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Subject and Goal

The key objective of the initiative is the comprehensive systems analysis of photosynthesis and its regulation in response to selected environmental factors in a model algal system, Chlamydomonas reinhardtii, and the integration of the obtained insight with research on higher model plant and crop plant species.

Photosynthesis is a central determinant of crop growth and productivity, as well as being a crucial parameter in determining the distribution of species and, at an ecosystem level, being the major route by which the biosphere affects the composition of the atmosphere, with all of the implications for global change. The rate of photosynthesis will be a crucial contributor towards bio-fuels production, while maintaining capacity for food production. Further, photosynthesis is a process that is unique to unicellular algae and multi-cellular plants and therefore cannot be studied in non-photosynthetic model organisms.

GoFORSYS proposes a Systems Biology approach to underpin the analysis and improvement of crop plant photosynthesis. Central to the subject is the comprehensive systems analysis of the expression and regulation of photosynthesis in response to selected environmental factors in a model algal system, i.e. Chlamydomonas reinhardtii, and the integration of the insights with research on a model higher plant and a model crop plant.

There are two main reasons for performing the initial systems analysis in a unicellular organism, rather than a crop plant: first, its accessibility to a systems approach, in contrast to the currently too complex higher plant system where processes are strongly influenced by developmental factors and many different cell types need to be dealt with; second, the high conservation of the central processes of photosynthesis between algae and higher plants.

A two-step approach will be pursued in order to maximise information relevant to higher plants: In a first step, the environmental factors investigated in the Chlamydomonas system will be chosen based on their importance for constraining photosynthesis and productivity in crop plants, and their amenability to analysis in a model algal system. These include, for example, interactions between light intensity, light quality and temperature, and between light intensity, light quality and nitrogen availability. In a second step, the applicability of findings in Chlamydomonas will be tested by analyzing the response to analogous environmental challenges, and the underlying molecular mechanisms, in model plants and crops. Central to this testing phase will be the use of natural accessions (ecotypes) in Arabidopsis thaliana and tomato. These will be selected based on their different capacities to adjust to a wide variety of environmental conditions, most importantly light intensity, light quality, temperature and nitrogen availability, resulting in strong differences in photosynthetic rates and growth. Natural accessions provide an ‘unbiased’ population of genotypes that have adjusted over large evolutionary timescales and via changes in multiple genes to prevailing conditions. They provide an ideal representation of the optimisation of the system ´photosynthesis´ to different environmental conditions in higher plants. This is a better genotypic resource to test conclusions from the systems analysis of Chlamydomonas photosynthesis than single gene-driven and ‘biased’ transgenic approaches or mutant approaches.

Within GoFORSYS, using the established expertise in Potsdam-Golm, we will focus on a single, but central biological problem, as to how plants adjust and optimise photosynthesis to a changing environment, with the ultimate goal of understanding how this translates into plant biomass accumulation and, hence, growth.
To answer this question, we will establish a highly interdisciplinary research platform that incorporates sixteen partners from academia with expertise in biology, biochemistry, chemistry, computational biology, theoretical physics, and mathematics and one partner from industry with a unique experience in metabolomics and data analysis in plant systems. Multi-parallel high-throughput experiments will be carried out providing data on gene expression, metabolite and protein concentrations, genetic variations as well as molecular fluxes. Methods for the integrated analysis of these complex profile data will be applied and developed. Existing modelling and simulation approaches will be expanded to include the reconstruction of dynamical cellular processes from experimental data.