Next-generation sequencing of cervical DNA detects human papillomavirus types not detected by commercial kits

Background Human papillomavirus (HPV) is the aetiological agent for cervical cancer and genital warts. Concurrent HPV and HIV infection in the South African population is high. HIV positive (+) women are often infected with multiple, rare and undetermined HPV types. Data on HPV incidence and genotype distribution are based on commercial HPV detection kits, but these kits may not detect all HPV types in HIV + women. The objectives of this study were to (i) identify the HPV types not detected by commercial genotyping kits present in a cervical specimen from an HIV positive South African woman using next generation sequencing, and (ii) determine if these types were prevalent in a cohort of HIV-infected South African women. Methods Total DNA was isolated from 109 cervical specimens from South African HIV + women. A specimen within this cohort representing a complex multiple HPV infection, with 12 HPV genotypes detected by the Roche Linear Array HPV genotyping (LA) kit, was selected for next generation sequencing analysis. All HPV types present in this cervical specimen were identified by Illumina sequencing of the extracted DNA following rolling circle amplification. The prevalence of the HPV types identified by sequencing, but not included in the Roche LA, was then determined in the 109 HIV positive South African women by type-specific PCR. Results Illumina sequencing identified a total of 16 HPV genotypes in the selected specimen, with four genotypes (HPV-30, 74, 86 and 90) not included in the commercial kit. The prevalence's of HPV-30, 74, 86 and 90 in 109 HIV positive South African women were found to be 14.6 %, 12.8 %, 4.6 % and 8.3 % respectively. Conclusions Our results indicate that there are HPV types, with substantial prevalence, in HIV positive women not being detected in molecular epidemiology studies using commercial kits. The significance of these types in relation to cervical disease remains to be investigated.

Recombination, decreased host specificity and increased mobility may have driven the emergence of maize streak virus as an agricultural pathogen

Maize streak virus (MSV; family Geminiviridae, genus Mastrevirus), the causal agent of maize streak disease, ranks amongst the most serious biological threats to food security in subSaharan Africa. Although five distinct MSV strains have been currently described, only one of these - MSV-A - causes severe disease in maize. Due primarily to their not being an obvious threat to agriculture, very little is known about the 'grass-adapted' MSV strains, MSV-B, -C, -D and -E. Since comparing the genetic diversities, geographical distributions and natural host ranges of MSV-A with the other MSV strains could provide valuable information on the epidemiology, evolution and emergence of MSV-A, we carried out a phylogeographical analysis of MSVs found in uncultivated indigenous African grasses. Amongst the 83 new MSV genomes presented here, we report the discovery of six new MSV strains (MSV-F to -K). The non-random recombination breakpoint distributions detectable with these and other available mastrevirus sequences partially mirror those seen in begomoviruses, implying that the forces shaping these breakpoint patterns have been largely conserved since the earliest geminivirus ancestors. We present evidence that the ancestor of all MSV-A variants was the recombinant progeny of ancestral MSV-B and MSV-G/-F variants. While it remains unknown whether recombination influenced the emergence of MSV-A in maize, our discovery that MSV-A variants may both move between and become established in different regions of Africa with greater ease, and infect more grass species than other MSV strains, goes some way towards explaining why MSV-A is such a successful maize pathogen. © 2008 SGM.

Maize streak virus: An old and complex 'emerging' pathogen

Maize streak virus (MSV; Genus Mastrevirus, Family Geminiviridae) occurs throughout Africa, where it causes what is probably the most serious viral crop disease on the continent. It is obligately transmitted by as many as six leafhopper species in the Genus Cicadulina, but mainly by C. mbila Naudé and C. storeyi. In addition to maize, it can infect over 80 other species in the Family Poaceae. Whereas 11 strains of MSV are currently known, only the MSV-A strain is known to cause economically significant streak disease in maize. Severe maize streak disease (MSD) manifests as pronounced, continuous parallel chlorotic streaks on leaves, with severe stunting of the affected plant and, usuallly, a failure to produce complete cobs or seed. Natural resistance to MSV in maize, and/or maize infections caused by non-maize-adapted MSV strains, can result in narrow, interrupted streaks and no obvious yield losses. MSV epidemiology is primarily governed by environmental influences on its vector species, resulting in erratic epidemics every 3-10 years. Even in epidemic years, disease incidences can vary from a few infected plants per field, with little associated yield loss, to 100% infection rates and complete yield loss. Taxonomy: The only virus species known to cause MSD is MSV, the type member of the Genus Mastrevirus in the Family Geminiviridae. In addition to the MSV-A strain, which causes the most severe form of streak disease in maize, 10 other MSV strains (MSV-B to MSV-K) are known to infect barley, wheat, oats, rye, sugarcane, millet and many wild, mostly annual, grass species. Seven other mastrevirus species, many with host and geographical ranges partially overlapping those of MSV, appear to infect primarily perennial grasses. Physical properties: MSV and all related grass mastreviruses have single-component, circular, single-stranded DNA genomes of approximately 2700 bases, encapsidated in 22 × 38-nm geminate particles comprising two incomplete T = 1 icosahedra, with 22 pentameric capsomers composed of a single 32-kDa capsid protein. Particles are generally stable in buffers of pH 4-8. Disease symptoms: In infected maize plants, streak disease initially manifests as minute, pale, circular spots on the lowest exposed portion of the youngest leaves. The only leaves that develop symptoms are those formed after infection, with older leaves remaining healthy. As the disease progresses, newer leaves emerge containing streaks up to several millimetres in length along the leaf veins, with primary veins being less affected than secondary or tertiary veins. The streaks are often fused laterally, appearing as narrow, broken, chlorotic stripes, which may extend over the entire length of severely affected leaves. Lesion colour generally varies from white to yellow, with some virus strains causing red pigmentation on maize leaves and abnormal shoot and flower bunching in grasses. Reduced photosynthesis and increased respiration usually lead to a reduction in leaf length and plant height; thus, maize plants infected at an early stage become severely stunted, producing undersized, misshapen cobs or giving no yield at all. Yield loss in susceptible maize is directly related to the time of infection: Infected seedlings produce no yield or are killed, whereas plants infected at later times are proportionately less affected. Disease control: Disease avoidance can be practised by only planting maize during the early season when viral inoculum loads are lowest. Leafhopper vectors can also be controlled with insecticides such as carbofuran. However, the development and use of streak-resistant cultivars is probably the most effective and economically viable means of preventing streak epidemics. Naturally occurring tolerance to MSV (meaning that, although plants become systemically infected, they do not suffer serious yield losses) has been found, which has primarily been attributed to a single gene, msv-1. However, other MSV resistance genes also exist and improved resistance has been achieved by concentrating these within individual maiz genotypes. Whereas true MSV immunity (meaning that plants cannot be symptomatically infected by the virus) has been achieved in lines that include multiple small-effect resistance genes together with msv-1, it has proven difficult to transfer this immunity into commercial maize genotypes. An alternative resistance strategy using genetic engineering is currently being investigated in South Africa. Useful websites: 〈http://www.mcb.uct.ac.za/MSV/mastrevirus.htm〉; 〈http://www. danforthcenter.org/iltab/geminiviridae/geminiaccess/mastrevirus/Mastrevirus. htm〉. © 2009 Blackwell Publishing Ltd.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Food insecurity among adults residing in disadvantaged urban areas : potential health and dietary consequences

Objective: Food insecurity is the limited or uncertain availability or access to nutritionally-adequate, culturally-appropriate and safe foods. Food insecurity may result in inadequate dietary intakes, overweight or obesity and the development of chronic disease. Internationally, few studies have focused on the range of potential health outcomes related to food insecurity among adults residing in disadvantaged locations and no such Australian studies exist. The objective of this study was to investigate associations between food insecurity, socio-demographic and health factors and dietary intakes among adults residing in disadvantaged urban areas. Design: Data were collected by mail survey (n= 505, 53% response rate), which ascertained information about food security status, demographic characteristics (such as age, gender, household income, education) fruit and vegetable intakes, take-away and meat consumption, general health, depression and chronic disease. Setting: Disadvantaged suburbs of Brisbane city, Australia, 2009. Subjects: Individuals aged ≥ 20 years. Results: Approximately one-in-four households (25%) were food insecure. Food insecurity was associated with lower household income, poorer general health, increased healthcare utilisation and depression. These associations remained after adjustment for age, gender and household income. Conclusion: Food insecurity is prevalent in urbanised disadvantaged areas in developed countries such as Australia. Low-income households are at high risk of experiencing food insecurity. Food insecurity may result in significant health burdens among the population, and this may be concentrated in socioeconomically-disadvantaged suburbs.

When the right to be counted doesn’t count : the politics and challenges of researching the health of asylum seekers

A fundamental prerequisite of population health research is the ability to establish an accurate denominator. This in turn requires that every individual in the study population is counted. However, this seemingly simple principle has become a point of conflict between researchers whose aim is to produce evidence of disparities in population health outcomes and governments whose policies promote(intentionally or not) inequalities that are the underlying causes of health disparities. Research into the health of asylum seekers is a case in point. There is a growing body of evidence documenting the adverse affects of recent changes in asylum-seeking legislation, including mandatory detention. However, much of this evidence has been dismissed by some governments as being unsound, biased and unscientific because, it is argued, evidence is derived from small samples or from case studies. Yet, it is the policies of governments that are the key barrier to the conduct of rigorous population health research on asylum seekers. In this paper, the authors discuss the challenges of counting asylum seekers and the limitations of data reported in some industrialized countries. They argue that the lack of accurate statistical data on asylum seekers has been an effective neo-conservative strategy for erasing the health inequalities in this vulnerable population, indeed a strategy that renders invisible this population. They describe some alternative strategies that may be used by researchers to obtain denominator data on hard-to-reach populations such as asylum seekers.

A six-year descriptive analysis of hospitalisations for ambulatory care sensitive conditions among people born in refugee-source countries

Background: Hospitalisation for ambulatory care sensitive conditions (ACSHs) has become a recognised tool to measure access to primary care. Timely and effective outpatient care is highly relevant to refugee populations given the past exposure to torture and trauma, and poor access to adequate health care in their countries of origin and during flight. Little is known about ACSHs among resettled refugee populations. With the aim of examining the hypothesis that people from refugee backgrounds have higher ACSHs than people born in the country of hospitalisation, this study analysed a six-year state-wide hospital discharge dataset to estimate ACSH rates for residents born in refugee-source countries and compared them with the Australia-born population. Methods: Hospital discharge data between 1 July 1998 and 30 June 2004 from the Victorian Admitted Episodes Dataset were used to assess ACSH rates among residents born in eight refugee-source countries, and compare them with the Australia-born average. Rate ratios and 95% confidence levels were used to illustrate these comparisons. Four categories of ambulatory care sensitive conditions were measured: total, acute, chronic and vaccine-preventable. Country of birth was used as a proxy indicator of refugee status. Results: When compared with the Australia-born population, hospitalisations for total and acute ambulatory care sensitive conditions were lower among refugee-born persons over the six-year period. Chronic and vaccine-preventable ACSHs were largely similar between the two population groups. Conclusion: Contrary to our hypothesis, preventable hospitalisation rates among people born in refugee-source countries were no higher than Australia-born population averages. More research is needed to elucidate whether low rates of preventable hospitalisation indicate better health status, appropriate health habits, timely and effective care-seeking behaviour and outpatient care, or overall low levels of health care-seeking due to other more pressing needs during the initial period of resettlement. It is important to unpack dimensions of health status and health care access in refugee populations through ad-hoc surveys as the refugee population is not a homogenous group despite sharing a common experience of forced displacement and violence-related trauma.

Hospital utilisation among people born in refugee-source countries : an analysis of hospital admissions, Victoria, 1998–2004

Objective: To investigate whether hospital utilisation and health outcomes in Victoria differ between people born in refugee-source countries and those born in Australia. Design and setting: Analysis of a statewide hospital discharge dataset for the 6 financial years from 1 July 1998 to 30 June 2004. Hospital admissions of people born in eight countries for which the majority of entrants to Australia arrived as refugees were included in the analysis. Main outcome measures: Age-standardised rates and rate ratios for: total hospital admissions; emergency admissions; surgical admissions; total days in hospital; discharge at own risk; hospital deaths; admissions due to infectious and parasitic diseases; and admissions due to mental and behavioural disorders. Results: In 2003–04, compared with the Australia-born Victorian population, people born in refugee-source countries had lower rates of surgical admission (rate ratio [RR], 0.85; 95% CI, 0.81–0.88), total days in hospital (RR, 0.74; 95% CI, 0.73–0.75), and admission due to mental and behavioural disorders (RR, 0.70; 95% CI, 0.65–0.76). Over the 6-year period, rates of total days in hospital and rates of admission due to mental and behavioural disorders for people born in refugee-source countries increased towards Australian-born averages, while rates of total admissions, emergency admissions, and admissions due to infectious and parasitic diseases increased above the Australian-born averages. Conclusions: Use of hospital services among people born in refugee-source countries is not higher than that of the Australian-born population and shows a trend towards Australian-born averages. Our findings indicate that the Refugee and Humanitarian Program does not currently place a burden on the Australian hospital system.

Associations between socioeconomic position, food insecurity and BMI

Introduction: Food insecurity is a social determinant of health and is defined as limited ability to access sufficient amounts of nutritionally adequate or safe food for a healthy and active life. Food insecurity is associated with poor health status and the exacerbation of other health inequalities. This study examined whether an association existed between 1) socioeconomic position (SEP) and food insecurity and 2) food insecurity and weight status. Methods: Data from the 1995 National Nutrition Survey was analysed. A random sample of households (n = 13 858) were asked about dietary habits and food choices. Information about gender, age, BMI, waist circumference, household income and whether the household had run out of money to purchase food in the previous 12 months was obtained and analysed using chi-square and logistic regression. Results: Income was significantly associated with food insecurity; households with lower income were at higher risk of food insecurity. Lower income males were nine times more likely to experience food insecurity and lower income females were three times more likely to experience food insecurity than their higher income counterparts. Food insecurity was significantly associated with body mass index (BMI) among women but not men. Women experiencing food insecurity were at higher risk of overweight/obesity according to BMI and waist circumference measures. Conclusion: Evidence suggests that low income households are at higher risk of food insecurity and women who are food insecure are at higher risk of being overweight or obese. Food insecurity may mediate the association between SEP and BMI.

Does food insecurity contribute to socioeconomic inequalities in BMI?

Introduction: Food insecurity is a social determinant of health and is defined as limited ability to access sufficient amounts of nutritionally adequate or safe food for a healthy and active life. Food insecurity is associated with poor health status and the exacerbation of other health inequalities. This study examined whether an association existed between 1) socioeconomic position (SEP) and food insecurity and 2) food insecurity and weight status. Methods: Data from the 1995 National Nutrition Survey was analysed. A random sample of households (n = 13 858) were asked about dietary habits and food choices. Information about gender, age, BMI, waist circumference, household income and whether the household had run out of money to purchase food in the previous 12 months was obtained and analysed using chi-square and logistic regression. Results: Income was significantly associated with food insecurity; households with lower income were at higher risk of food insecurity. Lower income males were nine times more likely to experience food insecurity and lower income females were three times more likely to experience food insecurity than their higher income counterparts. Food insecurity was significantly associated with body mass index (BMI) among women but not men. Women experiencing food insecurity were at higher risk of overweight/obesity according to BMI and waist circumference measures. Conclusion: Evidence suggests that low income households are at higher risk of food insecurity and women who are food insecure are at higher risk of being overweight or obese. Food insecurity may mediate the association between SEP and BMI.

Potential dietary consquences of food insecurity among Australian adults residing in urbanised disadvantaged areas

Introduction: Food insecurity is the limited/uncertain availability, access to or ability to acquire nutritionally-adequate, culturallyrelevant and safe foods. Adults suffering from food insecurity are at risk of inadequate nutrient intakes or, paradoxically, overweight/ obesity and the development of chronic disease. Despite the global financial crisis and rising costs of living, there are few studies investigating the potential dietary consequences of food insecurity among the Australian population. This study examined whether food insecurity was associated with weight status and poorer intakes of fruits, vegetable and takeaway foods among adults residing in socioeconomically-disadvantaged urbanised areas. Methods: In this cross-sectional study, a random sample of residents (n=1000) were selected from the most disadvantaged suburbs of Brisbane city (response rate 51%). Data were collected by postal questionnaire which ascertained information on sociodemographic information, household food security status, height, weight, fruit and vegetable intakes and takeaway consumption. Data were analysed using chi-square and logistic regression. Results: The overall prevalence of food insecurity was 31%. Food insecurity was not associated with weight status among men or women. Associations between food security status and potential dietary consequences differed for men and women. Among women, food security was not associated with intakes of fruit, vegetable or takeaway consumption. Contrastingly, among men food security was associated with vegetable intakes and consumption of takeaway food: men reporting food insecurity had lower intakes of vegetables and were more likely to consume takeaway foods compared to those that were food secure. Conclusion: Food security is an important public health issue in Australia and has potential dietary consequences that may adversely affect the health of food-insecure groups, most notably men residing in food-insecure households.

Potential health and dietary consequences of food insecurity among Australian adults residing in urbanised disadvantaged areas

Purpose: Food insecurity is the limited/uncertain availability or ability to acquire nutritionally-adequate, culturally-relevant and safe foods. Adults suffering from food insecurity are at risk of inadequate nutrient intakes or, paradoxically, overweight/obesity and the development of chronic disease. Despite the global financial crisis and rising costs of living, few studies have investigated the potential dietary and health consequences of food insecurity among the Australian population. This study examined whether food insecurity was associated with health behaviours and dietary intakes among adults residing in socioeconomically-disadvantaged urbanised areas. Methods: In this cross-sectional study, a random sample of residents (n = 1000) were selected from the most disadvantaged suburbs of Brisbane city (response rate 51%). Data were collected by postal questionnaire which ascertained information on socio-demographic information, household food security, height, weight, frequency of healthcare utilisation, presence of chronic disease and intakes of fruit, vegetables and take-away. Data were analysed using logistic regression. Results/Findings: The prevalence of food insecurity was 25%. Those reporting food insecurity were two-to-three times more likely to have seen a general practitioner or been hospitalised within the previous 6 months. Furthermore, food insecurity was associated with a three-to-six-fold increase in the likelihood of experiencing depression. Food insecurity was associated with higher intakes of some take-away foods, however was not significantly associated with weight status or intakes of fruits or vegetables among this disadvantaged sample. Conclusion: Food insecurity has potential adverse health consequences that may result in significant health burdens among the population, and this may be concentrated in socioeconomically-disadvantaged suburbs.

Smoking status as a moderator of the association between food insecurity and decreased fruit and vegetable consumption

Food insecurity is the inadequate access to, or availability of, sufficient amounts of nutritious, culturally-appropriate and safe foods, or the inability to acquire such foods by socially acceptable means. Food insecurity has been shown to be associated with poor dietary intakes and poor health status. Recently, evidence has emerged suggesting increased rates of food insecurity among those with substance abuse problems, including those who smoke. This cross-sectional study investigates the potential moderating effect of smoking on the association between food insecurity and fruit and vegetable intakes among the Australian population, using regression analyses. Participants were adults 18 years and older participating in the 2004/05 National Health Survey (n = 19,500). Those from food insecure households were up to two-times more likely to report inadequate fruit and vegetable intakes compared to those who were food secure. Those who smoked were nearly six times more likely to report being food insecure, and up to three-times more likely to report inadequate fruit and vegetable intakes, compared to their non-smoking counterparts. Further analyses revealed a marked decline in the strength of the association between food insecurity and fruit consumption with the addition of smoking status into a regression model. These findings have important implications for the development of policy and interventions to address food insecurity, suggesting that those from food insecure households are less likely to comply with national dietary recommendations, and that this may in part be moderated by smoking status.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.