iEC7871 Quercus suber model: the first multi-tissue diel cycle genome-scale metabolic model of a woody tree

In the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behaviour at the tissue and multi-tissue level in different environmental conditions. Quercus suber (Q. suber), also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871), the first of a woody plant. The metabolic model comprises 7871 genes, 6230 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen. Each tissue’s biomass composition was determined to improve model accuracy and merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyze the pathways associated with the synthesis of suberin monomers. Nevertheless, the models developed in this work can provide insights about other aspects of the metabolism of Q. suber, such as its secondary metabolism and cork formation.

Comparative analysis of metabolic and transcriptomic features of Nothobranchius furzeri

Some species have a longer lifespan than others, but usually lifespan is correlated with typical body weight. Here, we study the lifetime evolution of the metabolic behaviour of Nothobranchius furzeri , a killifish with an extremely short lifespan with respect to other fishes, even when taking into account rescaling by body weight. Comparison of the gene expression patterns of N. furzeri with those of zebrafish Danio rerio and mouse ( Mus musculus ) shows that a broad set of metabolic genes and pathways are affected in N. furzeri during ageing in a way that is consistent with a global deregulation of chromatin. Computational analysis of the glycolysis pathway for the three species highlights a rapid increase in the metabolic activity during the lifetime of N. furzeri with respect to the other species. Our results highlight that the unusually short lifespan of N. furzeri is associated with peculiar patterns in the metabolic activities and in chromatin dynamics.

Metabolomic discrimination of the edible mushrooms Kuehneromyces mutabilis and Hypholoma capnoides (Strophariaceae, Agaricales) by NMR spectroscopy

Two edible, cultivable mushroom species of the family Strophariaceae, Kuehneromyces mutabilis (sheathed woodtuft) and Hypholoma capnoides (conifer tuft), were studied using proton nuclear magnetic resonance metabolomic approach. The variation in the metabolites of the two species and their metabolic behaviour regarding caps and stipes and different collection sites were analysed by multivariate analysis methods. Altogether 169 cap and stipe samples of the mushrooms were investigated. The clearest difference between the species was in the sugar composition, which was more diverse in H. capnoides. When mushroom samples collected from different locations were compared, more variance was found in H. capnoides, whereas K. mutabilis appeared more homogeneous as a species. As far as the caps and stipes were concerned, in both species the amount of α-α-trehalose was clearly higher in the stipes, and the caps contained a larger proportion of the amino acids and organic acids.

Mapping high-growth phenotypes in the flux space of microbial metabolism

Experimental and empirical observations on cell metabolism cannot be understood as a whole without their integration into a consistent systematic framework. However, the characterization of metabolic flux phenotypes is typically reduced to the study of a single optimal state, such as maximum biomass yield that is by far the most common assumption. Here, we confront optimal growth solutions to the whole set of feasible flux phenotypes (FFPs), which provides a benchmark to assess the likelihood of optimal and high-growth states and their agreement with experimental results. In addition, FFP maps are able to uncover metabolic behaviours, such as aerobic fermentation accompanying exponential growth on sugars at nutrient excess conditions, that are unreachable using standard models based on optimality principles. The information content of the full FFP space provides us with a map to explore and evaluate metabolic behaviour and capabilities, and so it opens new avenues for biotechnological and biomedical applications.