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The ribosomopathy paradoxMolecular Biology Begins With

DNA, Codons and the Amino Acid Code

Collectively, the ribosomopathies are caused by defects in ribosome biogenesis. Although these disordersencompass deficiencies in a ubiquitous and fundamental process, the clinical manifestationsare extremely variable and typically display tissue specificity.

DBA25-35%RPL5, RPL11, RPS26, RPS24, RPS17, RPS10, RPL35a,RPS7, RPL26, RPL15 25% RPS1940-50% ?? ~80 RP genes in total 10 are known to be affected in DBA GATA1 may also have a roleMutations affecting:Mutations affecting ribosomal protein (RP) genesHeterozygous, autosomal dominantLeading to RP haploinsufficiencyDBA is a ribosomopathyDNA, RNA & Proteins (& Cake)

Amino acidsThe Ribosome (80S)

40S (S) unit:18SRNA + 33 proteins

60S (L) unit:5S RNA,28S RNA,5.8S RNA + ~49 proteinsA cake making machine that uses mRNA as the recipe and amino acids as the ingredientsTypes of Mutations in DBA 1) Missense

Change in recipe use salt instead of sugar= cake no good!Types of Mutations 2) Nonsense

Change in recipe leave out half of ingredients= cake no good!Types of Mutations 3) Frameshift

Change in recipe words become unreadable= cake no good!Types of Mutations 4) Splice Site

Change in recipe pages left out or go blank= cake no good!Types of Mutations 5) Copy Number Variation (CNV)

Change in recipe pages torn out= cake no good!

10 Commonly Identified DBA associated RP Genes = 7 genes in conventional molecular screenMutations are mostly SNVs and indels, but large deletions & insertion are also seen

Peripheral BloodExtract DNA

RPS19RPL5RPL11

RPS24RPS17RPL35aRPS7Standard DBA Screening Pipeline

Measure & QC

Sanger Sequence

PCR target gene exonsGenes: Exons, Introns & Splicing

For many years now, gene expression has been measured as areflection of transcriptional activation, and the assumption hasbeen made that the absolute level of mRNA for a given genewithin the cell directly correlates with protein level for thatgene. Although mRNA level strongly correlates with proteinexpression, more recent evidence highlights the very importantrole that posttranscriptional events, including translation and microRNA (miRNA) regulation of mRNA, play in regulating geneexpressionSimilar to key regulators of gene transcription (e.g., p53or c-Myc), key regulators of translation are specifically targetedin human diseases, including cancer.Indeed, recent data suggestthat RNA binding proteins (RBPs) are frequently associated with diseaseFragile-X mental retardation proteinFragile-X syndrome and autismDarnell et al.,2011musashi-1 and -2Stem cell biology and leukemia Kharas et al., 2010NPM1hematological malignanciesGrisendi et al., 2006RPS7, RPS10,RPS17, RPS19DiamondBlackfan anemiaIdol et al, 2009

TCOF1, POLR1D,POLR1CTreacher Collins syndromeDauwerse et al, 2011DKC1dyskeratosis congenita

Heiss et al, 2002

THE PARADOX..Individually, the ribosomopathies are rare and phenotypically unique. Intuitively, mutations affecting the ribosome, a molecule essential for protein synthesis in every cell, should affect all tissues and cell types. On the contrary, ribosome biogenesis disorders are highly heterogeneous in both their physical manifestations and modes of inheritance, and there is a surprising tendency toward tissue specificity in these diseasesHow can ribosomopathies first appear as diseases caused by too few cells, but later turn into diseases caused by too many cells? This paradox has puzzled the scientific community for years.Over the last number of years, there has been increasing awareness of the role that ribosome, ribosome biogenesis, and various other factors that relate to translation play in normal cellular homeostasis, and in human disease (Xue and Barna, 2012).

However, there is a pressing need to understand in greater detailthe many factors that contribute to ribosome function and theregulation of translation on a global scale. Thus, we set out toanalyze in a nonbiased, high-throughput manner the numerousfactors that coordinate ribosome function and mRNA translation.Here, we present an overview of the riboproteome, as characterizedby analysis of several different cell lines and different cellularcontexts.

HYPOTHESISThey hypothesize that the process of active translation within the cell is regulated by a multitude of proteins that can interact witheither the ribosome itself, the mRNAs that are being actively translated, or proteins that may have the capacity to interact with both the ribosome and mRNA.WHAT DID THEY DO???In order to characterize the components that constitute the actively translating ribosome (i.e., the riboproteome), They applied a mass spectrometry approach to quantitatively evaluate the protein components that are differentially associated with translation in different cellular contexts, while also allow for a comprehensive overview of the proteins that make up the riboproteome.EXPERIMENTAL PROCEDURESSILAC Labeling and Mass SpectrometryMetabolic labeling of prostate cancer cell lines (PC3, PPC1, Du145, RWPE1, and PWR1E) and MEFs was carried out using either normal arginine and lysine or heavier isotopic variants of the two amino acids (L-lysine 2HCL [U-13C6], L-arginine HCL [U-13C6, U-N15N4]) (Ong etal., 2002) using Invitrogens SILAC-FLEX Media kits.

EXPERIMENT

SILAC (stable isotope labeling by amino acids in cell culture) media to incorporate amino acids for light (Lys0 C13; Arg0 N14) or heavy (Lys6 C13; Arg10 N15) labeling of proteins, achieving a labeling efficiency of greater than 95%

Importantly, an initial comparison between polysomes derived from Du145 heavy- and light-labeled cells revealed that all quantifiedproteins showed an average Log2 (H/L) ratio of around 0 (226 quantified proteins; mean 0.0029, SD 0.1866

demonstrating that differences observed between celllines do not arise from variations in sample preparation and confirmingboth reliability as well as reproducibility of the technique.Polysome Isolation and Analysis

Standard scatterplots with normalized Log2 (H/L) ratios/Log10 Intensities (Normal versus Cancer n = 3, left panel; Cancer versus Cancer n = 3, middle panel;PPC1 DMSO versus PP242, n = 3, right panel) highlighting the distribution of quantified proteins in each screen (cutoff values for enriched proteins was 2 SDs (2s)from the mean, dashed red lines). Proteins of interest in either experimental setting are highlighted.Bioinformatics Analysis of the Riboproteome

To identify functional gene sets enriched in the riboproteome genes, they uploaded the riboproteome genes to Ingenuity Pathway Analysis (http://www.ingenuity.com) and identified the top biological functions gene sets and canonical pathways gene sets enriched in the riboproteome gene set. To identify KEGG pathways specifically enriched in the subset of riboproteome genes they uploaded the five of five experiments gene list to DAVID and used the one of five experiments gene list as background.Gene ontology analysis was carried out using the online DAVID bioinformatics resource tool.TCGA-Based Analyses of Riboproteome Genomic Alterations across Human Cancers

Western Blot Analysis

Western blot analysis from pooled polysomalfractions validating ribosome-associated proteinsfrom ribosomes of PC3, PPC1, Du145, RWPE1and PWR1E cells. For this analysis, polyribosomeshave been isolated from all cell lines and fractionshave been pooled to obtain subunitsDISCUSSIONFirst, by cross-referencing data from independent SILAC riboproteomic experiments showed that data set is highly enriched in factors that relate directly to the ribosome, to translational initiation and elongation, and to pathways that are known to regulate and control translation.Second, the data sets indicate that the diversity within the riboproteome itself may have the capacity to categorize cell types and tissues and, importantly, may specifically contribute to regulation of gene expression within a given cellular compartment.DISCUSSIONThird, by examining globally how the riboproteome may be altered in diseases such as human cancer, we have made further unexpected observations. We find that riboproteomic components display frequent copy-number amplifications in human cancer, whereas genomic losses within the riboproteome are significantly less than that for nonriboproteomic genes.Fourth, in addition to characterizing the riboproteome landscape in various cell types, we identified and validated a number of proteins previously not known to be associated with actively translating ribosomesLast, our data demonstrate that the cancer riboproteome can be pharmacologically modulated for therapy on the basis of this molecular knowledge.

HighlightsMass spectrometry identifies differential riboproteome components in cancer cellsRiboproteomic genes are frequent targets of genetic amplification in cancerRiboproteomics identifies previously unrecognized ribosome-associated proteins

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