- Comparative genomics of pathogenic yeast
- Integrated data analysis for discovery of biologically important patterns in networks of protein and gene interactions
- Spatio-Temporal Dynamics of Cell Signalling
- Advanced computational and NMR studies of GIP with extracellular domain of GPCR
- Bioinformatic and Molecular Analysis of Alternative Transcript Expression in Malignant Melanoma
- Functional genomics and systems biology of mycobacteria-macrophage interactions in cattle
- Modelling the evolution of protein interactions and discovery of protein sequence motif/oligopeptide mediated signalling
- Discovery of oligopeptides modulating platelet signalling processes
- Computational modeling of structurally constrained peptides as peptide mimetics
The Butler group at the Conway Institute, University College Dublin, is part of an international consortium that has sequenced and annotated 6 Candida genomes. Our main focus is on Candida parapsilosis, a yeast that causes disease in premature infants and immune compromised individuals. We have designed the first microarrays for use in this species, and we have identified regulators that are important for biofilm development and pathogenesis. The formation of biofilms (living mats) on indwelling medical devices is an important source of infection. We are using state-of-the-art technology (including Illumina/Solexa sequencing for RNA-seq and ChIP-seq) to investigate the transcriptional networks involved. We also exploit the significant genomic resources available to compare pathways within species. The PhD student will contribute to a project developing the use of RNA-seq and ChIP-seq for newly sequenced genomes. He/she will also develop methods fro transcriptional profiling analysis using RNA-seq. The project will begin as soon as possible, or during the summer of 2009. Applications should be made directly to Dr Geraldine Butler (email@example.com) before 1st March 2009. More details available at: http://www.ucd.ie/biochem/gb/Lab/
Integrated data analysis for discovery of biologically important patterns in networks of protein and gene interactionsSupervisors: Gerard Cagney, Denis Shields
Understanding of protein signaling networks is being driven by the emergence of large databases of protein physical pairwise interactions, protein physical co-complex membership, and gene pairwise functional interactions. These often provide insights into the cross-talk between complexes in different signaling processes. However, how can we tell if a suggested cross-talk is of strong interest, or a chance observation, relying on only one piece of data to support it? This project will combine evidence from multiple sources to characterize these interesting regions of signaling networks. The pattern of distribution of gene and protein properties, (including sequence motifs and domains), and of small network motifs across the larger network will be investigated. As the project is part of a multi-disciplinary programme, there will be opportunities and supports to explore techniques from bioinformatics, from network visualization, from statistical network modeling, and from computer science, as well as opportunities to take part in experimental validation of the models generated.
Spatio-Temporal Dynamics of Cell Signalling - Getting Understanding of Protein Activity Gradients and Propagation of Spatial InformationSupervisors: Boris N. Kholodenko (in collaboration with Zoltan Neufeld and Ted Cox)
During evolution, cells have developed mechanisms for precise sensing of the positional information and spatial guidance of signalling processes. This spatial regulation of signalling is pivotal for controlling physiological processes, such as cell division, motility and migration. The existence of protein activity gradients within a cell was first proposed theoretically , and later these gradients were discovered in live cells. For example, spatial gradients of phosphorylated aurora B kinase and its substrates were proposed to provide a mechanism to communicate the chromosome location in anaphase, the stage of cell division when sister chromosomes move to opposite poles of the cell . Without precise spatial cues, cell division, and more importantly life, as we know it could not exist. Another example includes the small GTPase Ran and stathmin-oncoprotein 18, which regulate the mitotic spindle assembly. Yet, how these spatial cues are generated by signalling networks remains poorly understood. Moreover, how spatial information propagates through signalling cascades and how this depends on the cascade structure and dynamics are unsolved problems in cell biology.
This project is aimed at understanding how signaling networks can transmit precise spatial information in a dynamic and robust manner to control the execution of spatially resolved cellular processes. Critical to gaining this understanding will be the development of mathematical, reaction-diffusion models of the GTPase and kinase/phosphatase signaling cascades, which control pivotal cellular processes. The models will be based on experimental data and will explain and predict the complex spatio-temporal dynamics of these cascades, including the generation of positional cues and propagating waves of protein activities [3-5]. Computational models will be based primarily on ordinary and partial differential equations, although stochastic methods and probabilistic approaches may also be used. Applicants should have a genuine interest in modeling of biological processes and experience with nonlinear dynamics and numerical calculations. Although the work will mostly involve theoretical/computational modelling, there will be some participation in experimental work.References to start reading:
- Brown, G. C. & Kholodenko, B. N. Spatial gradients of cellular phospho-proteins. (1999) FEBS Lett, 457, 452-454. (Spatial segregation of opposing reactions, e.g., kinase and phosphatase, in a protein-modification cycle was shown to be a basic prerequisite for signalling gradients).
- Fuller BG et al Midzone activation of aurora B in anaphase produces an intracellular phosphorylation gradient. Nature. 2008 May 7. [Epub ahead of print].
- Markevich, N., Hoek, J. B. & Kholodenko, B. N. (2004). Signaling switches and bistability arising from multisite phosphorylation in protein kinase cascades. J Cell Biology, 164, 353-359. (A general model of the ERK cycle that leads to bistability).
- Markevich, N., Tsyganov MA, Hoek, J. B. & Kholodenko, B. N. (2006) Long-range signaling by phosphoprotein waves arising from bistability in protein kinase cascades. Mol Syst Biol. 2006; 2:61. PMID: 17102806 (A general model of spatio-temporal dynamics for MAPK or other kinase/phosphatase cascades).
- Stelling, J & Kholodenko, B.N. Signaling cascades as cellular devices for spatial computations. J. Math. Biol. (2008) PMID: 18283462 (Initial, simple models of spatial gradients arising in GTPase cascades with feedforward loops and spatial separation of activating and deactivation enzymes)
- Kholodenko, B. N. (2006) Cell-signalling dynamics in time and space, Nat Rev Mol Cell Biol. 7, 165-176. (Explanations of some general modelling concepts and complex non-linear dynamic behaviour. Simple positive negative cascade models that display bistability and oscillations).
It is estimated that more than 250 million people worldwide suffer from type 2 diabetes and WHO estimate these numbers will double in the next 20 years. These vulnerable people are five times more likely to suffer from heart disease and three times more likely to have a stroke or related complications. The cost of treating diabetes and its complications is substantial, currently estimated at up to 10% of the total health budget in European Union. Currently available drugs are not ideal and therefore considerable interest in the pharmaceutical industry in the development of potential new drugs for type 2 diabetes.
Glucose-dependent insulinotropic polypeptide (GIP) is a hormone that stimulates the secretion of insulin into the bloodstream after meal ingestion upon binding to a 7-transmembrane G-protein coupled receptor (GPCR). However, this function is lost in diabetic patients. Recent studies in our laboratory identified the structurally important bioactive conformation of the GIP ligand in variety of media showing biologically important residues which recognise the receptor. In this proposal we would like to develop advanced bioinformatics and computational tools to study the GIP ligand interactions with its GPCR receptor which would be useful for understanding of drug binding process. Understanding of the structural and functional properties of GIP bound to its receptor should lead to the design of drugs towards the Class B family GPCR receptors. This will advance the field of therapeutic peptide or non-peptide drug development with implications for the treatment of type 2 diabetes and other related diseases.
- Bioactive conformation of glucose-dependent insulinotropic polypeptide by NMR and CD spectroscopy.
Alana I, Malthouse JP, O'Harte FP, Hewage CM.
PROTEINS: Structure, Func and Bioinfor., 2007, 68(1):92-9.
- NMR and alanine scan studies of glucose-dependent insulinotropic polypeptide in water
Alana I, Parker JC, Gault VA, Flatt PR, O'Harte FP, Malthouse JP, Hewage CM.
J Biol Chem. 2006, 281, 16370-6.
Malignant melanoma is a very aggressive form of skin cancer, which fails to respond to conventional chemotherapy and spreads rapidly to other parts of the body. In this project, we wish to study, on both bioinformatic and molecular levels, alternative splicing of transcripts in melanoma, and how these phenomena may contribute to the disease. Prof. Gallagher’s group has recently performed DNA microarray-based transcriptomic profiling using Affymetrix exon arrays on a series of isogenic melanoma cell lines that mimic progression from an early melanoma to a late metastatic stage. These exon arrays provide differential mRNA expression and alternative splicing data for all annotated transcripts/genes in the cell. The PhD student will first analyse these data to determine at the mRNA level what alterations in gene expression and alternative splicing are associated with progression, from the early to late stage melanoma cell lines.
Initially, the tools for analysis of exon arrays were quite rudimentary. However, the R/BioConductor project has recently developed newer tools to more fully exploit the potential of this platform. The student will apply these techniques to identify exon skip events at the mRNA level in the melanoma cell lines. A complementary approach to the identification of splice isoforms in proteomics data has been developed recently by Dr. Ó Gaora and co-workers. Databases representing potential exon skip events in each of the human, mouse and rat genomes have been generated. These databases house the theoretical trypsin junction peptides derived from all possible exon skip events according to the latest annotations of the genomes available from Ensembl. Using the in-house proteomics pipeline, Proline, we have already identified several novel splice isoforms in breast cancer cell lines and are currently carrying out a large scale screen of exon skip events in platelets. The student will apply this approach to identify alternative splice events at the protein level in the cell lines described above. Exon skipping accounts for approximately 75% of AS events.
To identify other types of AS events a new methodology will be developed. Protein identifications from standard databases (e.g. IPI) will be saved and three-frame translations of each encoding gene will be generated and saved to a temporary, sample-specific database. Unidentified spectra from that sample will then be searched against this database with a view to identifying events such as alternative 5' or 3' splice sites or intron retention. By dynamically creating a database using the prior knowledge of bona fide identifications within the sample, the search space is dramatically reduced, making such a genome-based method feasible and indeed highly practical. A set of alternatively spliced transcripts which represent different melanoma stages will then be validated by RT-PCR analysis in melanoma cell lines and tissues. To this end, Prof. Gallagher’s group has already extracted RNA from 150 melanoma tumours and 70 benign nevi (normal skin). Overall, this combined approach will provide new insights into the role of alternative transcript expression in melanoma progression. Expected split between bioinformatics and wet-lab activities would be 70/30, respectively.
Host recognition of bacterial pathogens is a critical component of the host immune response. Macrophages are evolutionarily ancient cells that express innate immune receptors for antigen recognition known as pathogen recognition receptors (PRRs). Macrophages initiate the inflammatory response via an extensive repertoire of PRRs, including the Toll-like receptors (TLRs) that drive the subsequent immune response through phagocytosis, release of cytotoxic granules, and production of cytokines and other effector molecules including antimicrobial peptides (AMPs). Pathogenic mycobacteria such as Mycobacterium bovis (the causative agents of tuberculosis in cattle) can survive and grow within host cells, particularly macrophages. These bacterial species have evolved sophisticated immunoevasion and immunomodulatory strategies to subvert and avoid the bactericidal properties of the macrophage.
The primary aim of the proposed project is to use a systems biology approach to analyse a large Affymetrix GeneChip® gene expression data set generated from in vitro studies of macrophages stimulated with M. bovis, M. avium subsp. paratuberculosis and attenuated M. bovis (BCG). These analyses will shed light on the immune response to mycobacterial infections, and in particular, will identify host genes, pathways and gene networks involved in interactions between the macrophage and mycobacterial pathogens. Results from these investigations will guide follow-on bioinformatics, functional genomics, proteomics, comparative immunology and structural genomics work.
Modelling the evolution of protein interactions and discovery of protein sequence motif/oligopeptide mediated signallingSupervisor: Denis Shields, UCD; funding: Science Foundation Ireland
How do protein interactions evolve? Are interactions mediated by short protein sequence motifs, which can easily evolve convergently in unrelated proteins, an important driver of functional change during the evolution of protein interaction networks? The objective of this project is to identify how often the ease with which short protein motifs can evolve from scratch has been exploited in the re-wiring of protein interaction networks during evolution. The student will develop methods for evolutionary modelling of ancestral sequence states of functional motifs and interactions, as well as of protein domains. The student will additionally get some experimental laboratory training in assessing the biological function of ancestrally predicted motifs.
Palmitylated oligopeptides can alter transmembrane protein activity, acting on their cytoplasmic signaling (Nature Chem Biol 3:108-112). Platelets play a key role in thrombosis. The project is to apply bioinformatic methods (http://bioware.ucd.ie) to identify motifs involved in integrin and other adhesion protein signaling in platelets, followed by experimental validation, including competition assays and peptide arrays. By determining which pathways or interacting proteins the peptides are modulating, the ultimate goal is to improve understanding of how platelet signaling works, and can be therapeutically modified.
Short peptide contacts between proteins represent a potential target for modulating protein-protein interactions. Short peptides synthesized independently of their parent proteins may have bioactivity, but often lack strong binding affinity, making them less useful as potential drugs. Constraining the peptide’s rotational freedom (e.g. cyclising the peptide) often yields substantial increases in binding affinity. This project is focused on the development of a large computational library of synthesisable constrained peptides. These will then be docked computationally to a set of structurally known peptide binding domains. A number of the most interesting compounds that mimic important peptides will be synthesized in the laboratory and tested experimentally. This project may suit a student with a background in chemistry and an aptitude for computer programming.