蛋黄液中沙门氏菌温度预测模型的建立

为探究温度对沙门氏菌在蛋液中生长规律的影响,测定了在4、10、15、20、25、30、37和42℃等不同温度下沙门氏菌的生长曲线,利用Origin 8.0软件中非线性最小二乘法的原理进行修正Gompertz方程、修正Logistic方程的拟合以及DMFit软件进行Baranyi模型的拟合,研究结果表明修正Gompertz模型、修正Logistic模型和Baranyi模型均能得到较高的决定系数(0.99),选取决定系数相对较高的修正Logistic模型进行一级模型的建立。通过参数估计后利用Ratkowsky模型对最大比生长速率以及迟滞期进行二级模型的拟合,通过Baranyi模型得到的生长参数建立的二级模型拟合度高于其他模型,最大比生长速率以及迟滞期二级模型决定系数分别为0.978和0.866。经检验,研究建立的模型可用于10~42℃温度范围内蛋黄液中沙门氏菌的生长预测。     

冷却猪肉中气单胞菌生长预测模型的建立和检验

为探讨冷却猪肉中气单胞菌的生长规律,将气单胞茵接种到经过80℃无菌水灭菌的冷却猪肉中,构建Gompertz和Baranyi初级模型来描述气单胞菌在不同温度下的生长状况。结果表明：修正的Gompertz模型对气单胞菌生长曲线的拟合效果优于Baranyi模型,R2均在0．97以上。应用平方根模型和Arrhenius模型对由修正的Gompertz模型得出的最大比生长速率进行拟合,所得平方根模型拟合效果略优于Arrhenius模型。实验所建二级模型能预测0-35℃贮藏条件下气单胞菌的生长。     

金黄色葡萄球菌AgrA/C双组分信号转导模型的构建与功能评价

【背景】抗生素的无序使用加剧了耐药性金黄色葡萄球菌超级菌株的出现,由其引发的感染已成为最难解决的感染性疾患。在生物体系外构建AgrA/C双组分系统的跨膜信号转导过程,对解决金黄色葡萄球菌的耐药性问题和发现新型抗菌药物具有重要的研究意义。【目的】人工模拟构建金黄色葡萄球菌AgrA/C双组分信号转导模型,为生物体外研究金黄色葡萄球菌双组分信号转导的机制及以其为靶点的药物筛选提供新途径。【方法】在大肠杆菌宿主细胞中大量表达AgrA和Agr C蛋白,利用亲和层析和分子筛凝胶层析对其进行分离纯化,利用非放射性凝胶阻滞实验(EMSA)检测AgrA蛋白活性,并检测Agr C激酶活性;进而利用脂质体介导法在体外组装AgrA/C双组分信号转导模型,应用EMSA方法进行评价。【结果】分离纯化得到AgrA和Agr C蛋白,二者纯度均达到90%以上,均具有活性。在生物体系外构建了金黄色葡萄球菌AgrA/C双组分信号转导模型,该系统可增强AgrA对DNA的延滞作用,具有信号传递功能。【结论】初步构建AgrA/C双组分信号转导模型,该模型具有信号传递能力,有望作为针对金黄色葡萄球菌开发新型抗菌药物的筛选平台。     

鲜切生菜中沙门氏菌二级生长预测模型的建立

以鲜切生菜为研究对象,比较了修正的Gompertz、Gompertz、Logistic和MMF 4种一级模型对不同温度下鲜切生菜中沙门氏菌生长曲线的拟合情况,发现在36℃、20℃和10℃时,修正的Gompertz模型均为最佳的拟合模型,4℃时沙门氏菌生长受到抑制,对失活/存活曲线进行"镜像化"处理后发现拟合程度相对较低,相关系数为0.962 7,故未用于二级模型中;采用其他温度下的修正的Gompertz模型中的最大比生长速率作为二级模型的响应值,建立平方根二级模型;准确因子和偏差因子对二级模型的准确性验证结果表明,两者均接近1.0,说明所建立的二级模型用于预测鲜切生菜中沙门氏菌生长情况。本研究为鲜切生菜的微生物安全控制提供科学依据。     

熟肉制品中金黄色葡萄球菌生长模型的建立

对不同温度下(10℃、15℃、25℃、30℃和37℃)熟肉制品中金黄色葡萄球菌的生长进行拟合。一级生长预测模型的建立采用SGompertz和Slogistic模型,由此获得恒定温度下的参数值(最大比生长速率:μ_(max)和延滞期:λ)。同时选用平方根模型(Square Root model)和二次多项式模型(Quadratic Polynomial model)对一级生长预测模型获得的μ_(max)和λ进行拟合,建立二级生长预测模型,并对模型的拟合度和可靠性进行评价。研究发现SGompertz模型可以更好地拟合熟肉制品中金黄色葡萄球菌在10℃~37℃下的生长;二次多项式模型是拟合温度与μ_(max)之间关系的最适模型;平方根模型是拟合温度与λ之间关系的最适模型。     

牛肉中单增李斯特菌的热失活模型

【目的】建立牛肉中单增李斯特菌的热失活动力学模型。【方法】将接种了3种不同血清型的单增李斯特菌混合菌液的牛肉分别在55℃、57.5℃、60℃、63℃、66℃和70℃进行热处理,在不同温度条件下单增李斯特菌数从109CFU/g下降至103CFU/g,其热失活曲线用修正的Gompertz模型进行了拟合;利用线性模型对单增李斯特菌的相对失活率(μ)和所持续时间(M)的自然对数值与温度(55℃-70℃)进行拟合;通过在59℃和64℃对牛肉中单增李斯特菌热处理,对所建的模型进行了验证。【结果】建立了牛肉中单增李斯特菌热失活动力学的一级模型和二级模型,经验证其准确因子和偏差因子均在可接受范围内。【结论】本研究所建立的模型能较好的模拟不同温度(55℃-70℃)对牛肉中单增李斯特菌热失活的影响。     

一株金黄色葡萄球菌噬菌体的分离鉴定与生物学特性

【背景】金黄色葡萄球菌作为一种条件致病菌,在临床感染中扮演着重要的角色,需要研究更多更有效的防治手段。【目的】分离金黄色葡萄球菌噬菌体,研究其生物学特性,从而为金黄色葡萄球菌的替代防治提供理论借鉴。【方法】以金黄色葡萄球菌D085为宿主从污水中分离得到一株噬菌体,命名为v B_Sau S_SAP3,用PEG8000浓缩、氯化铯密度梯度离心获得高纯度的噬菌体,1%乙酸双氧铀染色噬菌体进行电镜观察。测定噬菌体宿主谱、最佳感染复数(Multiplicity of Infection,MOI)、一步生长曲线、热稳定性、pH值稳定性及有机溶剂对噬菌体活性的影响。平衡酚法获取噬菌体基因组,Illumina测序技术和SPAdes软件进行基因组测序分析。【结果】电镜下,噬菌体SAP3头部直径为60±5 nm,尾部长170±5 nm。噬菌体vB_SauS_SAP3还能裂解5株金黄色葡萄球菌和1株产色葡萄球菌,其最佳感染复数为0.1。噬菌体vB_SauS_SAP3潜伏期为20 min,60 min后进入平台期,裂解量约为210 PFU/cell;对45°C以下温度有一定耐受性,超过45°C开始急剧失活;能在中性pH值时保持稳定活性,酸性环境会使其急剧失活,对碱性环境有一定的抵抗力;对氯仿和异戊醇不耐受。其基因组分析结果表明:噬菌体基因组大小为41950bp,GC含量为35.42%,预测有65个开放阅读框(Open Reading Frame,ORF)。进化分析表明,噬菌体vB_SauS_SAP3属于长尾科噬菌体,是一种新型的噬菌体。【结论】噬菌体vB_SauS_SAP3是一株窄谱的能够耐受一定温度和碱性环境的长尾科新型噬菌体,对其研究可为金黄色葡萄球菌噬菌体的研究提供理论材料。     

卤鸡腿中大肠杆菌生长模型的研究

为探讨食源性大肠杆菌的生长特性,建立即食食品卤鸡腿中大肠杆菌生长模型,在20℃、25℃、30℃、35℃和40℃等不同温度下测定了大肠杆菌的生长状态。采用修正的Gompertz 方程拟合大肠杆菌的生长曲线,分析了大肠杆菌的生长参数。结果表明,修正的Gompertz函数能够很好地描述大肠杆菌在20 ℃、25 ℃、30 ℃、35 ℃和40℃贮藏条件下的生长动态（R2＞0.933 6)。应用平方根模型描述了温度对最大比生长速率(μm）和延滞时间(λ)参数的影响,结果表明,温度与最大比生长速率呈现较好的线性关系。此外,应用20 ℃、25℃、30 ℃、35 ℃和40℃条件下实际测得的数值与预测模型数据进行比较,验证了恒定温度下模型的有效性。所建立的预测模型能有效地预测大肠杆菌在卤鸡腿中的生长动态,为控制即食食品中大肠杆菌污染提供理论依据。     

高通量快速测定致病性及非致病性副溶血性弧菌最大比生长速率

【目的】比较15 °C、20 °C和25 °C时, 9株不同致病性与非致病性副溶血性弧菌菌株在TSB (3% NaCl, pH 8.0)中的最大比生长速率之间的差异。【方法】应用Bioscreen C全自动微生物生长曲线分析仪测定副溶血性弧菌的最大比生长速率。【结果】15 °C、 20 °C和25 °C时, 9株副溶血性弧菌菌株间最大比生长速率的变异系数分别为20.72%、17.5%和15.98%。不同副溶血性弧菌最大比生长速率之间的差异随着温度的降低而增加。【结论】在进行定量微生物风险评估时, 应用仅基于一株菌建立的生长预测模型会给预测结果带来较大的不确定性。需建立可描述不同副溶血性弧菌菌株的最大比生长速率的随机模型来为定量微生物风险评估提供更准确有效的预测模型。     

功能作图(functional mapping)分析大肠杆菌和金黄色葡萄球菌之间的竞争互作

【背景】功能作图(functionalmapping)模型是基于统计方法的分析生物体动态复杂性状发育的全基因组作图方法,旨在定位性状发育过程中的数量性状位点(quantitative trait loci, QTL),将功能作图应用于微生物研究有助于解析复杂的互作过程。【目的】利用功能作图定位两种微生物在动态生长发育过程中发挥显著作用的QTL,通过基因功能注释找到影响微生物表型生长的基因。【方法】将大肠杆菌和金黄色葡萄球菌各100个菌株单独培养和一一配对共同培养,将取得的各菌株生长丰度表型数据和单核苷酸多态性(singlenucleotidepolymorphism,SNP)数据进行关联分析,找到同一物种在不同培养条件下对生长起作用的显著QTL。【结果】通过功能作图分析,在大肠杆菌中定位到217个QTL,金黄色葡萄球菌中定位到152个QTL;通过功能聚类和基因注释分析发现,QTL所在候选基因中金黄色葡萄球菌scdA、sdrC、sdrD、ftsA和大肠杆菌phr、nagC、eptA、ppsA、priA、flim基因对微生物的生长发挥了较大作用。【结论】本文借助功能作图定位了大肠杆菌和金黄...     

Modeling surface growth of Escherichia coli on agar plates

Surface growth of Escherichia coli cells on a membrane filter placed on a nutrient agar plate under various conditions was studied with a mathematical model. The surface growth of bacterial cells showed a sigmoidal curve with time on a semilogarithmic plot. To describe it, a new logistic model that we presented earlier (H. Fujikawa et al., Food Microbiol. 21:501-509, 2004) was modified. Growth curves at various constant temperatures (10 to 34 degrees C) were successfully described with the modified model (model III). Model III gave better predictions of the rate constant of growth and the lag period than a modified Gompertz model and the Baranyi model. Using the parameter values of model III at the constant temperatures, surface growth at various temperatures was successfully predicted. Surface growth curves at various initial cell numbers were also sigmoidal and converged to the same maximum cell numbers at the stationary phase. Surface growth curves at various nutrient levels were also sigmoidal. The maximum cell number and the rate of growth were lower as the nutrient level decreased. The surface growth curve was the same as that in a liquid, except for the large curvature at the deceleration period. These curves were also well described with model III. The pattern of increase in the ATP content of cells grown on a surface was sigmoidal, similar to that for cell growth. We discovered several characteristics of the surface growth of bacterial cells under various growth conditions and examined the applicability of our model to describe these growth curves.     

Modeling Surface Growth of Escherichia coli on Agar Plates

Surface growth of Escherichia coli cells on a membrane filter placed on a nutrient agar plate under various conditions was studied with a mathematical model. The surface growth of bacterial cells showed a sigmoidal curve with time on a semilogarithmic plot. To describe it, a new logistic model that we presented earlier (H.Fujikawa et al., Food Microbiol. 21:501-509, 2004) was modified. Growth curves at various constant temperatures (10 to 34°C) were successfully described with the modified model (model III). Model III gave better predictions of the rate constant of growth and the lag period than a modified Gompertz model and the Baranyi model. Using the parameter values of model III at the constant temperatures, surface growth at various temperatures was successfully predicted. Surface growth curves at various initial cell numbers were also sigmoidal and converged to the same maximum cell numbers at the stationary phase. Surface growth curves at various nutrient levels were also sigmoidal. The maximum cell number and the rate of growth were lower as the nutrient level decreased. The surface growth curve was the same as that in a liquid, except for the large curvature at the deceleration period. These curves were also well described with model III. The pattern of increase in the ATP content of cells grown on a surface was sigmoidal, similar to that for cell growth. We discovered several characteristics of the surface growth of bacterial cells under various growth conditions and examined the applicability of our model to describe these growth curves.     

Determination of the shelf life of sliced cooked ham based on the growth of lactic acid bacteria in different steps of the chain

Aims: Development of a predictive model for the determination of the shelf life of modified atmosphere‐packed (MAP) cooked sliced ham in each step of the cold chain. Methods and Results: The growth of lactic acid bacteria (LAB), as well as the development of the total viable count and changes of sensory and pH value parameters in MAP cooked sliced ham, stored under different constant temperature conditions from 2 to 15°C was investigated. As a result of the measurements, the end of the shelf life could be considered as the time when LAB reach more than 7 log₁₀ CFU g^?1. Different primary and secondary models were tested and analysed to find the best way to calculate the shelf life. For primary modelling, the modified Gompertz Function and the modified Logistic Function were compared. There was no substantial difference between either model. The effect of temperature on the growth rate was modelled by using the Arrhenius and the Square root model, whereas the Arrhenius equation gave a better result. A combination of the primary and secondary model was used for shelf‐life prediction under dynamic conditions. This combination showed the best prediction of microbial counts using the modified Logistic model and the Arrhenius equation. Conclusions: With the developed model, it is possible to predict the shelf life of MAP cooked sliced ham based on the growth of LAB under different temperature conditions. Significance and Impact of the Study: The developed model can be used to calculate the remaining shelf life in different steps of the chain. Thus, it can deliver an important contribution to improve food quality by optimizing the storage management.     

Modelling and predicting the effect of temperature,water activity and pH on growth of Streptococcus iniae in Tilapia

Aims: To evaluate and model the growth of Streptococcus iniae affect by temperatures (10–45°C), water activity (A_w; 0·995–0·957), and pH (5–8). Methods and Results: Temperatures, A_w, and pH were adjusted. The behaviour of S. iniae was studied and modelled. Growth curves were fitted by using logistic, Gompertz, and Baranyi models. The maximum growth rates obtained from the primary model were then modelled as a function of temperature, A_w, and pH using the Belehradek‐type models for secondary model. The optimum values for growth were found to be in the range of 35–40°C, A_w 0.995–1, and pH 6–7. The statistical characteristics of the models were validated by r², mean square error, bias, and accuracy factors. The results of validation indicated that Baranyi model performed the best. Conclusions: The effect of temperature, A_w/NaCl, pH control of S. iniae in tilapia could be satisfactorily predicted under current experimental conditions, and the proposed models could serve as a tool for this purpose. Significance and Impact of the Study: The suggested predictive model can be used for risk assessment concerning S. iniae in tilapia.     

Optimization of the cell seeding density and modeling of cell growth and metabolism using the modified Gompertz model for microencapsulated animal cell culture

Cell microencapsulation is one of the promising strategies for the in vitro production of proteins or in vivo delivery of therapeutic products. In order to design and fabricate the optimized microencapsulated cell system, the Gompertz model was applied and modified to describe the growth and metabolism of microencapsulated cell, including substrate consumption and product formation. The Gompertz model successfully described the cell growth kinetics and the modified Gompertz models fitted the substrate consumption and product formation well. It was demonstrated that the optimal initial cell seeding density was about 4-5 x 10(6) cells/mL of microcapsule, in terms of the maximum specific growth rate, the glucose consumption potential and the product formation potential calculated by the Gompertz and modified Gompertz models. Modeling of cell growth and metabolism in microcapsules provides a guideline for optimizing the culture of microencapsulated cells.     

一株苯酚降解菌的鉴定及其降解特性

【目的】鉴定从某化工厂附近土样中分离到的一株耐高浓度苯酚的菌株T10,通过优化菌株的培养条件提高菌株对苯酚的降解率。【方法】根据菌株的形态、生理生化鉴定及16S rDNA测序分析确定其种属,以液体摇瓶培养菌株T10对苯酚的降解率为指标,对菌株的生长条件进行优化。【结果】菌株T10属恶臭假单胞菌(Pseudomonas putida)。添加葡萄糖、蛋白胨能有效缩短T10菌的生长周期,并使苯酚的降解率提高1.7倍。在菌体初始接种浓度为10%、温度为30°C、转速为180 r/min条件下,对初始苯酚浓度、pH和装液量的响应面优化结果如下:初始苯酚浓度3 000 mg/L、pH 7.5和装液量80 mL/250 mL,苯酚去除率最高可达到87.56%。【结论】T10菌能够耐受较高浓度的含酚废水,并且对苯酚有较强的降解能力,为下一步利用生物法处理含酚废水提供科学依据。     

Behaviour of Listeria monocytogenes under combined chilling processes

The behaviour of Listeria monocytogenes under chilling processes was investigated. Growth kinetics were measured at 7 degrees C in TSBYE culture medium as a function of pH (7.2 and 6.2), pre-incubation temperatures (4 or 7 degrees C), cooling (0.05 or 0.1 degree C min-1) and freezing (0 and -5 degrees C) treatments. Growth curves generated were fitted by Gompertz and Baranyi functions. The Baranyi function gave better parameter estimation values than the Gompertz equation which over-estimated the specific growth rate values. Listeria monocytogenes grew at 7 degrees C without a lag phase, except when the sub-culture was performed at 37 degrees C, whereas the specific growth rate was affected by the chilling processes. In fact, L. monocytogenes grew slightly faster at 7 degrees C when a 4 degrees C pre-incubation treatment was applied than with a 7 degrees C pre-incubation treatment. These results suggest that to mimic the processes of contamination in industry, predictive microbiology studies with L. monocytogenes should be performed with organisms cultured at low temperatures.     

Conditions affecting growth and enterotoxin production by Staphylococcus aureus on temperature-abused chicken meat

Growth of Staphylococcus aureus at 15°C, with and without addition of representative spoilage bacteria, was studied in cooked, whole chicken meat and chicken broth. In the absence of competitors, the organism grew better in broth culture than on whole meat, but multiplied more slowly in broth when other organisms were present, even from twice the previous level of inoculum. The presence of competitors had no marked effect on the growth of Staph. aureus on whole meat. Enterotoxin A was not produced at 15°C on either whole meat or in broth, and occurred at 20°C only in pure culture. At 30° and 37°C, toxin was produced whether or not competitors were present. Toxin production by Staph. aureus appeared to be influenced more by growth temperature than by bacterial competition.