Enhancing the sweetening power of lactose by enzymatic modification in the reformulation of dairy products

Lactose solutions of up to 50% (w/v) were incubated with lactases and glucose isomerases for subsequent implementation in dairy product samples to enhance sweetness. A degree of hydrolysis of >90% and of isomerisation of 50% were attainable. The sensory sweetening power of lactose in solutions of up to 50% (w/v) can be enhanced 2–3 times. Based on sensory experiments, application of this bi‐enzymatic system in yoghurt and pudding samples allowed for a 10–20% (w/w) reduction in the total sugar content, whilst retaining equal sweetness. The growth of yoghurt starter cultures was not affected, yet furosine formation more than doubled in high heated, enzyme‐modified milk.     

基于高通量测序的东湖蓝藻动态变化研究

采用高通量测序(High-throughput sequencing technology)和实时荧光定量PCR技术,结合水质参数的检测,研究了东湖两个不同富营养化程度湖区蓝藻整年丰度和群落结构的变化,并统计分析蓝藻与环境参数之间的关系。结果表明:(1)两区域微囊藻在6~7月达到全年最高值,但拷贝数相差近20倍。(2)两区域蓝藻门在属水平的变化也有显著差异,H区蓝藻在4~11月主要由浮丝藻属(Planktothrix)(4~6月)、微囊藻属(Microcystis)(6~9月)、聚球藻属(Synechococcus sp. PS717)(7~11月)交替演变,L区蓝藻主要是由束丝藻属(Aphanizomenon)(4~6月)和聚球藻属(Synechococcus sp. PS717)(4~10月)组成,并且与H区在相对丰度变化上比较,L区较平稳。(3) RDA分析表明,Tw、p H、NH4-N是影响H区蓝藻属水平分类差异的主要因素,影响L区蓝藻属水平差异的主要因素是Tw、TP、p H。(4)与以往传统藻类计数相比,还发现了以往显微观察难以发现的聚球藻属和拟柱孢藻属等,且聚球藻属在东湖蓝藻门中占优势地位,应在以后的研究中得到更多的关注。     

PSTI1可提高大肠杆菌应答胁迫能力

指出含典型34肽重复序列结构域(tetratricopeptide repeat,TPR)的胁迫诱导蛋白(stress-in-ducible protein-1,STI1)是真核生物特有的一类与胁迫应答有关的分子伴侣蛋白.作者从多头绒泡菌分离出一个STI1类似蛋白cDNA,因其编码蛋白含有两个非典型的TPR结构域,命名为PSTI1.为了解PSTI1对原核生物胁迫应答功能的影响,观察表达PSTI1的大肠杆菌(Escherichia coli,E.coli)与原菌株的增殖差异,发现PSTI1表达菌耐受盐、渗透压、重金属离子、氧化、缺氧和酸碱变化胁迫的能力均增强,但对高温敏感.PSTI1保守结构域TPR1能提高E.coli耐受渗透压胁迫的能力,但TPR2会使E.coli对盐和渗透压胁迫敏感,说明TPR1和TPR2在PSTI1调控胁迫应答中可能扮演不同角色.通过pull-down和质谱分析技术检测了与PSTI1作用的E.coli蛋白,发现PSTI1能与E.coli的HtpG(Hsp90)、La蛋白酶和过氧化氢酶HpII等作用,说明PSTI1具有原核生物非典型TPR结构域蛋白的类似功能,是类似STI1的胁迫应答蛋白.     

“环境工程微生物学”课程教学方法探析

环境工程微生物学课程内容具有一定的抽象性,如何在教学过程中变抽象为具体,激发学生学习兴趣尤为重要。文章针对该门课程不同的教学内容采取了相应的教学方法和教学手段,以达到全面提高教学质量,整体优化教学过程的目的。     

The use of gold markers in immunocytochemical studies of microbiological organisms: a review

Colloidal gold probes have revolutionized electron immunocytochemistry and are now used extensively for microbiological studies. The gold probes can be applied in one of several methods to gain valuable information from the sample. The pre-embedding technique, the post-embedding technique, the immunonegative stain technique, the immunoreplica technique and the immunofreeze-fracture technique, are each described and their applications in microbiology, for diagnosis, for the detection of the site of antigen synthesis in host cells, for vaccine production and for genetic engineering are reported.     

Simulation of Fluctuating Populations of Microorganisms and Macroorganisms with Models Having a Normal Random Variate Term

Fluctuating populations of micro- and macroorganisms play a major role in the stability and safety of food and agricultural products. In recent years such populations have been described by ‘chaotic’ models, most notably the discrete logistic function. This model's major limitations, however, are that it implies determinism and that it can account for neither population explosions nor extinction. Consequently, it is suggested that in order to simulate realistic population histories, the growth rate constant, r, in the original discrete logistic function X_n+1=rX_n(1-X_n) can be replaced by a randomly varying term, r_n. The latter can be defined as r_n=r₀ exp(kZ_rn) where r₀ is a characteristic constant, Z_rn a normal random variate produced by a normally distributed random number generator and k its chosen standard deviation. Theoretically, the magnitude of such r_n (and its corresponding X_n) can be anywhere in the range 0<X_n<∞. However, the magnitude of k can be selected so that X_n>1 is a very rare event. In the special case of widely fluctuating populations dominated by random factors, the model can be replaced by N_n/N₀=exp(k′Z_rn), where N₀ is a characteristic number. In this form the model can account for occasional aperiodic population explosions, and if a lower limit to a viable number is also set (eg N/N₀>0·01), for extinction events as well. The flexibility of the two models is demonstrated with simulated population evolution patterns of different kinds. © 1997 SCI.     

Effect on weaner pig performance and diet microbiology of feeding a liquid diet acidified to pH 4 with either lactic acid or through fermentation with Pediococcus acidilactici

The effect of feeding newly weaned pigs acidified liquid diets was investigated. The control diet was acidified to about pH 4 with lactic acid (LA). A second diet of the same formulation was acidified to about pH 4 by fermentation with Pediococcus acidilactici (PA). Forty‐eight weaner pigs (weight 7 kg±1 kg, age 24±4 days) were allocated to the two dietary treatments according to a randomised block design and fed ad libitum for 28 days. Food intake, daily gain and water intake were recorded, and a microbial assessment of the liquid diet was conducted. Reducing pH<4.0 in either of the liquid diets was effective in eliminating coliform bacteria. There were no significant differences in any of the performance parameters measured. The average daily liveweight gain overall was 474 and 496±17.8 g d⁻¹ for PA and LA, respectively, with a feed conversion ratio overall of 1.15 and 1.11±0.025 for PA and LA, respectively. Fermentation of liquid diets for newly weaned piglets could provide a more cost effective means of acidifying diets than the use of organic acids. Reducing the pH of the liquid diet to 4.00 by fermentation with Pediococcus acidilactici was a cost effective method of eliminating enteropathogens and spoilage organisms from the diet. © 1999 Society of Chemical Industry     

Predictive modeling of microbial single cells: A review

In practice, food products tend to be contaminated with food-borne pathogens at a low inoculum level. However, the huge potential risk cannot be ignored because microbes may initiate high-speed growth suitable conditions during the food chain, such as transportation or storage. Thus, it is important to perform predictive modeling of microbial single cells. Several key aspects of microbial single-cell modeling are covered in this review. First, based on previous studies, the techniques of microbial single-cell data acquisition and growth data collection are presented in detail. In addition, the sources of microbial single-cell variability are also summarized. Due to model microbial growth, traditional deterministic mathematical models have been developed. However, most models fail to make accurate predictions at low cell numbers or at the single-cell level due to high cell-to-cell heterogeneity. Stochastic models have been a subject of great interest; and these models take into consideration the variability in microbial single-cell behavior.