Biomedical subjects

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↗

PubMed2007

Nonsupervised construction and application of mass spectral and retention time index libraries from time-of-flight gas chromatography-mass spectrometry metabolite profiles.

Gas chromatography-mass spectrometry (GC-MS) is routinely applied to the metabolite profiling of biological samples. Time-of-flight (TOF)-GC-MS metabolite profiling is based on highly reproducible electron impact ionization. Single chromatograms may comprise 200-1000 mass spectral components. The nature and composition of these mass spectral components depend on the choice of metabolite extraction, type of biological sample, and experimental condition. The components represent mass spectral tags (MSTs) of volatile metabolites or metabolite derivatives. Identification of MSTs is the major challenge in GC-MS metabolite profiling. We describe methods suitable for the automated construction of mass spectral and retention time index databases from large sets of TOF-GC-MS profiles. Application of these libraries for automated identification by pure reference compounds and classification of hitherto unidentified MSTs from biological sources is demonstrated.

Carbohydrate Metabolism↗

PubMed2006

Metabolic labeling of plant cell cultures with K(15)NO3 as a tool for quantitative analysis of proteins and metabolites.

Strategies for robust quantitative comparison between different biological samples are of high importance in experiments that address biological questions beyond the establishment of protein lists. Here, we propose the use of 15N-KNO3 as the only nitrogen source in Arabidopsis cell cultures in order to achieve a metabolically fully labeled cell population. Proteins from such metabolically labeled culture are distinguishable from unlabeled protein populations by a characteristic mass shift that depends on the amino acid composition of the tryptic peptide analyzed. In addition, the metabolically labeled cell extracts are also suitable for comparative quantitative analysis of nitrogen-containing cellular metabolic complement. Protein extracts from unlabeled and from standardized 15N-labeled cells were combined into one sample for joined analytical processing. This has the advantage of (i) reduced experimental variability and (ii) immediate relative quantitation at the level of single extracted peptide and metabolite spectra. Together ease and accuracy of relative quantitation for profiling experiments is substantially improved. The metabolic labeling strategy has been validated by mixtures of protein extracts and metabolite extracts from the same cell cultures in known ratios of labeled to unlabeled extracts (1:1, 1:4, and 4:1). We conclude that saturating metabolic 15N-labeling provides a robust and affordable integrative strategy to answer questions in quantitative proteomics and nitrogen focused metabolomics.

Journal Article↗

PubMed2006

DOF transcription factor AtDof1.1 (OBP2) is part of a regulatory network controlling glucosinolate biosynthesis in Arabidopsis.

Glucosinolates are a group of secondary metabolites that function as defense substances against herbivores and micro-organisms in the plant order Capparales. Indole glucosinolates (IGS), derivatives of tryptophan, may also influence plant growth and development. In Arabidopsis thaliana, indole-3-acetaldoxime (IAOx) produced from tryptophan by the activity of two cytochrome P450 enzymes, CYP79B2 and CYP79B3, serves as a precursor for IGS biosynthesis but is also an intermediate in the biosynthetic pathway of indole-3-acetic acid (IAA). Another cytochrome P450 enzyme, CYP83B1, funnels IAOx into IGS. Although there is increasing information about the genes involved in this biochemical pathway, their regulation is not fully understood. OBP2 has recently been identified as a member of the DNA-binding-with-one-finger (DOF) transcription factors, but its function has not been studied in detail so far. Here we report that OBP2 is expressed in the vasculature of all Arabidopsis organs, including leaves, roots, flower stalks and petals. OBP2 expression is induced in response to a generalist herbivore, Spodoptera littoralis, and by treatment with the plant signalling molecule methyl jasmonate, both of which also trigger IGS accumulation. Constitutive and inducible over-expression of OBP2 activates expression of CYP83B1. In addition, auxin concentration is increased in leaves and seedlings of OBP2 over-expression lines relative to wild-type, and plant size is diminished due to a reduction in cell size. RNA interference-mediated OBP2 blockade leads to reduced expression of CYP83B1. Collectively, these data provide evidence that OBP2 is part of a regulatory network that regulates glucosinolate biosynthesis in Arabidopsis.

Acetates↗

PubMed2006

Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement.

Tomato represents an important source of fiber and nutrients in the human diet and is a central model for the study of fruit biology. To identify components of fruit metabolic composition, here we have phenotyped tomato introgression lines (ILs) containing chromosome segments of a wild species in the genetic background of a cultivated variety. Using this high-diversity population, we identify 889 quantitative fruit metabolic loci and 326 loci that modify yield-associated traits. The mapping analysis indicates that at least 50% of the metabolic loci are associated with quantitative trait loci (QTLs) that modify whole-plant yield-associated traits. We generate a cartographic network based on correlation analysis that reveals whole-plant phenotype associated and independent metabolic associations, including links with metabolites of nutritional and organoleptic importance. The results of our genomic survey illustrate the power of genome-wide metabolic profiling and detailed morphological analysis for uncovering traits with potential for crop breeding.

Computer Simulation↗

PubMed2006

Genetic and genomic analysis of legume flowers and seeds.

New tools, such as ordered mutant libraries, microarrays and sequence based comparative maps, are available for genetic and genomic studies of legumes that are being used to shed light on seed production, the objective of most arable farming. The new information and understanding brought by these tools are revealing the biological processes that underpin and impact on seed production.

Computational Biology↗

PubMed2006

Current challenges and developments in GC-MS based metabolite profiling technology.

Gas chromatography-mass spectrometry (GC-MS) based metabolite profiling of biological samples is one of the key technologies for metabolite profiling and substantially contributes to our understanding of the metabolome. While the technology is in increasing use it is challenged with novel demands. Increasing the number of metabolite identifications within existing profiling platforms is prerequisite for a substantially improved scope of profiling studies. Clear, reproducible strategies for metabolite identification and exchange of identifications between laboratories will facilitate further developments, such as the extension of profiling technologies towards metabolic signals and other technically demanding trace compound analysis. Using GC-MS technology as an example the concept of mass spectral tags (MSTs) is presented. A mass spectral tag is defined by the chemometric properties, molecular mass to charge ratio, chromatographic retention index and an induced mass fragmentation pattern such as an electron impact mass spectrum (EI-MS) or secondary fragmentation (MS(2)). These properties if properly documented will allow identification of hitherto non-identified MSTs by standard addition experiments of authenticated reference substances even years after first MST description. Strategies are discussed for MST identification and enhanced MST characterization utilizing experimental schemes such as in vivo stable isotope labelling of whole organisms and open access information distribution, for example the GMG internet platform initiated in 2004 (GMD, http://www.csbdb.mpimp-golm.mpg.de/gmd.html).

Carbohydrate Metabolism↗

PubMed2005

Inferring hypotheses on functional relationships of genes: Analysis of the Arabidopsis thaliana subtilase gene family.

The gene family of subtilisin-like serine proteases (subtilases) in Arabidopsis thaliana comprises 56 members, divided into six distinct subfamilies. Whereas the members of five subfamilies are similar to pyrolysins, two genes share stronger similarity to animal kexins. Mutant screens confirmed 144 T-DNA insertion lines with knockouts for 55 out of the 56 subtilases. Apart from SDD1, none of the confirmed homozygous mutants revealed any obvious visible phenotypic alteration during growth under standard conditions. Apart from this specific case, forward genetics gave us no hints about the function of the individual 54 non-characterized subtilase genes. Therefore, the main objective of our work was to overcome the shortcomings of the forward genetic approach and to infer alternative experimental approaches by using an integrative bioinformatics and biological approach. Computational analyses based on transcriptional co-expression and co-response pattern revealed at least two expression networks, suggesting that functional redundancy may exist among subtilases with limited similarity. Furthermore, two hubs were identified, which may be involved in signalling or may represent higher-order regulatory factors involved in responses to environmental cues. A particular enrichment of co-regulated genes with metabolic functions was observed for four subtilases possibly representing late responsive elements of environmental stress. The kexin homologs show stronger associations with genes of transcriptional regulation context. Based on the analyses presented here and in accordance with previously characterized subtilases, we propose three main functions of subtilases: involvement in (i) control of development, (ii) protein turnover, and (iii) action as downstream components of signalling cascades. Supplemental material is available in the Plant Subtilase Database (PSDB) (http://csbdb.mpimp-golm.mpg.de/psdb.html), as well as from the CSB.DB (http://csbdb.mpimp-golm.mpg.de).

Animals↗

PubMed2005

Organization and metabolism of plastids and mitochondria in arbuscular mycorrhizal roots of Medicago truncatula.

Colonization of root cortical cells by arbuscular mycorrhizal fungi leads to marked cytological changes of plastids and mitochondria. Plastids in particular are forming tubular extensions partially connecting individual organelles in a network-like way. These cytological changes correspond to an increased need for plastid and mitochondrial products during establishment and functioning of the symbiosis. The analysis of metabolite and transcript levels in mycorrhizal and nonmycorrhizal roots from Medicago truncatula revealed concomitant changes regarding a number of metabolic pathways. Our results indicate the activation of the mitochondrial tricarboxylic acid cycle and of plastid biosynthetic pathways producing fatty acids, amino acids, and apocarotenoids. These observations provide a general overview of structural and metabolic changes of plastids and mitochondria during colonization of root cortical cells by arbuscular mycorrhizal fungi.

Amino Acids↗

PubMed2005

Non-linear PCA: a missing data approach.

MOTIVATION: Visualizing and analysing the potential non-linear structure of a dataset is becoming an important task in molecular biology. This is even more challenging when the data have missing values. RESULTS: Here, we propose an inverse model that performs non-linear principal component analysis (NLPCA) from incomplete datasets. Missing values are ignored while optimizing the model, but can be estimated afterwards. Results are shown for both artificial and experimental datasets. In contrast to linear methods, non-linear methods were able to give better missing value estimations for non-linear structured data. APPLICATION: We applied this technique to a time course of metabolite data from a cold stress experiment on the model plant Arabidopsis thaliana, and could approximate the mapping function from any time point to the metabolite responses. Thus, the inverse NLPCA provides greatly improved information for better understanding the complex response to cold stress. CONTACT: scholz@mpimp-golm.mpg.de.

Adaptation, Physiological↗

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

Metabolite profiling reveals a role for atypical cinnamyl alcohol dehydrogenase CAD1 in the synthesis of coniferyl alcohol in tobacco xylem.

In angiosperms, lignin is built from two main monomers, coniferyl and sinapyl alcohol, which are incorporated respectively as G and S units in the polymer. The last step of their synthesis has so far been considered to be performed by a family of dimeric cinnamyl alcohol dehydrogenases (CAD2). However, previous studies on Eucalyptus gunnii xylem showed the presence of an additional, structurally unrelated, monomeric CAD form named CAD1. This form reduces coniferaldehyde to coniferyl alcohol, but is inactive on sinapaldehyde. In this paper, we report the functional characterization of CAD1 in tobacco (Nicotiana tabacum L.). Transgenic tobacco plants with reduced CAD1 expression were obtained through an RNAi strategy. These plants displayed normal growth and development, and detailed biochemical studies were needed to reveal a role for CAD1. Lignin analyses showed that CAD1 down-regulation does not affect Klason lignin content, and has a moderate impact on G unit content of the non-condensed lignin fraction. However, comparative metabolic profiling of the methanol-soluble phenolic fraction from basal xylem revealed significant differences between CAD1 down-regulated and wild-type plants. Eight compounds were less abundant in CAD1 down-regulated lines, five of which were identified as dimers or trimers of monolignols, each containing at least one moiety derived from coniferyl alcohol. In addition, 3-trans-caffeoyl quinic acid accumulated in the transgenic plants. Together, our results support a significant contribution of CAD1 to the synthesis of coniferyl alcohol in planta, along with the previously characterized CAD2 enzymes.

Alcohol Oxidoreductases↗

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↗