Huijuan Xu

Two-step liquid hot water pretreatment of Eucalyptus grandis to enhance sugar recovery and enzymatic digestibility of cellulose

A two-step liquid hot water pretreatment (TSLHW) was developed with the objective of achieving complete saccharification of both hemicellulose and cellulose of Eucalyptus grandis, thereby avoiding the problems associated with the use of strong acid catalysts. The first step of the pretreatment was studied in the temperature range 180-200 degrees C, and the highest yield of total xylose achieved was 86.4% after 20 min at 180 degrees C. The second-step of the pretreatment was studied in the temperature range 180-240 degrees C and for lengths of time of 0-60 min. The conversion rate of glucan was more sensitive to temperature than time. The optimum reaction conditions for the second step of the pretreatment with minimal degradation of sugars were 200 degrees C for 20 min. the total sugar recovery from E. grandis with the optimized pretreatment and 72 h enzymatic digestion, reached 96.63%, which is superior to the recovery from a single-step pretreatment with hot water or dilute acid.

Artificial neural network-genetic algorithm based optimization for the immobilization of cellulase on the smart polymer Eudragit L-100

Cellulase was covalently immobilized on a smart polymer, Eudragit L-100 by carbodiimide coupling. Using data of central composite design, response surface methodology (RSM) and artificial neural network (ANN) were developed to investigate the effect of pH, carbodiimide concentration, and coupling time on the activity yield of immobilized cellulase. Results showed simulation and prediction accuracy of ANN was apparently higher compared to RSM. The maximum activity yield obtained from RSM was 57.56% at pH 5.54, carbodiimide concentration 0.32%, and coupling time 3.03 h, where the experimental value was 60.87 + or - 4.79%. Using ANN as fitness function, a maximum activity yield of 69.83% was searched by genetic algorithm at pH 5.07, carbodiimide concentration 0.36%, and coupling time 4.10 h, where the experimental value was 66.75 + or - 5.21%. ANN gave a 9.7% increase of activity yield over RSM. After reusing immobilized cellulase for 5 cycles, the remaining productivity was over 50%.

Medium optimization for ethanol production with Clostridium autoethanogenum with carbon monoxide as sole carbon source

Plackett-Burman and central composite designs were applied to optimize the medium for ethanol production by Clostridium autoethanogenum with CO as sole carbon source, and a medium containing (g/L): NaCl 1.0, KH(2)PO(4) 0.1, CaCl(2) 0.02, yeast extract 0.15, MgSO(4) 0.116, NH(4)Cl 1.694 and pH 4.74 was found optimal. The optimum ethanol yields predicted by response surface methodology (RSM) and an artificial neural network-genetic algorithm (ANN-GA) were 247.48 and 261.48mg/L, respectively. These values are similar to those obtained experimentally under the optimal conditions suggested by the statistical methods (254.26 and 259.64mg/L). The fitness of the ANN-GA model was higher than that of the RSM model. The yields obtained substantially exceed those previously reported (60-70mg/L) with this organism.

Cellulase deactivation based kinetic modeling of enzymatic hydrolysis of steam-exploded wheat straw.

Applying mass action law and quasi-steady-state theory, two cellulase kinetic models namely Eqs. (5) and (8) were developed on the basis of the first and second order reactions of enzyme deactivation, respectively. The two models are compared according to analysis of experimental data from enzymatic hydrolysis steam-exploded wheat straw. Both simulation and prediction results show Eq. (8) has much higher accuracy than Eq. (5). Analysis of initial hydrolysis rate is also in accordance with Eq. (8) and against Eq. (5). Fitted values of k(2) (the rate constant of product formation), k(de2) (the rate constant of enzyme deactivation) and K(e) (the equilibrium constant) determined from Eq. (8) are 0.4732 h(-1), 0.4011 L/(hg), and 16.8597 g/L, respectively. The higher the enzyme concentration is, the larger the deactivation rate.

Characterization of direct cellulase immobilization with superparamagnetic nanoparticles

Abstract Methods of cellulase immobilization on magnetic particles via glutaraldehyde binding were studied. The binding was confirmed by transmission electronic microscopy (TEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR) and vibrating sample magnetometry (VSM). Samples analyzed by TEM and XRD showed that the magnetic particles with or without bound cellulase were all nanosized particles with a mean diameter of 11.5 nm, and the binding process did not cause significant changes in particle size and structure. Analysis by FTIR showed that the binding of cellulase to the magnetic nanoparticles might be via covalent bonding between residual amine groups on Fe3O4 nanoparticles and amine groups of the cellulase. The VSM analysis showed that magnetic nanoparticles with or without bound cellulase were all superparamagnetic. The immobilized cellulase had a wider pH and temperature range and improved storage stability compared with the free enzyme. Determination of the Michaelis constants revealed that the immobilized cellulase had a greater affinity for the cellulosic substrate than the free enzyme. The immobilized cellulase showed better performance on hydrolysis of steam-exploded corn stalks than of bleached sulfite bagasse pulp.

A study of CO/syngas bioconversion by Clostridium autoethanogenum with a flexible gas-cultivation system

Bioconversion of CO/syngas to produce ethanol is a novel route in bioethanol production, which can be accomplished by some acetogens. Specific culture vessels and techniques are needed to cultivate these microorganisms since they are anaerobic and substrates are gaseous. In this work, gas-sampling bag was applied as a gas-cultivation system to study CO/syngas bioconversion by Clostridium autoethanogenum and was demonstrated to be efficient because of its flexibility and excellent ability to maintain the headspace atmosphere. C. autoethanogenum can use CO as the sole carbon and energy source to produce ethanol, acetate as well as CO2. In the experimental range, higher ethanol production was favored by higher yeast extract concentrations, and the maximum ethanol concentration of 3.45g/L was obtained at 1.0g/L of yeast extract. Study with various bottled gases showed that C. autoethanogenum preferred to use CO other than CO2 and produced the highest level of ethanol with 100% CO as the substrate. C. autoethanogenum can also utilize biomass-generated syngas (36.2% CO, 23.0% H2, 15.4% CO2, 11.3% N2), but the process proceeded slowly and insufficiently due to the presence of O2 and C2H2. In our study, C. autoethanogenum showed a better performance in the bioconversion of CO to ethanol than Clostridium ljungdahlii, a strain which has been most studied, and for both strains, ethanol production was promoted by supplementing 0.5g/L of acetate.

In situ deep eutectic solvent pretreatment to improve lignin removal from garden wastes and enhance production of bio-methane and microbial lipids

Biomass pretreatment can improve the conversion efficiency of bioenergy production. Liquid hot water (LHW) pretreatment is a truly green pretreatment due to its zero chemical use, but has the disadvantages of low lignin removal and pseudo-lignin formation. A modified liquid hot water (MLHW) process based on in situ synthesis of deep eutectic solvent (DES) could efficiently improve delignification of Roystonea regia leaves (LR) and leaf sheaths (LSR). LSR was less recalcitrant than LR, and its characteristics of higher porosity (34.8%) and thinner cell walls (5.2 μm) for LSR contributed it higher lignin removal (53.6%) and lower choline chloride (ChCl) consumption (H2O-ChCl mass ratio of 2:1) than those (44.6% and 1:2) from LR. Moreover, a great improvement of 309.0% in bio-methane yield was achieved for the MLHW-treated LSR. In addition, in situ DES in MLHW had good biocompatibility with cellulase, microalgae, and yeast.

Metagenomic analysis for the microbial consortium of anaerobic CO oxidizers

Metagenomics analysis has been applied to identify the dominant anaerobic microbial consortium of the carbon monoxide (CO) oxidizers in anaerobic sludge. Reads from the hypervariable V6 region in the bacterial 16s rDNA were aligned and finally clustered into operational taxonomic units (OTUs). The OTUs from different stages in anaerobic CO condition were classified. Alphaproteobacteria, clostridia, betaproteobacteria and actinobacteria were the most abundant groups, while alphaproteobacteria, betaproteobacteria and actinobacteria were variable groups. CO consumption and production efficiency of the microbial consortium were studied. Semi‐continuous trials showed that these anaerobic CO oxidizers formed a stable microbial community, and the CO conversion rate was at over 84%, with the highest CO consumption activity of 28.9 mmol CO/g VSS●day and methane production activity at 7.6 mmol CH4/g VSS●day during six cycles.