In practice, we have based our research platform on four concepts: genetic diversity, gauntlets, phenotyping, and biomodeling. Genetic diversity is created using forward and reverse genetics and by taking advantage of naturally occurring variation. Phenotyping is the characterisation of observable plant traits. Gauntlets are ordered sets of plant growth conditions that bring about quantitative changes in phenotype. Computational biomodeling builds computer simulations of the plant system.
By altering genetic parameters in the plant system and analysing the effects of these perturbations, we gain insight into biological processes. Often, variation is brought about using transgenic technology or mutagenesis. We routinely carry out genetic modifications of the genomes in the nucleus and the chloroplast of both model species and crops and we also make use of naturally occurring genetic variation (e.g. recombinant inbred lines, near isogenic lines, and introgression lines).
We measure the effects of system perturbation by phenotyping. The phenotype is the observable properties of a plant (including morphology, development, and behaviour). The genotype, on the other hand, is the inherited instructions the plant carries, which may or may not be expressed. The phenotype arises from the interaction of the genotype with its environment. Expression profiling is a functional genomics approach that allows us to get an overview of phenotype by checking out where and when transcripts, proteins, and metabolites are expressed. For high-throughput transcript profiling, Affymetrix gene chip arrays are used or custom microarrays are produced by arraying expressed sequence tags (ESTs) or oligonucleotides on high-density membranes. The Transcript Profiling group manages these arrays, which are now also used to study translational regulation in the cytosol, the plastid and the mitochondrion (via polysome profiling).
We have developed a gas chromatography/mass spectroscopy-based, high throughput metabolite profiling approach with which more than 1000 leaf extract compounds and 400 phloem exudate compounds can be detected. Two of our research groups are profiling proteins in specific tissues or cell types. A system enabling searches for post-translational protein modifications is also in place.
Transcript, metabolite, and protein profiling have enormous resolving power but lack spatial resolution. To remedy this, we generate tissue and cell type-specific samples for analysis. Subcellular metabolite distributions are resolved using non-aqueous fractionation.
Plants are analysed at the whole plant level by looking at yields, photosynthetic rates, and so on, in growth chambers and during field trials. We often analyse plants kinetically by coupling precursor feeding to mass spectral analysis.We use confocal microscopy to analyse morphology, and employ various forms of electrophysiological analysis.
We have developed suites of high-throughput sensitive cycling tests for metabolites to process large numbers of samples from plants that have been passed through gauntlets (see below). We have established assays for sugars, amino acids, pyrophosphate, glycolysis intermediates, and several other compounds.
Many of these assays are based in a novel enzyme cycling system. They are adapted for multiwell plates and a pipetting robot and help us prioritise samples for expression profiling. Moreover, we are developing accurate high throughput enzyme assays that can be adapted to detect post-translational regulation.
Many interesting phenotypes are missed because they are environmentally conditional or subtle. To help us perceive such phenotypes, we have developed gauntlets – sets of well-defined growth conditions (either mimicking naturally occurring environmental stresses or forcing plants to cope with informative, non-natural situations) that result in quantitative phenotypic changes. Gauntlets set up so far include nitrogen supply, low sugar, micronutrients, low temperatures, different atmospheric conditions, and light cycles.
Data mining and biomodeling
The large volumes of data acquired through our functional genomic approaches is systematically analysed and mined. Two of our research groups focus exclusively on these research aspects (see the Bioinformatics and Computational Biology group profiles). The Bioinformatics group focuses expressly on developing informational systems that foster an infrastructure for the analytical methods established in our institute. Institute-wide, our research efforts promote advances in our biomodeling capabilities.
Although primarily developed for basic research, some of our techniques and tools for genetic engineering also offer great potential in plant biotechnology. Furthermore, we are interested in exploring the practical applicability of the knowledge we gain about plant metabolism and gene functions. We use nuclear and chloroplast transformation technologies to pursue proof-of-concept applications in metabolic engineering, molecular farming and engineering of disease resistances and stress tolerance.