My research interests stem from the understanding and application of molecular evolution and bioinformatics. In this context, I seek to develop and apply bioinformatics techniques, including the development of novel bioinformatics software tools. The dominating technique in my research toolkit is biological sequence analysis but I am also interested in biological network analysis and applications of machine learning to biological questions. The questions I am addressing can be broadly subdivided into three main themes.
The molecular basis of protein-protein interactions in signalling networks.
My primary research interest is the structural and functional nature of protein-protein interactions (PPI). Of particular interest are Short Linear Motifs (SLiMs), which are short functional protein sequences that mediate transient PPI as ligands for other proteins. SLiMs, also referred to as linear motifs or minimotifs, play a central role in many diverse biological pathways and are particularly important in subcellular signalling networks; SLiM-mediated PPI include post-translational modifications, subcellular localisation, and ligand binding. SLiM identification is challenging and I am heavily involved in developing better bioinformatics algorithms and software tools for detecting both known and novel protein motifs in protein datasets.
This work is currently being funded by a BBSRC New Investigator Award (BB/I006230/1) "Integrated in silico prediction of protein interaction motifs using interactome networks and high-resolution 3-dimensional structures". The primary objective of this project is to integrate a number of leading computational techniques to predict novel SLiMs and, in so doing, add crucial detail to protein-protein interaction networks. Previously, I developed the most successful of these tools on benchmarking data, SLiMFinder, which accounts for both the evolutionary relationships found between input proteins and the total motif space being searched to estimate the statistical significance of over-represented motifs. My group is now benchmarking "Query SLiMFinder" (QSLiMFinder), an extension of SLiMFinder that uses knowledge regarding the site of interaction in one protein to reduce the motif search space and make the method much more sensitive. Once benchmarked, QSLiMFinder will be combined with tools for predicting regions of proteins involved in SLiM-mediated interactions from 3D structures of interacting proteins to perform a large-scale prediction of human domain-motif interactions.
Applications of bioinformatics and molecular evolution to experimental biology.
I have broad interests in most aspects of evolutionary biology and I am involved in several collaborative projects with experimental biologists. These projects are primarily driven by the domain specialist, with my primary contributions being bioinformatics pipeline development and shared supervision of a research team members. Predominantly, I collaborate in diverse projects relating to proteomic and genetic responses to environmental stresses, including ethanol response in C. elegans; drought response in poplar; CO2 response in Plantago; light response in marine algae; responses of marine organisms (coccoliths and coral) to climate change and ocean acidification. I also have some collaborations relating to microbiology and human pathogens including biofilm formation/evolution, proteomic analysis of chlamydia and the response of Pneumococcal bacteria to vaccination.
Post-transcriptional regulation of protein expression and function.
It is clear that gene expression only provides a very limited window into the activity of the main drivers of biological processes, namely proteins. I have an on-going interdisciplinary collaboration with the experimental group of Dr Mark Coldwell, asking the question: how does the ribosome choose where to start translating a protein? We are combining bioinformatics screens of the human and mouse transcriptomes with reporter assays developed in the Coldwell lab to identify candidates for non-canonical and multiple alternative initiation codons (AIC). Initial searches looked for upstream (5’) in-frame AIC candidates. Assays developed with pump-priming “Adventure in Research” funding from the University of Southampton suggest that the most efficient non-AUGs are CUG, ACG and GUG. We used these results to select human AIC candidates for an initial screen in a reporter assay as part of undergraduate research projects and identified a number of positive instances of AIC use. These data have subsequently formed the foundation of a further grant proposals under development to (1) increase the number of candidates screened; (2) investigate the role of cis- and trans¬- factors in AIC selection; (3) analyse possible roles of N-terminal extensions in protein interactions and subcellular localisation for genes shown to have AIC.
Matthew Allwright (2012)
Joseph Jenkins (2012)
Andreas Johannson (2011)
Alex Watson-Lazowski (2011)
Suzie Milner (2008)
Molecular and Cellular Biosciences
Affiliate research group(s)
Computational Modelling Group (CMG), Institute for Complex Systems Simulation (ICSS), Institute for Life Sciences (IfLS)
Utilising Populus to assess the flood tolerance mechanisms in repeated anoxic flooding events.
Large-scale prediction of functionally important protein-protein interaction motifs.
Using the model organism, Caenorhabditis elegans, to investigate the broad molecular, cellular and systems level impacts of acute and chronic ethanol treatment.
Combining bioinformatics and molecular biology to identify novel pathogen receptor proteins in marine crustaceans.
Comparison of genome-wide gene expression of parasitised and unparasitised larvae focuses on genes which play a role in the actual immune response.
Integrating leading computational techniques to predict novel protiein-protein interaction moitfs.
Combining bioinformatics searches with experimental data to broaden our knowledge of eukaryotic translation initiation.
Using NGS to investigate novel acclimations and adaptions to elevated atmosphere CO2 in Plantago lanceolata to help explain what the future environment holds for plants.
Using NGS technology and bioinformatics techniques to better understand the implications of drought for soil microbe communities.
Dr Richard J Edwards
Biological Sciences Faculty of Natural & Environmental Sciences Life Sciences Building 85 University of Southampton Highfield Campus Southampton SO17 1BJ
Room Number: 85/3001
Telephone: (023) 8059 3349
Dr Richard J Edwards's
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