Carbon Dioxide Inhibition of Escherichia coli and Staphylococcus aureus on a pH-adjusted Surface in a Model System

Growth of Escherichia coli and Staphylococcus aureuson the surface of Trypticase Soy Agar (TSA) packaged with various CO₂ partial pressures (0, 20, 40, 60, 80, 100%, balance N₂) was compared to the control (N₂ 100%) on TSA in which the pH was adjusted to equal that in CO₂ atmospheres at 15°C and 30°C. At 15°C, the biostatic effect was noted with all CO₂ partial pressures for both species. At 30°C, the biostatic effect of CO₂ was almost completely nullified for E. coli, but that for S. aureus was still effective. S. aureus was more sensitive to the inhibitory effects of CO₂ than E. coli at both the temperatures.     

Hydrogen production and metabolic flux analysis of metabolically engineered Escherichia coli strains

Escherichia coli can produce H₂ from glucose via formate hydrogen lyase (FHL). In order to improve the H₂ production rate and yield, metabolically engineered E. coli strains, which included pathway alterations in their H₂ production and central carbon metabolism, were developed and characterized by batch experiments and metabolic flux analysis. Deletion of hycA, a negative regulator for FHL, resulted in twofold increase of FHL activity. Deletion of two uptake hydrogenases (1 (hya) and hydrogenase 2 (hyb)) increased H₂ production yield from 1.20 mol/mol glucose to 1.48 mol/mol glucose. Deletion of lactate dehydrogenase (ldhA) and fumarate reductase (frdAB) further improved the H₂ yield; 1.80 mol/mol glucose under high H₂ pressure or 2.11 mol/mol glucose under reduced H₂ pressure. Several batch experiments at varying concentrations of glucose (2.5–10 g/L) and yeast extract (0.3 or 3.0 g/L) were conducted for the strain containing all these genetic alternations, and their carbon and energy balances were analyzed. The metabolic flux analysis revealed that deletion of ldhA and frdABdirected most of the carbons from glucose to the glycolytic pathway leading to H₂ production by FHL, not to the pentose phosphate pathway.     

Nonlinear Predictive Control of Fed‐Batch Cultures of Escherichia coli

A strategy for controlling a fed‐batch Escherichia coli culture is described to maintain the culture at the boundary between oxidative and oxido‐fermentative regimes. A nonlinear predictive controller is designed to regulate the acetate concentration, constraining the feed rate to follow an optimal reference profile which maximizes the biomass growth. For the sake of simplicity and efficiency, the original problem is converted into an unconstrained nonlinear programming problem, solved by control vector parameterization techniques. The robustness of the structure is further improved by explicitly including the difference between system and model prediction. A robustness study based on a Monte Carlo approach is used to evaluate the performance of the proposed controller. This control law is finally compared to the generic model control strategy.     

Use of multivariate analysis for the improvement in prediction accuracy of bacterial aerobic plate count by flow cytometry

Flow cytometry (FCM) and aerobic plate count (APC) by the culture method were performed on green tea samples spiked with Escherichia coli type strain NCTC9001 (ATCC11775) solutions of different concentrations. In FCM, fluorescence signals from multiple stained bacteria and other fluorophores are detected using detector channels, and recorded as events with a voltage at each channel. FCM data were analyzed in two ways: conventional and multivariate analysis. In the former, the number of events with voltages larger than the defined threshold values was regarded as the predicted APC. In the latter, voltage histograms of all channels were obtained and merged horizontally to serve as explanatory variables. Then a partial least squares regression (PLSR) model was built to predict APC from the histogram data. The coefficient of determination (R²) and the root mean square error (RMSE) between APC by the culture method and that predicted by conventional FCM were 0.916 and 1.08 cfu/ml². The APC values predicted by the PLSR model and those measured were in good agreement with R² of 0.982 and RMSE of 0.417 cfu/ml, which verified the potential of the proposed method for improving APC prediction accuracy by FCM.     

Fermentative hydrogen production by Clostridium butyricum and Escherichia coli in pure and cocultures

The effect of coculture of Clostridium butyricum and Escherichia coli on hydrogen production was investigated. C. butyricum and E. coli were grown separately and together as batch cultures. Gas production, growth, volatile fatty acid production and glucose degradation were monitored. Whilst C. butyricum alone produced 2.09 mol-H₂/mol-glucose the coculture produced 1.65 mol-H₂/mol-glucose. However, the coculture utilized glucose more efficiently in the batch culture, i.e., it was able to produce more H₂ (5.85 mmol H₂) in the same cultivation setting than C. butyricum (4.62 mmol H₂), before the growth limiting pH was reached.     

Prospecting hydrogen production of Escherichia coli by metabolic network modeling

Genome-scale model was applied to analyze the anaerobic metabolism of Escherichia coli. Three different methods were used to find deletions affecting fermentative hydrogen production: flux balance analysis (FBA), algorithm for blocking competing pathways (ABCP), and manual selection. Based on these methods, 81 E. coli mutants possessing one gene deletion were selected and cultivated in batch experiments. Experimental results of H₂ and biomass production were compared against the results of FBA. Several gene deletions enhancing H₂ production were found. Correctness of gene essentiality predictions of FBA for the selected genes was 78% and 77% in glucose and galactose media, respectively. 33% of the mutations that were predicted by FBA to increase H₂ production had a positive effect in experiments. Batch cultivation is a simple and straightforward experimental way to screen improvements in H₂ production. However, the ability of FBA to predict the H₂ production rate cannot be evaluated by batch experiments. Metabolic network models provide a method for gaining broader understanding of the complicated metabolic system of a cell and can aid in prospecting suitable gene deletions for enhancing H₂ production.     

大肠杆菌中芥蓝抗坏血酸过氧化物酶基因的高效表达

将芥蓝抗坏血酸过氧化物酶(Apx)在大肠杆菌中高效表达。以芸薹属植物apx保守区基因序列为基础,利用PCR,RACE技术从芥蓝中扩增得到全长为753 bp的芥蓝apx编码基因,用DNAMAN V6软件分析该基因氨基酸组成,计算出蛋白分子质量约为27.6 kDa。通过构建重组质粒pET-28a-apx,转化大肠杆菌E.coli BL21,实现了芥蓝Apx的可溶性表达。通过单因素实验优化诱导表达条件,结果表明:0.2 mmol/L IPTG,23℃诱导培养10 h为最佳诱导条件。采用Ni2+亲和层析,纯化了重组蛋白,并得到重组酶最适反应条件为pH 6.5和40℃。为进一步研究Apx的生理特性和功能打下基础。     

Synthesis of Mixed Refrigerant Cascade Cycles

This paper considers the synthesis of refrigeration systems with refrigerant mixtures as working fluids. The employed refrigeration topology encompasses features from industrial liquefaction of natural gas (LNG) systems. This configuration consists of a combination of horizontal and vertical cascades generalizing the vertical cascade of pure refrigerant systems. The key features of mixtures exploited here are their ability to evaporate/condense over a temperature range and their potential to generate streams with different compositions through partial condensation. The synthesis problem is formulated and solved as a nonlinear program. The proposed methodology is illustrated using an example of cooling a methane-rich stream.     

An Interpretation Model For The UV-VIS Spectra Of Microorganisms

Multiwavelength UV-vis spectra of microorganisms and cell suspensions contain quantitative information on their properties such as number, size, shape, chemical composition, and internal structure. These properties are essential for the identification and classification of cells. The complexity of microorganisms in terms of their chemical composition and internal structure makes the interpretation of their spectral signature a difficult task. In this article a model is proposed for the interpretation of the multiwavelength spectra of microorganisms. The proposed interpretation model is based on light scattering theory, spectral deconvolution techniques, and the approximation of the frequency-dependent optical properties of the basic constituents of living organisms. The optical properties as functions of wavelength and available literature data on the size and chemical composition of E. coli cells and Bacillus globigii spores were used to explore the sensitivity of the calculated spectra to the model parameters. It is shown that the proposed model can reproduce the features of experimentally measured spectra. The sensitivity of the spectra to the model parameters suggests that the proposed model can be used for the quantitative deconvolution of the UV-vis spectra in terms of critical information necessary for the detection and identification of microorganisms.