SLiMFinder: a probabilistic method for identifying over-represented, convergently evolved, short linear motifs in proteins

Edwards RJ, Davey NE & Shields DC (2007): SLiMFinder: A probabilistic method for identifying over-represented, convergently evolved, short linear motifs in proteins. PLoS ONE 2(10): e967.

Abstract

BACKGROUND: Short linear motifs (SLiMs) in proteins are functional microdomains of fundamental importance in many biological systems. SLiMs typically consist of a 3 to 10 amino acid stretch of the primary protein sequence, of which as few as two sites may be important for activity, making identification of novel SLiMs extremely difficult. In particular, it can be very difficult to distinguish a randomly recurring “motif” from a truly over-represented one. Incorporating ambiguous amino acid positions and/or variable-length wildcard spacers between defined residues further complicates the matter.

METHODOLOGY/PRINCIPAL FINDINGS: In this paper we present two algorithms. SLiMBuild identifies convergently evolved, short motifs in a dataset of proteins. Motifs are built by combining dimers into longer patterns, retaining only those motifs occurring in a sufficient number of unrelated proteins. Motifs with fixed amino acid positions are identified and then combined to incorporate amino acid ambiguity and variable-length wildcard spacers. The algorithm is computationally efficient compared to alternatives, particularly when datasets include homologous proteins, and provides great flexibility in the nature of motifs returned. The SLiMChance algorithm estimates the probability of returned motifs arising by chance, correcting for the size and composition of the dataset, and assigns a significance value to each motif. These algorithms are implemented in a software package, SLiMFinder. SLiMFinder default settings identify known SLiMs with 100% specificity, and have a low false discovery rate on random test data.

CONCLUSIONS/SIGNIFICANCE: The efficiency of SLiMBuild and low false discovery rate of SLiMChance make SLiMFinder highly suited to high throughput motif discovery and individual high quality analyses alike. Examples of such analyses on real biological data, and how SLiMFinder results can help direct future discoveries, are provided. SLiMFinder is freely available for download under a GNU license from http://bioinformatics.ucd.ie/shields/software/slimfinder/.

PMID: 17912346

Rich Edwards (Principal Investigator)

Rich Edwards is a Principal Research Fellow in the University of Western Australia (UWA) Oceans Institute, and the lead academic for the Minderoo OceanOmics Centre at UWA. The centre is a collaboration between the Minderoo Foundation and UWA, supporting an ambitious research program to revolutionise the way that environmental DNA (eDNA) is used to monitor and protect marine vertebrate biodiversity. Rich leads the technical team that runs the centre, and an academic research program in evolutionary/conservation genomics. Here, the focus is collaborating with research groups across Australia (and taxa!) to generate high-quality genome assemblies in support of applications in conservation and evolutionary biology. Rich maintains an adjunct Associate Professor position in the School of Biotechnology and Biomolecular Sciences (BABS) at the University of New South Wales.

Originally from southern England, Rich trained a geneticist at the University of Nottingham (UK), studying the population genetics of transposable elements in bacteria for his PhD. He moved to Dublin (Ireland) in 2001 to become a full time bioinformatician in the Shields Lab, developing a sequence analysis methods for rational design of biologically active short peptides based on functional specificity and ancestral sequence prediction. The biological activity of these short peptides started an interest in Short Linear Motifs (SLiMs), which are short regions of proteins that mediate interactions with other proteins.

Rich has developed several tools for the prediction and analysis of SLiMs, distributed in the SLiMSuite package (as well as coining the term “SLiM” to describe this specific type of protein interaction motif). The lab was established in 2007 when Rich moved to the University of Southampton (UK), where he continued to work on SLiMs but diversified to collaborate on numerous projects involving DNA and/or protein sequence analysis.

Rich moved to UNSW in late 2013, where he has built a close working relationship with the Ramaciotti Centre for Genomics and established genomics as a core research activity. Here, he was involved in multiple de novo whole genome sequencing and assembly projects, using short read (Illumina), long read (PacBio & Nanopore) and linked read (10x Chromium) sequencing, and Hi-C proximity ligation. These include yeast, bacteria, invasive cane toads and starlings, venomous Australian snakes through the BABS Genome Project, Aussie marsupials as part of the Oz Mammals Genomics initiative, dogs, dingoes, rainforest trees, pathogenic rust fungi, and the NSW Waratah as part of the Genomics of Australian Plants initiative. In 2022, he moved to Perth to lead the Minderoo OceanOmics Centre at UWA, where he is heavily involved in marine vertebrate genome sequencing assembly with the Ocean Genomes project.

Employment History

• 2022-present: Principal Research Fellow, OceanOmics Centre and Laboratory Lead, Ocean Genomes Laboratory. UWA Oceans Institute, University of Western Australia.
• 2022-present: Adjunct Associate Professor in Genomics and Bioinformatics. School of Biotechnology and Biomolecular Sciences, University of New South Wales, Australia.
• 2013-2022: Senior Lecturer. School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia.
• 2014-2016: Adjunct Associate Professor. Centre for Biological Sciences, University of Southampton, Southampton SO17 1BJ, UK.
• 2013-2014: Senior Lecturer. Centre for Biological Sciences, University of Southampton, Southampton SO17 1BJ, UK.
• 2011-2013: Lecturer. Centre for Biological Sciences, University of Southampton, Southampton SO17 1BJ, UK.
• 2007-2011: Senior Research Fellow. School of Biological Sciences, University of Southampton, Southampton SO16 7PX, UK.
• 2005-2007: Postdoctoral Research Fellow. The Conway Institute, University College Dublin, Dublin, Ireland.
• 2001-2005: Postdoctoral Research Fellow. The Royal College of Surgeons in Ireland, Dublin, Ireland.

Summary of Academic Qualifications

• 2010: Post-graduate Certificate in Academic Practice. University of Southampton, UK.
• 2002: PhD, "Adaptive Insertion Mutations in Bacteria". Institute of Genetics, University of Nottingham
• 1998: BSc (Hons) Genetics. Division of Genetics, University of Nottingham.

Awards

• 2020 Genetics Society of AustralAsia Award for Excellence in Education.

Main Funding History

• 2022-2027: Minderoo OceanOmics Centre at UWA (Minderoo Foundation)
• 2019-2022: ARC Linkage Project (Royal Botanic Gardens and Domain Trust).
• 2016-2019: ARC Linkage Project (Microbiogen Pty Ltd).
• 2015-2015: Department of Industry and Science, Research Connections Grant (Microbiogen Pty Ltd).
• 2011-2014: BBSRC New Investigator Award BB/I006230/1.
• 2007-2012: University of Southampton Research Fellowship.
• 2003-2007: SFI Investigator Award (D Shields). [Named Researcher]
• 2002-2005: HRB Programme Grant, Platelet Biology (D Kenny). [Named Researcher]
• 2001-2003: PRTLI HEA Cycle 2 (RCSI).

The SLiMDisc server: short, linear motif discovery in proteins

Davey NE*, Edwards RJ* & Shields DC (2007): The SLiMDisc server: short, linear motif discovery in proteins. Nucleic Acids Res. 35(Web Server issue):W455-9. *Joint first authors

Abstract

Short, linear motifs (SLiMs) play a critical role in many biological processes, particularly in protein-protein interactions. Overrepresentation of convergent occurrences of motifs in proteins with a common attribute (such as similar subcellular location or a shared interaction partner) provides a feasible means to discover novel occurrences computationally. The SLiMDisc (Short, Linear Motif Discovery) web server corrects for common ancestry in describing shared motifs, concentrating on the convergently evolved motifs. The server returns a listing of the most interesting motifs found within unmasked regions, ranked according to an information content-based scoring scheme. It allows interactive input masking, according to various criteria. Scoring allows for evolutionary relationships in the data sets through treatment of BLAST local alignments. Alongside this ranked list, visualizations of the results improve understanding of the context of suggested motifs, helping to identify true motifs of interest. These visualizations include alignments of motif occurrences, alignments of motifs and their homologues and a visual schematic of the top-ranked motifs. Additional options for filtering and/or re-ranking motifs further permit the user to focus on motifs with desired attributes. Returned motifs can also be compared with known SLiMs from the literature. SLiMDisc is available at: http://bioware.ucd.ie/~slimdisc/.

PMID: 17576682

Evolution of specificity and diversity

Shields DC, Johnston CR, Wallace IM & Edwards RJ (2007): Evolution of specificity and diversity. In: Ancestral Sequence Reconstruction Edited by DH Ardell, DA Liberles, G Matassi. Oxford University Press.

Evaluation of whether accelerated protein evolution in chordates has occurred before, after, or simultaneously with gene duplication

Johnston CR, O’dushlaine C, Fitzpatrick DA, Edwards RJ & Shields DC (2007): Evaluation Of Whether Accelerated Protein Evolution In Chordates Has Occurred Before, After Or Simultaneously With Gene Duplication. Mol. Biol. Evol. 24:315-323.

Abstract

Gene duplication and loss are predicted to be at least of the order of the substitution rate and are key contributors to the development of novel gene function and overall genome evolution. Although it has been established that proteins evolve more rapidly after gene duplication, we were interested in testing to what extent this reflects causation or association. Therefore, we investigated the rate of evolution prior to gene duplication in chordates. Two patterns emerged; firstly, branches, which are both preceded by a duplication and followed by a duplication, display an elevated rate of amino acid replacement. This is reflected in the ratio of nonsynonymous to synonymous substitution (mean nonsynonymous to synonymous nucleotide substitution rate ratio [Ka:Ks]) of 0.44 compared with branches preceded by and followed by a speciation (mean Ka:Ks of 0.23). The observed patterns suggest that there can be simultaneous alteration in the selection pressures on both gene duplication and amino acid replacement, which may be consistent with co-occurring increases in positive selection, or alternatively with concurrent relaxation of purifying selection. The pattern is largely, but perhaps not completely, explained by the existence of certain families that have elevated rates of both gene duplication and amino acid replacement. Secondly, we observed accelerated amino acid replacement prior to duplication (mean Ka:Ks for postspeciation preduplication branches was 0.27). In some cases, this could reflect adaptive changes in protein function precipitating a gene duplication event. In conclusion, the circumstances surrounding the birth of new proteins may frequently involve a simultaneous change in selection pressures on both gene-copy number and amino acid replacement. More precise modeling of the relative importance of preduplication, postduplication, and simultaneous amino acid replacement will require larger and denser genomic data sets from multiple species, allowing simultaneous estimation of lineage-specific fluctuations in mutation rates and adaptive constraints.

PMID: 17065596

Bioinformatic discovery of novel bioactive peptides

Edwards RJ*, Moran N*, Devocelle M, Kiernan A, Meade G, Signac W, Foy M, Park SDE, Dunne E, Kenny D & Shields DC (2007): Bioinformatic discovery of novel bioactive peptides. Nature Chem. Biol. 3(2):108-112. *Joint first authors

Abstract

Short synthetic oligopeptides based on regions of human proteins that encompass functional motifs are versatile reagents for understanding protein signaling and interactions. They can either mimic or inhibit the parent protein’s activity and have been used in drug development. Peptide studies typically either derive peptides from a single identified protein or (at the other extreme) screen random combinatorial peptides, often without knowledge of the signaling pathways targeted. Our objective was to determine whether rational bioinformatic design of oligopeptides specifically targeted to potentially signaling-rich juxtamembrane regions could identify modulators of human platelet function. High-throughput in vitro platelet function assays of palmitylated cell-permeable oligopeptides corresponding to these regions identified many agonists and antagonists of platelet function. Many bioactive peptides were from adhesion molecules, including a specific CD226-derived inhibitor of inside-out platelet signaling. Systematic screens of this nature are highly efficient tools for discovering short signaling motifs in molecular signaling pathways.

Comment in

A shortcut to peptides to modulate platelets. Nat Chem Biol. 2007.

PMID: 17220901