Nitrogen partitioning between branched-chain amino acids and urea cycle enzymes sustains renal cancer progression

Metabolic reprogramming is critical for tumor initiation and progression. However, the exact impact of specific metabolic changes on cancer progression is poorly understood. Here, we combined multi-omics datasets of primary and metastatic clonally-related clear cell renal cancer cells (ccRCC) and generated a computational tool to explore the metabolic landscape during cancer progression. We show that a VHL loss-dependent reprogramming of branched-chain amino acid catabolism is required to maintain the aspartate pool in cancer cells across all tumor stages. We also provide evidence that metastatic renal cancer cells reactivate argininosuccinate synthase (ASS1), a urea cycle enzyme suppressed in primary ccRCC, to enable invasion in vitro and metastasis in vivo. Overall, our study provides the first comprehensive elucidation of the molecular mechanisms responsible for metabolic flexibility in ccRCC, paving the way to the development of therapeutic strategies based on the specific metabolism that characterizes each tumor stage.

Modeling photosynthetic resource allocation connects physiology with evolutionary environments

The regulation of resource allocation in biological systems observed today is the cumulative result of natural selection in ancestral and recent environments. To what extent are observed resource allocation patterns in different photosynthetic types optimally adapted to current conditions, and to what extent do they reflect ancestral environments? Here, we explore these questions for C3, C4, and C3–C4 intermediate plants of the model genus Flaveria. We developed a detailed mathematical model of carbon fixation, which accounts for various environmental parameters and for energy and nitrogen partitioning across photosynthetic components. This allows us to assess environment-dependent plant physiology and performance as a function of resource allocation patterns. Models of C4 plants optimized for conditions experienced by evolutionary ancestors perform better than models accounting for experimental growth conditions, indicating low phenotypic plasticity. Supporting this interpretation, the model predicts that C4 species need to re-allocate more nitrogen between photosynthetic components than C3 species to adapt to new environments. We thus hypothesize that observed resource distribution patterns in C4 plants still reflect optimality in ancestral environments, allowing the quantitative inference of these environments from today’s plants. Our work allows us to quantify environmental effects on photosynthetic resource allocation and performance in the light of evolutionary history.

Efficiency in nitrogen management using conventional and transgenic technology in the cultivation of maize

The objective to evaluate the maize yield components as a function of the top-dressing nitrogen partitioning in maize plants with conventional and transgenic technology. The experiment was carried out in the agricultural crops of 2012/2013 and 2013/2014, in the municipality of Tenente Portela-RS, Brazil. The experiment was set up in a randomized block design in a factorial scheme with two genetic technologies x 11 nitrogen fertilization treatments, arranged in three replications. The treatments were composed of top-dressing applications in the phenological stages V2 - two fully expanded leaves, (V2), V4 - four fully expanded leaves, (V4), V6 - six fully expanded leaves (V6) and V8 - with eight fully expanded leaves (V8) and split applications in V2+V4; V2+V6; V2+V8; V4+V6; V4+V8; V6+V8; and V2+V4+V6+V8. There was interaction between genetic technologies and levels of nitrogen fertilization in the maize crop. The highest grain yield was obtained with conventional technology because it presented plants with greater prolificacy, ear diameter and number of grains per row. Grain yield was superior with nitrogen fertilization in V4 and in nitrogen splitting in the V4 + V6, V4 + V8 and V2 + V4 + V6 + V8 stages.

Intraspecific kin recognition contributes to interspecific allelopathy：A case study of allelopathic rice interference with paddy weeds

Species interactions and mechanisms affect plant coexistence and community assembly. Despite increasing knowledge of kin recognition and allelopathy in regulating interspecific and intraspecific interactions among plants, little is known about whether kin recognition mediates allelopathic interference. We used allelopathic rice cultivars with the ability for kin recognition grown in kin vs. non-kin mixtures to determine their impacts on paddy weeds in field trials and a series of controlled experiments. We experimentally tested potential mechanisms of the interaction via altered root behavior, allelochemical production, and soil microbial community composition, as well as carbon and nitrogen partitioning in the weeds. We consistently found that the establishment and growth of paddy weeds were more inhibited by kin mixtures compared to non-kin mixtures. The effect was driven by kin recognition that induced altered root placement, established similar soil microbial communities, and altered weed carbon and nitrogen partitioning. Importantly, genetic relatedness enhanced the production of intrusive roots towards weeds and reduced the production of rice allelochemicals. These findings suggest that relatedness allows allelopathic plants to discriminate their neighboring collaborators (kin) or competitors and then adjust their growth, competitiveness and chemical defense accordingly.

Changes in Leaf-Level Nitrogen Partitioning and Mesophyll Conductance Deliver Increased Photosynthesis for Lolium perenne Leaves Engineered to Accumulate Lipid Carbon Sinks

Diacylglycerol acyl-transferase (DGAT) and cysteine oleosin (CO) expression confers a novel carbon sink (of encapsulated lipid droplets) in leaves of Lolium perenne and has been shown to increase photosynthesis and biomass. However, the physiological mechanism by which DGAT + CO increases photosynthesis remains unresolved. To evaluate the relationship between sink strength and photosynthesis, we examined fatty acids (FA), water-soluble carbohydrates (WSC), gas exchange parameters and leaf nitrogen for multiple DGAT + CO lines varying in transgene accumulation. To identify the physiological traits which deliver increased photosynthesis, we assessed two important determinants of photosynthetic efficiency, CO2 conductance from atmosphere to chloroplast, and nitrogen partitioning between different photosynthetic and non-photosynthetic pools. We found that DGAT + CO accumulation increased FA at the expense of WSC in leaves of L. perenne and for those lines with a significant reduction in WSC, we also observed an increase in photosynthesis and photosynthetic nitrogen use efficiency. DGAT + CO L. perenne displayed no change in rubisco content or Vcmax but did exhibit a significant increase in specific leaf area (SLA), stomatal and mesophyll conductance, and leaf nitrogen allocated to photosynthetic electron transport. Collectively, we showed that increased carbon demand via DGAT+CO lipid sink accumulation can induce leaf-level changes in L. perenne which deliver increased rates of photosynthesis and growth. Carbon sinks engineered within photosynthetic cells provide a promising new strategy for increasing photosynthesis and crop productivity.