針對細菌引起之食媒性(foodborne)疾病爆發的探討與監控需要使用分子分型(molecular subtyping)方法達到，在本研究中將利用全基因體序列建立泛基因體等位基因資料庫，並利用多位點基因座序列分型(multilocus sequence typing, MLST)針對泛基因體序列進行分析，利用圖型化的方式建立同一種細菌不同菌株間的基因親緣關係樹狀圖，並標示出疾病爆發的菌株群集。利用此分子分型方法的輸出將能夠於不同實驗室間進行比較與應用。利用全基因體(whole-genome)序列做為多位點基因座序列分型之資料來源更能代表細菌資料的完整性，但其數量龐大之基因座資料集將會造成分型過程耗時，在本研究中將利用Python程式腳本與特徵選擇(feature selection)方法：變異量數閾值(variance threshold)、特徵重要性(feature importance)針對原始泛基因體序列進行無用或對於疾病爆發相關性低之基因座（特徵）的移除，挑選出最精簡與準確性高的基因特徵框架(scheme)做為細菌分子分型的輸入，期望以此精簡化之基因框架獲得與原始資料集相同分子分型結果，改善現有技術之缺點，在將來也能應用於針對細菌抗生素抗藥性之水平基因轉移(horizontal gene transfer, HGT)相關研究。本研究開發了一wgMLST-BacCompare網頁工具(http://bactyper.imst.nsysu.edu.tw)，並測試四種不同細菌：空腸彎曲桿菌(Campylobacter jejuni)、大腸桿菌(Escherichia coli)、李斯特菌(Listeria monocytogenes)、腸道沙門氏菌(Salmonella enterica)，並將其結果與現有之細菌基因基準資料集(benchmark dataset)進行比較，驗證此工具準確性與穩定性。在本研究結果中可以看到利用特徵選擇方法篩選出來的極少量基因座資訊便可以達成良好的分型效果，改善了舊有分型方法的效率及保持其準確性。我們相信wgMLST-BacCompare工具將有助於流行病學領域之研究發展。

To investigate and surveillance the foodborne disease outbreak caused by bacteria, molecular sequence subtyping method would be employed. In our study, we build an open-access website platform wgMLST-BacCompare for molecular subtyping which utilize multilocus sequence typing (MLST) approach with whole genome sequence data. We construct visualized genetic relatedness trees of the uploaded isolates and indicate disease outbreak subgroup. In general, utilize pan-genome sequences as the multilocus sequence typing process data resource can make the result of analysis more complete and exhaustive. But the pan-genome sequence lead to the enlargement of dataset and subtyping time-consuming. In this study, we make use of Python script and feature selection methods: variance threshold and feature importance. These methods are exploited to remove useless or low influence features (gene loci) for investigating disease outbreak from raw whole-genome sequence. We would take advantage of wgMLST-BacCompare website service (http://bactyper.imst.nsysu.edu.tw) testing four species of bacterial: Campylobacter jejuni, Escherichia coli, Listeria monocytogenes, and Salmonella enterica. And compare the results with existing bacterial gene benchmark dataset, identifying the accuracy and robustness of the web tool. We can achieve well subtyping results by small amount of gene locus information which filtered by feature selection methods. Besides the improvement of efficiency, we can still maintain the accuracy. And we believe that the wgMLST-BacCompare will be a useful online tool for epidemiology studies.

論文審定書 i
摘要 ii
Abstract iii
目錄 v
圖次 vii
表次 ix
第一章 緒論 1
1.1 研究動機與背景 1
1.1.1 病原細菌(Pathogenic bacteria) 1
1.1.2 分子分型(Molecular subtyping) 2
1.1.3 特徵選擇(Feature selection) 4
1.1.4 研究目的 5
第二章 實驗方法 6
2.1 實驗架構 6
2.1.1 預設分析 7
2.1.1.1 基因體片段重疊群註解(Genome contigs annotation) 7
2.1.1.2 建立全基因體等位基因資料庫(Pan-genome allele database, PGAdb) 8
2.1.1.3 建立親緣關係樹狀圖(Genetic relatedness tree) 9
2.1.1.4 特徵選擇方法篩選原始資料集 12
2.1.1.5 特徵選擇：變異量數閾值(Variance threshold) 12
2.1.2 進階分析 13
2.1.2.1 特徵選擇：特徵重要性(Feature importance) 13
第三章 結果與討論 17
3.1 泛基因體等位基因資料庫與特徵選擇演算法目標 17
3.2 網頁服務架設 17
3.3 網頁服務使用介紹 17
3.3.1 輸入格式 17
3.3.2 輸出格式：Build_PGAdb (Default analysis) 18
3.3.3 輸出格式：Locus_refinement (Advanced analysis) 19
3.4 網頁服務測試 20
3.4.1 利用空腸彎曲桿菌(Campylobacter jejuni)為測試細菌菌種 20
3.4.2 利用大腸桿菌(Escherichia coli, E. coli)為測試細菌菌種 24
3.4.3 利用李斯特菌(Listeria monocytogenes)為測試細菌菌種 28
3.4.4 利用腸道沙門氏菌(Salmonella enterica)為測試細菌菌種 32
3.4.5 利用鼠傷寒沙門氏菌(Salmonella typhimurium)為測試細菌菌種 36
3.4.6 特徵選擇策略 40
第四章 結論與未來展望 41
4.1 結論 41
4.2 未來展望 42
參考文獻 43

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