260 research outputs found

    Intensification of corn fiber saccharification using a tailor made enzymatic cocktail

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    The transition from an economic model based on resource extraction to a more sustainable and circular economy requires the development of innovative methods to unlock the potential of raw materials such as lignocellulosic biomasses. Corn fiber differs from more traditional lignocellulosic biomasses due to its high starch content, which provides additional carbohydrates for fermentation-based biomanufacturing processes. Due to its unique chemical composition, this study focused on the development of a tailor made enzymatic cocktail for corn fiber saccharification into monosaccharides. Three commercially available hydrolytic enzymes (Cellic® CTec2, Pentopan® Mono BG, and Termamyl® 300 L) were combined to hydrolyze the polysaccharide structure of the three main carbohydrate fractions of corn fiber (cellulose, hemicellulose and starch, respectively). Prior to saccharification, corn fiber was submitted to a mild hydrothermal pretreatment (30 min at 100 oC). Then, two experimental designs were used to render an enzymatic cocktail capable of providing efficient release of monosaccharides. Using 60 FPU/g DM of Cellic® CTec2 and 4.62 U/g DM of Termamyl® 300 L, without addition of Pentopan® Mono BG, resulted in the highest efficiencies for glucose and xylose release (66% and 30%, respectively). While higher enzyme dosages could enhance the saccharification efficiency, adding more enzymes would have a more pronounced effect on the overall process costs rather than in increasing the efficiency for monosaccharides release. The results revealed that the recalcitrance of corn fiber poses a problem for its full enzymatic degradation. This fact combined with the unique chemical composition of this material, justify the need for developing a tailor made enzymatic cocktail for its degradation. However, attention should also be given to the pretreatment step to reduce even more the recalcitrance of corn fiber and improve the performance of the tailored cocktail, as a consequence

    Microbial meat:A sustainable vegan protein source produced from agri-waste to feed the world

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    In the modern world, animal and plant protein may not meet the sustainability criteria due to their high need for arable land and potable water consumption, among other practices. Considering the growing population and food shortage, finding alternative protein sources for human consumption is an urgent issue that needs to be solved, especially in developing countries. In this context, microbial bioconversion of valuable materials in nutritious microbial cells represent a sustainable alternative to the food chain. Microbial protein, also known as single-cell protein (SCP), consist of algae biomass, fungi or bacteria that are currently used as food source for both humans and animals. Besides contributing as a sustainable source of protein to feed the world, producing SCP, is important to reduce waste disposal problems and production costs meeting the sustainable development goals. However, for microbial protein as feed or food to become an important and sustainable alternative, addressing the challenges of raising awareness and achieving wider public regulatory acceptance is real and must be addressed with care and convenience. In this work, we critically reviewed the potential technologies for microbial protein production, its benefits, safety, and limitations associated with its uses, and perspectives for broader large-scale implementation. We argue that the information documented in this manuscript will assist in developing microbial meat as a major protein source for the vegan world.</p

    Extrusion of process flavorings from methionine and dextrose using modified starch as a carrier

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    This study aimed to produce process flavorings from methionine and glucose via Maillard reaction by extrusion method. Modified starch was used as a carrier to reduce the torque and facilitate the production process. Five formulations of process flavorings with different ratios of methionine: dextrose: modified starch: water as MS5 (72:18:5:5), MS15 (64:16:15:5), MS25 (56:14:25:5), MS35 (42:12:35:5), and MS45 (40:10:45:5) were prepared and feded into the extruder. The temperatures of the extruder barrel in zones 1 and 2 were controlled at 100, and 120°C, with a screw speed of 30 rpm. The appearance of the obtained products, torque, pH before and after extrusion, color, volatile compounds, and sensory evaluation were determined. The extrudate from the formulation containing the highest amount of modified starch (MS45) gave the highest L* (lightness) of 88.00, which increased to 93.00 (very light) after grinding into a powder. The process flavorings from all formulations exhibited similar sensory scores in terms of aroma, taste, and water solubility, with a very slight difference in color. However, MS25, MS35 and MS45 indicated the torque at 10 Nm/cm3, while MS5 and MS 15 exhibited higher torque at 18, and 25 Nm/cm3, respectively. Extruded process flavorings from MS25 were analyzed for their flavor profiles by gas chromatography-mass spectrometry. Twelve volatile compounds including the key volatile compounds for sulfurous and vegetable odor type, dimethyl disulfide, methional, and methanethiol, were found. Four pyrazine compounds presented nutty, musty and caramelly odor; and 3-hydroxybutan-2-one and heptane-2,3-dione, which gave buttery odor type, were also detected. The results demonstrated a successful production of process flavorings using modified starch as carrier to facilitate and reduce the torque during the extrusion process

    Enzyme-constrained metabolic model and in silico metabolic engineering of Clostridium ljungdahlii for the development of sustainable production processes

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    Constraint-based genome-scale models (GEMs) of microorganisms provide a powerful tool for predicting and analyzing microbial phenotypes as well as for understanding how these are affected by genetic and environmental perturbations. Recently, MATLAB and Python-based tools have been developed to incorporate enzymatic constraints into GEMs. These constraints enhance phenotype predictions by accounting for the enzyme cost of catalyzed model´s reactions, thereby reducing the space of possible metabolic flux distributions. In this study, enzymatic constraints were added to an existing GEM of Clostridium ljungdahlii, a model acetogenic bacterium, by including its enzyme turnover numbers (kcats) and molecular masses, using the Python-based AutoPACMEN approach. When compared to the metabolic model iHN637, the enzyme cost-constrained model (ec_iHN637) obtained in our study showed an improved predictive ability of growth rate and product profile. The model ec_iHN637 was then employed to perform in silico metabolic engineering of C. ljungdahlii, by using the OptKnock computational framework to identify knockouts to enhance the production of desired fermentation products. The in silico metabolic engineering was geared towards increasing the production of fermentation products by C. ljungdahlii, with a focus on the utilization of synthesis gas and CO2. This resulted in different engineering strategies for overproduction of valuable metabolites under different feeding conditions, without redundant knockouts for different products. Importantly, the results of the in silico engineering results indicated that the mixotrophic growth of C. ljungdahlii is a promising approach to coupling improved cell growth and acetate and ethanol productivity with net CO2 fixation
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