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

Directed -in vitro- evolution of Precambrian and extant Rubiscos

Rubisco is an ancient, catalytically conserved yet slow enzyme, which plays a central role in the biosphere’s carbon cycle. The design of Rubiscos to increase agricultural productivity has hitherto relied on the use of in vivo selection systems, precluding the exploration of biochemical traits that are not wired to cell survival. We present a directed -in vitro- evolution platform that extracts the enzyme from its biological context to provide a new avenue for Rubisco engineering. Precambrian and extant form II Rubiscos were subjected to an ensemble of directed evolution strategies aimed at improving thermostability. The most recent ancestor of proteobacteria -dating back 2.4 billion years- was uniquely tolerant to mutagenic loading. Adaptive evolution, focused evolution and genetic drift revealed a panel of thermostable mutants, some deviating from the characteristic trade-offs in CO2-fixing speed and specificity. Our findings provide a novel approach for identifying Rubisco variants with improved catalytic evolution potential.This work was supported by the REPSOL Research contracts Rubolution (RC020401120018), Rubolution 2.0 (RC 020401140042), the CSIC project PIE-201780E043 and the Australian Research Council grant CE140100015

Metabolic Adaptation in Transplastomic Plants Massively Accumulating Recombinant Proteins

BACKGROUND: Recombinant chloroplasts are endowed with an astonishing capacity to accumulate foreign proteins. However, knowledge about the impact on resident proteins of such high levels of recombinant protein accumulation is lacking. METHODOLOGY/PRINCIPAL FINDINGS: Here we used proteomics to characterize tobacco (Nicotiana tabacum) plastid transformants massively accumulating a p-hydroxyphenyl pyruvate dioxygenase (HPPD) or a green fluorescent protein (GFP). While under the conditions used no obvious modifications in plant phenotype could be observed, these proteins accumulated to even higher levels than ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco), the most abundant protein on the planet. This accumulation occurred at the expense of a limited number of leaf proteins including Rubisco. In particular, enzymes involved in CO(2) metabolism such as nuclear-encoded plastidial Calvin cycle enzymes and mitochondrial glycine decarboxylase were found to adjust their accumulation level to these novel physiological conditions. CONCLUSIONS/SIGNIFICANCE: The results document how protein synthetic capacity is limited in plant cells. They may provide new avenues to evaluate possible bottlenecks in recombinant protein technology and to maintain plant fitness in future studies aiming at producing recombinant proteins of interest through chloroplast transformation

Positively selected amino acid replacements within the RuBisCO enzyme of oak trees are associated with ecological adaptations

Phylogenetic analysis by maximum likelihood (PAML) has become the standard approach to study positive selection at the molecular level, but other methods may provide complementary ways to identify amino acid replacements associated with particular conditions. Here, we compare results of the decision tree (DT) model method with ones of PAML using the key photosynthetic enzyme RuBisCO as a model system to study molecular adaptation to particular ecological conditions in oaks (Quercus). We sequenced the chloroplast rbcL gene encoding RuBisCO large subunit in 158 Quercus species, covering about a third of the global genus diversity. It has been hypothesized that RuBisCO has evolved differentially depending on the environmental conditions and leaf traits governing internal gas diffusion patterns. Here, we show, using PAML, that amino acid replacements at the residue positions 95, 145, 251, 262 and 328 of the RuBisCO large subunit have been the subject of positive selection along particular Quercus lineages associated with the leaf traits and climate characteristics. In parallel, the DT model identified amino acid replacements at sites 95, 219, 262 and 328 being associated with the leaf traits and climate characteristics, exhibiting partial overlap with the results obtained using PAML