996 resultados para microbial metabolic quotient
Resumo:
Flour-rich waste (FRW) and by-product streams generated by bakery, confectionery and wheat milling plants could be employed as the sole raw materials for generic fermentation media production, suitable for microbial oil synthesis. Wheat milling by-products were used in solid state fermentations (SSF) of Aspergillus awamori for the production of crude enzymes, mainly glucoamylase and protease. Enzyme-rich SSF solids were subsequently employed for hydrolysis of FRW streams into nutrient-rich fermentation media. Batch hydrolytic experiments using FRW concentrations up to 205 g/L resulted in higher than 90%(w/w) starch to glucose conversion yields and 40% (w/w) total Kjeldahl nitrogen to free amino nitro-gen conversion yields. Starch to glucose conversion yields of 98.2, 86.1 and 73.4% (w/w) were achieved when initial FRW concentrations of 235, 300 and 350 g/L were employed in fed-batch hydrolytic experiments, respectively. Crude hydrolysates were used as fermentation media in shake flask cultures with the oleaginous yeast Lipomyces starkeyi DSM 70296 reaching a total dry weight of 30.5 g/L with a microbial oil content of 40.4% (w/w), higher than that achieved in synthetic media. Fed-batch bioreactor cultures led to a total dry weight of 109.8 g/L with a microbial oil content of 57.8% (w/w) and productivity of 0.4 g/L/h.
Resumo:
Experimental results from the open literature have been employed for the design and techno-economic evaluation of four process flowsheets for the production of microbial oil or biodiesel. The fermentation of glucose-based media using the yeast strain Rhodosporidium toruloides has been considered. Biodiesel production was based on the exploitation of either direct transesterification (without extraction of lipids from microbial biomass) or indirect transesterifaction of extracted microbial oil. When glucose-based renewable resources are used as carbon source for an annual production capacity of 10,000 t microbial oil and zero cost of glucose (assuming development of integrated biorefineries in existing industries utilising waste or by-product streams) the estimated unitary cost of purified microbial oil is $3.4/kg. Biodiesel production via indirect transesterification of extracted microbial oil proved more cost-competitive process compared to the direct conversion of dried yeast cells. For a price of glucose of $400/t oil production cost and biodiesel production cost are estimated to be $5.5/kg oil and $5.9/kg biodiesel, correspondingly. Industrial implementation of microbial oil production from oleaginous yeast is strongly dependent on the feedstock used and on the fermentation stage where significantly higher productivities and final microbial oil concentrations should be achieved.
Resumo:
The rapid development of biodiesel production technology has led to the generation of tremendous quantities of glycerol wastes, as the main by-product of the process. Stoichiometrically, it has been calculated that for every 100 kg of biodiesel, 10 kg of glycerol are produced. Based on the technology imposed by various biodiesel plants, glycerol wastes may contain numerous kinds of impurities such as methanol, salts, soaps, heavy metals and residual fatty acids. This fact often renders biodiesel-derived glycerol unprofitable for further purification. Therefore, the utilization of crude glycerol though biotechnological means represents a promising alternative for the effective management of this industrial waste. This review summarizes the effect of various impurities-contaminants that are found in biodiesel-derived crude glycerol upon its conversion by microbial strains in biotechnological processes. Insights are given concerning the technologies that are currently applied in biodiesel production, with emphasis to the impurities that are added in the composition of crude glycerol, through each step of the production process. Moreover, extensive discussion is made in relation with the impact of the nature of impurities upon the performances of prokaryotic and eukaryotic microorganisms, during crude glycerol bioconversions into a variety of high added-value metabolic products. Finally, aspects concerning ways of crude glycerol treatment for the removal of inhibitory contaminants as reported in the literature are given and comprehensively discussed
Resumo:
SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework designed to simulate microbial dynamics and biogeochemical cycling during initial ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The rationale for model development arises from decades of empirical observations in glacier forefields, and enables a quantitative and process focussed approach. Here, we provide a detailed description of SHIMMER, test its performance in two case study forefields: the Damma Glacier (Switzerland) and the Athabasca Glacier (Canada) and analyse sensitivity to identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Primary production is responsible for the initial build-up of labile substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter, and nitrogen fixation, are important in sustaining this productivity. The development and application of SHIMMER also highlights aspects of these systems that require further empirical research: quantifying nutrient budgets and biogeochemical rates, exploring seasonality and microbial growth and cell death. This will lead to increased understanding of how glacier forefields contribute to global biogeochemical cycling and climate under future ice retreat.
Resumo:
Inositol levels, maintained by the biosynthetic enzyme inositol-3-phosphate synthase (Ino1), are altered in a range of disorders including bipolar disorder and Alzheimer's disease. To date, most inositol studies have focused on the molecular and cellular effects of inositol depletion without considering Ino1 levels. Here we employ a simple eukaryote, Dictyostelium, to demonstrate distinct effects of loss of Ino1 and inositol depletion. We show that loss of Ino1 results in inositol auxotrophy that can only be partially rescued by exogenous inositol. Removal of inositol supplementation from the ino1- mutant results in a rapid 56% reduction in inositol levels, triggering the induction of autophagy, reduced cytokinesis and substrate adhesion. Inositol depletion also caused a dramatic generalised decrease in phosphoinositide levels that was rescued by inositol supplementation. However, loss of Ino1 triggered broad metabolic changes consistent with the induction of a catabolic state that was not rescued by inositol supplementation. These data suggest a metabolic role for Ino1 independent of inositol biosynthesis. To characterise this role, an Ino1 binding partner containing SEL1L1 domains (Q54IX5) was identified with homology to mammalian macromolecular complex adaptor proteins. Our findings therefore identify a new role for Ino1, independent of inositol biosynthesis, with broad effects on cell metabolism.
Resumo:
Background Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity–associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D). Methods The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model. Results There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (Pinteraction = 0.04), where the ‘A’ allele carriers had 2.46 times increased risk of obesity than those with ‘CC’ genotype (P = 3.0 × 10−5) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (Pinteraction = 0.0008), where individuals with AA genotype who are in the 3rd tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with ‘T’ allele carriers (P = 0.02). Furthermore, among those who were physically inactive, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with ‘CC’ genotype (P = 4.0 × 10−5). Conclusions This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population.