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.

The structures of COPI-coated vesicles reveal alternate coatomer conformations and interactions

Transport between compartments of eukaryotic cells is mediated by coated vesicles. The archetypal protein coats COPI, COPII, and clathrin are conserved from yeast to human. Structural studies of COPII and clathrin coats assembled in vitro without membranes suggest that coat components assemble regular cages with the same set of interactions between components. Detailed three-dimensional structures of coated membrane vesicles have not been obtained. Here, we solved the structures of individual COPI-coated membrane vesicles by cryoelectron tomography and subtomogram averaging of in vitro reconstituted budding reactions. The coat protein complex, coatomer, was observed to adopt alternative conformations to change the number of other coatomers with which it interacts and to form vesicles with variable sizes and shapes. This represents a fundamentally different basis for vesicle coat assembly.

Proteolytic activation of Chlamydia trachomatis HTRA is mediated by PDZ1 domain interactions with protease domain loops L3 and LC and beta strand β5

Chlamydia trachomatis is a bacterial pathogen responsible for one of the most prevalent sexually transmitted infections worldwide. Its unique development cycle has limited our understanding of its pathogenic mechanisms. However, CtHtrA has recently been identified as a potential C. trachomatis virulence factor. CtHtrA is a tightly regulated quality control protein with a monomeric structural unit comprised of a chymotrypsin-like protease domain and two PDZ domains. Activation of proteolytic activity relies on the C-terminus of the substrate allosterically binding to the PDZ1 domain, which triggers subsequent conformational change and oligomerization of the protein into 24-mers enabling proteolysis. This activation is mediated by a cascade of precise structural arrangements, but the specific CtHtrA residues and structural elements required to facilitate activation are unknown. Using in vitro analysis guided by homology modeling, we show that the mutation of residues Arg362 and Arg224, predicted to disrupt the interaction between the CtHtrA PDZ1 domain and loop L3, and between loop L3 and loop LD, respectively, are critical for the activation of proteolytic activity. We also demonstrate that mutation to residues Arg299 and Lys160, predicted to disrupt PDZ1 domain interactions with protease loop LC and strand β5, are also able to influence proteolysis, implying their involvement in the CtHtrA mechanism of activation. This is the first investigation of protease loop LC and strand β5 with respect to their potential interactions with the PDZ1 domain. Given their high level of conservation in bacterial HtrA, these structural elements may be equally significant in the activation mechanism of DegP and other HtrA family members.

Interactions between hypoxia and epidermal growth factor receptor in non-small-cell-lung cancer

Tumor hypoxia has been recognized to confer resistance to anticancer therapy since the early 20th century. More recently, its fundamental role in tumorigenesis has been established. Hypoxia-inducible factor (HIF)-1 has been identified as an important transcription factor that mediates the cellular response to hypoxia, promoting both cellular survival and apoptosis under different conditions. Increased tumor cell expression of this transcription factor promotes tumor growth In vivo and is associated with a worse prognosis in patients with non-small-cell lung cancer (NSCLC) undergoing tumor resection. The epidermal growth factor receptor (EGFR) promotes tumor cell proliferation and anglogenesis and inhibits apoptosis. Epidermal growth factor receptor expression increases in a stepwise manner during tumorigenesis and is overexpressed in > 50% of NSCLC tumors. This review discusses the reciprocal relationship between tumor cell hypoxia and EGFR. Recent studies suggest that hypoxia induces expression of EGFR and its ligands. In return, EGFR might enhance the cellular response to hypoxia by increasing expression of HIF-1α, and so act as a survival factor for hypoxic cancer cells. Immunohistochemical studies on a series of resected NSCLC tumors add weight to this contention by demonstrating a close association between expression of EGFR, HIF-1α, and:1 of HIF-1's target proteins, carbonic anhydrase IX. In this article we discuss emerging treatment strategies for NSCLC that target HIF-1, HIF-1 transcriptional targets, and EGFR.

Paracrine interactions between LNCaP prostate cancer cells and bioengineered bone in 3D in vitro culture reflect molecular changes during bone metastasis

As microenvironmental factors such as three-dimensionality and cell–matrix interactions are increasingly being acknowledged by cancer biologists, more complex 3D in vitro models are being developed to study tumorigenesis and cancer progression. To better understand the pathophysiology of bone metastasis, we have established and validated a 3D indirect co-culture model to investigate the paracrine interactions between prostate cancer (PCa) cells and human osteoblasts. Co-culture of the human PCa, LNCaP cells embedded within polyethylene glycol hydrogels with human osteoblasts in the form of a tissue engineered bone construct (TEB), resulted in reduced proliferation of LNCaP cells. LNCaP cells in both monoculture and co-culture were responsive to the androgen analog, R1881, as indicated by an increase in the expression (mRNA and/or protein induction) of androgen-regulated genes including prostate specific antigen and fatty acid synthase. Microarray gene expression analysis further revealed an up-regulation of bone markers and other genes associated with skeletal and vasculature development and a significant activation of transforming growth factor β1 downstream genes in LNCaP cells after co-culture with TEB. LNCaP cells co-cultured with TEB also unexpectedly showed similar changes in classical androgen-responsive genes under androgen-deprived conditions not seen in LNCaP monocultures. The molecular changes of LNCaP cells after co-culturing with TEBs suggest that osteoblasts exert a paracrine effect that may promote osteomimicry and modulate the expression of androgen-responsive genes in LNCaP cells. Taken together, we have presented a novel 3D in vitro model that allows the study of cellular and molecular changes occurring in PCa cells and osteoblasts that are relevant to metastatic colonization of bone. This unique in vitro model could also facilitate cancer biologists to dissect specific biological hypotheses via extensive genomic or proteomic assessments to further our understanding of the PCa-bone crosstalk.

RAD51-associated Protein 1 (RAD51AP1) Interacts with the Meiotic Recombinase DMC1 through a Conserved Motif

Homologous recombination (HR) reactions mediated by the RAD51 recombinase are essential for DNA and replication fork repair, genome stability, and tumor suppression. RAD51-associated protein 1 (RAD51AP1) is an important HR factor that associates with and stimulates the recombinase activity of RAD51. We have recently shown that RAD51AP1 also partners with the meiotic recombinase DMC1, displaying isoform-specific interactions with DMC1. Here, we have characterized the DMC1 interaction site in RAD51AP1 by a series of truncations and point mutations to uncover a highly conserved WVPP motif critical for DMC1 interaction but dispensable for RAD51 association. This RAD51AP1 motif is reminiscent of the FVPP motif in the tumor suppressor protein BRCA2 that mediates DMC1 interaction. These results further implicate RAD51AP1 in meiotic HR via RAD51 and DMC1.

Molecular basis for enhancement of the meiotic DMC1 recombinase by RAD51 associated protein 1 (RAD51AP1)

Homologous recombination is needed for meiotic chromosome segregation, genome maintenance, and tumor suppression. RAD51AP1 (RAD51 associated protein 1) has been shown to interact with and enhance the recombinase activity of RAD51. Accordingly, genetic ablation of RAD51AP1 leads to enhanced sensitivity to and also chromosome aberrations upon DNA damage, demonstrating a role for RAD51AP1 in mitotic homologous recombination. Here we show physical association of RAD51AP1 with the meiosis-specific recombinase DMC1 and a stimulatory effect of RAD51AP1 on the DMC1-mediated D-loop reaction. Mechanistic studies have revealed that RAD51AP1 enhances the ability of the DMC1 presynaptic filament to capture the duplex-DNA partner and to assemble the synaptic complex, in which the recombining DNA strands are homologously aligned. We also provide evidence that functional cooperation is dependent on complex formation between DMC1 and RAD51AP1 and that distinct epitopes in RAD51AP1 mediate interactions with RAD51 and DMC1. Finally, we show that RAD51AP1 is expressed in mouse testes, and that RAD51AP1 foci colocalize with a subset of DMC1 foci in spermatocytes. These results suggest that RAD51AP1 also serves an important role in meiotic homologous recombination.

Drosophila 3′ UTRs are more complex than protein-coding sequences

The 3′ UTRs of eukaryotic genes participate in a variety of post-transcriptional (and some transcriptional) regulatory interactions. Some of these interactions are well characterised, but an undetermined number remain to be discovered. While some regulatory sequences in 3′ UTRs may be conserved over long evolutionary time scales, others may have only ephemeral functional significance as regulatory profiles respond to changing selective pressures. Here we propose a sensitive segmentation methodology for investigating patterns of composition and conservation in 3′ UTRs based on comparison of closely related species. We describe encodings of pairwise and three-way alignments integrating information about conservation, GC content and transition/transversion ratios and apply the method to three closely related Drosophila species: D. melanogaster, D. simulans and D. yakuba. Incorporating multiple data types greatly increased the number of segment classes identified compared to similar methods based on conservation or GC content alone. We propose that the number of segments and number of types of segment identified by the method can be used as proxies for functional complexity. Our main finding is that the number of segments and segment classes identified in 3′ UTRs is greater than in the same length of protein-coding sequence, suggesting greater functional complexity in 3′ UTRs. There is thus a need for sustained and extensive efforts by bioinformaticians to delineate functional elements in this important genomic fraction. C code, data and results are available upon request.

Modeling of protein signaling networks in clinical proteomics

Molecular interactions that underlie pathophysiological states are being elucidated using techniques that profile proteomicend points in cellular systems. Within the field of cancer research, protein interaction networks play pivotal roles in the establishment and maintenance of the hallmarks of malignancy, including cell division, invasion, and migration. Multiple complementary tools enable a multifaceted view of how signal protein pathway alterations contribute to pathophysiological states.One pivotal technique is signal pathway profiling of patient tissue specimens. This microanalysis technology provides a proteomic snapshot at one point in time of cells directly procured from the native context of a tumor micro environment. To study the adaptive patterns of signal pathway events over time, before and after experimental therapy, it is necessary to obtain biopsies from patients before, during, and after therapy. A complementary approach is the profiling of cultured cell lines with and without treatment. Cultured cell models provide the opportunity to study short-term signal changes occurring over minutes to hours. Through this type of system, the effects of particular pharmacological agents may be used to test the effects of signal pathway inhibition or activation on multiple endpoints within a pathway. The complexity of the data generated has necessitated the development of mathematical models for optimal interpretation of interrelated signaling pathways. In combination,clinical proteomic biopsy profiling, tissue culture proteomic profiling, and mathematical modeling synergistically enable a deeper understanding of how protein associations lead to disease states and present new insights into the design of therapeutic regimens.

Interaction of metal salts with cytoskeletal motor protein systems

Interactions of chemicals with the microtubular network of cells may lead to genotoxicity. Micronuclei (MN) might be caused by interaction of metals with tubulin and/or kinesin. The genotoxic effects of inorganic lead and mercury salts were studied using the MN assay and the CREST analysis in V79 Chinese hamster fibroblasts. Effects on the functional activity of motor protein systems were examined by measurement of tubulin assembly and kinesin-driven motility. Lead and mercury salts induced MN dose-dependently. The no-effect-concentration for MN induction was 1.1 μM PbCl2, 0.05 μM Pb(OAc)2 and 0.01 μM HgCl2. The in vitro results obtained for PbCl2 correspond to reported MN induction in workers occupationally exposed to lead, starting at 1.2 μM Hg(II) (Vaglenov et al., 2001, Environ. Health Perspect. 109, 295-298). The CREST Analysis indicate aneugenic effects of Pb(II) and aneugenic and additionally clastogenic effects of Hg(II). Lead (chloride, acetate, and nitrate) and mercury (chloride and nitrate) interfered dose-dependently with tubulin assembly in vitro. The no-effect-concentration for lead salts in this assay was 10 μM. Inhibition of tubulin assembly by mercury started at 2 μM. The gliding velocity of microtubules along immobilised kinesin molecules was affected by 25 μM Pb(NO3)2 and 0.1 μM HgCl2 in a dose-dependent manner. Our data support the hypothesis that lead and mercury genotoxicity may result, at least in part, via disturbance of chromosome segregation via interaction with cytoskeletal proteins.

Protein loaded mesoporous silica spheres as a controlled delivery platform

Background The adsorption of bovine serum albumin (BSA) onto mesoporous silica spheres (MPS) synthesized from silica colloids was studied employing real time in situ measurements. The stabilities of the BSA at different pH values, their isoelectric points and zeta potentials were determined in order to probe the interactions between the protein and the mesoporous silica. Results The pore size of MPS was designed for protein, and this, coupled with an in depth understanding of the physico-chemical characteristics of the protein and MPS has yielded a better binding capacity and delivery profile. The adsorption isotherm at pH 4.2 fitted the Langmuir model and displayed the highest adsorption capacity (71.43 mg mL-1 MPS). Furthermore, the delivery rates of BSA from the MPS under physiological conditions were shown to be dependent on the ionic strength of the buffer and protein loading concentration. Conclusion Economics and scale-up considerations of mesoporous material synthesized via destabilization of colloids by electrolyte indicate the scaleability and commercial viability of this technology as a delivery platform for biopharmaceutical applications.

Identification and characterization of novel proteolytic interactions of prostate cancer-expressed kallikrein-related peptidases, type II transmembrane serine proteases and matrix metalloproteinases

This study investigated interactions of protein-cleaving enzymes (or proteases) that promote prostate cancer progression. It provides the first evidence of a novel regulatory network of protease activity at the surface of cells. The proteases kallikrein-related peptidases 4 and 14, and matrix metalloproteinases 3 and 9 are cleaved at the cell surface by the cell surface proteases hepsin and TMPRSS2. These cleavage events potentially regulate activation of downstream targets of kallikrein 4 and 14 such as cell surface signalling via the protease-activated receptors (PARs) and cell growth-promoting factors such as hepatocyte-growth factor.

Investigation of the binding interactions between insulin and its receptor

This project investigated the interactions between insulin and its receptor. A combination of computational and experimental investigations resulted in the identification of four residues in non-canonical sites that, when mutated, had detrimental effects on insulin binding. An increased understanding of the binding mechanism will aid future research into diseases involving the insulin receptor and its relatives and could potentially lead to new therapeutic avenues to combat these health related issues.

Analysis on conservation of disulphide bonds and their structural features in homologous protein domain families

Background: Disulphide bridges are well known to play key roles in stability, folding and functions of proteins. Introduction or deletion of disulphides by site-directed mutagenesis have produced varying effects on stability and folding depending upon the protein and location of disulphide in the 3-D structure. Given the lack of complete understanding it is worthwhile to learn from an analysis of extent of conservation of disulphides in homologous proteins. We have also addressed the question of what structural interactions replaces a disulphide in a homologue in another homologue. Results: Using a dataset involving 34,752 pairwise comparisons of homologous protein domains corresponding to 300 protein domain families of known 3-D structures, we provide a comprehensive analysis of extent of conservation of disulphide bridges and their structural features. We report that only 54% of all the disulphide bonds compared between the homologous pairs are conserved, even if, a small fraction of the non-conserved disulphides do include cytoplasmic proteins. Also, only about one fourth of the distinct disulphides are conserved in all the members in protein families. We note that while conservation of disulphide is common in many families, disulphide bond mutations are quite prevalent. Interestingly, we note that there is no clear relationship between sequence identity between two homologous proteins and disulphide bond conservation. Our analysis on structural features at the sites where cysteines forming disulphide in one homologue are replaced by non-Cys residues show that the elimination of a disulphide in a homologue need not always result in stabilizing interactions between equivalent residues. Conclusion: We observe that in the homologous proteins, disulphide bonds are conserved only to a modest extent. Very interestingly, we note that extent of conservation of disulphide in homologous proteins is unrelated to the overall sequence identity between homologues. The non-conserved disulphides are often associated with variable structural features that were recruited to be associated with differentiation or specialisation of protein function.

Fluctuations in protein synthesis from a single RNA template: Stochastic kinetics of ribosomes

Proteins are polymerized by cyclic machines called ribosomes, which use their messenger RNA (mRNA) track also as the corresponding template, and the process is called translation. We explore, in depth and detail, the stochastic nature of the translation. We compute various distributions associated with the translation process; one of them-namely, the dwell time distribution-has been measured in recent single-ribosome experiments. The form of the distribution, which fits best with our simulation data, is consistent with that extracted from the experimental data. For our computations, we use a model that captures both the mechanochemistry of each individual ribosome and their steric interactions. We also demonstrate the effects of the sequence inhomogeneities of real genes on the fluctuations and noise in translation. Finally, inspired by recent advances in the experimental techniques of manipulating single ribosomes, we make theoretical predictions on the force-velocity relation for individual ribosomes. In principle, all our predictions can be tested by carrying out in vitro experiments.