Targeting novel chemical and constitutive primed metabolites against Plectosphaerella cucumerina.

Priming is a physiological state for protection of plants against a broad range of pathogens, and is achieved through stimulation of the plant immune system. Various stimuli, such as beneficial microbes and chemical induction, activate defense priming. In the present study, we demonstrate that impairment of the high-affinity nitrate transporter 2.1 (encoded by NRT2.1) enables Arabidopsis to respond more quickly and strongly to Plectosphaerella cucumerina attack, leading to enhanced resistance. The Arabidopsis thaliana mutant lin1 (affected in NRT2.1) is a priming mutant that displays constitutive resistance to this necrotroph, with no associated developmental or growth costs. Chemically induced priming by ß-aminobutyric acid treatment, the constitutive priming mutant ocp3 and the constitutive priming present in the lin1 mutant result in a common metabolic profile within the same plant-pathogen interactions. The defense priming significantly affects sugar metabolism, cell-wall remodeling and shikimic acid derivatives levels, and results in specific changes in the amino acid profile and three specific branches of Trp metabolism, particularly accumulation of indole acetic acid, indole-3-carboxaldehyde and camalexin, but not the indolic glucosinolates. Metabolomic analysis facilitated identification of three metabolites in the priming fingerprint: galacturonic acid, indole-3-carboxylic acid and hypoxanthine. Treatment of plants with the latter two metabolites by soil drenching induced resistance against P. cucumerina, demonstrating that these compounds are key components of defense priming against this necrotrophic fungus. Here we demonstrate that indole-3-carboxylic acid induces resistance by promoting papillae deposition and H2 O2 production, and that this is independent of PR1, VSP2 and PDF1.2 priming.

Soluble phenylpropanoids are involved in the defense response of Arabidopsis against Verticillium longisporum.

Verticillium longisporum is a soil-borne vascular pathogen causing economic loss in rape. Using the model plant Arabidopsis this study analyzed metabolic changes upon fungal infection in order to identify possible defense strategies of Brassicaceae against this fungus. Metabolite fingerprinting identified infection-induced metabolites derived from the phenylpropanoid pathway. Targeted analysis confirmed the accumulation of sinapoyl glucosides, coniferin, syringin and lignans in leaves from early stages of infection on. At later stages, the amounts of amino acids increased. To test the contribution of the phenylpropanoid pathway, mutants in the pathway were analyzed. The sinapate-deficient mutant fah1-2 showed stronger infection symptoms than wild-type plants, which is most likely due to the lack of sinapoyl esters. Moreover, the coniferin accumulating transgenic plant UGT72E2-OE was less susceptible. Consistently, sinapoyl glucose, coniferyl alcohol and coniferin inhibited fungal growth and melanization in vitro, whereas sinapyl alcohol and syringin did not. The amount of lignin was not significantly altered supporting the notion that soluble derivatives of the phenylpropanoid pathway contribute to defense. These data show that soluble phenylpropanoids are important for the defense response of Arabidopsis against V. longisporum and that metabolite fingerprinting is a valuable tool to identify infection-relevant metabolic markers.

Verticillium transcription activator of adhesion Vta2 suppresses microsclerotia formation and is required for systemic infection of plant roots.

Six transcription regulatory genes of the Verticillium plant pathogen, which reprogrammed nonadherent budding yeasts for adhesion, were isolated by a genetic screen to identify control elements for early plant infection. Verticillium transcription activator of adhesion Vta2 is highly conserved in filamentous fungi but not present in yeasts. The Magnaporthe grisea ortholog conidiation regulator Con7 controls the formation of appressoria which are absent in Verticillium species. Vta2 was analyzed by using genetics, cell biology, transcriptomics, secretome proteomics and plant pathogenicity assays. Nuclear Vta2 activates the expression of the adhesin-encoding yeast flocculin genes FLO1 and FLO11. Vta2 is required for fungal growth of Verticillium where it is a positive regulator of conidiation. Vta2 is mandatory for accurate timing and suppression of microsclerotia as resting structures. Vta2 controls expression of 270 transcripts, including 10 putative genes for adhesins and 57 for secreted proteins. Vta2 controls the level of 125 secreted proteins, including putative adhesins or effector molecules and a secreted catalase-peroxidase. Vta2 is a major regulator of fungal pathogenesis, and controls host-plant root infection and H2 O2 detoxification. Verticillium impaired in Vta2 is unable to colonize plants and induce disease symptoms. Vta2 represents an interesting target for controlling the growth and development of these vascular pathogens.

Single-Institution Prospective Evaluation of Moderately Hypofractionated Whole-Breast Radiation Therapy With Simultaneous Integrated Boost With or Without Lymphatic Drainage Irradiation After Breast-Conserving Surgery.

Purpose: We report treatment outcomes for patients who received adjuvant moderate hypofractionated whole-breast radiation therapy with simultaneous integrated boost (SIB-mhWBRT) after breast-conserving surgery. Methods and Materials: SIB-mhWBRT for patients with breast cancer was introduced in our department in July 2017. This prospective evaluation includes 424 consecutive patients treated with SIB-mhWBRT for stage I-III invasive breast cancer (n = 391) and/or ductal carcinoma in situ (n = 33) until December 2021. SIB-mhWBRT was applied with 40 Gy in 15 daily fractions over 3 weeks according to the START B trial, with an SIB dose to the tumor bed of 48 Gy according to Radiation Therapy Oncology Group 1005/UK-IMPORT-HIGH, delivered as 3-dinemsional conformal radiation therapy (RT; n = 402), intensity modulated RT (n = 4), or volumetric modulated arc therapy (n = 18). The mean patient age was 60 years (range, 27-88). Since May 2018, patients with indications for lymphatic pathway RT were included (n = 62). Baseline parameters and follow-up data were recorded and reported, including objective assessment of treatment-related outcomes and subjective patient-reported outcome measures (PROMs). Results: Mean/median follow-up was 29/33 months (range, 2-60). Acute toxicity grade 0, 1, 2, and 3 was observed in 25.0%, 61.4%, 13.3%, and 0%, respectively, at the completion of RT. Data of 281, 266, 243, 172, and 58 patients were available for 6-month and 1-, 2-, 3-, and 4-year follow-up, respectively. Grade 2 late effects were identified in 8.5%, 6.0%, 4.9%, 2.2%, and 10.2% and grade 3 in 2.8%, 1.1%, 1.2%, 0%, and 0% of patients at 6-month and 1-, 2-, 3-, and 4-year follow-up, respectively. Medical treatment of breast edema was the only grade 3 late effect observed. PROM cosmesis results were evaluated as excellent-good, fair, and poor in 97.2%, 2.5%, and 0.4%; 96.5%, 3.1%, and 0.4%; 97.4%, 2.2%, and 0.4%; 97.5%, 2.5%, and 0%; and 96.5%, 3.5%, and 0.0% at 6 months and 1, 2, 3, and 4 years post-RT, respectively. For all patients, the 3-year overall, cancer-specific, and disease-free survival rates were 98.2%, 99.1%, and 95.9%, respectively. Three-year risk of any locoregional recurrence was 0.6%. No mortality or relapse was observed in patients with ductal carcinoma in situ. Conclusions: SIB-mhWBRT demonstrated very favorable side effect profiles and cosmesis/PROMs. Three-year results demonstrate excellent locoregional control. This short-term regimen offers substantial patient comfort and improves institutional efficacy.

Arabidopsis mutants of sphingolipid fatty acid α-hydroxylases accumulate ceramides and salicylates.

In Arabidopsis, the fatty acid moiety of sphingolipids is mainly α-hydroxylated. The consequences of a reduction in this modification were analysed. Mutants of both Fatty Acid Hydroxylase genes (AtFAH1 and AtFAH2) were analysed for sphingolipid profiles. To elucidate further consequences of the mutations, metabolic analyses were performed and the influence on pathogen defence was determined. Ceramide and glucosylceramide profiles of double-mutant plants showed a reduction in sphingolipids with α-hydroxylated fatty acid moieties, and an accumulation of sphingolipids without these moieties. In addition, the free trihydroxylated long-chain bases and ceramides were increased by five- and ten-fold, respectively, whereas the amount of glucosylceramides was decreased by 25%. Metabolite analysis of the double mutant revealed salicylates as enriched metabolites. Infection experiments supported the metabolic changes, as the double mutant showed an enhanced disease-resistant phenotype for infection with the obligate biotrophic pathogen Golovinomyces cichoracearum. In summary, these results suggest that fatty acid hydroxylation of ceramides is important for the biosynthesis of complex sphingolipids. Its absence leads to the accumulation of long-chain bases and ceramides as their precursors. This increases salicylate levels and resistance towards obligate biotrophic fungal pathogens, confirming a role of sphingolipids in salicylic acid-dependent defence reactions.

MarVis-Filter: ranking, filtering, adduct and isotope correction of mass spectrometry data.

Statistical ranking, filtering, adduct detection, isotope correction, and molecular formula calculation are essential tasks in processing mass spectrometry data in metabolomics studies. In order to obtain high-quality data sets, a framework which incorporates all these methods is required. We present the MarVis-Filter software, which provides well-established and specialized methods for processing mass spectrometry data. For the task of ranking and filtering multivariate intensity profiles, MarVis-Filter provides the ANOVA and Kruskal-Wallis tests with adjustment for multiple hypothesis testing. Adduct and isotope correction are based on a novel algorithm which takes the similarity of intensity profiles into account and allows user-defined ionization rules. The molecular formula calculation utilizes the results of the adduct and isotope correction. For a comprehensive analysis, MarVis-Filter provides an interactive interface to combine data sets deriving from positive and negative ionization mode. The software is exemplarily applied in a metabolic case study, where octadecanoids could be identified as markers for wounding in plants.

The COP9 signalosome mediates transcriptional and metabolic response to hormones, oxidative stress protection and cell wall rearrangement during fungal development.

The COP9 signalosome complex (CSN) is a crucial regulator of ubiquitin ligases. Defects in CSN result in embryonic impairment and death in higher eukaryotes, whereas the filamentous fungus Aspergillus nidulans survives without CSN, but is unable to complete sexual development. We investigated overall impact of CSN activity on A. nidulans cells by combined transcriptome, proteome and metabolome analysis. Absence of csn5/csnE affects transcription of at least 15% of genes during development, including numerous oxidoreductases. csnE deletion leads to changes in the fungal proteome indicating impaired redox regulation and hypersensitivity to oxidative stress. CSN promotes the formation of asexual spores by regulating developmental hormones produced by PpoA and PpoC dioxygenases. We identify more than 100 metabolites, including orsellinic acid derivatives, accumulating preferentially in the csnE mutant. We also show that CSN is required to activate glucanases and other cell wall recycling enzymes during development. These findings suggest a dual role for CSN during development: it is required early for protection against oxidative stress and hormone regulation and is later essential for control of the secondary metabolism and cell wall rearrangement.

Pseudomonas Strains Induce Transcriptional and Morphological Changes and Reduce Root Colonization of Verticillium spp.

Phytopathogenic Verticillia cause Verticillium wilt on numerous economically important crops. Plant infection begins at the roots, where the fungus is confronted with rhizosphere inhabiting bacteria. The effects of different fluorescent pseudomonads, including some known biocontrol agents of other plant pathogens, on fungal growth of the haploid Verticillium dahliae and/or the amphidiploid Verticillium longisporum were compared on pectin-rich medium, in microfluidic interaction channels, allowing visualization of single hyphae, or on Arabidopsis thaliana roots. We found that the potential for formation of bacterial lipopeptide syringomycin resulted in stronger growth reduction effects on saprophytic Aspergillus nidulans compared to Verticillium spp. A more detailed analyses on bacterial-fungal co-cultivation in narrow interaction channels of microfluidic devices revealed that the strongest inhibitory potential was found for Pseudomonas protegens CHA0, with its inhibitory potential depending on the presence of the GacS/GacA system controlling several bacterial metabolites. Hyphal tip polarity was altered when V. longisporum was confronted with pseudomonads in narrow interaction channels, resulting in a curly morphology instead of straight hyphal tip growth. These results support the hypothesis that the fungus attempts to evade the bacterial confrontation. Alterations due to co-cultivation with bacteria could not only be observed in fungal morphology but also in fungal transcriptome. P. protegens CHA0 alters transcriptional profiles of V. longisporum during 2 h liquid media co-cultivation in pectin-rich medium. Genes required for degradation of and growth on the carbon source pectin were down-regulated, whereas transcripts involved in redox processes were up-regulated. Thus, the secondary metabolite mediated effect of Pseudomonas isolates on Verticillium species results in a complex transcriptional response, leading to decreased growth with precautions for self-protection combined with the initiation of a change in fungal growth direction. This interplay of bacterial effects on the pathogen can be beneficial to protect plants from infection, as shown with A. thaliana root experiments. Treatment of the roots with bacteria prior to infection with V. dahliae resulted in a significant reduction of fungal root colonization. Taken together we demonstrate how pseudomonads interfere with the growth of Verticillium spp. and show that these bacteria could serve in plant protection.

Verticillium longisporum Elicits Media-Dependent Secretome Responses With Capacity to Distinguish Between Plant-Related Environments.

Verticillia cause a vascular wilt disease affecting a broad range of economically valuable crops. The fungus enters its host plants through the roots and colonizes the vascular system. It requires extracellular proteins for a successful plant colonization. The exoproteomes of the allodiploid Verticillium longisporum upon cultivation in different media or xylem sap extracted from its host plant Brassica napus were compared. Secreted fungal proteins were identified by label free liquid chromatography-tandem mass spectrometry screening. V. longisporum induced two main secretion patterns. One response pattern was elicited in various non-plant related environments. The second pattern includes the exoprotein responses to the plant-related media, pectin-rich simulated xylem medium and pure xylem sap, which exhibited similar but additional distinct features. These exoproteomes include a shared core set of 221 secreted and similarly enriched fungal proteins. The pectin-rich medium significantly induced the secretion of 143 proteins including a number of pectin degrading enzymes, whereas xylem sap triggered a smaller but unique fungal exoproteome pattern with 32 enriched proteins. The latter pattern included proteins with domains of known pathogenicity factors, metallopeptidases and carbohydrate-active enzymes. The most abundant proteins of these different groups are the necrosis and ethylene inducing-like proteins Nlp2 and Nlp3, the cerato-platanin proteins Cp1 and Cp2, the metallopeptidases Mep1 and Mep2 and the carbohydrate-active enzymes Gla1, Amy1 and Cbd1. Their pathogenicity contribution was analyzed in the haploid parental strain V. dahliae. Deletion of the majority of the corresponding genes caused no phenotypic changes during ex planta growth or invasion and colonization of tomato plants. However, we discovered that the MEP1, NLP2, and NLP3 deletion strains were compromised in plant infections. Overall, our exoproteome approach revealed that the fungus induces specific secretion responses in different environments. The fungus has a general response to non-plant related media whereas it is able to fine-tune its exoproteome in the presence of plant material. Importantly, the xylem sap-specific exoproteome pinpointed Nlp2 and Nlp3 as single effectors required for successful V. dahliae colonization.

MarVis: a tool for clustering and visualization of metabolic biomarkers.

BACKGROUND: A central goal of experimental studies in systems biology is to identify meaningful markers that are hidden within a diffuse background of data originating from large-scale analytical intensity measurements as obtained from metabolomic experiments. Intensity-based clustering is an unsupervised approach to the identification of metabolic markers based on the grouping of similar intensity profiles. A major problem of this basic approach is that in general there is no prior information about an adequate number of biologically relevant clusters. RESULTS: We present the tool MarVis (Marker Visualization) for data mining on intensity-based profiles using one-dimensional self-organizing maps (1D-SOMs). MarVis can import and export customizable CSV (Comma Separated Values) files and provides aggregation and normalization routines for preprocessing of intensity profiles that contain repeated measurements for a number of different experimental conditions. Robust clustering is then achieved by training of an 1D-SOM model, which introduces a similarity-based ordering of the intensity profiles. The ordering allows a convenient visualization of the intensity variations within the data and facilitates an interactive aggregation of clusters into larger blocks. The intensity-based visualization is combined with the presentation of additional data attributes, which can further support the analysis of experimental data. CONCLUSION: MarVis is a user-friendly and interactive tool for exploration of complex pattern variation in a large set of experimental intensity profiles. The application of 1D-SOMs gives a convenient overview on relevant profiles and groups of profiles. The specialized visualization effectively supports researchers in analyzing a large number of putative clusters, even though the true number of biologically meaningful groups is unknown. Although MarVis has been developed for the analysis of metabolomic data, the tool may be applied to gene expression data as well.

Divergent co-transcriptomes of different host cells infected with Toxoplasma gondii reveal cell type-specific host-parasite interactions.

The apicomplexan parasite Toxoplasma gondii infects various cell types in avian and mammalian hosts including humans. Infection of immunocompetent hosts is mostly asymptomatic or benign, but leads to development of largely dormant bradyzoites that persist predominantly within neurons and muscle cells. Here we have analyzed the impact of the host cell type on the co-transcriptomes of host and parasite using high-throughput RNA sequencing. Murine cortical neurons and astrocytes, skeletal muscle cells (SkMCs) and fibroblasts differed by more than 16,200 differentially expressed genes (DEGs) before and after infection with T. gondii. However, only a few hundred of them were regulated by infection and these largely diverged in neurons, SkMCs, astrocytes and fibroblasts indicating host cell type-specific transcriptional responses after infection. The heterogeneous transcriptomes of host cells before and during infection coincided with ~5,400 DEGs in T. gondii residing in different cell types. Finally, we identified gene clusters in both T. gondii and its host, which correlated with the predominant parasite persistence in neurons or SkMCs as compared to astrocytes or fibroblasts. Thus, heterogeneous expression profiles of different host cell types and the parasites' ability to adapting to them may govern the parasite-host cell interaction during toxoplasmosis.

Non-targeted metabolomics by high resolution mass spectrometry in HPRT knockout mice.

AIMS: Lesch-Nyhan disease (LND) is characterized by hyperuricemia as well as neurological and neuropsychiatric symptoms including repetitive self-injurious behavior. Symptoms are caused by a deficiency of the enzyme hypoxanthine-guanine phosphoribosyltransferase (HPRT) as a result of a mutation on the X chromosome. To elucidate the pathophysiology of LND, we performed a metabolite screening for brain and serum extracts from HPRT knockout mice as an animal model for LND. MAIN METHODS: Analyses were performed by high performance liquid chromatography (HPLC)-coupled quadrupole time-of-flight mass spectrometry (QTOF-MS). KEY FINDINGS: In brain extracts, we found six metabolites with significantly different contents in wild-type and HPRT-deficient mice. Two compounds we could identify as 5-aminoimidazole-4-carboxamide ribotide (AICAR) and 1-methylimidazole-4-acetic acid (1-MI4AA). Whereas AICAR was accumulated in brains of HPRT knockout mice, 1-MI4AA was decreased in these mice. SIGNIFICANCE: Both metabolites play a role in histidine metabolism and, as a consequence, histamine metabolism. AICAR, in addition, is part of the purine metabolism. Our findings may help to better understand the mechanisms leading to the behavioral phenotype of LND.

MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data.

A central aim in the evaluation of non-targeted metabolomics data is the detection of intensity patterns that differ between experimental conditions as well as the identification of the underlying metabolites and their association with metabolic pathways. In this context, the identification of metabolites based on non-targeted mass spectrometry data is a major bottleneck. In many applications, this identification needs to be guided by expert knowledge and interactive tools for exploratory data analysis can significantly support this process. Additionally, the integration of data from other omics platforms, such as DNA microarray-based transcriptomics, can provide valuable hints and thereby facilitate the identification of metabolites via the reconstruction of related metabolic pathways. We here introduce the MarVis-Pathway tool, which allows the user to identify metabolites by annotation of pathways from cross-omics data. The analysis is supported by an extensive framework for pathway enrichment and meta-analysis. The tool allows the mapping of data set features by ID, name, and accurate mass, and can incorporate information from adduct and isotope correction of mass spectrometry data. MarVis-Pathway was integrated in the MarVis-Suite (http://marvis.gobics.de), which features the seamless highly interactive filtering, combination, clustering, and visualization of omics data sets. The functionality of the new software tool is illustrated using combined mass spectrometry and DNA microarray data. This application confirms jasmonate biosynthesis as important metabolic pathway that is upregulated during the wound response of Arabidopsis plants.

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

Integrative study of Arabidopsis thaliana metabolomic and transcriptomic data with the interactive MarVis-Graph software.

State of the art high-throughput technologies allow comprehensive experimental studies of organism metabolism and induce the need for a convenient presentation of large heterogeneous datasets. Especially, the combined analysis and visualization of data from different high-throughput technologies remains a key challenge in bioinformatics. We present here the MarVis-Graph software for integrative analysis of metabolic and transcriptomic data. All experimental data is investigated in terms of the full metabolic network obtained from a reference database. The reactions of the network are scored based on the associated data, and sub-networks, according to connected high-scoring reactions, are identified. Finally, MarVis-Graph scores the detected sub-networks, evaluates them by means of a random permutation test and presents them as a ranked list. Furthermore, MarVis-Graph features an interactive network visualization that provides researchers with a convenient view on the results. The key advantage of MarVis-Graph is the analysis of reactions detached from their pathways so that it is possible to identify new pathways or to connect known pathways by previously unrelated reactions. The MarVis-Graph software is freely available for academic use and can be downloaded at: http://marvis.gobics.de/marvis-graph.

Membrane-bound methyltransferase complex VapA-VipC-VapB guides epigenetic control of fungal development.

Epigenetic and transcriptional control of gene expression must be coordinated in response to external signals to promote alternative multicellular developmental programs. The membrane-associated trimeric complex VapA-VipC-VapB controls a signal transduction pathway for fungal differentiation. The VipC-VapB methyltransferases are tethered to the membrane by the FYVE-like zinc finger protein VapA, allowing the nuclear VelB-VeA-LaeA complex to activate transcription for sexual development. Once the release from VapA is triggered, VipC-VapB is transported into the nucleus. VipC-VapB physically interacts with VeA and reduces its nuclear import and protein stability, thereby reducing the nuclear VelB-VeA-LaeA complex. Nuclear VapB methyltransferase diminishes the establishment of facultative heterochromatin by decreasing histone 3 lysine 9 trimethylation (H3K9me3). This favors activation of the regulatory genes brlA and abaA, which promote the asexual program. The VapA-VipC-VapB methyltransferase pathway combines control of nuclear import and stability of transcription factors with histone modification to foster appropriate differentiation responses.

Metabolite-based clustering and visualization of mass spectrometry data using one-dimensional self-organizing maps.

BACKGROUND: One of the goals of global metabolomic analysis is to identify metabolic markers that are hidden within a large background of data originating from high-throughput analytical measurements. Metabolite-based clustering is an unsupervised approach for marker identification based on grouping similar concentration profiles of putative metabolites. A major problem of this approach is that in general there is no prior information about an adequate number of clusters. RESULTS: We present an approach for data mining on metabolite intensity profiles as obtained from mass spectrometry measurements. We propose one-dimensional self-organizing maps for metabolite-based clustering and visualization of marker candidates. In a case study on the wound response of Arabidopsis thaliana, based on metabolite profile intensities from eight different experimental conditions, we show how the clustering and visualization capabilities can be used to identify relevant groups of markers. CONCLUSION: Our specialized realization of self-organizing maps is well-suitable to gain insight into complex pattern variation in a large set of metabolite profiles. In comparison to other methods our visualization approach facilitates the identification of interesting groups of metabolites by means of a convenient overview on relevant intensity patterns. In particular, the visualization effectively supports researchers in analyzing many putative clusters when the true number of biologically meaningful groups is unknown.