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Joachim Kopka

Publications and source records attributed to Joachim Kopka.

At least 19 recordsLinked to original sources
PubMed2025

Unveiling Potato Cultivars With Microbiome Interactive Traits for Sustainable Agricultural Production.

Root traits significantly shape rhizosphere microbiomes, yet their interaction with microbes is often overlooked in plant breeding programs. Here, we propose that selecting modern cultivars based on microbiome interactive trait (MIT), such as root biomass, exudate patterns and the rhizosphere microbiome, can enhance agricultural sustainability by interacting effectively with soil microbiomes, which in turn, promotes plant growth and resistance to stress, thereby reducing reliance on synthetic crop protectants. Through a stepwise selection process (in silico and in vitro) that started with approximately 1000 potato genotypes, we chose 51 potato cultivars based on known phenotypical properties and distinct root exudate patterns. We conducted a greenhouse experiment to evaluate their capacity to interact with the soil microbiome and to assess their MIT scores. Our findings revealed that cultivars significantly influence plant growth, metabolite profiles, and rhizosphere fungal community composition. Moreover, we observed a positive correlation between microbial community diversity and root biomass. Additionally, leaf metabolites were correlated with rhizosphere bacterial composition, supporting the plant holobiont framework. Utilising z-scores, we aggregated all data related to plant growth, metabolomes, and microbiomes, creating a classification of 51 cultivars based on a gradient of MIT scores. By examining the distribution of low, intermediate, and high MIT, we identified a group of 11 potato cultivars suitable for further studies to assess their resilience and productivity under low-input production systems. This study provides an in-depth correlation between microbiome and several plant traits across 51 cultivars, offering tools to facilitate and expedite the incorporation of microbiome traits into breeding goals to support sustainable agriculture.

Solanum tuberosum↗
PubMed2005

Identification of brassinosteroid-related genes by means of transcript co-response analyses.

The comprehensive systems-biology database (CSB.DB) was used to reveal brassinosteroid (BR)-related genes from expression profiles based on co-response analyses. Genes exhibiting simultaneous changes in transcript levels are candidates of common transcriptional regulation. Combining numerous different experiments in data matrices allows ruling out outliers and conditional changes of transcript levels. CSB.DB was queried for transcriptional co-responses with the BR-signalling components BRI1 and BAK1: 301 out of 9694 genes represented in the nasc0271 database showed co-responses with both genes. As expected, these genes comprised pathway-involved genes (e.g. 72 BR-induced genes), because the BRI1 and BAK1 proteins are required for BR-responses. But transcript co-response takes the analysis a step further compared with direct approaches because BR-related non BR-responsive genes were identified. Insights into networks and the functional context of genes are provided, because factors determining expression patterns are reflected in correlations. Our findings demonstrate that transcript co-response analysis presents a valuable resource to uncover common regulatory patterns of genes. Different data matrices in CSB.DB allow examination of specific biological questions. All matrices are publicly available through CSB.DB. This work presents one possible roadmap to use the CSB.DB resources.

Arabidopsis↗
PubMed2005

Systems rebalancing of metabolism in response to sulfur deprivation, as revealed by metabolome analysis of Arabidopsis plants.

Sulfur is an essential macro-element in plant and animal nutrition. Plants assimilate inorganic sulfate into two sulfur-containing amino acids, cysteine and methionine. Low supply of sulfate leads to decreased sulfur pools within plant tissues. As sulfur-related metabolites represent an integral part of plant metabolism with multiple interactions, sulfur deficiency stress induces a number of adaptive responses, which must be coordinated. To reveal the coordinating network of adaptations to sulfur deficiency, metabolite profiling of Arabidopsis has been undertaken. Gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry techniques revealed the response patterns of 6,023 peaks of nonredundant ion traces and relative concentration levels of 134 nonredundant compounds of known chemical structure. Here, we provide a catalogue of the detected metabolic changes and reconstruct the coordinating network of their mutual influences. The observed decrease in biomass, as well as in levels of proteins, chlorophylls, and total RNA, gives evidence for a general reduction of metabolic activity under conditions of depleted sulfur supply. This is achieved by a systemic adjustment of metabolism involving the major metabolic pathways. Sulfur/carbon/nitrogen are partitioned by accumulation of metabolites along the pathway O-acetylserine to serine to glycine, and are further channeled together with the nitrogen-rich compound glutamine into allantoin. Mutual influences between sulfur assimilation, nitrogen imbalance, lipid breakdown, purine metabolism, and enhanced photorespiration associated with sulfur-deficiency stress are revealed in this study. These responses may be assembled into a global scheme of metabolic regulation induced by sulfur nutritional stress, which optimizes resources for seed production.

Amino Acids↗
PubMed2005

Lotus japonicus metabolic profiling. Development of gas chromatography-mass spectrometry resources for the study of plant-microbe interactions.

Symbiotic nitrogen fixation (SNF) in legume root nodules requires differentiation and integration of both plant and bacterial metabolism. Classical approaches of biochemistry, molecular biology, and genetics have revealed many aspects of primary metabolism in legume nodules that underpin SNF. Functional genomics approaches, especially transcriptomics and proteomics, are beginning to provide a more holistic picture of the metabolic potential of nodules in model legumes like Medicago truncatula and Lotus japonicus. To extend these approaches, we have established protocols for nonbiased measurement and analysis of hundreds of metabolites from L. japonicus, using gas chromatography coupled with mass spectrometry. Following creation of mass spectral tag libraries, which represent both known and unknown metabolites, we measured and compared relative metabolite levels in nodules, roots, leaves, and flowers of symbiotic plants. Principal component analysis of the data revealed distinct metabolic phenotypes for the different organs and led to the identification of marker metabolites for each. Metabolites that were enriched in nodules included: octadecanoic acid, asparagine, glutamate, homoserine, cysteine, putrescine, mannitol, threonic acid, gluconic acid, glyceric acid-3-P, and glycerol-3-P. Hierarchical cluster analysis enabled discrimination of 10 groups of metabolites, based on distribution patterns in diverse Lotus organs. The resources and tools described here, together with ongoing efforts in the areas of genome sequencing, and transcriptome and proteome analysis of L. japonicus and Mesorhizobium loti, should lead to a better understanding of nodule metabolism that underpins SNF.

Gas Chromatography-Mass Spectrometry↗
PubMed2005

Profiling of diurnal patterns of metabolite and transcript abundance in potato (Solanum tuberosum) leaves.

Diurnal changes in carbohydrates and a broad range of primary metabolites were analysed through a diurnal period in potato leaves (Solanum tuberosum cv. Desiree) using an established gas chromatography-mass spectrometry based metabolic profiling protocol alongside conventional spectrophotometric technologies. In tandem, we profiled transcript levels using both a custom array containing approximately 2,500 cDNA clones predominantly representing transcripts involved in primary metabolism and commercially available arrays containing approximately 12,000 cDNA clones that gave coverage of transcript levels over a broader functional range. The levels of many metabolites and transcripts varied during the diurnal period with 56 significant differences observed in the metabolite contents and 832 significant differences recorded in transcript levels. Whilst a large number of the differences would be expected from what has been known previously, several novel changes were observed in these experiments. Notably, qualitative comparison of the combined data sets obtained from the parallel analysis of transcripts and metabolites suggests relatively few changes in gene expression strongly correlate with changes in metabolite levels during a diurnal cycle. Furthermore, these changes appear to be confined to the central metabolic pathways. However, principal component analysis of the metabolic profiles obtained here revealed that metabolite patterns change progressively through a diurnal period suggesting the operation of mechanisms for tight temporal regulation of metabolite composition.

Amino Acids↗
PubMed2005

GC-MS libraries for the rapid identification of metabolites in complex biological samples.

Gas chromatography-mass spectrometry based metabolite profiling of biological samples is rapidly becoming one of the cornerstones of functional genomics and systems biology. Thus, the technology needs to be available to many laboratories and open exchange of information is required such as those achieved for transcript and protein data. The key-step in metabolite profiling is the unambiguous identification of metabolites in highly complex metabolite preparations with composite structure. Collections of mass spectra, which comprise frequently observed identified and non-identified metabolites, represent the most effective means to pool the identification efforts currently performed in many laboratories around the world. Here, we describe a platform for mass spectral and retention time index libraries that will enable this process (MSRI; www.csbdb.mpimp-golm.mpg.de/gmd.html). This resource should ameliorate many of the problems that each laboratory will face both for the initial establishment of metabolome analysis and for its maintenance at a constant sample throughput.

Amino Acids↗
PubMed2005

Metabolome analysis: the potential of in vivo labeling with stable isotopes for metabolite profiling.

Metabolome analysis technologies are still in early development because, unlike genome, transcriptome and proteome analyses, metabolome analysis has to deal with a highly diverse range of biomolecules. Combinations of different analytical platforms are therefore required for comprehensive metabolomic studies. Each of these platforms covers only part of the metabolome. To establish multiparallel technologies, thorough standardization of each measured metabolite is required. Standardization is best achieved by addition of a specific stable isotope-labeled compound, a mass isotopomer, for each metabolite. This suggestion, at first glance, seems unrealistic because of cost and time constraints. A possible solution to this problem is discussed in this article. Saturation in vivo labeling with stable isotopes enables the biosynthesis of differentially mass-labeled metabolite mixtures, which can be exploited for highly standardized metabolite profiling by mass isotopomer ratios.

Biochemistry↗
PubMed2004

GMD@CSB.DB: the Golm Metabolome Database.

UNLABELLED: Metabolomics, in particular gas chromatography-mass spectrometry (GC-MS) based metabolite profiling of biological extracts, is rapidly becoming one of the cornerstones of functional genomics and systems biology. Metabolite profiling has profound applications in discovering the mode of action of drugs or herbicides, and in unravelling the effect of altered gene expression on metabolism and organism performance in biotechnological applications. As such the technology needs to be available to many laboratories. For this, an open exchange of information is required, like that already achieved for transcript and protein data. One of the key-steps in metabolite profiling is the unambiguous identification of metabolites in highly complex metabolite preparations from biological samples. Collections of mass spectra, which comprise frequently observed metabolites of either known or unknown exact chemical structure, represent the most effective means to pool the identification efforts currently performed in many laboratories around the world. Here we present GMD, The Golm Metabolome Database, an open access metabolome database, which should enable these processes. GMD provides public access to custom mass spectral libraries, metabolite profiling experiments as well as additional information and tools, e.g. with regard to methods, spectral information or compounds. The main goal will be the representation of an exchange platform for experimental research activities and bioinformatics to develop and improve metabolomics by multidisciplinary cooperation. AVAILABILITY: http://csbdb.mpimp-golm.mpg.de/gmd.html CONTACT: Steinhauser@mpimp-golm.mpg.de SUPPLEMENTARY INFORMATION: http://csbdb.mpimp-golm.mpg.de/

Database Management Systems↗
PubMed2004

Exploring the temperature-stress metabolome of Arabidopsis.

Metabolic profiling analyses were performed to determine metabolite temporal dynamics associated with the induction of acquired thermotolerance in response to heat shock and acquired freezing tolerance in response to cold shock. Low-M(r) polar metabolite analyses were performed using gas chromatography-mass spectrometry. Eighty-one identified metabolites and 416 unidentified mass spectral tags, characterized by retention time indices and specific mass fragments, were monitored. Cold shock influenced metabolism far more profoundly than heat shock. The steady-state pool sizes of 143 and 311 metabolites or mass spectral tags were altered in response to heat and cold shock, respectively. Comparison of heat- and cold-shock response patterns revealed that the majority of heat-shock responses were shared with cold-shock responses, a previously unknown relationship. Coordinate increases in the pool sizes of amino acids derived from pyruvate and oxaloacetate, polyamine precursors, and compatible solutes were observed during both heat and cold shock. In addition, many of the metabolites that showed increases in response to both heat and cold shock in this study were previously unlinked with temperature stress. This investigation provides new insight into the mechanisms of plant adaptation to thermal stress at the metabolite level, reveals relationships between heat- and cold-shock responses, and highlights the roles of known signaling molecules and protectants.

Acclimatization↗
PubMed2004

CSB.DB: a comprehensive systems-biology database.

SUMMARY: The open access comprehensive systems-biology database (CSB.DB) presents the results of bio-statistical analyses on gene expression data in association with additional biochemical and physiological knowledge. The main aim of this database platform is to provide tools that support insight into life's complexity pyramid with a special focus on the integration of data from transcript and metabolite profiling experiments. The central part of CSB.DB, which we describe in this applications note, is a set of co-response databases that currently focus on the three key model organisms, Escherichia coli, Saccharomyces cerevisiae and Arabidopsis thaliana. CSB.DB gives easy access to the results of large-scale co-response analyses, which are currently based exclusively on the publicly available compendia of transcript profiles. By scanning for the best co-responses among changing transcript levels, CSB.DB allows to infer hypotheses on the functional interaction of genes. These hypotheses are novel and not accessible through analysis of sequence homology. The database enables the search for pairs of genes and larger units of genes, which are under common transcriptional control. In addition, statistical tools are offered to the user, which allow validation and comparison of those co-responses that were discovered by gene queries performed on the currently available set of pre-selectable datasets. AVAILABILITY: All co-response databases can be accessed through the CSB.DB Web server (http://csbdb.mpimp-golm.mpg.de/).

Database Management Systems↗
PubMed2004

Metabolite profiling in plant biology: platforms and destinations.

Optimal use of genome sequences and gene-expression resources requires powerful phenotyping platforms, including those for systematic analysis of metabolite composition. The most used technologies for metabolite profiling, including mass spectral, nuclear magnetic resonance and enzyme-based approaches, have various advantages and disadvantages, and problems can arise with reliability and the interpretation of the huge datasets produced. These techniques will be useful for answering important biological questions in the future.

Biology↗
PubMed2004

PaVESy: Pathway Visualization and Editing System.

UNLABELLED: A data managing system for editing and visualization of biological pathways is presented. The main component of PaVESy (Pathway Visualization and Editing System) is a relational SQL database system. The database design allows storage of biological objects, such as metabolites, proteins, genes and respective relations, which are required to assemble metabolic and regulatory biological interactions. The database model accommodates highly flexible annotation of biological objects by user-defined attributes. In addition, specific roles of objects are derived from these attributes in the context of user-defined interactions, e.g. in the course of pathway generation or during editing of the database content. Furthermore, the user may organize and arrange the database content within a folder structure and is free to group and annotate database objects of interest within customizable subsets. Thus, we allow an individualized view on the database content and facilitate user customization. A JAVA-based class library was developed, which serves as the database programming interface to PaVESy. This API provides classes, which implement the concepts of object persistence in SQL databases, such as entries, interactions, annotations, folders and subsets. We created editing and visualization tools for navigation in and visualization of the database content. User approved pathway assemblies are stored and may be retrieved for continued modification, annotation and export. Data export is interfaced with a range of network visualization programs, such as Pajek or other software allowing import of SBML or GML data format. AVAILABILITY: http://pavsey.mpimp-golm.mpg.de

Database Management Systems↗
PubMed2004

Hypothesis-driven approach to predict transcriptional units from gene expression data.

MOTIVATION: A major issue in computational biology is the reconstruction of functional relationships among genes, for example the definition of regulatory or biochemical pathways. One step towards this aim is the elucidation of transcriptional units, which are characterized by co-responding changes in mRNA expression levels. These units of genes will allow the generation of hypotheses about respective functional interrelationships. Thus, the focus of analysis currently moves from well-established functional assignment through comparison of protein and DNA sequences towards analysis of transcriptional co-response. Tools that allow deducing common control of gene expression have the potential to complement and extend routine BLAST comparisons, because gene function may be inferred from common transcriptional control. RESULTS: We present a co-clustering strategy of genome sequence information and gene expression data, which was applied to identify transcriptional units within diverse compendia of expression profiles. The phenomenon of prokaryotic operons was selected as an ideal test case to generate well-founded hypotheses about transcriptional units. The existence of overlapping and ambiguous operon definitions allowed the investigation of constitutive and conditional expression of transcriptional units in independent gene expression experiments of Escherichia coli. Our approach allowed identification of operons with high accuracy. Furthermore, both constitutive mRNA co-response as well as conditional differences became apparent. Thus, we were able to generate insight into the possible biological relevance of gene co-response. We conclude that the suggested strategy will be amenable in general to the identification of transcriptional units beyond the chosen example of E.coli operons. AVAILABILITY: The analyses of E.coli transcript data presented here are available upon request or at http://csbdb.mpimp-golm.mpg.de/

Algorithms↗
PubMed2004

A proposed framework for the description of plant metabolomics experiments and their results.

The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known as ArMet (architecture for metabolomics). It encompasses the entire experimental time line from experiment definition and description of biological source material, through sample growth and preparation to the results of chemical analysis. Such formal data descriptions, which specify the full experimental context, enable principled comparison of data sets, allow proper interpretation of experimental results, permit the repetition of experiments and provide a basis for the design of systems for data storage and transmission. The current design and example implementations are freely available (http://www.armet.org/). We seek to advance discussion and community adoption of a standard for metabolomics, which would promote principled collection, storage and transmission of experiment data.

Database Management Systems↗
PubMed2004

Global changes in transcription orchestrate metabolic differentiation during symbiotic nitrogen fixation in Lotus japonicus.

Research on legume nodule metabolism has contributed greatly to our knowledge of primary carbon and nitrogen metabolism in plants in general, and in symbiotic nitrogen fixation in particular. However, most previous studies focused on one or a few genes/enzymes involved in selected metabolic pathways in many different legume species. We utilized the tools of transcriptomics and metabolomics to obtain an unprecedented overview of the metabolic differentiation that results from nodule development in the model legume, Lotus japonicus. Using an array of more than 5000 nodule cDNA clones, representing 2500 different genes, we identified approximately 860 genes that were more highly expressed in nodules than in roots. One-third of these are involved in metabolism and transport, and over 100 encode proteins that are likely to be involved in signalling, or regulation of gene expression at the transcriptional or post-transcriptional level. Several metabolic pathways appeared to be co-ordinately upregulated in nodules, including glycolysis, CO(2) fixation, amino acid biosynthesis, and purine, haem, and redox metabolism. Insight into the physiological conditions that prevail within nodules was obtained from specific sets of induced genes. In addition to the expected signs of hypoxia, numerous indications were obtained that nodule cells also experience P-limitation and osmotic stress. Several potential regulators of these stress responses were identified. Metabolite profiling by gas chromatography coupled to mass spectrometry revealed a distinct metabolic phenotype for nodules that reflected the global changes in metabolism inferred from transcriptome analysis.

Expressed Sequence Tags↗
PubMed2003

Parallel analysis of transcript and metabolic profiles: a new approach in systems biology.

The past few years in the medical and biological sciences have been characterized by the advent of systems biology. However, despite the well-known connectivity between the molecules described by transcriptomic, proteomic and metabolomic approaches, few studies have tried to correlate parameters across the various levels of systemic description. When comparing the discriminatory power of metabolic and RNA profiling to distinguish between different potato tuber systems, using the techniques described here suggests that metabolic profiling has a higher resolution than expression profiling. When applying pairwise transcript-metabolite correlation analyses, 571 of the 26,616 possible pairs showed significant correlation, most of which was novel and included several strong correlations to nutritionally important metabolites. We believe this approach to be of high potential value in the identification of candidate genes for modifying the metabolite content of biological systems.

Computational Biology↗
PubMed2003

Comprehensive chemical derivatization for gas chromatography-mass spectrometry-based multi-targeted profiling of the major phytohormones.

In the present investigation we report selection of the N-methyl-N-(tert.-butydimethylsilyl)trifluoroacetamide (MTBSTFA) reagent as the most comprehensive derivatization protocol among 17 tested reactions covering trifluoroacetylation, pentafluorobenzylation, methylations, and trimethylsilylations. MTBSTFA allowed easy and robust tert.-butyldimethylsilyl derivatization of 1-aminocyclopropane-1-carboxylic acid, indole-3-acetic acid, (+/-)-jasmonic acid, salicylic acid, (+/-)-abscisic acid, meta-topolin, and trans-zeatin. Detection limits as analysed by selected ion monitoring quadrupole GC-MS were 0.2, 0.01, 1.0, 0.02, 0.3, 0.3, and 0.9 pmol of injected substance, respectively. Analysis of gibberellic acid A3, trans-zeatin riboside and (+/-)-abscisic acid-beta-D-glucopyranosyl ester was best when coupled by splitting extracts and trimethysilylation. The MTBSTFA derivatization protocol was optimised, and validated. The preparation was insensitive to 2% residual water and to < or = 1 day storage at room temperature. The final scheme was highly reproducible and successfully applied to extracts from approximately 300 mg (fresh mass) of tobacco (Nicotiana tabacum) root and Arabidopsis thaliana seedling.

Gas Chromatography-Mass Spectrometry↗