Cell signalling analyses in the functional genomics era.

The advancements in proteomics over the past decade have brought tremendous increases in sensitivity of mass spectrometry (MS) analyses and new technologies such as methods for quantitative MS and phosphoproteomics. The development of antibodies targeting a large fraction of the human proteome as well as specific antibodies that detect phosphorylations and other post-translational modifications now allows detection of a great variety of signalling marks. Combined with medium and high throughput methods for detecting many parallel signalling events such as phospho-flow cytometry analyses and MS-based analyses to identify signalling complexes, the available tools now allows analysis of whole signalling networks facilitating systems level understanding of cellular signalling. The even more recent advances in chemical biology and chemical proteomics are further enhancing the development in this area by providing a cache of small molecule compounds allowing perturbations of signal pathways further advancing our global understanding of the signal transduction dynamics at the single cell level as well as in cellular system, tissue and whole organs. This review highlights the recent advances of quantitative MS, phosphoflow cytometry and chemical biology with focus on the dynamic spatiotemporal phosphorylation events, and examples of their application.

[1]  M. Mann,et al.  Stable Isotope Labeling by Amino Acids in Cell Culture, SILAC, as a Simple and Accurate Approach to Expression Proteomics* , 2002, Molecular & Cellular Proteomics.

[2]  A. Danckaert,et al.  HIV infection perturbs interleukin-7 signaling at the step of STAT5 nuclear relocalization , 2011, AIDS.

[3]  Sam A. Johnson,et al.  Kinomics: methods for deciphering the kinome , 2004, Nature Methods.

[4]  Corey Nislow,et al.  Recent advances and method development for drug target identification. , 2010, Trends in pharmacological sciences.

[5]  Carlo Gambacorti-Passerini,et al.  Part I: Milestones in personalised medicine--imatinib. , 2008, The Lancet. Oncology.

[6]  O. Perez,et al.  Multiparameter Analysis of Intracellular Phosphoepitopes in Immunophenotyped Cell Populations by Flow Cytometry , 2005, Current Protocols in Cytometry.

[7]  Javier Muñoz,et al.  Deconvolution of overlapping isotopic clusters improves quantification of stable isotope-labeled peptides. , 2011, Journal of proteomics.

[8]  Albert J R Heck,et al.  High-resolution mapping of prostaglandin E2-dependent signaling networks identifies a constitutively active PKA signaling node in CD8+CD45RO+ T cells. , 2010, Blood.

[9]  Sean C. Bendall,et al.  Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum , 2011, Science.

[10]  K. Hunter,et al.  Mapping normal and cancer cell signalling networks: towards single-cell proteomics , 2006 .

[11]  J. V. Moran,et al.  Initial sequencing and analysis of the human genome. , 2001, Nature.

[12]  B. Druker,et al.  Lessons learned from the development of an abl tyrosine kinase inhibitor for chronic myelogenous leukemia. , 2000, The Journal of clinical investigation.

[13]  Bernd Thiede,et al.  Isobaric peptide termini labeling for MS/MS-based quantitative proteomics. , 2009, Journal of proteome research.

[14]  K. Torgersen,et al.  T Cell-Signaling Network Analysis Reveals Distinct Differences between CD28 and CD2 Costimulation Responses in Various Subsets and in the MAPK Pathway between Resting and Activated Regulatory T Cells , 2011, The Journal of Immunology.

[15]  A. Heck,et al.  The quantitative proteomes of human-induced pluripotent stem cells and embryonic stem cells , 2011, Molecular systems biology.

[16]  H. Daub,et al.  Proteome‐wide analysis of temporal phosphorylation dynamics in lysophosphatidic acid‐induced signaling , 2012, Proteomics.

[17]  D. Carrasco,et al.  Multiplex Flow Cytometry Barcoding and Antibody Arrays Identify Surface Antigen Profiles of Primary and Metastatic Colon Cancer Cell Lines , 2013, PloS one.

[18]  G. Nolan Deeper insights into hematological oncology disorders via single-cell phospho-signaling analysis. , 2006, Hematology. American Society of Hematology. Education Program.

[19]  J. García,et al.  Functional and quantitative proteomics using SILAC in cancer research , 2008 .

[20]  Jonathan M Irish,et al.  Single Cell Profiling of Potentiated Phospho-Protein Networks in Cancer Cells , 2004, Cell.

[21]  Matthias Mann,et al.  Selective Anchoring of TFIID to Nucleosomes by Trimethylation of Histone H3 Lysine 4 , 2007, Cell.

[22]  Garry P Nolan,et al.  Transcending the biomarker mindset: deciphering disease mechanisms at the single cell level. , 2006, Current opinion in chemical biology.

[23]  Martin Meier-Schellersheim,et al.  Systems biology in immunology: a computational modeling perspective. , 2011, Annual review of immunology.

[24]  Joost W Gouw,et al.  Highly robust, automated, and sensitive online TiO2-based phosphoproteomics applied to study endogenous phosphorylation in Drosophila melanogaster. , 2008, Journal of proteome research.

[25]  M. Joel,et al.  EGF signalling and rapamycin-mediated mTOR inhibition in glioblastoma multiforme evaluated by phospho-specific flow cytometry , 2013, Journal of Neuro-Oncology.

[26]  B. Thiede,et al.  High Resolution Quantitative Proteomics of HeLa Cells Protein Species Using Stable Isotope Labeling with Amino Acids in Cell Culture(SILAC), Two-Dimensional Gel Electrophoresis(2DE) and Nano-Liquid Chromatograpohy Coupled to an LTQ-OrbitrapMass Spectrometer* , 2012, Molecular & Cellular Proteomics.

[27]  Kristen M. Naegle,et al.  An integrated comparative phosphoproteomic and bioinformatic approach reveals a novel class of MPM-2 motifs upregulated in EGFRvIII-expressing glioblastoma cells. , 2008, Molecular bioSystems.

[28]  O. Perez,et al.  Phospho‐proteomic immune analysis by flow cytometry: from mechanism to translational medicine at the single‐cell level , 2006, Immunological reviews.

[29]  Garry P Nolan,et al.  Fluorescent cell barcoding in flow cytometry allows high-throughput drug screening and signaling profiling , 2006, Nature Methods.

[30]  S. Gammeltoft,et al.  Quantitative Phosphoproteomics Dissection of Seven-transmembrane Receptor Signaling Using Full and Biased Agonists* , 2010, Molecular & Cellular Proteomics.

[31]  K. Parker,et al.  Multiplexed Protein Quantitation in Saccharomyces cerevisiae Using Amine-reactive Isobaric Tagging Reagents*S , 2004, Molecular & Cellular Proteomics.

[32]  Garry P. Nolan,et al.  Simultaneous measurement of multiple active kinase states using polychromatic flow cytometry , 2002, Nature Biotechnology.

[33]  Identifying and Quantifying Sites of Protein Methylation by Heavy Methyl SILAC , 2006, Current protocols in protein science.

[34]  Jinxing Lin,et al.  Proteomic and phosphoproteomic analysis of Picea wilsonii pollen development under nutrient limitation. , 2012, Journal of proteome research.

[35]  Roy E. Welsch,et al.  MCAM: Multiple Clustering Analysis Methodology for Deriving Hypotheses and Insights from High-Throughput Proteomic Datasets , 2011, PLoS Comput. Biol..

[36]  S. Gygi,et al.  Quantitative analysis of complex protein mixtures using isotope-coded affinity tags , 1999, Nature Biotechnology.

[37]  Kjetil Taskén,et al.  Analysing phosphorylation-based signalling networks by phospho flow cytometry. , 2011, Cellular signalling.

[38]  G. Nolan,et al.  Retroviral delivery of peptide modulators of cellular functions. , 2000, Molecular therapy : the journal of the American Society of Gene Therapy.

[39]  K. Torgersen,et al.  Molecular mechanisms for protein kinase A-mediated modulation of immune function. , 2002, Cellular signalling.