Research

Research

Genes to proteins to metabolites - molecular phenotypes and synergetics

  • Together, metabolites, proteins, and transcripts form correlated, dynamic networks that mediate plant responses to environmental cues. The complexity of this system is enormous. Our work focuses on identifying and quantifying these network components and their interaction. 
  • Transcript profiling is widely used in this and other laboratories, but over the past few years, the importance of metabolite and protein profiling for a systems understanding became obvious. We’ve established GC/MS and LC/MS based metabolomics, and LC/MS based shotgun proteomics techniques. A further approach in our laboratory is mass spectrometry-based techniques to investigate plant signaling cascades and protein phosphorylation as playing a central role in controling network processes. To integrate these multilevel omics data, we use statistical and mathematical models tailor made for biological interpretation and systems-oriented biomarker discovery (for subtopics see references below).
  • A strong research field is data integration in combination with pattern recognition techniques. This unique approach combines high through put profiling strategies with biological interpretation and metabolic modelling of high dimensional data matrixes and complex metabolic networks (see Weckwerth 2008).

Green Systems Biology

  • for details see: Green systems biology - From single genomes, proteomes and metabolomes to ecosystems research and biotechnology. Weckwerth W. J Proteomics. 2011 Jul 23. ... Abstract Pubmed

Plants have shaped our human life form from the outset. With the emerging recognition of world population feeding, global climate change and limited energy resources with fossil fuels, the relevance of plant biology and biotechnology is becoming dramatically important. One key issue is to improve plant productivity and abiotic/biotic stress resistance in agriculture due to restricted land area and increasing environmental pressures. Another aspect is the development of CO(2)-neutral plant resources for fiber/biomass and biofuels: a transition from first generation plants like sugar cane, maize and other important nutritional crops to second and third generation energy crops such as Miscanthus and trees for lignocellulose and algae for biomass and feed, hydrogen and lipid production. At the same time we have to conserve and protect natural diversity and species richness as a foundation of our life on earth. Here, biodiversity banks are discussed as a foundation of current and future plant breeding research. Consequently, it can be anticipated that plant biology and ecology will have more indispensable future roles in all socio-economic aspects of our life than ever before. We therefore need an in-depth understanding of the physiology of single plant species for practical applications as well as the translation of this knowledge into complex natural as well as anthropogenic ecosystems. Latest developments in biological and bioanalytical research will lead into a paradigm shift towards trying to understand organisms at a systems level and in their ecosystemic context: (i) shotgun and next-generation genome sequencing, gene reconstruction and annotation, (ii) genome-scale molecular analysis using OMICS technologies and (iii) computer-assisted analysis, modeling and interpretation of biological data. Systems biology combines these molecular data, genetic evolution, environmental cues and species interaction with the understanding, modeling and prediction of active biochemical networks up to whole species populations. This process relies on the development of new technologies for the analysis of molecular data, especially genomics, metabolomics and proteomics data. The ambitious aim of these non-targeted 'omic' technologies is to extend our understanding beyond the analysis of separated parts of the system, in contrast to traditional reductionistic hypothesis-driven approaches. The consequent integration of genotyping, pheno/morphotyping and the analysis of the molecular phenotype using metabolomics, proteomics and transcriptomics will reveal a novel understanding of plant metabolism and its interaction with the environment. The analysis of single model systems - plants, animals and bacteria - will finally emerge in the analysis of populations of plants and other organisms and their adaptation to the ecological niche. In parallel, this novel understanding of ecophysiology will translate into knowledge-based approaches in crop plant biotechnology and marker- or genome-assisted breeding approaches. In this review the foundations of green systems biology are described and applications in ecosystems research are presented. Knowledge exchange of ecosystems research and green biotechnology merging into green systems biology is anticipated based on the principles of natural variation, biodiversity and the genotype-phenotype environment relationship as the fundamental drivers of ecology and evolution.

Unpredictability of Metabolism – a genotype-phenotype equation

  • for details see: Unpredictability of metabolism-the key role of metabolomics science in combination with next-generation genome sequencing. Weckwerth W. Anal Bioanal Chem. 2011 Jun;400(7):1967-78. ... Abstract Pubmed

Next generation sequencing (NGS) provides technologies to sequence whole prokaryotic and eukaryotic genomes in days, to perform genome-wide association (GWA) studies, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and RNA sequencing (RNA-seq) for transcriptome studies. An exponential growing volume of sequence data can be anticipated, yet, functional interpretation does not keep pace with the amount of data produced. In principle, these data contain all the secrets of living systems, the genotype-phenotype-relationship. Firstly, it is possible to derive the structure and connectivity of the metabolic network from the genotype of an organism in form of the stoichiometric matrix N. This is, however, static information. Strategies for modelling and prediction of dynamic metabolic networks based on genome sequences need to be applied. Despite very few examples it becomes obvious how difficult the functional interpretation of newly sequenced genomes and the prediction of the corresponding dynamic metabolic networks are. Consequently, metabolomics science – the quantitative measurement of metabolism in conjunction with metabolic modelling - is a key discipline for the functional interpretation of whole genomes and especially for testing the numerical predictions of metabolism based on genome-scale metabolic network models. In this context, a systematic equation is derived based on metabolomics covariance data and the genome-scale stoichiometric matrix which describes the genotype-phenotype relationship.

Strategy for functional interpretation of genotype data and environmental phenotypes based on molecular data.

  • for details see: Targeted proteomics for Chlamydomonas reinhardtii combined with rapid subcellular protein fractionation, metabolomics and metabolic flux analyses. Wienkoop S, Weiss J, May P, Kempa S, Irgang S, Recuenco-Munoz L, Pietzke M, Schwemmer T, Rupprecht J, Egelhofer V, Weckwerth W. Mol Biosyst. 2010 Jun 18;6(6):1018-31.
    ... Abstract

Profiling Platform MoSys to combine proteomics-assisted genome annotation (May et al., 2008), targeted proteomics (Mass Western (Wienkoop and Weckwerth, 2006; Lehmann et al., 2008; Wienkoop et al., 2008a)), subcellular fractionation, untargeted proteomics (MAPA: mass accuracy precursor alignment (Hoehenwarter et al., 2008)) for analysis of dynamic proteomes as well as to integrate the data with metabolomics and metabolic flux data (Weckwerth, 2008). The following algorithms were used to assemble the complete data set presented in this study: PROTMAX for the MAPA approach (Hoehenwarter et al., 2008), METMAX for the metabolomics and mass isotopomer analysis (Kempa et al., 2009) and PROMEX (http://www.promexdb.org) for proteomics data assembly, storage and spectral comparison (Hummel et al., 2007).

Workflow Metabolomics

for details see: Unpredictability of metabolism-the key role of metabolomics science in combination with next-generation genome sequencing.
Weckwerth W. Anal Bioanal Chem. 2011 Jun;400(7):1967-78.

... Abstract Pubmed

Workflow Proteomics

for details see: Green systems biology - From single genomes, proteomes and metabolomes to ecosystems research and biotechnology. Weckwerth W. J Proteomics. 2011 Jul 23.

... Abstract Pubmed

 

Subtopics

Metabolomics in Ecology

  • Metabolomics unravel contrasting effects of biodiversity on the performance of individual plant species.
    Scherling C, Roscher C, Giavalisco P, Schulze ED, Weckwerth W. PLoS One. 2010 Sep 7;5(9):e12569. ... Abstract

Metabolomics in Systems Biology

  • Metabolomics in systems biology.
    Weckwerth, W. Annu Rev Plant Biol 2003, 54, 669-689. ... Abstract

Metabolomics technology

  • Differential metabolic networks unravel the effects of silent plant phenotypes.
    Weckwerth W, Ehlers-Loureiro M, Wenzel K, and Fiehn O PNAS 2004, 101, 7809–7814. ... full article
  • An automated GCxGC-TOF-MS protocol for batch-wise extraction and alignment of mass isotopomer matrixes from differential (13)C-labelling experiments: a case study for photoautotrophic-mixotrophic grown Chlamydomonas reinhardtii cells.
    Kempa, S., Hummel, J., Schwemmer, T., Pietzke, M., et al. J Basic Microbiol 2009. ... Abstract

Proteomics technology - MAPA: Mass Accuracy Precursor Alignment

  • A rapid approach for phenotype-screening and database independent detection of cSNP/protein polymorphism using mass accuracy precursor alignment. Proteomics 2008, 8, 4214-25.
    Hoehenwarter W, van Dongen JT, Wienkoop S, Steinfath M, Hummel J, Erban A, Sulpice R, Regierer B, Kopka J, Geigenberger P, Weckwerth W. Proteomics 2008, 8, 4214-25 ... Abstract
    ..... goto ProtMax

Data integration combined with multivariate data mining

  • Process for the integrated extraction identification, and quantification of metabolites, proteins and RNA to reveal their co-regulation in biochemical networks. Weckwerth, W., Wenzel, K., Fiehn, O.Proteomics 2004, 4, 78-83. ... Abstract
  • Correlative GC-TOF-MS based metabolite profiling and LC-MS based protein profiling reveal time-related systemic regulation of metabolite-protein networks and improve pattern recognition for multiple biomarker selection. Morgenthal, K., Wienkoop, S., Scholz, M., Selbig, J., Weckwerth, W. Metabolomics 2005, 1, 109-121.
    ... Abstract
  • Integration of metabolomic and proteomic phenotypes: analysis of data covariance dissects starch and RFO metabolism from low and high temperature compensation response in Arabidopsis thaliana.
    Wienkoop, S., Morgenthal, K., Wolschin, F., Scholz, M., et al. Mol Cell Proteomics 2008a, 7, 1725-1736. ... Abstract
  • Integration of metabolomics and proteomics in molecular plant physiology - coping with the complexity by data-dimensionality reduction. Weckwerth, W. Physiol Plantarum 2008, 132, 176-189. ... Abstract
  • Targeted proteomics for Chlamydomonas reinhardtii combined with rapid subcellular protein fractionation, metabolomics and metabolic flux analyses. Wienkoop S, Weiss J, May P, Kempa S, Irgang S, Recuenco-Munoz L, Pietzke M, Schwemmer T, Rupprecht J, Egelhofer V, Weckwerth W. Mol Biosyst. 2010 Jun 18;6(6):1018-31. ... Abstract

Phosphoproteomics

  • Enrichment of phosphorylated proteins and peptides from complex mixtures using metal oxide/hydroxide affinity chromatography (MOAC). Wolschin, F., Wienkoop, S., Weckwerth, W.
    Proteomics 2005, 5, 4389-4397. ... Abstract
  • ProMEX: a mass spectral reference database for proteins and protein phosphorylation sites. Hummel J, Niemann M, Wienkoop S, Schulze WX, Steinhauser D, Selbig J, Walther D and Weckwerth W. BMC Bioinformatics, 2007, 1-8
    ... Abstract
  • Comparative analysis of phytohormone - responsive phosphoproteins in Arabidopsis thaliana using TiO2-phosphopeptide enrichment and MAPA. Chen Y., Hoehenwarter W. and Weckwerth W. (2010) Plant J. 2010; 63:1-17. ... Abstract
  • .... goto ProMEX

Mass Western

  • If the antibody fails – a mass Western approach. Lehmann, U., Wienkoop, S., Tschoep, H., Weckwerth, W.
    Plant Journal, 55, 1039–1046. ... Abstract
  • Targeted proteomics for Chlamydomonas reinhardtii combined with rapid subcellular protein fractionation, metabolomics and metabolic flux analyses. Wienkoop S, Weiss J, May P, Kempa S, Irgang S, Recuenco-Munoz L, Pietzke M, Schwemmer T, Rupprecht J, Egelhofer V, Weckwerth W. Mol Biosyst. 2010 Jun 18;6(6):1018-31.
    ... Abstract

Metabolomics and Proteomics Assisted Genome Annotation

  • Metabolomics- and proteomics-assisted genome annotation and analysis of the draft metabolic network of Chlamydomonas reinhardtii. May, P., Wienkoop, S., Kempa, S., Usadel, B., et al. Genetics 2008, 179, 157-166.
    ... Abstract