白色念珠菌被認為是共生真菌，但根據宿主病情被認為是機會性致病真菌。此外，白色念珠菌存在於許多器官如口腔，陰道粘膜和胃腸道中，特別是口腔上皮細胞。常見的疾病有假膜念珠菌病和義齒相關的紅斑念珠菌病。同時，白色念珠菌與易感因素相關，包括口腔真菌菌落與長期使用廣譜抗生素的平衡。然而，白色念珠菌的常見臨床菌株是SC5314和WO-1。 因此，我們需要調查在不同菌株的白色念珠菌感染期間OKF6 / TERT-2細胞中共同的致病分子機制。
在本研究中，我們採用系統生物學方法來研究不同菌株的白色念珠菌感染期間OKF6 / TERT-2細胞的共同和特異性感染機制。我們透過大數據挖掘建構候選宿主病原體遺傳和表觀遺傳的共同性和特異性網絡（GEIN），藉由雙側NGS數據鑑定宿主與病原體交互的GEIN，通過系統階數檢測方案來修正候選宿主病原體GEIN中的假陽性，透過主要網絡投影（PNP）提取核心宿主病原體交互GEIN，再與不同菌株的核心宿主-病原體交互GEIN進行比較，以檢測宿主-病原體核心交互網絡（HPCN）作為網絡生物標誌來調查來自不同菌株的白色念珠菌感染進展的共同和特異性致病機制。在我們的共同致病機制網絡標記的基礎上，我們表明orf19.5034（YBP1）具有抗ROS能力，以及orf19.939（NAM7），orf19.2087（SAS2），orf19.1093（FLO8）和orf19 .1854（HHF22）在菌絲生長和病原體蛋白質相互作用中起重要作用。此外，orf19.5585（SAP5），orf19.5542（SAP6）和orf19.4519（SUV3）將導致生物膜形成。另外，orf19.7247協調其他病原體蛋白質作用於宿主細胞蛋白質CDH1的降解。以前的研究表明，orf19.1816（ALS3），orf19.610（EFG1），orf19.1321（HWP1），orf19.4433（CPH1）和orf19.723（BCR1）也與內吞作用和形態轉化有關和被我們的結果證實。最終，這些白色念珠菌致病性蛋白質可以被認為是藥物靶標以及提出一些潛在的常見多分子藥物包括特比萘芬，番紅素，衣黴素，漢防己甲素和四環素,由於其抑制能力，用於治療不同白色念珠菌菌株對於上述藥物靶標和網絡標記物的共同病原體分子

Candida albicans is considered as a commensal fungus but an opportunistic pathogenic fungus according to host’s condition. Moreover, C. albicans exists in the oral, and vaginal mucosa and gastrointestinal tract of many organelles, especially oral epithelial cell. The common disease is pseudomembranous candidiasis and denture-associated erythematous candidiasis. Meanwhile, C. albicans is associated with susceptible factors including a balance between oral bacterial community and long-term use of broad-spectrum antibiotic. However, the common clinical strains of C. albicans are SC5314 and WO-1. Hence, we need to investigate common pathogenic molecular mechanisms in OKF6/TERT-2 cells during the infection of different strains of C. albicans.
In this study, we employed systems biology method to investigate the common and specific infection mechanisms in human oral epithelial cells during the infection of different strains of C. albicans. We constructed candidate host-pathogen genetic and epigenetic interspecies network (GEIN) through big data mining, identified host-pathogen cross-talk GEINs via two-sided NGS data to prune false-positives in candidate host-pathogen GEIN through system order detection scheme, extracted core host-pathogen cross-talk GEINs by principal network projection (PNP) and compared to core host-pathogen cross-talk GEINs of different strains to detect host-pathogen core cross-talk networks (HPCNs) as network biomarkers to investigate the common and specific pathogenic mechanism from the infection progression of different strains of Candida albicans infection. On the basis of our network marker of common pathogenic mechanisms, we indicate that orf19.5034 (YBP1) has anti-ROS ability, and orf19.939 (NAM7), orf19.2087 (SAS2), orf19.1093 (FLO8) and orf19.1854 (HHF22) play an important role in hyphae growth and pathogen protein interaction. Moreover, orf19.5585 (SAP5), orf19.5542 (SAP6) and orf19.4519 (SUV3) will cause biofilm formation. Additionally, orf19.7247 coordinates other pathogen proteins for the degradation of host cell protein CDH1. As the indication of previous studies indicates that orf19.1816 (ALS3), orf19.610 (EFG1), orf19.1321 (HWP1), orf19.4433 (CPH1) and orf19.723 (BCR1) are also verified as important roles related to endocytosis and morphological transformation by our results. Eventually, these C. albicans pathogenic proteins could be considered as drug targets and some potential common multiple-molecule drugs including Terbinafine, Cerulenin, Tunicamycin, Tetrandrine and Tetracycline are proposed for the therapeutic treatment of different strains of C. albicans due to their suppression abilities toward above drug targets and common pathogen molecules of network marker.
In this study, we employed systems biology method to investigate the common and specific infection mechanisms in human oral epithelial cells during the infection of different strains of C. albicans. We constructed candidate host-pathogen genetic and epigenetic interspecies network (GEIN) through big data mining, identified host-pathogen cross-talk GEINs via two-sided NGS data to prune false-positives in candidate host-pathogen GEIN through system order detection scheme, extracted core host-pathogen cross-talk GEINs by principal network projection (PNP) and compared to core host-pathogen cross-talk GEINs of different strains to detect host-pathogen core cross-talk networks (HPCNs) as network biomarkers to investigate the common and specific pathogenic mechanism from the infection progression of different strains of Candida albicans infection. On the basis of our network marker of common pathogenic mechanisms, we indicate that orf19.5034 (YBP1) has anti-ROS ability, and orf19.939 (NAM7), orf19.2087 (SAS2), orf19.1093 (FLO8) and orf19.1854 (HHF22) play an important role in hyphae growth and pathogen protein interaction. Moreover, orf19.5585 (SAP5), orf19.5542 (SAP6) and orf19.4519 (SUV3) will cause biofilm formation. Additionally, orf19.7247 coordinates other pathogen proteins for the degradation of host cell protein CDH1. As the indication of previous studies indicates that orf19.1816 (ALS3), orf19.610 (EFG1), orf19.1321 (HWP1), orf19.4433 (CPH1) and orf19.723 (BCR1) are also verified as important roles related to endocytosis and morphological transformation by our results. Eventually, these C. albicans pathogenic proteins could be considered as drug targets and some potential common multiple-molecule drugs including Terbinafine, Cerulenin, Tunicamycin, Tetrandrine and Tetracycline are proposed for the therapeutic treatment of different strains of C. albicans due to their suppression abilities toward above drug targets and common pathogen molecules of network marker.

誌謝 I
中文摘要 II
Abstract III
Contents IV
Introduction 1
Materials and Methods 5
2.1 Overview of the construction of GEINs and HPCNs in OKF6/TERT-2 cells line during the infection of C. albicans SC5314 and C. albicans WO-1 5
2.2 Data preprocessing of microarray data for human and pathogen 5
Results 7
3.1 The identified interspecies GEINs under the infection of Candida albicans SC5314 and Candida albicans WO-1 7
3.2 The host-pathogen core cross-talk networks (HPCNs) during infection of C. albicans SC5314 and C. albicans WO-1 8
3.3 Analysis of core interspecies pathways to investigate host/pathogen cross-talk and common and specific pathogenic progression mechanisms during C. albicans SC5314 infection 9
3.4 Analysis of core interspecies pathways to investigate host/pathogen cross-talk and common and specific pathogenic mechanisms during C. albicans WO-1 infection 13
Discussion 15
4.1 Defensive mechanism of OKF6/TERT-2 cell and the offensive mechanism of different strains of C. albicans at host cell surface 15
4.2 OKF6/TERT-2 cell confronts different strains of C. albicans by strong ROS and microenvironment response 19
4.3 Released pathogenic factor and accumulated cellular response result in apoptosis and inflammatory response further leading to necrosis 24
4.4 Prediction of drug target proteins and multiple-molecules drug design for the infection of different strains of C. albicans 29
Conclusion 33
Tables 34
Table 1. Information about the numbers of nodes of candidate interspecies GEINs and real interspecies GEINs by the proposed system identification method in the infection of C. albicans SC5314 and C. albicans WO-1 of two replicates 34
Table 2.Information about the identified number of edges of candidate interspecies GEINs and real interspecies GEINs by proposed system identification method in the infection of C. albicans SC5314 and C. albicans WO-1 of two replicates 34
Table 3. The specific and common host cellular functions and functional abundance analysis of related pathways of the conserved host target-genes among 2 replicates in the infection of C .albicans SC5314 and WO-1 on the basis of GO terms by applying the DAVID analysis 35
Table 4. The specific and common pathogen functions and functional abundance analysis of related pathways of the conserved target- pathogen genes among 2 replicates in the infection of C .albicans SC5314 and WO-1 on the basis of GO terms by applying the CGD Gene Ontology Term Finder analysis 36
Figure 38
Figure 1. The flow chart of the systems biology method applied to construct genetic and epigenetic interspecies networks (GEINs) for extracting HPCNs to discover the common and specific pathogenic mechanisms during the infection of C. albicans SC5314 and C. albicans WO-1 for drug targets and potential common molecule drugs. 38
Figure 2. The core cross-talk pathways extracted and rearranged based on KEGG pathways from the cross-talk HPCN in Figure S4 during the C. albicans SC5314 infection. 40
Figure 3. The core cross-talk pathways extracted and rearranged based on KEGG pathways from the cross-talk HPCN in Figure S5 during the C. albicans WO-1 infection. 41
Figure 4. The specific and common host defense mechanism in the infection of different strains of C. albicans are extracted from Figures 2 and 3. A) OKF6/TERT-2 cells take a defense strategy against C. albicans SC5314 at the beginning of infection. B) OKF6/TERT-2 cells take a defense strategy against with C. albicans WO-1 at the beginning of infection. 43
Figure 5. The continuous ROS and stress production as defense mechanism in host cells, and the corresponding anti-ROS and offensive mechanism of C. albicans. A) OKF6/TERT-2 cells antagonize in C. albicans SC5314 invasion. B) OKF6/TERT-2 cells antagonize in C. albicans WO-1 invasion. 44
Figure 6. C. albicans could release pathogenic factor and the accumulated cellular stress in host cell could result in apoptosis and inflammatory response leading to necrosis 46
Figure 7. Summarizing the common and specific epigenetic and genetic pathogenic mechanisms in the infection of different strains of C. albicans 48
Figure 8. The potential common multiple-molecule drugs for the treatment of infection of different strains of C. albicans 49
Supplementary Material 51
6.1 Construction of candidate interspecies GEINs via big data mining 51
6.2 Dynamic models of candidate interspecies GEINs for OKF6/TERT-2 cells and C. albicans during the infection 53
6.3 Parameter estimation of the dynamic models of candidate interspecies GEIN by system identification approach 57
6.4 Trimming false-positives in candidate GEINs by system order detection scheme 67
6.5 Extracting core network structures from real interspecies GEINs by using PNP approach 70
Supplementary Material Figure 74
Figure S1. The constructing programs of intra-species candidate GEIN. A) C. albicans SC5314- C. albicans SC5314 candidate intra-species PPIN; B) host-C. albicans SC5314 candidate inter-species PPIN; C) candidate GRN of host-TFs targeting C. albicans SC5314-genes; D) candidate GRN of host-miRNAs targeting C. albicans SC5314-genes; E) candidate GRN of C. albicans SC5314 TFs targeting host-genes; F) candidate GRN of C. albicans SC5314 TFs targeting host- miRNAs; G) candidate GRN of C. albicans SC5314 TFs targeting C. albicans SC5314-genes. 77
Figure S2. The constructing programs of candidate GEIN. A) C. albicans WO-1- C. albicans WO-1 candidate intra-species PPIN; B) host-C. albicans WO-1 candidate inter-species PPIN; C) candidate GRN of host-TFs targeting C. albicans WO-1-genes; D) candidate GRN of host-miRNAs targeting C. albicans WO-1-genes; E) candidate GRN of C. albicans WO-1 TFs targeting host-genes; F) candidate GRN of C. albicans WO-1 TFs targeting host- miRNAs; G) candidate GRN of C. albicans WO-1 TFs targeting C. albicans WO-1-genes. 80
Figure S3. The real interspecies GEINs of two replicates during the infection of C. albicans SC5314 and C. albicans WO-1 with OKF6/TERT-2 cells, respectively. 81
Figure S4. Cross-talk HPCN of OKF6/TERT-2 cells during the infection of C. albicans SC5314. 83
Figure S5. Cross-talk HPCN of OKF6/TERT-2 cells during the infection of C. albicans WO-1. 84
Reference 84