Modulation of the SHBG signalling axis

Sex hormone-binding globulin (SHBG) is a homodimeric plasma glycoprotein that is the major sex steroid carrier-protein in the bloodstream and functions also as a key regulator of steroid bioavailability within target tissues, such as the prostate. Additionally, SHBG binds to prostatic cell membranes via the putative and unidentified SHBG receptor (RSHBG), activating a signal transduction pathway implicated in stimulating both proliferation and expression of prostate specific antigen (PSA) in prostate cell lines in vitro. A yeast-two hybrid assay suggested an interaction between SHBG and kallikrein-related protease (KLK) 4, which is a serine protease implicated in the progression of prostate cancer. The potential interaction between these two proteins was investigated in this PhD thesis to determine whether SHBG is a proteolytic substrate of KLK4 and other members of the KLK family including KLK3/PSA, KLK7 and KLK14. Furthermore, the effects from SHBG proteolytic degradation on SHBG-regulated steroid bioavailability and the activation of the putative RSHBG signal transduction pathway were examined in the LNCaP prostate cancer cell line. SHBG was found to be a proteolytic substrate of the trypsin-like KLK4 and KLK14 in vitro, yielding several proteolysis fragments. Both chymotrypsin-like PSA and KLK7 displayed insignificant proteolytic activity against SHBG. The kinetic parameters of SHBG proteolysis by KLK4 and KLK14 demonstrate a strong enzyme-substrate binding capacity, possessing a Km of 1.2 ± 0.7 µM and 2.1 ± 0.6 µM respectively. The catalytic efficiencies (kcat/Km) of KLK4 and KLK14 proteolysis of SHBG were 1.6 x 104 M-1s-1 and 3.8 x 104 M-1s-1 respectively, which were comparable to parameters previously reported for peptide substrates. N-terminal sequencing of the fragments revealed cleavage near the junction of the N- and C-terminal laminin globulin-like (G-like) domains of SHBG, resulting in the division of the two globulins and ultimately the full degradation of these fragments by KLK4 and KLK14 over time. Proteolytic fragments that may retain steroid binding were rapidly degraded by both proteases, while fragments containing residues beyond the steroid binding pocket were less degraded over the same period of time. Degradation of SHBG was inhibited by the divalent metal cations calcium and zinc for KLK4, and calcium, zinc and magnesium for KLK14. The human secreted serine protease inhibitors (serpins), α1-antitrypsin and α2-antiplasmin, inhibited KLK4 and KLK14 proteolysis of SHBG; α1-antichymotrypsin inhibited KLK4 but not KLK14 activity. The inhibition by these serpins was comparable and in some cases more effective than general trypsin protease inhibitors such as aprotinin and phenylmethanesulfonyl fluoride (PMSF). The binding of 5α-dihydrotestosterone (DHT) to SHBG modulated interactions with KLK4 and KLK14. Steroid-free SHBG was more readily digested by both enzymes than DHT-bound SHBG. Moreover, a binding interaction exists between SHBG and pro-KLK4 and pro-KLK14, with DHT strengthening the binding to pro-KLK4 only. The inhibition of androgen uptake by cultured prostate cancer cells, mediated by SHBG steroid-binding, was examined to assess whether SHBG proteolysis by KLK4 and KLK14 modulated this process. Proteolytic digestion eliminated the ability of SHBG to inhibit the uptake of DHT from conditioned media into LNCaP cells. Therefore, the proteolysis of SHBG by KLK4 and KLK14 increased steroid bioavailability in vitro, leading to an increased uptake of androgens by prostate cancer cells. Interestingly, different transcriptional responses of PSA and KLK2, which are androgen-regulated genes, to DHT-bounsd SHBG treatment were observed between low and high passage number LNCaP cells (lpLNCaP and hpLNCaP respectively). HpLNCaP cells treated with DHT-bound SHBG demonstrated a significant synergistic upregulation of PSA and KLK2 above DHT or SHBG treatment alone, which is similar to previously reported downstream responses from RSHBG-mediated signaling activation. As this result was not seen in lpLNCaP cells, only hpLNCaP cells were further investigated to examine the modulation of potential RSHBG activity by KLK4 and KLK14 proteolysis of SHBG. Contrary to reported results, no increase in intracellular cAMP was observed in hpLNCaP cells when treated with SHBG in the presence and absence of either DHT or estradiol. As a result, the modulation of RSHBG-mediated signaling activation could not be determined. Finally, the identification of the RSHBG from both breast (MCF-7) and prostate cancer (LNCaP) cell lines was attempted. Fluorescently labeled peptides corresponding to the putative receptor binding domain (RBD) of SHBG were shown to be internalized by MCF-7 cells. Crosslinking of the RBD peptide to the cell surfaces of both MCF-7 and LNCaP cells, demonstrated the interaction of the peptide with several targets. These targets were then captured using RBD peptides synthesized onto a hydrophilic scaffold and analysed by mass spectrometry. The samples captured by the RBD peptide returned statistically significantly matches for cytokeratin 8, 18 and 19 as well as microtubule-actin crosslinking factor 1, which may indicate a novel interaction between SHBG and these proteins, but ultimately failed to detect a membrane receptor potentially responsible for the putative RSHBG-mediated signaling. This PhD project has reported the proteolytic processing of SHBG by two members of the kallikrein family, KLK4 and KLK14. The effect of SHBG proteolysis by KLK4 and KLK14 on RSHBG-mediated signaling activation was unable to be determined as the reported signal transduction pathway was not activated after treatment with SHBG, in combination with either DHT or estradiol. However, the digestion of SHBG by these two proteases positively regulated androgen bioavailability to prostate cancer cells in vitro. The increased uptake of androgens is deleterious in prostate cancer due to the promotion of proliferation, metastasis, invasion and the inhibition of apoptosis. The increased bioavailability of androgens, from SHBG proteolysis by KLK4 and KLK14, may therefore promote both carcinogenesis and progression of prostate cancer. Finally, this information may contribute to the development of therapeutic treatment strategies for prostate cancer by inhibiting the proteolysis of SHBG, by KLK4 and KLK14, to prevent the increased uptake of androgens by hormone-dependent cancerous tissues.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

Influence of preexercise muscle glycogen content on transcriptional activity of metabolic and myogenic genes in well-trained humans

To determine whether pre-exercise muscle glycogen content influences the transcription of several early-response genes involved in the regulation of muscle growth, seven male strength-trained subjects performed one-legged cycling exercise to exhaustion to lower muscle glycogen levels (Low) in one leg compared with the leg with normal muscle glycogen (Norm) and then the following day completed a unilateral bout of resistance training (RT). Muscle biopsies from both legs were taken at rest, immediately after RT, and after 3 h of recovery. Resting glycogen content was higher in the control leg (Norm leg) than in the Low leg (435 ± 87 vs. 193 ± 29 mmol/kg dry wt; P < 0.01). RT decreased glycogen content in both legs (P < 0.05), but postexercise values remained significantly higher in the Norm than the Low leg (312 ± 129 vs. 102 ± 34 mmol/kg dry wt; P < 0.01). GLUT4 (3-fold; P < 0.01) and glycogenin mRNA abundance (2.5-fold; not significant) were elevated at rest in the Norm leg, but such differences were abolished after exercise. Preexercise mRNA abundance of atrogenes was also higher in the Norm compared with the Low leg [atrogin: ?14-fold, P < 0.01; RING (really interesting novel gene) finger: ?3-fold, P < 0.05] but decreased for atrogin in Norm following RT (P < 0.05). There were no differences in the mRNA abundance of myogenic regulatory factors and IGF-I in the Norm compared with the Low leg. Our results demonstrate that 1) low muscle glycogen content has variable effects on the basal transcription of select metabolic and myogenic genes at rest, and 2) any differences in basal transcription are completely abolished after a single bout of heavy resistance training. We conclude that commencing resistance exercise with low muscle glycogen does not enhance the activity of genes implicated in promoting hypertrophy.

Actions for declaratory or injunctive relief by the Corporate Regulator under s 471B of the Corporations Act

This article by Ben McEniery discusses the matters a court will consider when leave to commence or proceed against a company in liquidation is sought not by a creditor seeking to prove a debt, but by the corporate regulator pursuing declaratory or injunctive relief.

Temporal tracking of mineralization and transcriptional developments of shell formation during the early life history of pearl oyster Pinctada maxima

Molluscan larval ontogeny is a highly conserved process comprising three principal developmental stages. A characteristic unique to each of these stages is shell design, termed prodissoconch I, prodissoconch II and dissoconch. These shells vary in morphology, mineralogy and microstructure. The discrete temporal transitions in shell biomineralization between these larval stages are utilized in this study to investigate transcriptional involvement in several distinct biomineralization events. Scanning electron microscopy and X-ray diffraction analysis of P. maxima larvae and juveniles collected throughout post-embryonic ontogenesis, document the mineralogy and microstructure of each shelled stage as well as establishing a timeline for transitions in biomineralization. P. maxima larval samples most representative of these biomineralization distinctions and transitions were analyzed for differential gene expression on the microarray platform PmaxArray 1.0. A number of transcripts are reported as differentially expressed in correlation to the mineralization events of P. maxima larval ontogeny. Some of those isolated are known shell matrix genes while others are novel; these are discussed in relation to potential shell formation roles. This interdisciplinary investigation has linked the shell developments of P. maxima larval ontogeny with corresponding gene expression profiles, furthering the elucidation of shell biomineralization.

Characterisation of the TaNF-Y family of transcription factors in wheat

Light plays a unique role for plants as it is both a source of energy for growth and a signal for development. Light captured by the pigments in the light harvesting complexes is used to drive the synthesis of the chemical energy required for carbon assimilation. The light perceived by photoreceptors activates effectors, such as transcription factors (TFs), which modulate the expression of light-responsive genes. Recently, it has been speculated that increasing the photosynthetic rate could further improve the yield potential of three carbon (C3) crops such as wheat. However, little is currently known about the transcriptional regulation of photosynthesis genes, particularly in crop species. Nuclear factor Y (NF-Y) TF is a functionally diverse regulator of growth and development in the model plant species, with demonstrated roles in embryo development, stress response, flowering time and chloroplast biogenesis. Furthermore, a light-responsive NF-Y binding site (CCAAT-box) is present in the promoter of a spinach photosynthesis gene. As photosynthesis genes are co-regulated by light and co-regulated genes typically have similar regulatory elements in their promoters, it seems likely that other photosynthesis genes would also have light-responsive CCAAT-boxes. This provided the impetus to investigate the NF-Y TF in bread wheat. This thesis is focussed on wheat NF-Y members that have roles in light-mediated gene regulation with an emphasis on their involvement in the regulation of photosynthesis genes. NF-Y is a heterotrimeric complex, comprised of the three subunits NF-YA, NF-YB and NF-YC. Unlike the mammalian and yeast counterparts, each of the three subunits is encoded by multiple genes in Arabidopsis. The initial step taken in this study was the identification of the wheat NF-Y family (Chapter 3). A search of the current wheat nucleotide sequence databases identified 37 NF-Y genes (10 NF-YA, 11 NF-YB, 14 NF-YC & 2 Dr1). Phylogenetic analysis revealed that each of the three wheat NF-Y (TaNF-Y) subunit families could be divided into 4-5 clades based on their conserved core regions. Outside of the core regions, eleven motifs were identified to be conserved between Arabidopsis, rice and wheat NF-Y subunit members. The expression profiles of TaNF-Y genes were constructed using quantitative real-time polymerase chain reaction (RT-PCR). Some TaNF-Y subunit members had little variation in their transcript levels among the organs, while others displayed organ-predominant expression profiles, including those expressed mainly in the photosynthetic organs. To investigate their potential role in light-mediated gene regulation, the light responsiveness of the TaNF-Y genes were examined (Chapters 4 and 5). Two TaNF-YB and five TaNF-YC members were markedly upregulated by light in both the wheat leaves and seedling shoots. To identify the potential target genes of the light-upregulated NF-Y subunit members, a gene expression correlation analysis was conducted using publically available Affymetrix Wheat Genome Array datasets. This analysis revealed that the transcript expression levels of TaNF-YB3 and TaNF-YC11 were significantly correlated with those of photosynthesis genes. These correlated express profiles were also observed in the quantitative RT-PCR dataset from wheat plants grown under light and dark conditions. Sequence analysis of the promoters of these wheat photosynthesis genes revealed that they were enriched with potential NF-Y binding sites (CCAAT-box). The potential role of TaNF-YB3 in the regulation of photosynthetic genes was further investigated using a transgenic approach (Chapter 5). Transgenic wheat lines constitutively expressing TaNF-YB3 were found to have significantly increased expression levels of photosynthesis genes, including those encoding light harvesting chlorophyll a/b-binding proteins, photosystem I reaction centre subunits, a chloroplast ATP synthase subunit and glutamyl-tRNA reductase (GluTR). GluTR is a rate-limiting enzyme in the chlorophyll biosynthesis pathway. In association with the increased expression of the photosynthesis genes, the transgenic lines had a higher leaf chlorophyll content, increased photosynthetic rate and had a more rapid early growth rate compared to the wild-type wheat. In addition to its role in the regulation of photosynthesis genes, TaNF-YB3 overexpression lines flower on average 2-days earlier than the wild-type (Chapter 6). Quantitative RT-PCR analysis showed that there was a 13-fold increase in the expression level of the floral integrator, TaFT. The transcript levels of other downstream genes (TaFT2 and TaVRN1) were also increased in the transgenic lines. Furthermore, the transcript levels of TaNF-YB3 were significantly correlated with those of constans (CO), constans-like (COL) and timing of chlorophyll a/b-binding (CAB) expression 1 [TOC1; (CCT)] domain-containing proteins known to be involved in the regulation of flowering time. To summarise the key findings of this study, 37 NF-Y genes were identified in the crop species wheat. An in depth analysis of TaNF-Y gene expression profiles revealed that the potential role of some light-upregulated members was in the regulation of photosynthetic genes. The involvement of TaNF-YB3 in the regulation of photosynthesis genes was supported by data obtained from transgenic wheat lines with increased constitutive expression of TaNF-YB3. The overexpression of TaNF-YB3 in the transgenic lines revealed this NF-YB member is also involved in the fine-tuning of flowering time. These data suggest that the NF-Y TF plays an important role in light-mediated gene regulation in wheat.

Cyclin-dependent kinase-mediated phosphorylation of RBP1 and pRb promotes their dissociation to mediate release of the SAP30·mSin3·HDAC transcriptional repressor complex

Eukaryotic cell cycle progression is mediated by phosphorylation of protein substrates by cyclin-dependent kinases (CDKs). A critical substrate of CDKs is the product of the retinoblastoma tumor suppressor gene, pRb, which inhibits G1-S phase cell cycle progression by binding and repressing E2F transcription factors. CDK-mediated phosphorylation of pRb alleviates this inhibitory effect to promote G1-S phase cell cycle progression. pRb represses transcription by binding to the E2F transactivation domain and recruiting the mSin3·histone deacetylase (HDAC) transcriptional repressor complex via the retinoblastoma-binding protein 1 (RBP1). RBP1 binds to the pocket region of pRb via an LXCXE motif and to the SAP30 subunit of the mSin3·HDAC complex and, thus, acts as a bridging protein in this multisubunit complex. In the present study we identified RBP1 as a novel CDK substrate. RBP1 is phosphorylated by CDK2 on serines 864 and 1007, which are N- and C-terminal to the LXCXE motif, respectively. CDK2-mediated phosphorylation of RBP1 or pRb destabilizes their interaction in vitro, with concurrent phosphorylation of both proteins leading to their dissociation. Consistent with these findings, RBP1 phosphorylation is increased during progression from G 1 into S-phase, with a concurrent decrease in its association with pRb in MCF-7 breast cancer cells. These studies provide new mechanistic insights into CDK-mediated regulation of the pRb tumor suppressor during cell cycle progression, demonstrating that CDK-mediated phosphorylation of both RBP1 and pRb induces their dissociation to mediate release of the mSin3·HDAC transcriptional repressor complex from pRb to alleviate transcriptional repression of E2F.

ATF5, a possible regulator of osteogenic differentiation in human adipose-derived stem cells

The regulatory pathways involved in maintaining the pluripotency of embryonic stem cells are partially known, whereas the regulatory pathways governing adult stem cells and their "stem-ness" are characterized to an even lesser extent. We, therefore, screened the transcriptome profiles of 20 osteogenically induced adult human adipose-derived stem cell (ADSC) populations and investigated for putative transcription factors that could regulate the osteogenic differentiation of these ADSC. We studied a subgroup of donors' samples that had a disparate osteogenic response transcriptome from that of induced human fetal osteoblasts and the rest of the induced human ADSC samples. From our statistical analysis, we found activating transcription factor 5 (ATF5) to be significantly and consistently down-regulated in a randomized time-course study of osteogenically differentiated adipose-derived stem cells from human donor samples. Knockdown of ATF5 with siRNA showed an increased sensitivity to osteogenic induction. This evidence suggests a role for ATF5 in the regulation of osteogenic differentiation in adipose-derived stem cells. To our knowledge, this is the first report that indicates a novel role of transcription factors in regulating osteogenic differentiation in adult or tissue specific stem cells. © 2012 Wiley Periodicals, Inc.

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.