Marc R Wilkins

University of New South Wales, Kensington, New South Wales, Australia

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Publications (142)554.67 Total impact

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    ABSTRACT: Pathogenic species within the Campylobacter genus are responsible for a considerable burden on global health. Campylobacter concisus is an emergent pathogen that plays a role in acute and chronic gastrointestinal disease. Despite ongoing research on Campylobacter virulence mechanisms, little is known regarding the immunological profile of the host response to Campylobacter infection. In this study, we describe a comprehensive global profile of innate immune responses to C. concisus infection in differentiated THP-1 macrophages infected with an adherent and invasive strain of C. concisus. Using RNA-seq, qPCR, mass spectrometry and confocal microscopy, we observed differential expression of pattern recognition receptors and robust upregulation of DNA and RNA sensing molecules. In particular, we observed IFI16 inflammasome assembly in C. concisus-infected macrophages. Global profiling of the transcriptome revealed the significant regulation of a total of 8,343 transcripts upon infection with C. concisus, which included the activation of key inflammatory pathways involving CREB1, NF-κB, STAT and IRF signaling. Thirteen microRNAs and 333 non-coding RNAs were significantly regulated upon infection, including MIR221 which has been associated with colorectal carcinogenesis. This study represents a major advance in our understanding of host recognition and innate immune responses to infection by C. concisus. Copyright © 2014, American Society for Microbiology. All Rights Reserved.
    Infection and immunity. 12/2014;
  • Daniel L Winter, Melissa A Erce, Marc R Wilkins
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    ABSTRACT: Many proteins, including p53, the FoxO transcription factors, RNA polymerase II, pRb and the chaperones, have extensive post-translational modifications (PTMs). Many of these modifications modulate protein-protein interactions, controlling interaction presence / absence and specificity. Here we propose the notion of the interaction code; a widespread means by which modifications are used to control interactions in the proteome. Minimal interaction codes are likely to exist on proteins that have two or more modifications on an interaction interface and two or more interaction partners. By contrast, complex interaction codes are likely to be found on 'date hub' proteins that have many interactions, many PTMs, and/or are targeted by many modifying and demodifying enzymes. Proteins with new interaction codes should be discoverable by examining protein interaction networks, annotated with PTMs and protein modifying enzyme-substrate links. Multiple instances or combinations of phosphorylation, acetylation, methylation, O-GlcNAc and/or ubiquitination will likely form interaction codes, especially when co-located on a protein's single interaction interface. A network-based example of code discovery is given, predicting the yeast protein Npl3p to have a methylation / phosphorylation dependent interaction code.
    Journal of Proteome Research 10/2014; · 5.06 Impact Factor
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    ABSTRACT: The koala, Phascolarctos cinereus, is a biologically unique and evolutionarily distinct Australian arboreal marsupial. The goal of this study was to sequence the transcriptome from several tissues of two geographically separate koalas, and to create the first comprehensive catalog of annotated transcripts for this species, enabling detailed analysis of the unique attributes of this threatened native marsupial, including infection by the koala retrovirus.
    BMC Genomics 09/2014; 15(1):786. · 4.40 Impact Factor
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    ABSTRACT: Here we describe the discovery of S. cerevisiae protein YJR129Cp as a new eukaryotic seven-beta-strand lysine methyltransferase. An immunoblotting screen of 21 putative methyltransferases showed a loss in the methylation of elongation factor 2 (EF2) on knockout of YJR129C. Mass spectrometric analysis of EF2 tryptic peptides localized this loss of methylation to lysine 509, in peptide LVEGLKR. In vitro methylation, using recombinant methyltransferases and purified EF2, validated YJR129Cp as responsible for methylation of lysine 509 and Efm2p as responsible for methylation at lysine 613. Contextualised on previously described protein structures, both sites of methylation were found at the interaction interface between EF2 and the 40S ribosomal subunit. In line with the recently discovered Efm1 and Efm2 we propose that YJR129C be named elongation factor methyltransferase 3 (Efm3). The human homolog of Efm3 is likely to be the putative methyltransferase FAM86A, according to sequence homology and multiple lines of literature evidence.
    Biochemical and Biophysical Research Communications 07/2014; · 2.28 Impact Factor
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    ABSTRACT: The phenotype of osteoblastic (OB) cells in culture is currently defined using a limited number of markers of low sensitivity and specificity. For the clinical use of human skeletal (stromal, mesenchymal) stem cells (hMSC) in therapy, there is also a need to identify a set of gene markers that predict in vivo bone forming capacity. Thus, we used RNA sequencing to examine changes in expression for a set of skeletally-related genes across 8 time points between 0-12 days of ex vivo OB differentiation of hMSC. We identified 123 genes showing significant temporal expression change. Hierarchical clustering and Pearson's correlation generated 4 groups of genes: early stage differentiation genes (peak expression: 0-24hrs, n=28) which were enriched for extracellular matrix organisation, e.g. COL1A1, LOX, SERPINH1; middle stage differentiating genes (peak expression days: 3 and 6, n=20) which were enriched for extracellular matrix/skeletal system development e.g. BMP4, CYP24A1, TGFBR2; and late stage differentiation genes (peak expression days: 9 and 12, n=27) which were enriched for bone development/osteoblast differentiation, e.g. BMP2, IGF2. In addition, we identified 13 genes with bimodal temporal expression (2 peaks of expression: day 0 and 12) including VEGFA, PDGFA and FGF2. We examined the specificity of the 123 genes' expression in skeletal tissues and thus propose a set of ex vivo differentiation-stage-specific markers (n=21). In an independent analysis, we identified a subset of genes (n=20, e.g. ELN, COL11A1, BMP4) to predict the bone forming capacity of hMSC and another set (n=20, e.g. IGF2, TGFB2, SMAD3) associated with the ex vivo phenotype of hMSC obtained from osteoporotic patients.
    Bone 06/2014; · 4.46 Impact Factor
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    ABSTRACT: This is the story of the experience of a multidisciplinary group at Macquarie University in Sydney as we participated in, and impacted upon, major currents that washed through protein science as the field of Proteomics emerged. The large scale analysis of proteins became possible. This is not a history of the field. Instead we have tried to encapsulate the stimulating personal ride we had transiting from conventional academe, to a Major National Research Facility, to the formation of Proteomics company Proteome Systems Ltd. There were lots of blind alleys, wrong directions, but we also got some things right and our efforts, along with those of many other groups around the world, did change the face of protein science. While the transformation is by no means yet complete, protein science is very different from the field in the 1990's. This article is part of a Special Issue entitled: 20years of Proteomics.
    Journal of proteomics 04/2014; · 5.07 Impact Factor
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    ABSTRACT: Post-translational lysine methylation is well established as a regulator of histone activity; however it is emerging that these modifications are also likely to play extensive roles outside of the histone code. Here we obtain new insights into non-histone lysine methylation and protein lysine methyltransferase (PKMT) activity by elucidating absolute stoichiometries of lysine methylation, using mass spectrometry and absolute quantification (AQUA), in wild-type and 5 PKMT gene deletion strains of Saccharomyces cerevisiae. By analyzing 8 sites of methylation in 3 non-histone proteins - elongation factor 1-α (EF1α), elongation factor 2 (EF2) and 60S ribosomal protein L42-A/B (Rpl42ab) - we find that: production of preferred methylation states on individual lysine residues is commonplace, and likely occurs through processive PKMT activity; Class I PKMTs can be associated with processive methylation; lysine residues are selectively methylated by specific PKMTs; and lysine methylation exists over a broad range of stoichiometries. Together these findings suggest that specific sites and forms of lysine methylation may play specialized roles in the regulation of non-histone protein activity. We also uncover new relationships between two proteins previously characterized as PKMTs, SEE1 and EFM1, in EF1α methylation, and show that past characterizations of EFM1 as having direct PKMT activity may require reinterpretation.
    Journal of Proteome Research 02/2014; · 5.06 Impact Factor
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    ABSTRACT: Diatoms are of enormous ecological importance as they account for as much as 20% of global primary production, yet they are still understudied from a genomic perspective. The benthic diatom Ceratoneis closterium is well-characterized from an ecotoxicological perspective including its use in ecotoxicological risk assessments and investigating the mode-of-action of metal toxicity. However, this organism has little sequence information available. In this study, 454 pyrosequencing of the stressor-responsive transcriptome was undertaken. These transcripts could be used to characterize general physiological processes such as photosynthesis and respiration, as well as to enable a description of the ecotoxicogenomic responses of this organism. After a 96h exposure to the concentration of toxicant that inhibited growth rate by 10% (IC10) for the following common coastal contaminants: ammonia, copper, crude oil and simazine (a photosystem II inhibiting herbicide), diatom cells were harvested for RNA extraction and their transcriptomes characterized via 454 pyrosequencing. This resulted in 1.25million reads, which were assembled into 4768 contigs, when contigs encoding rRNA were removed. More than 80% of the remaining contigs had an ortholog in the BLASTx protein databases. These contigs represented 1660 unique transcripts. The role of these transcripts in stress response, as well as photosynthesis and respiration is discussed. Overall, this study greatly enhances the genomic information available for this important taxonomic group.
    Marine Genomics 01/2014; · 1.34 Impact Factor
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    ABSTRACT: The human oral microbiome has a major role in oral diseases including dental caries. Our studies on progression of caries infection through dentin and more recently, the invasion of vital dental pulp, detected Lactobacillus rhamnosus in the initial stages of infection of vital pulp tissue. In this study employing current high-throughput next generation sequencing technology we sought to obtain insight into genomic traits of tissue invasive L. rhamnosus, to recognise biomarkers that could provide an understanding of pathogenic potential of lactobacilli, generally regarded as safe. Roche GS FLX+ technology was used to generate whole genome sequences of two clinical isolates of L. rhamnosus infecting vital pulp. Detailed genome-wide comparison of the genetic profiles of tissue invasive L. rhamnosus with probiotic L. rhamnosus was performed to test the hypothesis that specific strains of L. rhamnosus possessing a unique gene complement are selected for the capacity to invade vital pulp tissue. Analysis identified 264 and 258 genes respectively, from dental pulp-invasive L. rhamnosus strains LRHMDP2 and LRHMDP3 isolated from two different subjects that were not present in the reference probiotic L. rhamnosus strain ATCC 53103 (GG). Distinct genome signatures identified included the presence of a modified exopolysaccharide cluster, a characteristic confirmed in a further six clinical isolates. Additional features of LRHMDP2 and LRHMDP3 were altered transcriptional regulators from RpoN, NtrC, MutR, ArsR and zinc-binding Cro/CI families, as well as changes in the two-component sensor kinase response regulator and ABC transporters for ferric iron. Both clinical isolates of L. rhamnosus contained a single SpaFED cluster, as in L. rhamnosus Lc705, instead of the two Spa clusters (SpaCBA and SpaFED) identified in L. rhamnosus ATCC 53103 (GG). Genomic distance analysis and SNP divergence confirmed a close relationship of the clinical isolates but segregation from the reference probiotic L. rhamnosus strain ATCC 53103 (GG).
    PLoS ONE 01/2014; 9(3):e90643. · 3.53 Impact Factor
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    ABSTRACT: Poly(A)-binding protein in mouse and man was recently found to be highly post-translationally modified. Here we analysed an ortholog of this protein, Pab1 from Saccharomyces cerevisiae, to assess the conservation and thus likely importance of these modifications. Pab1 showed the presence of six sites of methylated glutamate, five sites of lysine acetylation, and one phosphorylation of serine. Many modifications on Pab1 showed either complete conservation with those on human or mouse PABPC1, were present on nearby residues and/or were present in the same domain(s). The conservation of methylated glutamate, an unusual modification, was of particular note and suggests a conserved function. Comparison of methylated glutamate sites in human, mouse and yeast poly(A)-binding protein, along with methylation sites catalysed by CheR L-glutamyl protein methyltransferase from Salmonella typhimurium, revealed that the methylation of glutamate preferentially occurs in EE and DE motifs or other small regions of acidic amino acids. The conservation of methylated glutamate in the same protein between mouse, man and yeast suggests the presence of a eukaryotic L-glutamyl protein methyltransferase and that the modification is of functional significance.
    Biochemical and Biophysical Research Communications 12/2013; · 2.28 Impact Factor
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    ABSTRACT: Large-scale molecular interaction networks are dynamic in nature and are of special interest in the analysis of complex diseases, which are characterized by network-level perturbations rather than changes in individual genes/proteins. The methods developed for the identification of differentially expressed genes or gene sets are not suitable for network-level analyses. Consequently, bioinformatics approaches that enable a joint analysis of high-throughput transcriptomics datasets and large-scale molecular interaction networks for identifying perturbed networks are gaining popularity. Typically, these approaches require the sequential application of multiple bioinformatics techniques -- ID mapping, network analysis, and network visualization. Here, we present the Variability Analysis in Networks (VAN) software package: a collection of R functions to streamline this bioinformatics analysis. VAN determines whether there are network-level perturbations across biological states of interest. It first identifies hubs (densely connected proteins/microRNAs) in a network and then uses them to extract network modules (comprising of a hub and all its interaction partners). The function identifySignificantHubs identifies dysregulated modules (i.e. modules with changes in expression correlation between a hub and its interaction partners) using a single expression and network dataset. The function summarizeHubData identifies dysregulated modules based on a meta-analysis of multiple expression and/or network datasets. VAN also converts protein identifiers present in a MITAB-formatted interaction network to gene identifiers (UniProt identifier to Entrez identifier or gene symbol using the function generatePpiMap) and generates microRNA-gene interaction networks using TargetScan and Microcosm databases (generateMicroRnaMap). The function obtainCancerInfo is used to identify hubs (corresponding to significantly perturbed modules) that are already causally associated with cancer(s) in the Cancer Gene Census database. Additionally, VAN supports the visualization of changes to network modules in R and Cytoscape (visualizeNetwork and obtainPairSubset, respectively). We demonstrate the utility of VAN using a gene expression data from metastatic melanoma and a protein-protein interaction network from the Human Protein Reference Database. Our package provides a comprehensive and user-friendly platform for the integrative analysis of -omics data to identify disease-associated network modules. This bioinformatics approach, which is essentially focused on the question of explaining phenotype with a 'network type' and in particular, how regulation is changing among different states of interest, is relevant to many questions including those related to network perturbations across developmental timelines.
    BMC Research Notes 10/2013; 6(1):430.
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    ABSTRACT: High-throughput -omics data can be combined with large-scale molecular interaction networks, e.g., protein-protein interaction networks, to provide a unique framework for the investigation of human molecular biology. Interest in these integrative -omics methods is growing rapidly because of their potential to understand complexity and association with disease; such approaches have a focus on associations between phenotype and 'network-type'. The potential of this research is enticing yet there remain a series of important considerations. Here we discuss interaction data selection, data quality, the relative merits of using data from large high throughput studies versus a meta-database of smaller literature-curated studies, and possible issues of sociological or inspection bias in interaction data. Other work underway, especially international consortia to establish data formats, quality standards and address data redundancy, and the improvements these efforts are making to the field, is also evaluated. We present options for researchers intending to use large-scale molecular interaction networks as a functional context for protein or gene expression data, including microRNAs, especially in the context of human disease. This article is protected by copyright. All rights reserved.
    Proteomics 10/2013; · 4.43 Impact Factor
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    ABSTRACT: Direct links between proteomic and genomic / transcriptomic data are not frequently made, partly due to lack of appropriate bioinformatics tools. To help address this, we have developed the PG Nexus pipeline. The PG Nexus allow users to co-visualize peptides in the context of genomes or genomic contigs, along with RNA-seq reads. This is done in the Integrated Genome Viewer (IGV). A Results Analyser reports the precise base position where LC-MS/MS-derived peptides cover genes or gene isoforms, on the chromosomes or contigs where this occurs. In prokaryotes, the PG Nexus pipeline facilitates the validation of genes, where annotation or gene prediction is available, or the discovery of genes using a 'virtual protein'-based unbiased approach. We illustrate this with a comprehensive proteogenomics analysis of two strains of Campylobacter concisus. For higher eukaryotes, the PG Nexus facilitates gene validation and supports the identification of mRNA splice junction boundaries and splice variants that are protein-coding. This is illustrated with an analysis of splice junctions covered by human phosphopeptides, and other examples of relevance to the chromosome-centric Human Proteome Project. The PG Nexus is open-source and available from It has been integrated into Galaxy and made available in the Galaxy tool shed.
    Journal of Proteome Research 10/2013; · 5.06 Impact Factor
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    ABSTRACT: In spite of its association with gastroenteritis and inflammatory bowel diseases, the isolation of Campylobacter concisus from both diseased and healthy individuals has led to controversy regarding its role as an intestinal pathogen. One proposed reason for this is the presence of high genetic diversity among the genomes of C. concisus strains. In this study the genomes of six C. concisus strains were sequenced, assembled and annotated including two strains isolated from Crohn's disease patients (UNSW2 and UNSW3), three from gastroenteritis patients (UNSW1, UNSWCS and ATCC 51562) and one from a healthy individual (ATCC 51561). The genomes of C. concisus BAA-1457 and UNSWCD, available from NCBI, were included in subsequent comparative genomic analyses. The Pan and Core genomes for the sequenced C. concisus strains consisted of 3254 and 1556 protein coding genes, respectively. Genes were identified with specific conservation in C. concisus strains grouped by phenotypes such as invasiveness, adherence, motility and diseased states. Phylogenetic trees based on ribosomal RNA sequences and concatenated host-related pathways for the eight C. concisus strains were generated using the neighbor-joining method, of which the 16S rRNA gene and peptidoglycan biosynthesis grouped the C. concisus strains according to their pathogenic phenotypes. Furthermore, 25 non-synonymous amino acid changes with 14 affecting functional domains, were identified within proteins of conserved host-related pathways, which had possible associations with the pathogenic potential of C. concisus strains. Finally, the genomes of the eight C. concisus strains were compared to the nine available genomes of the well-established pathogen Campylobacter jejuni, which identified several important differences in the respiration pathways of these two species. Our findings indicate that C. concisus strains are genetically diverse, and suggest the genomes of this bacterium contain respiration pathways and modifications in the peptidoglycan layer that may play an important role in its virulence.
    BMC Genomics 08/2013; 14(1):585. · 4.40 Impact Factor
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    ABSTRACT: Protein-protein interactions can be modulated by the methylation of arginine residues. As a means of testing this, we recently described a conditional two-hybrid (C2H) system, based on the bacterial adenylate cyclase (BACTH) system. Here, we have used this C2H system to explore the effect of arginine methylation in modulating protein-protein interactions in a subset of the Saccharomyces cerevisiae arginine methylproteome network. Interactions between the yeast hub protein Npl3 and yeast proteins Air2, Ded1, Gbp2, Snp1 and Yra1 were first validated in the absence of methylation. The major yeast arginine methyltransferase Hmt1 was subsequently included in the C2H assay, initially to determine the degree of methylation which occurs. Proteins Snp1 and Yra1 were confirmed as Hmt1 substrates, with five and two novel arginine methylation sites mapped by ETD LC-MS/MS on these proteins, respectively. Proteins Ded1, and Gbp2, previously predicted but not confirmed as substrates of Hmt1, were also found to be methylated with 5 and 7 sites mapped respectively. Air2 was found to be a novel substate of Hmt1 with 2 sites mapped. Finally, we investigated the interactions of Npl3 with the five interaction partners in the presence of active Hmt1 and in the presence of Hmt1 with a G68R inactivation mutation. We found that the interaction between Npl3 and Air2, and Npl3 and Ded1, were significantly increased in the presence of active Hmt1; the interaction of Npl3 and Snp1 showed a similar degree of increase in interaction but this was not statistically significant. The interactions of Npl3 and Gbp2, along with Npl3 and Yra1, were not significantly increased or decreased by methylation. We conclude that methylarginine may be a widespread means by which the interactions of proteins are modulated.
    Molecular &amp Cellular Proteomics 08/2013; · 7.25 Impact Factor
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    ABSTRACT: Arginine methylation is a post-translational modification that has been implicated in a plethora of cellular processes. In the present manuscript, using two anti-methylarginine antibodies and combinatorial deletion mutants of arginine methyltransferases, we found evidence of widespread arginine methylation in the Saccharomyces cerevisiae proteome. Immunoprecipitation was used to enrich for methylarginine-containing proteins, which were identified via tandem mass spectrometry. From this, we identified a total of 90 proteins, of which 5 were previously known to be methylated. The proteins identified were involved in known methylarginine-associated biological functions such as RNA processing, nuclear transport, carbohydrate metabolic process, GMP biosynthetic process and protein folding. Through in vivo methylation by the incorporation of [(3)H]-methyl groups, we validated the methylation of 7 proteins (Ded1, Imd4, Lhp1, Nop1, Cdc11, Gus1, Pob3). By LC-MS/MS, we then confirmed a total of 15 novel methylarginine sites on 5 proteins (Ded1, Lhp1, Nop1, Pab1 and Ugp1). By examination of methylation on proteins from the triple knockout of methyltransferases Hmt1, Hsl7, Rmt2, we present evidence for the existence of additional unidentified arginine methyltransferases in the Saccharomyces cerevisiae proteome.
    Journal of Proteome Research 07/2013; · 5.06 Impact Factor
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    ABSTRACT: For disseminated melanoma, new prognostic biomarkers and therapeutic targets are urgently needed. The organization of protein-protein interaction (PPI) networks was assessed via the transcriptomes of four independent studies of metastatic melanoma, and related to clinical outcome and MAP-kinase pathway mutations (BRAF/NRAS). We also examined patient outcome-related differences in a predicted network of microRNAs and their targets. The 32 hub genes with the most reproducible survival-related disturbances in co-expression with their protein partner genes included oncogenes and tumor suppressors, previously known correlates of prognosis, and other proteins not previously associated with melanoma outcome. Notably, this network-based gene set could classify patients according to clinical outcomes with 67-80% accuracy among cohorts. Reproducibly disturbed networks were also more likely to have a higher functional mutation burden than would be expected by chance. The disturbed regions of networks are therefore markers of clinically relevant, selectable tumor evolution in melanoma which may carry driver mutations. This article is protected by copyright. All rights reserved.
    Pigment Cell & Melanoma Research 06/2013; · 5.84 Impact Factor
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    ABSTRACT: Krüppel-like factors 3 and 8 (KLF3 and KLF8) are highly related transcriptional regulators that bind to similar sequences of DNA. We have previously shown that in erythroid cells there is a regulatory hierarchy within the KLF family, whereby KLF1 drives the expression of both the Klf3 and Klf8 genes and KLF3 in turn represses Klf8 expression. While the erythroid roles of KLF1 and KLF3 have been explored, the contribution of KLF8 to this regulatory network has been unknown. To investigate this, we have generated a mouse model with disrupted KLF8 expression. Whilst these mice are viable, albeit with a reduced lifespan, mice lacking both KLF3 and KLF8 die at around E14.5, indicative of a genetic interaction between these two factors. In the fetal liver, Klf3 Klf8 double mutant embryos exhibit greater dysregulation of gene expression than either of the two single mutants. In particular, we observe derepression of embryonic, but not adult, globin expression. Taken together, these results suggest that KLF3 and KLF8 have overlapping roles in vivo and participate in the silencing of embryonic globin expression during development.
    Molecular and Cellular Biology 05/2013; · 5.04 Impact Factor
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    ABSTRACT: The hippocampus and cerebellum represent anatomically and functionally distinct parts of the human brain. The RNA-Seq technique makes it possible to investigate the human transcriptome with unprecedented resolution, allowing identification of differential mRNA splicing and promoter usage on a genome-wide scale. We undertook whole-mRNA sequencing of samples from the human hippocampus and cerebellum. A bioinformatic analysis revealed distinct expression patterns of genes related to the molecular physiology of neurons and glial cells. Upregulated genes in hippocampal tissue included serpin peptidase inhibitor, clade A (SERPINA3), lymphocyte antigen 6 complex, locus H (LY6H) and transthyretin (TTR). In cerebellum, the cerebellin 3 precursor (CLBN3) and Zic family member 4 (ZIC4) genes were significantly upregulated. These changes were validated in independent donor samples by qRT-PCR. The hippocampus and the cerebellum showed striking differences in splicing patterns and promoter usage. A notable example of this was the gene for NGFI-A binding protein 2 (NAB2), which displayed tissue-specific isoforms which may affect its function as a transcriptional repressor.
    Neuroscience Letters 02/2013; · 2.03 Impact Factor
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    ABSTRACT: The original bacterial two-hybrid system is widely used but does not permit the study of interactions regulated by post-translational modifications. Here, we have built a Conditional Two-Hybrid (C2H) system, in which bait and prey proteins can be co-expressed in the presence of a modifying enzyme such as a methyltransferase, acetyltransferase or kinase. Any increase or decrease in interaction due to the modification of the proteins can be measured by an increased or decreased level of reporter gene expression. The C2H system is comprised of eight new vectors based on the Novagen Duet co-expression plasmids. These vectors include two multiple cloning sites per vector as well as a hexahistidine tag or S-tag to aid in purification, if desired. We demonstrate the use of the C2H system to study the dimerization of the yeast protein Npl3, which is increased when methylated by the methyltransferase Hmt1.
    Proteomics 01/2013; · 4.43 Impact Factor

Publication Stats

6k Citations
554.67 Total Impact Points


  • 1995–2014
    • University of New South Wales
      • School of Biotechnology and Biomolecular Sciences (BABS)
      Kensington, New South Wales, Australia
  • 2013
    • Melanoma Institute Australia
      Sydney, New South Wales, Australia
  • 2011
    • University of Sydney
      Sydney, New South Wales, Australia
  • 1995–2011
    • Macquarie University
      • • Biomolecular Frontiers Research Centre (BFRC)
      • • Department of Biological Sciences
      • • Australian Proteome Analysis Facility (APF)
      Sydney, New South Wales, Australia
  • 2007
    • Ruhr-Universität Bochum
      Bochum, North Rhine-Westphalia, Germany
  • 1997–2005
    • University of Geneva
      • Department of Biochemistry
      Genève, GE, Switzerland
    • Pinnacle Biomedical Research Institute
      Bhopal, Madhya Pradesh, India
  • 2001
    • Université de Versailles Saint-Quentin
      Versailles, Île-de-France, France
  • 1999
    • Swiss Institute of Bioinformatics
      • Swiss-Prot Group
      Lausanne, Vaud, Switzerland