Abstract: In this study, Aspergillus niger ADM110 fungi was gamma irradiated to produce lipase enzyme and then immobilized onto magnetic barium ferrite nanoparticles (BFN) for biodiesel production. BFN were prepared by the citrate sol-gel auto-combustion method and characterized by transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier transform infrared (FTIR) and scanning electron microscopy with energy dispersive analysis of X-ray (SEM/EDAX) analysis. The activities of free and immobilized lipase were measured at various pH and temperature values. The results indicate that BFN–Lipase (5%) can be reused in biodiesel production without any treatment with 17% loss of activity after five cycles and 66% loss in activity in the sixth cycle. The optimum reaction conditions for biodiesel production from waste cooking oil (WCO) using lipase immobilized onto BFN as a catalyst were 45 °C, 4 h and 400 rpm. Acid values of WCO and fatty acid methyl esters (FAMEs) were 1.90 and 0.182 (mg KOH/g oil), respectively. The measured flash point, calorific value and cetane number were 188 °C, 43.1 MJ/Kg and 59.5, respectively. The cloud point (−3 °C), pour point (−9 °C), water content (0.091%) and sulfur content (0.050%), were estimated as well.
Abstract: Gene regulatory networks represent an abstract mapping of gene regulations in living cells. They aim to capture dependencies among molecular entities such as transcription factors, proteins and metabolites. In most applications, the regulatory network structure is unknown, and has to be reverse engineered from experimental data consisting of expression levels of the genes usually measured as messenger RNA concentrations in microarray experiments. Steady-state gene expression data are obtained from measurements of the variations in expression activity following the application of small perturbations to equilibrium states in genetic perturbation experiments. In this paper, the least absolute shrinkage and selection operator-vector autoregressive (LASSO-VAR) originally proposed for the analysis of economic time series data is adapted to include a stability constraint for the recovery of a sparse and stable regulatory network that describes data obtained from noisy perturbation experiments. The approach is applied to real experimental data obtained for the SOS pathway in Escherichia coli and the cell cycle pathway for yeast Saccharomyces cerevisiae. Significant features of this method are the ability to recover networks without inputting prior knowledge of the network topology, and the ability to be efficiently applied to large scale networks due to the convex nature of the method.
Abstract: Screening and obtaining a novel high activity cellulase and its producing microbe strain is the most important and essential way to improve the utilization of crop straw. In this paper, we devoted our efforts to isolating a novel microbe strain which could produce high activity cellulase. A novel strain Trichoderma virens ZY-01 was isolated from a cropland where straw is rich and decomposed, by using the soil dilution plate method with cellulose and Congo red. The strain has been licensed with a patent numbered ZL 201210295819.6. The cellulase activity in the cultivation broth could reach up to 7.4 IU/mL at a non-optimized fermentation condition with the newly isolated T. virens ZY-01. The cellulase was separated and purified from the T. virens culture broth through (NH4)2SO4 fractional precipitation, anion-exchange chromatography and gel filtration chromatography. With the separation process, the CMC specific activity increased from 0.88 IU/mg to 31.5 IU/mg with 35.8 purification fold and 47.04% yield. Furthermore, the enzymatic properties of the cellulase were investigated. The optimum temperature and pH is 50 °C and pH 5.0 and it has good thermal stability. Zn2+, Ca2+ and Mn2+ could remarkably promote the enzyme activity. Conversely, Cu2+ and Co2+ could inhibit the enzymatic activity. This work provides a new highly efficient T. virens strain for cellulase production and shows good prospects in practical application.
Abstract: The study of brain dynamics currently utilizes the new features of nanobiotechnology and bioengineering. New geometric and analytical approaches appear very promising in all scientific areas, particularly in the study of brain processes. Efforts to engage in deep comprehension lead to a change in the inner brain parameters, in order to mimic the external transformation by the proper use of sensors and effectors. This paper highlights some crossing research areas of natural computing, nanotechnology, and brain modeling and considers two interesting theoretical approaches related to brain dynamics: (a) the memory in neural network, not as a passive element for storing information, but integrated in the neural parameters as synaptic conductances; and (b) a new transport model based on analytical expressions of the most important transport parameters, which works from sub-pico-level to macro-level, able both to understand existing data and to give new predictions. Complex biological systems are highly dependent on the context, which suggests a “more nature-oriented” computational philosophy.
Abstract: Enterohemorrhagic Escherichia coli (EHEC) are responsible for large outbreaks of hemorrhagic colitis, which can progress to life-threatening hemolytic uremic syndrome (HUS) due to the release of Shiga-like toxins (Stx). The presence of a functional nitric oxide (NO·) reductase (NorV), which protects EHEC from NO· produced by immune cells, was previously found to correlate with high HUS incidence, and it was shown that NorV activity enabled prolonged EHEC survival and increased Stx production within macrophages. To enable quantitative study of EHEC NO· defenses and facilitate the development of NO·-potentiating therapeutics, we translated an existing kinetic model of the E. coli K-12 NO· response to an EHEC O157:H7 strain. To do this, we trained uncertain model parameters on measurements of [NO·] and [O2] in EHEC cultures, assessed parametric and prediction uncertainty with the use of a Markov chain Monte Carlo approach, and confirmed the predictive accuracy of the model with experimental data from genetic mutants lacking NorV or Hmp (NO· dioxygenase). Collectively, these results establish a methodology for the translation of quantitative models of NO· stress in model organisms to pathogenic sub-species, which is a critical step toward the application of these models for the study of infectious disease.
Abstract: Co-utilization of carbon sources in microbes is an important topic in metabolic engineering research. It is not only a way to reduce microbial production costs but also an attempt for either improving the yields of target products or decreasing the formation of byproducts. However, there are barriers in co-utilization of carbon sources in microbes, such as carbon catabolite repression. To overcome the barriers, different metabolic engineering strategies have been developed, such as inactivation of the phosphotransferase system and rewiring carbon assimilation pathways. This review summarizes the most recent developments of different strategies that support microbes to utilize two or more carbon sources simultaneously. The main content focuses on the co-utilization of glucose and pentoses, major sugars in lignocellulose.