董庆利,王忻,苏亮,刘箐.基于不同初始接菌量的铜绿假单胞菌生长模型[J].农业机械学报,2015,46(12):246-252.
Dong Qingli,Wang Xin,Su Liang,Liu Qing.Modeling on Growth of Pseudomonas aeruginosa with Different Inoculum Sizes[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(12):246-252.
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基于不同初始接菌量的铜绿假单胞菌生长模型   [下载全文]
Modeling on Growth of Pseudomonas aeruginosa with Different Inoculum Sizes   [Download Pdf][in English]
  
DOI:10.6041/j.issn.1000-1298.2015.12.033
中文关键词:  铜绿假单胞菌  初始接菌量  生长模型  预测微生物学
基金项目:国家自然科学基金资助项目(31271896)、上海市科委重点支撑资助项目(13430502400)、上海市科委长三角科技联合攻关领域项目(15395810900)和国家食品安全风险评估中心2015年委托项目
作者单位
董庆利 上海理工大学 
王忻 上海理工大学 
苏亮 国家食品安全风险评估中心 
刘箐 上海理工大学 
中文摘要:基于单细胞生长流动成像系统,探究铜绿假单胞菌单细胞生长规律,并运用随机建模方法建立单细胞与群体细胞生长之间的关系,获得不同初始接菌量下铜绿假单胞菌生长迟滞时间以及最大生长速率的分布,通过代入Baranyi模型修改式,结合单细胞水平建模(Individual-based modeling,IbM)的方法,对不同初始接菌量下铜绿假单胞菌的随机生长过程进行模拟。结果表明,随着初始接菌量的增大,铜绿假单胞菌生长迟滞期减小,25℃下平均迟滞时间由2.91 h减小至2.55 h,变异系数由29.90%减小至2.96%,35℃下平均迟滞时间由1.49 h减小至0.99 h,变异系数由22.53% 减小至4.64%。最大生长速率随不同初始接菌量变化不明显,其主要受温度的影响,由25℃下约0.70 lnCFU/h增加至35℃下约1.00 lnCFU/h,变异系数变化无明显规律。通过IbM模拟群体细胞生长发现,虽然单细胞的生长具有随机性,但随着初始接菌量的增大,微生物群体细胞生长的变异性逐渐降低,最终呈现出决定性生长的状态。相较于传统采用确定性模型进行的微生物生长建模,单细胞水平的生长动力学研究可为食品安全风险评估以及风险决策者提供更加准确与直观的风险指导。
Dong Qingli  Wang Xin  Su Liang  Liu Qing
University of Shanghai for Science and Technology,University of Shanghai for Science and Technology,China National Center for Food Safety Risk Assessment and University of Shanghai for Science and Technology
Key Words:Pseudomonas aeruginosa  Inoculum size  Growth model  Predictive microbiology
Abstract:A single cell growth image system was used to study the growth of Pseudomonas aeruginosa single cells. A stochastic modeling process was applied to connect the growth of P. aeruginosa single cells and cell populations, which made it possible to simulate the growth of P. aeruginosa . The lag time and specific growth rate distributions with different inoculum sizes were obtained as a result of the simulation’s repetitive executions which were further introduced into the reduced Baranyi model for establishing an individual-based model. Then a stochastic growth process of P. aeruginosa was conducted by using Monte Carlo simulation. Results showed that a negative relationship existed between lag time and inoculum size. As the inoculum size increased from 1 cell to 100 cells, the lag time decreased from 2.91 h to 2.55 h at 25℃ and from 1.49 h to 0.99 h at 35℃. The coefficient of variation decreased from 29.90% to 2.96% at 25℃ and from 22.53% to 4.64% at 35℃. The specific growth rate was more affective to the temperature changes which increased from 0.70 lnCFU/h at 25℃ to 1.00 lnCFU/h at 35℃. Meanwhile, the stochastic growth of P. aeruginosa with different inoculum sizes demonstrated that the growth of P. aeruginosa showed a determinate tendency as inoculum sizes increasing, in spite of the stochastic growth property of bacterial single cells. Compared with the traditional determinate predictive modelling, studying bacterial population growth from stochastic single cell dynamics opened the door for applications in risk assessment and prediction of shelf life.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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