Recent Submissions

  • Methods comparison for high-resolution transcriptional analysis of archival material on Affymetrix Plus 2.0 and Exon 1.0 microarrays.

    Linton, Kim M; Hey, Yvonne; Dibben, Sian; Miller, Crispin J; Freemont, Anthony J; Radford, John A; Pepper, Stuart D; Cancer Research UK Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK. kim.linton@christie.nhs.uk (2009-07)
    Microarray gene expression profiling of formalin-fixed paraffin-embedded (FFPE) tissues is a new and evolving technique. This report compares transcript detection rates on Affymetrix U133 Plus 2.0 and Human Exon 1.0 ST GeneChips across several RNA extraction and target labeling protocols, using routinely collected archival FFPE samples. All RNA extraction protocols tested (Ambion-Optimum, Ambion-RecoverAll, and Qiagen-RNeasy FFPE) provided extracts suitable for microarray hybridization. Compared with Affymetrix One-Cycle labeled extracts, NuGEN system protocols utilizing oligo(dT) and random hexamer primers, and cDNA target preparations instead of cRNA, achieved percent present rates up to 55% on Plus 2.0 arrays. Based on two paired-sample analyses, at 90% specificity this equalled an average 30 percentage-point increase (from 50% to 80%) in FFPE transcript sensitivity relative to fresh frozen tissues, which we have assumed to have 100% sensitivity and specificity. The high content of Exon arrays, with multiple probe sets per exon, improved FFPE sensitivity to 92% at 96% specificity, corresponding to an absolute increase of ~600 genes over Plus 2.0 arrays. While larger series are needed to confirm high correspondence between fresh-frozen and FFPE expression patterns, these data suggest that both Plus 2.0 and Exon arrays are suitable platforms for FFPE microarray expression analyses.
  • Mutation of a phosphorylatable residue in Put3p affects the magnitude of rapamycin-induced PUT1 activation in a Gat1p-dependent manner.

    Leverentz, Michael K; Campbell, Robert N; Connolly, Yvonne; Whetton, Anthony D; Reece, Richard J; Faculty of Life Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, United Kingdom. (2009-09-04)
    Saccharomyces cerevisiae can utilize high quality (e.g. glutamine and ammonia) as well as low quality (e.g. gamma-amino butyric acid and proline) nitrogen sources. The transcriptional activator Put3p allows yeast cells to utilize proline as a nitrogen source through expression of the PUT1 and PUT2 genes. Put3p activates high level transcription of these genes by binding proline directly. However, Put3p also responds to other lower quality nitrogen sources. As nitrogen quality decreases, Put3p exhibits an increase in phosphorylation concurrent with an increase in PUT gene expression. The proline-independent activation of the PUT genes requires both Put3p and the positively acting GATA factors, Gln3p and Gat1p. Conversely, the phosphorylation of Put3p is not dependent on GATA factor activity. Here, we find that the mutation of Put3p at amino acid Tyr-788 modulates the proline-independent activation of PUT1 through Gat1p. The phosphorylation of Put3p appears to influence the association of Gat1p, but not Gln3p, to the PUT1 promoter. Combined, our findings suggest that this may represent a mechanism through which yeast cells rapidly adapt to use proline as a nitrogen source under nitrogen limiting conditions.
  • SRC-induced disassembly of adherens junctions requires localized phosphorylation and degradation of the rac activator tiam1.

    Woodcock, Simon A; Rooney, Claire M; Liontos, Michalis; Connolly, Yvonne; Zoumpourlis, Vassilis; Whetton, Anthony D; Gorgoulis, Vassilis G; Malliri, Angeliki; Cell Signalling Group, Cancer Research UK Paterson Institute for Cancer Research, University of Manchester, Manchester, UK. (2009-03-13)
    The Rac activator Tiam1 is required for adherens junction (AJ) maintenance, and its depletion results in AJ disassembly. Conversely, the oncoprotein Src potently induces AJ disassembly and epithelial-mesenchymal transition (EMT). Here, we show that Tiam1 is phosphorylated on Y384 by Src. This occurs predominantly at AJs, is required for Src-induced AJ disassembly and cell migration, and creates a docking site on Tiam1 for Grb2. We find that Tiam1 is associated with ERK. Following recruitment of the Grb2-Sos1 complex, ERK becomes activated and triggers the localized degradation of Tiam1 at AJs, likely involving calpain proteases. Furthermore, we demonstrate that, in human tumors, Y384 phosphorylation positively correlates with Src activity, and total Tiam1 levels are inversely correlated. Thus, our data implicate Tiam1 phosphorylation and consequent degradation in Src-mediated EMT and resultant cell motility and establish a paradigm for regulating local concentrations of Rho-GEFs.
  • Quantitative proteomics analysis demonstrates post-transcriptional regulation of embryonic stem cell differentiation to hematopoiesis.

    Williamson, Andrew J K; Smith, Duncan L; Blinco, David; Unwin, Richard D; Pearson, Stella; Wilson, Claire L; Miller, Crispin J; Lancashire, Lee J; Lacaud, Georges; Kouskoff, Valerie; Whetton, Anthony D; Stem Cell and Leukemia Proteomics Laboratory, Faculty of Medical and Human Sciences, University of Manchester, Kinnaird House, Kinnaird Road, Manchester M20 4QL, United Kingdom. (2008-03)
    Embryonic stem (ES) cells can differentiate in vitro to produce the endothelial and hematopoietic precursor, the hemangioblasts, which are derived from the mesoderm germ layer. Differentiation of Bry(GFP/+) ES cell to hemangioblasts can be followed by the expression of the Bry(GFP/+) and Flk1 genes. Proteomic and transcriptomic changes during this differentiation process were analyzed to identify mechanisms for phenotypic change during early differentiation. Three populations of differentiating Bry(GFP) ES cells were obtained by flow cytometric sorting, GFP-Flk1- (epiblast), GFP+Flk1- (mesoderm), and GFP+Flk1+ (hemangioblast). Microarray analyses and relative quantification two-dimensional LCLC-MS/MS on nuclear extracts were performed. We identified and quantified 2389 proteins, 1057 of which were associated to their microarray probe set. These included a variety of low abundance transcription factors, e.g. UTF1, Sox2, Oct4, and E2F4, demonstrating a high level of proteomic penetrance. When paired comparisons of changes in the mRNA and protein expression levels were performed low levels of correlation were found. A strong correlation between isobaric tag-derived relative quantification and Western blot analysis was found for a number of nuclear proteins. Pathway and ontology analysis identified proteins known to be involved in the regulation of stem cell differentiation, and proteins with no described function in early ES cell development were also shown to change markedly at the proteome level only. ES cell development is regulated at the mRNA and protein level.
  • Exon level integration of proteomics and microarray data.

    Bitton, Danny A; Okoniewski, Michal J; Connolly, Yvonne; Miller, Crispin J; Cancer Research UK, Applied Computational Biology and Bioinformatics Group, Paterson Institute for Cancer Research, The University of Manchester, Christie Hospital Site, Wilmslow Road, Manchester, M20 4BX, UK. dbitton@picr.man.ac.uk (2008)
    BACKGROUND: Previous studies comparing quantitative proteomics and microarray data have generally found poor correspondence between the two. We hypothesised that this might in part be because the different assays were targeting different parts of the expressed genome and might therefore be subjected to confounding effects from processes such as alternative splicing. RESULTS: Using a genome database as a platform for integration, we combined quantitative protein mass spectrometry with Affymetrix Exon array data at the level of individual exons. We found significantly higher degrees of correlation than have been previously observed (r = 0.808). The study was performed using cell lines in equilibrium in order to reduce a major potential source of biological variation, thus allowing the analysis to focus on the data integration methods in order to establish their performance. CONCLUSION: We conclude that part of the variation observed when integrating microarray and proteomics data may occur as a consequence both of the data analysis and of the high granularity to which studies have until recently been limited. The approach opens up the possibility for the first time of considering combined microarray and proteomics datasets at the level of individual exons and isoforms, important given the high proportion of alternative splicing observed in the human genome.