluated using MTT and CV assays. In order to examine the mechanism of action of the most potent compound cell cycle analysis, apoptosis assay, caspase activity, CFSE and DHR staining, DAF-FM, autophagy and immunocytochemistry caspase-3 assays were performed. Results: During the fast screening, compound 9, was identified as prospective active CLP against B16F10 cell line at 10 μM concentration. MTT and CV assays exhibited at least four times higher cytotoxic potential of 9 (IC50 = 8.4±1.3 μM, MTT; 10.6±1.1 μM, CV) in comparison to control drug natural occurring CLP surfactin (IC50 = 50.3±0.6 μM, MTT; 40.4±0.3 μM, CV). The use of flow cytometry analysis confirmed that apoptosis was involved in the death of B16F10 cells after treatment with 9, as demonstrated also by DAPI staining. Caspase activity could be detected during cell death (ApoStat assay, immunocytochemistry caspase-3 assay). Compound 9 provokes enhancement of nitric oxide (NO) production in B16F10 cells but does not trigger ROS/RNS generation or autophagy. Conclusion: The study highlights synthetic compound 9 superior tumor-specificity and potential as an anticancer agent compared to surfactin and cisplatin. These findings could guide the development of more selective and less harmful macrocyclic lipopeptides for cancer therapy.

Systemic signaling is an essential hallmark of multicellular life. Pathogen encounter occurs locally but triggers organ-scale and organismic immune responses. In plants, elicitor perception provokes systemically expanding Ca2+ and H2O2 signals conferring immunity. Here, we identify a Ca2+ sensing bi-kinase module as becoming super-activated through mutual phosphorylation and as imposing synergistically enhanced NADPH oxidase activation. A combined two-layer bi-kinase/substrate phospho-code allows for sensitized signaling initiation already by near-resting elevations of Ca2+ concentration. Subsequently, it facilitates further signal wave proliferation with minimal Ca2+ amplitude requirement, triggering protective defense responses throughout the plant. Our study reveals how plants build and perpetuate trans-cellular immune signal proliferation while avoiding disturbance of ongoing cellular signaling along the path of response dissemination.

Herbivores sharing host plants are often temporally and spatially separated, limiting direct interactions between them. Nevertheless, as observed in numerous aboveground study systems, they can reciprocally influence each other via systemically induced plant responses. In contrast, examples of such plant-mediated interactions between belowground herbivores are scarce; however, we postulated that they similarly occur, given the large diversity of root-interacting soil organisms. To test this hypothesis, we analyzed the performance of cabbage root fly (Delia radicum) larvae feeding on the main roots of field mustard (Brassica rapa) plants whose fine roots were infected by the root-knot nematode (Meloidogyne incognita). Simultaneously, we studied the effects of M. incognita on D. radicum-induced defense responses and the accumulation of primary metabolites in the main root. We observed that almost 1.5 times as many D. radicum adults emerged from nematode-infected plants, indicating a facilitation effect of M. incognita infection. Although we observed increases in the accumulation of proteins and two essential amino acids, the strongest effect of nematode infection was visible in the defense response to D. radicum. We observed a 1.5 times higher accumulation of the defense-related phytohormone JA-Ile in response to D. radicum on nematode-infected plants, coinciding with a 75% increase in indole glucosinolate concentrations. Contrastingly, concentrations of aliphatic glucosinolates, secondary metabolites negatively affecting D. radicum, were 10-25% lower in nematode-infected plants. We hypothesize that the attenuated aliphatic glucosinolate concentrations result from antagonistic interactions between biosynthetic pathways of both glucosinolate classes, which was reflected in the expression of key biosynthesis genes. Our results provide explicit evidence of plant-mediated interactions between belowground organisms, likely via systemically induced responses in roots.

High-quality data preprocessing is essential for untargeted metabolomics experiments, where increasing dataset scale and complexity demand adaptable, robust, and reproducible software solutions. Modern preprocessing tools must evolve to integrate seamlessly with downstream analysis platforms, ensuring efficient and streamlined workflows. Since its introduction in 2005, the xcms R package has become one of the most widely used tools for LC-MS data preprocessing. Developed through an open-source, community-driven approach, xcms has maintained long-term stability while continuously expanding its capabilities and accessibility. We present recent advancements that position xcms as a central component of a modular and interoperable software ecosystem for metabolomics data analysis. Key improvements include enhanced scalability, enabling the processing of large-scale experiments with thousands of samples on standard computing hardware. These developments empower users to build comprehensive, customizable, and reproducible workflows tailored to diverse experimental designs and analytical needs. An expanding collection of tutorials, documentation, and teaching materials further supports both new and experienced users in leveraging the broader R and Bioconductor ecosystems. These resources facilitate the integration of statistical modeling, visualization tools, and domain-specific packages, extending the reach and impact of xcms workflows. Together, these enhancements solidify xcms as a cornerstone of modern metabolomics research.

The transition to flowering is governed by different pathways integrating endogenous and exogenous signals. Here, we evaluated the role of the phytohormone cytokinin (CK) in regulating Arabidopsis thaliana flowering time. By analyzing key mutants in CK metabolism, transport and signalling, we found that the hormone promotes flowering under both long-day (LD) and short-day (SD) conditions, with a stronger impact on flowering under SDs. Genetic analyses indicated that both trans- and cis-zeatin regulate the floral transition, while isopentenyladenine plays a minor role. Blocking CK export from roots and reciprocal grafting experiments revealed that root-derived CK is an important flowering signal. Perception and transmission of the CK flowering signal depended on distinct CK receptors, phosphotransmitter proteins and several B-type response regulators. Further, CK functioned through floral integrators such as OVEREXPRESSION OF CONSTANS1 (SOC1) and components of the age pathway. The CK status of plants affected the levels of the age pathway microRNAs miR156 and miR172. Cytokinin-promoted flowering required the miR156-target SQUAMOSA PROMOTER BINDING PROTEIN-LIKE15 (SPL15) and miR172, and the late-flowering phenotype of LD-grown CK-deficient plants depended on miR172-targeted APETALA2 (AP2)-like genes encoding floral repressors. Collectively, this study shows that CK regulates flowering time through the two-component signaling system and components of the age pathway, providing a genetic framework for future investigations.