BackgroundGiven its high surplus and low cost, glycerol has emerged as interesting carbon substrate for the synthesis of value-added chemicals. The soil bacterium Pseudomonas putida KT2440 can use glycerol to synthesize medium-chain-length poly(3-hydroxyalkanoates) (mcl-PHA), a class of biopolymers of industrial interest. Here, glycerol metabolism in P. putida KT2440 was studied on the level of gene expression (transcriptome) and metabolic fluxes (fluxome), using precisely adjusted chemostat cultures, growth kinetics and stoichiometry, to gain a systematic understanding of the underlying metabolic and regulatory network.ResultsGlycerol-grown P. putida KT2440 has a maintenance energy requirement [0.039 (mmolglycerol (gCDW h)−1)] that is about sixteen times lower than that of other bacteria, such as Escherichia coli, which provides a great advantage to use this substrate commercially. The shift from carbon (glycerol) to nitrogen (ammonium) limitation drives the modulation of specific genes involved in glycerol metabolism, transport electron chain, sensors to assess the energy level of the cell, and PHA synthesis, as well as changes in flux distribution to increase the precursor availability for PHA synthesis (Entner–Doudoroff pathway and pyruvate metabolism) and to reduce respiration (glyoxylate shunt). Under PHA-producing conditions (N-limitation), a higher PHA yield was achieved at low dilution rate (29.7 wt% of CDW) as compared to a high rate (12.8 wt% of CDW). By-product formation (succinate, malate) was specifically modulated under these regimes. On top of experimental data, elementary flux mode analysis revealed the metabolic potential of P. putida KT2440 to synthesize PHA and identified metabolic engineering targets towards improved production performance on glycerol.ConclusionThis study revealed the complex interplay of gene expression levels and metabolic fluxes under PHA- and non-PHA producing conditions using the attractive raw material glycerol as carbon substrate. This knowledge will form the basis for the development of future metabolically engineered hyper-PHA-producing strains derived from the versatile bacterium P. putida KT2440.

Here, we demonstrate whole-plant metabolic profiling by stable isotope labeling and combustion isotope-ratio mass spectrometry for precise quantification of assimilation, translocation, and molecular reallocation of 13 CO 2 and 15 NH 4 NO 3 . The technology was applied to rice (Oryza sativa) plants at different growth stages. For adult plants, 13 CO 2 labeling revealed enhanced carbon assimilation of the flag leaf from flowering to late grain-filling stage, linked to efficient translocation into the panicle. Simultaneous 13 CO 2 and 15 NH 4 NO 3 labeling with hydroponically grown seedlings was used to quantify the relative distribution of carbon and nitrogen. Two hours after labeling, assimilated carbon was mainly retained in the shoot (69%), whereas 7% entered the root and 24% was respired. Nitrogen, taken up via the root, was largely translocated into the shoot (85%). Salt-stressed seedlings showed decreased uptake and translocation of nitrogen (69%), whereas carbon metabolism was unaffected. Coupled to a gas chromatograph, labeling analysis provided enrichment of proteinogenic amino acids. This revealed significant protein synthesis in the panicle of adult plants, whereas protein biosynthesis in adult leaves was 8-fold lower than that in seedling shoots. Generally, amino acid enrichment was similar among biosynthetic families and allowed us to infer labeling dynamics of their precursors. On this basis, early and strong 13 C enrichment of Embden-Meyerhof-Parnas pathway and pentose phosphate pathway intermediates indicated high activity of these routes. Applied to mode-of-action analysis of herbicides, the approach showed severe disturbance in the synthesis of branched-chain amino acids upon treatment with imazapyr. The established technology displays a breakthrough for quantitative high-throughput plant metabolic phenotyping.

Aim Projections of biodiversity scenarios often rely solely on climate change to inform species distribution shifts in the future. Land use projections are rarely used due to their unavailability and, when available, are often at coarse spatial and thematic resolutions, making them unsuitable to capture fine scale habitat suitability. This study aims to (a) show how coupled land use change (LUC) models of high thematic resolution (HTR) can be used in species distribution models (SDM), (b) compare the impacts of HTR and low thematic resolution (LTR) explanatory predictors on biodiversity scenarios and (c) assess the impact of species' present area of occupancy on the effect of thematic resolution in SDMs. Location Belgium Taxon Bumblebees (Bombus) Methods We compared species distribution models with 17 land use predictors (HTR) against models with 5 land use predictors (LTR). We modelled the distribution of 17 bumblebee species in Belgium projected until 2035. We examined how model performance, variable importance and projections of distribution change differed depending on the thematic resolution of the land use predictors. Results Overall, HTR models performed better than LTR models. LTR models predicted greater extent per species. HTR projected a greater percentage of range gains, and both models projected similar losses of suitable habitat. However, the percentage loss and connectivity of suitable habitats varied differently for HTR and LTR models along a gradient of rare to common species. The HTR models projected greater loss of suitable areas for rare species and less loss for common species compared to LTR models. Main conclusions These results illustrate the importance of using ecologically relevant explanatory variables in SDMs, particularly for rare and localized species with specific habitat requirements. The results also indicate the need for large‐scale LUC projections to improve future biodiversity scenarios under climate change and to improve the ability of conservationists and policymakers to use SDM projections.

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