Molecular analysis of virulence mechanisms associated with adherent-invasive Escherichia coli (AIEC)

Crohn's Disease (CD) is a chronic inflammatory bowel disease of unknown etiology. Recent work has shown that a new pathotype of Escherichia coli, Adherent Invasive E. coli (AIEC) may be associated with CD. AIEC has been shown to adhere to and invade epithelial cells and to replicate within macrophages (together this is called the AIEC phenotype). In this thesis, the AIEC phenotype of 84 E. coli strains were determined in order to identify the prevalence of this phenotype within the E. coli genus. This study showed that a significant proportion of E. coli strains (approx. 5%) are capable of adhering to and invading epithelial cells and undergoing intramacrophage replication. Moreover, the results presented in this study indicate a correlation between survival in macrophage and resistance to grazing by amoeba supporting the coincidental evolution hypothesis that resistance to amoebae could be a driving force in the evolution of pathogenicity in some bacteria, such as AIEC. In addition, this study has identified an important regulatory role for the CpxA/R two component system (TCS) in the invasive abilities of AIEC HM605, a colonic mucosa-associated CD isolate. A mutation in cpxR was shown to be defective in the invasion of epithelial cells and this defect was shown to be independent of motility or the expression of Type 1 fimbriae, factors that have been shown to be involved in the invasion of another strain of AIEC, isolated from a patient with ileal CD, called LF82. The CpxA/R TCS responds to disturbances in the cell envelope and has been implicated in the virulence of a number of Gram negative pathogens. In this study it is shown that the CpxA/R TCS regulates the expression of a potentially novel invasin called SinH. SinH is found in a number of invasive strains of E. coli and Salmonella. Moreover work presented here shows that a critical mechanism underpinning AIEC persistence in macrophages is the repair of DNA bases damaged by macrophage oxidants. Together these findings provide evidence to suggest that AIEC are a diverse group of E. coli and possess diverse molecular mechanisms and virulence factors that contribute to the AIEC phenotype. In addition, AIEC may have gone through different evolutionary histories acquiring various molecular mechanisms ultimately culminating in the AIEC phenotype. The gastrointestinal (GI) tract harbors a diverse microbiota; most are symbiotic or commensal however some bacteria have the potential to cause disease (pathobiont). The work presented here provides evidence to support the model that AIEC are pathobionts. AIEC strains can be carried as commensals in healthy guts however, when the intestinal homeostasis is disrupted, such as in the compromised gut of CD patients, AIEC may behave as opportunistic pathogens and cause and/or contribute to disease by driving intestinal inflammation.

Molecular genetic analysis of DNA alterations in Irish colorectal cancer

Colorectal cancer is the most common cause of death due to malignancy in nonsmokers in the western world. In 1995 there were 1,757 cases of colon cancer in Ireland. Most colon cancer is sporadic, however ten percent of cases occur where there is a previous family history of the disease. In an attempt to understand the tumorigenic pathway in Irish colon cancer patients, a number of genes associated with colorectal cancer development were analysed in Irish sporadic and HNPCC colon cancer patients. The hereditary forms of colon cancer include Familial adenomatous polyposis coli (FAP) and Hereditary Non-Polyposis Colon Cancer (HNPCC). Genetic analysis of the gene responsible for FAP, (the APC gene) has been previously performed on Irish families, however the genetic analysis of HNPCC families is limited. In an attempt to determine the mutation spectrum in Irish HNPCC pedigrees, the hMSH2 and hMLHl mismatch repair genes were screened in 18 Irish HNPCC families. Using SSCP analysis followed by DNA sequencing, five mutations were identified, four novel and a previously reported mutation. In families where a mutation was detected, younger asyptomatic members were screened for the presence of the predisposing mutation (where possible). Detection of mutations is particularly important for the identification of at risk individuals as the early diagnosis of cancer can vastly improve the prognosis. The sensitive and efficient detection of multiple different mutations and polymorphisms in DNA is of prime importance for genetic diagnosis and the identification of disease genes. A novel mutation detection technique has recently been developed in our laboratory. In order to assess the efficacy and application of the methodology in the analysis of cancer associated genes, a protocol for the analysis of the K-ras gene was developed and optimised. Matched normal and tumour DNA from twenty sporadic colon cancer patients was analysed for K-ras mutations using the Glycosylase Mediated Polymorphism Detection technique. Five mutations of the K-ras gene were detected using this technology. Sequencing analysis verified the presence of the mutations and SSCP analysis of the same samples did not identify any additional mutations. The GMPD technology proved to be highly sensitive, accurate and efficient in the identification of K-ras gene mutations. In order to investigate the role of the replication error phenomenon in Irish colon cancer, 3 polyA tract repeat loci were analysed. The repeat loci included a 10 bp intragenic repeat of the TGF-β-RII gene. TGF-β-RII is involved in the TGF-β epithelial cell growth pathway and mutation of the gene is thought to play a role in cell proliferation and tumorigenesis. Due to the presence of a repeat sequence within the gene, TGFB-RII defects are associated with tumours that display the replication error phenomenon. Analysis of the TGF-β-RII 10 bp repeat failed to identify mutations in any colon cancer patients. Analysis of the Bat26 and Bat 40 polyA repeat sequences in the sporadic and HNPCC families revealed that instability is associated with HNPCC tumours harbouring mismatch repair defects and with 20 % of sporadic colon cancer tumours. No correlation between K-ras gene mutations and the RER+ phenotype was detected in sporadic colon cancer tumours.

On classical and other methods of discriminant analysis and estimation of log-odds

For two multinormal populations with equal covariance matrices the likelihood ratio discriminant function, an alternative allocation rule to the sample linear discriminant function when n1 ≠ n2 ,is studied analytically. With the assumption of a known covariance matrix its distribution is derived and the expectation of its actual and apparent error rates evaluated and compared with those of the sample linear discriminant function. This comparison indicates that the likelihood ratio allocation rule is robust to unequal sample sizes. The quadratic discriminant function is studied, its distribution reviewed and evaluation of its probabilities of misclassification discussed. For known covariance matrices the distribution of the sample quadratic discriminant function is derived. When the known covariance matrices are proportional exact expressions for the expectation of its actual and apparent error rates are obtained and evaluated. The effectiveness of the sample linear discriminant function for this case is also considered. Estimation of true log-odds for two multinormal populations with equal or unequal covariance matrices is studied. The estimative, Bayesian predictive and a kernel method are compared by evaluating their biases and mean square errors. Some algebraic expressions for these quantities are derived. With equal covariance matrices the predictive method is preferable. Where it derives this superiority is investigated by considering its performance for various levels of fixed true log-odds. It is also shown that the predictive method is sensitive to n1 ≠ n2. For unequal but proportional covariance matrices the unbiased estimative method is preferred. Product Normal kernel density estimates are used to give a kernel estimator of true log-odds. The effect of correlation in the variables with product kernels is considered. With equal covariance matrices the kernel and parametric estimators are compared by simulation. For moderately correlated variables and large dimension sizes the product kernel method is a good estimator of true log-odds.