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研究生: 方炫喻
Fang, Hsuan-Yu
論文名稱: 快速細菌檢測平台於監測益生菌產品製造程序之探討
Study on Rapid Bacterial Detection Platform for Monitoring the Manufacturing Process of Probiotic Products
指導教授: 張憲彰
Chang, Hsien-Chang
學位類別: 碩士
Master
系所名稱: 工學院 - 生物醫學工程學系
Department of BioMedical Engineering
論文出版年: 2021
畢業學年度: 109
語文別: 英文
論文頁數: 59
中文關鍵詞: 快速菌量計算 、益生菌 、電動力學
外文關鍵詞: Rapid bacterial counting, Probiotic, Electrokinetics
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  • 經與益生菌製造廠商的深入訪談與現場觀摩,得知現在益生菌產業中無論在繁忙的常規量產流程、發酵時間的決定,以及冷凍乾燥粉末成品的倉儲品管,其最迫切的需求就是一種快速且經濟的檢測方式。現行的益生菌計數方法是相對耗時的塗盤培養法(約需24~72小時),而益生菌批量生產的發酵周期通常在17小時內完成,顯示出目前耗時費力的檢測方式(塗盤培養法)確實不符合實際應用。在本研究中,我們開發了一個名為Bcount的快速細菌檢測平台,搭配活菌螢光染色技術嘗試來解決這個問題。檢測平台的核心技術是一種應用電動力學原理的環狀指叉型電極(RIDE)晶片,該晶片採用微影蝕刻技術製造,嵌入於三維CNC訂製的專用卡匣,藉以確保相同的單次檢測樣品體積,進而提升檢測批次間的一致性,達到快速量化益生菌樣品濃度的功能。我們使用電阻值為10 Ω/sq的ITO導電玻璃作為RIDE晶片的基板,其建議工作樣品溶液導電度為 <15 μS/cm,(1)當施加500 Hz 和15 VPP的交流電訊號時,可於3分鐘內將經過預處理的樣品中益生菌顆粒收集到電極的觀測中心區,(2)其次通過影像擷取並由軟體自動化計算菌粒總數,(3)最後對比已完成建置的檢量線,即可快速預估受測樣品中的益生菌濃度。Bcount平台的三大優勢包括樣品需求量小(僅160 μL/test)、檢測全程可在30分鐘內完成檢測,以及相對實惠的檢測成本。迄今我們也已完成超過30種來自益生菌產線上樣品的盲測試驗,其結果可驗證Bcount快速細菌檢測平台的適用性與穩定性。

    After in-depth interviews with probiotic manufacturers and several times of on-site observations, it was found out that in the probiotic industry, regardless of the routine mass production process, the determination of fermentation time, and the storage and quality assurance of freeze-dried powder products, the most urgent need is a fast and economical detection method. The current method for counting probiotics is the time-consuming method, the plate culture method (24-72 h). However, the fermentation cycle of probiotic mass production is usually completed within 17 h, showing that the current time-consuming and laborious detection method (plate culture method) does not meet the actual application. In this research, we have developed a rapid bacterial detection platform called "Bcount", which is combined with live bacterial fluorescent staining technology to try to solve this problem. The core technology of the detection platform is a ring-shaped interdigitated electrode (RIDE) chip that applies electrokinetic principles. The chip is manufactured by photolithography technology and embedded in a special clip that is customized by 3D CNC to ensure the same volume of the sample for a single test. It can improve the consistency of testing batches, and achieve the function of quickly quantifying the concentration of probiotic samples. We use ITO conductive glass with a resistance value of 10 Ω/sq as the substrate of the RIDE chip. The recommended conductivity of the working sample solution is less than 15 μS/cm. (1) Firstly, when an AC signal of 500 Hz and 15 VPP is applied, probiotic particles in the pretreated sample will be collected in the observation center area of the chip within 3 min. (2) Secondly, the total number of bacteria particles is automatically calculated by the software through image capture and analysis. (3) Finally, the particle counting result will be compared with the completed calibration curve and quickly estimate the probiotic concentration of the tested sample. There are three main advantages of the Bcount platform, the small sample requirements (only 160 μL/test), the fast detection process which can be entirely completed within 30 min, and the affordable detection costs. So far, we have completed blind tests for more than 30 kinds of samples from the real probiotic production line, indicating the usability and stability of the Bcount rapid detection platform.

    Abstract I 中文摘要 II 誌謝 III Contents IV List of Figures VII List of Tables X Chapter 1 Introduction 1 1.1 Background 1 1.1.1 Probiotic Industry 1 1.1.2 The Unmet Need of Probiotic Mass Production 2 1.2 Current Detection Products in Probiotic Industrial Use 2 1.2.1 Plate Culture Count 3 1.2.2 pH Value Detection Method 4 1.2.3 Flow Cytometry 4 1.3 Motivation and Aim 5 1.4 Experimental Framework 6 Chapter 2 Materials and Methods 7 2.1 Electrokinetics Theory 7 2.1.1 Dielectrophoresis 7 2.1.2 Electrical Double Layer 9 2.1.3 Electroosmosis 11 2.1.4 AC Electroosmosis 13 2.2 RIDE Chips Pattern Design 15 2.3 RIDE Chips Quality Control 17 2.4 The Establishment of Detection SOP 20 2.4.1 Sample Pretreatment 20 2.4.2 Plate Culture Count 21 2.4.3 RIDE Count 21 2.5 Image Analysis 22 2.5.1 Grayscale (Binary) Images 22 2.5.2 Label Image 23 2.6 Blind Test 24 2.6.1 Steps of the Blind Test 24 2.6.2 List of Probiotic Species 26 Chapter 3 Results and Discussion 27 3.1 Quality Control of RIDE Chips 27 3.2 Effects of Sample Pretreatment Process 31 3.3 Calibration Curve 34 3.3.1 Light View Calibration Curve 40 3.4 Blind Test 45 3.4.1 Blind Test with Light View Mode 45 3.4.2 Blind Test with Fluorescent Mode 49 3.4.3 Lower Sample Concentration Predicted by Bcount Platform 50 Chapter 4 Conclusion and Prospects 53 References 55 Personal Information 59

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