Dataset Information

MbT-Tool: An open-access tool based on Thermodynamic Electron Equivalents Model to obtain microbial-metabolic reactions to be used in biotechnological process.

ABSTRACT: Modelling cellular metabolism is a strategic factor in investigating microbial behaviour and interactions, especially for bio-technological processes. A key factor for modelling microbial activity is the calculation of nutrient amounts and products generated as a result of the microbial metabolism. Representing metabolic pathways through balanced reactions is a complex and time-consuming task for biologists, ecologists, modellers and engineers. A new computational tool to represent microbial pathways through microbial metabolic reactions (MMRs) using the approach of the Thermodynamic Electron Equivalents Model has been designed and implemented in the open-access framework NetLogo. This computational tool, called MbT-Tool (Metabolism based on Thermodynamics) can write MMRs for different microbial functional groups, such as aerobic heterotrophs, nitrifiers, denitrifiers, methanogens, sulphate reducers, sulphide oxidizers and fermenters. The MbT-Tool's code contains eighteen organic and twenty inorganic reduction-half-reactions, four N-sources (NH4 (+), NO3 (-), NO2 (-), N2) to biomass synthesis and twenty-four microbial empirical formulas, one of which can be determined by the user (CnHaObNc). MbT-Tool is an open-source program capable of writing MMRs based on thermodynamic concepts, which are applicable in a wide range of academic research interested in designing, optimizing and modelling microbial activity without any extensive chemical, microbiological and programing experience.

SUBMITTER: Araujo PG

PROVIDER: S-EPMC5013251 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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MbT-Tool: An open-access tool based on Thermodynamic Electron Equivalents Model to obtain microbial-metabolic reactions to be used in biotechnological process.

Araujo Pablo Granda PG Gras Anna A Ginovart Marta M

Computational and structural biotechnology journal 20160826

Modelling cellular metabolism is a strategic factor in investigating microbial behaviour and interactions, especially for bio-technological processes. A key factor for modelling microbial activity is the calculation of nutrient amounts and products generated as a result of the microbial metabolism. Representing metabolic pathways through balanced reactions is a complex and time-consuming task for biologists, ecologists, modellers and engineers. A new computational tool to represent microbial pat ...[more]

PMID: 27635191

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Project description:BackgroundCyanobacteria have emerged as highly efficient organisms for the production of chemicals and biofuels. Yet, the productivity of the cell has been low for commercial application. Cyanobacterial photobiotransformations utilize photosynthetic electrons to form reducing equivalents, such as NADPH-to-fuel biocatalytic reactions. These photobiotransformations are a measure to which extent photosynthetic electrons can be deviated toward heterologous biotechnological processes, such as the production of biofuels. By expressing oxidoreductases, such as YqjM from Bacillus subtilis in Synechocystis sp. PCC 6803, a high specific activity was obtained in the reduction of maleimides. Here, we investigated the possibility to accelerate the NAD(P)H-consuming redox reactions by addition of carbohydrates as exogenous carbon sources such as D-Glucose under light and darkness.ResultsA 1.7-fold increase of activity (150 µmol min-1 gDCW-1) was observed upon addition of D-Glucose at an OD750 = 2.5 (DCW = 0.6 g L-1) in the biotransformation of 2-methylmaleimide. The stimulating effect of D-Glucose was also observed at higher cell densities in light and dark conditions as well as in the reduction of other substrates. No increase in both effective photosynthetic yields of Photosystem II and Photosystem I was found upon D-Glucose addition. However, we observed higher NAD(P)H fluorescence when D-Glucose was supplemented, suggesting increased glycolytic activity. Moreover, the system was scaled-up (working volume of 200 mL) in an internally illuminated Bubble Column Reactor exhibiting a 2.4-fold increase of specific activity under light-limited conditions.ConclusionsResults show that under photoautotrophic conditions at a specific activity of 90 µmol min-1 gDCW-1, the ene-reductase YqjM in Synechocystis sp. PCC 6803 is not NAD(P)H saturated, which is an indicator that an increase of the rates of heterologous electron consuming processes for catalysis and biofuel production will require funnelling further reducing power from the photosynthetic chain toward heterologous processes.

Project description:BackgroundEconomic evaluation of emerging health technologies is mandated by agencies such as the National Institute for Health and Care Excellence (NICE) to ensure their cost is proportional to their benefit. To avoid bias, NICE stipulate that the benefit of a treatment is assessed across the lifetime of the patient population, which can be many decades. Unfortunately, follow-up from a clinical trial will not usually cover the required period and the observed follow-up will require extrapolation. For survival data this is often done by selecting a preferred model from a set of candidate parametric models. This approach is limited in that the choice of model is restricted to those originally fitted. What if none of the models are consistent with clinical prediction or external data?Method/resultsThis paper introduces SurvInt, a tool that estimates the parameters of common parametric survival models which interpolate key survival time co-ordinates specified by the user, which could come from external trials, real world data or expert clinical opinion. This is achieved by solving simultaneous equations based on the survival functions of the parametric models. The application of SurvInt is shown through two examples where traditional parametric modelling did not produce models that were consistent with external data or clinical opinion. Additional features include model averaging, mixture cure models, background mortality, piecewise modelling, restricted mean survival time estimation and probabilistic sensitivity analysis.ConclusionsSurvInt allows precise parametric survival models to be estimated and carried forward into economic models. It provides access to extrapolations that are consistent with multiple data sources such as observed data and clinical predictions, opening the door to precise exploration of regions of uncertainty/disagreement. SurvInt could avoid the need for post-hoc adjustments for complications such as treatment switching, which are often applied to obtain a plausible survival model but at the cost of introducing additional uncertainty. Phase III clinical trials are not designed with extrapolation in mind, and so it is sensible to consider alternative approaches to predict future survival that incorporate external information.

Dataset Information

MbT-Tool: An open-access tool based on Thermodynamic Electron Equivalents Model to obtain microbial-metabolic reactions to be used in biotechnological process.

Publications

MbT-Tool: An open-access tool based on Thermodynamic Electron Equivalents Model to obtain microbial-metabolic reactions to be used in biotechnological process.

Similar Datasets

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