The Cyanobacterial Hepatotoxin Microcystin Binds to Proteins and Increases the Fitness of Microcystis under Oxidative Stress Conditions

Microcystins are cyanobacterial toxins that represent a serious threat to drinking water and recreational lakes worldwide. Here, we show that microcystin fulfils an important function within cells of its natural producer Microcystis. The microcystin deficient mutant ΔmcyB showed significant changes in the accumulation of proteins, including several enzymes of the Calvin cycle, phycobiliproteins and two NADPH-dependent reductases. We have discovered that microcystin binds to a number of these proteins in vivo and that the binding is strongly enhanced under high light and oxidative stress conditions. The nature of this binding was studied using extracts of a microcystin-deficient mutant in vitro. The data obtained provided clear evidence for a covalent interaction of the toxin with cysteine residues of proteins. A detailed investigation of one of the binding partners, the large subunit of RubisCO showed a lower susceptibility to proteases in the presence of microcystin in the wild type. Finally, the mutant defective in microcystin production exhibited a clearly increased sensitivity under high light conditions and after hydrogen peroxide treatment. Taken together, our data suggest a protein-modulating role for microcystin within the producing cell, which represents a new addition to the catalogue of functions that have been discussed for microbial secondary metabolites

Systematic Analysis of Stability Patterns in Plant Primary Metabolism

Metabolic networks are characterized by complex interactions and regulatory mechanisms between many individual components. These interactions determine whether a steady state is stable to perturbations. Structural kinetic modeling (SKM) is a framework to analyze the stability of metabolic steady states that allows the study of the system Jacobian without requiring detailed knowledge about individual rate equations. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models) with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. Until now, SKM experiments applied univariate tests to detect the network components with the largest influence on stability. In this work, we present an extended SKM approach relying on supervised machine learning to detect patterns of enzyme-metabolite interactions that act together in an orchestrated manner to ensure stability. We demonstrate its application on a detailed SK-model of the Calvin-Benson cycle and connected pathways. The identified stability patterns are highly complex reflecting that changes in dynamic properties depend on concerted interactions between several network components. In total, we find more patterns that reliably ensure stability than patterns ensuring instability. This shows that the design of this system is strongly targeted towards maintaining stability. We also investigate the effect of allosteric regulators revealing that the tendency to stability is significantly increased by including experimentally determined regulatory mechanisms that have not yet been integrated into existing kinetic models

Stimulating photosynthetic processes increases productivity and water use efficiency in the field

Previous studies have demonstrated that independent stimulation of either electron transport or RuBP regeneration can increase the rate of photosynthetic carbon assimilation and plant biomass. In this paper, we present evidence that a multi-gene approach to simultaneously manipulate these two processes provides a further stimulation of photosynthesis. We report on the introduction of the cyanobacterial bifunctional enzyme fructose-1, 6- bisphosphatase/sedoheptulose-1,7-bisphosphatase or overexpression of the plant enzyme sedoheptulose-1,7-bisphosphatase, together with expression of the red algal protein cytochrome c6, and show that a further increase in biomass accumulation under both glasshouse and field conditions can be achieved. Furthermore, we provide evidence that stimulation of both electron transport and RuBP regeneration can lead to enhanced intrinsic water use efficiency under field conditions

New insights into the regulation of greening and carbon-nitrogen balance by sugar metabolism through a plastidic invertase

Since the photosynthetic apparatus of plants contains a massive amount of nitrogen, the regulation of its development by sugar signals is important to the maintenance of the carbon-nitrogen balance. Recently, we isolated a new Arabidopsis mutant, sicy (sugar-inducible cotyledon yellow)-192, whose cotyledons were prevented from greening by treatment with sucrose. On treatment with sucrose, the expression of photosynthesis- and nitrogen assimilation-related genes was respectively weaker and stronger in the mutant seedlings than the wild-type seedlings. In the mutants, the gene encoding plastidic alkaline/neutral (A/N) invertase (INV-E) was point-mutated at codon 294, with Tyr substituted for Cys (C294Y). These findings provide new insights into the regulation of greening and carbon-nitrogen balance by sugar metabolism through INV-E in plastids. In this addendum, we describe the phenotypes of sicy-192 on treatment with sucrose in more detail, and propose a possible relationship among sugar metabolism through INV-E, plastid-to-nucleus retrograde signaling, and ethylene, a plant hormone, in the regulation of plant development and metabolism