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  1. NTU Theses and Dissertations Repository
  2. 公共衛生學院
  3. 食品安全與健康研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90452
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dc.contributor.advisor盧冠宏zh_TW
dc.contributor.advisorKuan-Hung Luen
dc.contributor.author吳柳豔zh_TW
dc.contributor.authorLiu-Yean Gohen
dc.date.accessioned2023-10-03T16:08:24Z-
dc.date.available2025-08-31-
dc.date.copyright2023-10-03-
dc.date.issued2023-
dc.date.submitted2023-08-09-
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90452-
dc.description.abstract泌尿道致病性大腸桿菌 (UPEC) 是一種新興的食源性病原菌,是導致泌尿道感染 (UTIs)的主要原因,約占感染的65-75%。未經滅菌或其他加熱處理的新鮮果汁 (像是甘蔗汁) 容易受到微生物的污染,其中可能包括UPEC。越來越多的證據指出,家禽和肉類產品是UPEC的主要食物貯存庫 (food reservoir),因此近期有關UPEC在食品上的研究,多半著重在家禽和肉類產品中的生長。然而,有關於UPEC是否存在於臺灣市售新鮮製備的果汁,以及其於果汁中的生長行為,仍然知之甚少。本研究的目的為 (1) 瞭解臺灣市售新鮮製備果汁中UPEC之盛行率,(2) 針對UPEC盛行率較高的果汁 (甘蔗汁),透過建立預測模型瞭解UPEC在甘蔗汁中的生長行為,藉此降低透過攝食這類新鮮果汁所可能造成的食源性泌尿道感染之風險。
本研究自臺北市之夜市、路邊攤、手搖飲料店和百貨公司的美食街,收集了51件新鮮現榨果汁進行微生物檢驗,分別檢驗果汁樣本中的生菌數、大腸桿菌群及大腸桿菌。從樣品中單離出之大腸桿菌菌落,透過聚合酶連鎖反應 (PCR) 確認其UPEC特異性基因 (c3509、c3686和chuA) 的存在;而確認為UPEC之菌株者,再進一步檢測其攜帶之毒力基因並鑑定其演化型,以瞭解其潛在之致病力。研究結果顯示,在51個果汁樣本中有10個 (19.6%) 檢測到大腸桿菌,平均菌量為1.60 ± 0.51 log CFU/mL,其中又有6個 (11.8%) 被帶有UPEC特異性基因。UPEC之盛行率以甘蔗汁為最高 (4/12,33.3%),其次是蘋果汁 (1/13,7.7%) 和西瓜汁(1/13,7.7%)。而自果汁中總共單離出47株大腸桿菌,其中24株 (24/47,51.1%) 確認為UPEC。此24株UPEC分離株以演化型B2為主 (11/24,45.8%),其次是演化型A (5/24,20.8%) 和演化型B1 (5/24,20.8%)。其攜帶之毒力基因的比例則以fimH (15/24,62.5%) 為最高,其次依序為ompT (14/24,58.3%)、PAI IV536 (13/25,54.2%) 和sfaS (12/24,50.0%)。
由於UPEC在甘蔗汁中的盛行率為市售鮮榨果汁中最高,故接著以甘蔗汁作為接種之食品基質,建立UPEC之生長曲線。甘蔗汁樣品在稀釋和不稀釋的情況下都接種了4株UPEC 混合菌株,並在4、10、20、30、35和40℃恆溫培養下觀察UPEC之生長變化。透過以Huang model、Baranyi model和reparameterized model進行曲線擬合,得到UPEC的生長動力模型,以確定其最大生長速率 (μmax)、遲滯時間 (λ) 和最大菌量 (ymax)。再以Huang square-root model和Ratkowsky square-root model來描述溫度對μmax的影響,並採用線性回歸模型來描述溫度對λ的影響,以統計參數評估各模型的擬合結果
結果顯示,在稀釋與未稀釋甘蔗汁中,所有溫度下都觀察到UPEC的生長,除了4℃以及10℃。除此之外,各溫度 (20、30、35和40℃) 下兩種類型的甘蔗汁皆以reparameterized Gompertz model的擬合程度較佳,且相較於甘蔗原汁,UPEC於稀釋後的甘蔗汁之μmax顯著高於甘蔗原汁,遲滯時間也比甘蔗原汁的短。UPEC於甘蔗汁的生長情形,適合使用reparameterized Gompertz model和Huang square-root model去描述溫度對其μmax之影響。以Baranyi model結合Huang square-root model則適用於描述UPEC於稀釋甘蔗的生長情形。模型評估結果顯示,其bias factor (Bf)與accuracy factor (Af )於甘蔗汁為1.00和1.02;於稀釋甘蔗汁之Bf與Af分別為1.00及1.01。因此,所建立的二級模型皆適合用於描述UPEC之生長。
為確認建立於恆溫條件下的模型預測能力,以4℃與37℃之間的非等溫溫度下進行額外的獨立實驗。得出的結果顯示,從等溫條件下建立之模型參數能夠適當地預測UPEC在4至40℃溫度範圍內之甘蔗汁 (RMSE, 0.99 log CFU/mL; Bf, 0.91; Af, 1.11) 和稀釋甘蔗汁 (RMSE, 0.78 log CFU/mL; Bf, 0.94; Af, 1.07) 的非等溫條件下UPEC生長情況。
綜合上述研究結果, UPEC在稀釋後的甘蔗汁生長較快速,可能使得這類新鮮製備的飲料成為微生物風險較高的食品,亦具有較高的食源性泌尿道感染的風險。透過建立的預測模型瞭解到儲藏溫度對μmax和λ的影響,可以預測UPEC在兩種類型果汁的儲存和製備過程中的生長情況,因此可以為消費者和飲料製備業者,對甘蔗汁和其他類似果汁的微生物安全控制提供科學依據。
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dc.description.abstractUropathogenic Escherichia coli (UPEC) is an emerging foodborne pathogen, and are the major cause of urinary tract infections (UTIs), which responsible for approximately 65-75% of the infections. Freshly prepared fruit juices (e.g., sugarcane juice) without sterilized processes or other heat treatment are vulnerable to microbial contamination, including UPEC. A growing body of evidence indicates that poultry and meat products serve as a main food reservoir for UPEC. Therefore, many recent studies related to UPEC have focused on the growth of UPEC in poultry and meat products. However, the presence of UPEC among the freshly prepared fruit juice vended in Taiwan and the growth behavior of UPEC in freshly prepared fruit juices are still poorly understood. The present study aimed (1) to determine the prevalence of UPEC among the freshly prepared fruit juice and (2) to assess the growth behavior of UPEC in the sugarcane juice via predictive modeling, which can be applied to reducing the risk of foodborne UTI.
A total of 51 freshly prepared fruit juice were collected from the night market, roadside vendors, hand-shaken beverage shops, and food court located in Taipei for microbial sampling test. The aerobic bacteria, coliform, and E. coli were enumerated; the suspected E. coli colonies were isolated. For UPEC identification, the presence of UPEC-specific genes (c3509, c3686, and chuA) was determined via polymerase chain reaction (PCR). Isolates identified as UPEC were further screened for virulence and phylogenetic genes to reveal their uropathogenic potential. The result of present study showed that E. coli was detected in 10 out of 51 (19.6%) samples at an average level of 1.60 ± 0.51 log CFU/mL, while 6 out of 51 (11.8%) samples were found to contain UPEC. A high prevalence of UPEC (4/12, 33.3%) was found in sugarcane juice, followed by apple juice (1/13, 7.7%) and watermelon juice (1/13, 7.7%). A total of 47 E. coli isolated from freshly prepared fruit juice, 24 (51.1%) of the E. coli were identified as UPEC. In UPEC isolates, phylogenetic group B2 was predominant (11/24, 45.8%), followed by group A (5/24, 20.8%), and B1 (5/24, 20.8%). The most frequently detected virulence genes were fimH (15/24, 62.5%), ompT (14/24, 58.3%), PAI IV536 (13/25, 54.2%), and sfaS (12/24, 50.0%).
Based on the prevalence of UPEC among commercially available freshly prepared fruit juices, sugarcane juice was chosen as the food matrix for this study. Sugarcane juice samples with and without dilution were inoculated with a four-strain cocktail of UPEC, and bacterial growth was evaluated under storage at 4, 10, 20, 30, 35, and 40°C. The growth kinetic of UPEC were obtained by curve-fitting to the Huang model, Baranyi model, and reparameterized Gompertz model to determine the specific growth rate (μmax), lag-phase duration (λ), and maximum population density (ymax ). The effect of temperature on μmax was decribed by using Huang square-root and Ratkowsky square-root model, as well as a linear regression model was adopted to describe the effect of μmax on λ. By comparing the root mean square error (RMSE), Akaike information criterion (AIC), accuracy factor (Af) and bias factor (Bf) of each model, the model performance was determined.
No growth of UPEC was observed in both diluted and undiluted juice samples at storage temperatures 4 and 10°C. Moreover, the fitting results also demonstrated that the reparameterized Gompertz model was suitable as a primary model for simulating the growth of UPEC in sugarcane juice and diluted sugarcane juice under 20, 30, 35, and 40°C. Another finding is that the μmax of UPEC in diluted sugarcane juices was significantly higher than that in undiluted ones. In contrast, its λ in diluted sugarcane juices was notably shorter than that in undiluted. The combination of reparameterized Gompertz and Huang square-root model was more suitable than the other to describe the effect of temperature on μmax in the sugarcane juices. For UPEC growth in diluted sugarcane juice, the combination of Baranyi and Huang square-root model was more suitable. The bias factor (Bf) and accuracy factor (Af) of sugarcane juice were 1.00 and 1.02, respectively. While diluted sugarcane juice showed Bf and Af were 1.00 and 1.01, correspondingly. These results indicated that the secondary model could describe the growth of UPEC in sugarcane juice and diluted sugarcane juice with satisfaction.
Subsequently, the developed models were validated with additional independent experiments under non-isothermal temperatures between 4°C and 37°C for four-hour periods. The validation data showed that the model parameters obtained from isothermal growth data were acceptable for the estimation of the growth of UPEC under non-isothermal conditions in the temperature range assessed for sugarcane juice (RMSE, 0.99 log CFU/mL; Bf, 0.91; Af, 1.11) and diluted ones (RMSE, 0.78 log CFU/mL; Bf, 0.94; Af, 1.07).
Taken together, these data reveal that the ability of UPEC to grow faster in the diluted sugarcane juices could make this fresh beverage a potentially hazardous food with a higher risk of foodborne UTI. The developed models indicate the effects of growth temperatures on μmax and λ, which is an effective tool to predict the growth of UPEC in both juices during its storage and preparation, and therefore provide a theoretical basis for microbial safety control of sugarcane juice and other similar juice for consumer and beverage manufacturer.
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dc.description.tableofcontents口試委員審定書 I
誌謝 II
中文摘要 III
ABSTRACT V
CONTENTS IX
LIST OF ABBREVIATIONS XIII
LIST OF FIGURES XV
LIST OF TABLES XVII
CHAPTER 1 INTRODUCTION 1
CHAPTER 2 BACKGROUND AND LITERATURE REVIEW 5
2.1 Urinary tract infection (UTI): one of the most common infections worldwide 5
2.1.1 Introduction 5
2.1.2 Diagnosis and clinical symptom 5
2.1.3 UTI pathogens 6
2.1.4 Pathogenesis of UTI 7
2.2 Emerging of foodborne urinary tract infections (FUTI) 8
2.3 Uropathogenic Escherichia coli (UPEC) 10
2.3.1 Classification of E. coli 10
2.3.2 Identification method for UPEC 11
2.3.3 Phylogenetic group 13
2.3.4 Virulence factor 13
2.4 Freshly prepared fruit juice poses a greater microbial risk 16
2.4.1 Consumption of freshly prepared fruit juice 16
2.4.2 Foodborne illness and outbreaks associated with fruit juice consumption 17
2.4.3 Microbial contamination sources of fruit juice 17
2.5 Higher microbial risk for sugarcane juice 19
2.6 Predictive microbiology 20
2.6.1 Introduction 20
2.6.2 Type of model 21
2.6.3 Model validation and performances 24
2.6.4 Application 25
CHAPTER 3 MATERIALS AND METHODS 26
3.1 Experimental design 26
3.2 Sampling of fresh fruit juices 26
3.2.1 Sample collection 26
3.2.2 Microbiological analysis 27
3.2.3 Physicochemical analysis 28
3.2.4 Isolation and DNA extraction 28
3.2.5 UPEC confirmation by PCR 29
3.2.6 Phylogroup classification and virulence factors determination 30
3.3 Growth/ no growth experiment 31
3.3.1 Sample preparation 31
3.3.2 Adjustment of pH and measurement of total soluble solid (TSS) 31
3.3.3 Bacterial strains and inoculum preparation 32
3.3.4 Inoculation and storage conditions 33
3.3.5 Enumeration of bacterial growth 34
3.4 Growth model of UPEC in sugarcane juice 34
3.4.1 Preparation of sugarcane juice and diluted sugarcane juice 34
3.4.2 Measurement of pH, total soluble solid (TSS), and color of juice 35
3.4.3 Bacterial strains and inoculum preparation 35
3.4.4 Inoculation and storage conditions 36
3.4.5 Enumeration of UPEC 37
3.4.6 Primary model 37
3.4.7 Secondary model 39
3.4.8 Model evaluation 40
3.4.9 Model validation 42
3.5 Statistical analyses 43
CHAPTER 4 RESULTS AND DISCUSSION 44
4.1 Food sampling for identification of UPEC prevalence in freshly prepared fruit juice 44
4.1.1 Physicochemical properties of freshly prepared fruit juice 44
4.1.2 Contamination level and occurrence of coliforms and total aerobic bacteria 45
4.1.3 Prevalence and contamination of E. coli in freshly prepared fruit juice 46
4.1.4 Prevalence of UPEC among various freshly prepared fruit juice 47
4.1.5 Identification of UPEC isolated from freshly prepared fruit juice 47
4.1.6 Phylogrouping of UPEC isolates from freshly prepared fruit juices 49
4.1.7 Distribution of virulence factor among the UPEC isolated from fruit juice 50
4.2 Determination of growth/ no growth limit of UPEC under the effect of temperature and pH 52
4.2.1 Growth probability of UPEC 52
4.2.2 Changes in UPEC bacterial counts 53
4.3 Modeling the growth of UPEC in sugarcane juice and diluted sugarcane juice 54
4.3.1 Microbial and physical properties of juice 54
4.3.2 Growth curves of UPEC and estimates of kinetic parameters 55
4.3.3 Development of secondary models 59
4.3.4 Model validation 60
CHAPTER 5 LIMITATIONS AND SUGGESTIONS 63
CHAPTER 6 CONCLUSION 66
FIGURES 69
TABLES 91
REFERENCES 116
APPENDIXES 138
-
dc.language.isoen-
dc.subject食品安全zh_TW
dc.subject預測微生物學zh_TW
dc.subject果汁zh_TW
dc.subject泌尿道致病性大腸桿菌zh_TW
dc.subject泌尿道感染zh_TW
dc.subject生長模型zh_TW
dc.subjecturopathogenic Escherichia colien
dc.subjectpredictive microbiologyen
dc.subjectgrowth modelsen
dc.subjectfood safetyen
dc.subjectfruit juiceen
dc.subjecturinary tract infectionsen
dc.title泌尿道致病性大腸桿菌於新鮮果汁之盛行率及其於甘蔗汁之生長預測模型zh_TW
dc.titlePrevalence of uropathogenic Escherichia coli in freshly prepared fruit juices and predictive models for the growth in sugarcane juiceen
dc.typeThesis-
dc.date.schoolyear111-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee張靜文;吳彰哲;張育傑zh_TW
dc.contributor.oralexamcommitteeChing-Wen Chang;Chang-Jer Wu;Yu-Jie Changen
dc.subject.keyword泌尿道致病性大腸桿菌,果汁,預測微生物學,生長模型,食品安全,泌尿道感染,zh_TW
dc.subject.keyworduropathogenic Escherichia coli,fruit juice,predictive microbiology,growth models,food safety,urinary tract infections,en
dc.relation.page138-
dc.identifier.doi10.6342/NTU202303573-
dc.rights.note未授權-
dc.date.accepted2023-08-09-
dc.contributor.author-college公共衛生學院-
dc.contributor.author-dept食品安全與健康研究所-
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