From metagenomes to metabolism: Systematically assessing the metabolic flux feasibilities for "Candidatus Accumulibacter" species during anaerobic substrate uptake.

With the rapid growing availability of metagenome assembled genomes (MAGs) and associated metabolic models, the identification of metabolic potential in individual community members has become possible. However, the field still lacks an unbiassed systematic evaluation of the generated metagenomic information to uncover not only metabolic potential, but also feasibilities of these models under specific environmental conditions. In this study, we present a systematic analysis of the metabolic potential in species of "Candidatus Accumulibacter", a group of polyphosphate-accumulating organisms (PAOs). We constructed a metabolic model of the central carbon metabolism and compared the metabolic potential among available MAGs for "Ca. Accumulibacter" species. By combining Elementary Flux Modes Analysis (EFMA) with max-min driving force (MDF) optimization, we obtained all possible flux distributions of the metabolic network and calculated their individual thermodynamic feasibility. Our findings reveal significant variations in the metabolic potential among "Ca. Accumulibacter" MAGs, particularly in the presence of anaplerotic reactions. EFMA revealed 700 unique flux distributions in the complete metabolic model that enable the anaerobic uptake of acetate and its conversion into polyhydroxyalkanoates (PHAs), a well-known phenotype of "Ca. Accumulibacter". However, thermodynamic constraints narrowed down this solution space to 146 models that were stoichiometrically and thermodynamically feasible (MDF > 0 kJ/mol), of which only 8 were strongly feasible (MDF > 7 kJ/mol). Notably, several novel flux distributions for the metabolic model were identified, suggesting putative, yet unreported, functions within the PAO communities. Overall, this work provides valuable insights into the metabolic variability among "Ca. Accumulibacter" species and redefines the anaerobic metabolic potential in the context of phosphate removal. More generally, the integrated workflow presented in this paper can be applied to any metabolic model obtained from a MAG generated from microbial communities to objectively narrow the expected phenotypes from community members.

Design and thermodynamic analysis of a pathway enabling anaerobic production of poly-3-hydroxybutyrate in Escherichia coli.

Utilizing anaerobic metabolisms for the production of biotechnologically relevant products presents potential advantages, such as increased yields and reduced energy dissipation. However, lower energy dissipation may indicate that certain reactions are operating closer to their thermodynamic equilibrium. While stoichiometric analyses and genetic modifications are frequently employed in metabolic engineering, the use of thermodynamic tools to evaluate the feasibility of planned interventions is less documented. In this study, we propose a novel metabolic engineering strategy to achieve an efficient anaerobic production of poly-(R)-3-hydroxybutyrate (PHB) in the model organism Escherichia coli. Our approach involves re-routing of two-thirds of the glycolytic flux through non-oxidative glycolysis and coupling PHB synthesis with NADH re-oxidation. We complemented our stoichiometric analysis with various thermodynamic approaches to assess the feasibility and the bottlenecks in the proposed engineered pathway. According to our calculations, the main thermodynamic bottleneck are the reactions catalyzed by the acetoacetyl-CoA ß-ketothiolase (EC 2.3.1.9) and the acetoacetyl-CoA reductase (EC 1.1.1.36). Furthermore, we calculated thermodynamically consistent sets of kinetic parameters to determine the enzyme amounts required for sustaining the conversion fluxes. In the case of the engineered conversion route, the protein pool necessary to sustain the desired fluxes could account for 20% of the whole cell dry weight.

Machine learning-based immune phenotypes correlate with STK11/KEAP1 co-mutations and prognosis in resectable NSCLC: a sub-study of the TNM-I trial.

BACKGROUND: We aim to implement an immune cell score model in routine clinical practice for resected non-small-cell lung cancer (NSCLC) patients (NCT03299478). Molecular and genomic features associated with immune phenotypes in NSCLC have not been explored in detail. PATIENTS AND METHODS: We developed a machine learning (ML)-based model to classify tumors into one of three categories: inflamed, altered, and desert, based on the spatial distribution of CD8+ T cells in two prospective (n = 453; TNM-I trial) and retrospective (n = 481) stage I-IIIA NSCLC surgical cohorts. NanoString assays and targeted gene panel sequencing were used to evaluate the association of gene expression and mutations with immune phenotypes. RESULTS: Among the total of 934 patients, 24.4% of tumors were classified as inflamed, 51.3% as altered, and 24.3% as desert. There were significant associations between ML-derived immune phenotypes and adaptive immunity gene expression signatures. We identified a strong association of the nuclear factor-κB pathway and CD8+ T-cell exclusion through a positive enrichment in the desert phenotype. KEAP1 [odds ratio (OR) 0.27, Q = 0.02] and STK11 (OR 0.39, Q = 0.04) were significantly co-mutated in non-inflamed lung adenocarcinoma (LUAD) compared to the inflamed phenotype. In the retrospective cohort, the inflamed phenotype was an independent prognostic factor for prolonged disease-specific survival and time to recurrence (hazard ratio 0.61, P = 0.01 and 0.65, P = 0.02, respectively). CONCLUSIONS: ML-based immune phenotyping by spatial distribution of T cells in resected NSCLC is able to identify patients at greater risk of disease recurrence after surgical resection. LUADs with concurrent KEAP1 and STK11 mutations are enriched for altered and desert immune phenotypes.

Using Kinetic Modelling to Infer Adaptations in Saccharomyces cerevisiae Carbohydrate Storage Metabolism to Dynamic Substrate Conditions.

Microbial metabolism is strongly dependent on the environmental conditions. While these can be well controlled under laboratory conditions, large-scale bioreactors are characterized by inhomogeneities and consequently dynamic conditions for the organisms. How Saccharomyces cerevisiae response to frequent perturbations in industrial bioreactors is still not understood mechanistically. To study the adjustments to prolonged dynamic conditions, we used published repeated substrate perturbation regime experimental data, extended it with proteomic measurements and used both for modelling approaches. Multiple types of data were combined; including quantitative metabolome, 13C enrichment and flux quantification data. Kinetic metabolic modelling was applied to study the relevant intracellular metabolic response dynamics. An existing model of yeast central carbon metabolism was extended, and different subsets of enzymatic kinetic constants were estimated. A novel parameter estimation pipeline based on combinatorial enzyme selection supplemented by regularization was developed to identify and predict the minimum enzyme and parameter adjustments from steady-state to dynamic substrate conditions. This approach predicted proteomic changes in hexose transport and phosphorylation reactions, which were additionally confirmed by proteome measurements. Nevertheless, the modelling also hints at a yet unknown kinetic or regulation phenomenon. Some intracellular fluxes could not be reproduced by mechanistic rate laws, including hexose transport and intracellular trehalase activity during substrate perturbation cycles.

Predicting the impact of temperature on metabolic fluxes using resource allocation modelling: Application to polyphosphate accumulating organisms.

The understanding of microbial communities and the biological regulation of its members is crucial for implementation of novel technologies using microbial ecology. One poorly understood metabolic principle of microbial communities is resource allocation and biosynthesis. Resource allocation theory in polyphosphate accumulating organisms (PAOs) is limited as a result of their slow imposed growth rate (typical sludge retention times of at least 4 days) and limitations to quantify changes in biomass components over a 6 hours cycle (less than 10% of their growth). As a result, there is no direct evidence supporting that biosynthesis is an exclusive aerobic process in PAOs that alternate continuously between anaerobic and aerobic phases. Here, we apply resource allocation metabolic flux analysis to study the optimal phenotype of PAOs over a temperature range of 4 °C to 20 °C. The model applied in this research allowed to identify optimal metabolic strategies in a core metabolic model with limited constraints based on biological principles. The addition of a constraint limiting biomass synthesis to be an exclusive aerobic process changed the metabolic behaviour and improved the predictability of the model over the studied temperature range by closing the gap between prediction and experimental findings. The results validate the assumption of limited anaerobic biosynthesis in PAOs, specifically "Candidatus Accumulibacter" related species. Interestingly, the predicted growth yield was lower, suggesting that there are mechanistic barriers for anaerobic growth not yet understood nor reflected in the current models of PAOs. Moreover, we identified strategies of resource allocation applied by PAOs at different temperatures as a result of the decreased catalytic efficiencies of their biochemical reactions. Understanding resource allocation is paramount in the study of PAOs and their currently unknown complex metabolic regulation, and metabolic modelling based on biological first principles provides a useful tool to develop a mechanistic understanding.

Atmosphere-Snow Exchange Explains Surface Snow Isotope Variability.

The climate signal imprinted in the snow isotopic composition allows to infer past climate variability from ice core stable water isotope records. The concurrent evolution of vapor and surface snow isotopic composition between precipitation events indicates that post-depositional atmosphere-snow humidity exchange influences the snow and hence the ice core isotope signal. To date, however, this is not accounted for in paeleoclimate reconstructions from isotope records. Here we show that vapor-snow exchange explains 36% of the summertime day-to-day δ18O variability of the surface snow between precipitation events, and 53% of the δD variability. Through observations from the Greenland Ice Sheet and accompanying modeling we demonstrate that vapor-snow exchange introduces a warm bias on the summertime snow isotope value relevant for ice core records. In case of long-term variability in atmosphere-snow exchange the relevance for the ice core signal is also variable and thus paleoclimate reconstructions from isotope records should be revisited.

Non-Equilibrium Fractionation Factors for D/H and 18O/16O During Oceanic Evaporation in the North-West Atlantic Region.

Ocean isotopic evaporation models, such as the Craig-Gordon model, rely on the description of nonequilibrium fractionation factors that are, in general, poorly constrained. To date, only a few gradient-diffusion type measurements have been performed in ocean settings to test the validity of the commonly used parametrization of nonequilibrium isotopic fractionation during ocean evaporation. In this work, we present 6 months of water vapor isotopic observations collected from a meteorological tower located in the northwest Atlantic Ocean (Bermuda) with the objective of estimating nonequilibrium fractionation factors (k, ‰) for ocean evaporation and their wind speed dependency. The Keeling Plot method and Craig-Gordon model combination were sensitive enough to resolve nonequilibrium fractionation factors during evaporation resulting into mean values of k 18 = 5.2 ± 0.6‰ and k 2 = 4.3 ± 3.4‰. Furthermore, we evaluate the relationship between k and 10-m wind speed over the ocean. Such a relationship is expected from current evaporation theory and from laboratory experiments made in the 1970s, but observational evidence is lacking. We show that (a) in the observed wind speed range [0-10 m s-1], the sensitivity of k to wind speed is small, in the order of -0.2‰ m-1 s for k 18, and (b) there is no empirical evidence for the presence of a discontinuity between smooth and rough wind speed regime during isotopic fractionation, as proposed in earlier studies. The water vapor d-excess variability predicted under the closure assumption using the k values estimated in this study is in agreement with observations over the Atlantic Ocean.

Predicting Metabolic Adaptation Under Dynamic Substrate Conditions Using a Resource-Dependent Kinetic Model: A Case Study Using Saccharomyces cerevisiae.

Exposed to changes in their environment, microorganisms will adapt their phenotype, including metabolism, to ensure survival. To understand the adaptation principles, resource allocation-based approaches were successfully applied to predict an optimal proteome allocation under (quasi) steady-state conditions. Nevertheless, for a general, dynamic environment, enzyme kinetics will have to be taken into account which was not included in the linear resource allocation models. To this end, a resource-dependent kinetic model was developed and applied to the model organism Saccharomyces cerevisiae by combining published kinetic models and calibrating the model parameters to published proteomics and fluxomics datasets. Using this approach, we were able to predict specific proteomes at different dilution rates under chemostat conditions. Interestingly, the approach suggests that the occurrence of aerobic fermentation (Crabtree effect) in S. cerevisiae is not caused by space limitation in the total proteome but rather an effect of constraints on the mitochondria. When exposing the approach to repetitive, dynamic substrate conditions, the proteome space was allocated differently. Less space was predicted to be available for non-essential enzymes (reserve space). This could indicate that the perceived "overcapacity" present in experimentally measured proteomes may very likely serve a purpose in increasing the robustness of a cell to dynamic conditions, especially an increase of proteome space for the growth reaction as well as of the trehalose cycle that was shown to be essential in providing robustness upon stronger substrate perturbations. The model predictions of proteome adaptation to dynamic conditions were additionally evaluated against respective experimentally measured proteomes, which highlighted the model's ability to accurately predict major proteome adaptation trends. This proof of principle for the approach can be extended to production organisms and applied for both understanding metabolic adaptation and improving industrial process design.

Engineering an acetoacetyl-CoA reductase from Cupriavidus necator toward NADH preference under physiological conditions.

The coupling of PHB generation with NADH reoxidation is required to generate PHB as a fermentation product. A fundamental trait to accomplish this feature is to express a functional NADH-preferring acetoacetyl-CoA reductase, engaged in PHB accumulation. One way to obtain such a reductase is by engineering the cofactor preference of the acetoacetyl-CoA reductase encoded by the phaB1 gene from Cupriavidus necator (AARCn1). Aiming to have a deeper understanding of the structural determinants of the cofactor preference in AARCn1, and to obtain an NADH-preferring acetoacetyl-CoA reductase derived from this protein, some engineered enzymes were expressed, purified and kinetically characterized, together with the parental AARCn1. One of these engineered enzymes, Chimera 5, experimentally showed a selectivity ratio ((kcat/KM)NADH/(kcat/KM)NADPH) ≈ 18, which is 160 times higher than the selectivity ratio experimentally observed in the parental AARCn1. A thermodynamic-kinetic approach was employed to estimate the cofactor preference and flux capacity of Chimera 5 under physiological conditions. According to this approach, Chimera 5 could prefer NADH over NADPH between 25 and 150 times. Being a derivative of AARCn1, Chimera 5 should be readily functional in Escherichia coli and C. necator. Moreover, with the expected expression level, its activity should be enough to sustain PHB accumulation fluxes similar to the fluxes previously observed in these biotechnologically relevant cell factories.

Kinetic Modeling of Saccharomyces cerevisiae Central Carbon Metabolism: Achievements, Limitations, and Opportunities.

Central carbon metabolism comprises the metabolic pathways in the cell that process nutrients into energy, building blocks and byproducts. To unravel the regulation of this network upon glucose perturbation, several metabolic models have been developed for the microorganism Saccharomyces cerevisiae. These dynamic representations have focused on glycolysis and answered multiple research questions, but no commonly applicable model has been presented. This review systematically evaluates the literature to describe the current advances, limitations, and opportunities. Different kinetic models have unraveled key kinetic glycolytic mechanisms. Nevertheless, some uncertainties regarding model topology and parameter values still limit the application to specific cases. Progressive improvements in experimental measurement technologies as well as advances in computational tools create new opportunities to further extend the model scale. Notably, models need to be made more complex to consider the multiple layers of glycolytic regulation and external physiological variables regulating the bioprocess, opening new possibilities for extrapolation and validation. Finally, the onset of new data representative of individual cells will cause these models to evolve from depicting an average cell in an industrial fermenter, to characterizing the heterogeneity of the population, opening new and unseen possibilities for industrial fermentation improvement.

Yellow (Lens) Better: Bioelectrical and Biometrical Measures to Assess Arousing and Focusing Effects.

Colours can induce several psychological effects, conditioning perceptions, cognitive/emotional states and human performances. In this exploratory study we investigated the effect of a yellow light exposure, obtained filtering the ambient light with coloured glasses, on the human's psychological functioning. In particular we wanted to assess if people are more able to focus when exposed to a yellow light. We recorded EEG, SC, HR and gaze-related data from 16 subjects (50% split in experimental and control group) during the execution of a reactivity test (the Hazard Perception Test, HPT). Compared with the control group, the experimental group showed increases in concentration, focus, visual attention and arousal, as measured by increases of first fixation duration and Beta over-Alpha ratio (BAR) as well as by decreases of distraction, workload, and number of gaze revisits.

Simultaneous Quantification of the Concentration and Carbon Isotopologue Distribution of Polar Metabolites in a Single Analysis by Gas Chromatography and Mass Spectrometry.

13C-isotope tracing is a frequently employed approach to study metabolic pathway activity. When combined with the subsequent quantification of absolute metabolite concentrations, this enables detailed characterization of the metabolome in biological specimens and facilitates computational time-resolved flux quantification. Classically, a 13C-isotopically labeled sample is required to quantify 13C-isotope enrichments and a second unlabeled sample for the quantification of metabolite concentrations. The rationale for a second unlabeled sample is that the current methods for metabolite quantification rely mostly on isotope dilution mass spectrometry (IDMS) and thus isotopically labeled internal standards are added to the unlabeled sample. This excludes the absolute quantification of metabolite concentrations in 13C-isotopically labeled samples. To address this issue, we have developed and validated a new strategy using an unlabeled internal standard to simultaneously quantify metabolite concentrations and 13C-isotope enrichments in a single 13C-labeled sample based on gas chromatography-mass spectrometry (GC/MS). The method was optimized for amino acids and citric acid cycle intermediates and was shown to have high analytical precision and accuracy. Metabolite concentrations could be quantified in small tissue samples (≥20 mg). Also, we applied the method on 13C-isotopically labeled mammalian cells treated with and without a metabolic inhibitor. We proved that we can quantify absolute metabolite concentrations and 13C-isotope enrichments in a single 13C-isotopically labeled sample.

Resource allocation explains lactic acid production in mixed-culture anaerobic fermentations.

Lactate production in anaerobic carbohydrate fermentations with mixed cultures of microorganisms is generally observed only in very specific conditions: the reactor should be run discontinuously and peptides and B vitamins must be present in the culture medium as lactic acid bacteria (LAB) are typically auxotrophic for amino acids. State-of-the-art anaerobic fermentation models assume that microorganisms optimise the adenosine triphosphate (ATP) yield on substrate and therefore they do not predict the less ATP efficient lactate production, which limits their application for designing lactate production in mixed-culture fermentations. In this study, a metabolic model taking into account cellular resource allocation and limitation is proposed to predict and analyse under which conditions lactate production from glucose can be beneficial for microorganisms. The model uses a flux balances analysis approach incorporating additional constraints from the resource allocation theory and simulates glucose fermentation in a continuous reactor. This approach predicts lactate production is predicted at high dilution rates, provided that amino acids are in the culture medium. In minimal medium and lower dilution rates, mostly butyrate and no lactate is predicted. Auxotrophy for amino acids of LAB is identified to provide a competitive advantage in rich media because less resources need to be allocated for anabolic machinery and higher specific growth rates can be achieved. The Matlab™ codes required for performing the simulations presented in this study are available at https://doi.org/10.5281/zenodo.4031144.

An NADH preferring acetoacetyl-CoA reductase is engaged in poly-3-hydroxybutyrate accumulation in Escherichia coli.

Oxygen supply implies higher production cost and reduction of maximum theoretical yields. Thus, generation of fermentation products is more cost-effective. Aiming to find a key piece for the production of (poly)-3-hydroxybutyrate (PHB) as a fermentation product, here we characterize an acetoacetyl-CoA reductase, isolated from a Candidatus Accumulibacter phosphatis-enriched mixed culture, showing a (kcatNADH/KMNADH)/(kcatNADPH/KMNADPH)>500. Further kinetic analyses indicate that, at physiological concentrations, this enzyme clearly prefers NADH, presenting the strongest NADH preference so far observed among the acetoacetyl-CoA reductases. Structural and kinetic analyses indicate that residues between E37 and P41 have an important role for the observed NADH preference. Moreover, an operon was assembled combining the phaCA genes from Cupriavidus necator and the gene encoding for this NADH-preferring acetoacetyl-CoA reductase. Escherichia coli cells expressing that assembled operon showed continuous accumulation of PHB under oxygen limiting conditions and PHB titer increased when decreasing the specific oxygen consumption rate. Taken together, these results show that it is possible to generate PHB as a fermentation product in E. coli, opening opportunities for further protein/metabolic engineering strategies envisioning a more efficient anaerobic production of PHB.

NADH-driven poly-3-hydroxybutyrate accumulation in Escherichia coli: Data from enzymatic assays and oxygen-limited continuous cultures.

Biosynthesis of poly-3-hydroxybutyrate (PHB) as a fermentation product enables the coupling of growth and product generation. Moreover, the reduction of oxygen supply should reduce operative cost and increase product yield. Generation of PHB as a fermentation product depends on the in vivo activity of an NADH-preferring acetoacetyl-CoA reductase. Proof of this concept requires (i) quantification of the cofactor preference, in physiologically relevant conditions, of a putative NADH-preferring acetoacetyl-CoA reductase and (ii) verification of PHB accumulation using an NADH-preferring acetoacetyl-CoA reductase in a species naturally incapable of doing so, for example, Escherichia coli. This dataset contains kinetic data obtained by spectrophotometry and data from a continuous culture of an engineered E. coli strain accumulating PHB under oxygen-limiting conditions. In this dataset it is possible to find (1) enzyme stability assays; (2) initial rates and progress curves from reactions catalyzed by two acetoacetyl-CoA reductases; (3) estimations of the relative use of NADH and NADPH by two acetoacetyl-CoA reductases; (4) estimations of the flux capacity of the reaction catalyzed by an acetoacetyl-CoA reductase; (5) biomass composition of an engineered E. coli strain transformed with a plasmid; (6) calculation of reconciled specific rates of this engineered strain growing on sucrose as the sole carbon source under oxygen limitation and (7) metabolic fluxes distributions during the continuous growth of this engineered strain. Because a relatively small number of acetoacetyl-CoA reductases have been kinetically characterized, data and scripts here provided could be useful for further kinetic characterizations. Moreover, the procedure described to estimate biomass composition could be interesting to estimate plasmid and protein burden in other strains. Application of data reconciliation to fermentations should help to obtain specific rates consistent with the principle of mass and electron conservation. All the required data and scripts to perform these analyses are deposited in a Mendeley Data repository. This article was co-submitted with the manuscript entitled "An NADH preferring acetoacetyl-CoA reductase is engaged in poly-3-hydroxybutyrate accumulation in Escherichiasia. coli".

Metabolic engineering strategies for butanol production in Escherichia coli.

The global market of butanol is increasing due to its growing applications as solvent, flavoring agent, and chemical precursor of several other compounds. Recently, the superior properties of n-butanol as a biofuel over ethanol have stimulated even more interest. (Bio)butanol is natively produced together with ethanol and acetone by Clostridium species through acetone-butanol-ethanol fermentation, at noncompetitive, low titers compared to petrochemical production. Different butanol production pathways have been expressed in Escherichia coli, a more accessible host compared to Clostridium species, to improve butanol titers and rates. The bioproduction of butanol is here reviewed from a historical and theoretical perspective. All tested rational metabolic engineering strategies in E. coli to increase butanol titers are reviewed: manipulation of central carbon metabolism, elimination of competing pathways, cofactor balancing, development of new pathways, expression of homologous enzymes, consumption of different substrates, and molecular biology strategies. The progress in the field of metabolic modeling and pathway generation algorithms and their potential application to butanol production are also summarized here. The main goals are to gather all the strategies, evaluate the respective progress obtained, identify, and exploit the outstanding challenges.

Escherichia coli metabolism under short-term repetitive substrate dynamics: adaptation and trade-offs.

BACKGROUND: Microbial metabolism is highly dependent on the environmental conditions. Especially, the substrate concentration, as well as oxygen availability, determine the metabolic rates. In large-scale bioreactors, microorganisms encounter dynamic conditions in substrate and oxygen availability (mixing limitations), which influence their metabolism and subsequently their physiology. Earlier, single substrate pulse experiments were not able to explain the observed physiological changes generated under large-scale industrial fermentation conditions. RESULTS: In this study we applied a repetitive feast-famine regime in an aerobic Escherichia coli culture in a time-scale of seconds. The regime was applied for several generations, allowing cells to adapt to the (repetitive) dynamic environment. The observed response was highly reproducible over the cycles, indicating that cells were indeed fully adapted to the regime. We observed an increase of the specific substrate and oxygen consumption (average) rates during the feast-famine regime, compared to a steady-state (chemostat) reference environment. The increased rates at same (average) growth rate led to a reduced biomass yield (30% lower). Interestingly, this drop was not followed by increased by-product formation, pointing to the existence of energy-spilling reactions. During the feast-famine cycle, the cells rapidly increased their uptake rate. Within 10 s after the beginning of the feeding, the substrate uptake rate was higher (4.68 µmol/gCDW/s) than reported during batch growth (3.3 µmol/gCDW/s). The high uptake led to an accumulation of several intracellular metabolites, during the feast phase, accounting for up to 34% of the carbon supplied. Although the metabolite concentrations changed rapidly, the cellular energy charge remained unaffected, suggesting well-controlled balance between ATP producing and ATP consuming reactions. CONCLUSIONS: The adaptation of the physiology and metabolism of E. coli under substrate dynamics, representative for large-scale fermenters, revealed the existence of several cellular mechanisms coping with stress. Changes in the substrate uptake system, storage potential and energy-spilling processes resulted to be of great importance. These metabolic strategies consist a meaningful step to further tackle reduced microbial performance, observed under large-scale cultivations.

Grand Research Challenges for Sustainable Industrial Biotechnology.

Future manufacturing will focus on new, improved products as well as on new and enhanced production methods. Recent biotechnological and scientific advances, such as CRISPR/Cas and various omic technologies, pave the way to exciting novel biotechnological research, development, and commercialization of new sustainable products. Rigorous mathematical descriptions of microbial cells and consortia thereof will enable deeper biological understanding and lead to powerful in silico cellular models. Biological engineering, namely model-based design together with synthetic biology, will accelerate the construction of robust and high-performing microorganisms. Using these organisms, and ambitions towards zero-concepts with respect to emissions and excess resources in bioprocess engineering, industrial biotechnology is expected to become highly integrated into sustainable generations of technology systems.

Measurement and implications of Saturn's gravity field and ring mass.

The interior structure of Saturn, the depth of its winds, and the mass and age of its rings constrain its formation and evolution. In the final phase of the Cassini mission, the spacecraft dived between the planet and its innermost ring, at altitudes of 2600 to 3900 kilometers above the cloud tops. During six of these crossings, a radio link with Earth was monitored to determine the gravitational field of the planet and the mass of its rings. We find that Saturn's gravity deviates from theoretical expectations and requires differential rotation of the atmosphere extending to a depth of at least 9000 kilometers. The total mass of the rings is (1.54 ± 0.49) × 1019 kilograms (0.41 ± 0.13 times that of the moon Mimas), indicating that the rings may have formed 107 to 108 years ago.

Looking through blue glasses: bioelectrical measures to assess the awakening after a calm situation.

Colors can elicit cognitive and emotional states. In particular, blue colour is associated to "refresh" and "restart" effects and is suggested to enhance a wake-up after a calm situation. In this exploratory study, these claims are investigated using Electroencephalographic (EEG), Skin Conductance (SC) and pupil diameter data. The results confirmed the "wake-up effect" for subjects wearing the lenses, as measured by Global Field Power (GFP) in Theta Band, Skin Conductance Response (SCR) and pupil diameter data.