世界上感染幽門桿菌(Helicobacter pylori, H. pylori)的盛行率超過了50%，更有研究指出H. pylori的感染與十二指腸潰瘍(duodenal ulcer, DU)與胃癌(gastric cancer, GC)的發生有高度的相關性，驅使世界衛生組織把H. pylori歸類為第一類致癌物質。其後，會造成DU與GC不同的病理變化也繼之被認為是受H. pylori本身帶有不同致病因子所導致，於是如何快速且精確的檢測出H. pylori的種類，乃是能提供正確治療資訊，促進臨床治癒率的不二法門。傳統檢測中的尿素酶試驗法已可在4 hr內判斷H. pylori感染之有無，但未能進一步鑑定菌種是其缺憾。另一方面，目前以PCR法固然可用來鑑定H. pylori菌種，然需細菌培養、DNA抽出等繁瑣耗時步驟始能為功。基於此，本研究嘗試以介電泳檢測技術捕捉H. pylori，再導入拉曼光譜法，以全細胞、非破壞方式來分析鑑定。
本研究共分為細菌的微晶片捕捉與Raman光譜鑑定分析兩部份：(1)藉由微機電製程技術設計、製作出擁有上下電極接合和圓洞電極陣列分佈，以及提供高捕捉率的微型立體式介電泳(DEP)晶片。在20 mM PBS溶液中，設定20 Vp-p頻率300 kHz的交流電訊號，可令H. pylori被所呈現的負介電泳力捕捉。(2)以Raman光譜儀分析H. pylori所呈現的光譜訊號，結果發現H. pylori經babA2基因剔除者與其野生型者(wild type)，在1002-1003 cm-1、1200-1400 cm-1與1500-1700 cm-1三個區段，呈現很明顯的差異。基於實際的樣本可能會混雜其它致病菌，將影響Raman圖譜之辨識，為此我們也建立了S. aureus、E. faecium、H. pylori和E. coli的拉曼光譜資料庫，並以主成分分析法(PCA)及聚類分析法(HCA)幫助複雜圖譜的區分歸類。此舉有利於我們進行11個GC與9個DU病患檢體培養出的H. pylori的拉曼光譜之辨識，特別是發現在1365-1373 cm-1的這一頻段中，H. pylori光譜出現明顯訊號的GC病患樣本佔了82.2%，而DU病患的則僅佔22.2%，應可作為其間差異的判斷指標。另外，我們也嘗試了被認為是BabA蛋白成份光譜區段中的1200-1250 cm-1，以HCA方式將20個H. pylori光譜群分化，得到在GC群中有8個GC但夾含2個DU，然在DU群中有7個DU但也出現了3個GC之初步結果。基於以上技術建立，我們也嘗試於DEP晶片上將H. pylori #238捕捉後，直接擷取其Raman光譜，然玻璃基材的高螢光背景值，導致H. pylori的訊號極為薄弱，尚難達能辨識的程度。
本項技術研發，若再能配合晶片系統的改良，並再有多數的臨床檢體樣本來充實資料庫，相信未來可提供檢體是否帶有H. pylori快速辨識之外，更可同時鑑定其是否為會導致GC抑或DU。

Helicobacter pylori, H. pylori's global prevailance rate is over fifty percent .patients with duodenal ulcer, DU or gastric cancers, GC are highly related to H. pylori infection. The WHO classifies H. pylori as the first part of carcinogen. Recent findings discover that different sickening factors result in different pathological presentation. The exact and quick classification of H. pylori can provide the doctors with accurate information to apply appropriate treatment.Conventional methods could provide H. pylori infection result in 4 hr. However, it can not further identify the species.Nonetheless, the procedures are relatively time-consuming. It is often weeks before accurate results can be obtained. In this research, a dielectrophoretic (DEP) technique has been applied to trapping H. pylori. And then we go to Raman spectroscopy, Raman spectrum’s scattering mechanism can be used to analyze molecular structure of bacteria and be applied to identification of H. pylori species.
This study has two parts; (1) we use MEMS Fabrication to make the 3D chip which was constructed by two electrode chips with one at the top, the other at the bottom and a fluidic channel sandwiched between to avoid electric field attenuation. The electrode design of circular holes array can increase trapping efficiency. In the 20 mM PBS solution at 20 Vp-p and 300 kHz, H. pylori were trapped successfully by nDEP force. (2) We use Raman spectroscopy to set up H. pylori Raman spectra. BabA protein expression can be identified by 1002-1003 cm-1、1200-1400 cm-1 and 1500-1700 cm-1 Raman shift of H. pylori Raman spectra. For practical conditions, real samples usually contain not only one kind of bacteria species. So that, we set up S. aureus, E. faecium, H. pylori and E. coli Raman spectra and use PCA and HCA methods to execute classification of bacteria. And then, we also establish 11GC and 9DU H. pylori Raman spectra successfully. According to qualitative analysis results, in 1365-1373 cm-1, H. pylori Raman spectra of GC patient and DU patient accounts for 82.2% and 22.2% respectively. On the side, we choose 1200-1250 cm-1 Raman shift (BabA protein part Raman shift ) of 20 H. pylori Raman spectra to execute HCA. The 20 H. pylori Raman spectra can be categorized in two groups. One group has eight GC and two DU. Another group has seven DU and three GC. At last, we combine Raman scattering technique with DEP chip for identification of H. pylori#238. However, the Raman singnal of H. pylori#238 is so weak by glass fluorescence.
This research can distinguish H. pylori with BabA protein difference from others and can tell the differnce between H. pylori and other pathogen on the spectrum. And find the Raman shift GC and DU differ in .We can increase the difference between GC and DU from the Raman shift. This method if go together with improvement of chip system can not only apply to patients’ H. pylori infection inspection, but also identify H. pylori to see if it lead to GC or DU. So this system takes short inspection time and can give us accurate results.

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