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基于不同初始接菌量的銅綠假單胞菌生長模型
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國家自然科學基金資助項目(31271896),、上海市科委重點支撐資助項目(13430502400)、上海市科委長三角科技聯(lián)合攻關領域項目(15395810900)和國家食品安全風險評估中心2015年委托項目


Modeling on Growth of Pseudomonas aeruginosa with Different Inoculum Sizes
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    基于單細胞生長流動成像系統(tǒng),,探究銅綠假單胞菌單細胞生長規(guī)律,,并運用隨機建模方法建立單細胞與群體細胞生長之間的關系,獲得不同初始接菌量下銅綠假單胞菌生長遲滯時間以及最大生長速率的分布,,通過代入Baranyi模型修改式,,結(jié)合單細胞水平建模(Individual-based modeling,IbM)的方法,,對不同初始接菌量下銅綠假單胞菌的隨機生長過程進行模擬,。結(jié)果表明,隨著初始接菌量的增大,,銅綠假單胞菌生長遲滯期減小,,25℃下平均遲滯時間由2.91 h減小至2.55 h,變異系數(shù)由29.90%減小至2.96%,,35℃下平均遲滯時間由1.49 h減小至0.99 h,,變異系數(shù)由22.53% 減小至4.64%。最大生長速率隨不同初始接菌量變化不明顯,,其主要受溫度的影響,,由25℃下約0.70 lnCFU/h增加至35℃下約1.00 lnCFU/h,,變異系數(shù)變化無明顯規(guī)律。通過IbM模擬群體細胞生長發(fā)現(xiàn),,雖然單細胞的生長具有隨機性,,但隨著初始接菌量的增大,微生物群體細胞生長的變異性逐漸降低,,最終呈現(xiàn)出決定性生長的狀態(tài),。相較于傳統(tǒng)采用確定性模型進行的微生物生長建模,單細胞水平的生長動力學研究可為食品安全風險評估以及風險決策者提供更加準確與直觀的風險指導,。

    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.

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董慶利,王忻,蘇亮,劉箐.基于不同初始接菌量的銅綠假單胞菌生長模型[J].農(nóng)業(yè)機械學報,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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  • 在線發(fā)布日期: 2015-12-10
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