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.

Frame-rate stereopsis using non-parametric transforms and programmable logic

A frame-rate stereo vision system, based on non-parametric matching metrics, is described. Traditional metrics, such as normalized cross-correlation, are expensive in terms of logic. Non-parametric measures require only simple, parallelizable, functions such as comparators, counters and exclusive-or, and are thus very well suited to implementation in reprogrammable logic.

Reduced expression of retinoblastoma gene product (pRB) and high expression of p53 are associated with poor prognosis in ovarian cancer

Paraffin sections (n = 168, 27 benign, 16 low malignant potential [LMP] and 125 malignant tumours) from epithelial ovarian tumours were evaluated immunohistochemically for expression of retinoblastoma gene product (pRB) and p53 protein, and the relationship among pRB, p53 and cyclin-dependent kinase inhibitor 2 (CDKN2) gene product p16INK4A (p16) was analysed, following our previous study of p16. Forty-one percent of the benign, 50% of the LMP and most (71%) of the malignant tumours showed high pRB expression. High expression of pRB (>50% pRB-positive cells) significantly correlated with non-mucinous histological subtypes. Reduced pRB expression, substage and residual disease were significant predictors for poor prognosis in stage I patients. All the benign and most of the LMP (81%) tumours were in either the p53-negative or low p53-positive category, but nearly half of the malignant tumours had high p53 expression. High p53 accumulation was found in non-mucinous, high grade and late stage tumours. For well-differentiated carcinomas, high p53 expression was a predictor of poor prognosis. However, even though high p53 expression was not associated with histological subtype, stage or the presence of residual disease, high p53 expression was not an independent predictor when all clinical parameters were combined. For all ovarian cancers, a close correlation was found between high p53 and high p16 expression. The relationship between the expression of pRB and p16 depended on tumour stage. In stage I tumours, high pRB was associated with low p16 reactivity. On the other hand, most advanced tumours showed both high pRB and high p16 reactivity. Int. J. Cancer 74:407–415, 1997. © 1997 Wiley-Liss, Inc.

Increased expression of cyclin-dependent kinase inhibitor 2 (CDKN2A) gene product P16INK4A in ovarian cancer is associated with progression and unfavourable prognosis

Paraffin sections from 190 epithelial ovarian tumours, including 159 malignant and 31 benign epithelial tumours, were analysed immunohistochemically for expression of cyclin-dependent kinase inhibitor 2 (CDKN2A) gene product p16INK4A (p16). Most benign tumours showed no p16 expression in the tumour cells, whereas only 11% of malignant cancers were p16 negative. A high proportion of p16-positive tumour cells was associated with advanced stage and grade, and with poor prognosis in cancer patients. For FIGO stage 1 tumours, a high proportion of p16-positive tumour cells was associated with poorer survival, suggesting that accumulation of p16 is an early event of ovarian tumorigenesis. In contrast to tumour cells, high expression of p16 in the surrounding stromal cells was not associated with the stage and grade, but was associated with longer survival. When all parameters were combined in multivariate analysis, high p16 expression in stromal cells was not an independent predictor for survival, indicating that low p16 expression in stromal cells is associated with other markers of tumour progression. High expression of p16 survival in the stromal cells of tumours from long-term survivors suggests that tumour growth is limited to some extent by factors associated with p16 expression in the matrix.

Expression of MUC1 and MUC2 mucins in epithelial ovarian tumours

This is the first study to describe the association between expression of MUC1 and MUC2 mucins and prognosis in ovarian cancer. Paraffin sections of epithelial ovarian tumours (n=182: 29 benign, 21 low malignant potential, and 132 invasive tumours) were analysed immunohistochemically for expression of MUC1 and MUC2 mucin core proteins. Most benign, low malignant potential, and invasive tumours showed high MUC1 expression in the cytoplasm. Low cytoplasmic expression of MUC1 was a predictor for good prognosis, particularly within stage III tumours. A minority of benign epithelial tumours, but most low malignant potential and invasive non-mucinous tumours, showed high MUC1 expression on the cell membrane. High apical MUC1 reactivity was associated with non-mucinous tumours. Low expression of MUC1 in the apical membrane was associated with early stage and good outcome for invasive tumours. Most benign and low malignant potential tumours, but only a minority of invasive tumours, showed MUC2 expression. MUC2 was found in non-mucinous as well as in mucinous tumours. The presence of MUC2 was inversely associated with high tumour grade but was not associated with altered survival. These results support experimental evidence that MUC1 influences the metastatic ability of ovarian cancer.

Stromal upregulation of lateral epithelial adhesions : gene expression analysis of signalling pathways in prostate epithelium

BACKGROUND: Stromal signalling increases the lateral cell adhesions of prostate epithelial cells grown in 3D culture. The aim of this study was to use microarray analysis to identify significant epithelial signalling pathways and genes in this process. METHODS: Microarray analysis was used to identify genes that were differentially expressed when epithelial cells were grown in 3D Matrigel culture with stromal co-culture compared to without stroma. Two culture models were employed: primary epithelial cells (ten samples) and an epithelial cell line (three experiments). A separate microarray analysis was performed on each model system and then compared to identify tissue-relevant genes in a cell line model. RESULTS: TGF beta signalling was significantly ranked for both model systems and in both models the TGF beta signalling gene SOX4 was significantly down regulated. Analysis of all differentially expressed genes to identify genes that were common to both models found several morphology related gene clusters; actin binding (DIAPH2, FHOD3, ABLIM1, TMOD4, MYH10), GTPase activator activity (BCR, MYH10), cytoskeleton (MAP2, MYH10, TMOD4, FHOD3), protein binding (ITGA6, CD44), proteinaceous extracellular matrix (NID2, CILP2), ion channel/ ion transporter activity (CACNA1C, CACNB2, KCNH2, SLC8A1, SLC39A9) and genes associated with developmental pathways (POFUT1, FZD2, HOXA5, IRX2, FGF11, SOX4, SMARCC1). CONCLUSIONS: In 3D prostate cultures, stromal cells increase lateral epithelial cell adhesions. We show that this morphological effect is associated with gene expression changes to TGF beta signalling, cytoskeleton and anion activity.

Gene expression profile of primary prostate epithelial and stromal cells in response to sulforaphane or iberin exposure

BACKGROUND: Broccoli consumption has been associated with a reduced risk of prostate cancer. Isothiocyanates (ITCs) derived from glucosinolates that accumulate in broccoli are dietary compounds that may mediate these health effects. Sulforaphane (SF, 4-methylsulphinylbutyl ITC) derives from heading broccoli (calabrese) and iberin (IB, 3-methylsulphinypropyl ITC) from sprouting broccoli. While there are many studies regarding the biological activity of SF, mainly undertaken with cancerous cells, there are few studies associated with IB. METHODS: Primary epithelial and stromal cells were derived from benign prostatic hyperplasia tissue. Affymetrix U133 Plus 2.0 whole genome arrays were used to compare global gene expression between these cells, and to quantify changes in gene expression following exposure to physiologically appropriate concentrations of SF and IB. Ontology and pathway analyses were used to interpret results. Changes in expression of a subset of genes were confirmed by real-time RT-PCR. RESULTS: Global gene expression profiling identified epithelial and stromal-specific gene expression profiles. SF induced more changes in epithelial cells, whereas IB was more effective in stromal cells. Although IB and SF induced different changes in gene expression in both epithelial and stromal cells, these were associated with similar pathways, such as cell cycle and detoxification. Both ITCs increased expression of PLAGL1, a tumor suppressor gene, in stromal cells and suppressed expression of the putative tumor promoting genes IFITM1, CSPG2, and VIM in epithelial cells. CONCLUSION: These data suggest that IB and SF both alter genes associated with cancer prevention, and IB should be investigated further as a potential chemopreventative agent.

mCOPA: analysis of heterogeneous features in cancer expression data

Background Cancer outlier profile analysis (COPA) has proven to be an effective approach to analyzing cancer expression data, leading to the discovery of the TMPRSS2 and ETS family gene fusion events in prostate cancer. However, the original COPA algorithm did not identify down-regulated outliers, and the currently available R package implementing the method is similarly restricted to the analysis of over-expressed outliers. Here we present a modified outlier detection method, mCOPA, which contains refinements to the outlier-detection algorithm, identifies both over- and under-expressed outliers, is freely available, and can be applied to any expression dataset. Results We compare our method to other feature-selection approaches, and demonstrate that mCOPA frequently selects more-informative features than do differential expression or variance-based feature selection approaches, and is able to recover observed clinical subtypes more consistently. We demonstrate the application of mCOPA to prostate cancer expression data, and explore the use of outliers in clustering, pathway analysis, and the identification of tumour suppressors. We analyse the under-expressed outliers to identify known and novel prostate cancer tumour suppressor genes, validating these against data in Oncomine and the Cancer Gene Index. We also demonstrate how a combination of outlier analysis and pathway analysis can identify molecular mechanisms disrupted in individual tumours. Conclusions We demonstrate that mCOPA offers advantages, compared to differential expression or variance, in selecting outlier features, and that the features so selected are better able to assign samples to clinically annotated subtypes. Further, we show that the biology explored by outlier analysis differs from that uncovered in differential expression or variance analysis. mCOPA is an important new tool for the exploration of cancer datasets and the discovery of new cancer subtypes, and can be combined with pathway and functional analysis approaches to discover mechanisms underpinning heterogeneity in cancers

‘I always look under the bed for a man’. Needs and barriers to the expression of sexuality in residential aged care: the views of residents with and without dementia

Objectives: This qualitative study canvassed residents' perceptions of the needs and barriers to the expression of sexuality in long-term care. Methods: Sixteen residents, including five with dementia, from six aged care facilities in two Australian states were interviewed. Data were analysed using a constant comparative method. Results: Four categories describe residents' views about sexuality, their needs and barriers to its expression: ‘It still matters’; ‘Reminiscence and resignation’, ‘It's personal’, and ‘It's an unconducive environment’. Discussion: Residents, including those with dementia, saw themselves as sexual beings and with a continuing need and desire to express their sexuality. The manner in which it was expressed varied. Many barriers to sexual expression were noted, including negative attitudes of staff, lack of privacy and limited opportunities for the establishment of new relationships or the continuation of old ones. Interviewees agreed that how a resident expressed their sexuality was their business and no one else's.

Full compensation no longer sacrosanct : reflections on the past and future economic loss ‘cap’ for high income earners

The civil liability provisions relating to the assessment of damages for past and future economic loss have abrogated the common law principle of full compensation by imposing restrictions on the damages award, most commonly by a “three times average weekly earnings” cap. This consideration of the impact of those provisions is informed by a case study of the Supreme Court of Victoria Court of Appeal decision, Tuohey v Freemasons Hospital (Tuohey) , which addressed the construction and arithmetic operation of the Victorian cap for high income earners. While conclusions as to operation of the cap outside of Victoria can be drawn from Tuohey, a number of issues await judicial determination. These issues, which include the impact of the damages caps on the calculation of damages for economic loss in the circumstances of fluctuating income; vicissitudes; contributory negligence; claims per quod servitum amisit; and claims by dependants, are identified and potential resolutions discussed.

Cloning of a novel insulin-regulated ghrelin transcript in prostate cancer

Ghrelin is a multifunctional hormone, with roles in stimulating appetite and regulating energy balance, insulin secretion and glucose homeostasis. The ghrelin gene locus (GHRL) is highly complex and gives rise to a range of novel transcripts derived from alternative first exons and internally spliced exons. The wild-type transcript encodes a 117 amino acid preprohormone that is processed to yield the 28 amino acid peptide ghrelin. Here, we identified insulin-responsive transcription corresponding to cryptic exons in intron 2 of the human ghrelin gene. A transcript, termed in2c-ghrelin (intron 2-cryptic), was cloned from the testis and the LNCaP prostate cancer cell line. This transcript may encode an 83 AA preproghrelin isoform that codes for the ghrelin, but not obestatin. It is expressed in a limited number of normal tissues and in tumours of the prostate, testis, breast and ovary. Finally, we confirmed that in2c-ghrelin transcript expression, as well as the recently described in1-ghrelin transcript, is significantly upregulated by insulin in cultured prostate cancer cells. Metabolic syndrome and hyperinsulinaemia has been associated with prostate cancer risk and progression. This may be particularly significant after androgen deprivation therapy for prostate cancer, which induces hyperinsulinaemia, and this could contribute to castrate resistant prostate cancer growth. We have previously demonstrated that ghrelin stimulates prostate cancer cell line proliferation in vitro. This study is the first description of insulin regulation of a ghrelin transcript in cancer, and should provide further impetus for studies into the expression, regulation and function of ghrelin gene products.

Effect of bone morphogenetic protein-4 (BMP-4) on the expression of Sox2, Oct-4 and c-Myc in human periodontal ligament cells during long-term culture

Recent studies demonstrated endogenous expression level of Sox2, Oct-4 and c-Myc is correlated with the pluripotency and successful induction of induced pluripotent stem cells (iPSCs). Periondontal ligament cells (PDLCs)have multi-lineage diferentiation capability and ability to maintain undifferentiated stage, which makes PDLCs a suitable cell source for tissue repair and regeneration. To elucidate the effect of in vitro culture condition on the stemness potential of PDLCs, we explored the cell growth, proliferation, cell cycle, and the expression of Sox2, Oct-4 and c-Myc in PDLCs from passage 1 to 7 with or without the addition of recombinant human BMP4(rhBMP4). Our results revealed that BMP-4 promoted cell growth and proliferation, arrested PDLCs in S phase of cell cycle and upregulated PI value. It was revealed that without the addition of rhBMP4, the expression of Sox2, Oct-4 and c-Myc in PDLCs only maintained nucleus location until passage 3, then lost nucleus location subsequently. The mRNA expression in PDLCs further confirmed that the level of Sox2 and Oct-4 peaked at passage 3, then decreased afterwards, whereas c-Myc maintained consistently upregulation along passages. after the treatment with rhBMP4, the expression of Sox2, Oct-4 and c-Myc in PDLCs maintained nucleus location even at passage 7 and the mRNA expression of Sox2 and Oct-4 significantly upregulated at passage 5 and 7. These results demonstrated that addition of rhBMP-4 in the culture media could improve the current culture condition for PDLCs to maintain in an undifferentiated stage.