Esta dissertação faz uma análise dos resultados de diversas simulações de transcrição usando o modelo binário da expressão gênica regulado externamente. Foram consideradas como variáveis estocásticas o número de moléculas de mRNA e o estado do gene. Neste modelo o gene pode estar no estado ativo (ON) ou reprimido (OFF) e a mudança de estado do gene ocorre a taxas deteminadas para a ativação e para a repressão em cada simulação. O número de moléculas de mRNA é alterado pela transcrição de novas moléculas e pela degradação das moléculas existentes, sendo que esses processos também ocorrem a taxas determinadas. Nas simulações foi utilizado o algoritmo de Gillespie para simulação estocástica exata de reações químicas acopladas / This dissertation analyzes the results of several transcription simulations using the binary model of externally regulated gene expression. The number of mRNA molecules and the state of the gene were considered as stochastic variables. In this model the gene may be in the active state (ON) or repressed state (OFF) and the change of gene state occurs at determined rates in each simulation for activation and for repression. The number of mRNA molecules is changed by the transcription of new molecules and by the degradation of existing molecules at determined rates. These simulations used the Gillespie algorithm for exact stochastic simulation of coupled chemical reactions was used

Esta dissertação faz uma análise dos resultados de diversas simulações de transcrição usando o modelo binário da expressão gênica regulado externamente. Foram consideradas como variáveis estocásticas o número de moléculas de mRNA e o estado do gene. Neste modelo o gene pode estar no estado ativo (ON) ou reprimido (OFF) e a mudança de estado do gene ocorre a taxas deteminadas para a ativação e para a repressão em cada simulação. O número de moléculas de mRNA é alterado pela transcrição de novas moléculas e pela degradação das moléculas existentes, sendo que esses processos também ocorrem a taxas determinadas. Nas simulações foi utilizado o algoritmo de Gillespie para simulação estocástica exata de reações químicas acopladas / This dissertation analyzes the results of several transcription simulations using the binary model of externally regulated gene expression. The number of mRNA molecules and the state of the gene were considered as stochastic variables. In this model the gene may be in the active state (ON) or repressed state (OFF) and the change of gene state occurs at determined rates in each simulation for activation and for repression. The number of mRNA molecules is changed by the transcription of new molecules and by the degradation of existing molecules at determined rates. These simulations used the Gillespie algorithm for exact stochastic simulation of coupled chemical reactions was used

Campylobacter jejuni is the commonest cause of bacterial foodborne gastroenteritis in industrialised countries. Despite its significance, it remains unclear how C. jejuni is disseminated in the environment, whether particular strains are more pathogenic than others, and by what routes this bacterium is transmitted to humans. One major factor hampering this knowledge is the lack of a standardised method for fingerprinting C. jejuni. Therefore, the overall aim of this project was to develop systematic and novel genotyping methods for C. jejuni. Chapter Three describes the use of single nucleotide polymorphisms (SNPs) derived from the multilocus sequence typing (MLST) database of C. jejuni and the closely related Campylobacter coli for genotyping these pathogens. The MLST database contains DNA sequence data for over 4000 strains, making it the largest comparative database available for these organisms. Using the in-house software package "Minimum SNPs", seven SNPs were identified from the C. jejuni/C. coli MLST database that gave a Simpson's Index of Diversity (D), or resolving power, of 0.98. An allele-specific real-time PCR method was developed and tested on 154 Australian C. jejuni and C. coli isolates. The major advantage of the seven SNPs over MLST is that they are cheaper, faster and simpler to interrogate than the sequence-based MLST method. When the SNP profiles were combined with sequencing of the rapidly evolving flaA short variable region (flaA SVR) locus, the genotype distributions were comparable to those obtained by MLST-flaA SVR. Recent technological advances have facilitated the characterisation of entire bacterial genomes using comparative genome hybridisation (CGH) microarrays. Chapter Four of this thesis explores the large volume of CGH data generated for C. jejuni and eight binary genes (genes present in some strains but absent in others) were identified that provided complete discrimination of 20 epidemiologically unrelated strains of C. jejuni. Real-time PCR assays were developed for the eight binary genes and tested on the Australian isolates. The results from this study showed that the SNP-binary assay provided a sufficient replacement for the more laborious MLST-flaA SVR sequencing method. The clustered regularly interspaced short palindromic repeat (CRISPR) region is comprised of tandem repeats, with one half of the repeat region highly conserved and the other half highly diverse in sequence. Recent advances in real-time PCR enabled the interrogation of these repeat regions in C. jejuni using high-resolution melt differentiation of PCR products. It was found that the CRISPR loci discriminated epidemiologically distinct isolates that were indistinguishable by the other typing methods (Chapter Five). Importantly, the combinatorial SNP-binary-CRISPR assay provided resolution comparable to the current 'gold standard' genotyping methodology, pulsed-field gel electrophoresis. Chapter Six describes a novel third module of "Minimum SNPs", 'Not-N', to identify genetic targets diagnostic for strain populations of interest from the remaining population. The applicability of Not-N was tested using bacterial and viral sequence databases. Due to the weakly clonal population structure of C. jejuni and C. coli, Not-N was inefficient at identifying small numbers of SNPs for the major MLST clonal complexes. In contrast, Not-N completely discriminated the 13 major subtypes of hepatitis C virus using 15 SNPs, and identified binary gene targets superior to those previously found for phylogenetic clades of C. jejuni, Yersinia enterocolitica and Clostridium difficile, demonstrating the utility of this additional module of "Minimum SNPs". Taken together, the presented work demonstrates the potentially far-reaching applications of novel and systematic genotyping assays to characterise bacterial pathogens with high accuracy and discriminatory power. This project has exploited known genetic diversity of C. jejuni to develop highly targeted assays that are akin to the resolution of the current 'gold standard' typing methods. By targeting differentially evolving genetic markers, an epidemiologically relevant, high-resolution fingerprint of the isolate in question can be determined at a fraction of the time, effort and cost of current genotyping procedures. The outcomes from this study will pave the way for improved diagnostics for many clinically significant pathogens as the concept of hierarchal combinatorial genotyping gains momentum amongst infectious disease specialists and public health-related agencies.