TOPICS IN (NANO) BIOTECHNOLOGY Genomics & Proteomics Lecture 13 21st June, 2006 PhD Course.

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TOPICS IN (NANO) BIOTECHNOLOGY Genomics & Proteomics Lecture 13 21st June, 2006 PhD Course

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Transcript of TOPICS IN (NANO) BIOTECHNOLOGY Genomics & Proteomics Lecture 13 21st June, 2006 PhD Course.

  • N2L Core Group meeting

  • High quality genome sequencing and annotation (2003)Complete sequencing the genomes of other model organisms (e.g. Mouse)

    The next step: Functional GenomicsDetermine what our genes do through systematic studies of function on a large scaleTranscriptomics - Comparative analysis of mRNA expression /splicingProteomics - Comparative analysis of protein expression and post-translational modificationsStructural genomics - Determine 3-D structures of key family membersIntervention studies - Effects of inhibiting gene expressionComparative genomics - Analysis of DNA sequence patterns of humans and well studies model organismsWhat next?

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  • Beyond Genomics Systems BiologyHuman Genome = 30,000 to 60,000 genes

    Human Proteome = 300,000 to 1,200,000 protein variants

    Human Metabalome = metabolic products of the organism (lipids,carbohydrates, amino acids, peptides, prostaglandins, etc)

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  • Whole genome Once the whole genome is truly known and the whole genome sequences become available for an organism, the challenge turns from identifying parts to understanding function

    Functional genomics The post-genomic era is defined as functional genomicsAssignation of function to identified genesOrganisation and control of genetic pathways that come together to make up the physiology of an organism Functional Genomics

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  • 42% of human genes of unknown function have been found in the human genomeassigning function to these genes using systematic high throughput methods is required

    Functional Genomics

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  • The Periodic Table: Functional grouping of Chemical Elements

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  • Biologists Periodic Table

    Will not be two-dimensionalWill reflect similarities at diverse levelsPrimary DNA sequence in coding and regulatory regionsPolymorphic variation within a species or subgroupTime and place of expression of RNAs during development, physiological response and diseaseSubcellular localisation and intermolecular interaction of protein products

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  • Array of hope? Arrays offer hope for global views of biological processesSystematic way to study DNA and RNA variationStandard tool for molecular biology research & clinical diagnosticsLabelled nucleic acid molecules can be used to interrogate nucleic acid molecules attached to solid support (remember Southern Blotting?)

    (Refer to January 1999, Nature Genetics Supplement, Volume 21)Gene Expression analysis

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  • DNA chips Also known as gene chips, biochips, microarraysbasically DNA-covered pieces of glass (or plastic) capable of simultaneously analysing thousands of genes at a time they can be high density arrays of oligonucleotides or cDNAChips allow the monitoring of mRNA expression on a big scale (i.e many many genes at the same time)

    Gene Expression analysisPre-1995, Northern Blots used to look at gene expression

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  • Gene Expression analysisIncyte

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  • AffymetrixGene Expression analysis

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  • Nanogen_Movie_1Nanogen_Movie_2Nanogen_Movie_3Affymetrix_Movie_3http://www.learner.org/channel/courses/biology/units/genom/images.html

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  • Determining gene functionsequence homologysequence motiftissue distributionchromsme localisationfunction . expression in diseasebiochemical assaysproteomics .expression in models

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  • Protein synthesis

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  • RNA synthesis and processing

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  • Alternatively spliced mRNA

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  • DEFINITION: The mRNA collection content, present at any given moment in a cell or a tissue, and its behaviour over time and cell states (Adam Sartel, COMPUGEN).

    The complete collection of mRNAs and their alternative splice forms is sometimes referred to as the trancriptome. The transcriptome is teh set of instructions for creating all of the different proteins found in an organism.(From Genome to Transcriptome, Incyte)

    The transcriptome

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  • Genome, proteome and transcriptomeThe Proteome- Index to a range of possible proteins - Useful as a map and for inter-organisms analysis- Describes what actually happens in the cell - Complex tools, partial results

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  • Discovery of new proteins: that are present in specific tissuesthat have specific cell locationsthat respond to specific cell statesDiscovery of new variants:of important genesthat work to increase/decrease the activity of the native protein

    The transcriptome reflects tissue source (cell type, organ) and also tissue activity and state such as the stage of development, growth and death, cell cycle, diseased or healthy, response to therapy or stress..

    Use of transcriptome analysis

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  • Proteomicswhere the genome hits the road Proteomics refers to the simultaneous, large scale analysis of all (or many) of the proteins made in a cell at one time to get a global picture of what proteins are made in cells and whenHopefully then we can determine the whys and what we can thus do about it very important for drug developmentThe proteome is the protein complement encoded by a genome and the term was first proposed by an Australian post-doc, Marc Wilkins in 1994

    Beyond genomicsproteomics

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  • Beyond the genome: ProteomicsGenomics involves study of mRNA expression-the full set of genetic information in an organism contains the recipes for making proteinsProteins constitute the bricks and mortar of cells and do most of the workProteins distinguish various types of cells, since all cells have essentially the same Genome their differences are dictated by which genes are active and the corresponding proteins that are madeSimilarly, diseased cells may produce dissimilar proteins to healthy cells However task of studying proteins is often more difficult than genes (e.g. post-translational modifications can dramatically alter protein function)

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  • Identification of all the proteins made in a given cell, tissue or organismIdentification of the intracellular networks associated with these proteinsIdentification of the precise 3D-structure of relevant proteins to enable researchers to identify potential drug targets to turn protein on or offProteomics very much requires a coordinated focus involving physicists, chemists, biologists and computer scientistsBeyond the genome: Proteomics

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  • Major challenge-how do we go from the treasure chest of information yielded by genomics in understanding cellular functionGenomics based approaches initially use computer-based similarity searches against proteins of known functionResults may allow some broad inferences to be made about possible functionHowever, a significant percentage (>30%) of the sequences thus far ascertained seem to code for proteins that are unrelated at this level to proteins of known function

    Beyond the genome: Proteomics

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  • Beyond the genetic make-up of an individual or organism, many other factors determine gene and ultimately protein expression and therefore affect proteins directlyThese include environmental factors such as pH, hypoxia, drug treatment to name a fewExamination of the genome alone can not take into account complex multigenic processes such as ageing, stress, disease or the fact that the cellular phenotype is influenced by the networks created by interaction between pathways that are regulated in a coordinated way or that overlap

    Beyond the genome: Proteomics

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  • Genomic analysis has certainly provided us with much insight into the possible role of particular genes in diseaseHowever proteins are the functional output of the cell and their dynamic nature in specific biological contexts is criticalThe expression or function of proteins is modulated at many diverse points from transcription to post-translation and very little of this can be predicted from a simple analysis of nucleic acids aloneThere is generally poor correlation between the abundance of mRNA transcribed from the DNA and the respective proteins translated from that mRNAFurthermore, transcript splicing can yield different protein formsProteins can undergo extensive modifications such as glycosylation, acetylation, and phosphorylation which can lead to multiple protein products from the same gene

    Beyond the genome: Proteomics

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  • Proteomics ToolsThe core methodologies for displaying the proteome are a combination of advanced separation techniques principally involving two-dimensional electrophoresis (2D-GE) and mass spectrometry http://www.learner.org/channel/courses/biology/units/proteo/images.htmlhttp://www.childrenshospital.org/cfapps/research/data_admin/Site602/mainpageS602P0.html

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  • 2D-GE: basic methodologySample (tissue, serum, cell extract) is solubilized and the proteins are denatured into polypeptide componentsThis mixture is separated by isoelectric focusing (IEF); on the application of a current, the charged polypeptide subunits migrate in a polyacrylamide gel strip that contains an immobilized pH gradient until they reach the pH at which their overall charge is neutral (isoelctric point or pI), hence producing a gel strip with distinct protein bands along its lengthThis strip is applied to the edge of a rectangular slab of polyacrylamide gel containing SDS. The focused polypeptides migrate in an electric current into the second gel and undergo separation on the basis of their molecular size

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  • The resultant gel is stained (Coomassie, silver, fluorescent stains) and spots are visualized by eye or an imager. Typically 1000-3000 spots can be visualized with silver. Complementary techniques, e.g. immunoblotting allow greater sensitivity for specific molecules. Multiple forms of individual proteins can be visualized and the particular subset of proteins examined from the proteome is determined by factors such as initial solubilization conditions, pH range of the IPG and gel gradient2D-GE: basic methodology

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  • General schematic of 2D-PAGE for protein identification in Toxicology

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  • Sample growthSample solubilizationIsoelectric focusing (IPG)2D-PAGEImage analysisImmunoblot (Western)Isolation of spots of interestTrypsin digestion of proteinsMS analysis of tryptic fragmentsIdentification of proteinsGeneral strategy for proteomic analysis

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  • Nature of IPG determines spot location on 2D-PAGE

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  • Limitations of 2D-GEIn the large scale analysis of proteomics, 2D-GE has been the major workhorse over the last 20 years-its unique application in being able to distinguish post-translational modifications and is analytically quantitativeHowever despite the significant improvements (e.g. immobilized pH gradients) to the technique and its coupling with MS analysis it is still difficult to automate Although at first glance the resolution of 2D seems very impressive, it still lags behind the enormous diversity of proteins and thus comigrating protein spots are not uncommonThis is especially of concern when trying to distinguish between highly abundant proteins e.g. actin (108 molecules/cell) and low abundant like transcription factors (100-1000)-this is beyond the dynamic range of 2DEnrichment or prefractionation can often overcome such discrepancies

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  • Limitations of 2D-GEChemical heterogeneity of proteins also presents a major limitationThus the full range of pIs and MWs of proteins exceeds what can routinely be analyzed on 2D-GE. However improvements to IPGs is expected to overcome some of these constraints and greatly imrpove the coverage of the entire proteome of the cellProblems liked with extraction and solubilization of proteins prior to 2D-GE present an even greater challenge-especially for extremely hydrophobic proteins, such as membrane and nuclear proteins. Again recent advances in buffer composition has diminished the scale of this problem

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  • Differential Gel Electrophoresis (DiGE)

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  • Protein identification and characterizationSpecialized imaging software allows for a more detailed analysis of spot identification and comparison between gels, and treatmentsBy a process of subtraction, differences (e.g. presence, absence, or intensity of proteins or different forms) between healthy and diseased samples can be revealedCross-references to protein databases allow assignment by known pIs and apparent molecular size. Ultimate protein identification requires spot digestion (enzymatic) and analysis of charge and mass by mass spectrometry (MS) Spot cutter tools can be coupled to image analysis tools and in gel tryptic digestion techniques in 96 or 384 well format can greatly reduce the bottle-neck in sample identification by MS

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  • Protein analysis by MSCompared to sequencing, MS is more sensitive (femtomole to attomole concentrations) and is higher throughputDigestion of excised spot with trypsin results in a mixture of peptides. These are ionized by electrospray ionization from liquid state or matrix-assisted laser desorption ionization from solid state (MALDI-TOF) and the mass of the ions is measured by various coupled analyzers (e.g. time of flight measures the time for ions to travel from the source to the detector, resulting in a peptide fingerprintThe resultant signature is compared with the peptide masses predicted from theoretical digestion of protein sequences found in databases-identification of protein!Tandem MS allows one to obtain actual protein sequence information-discrete peptide ions can be selected and further fragmented, and complex algorithms employed to correlate exp data with database derived peptide sequences

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  • MS analysis

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  • MS analysis

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  • Antibody arraysGood for low-abundance proteinsProblem is antibody specificity

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  • Protein microarrays

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  • CaveatsThe technology of proteomics is not as mature as genomics, owing to the lack of amplification schemes akin to PCR. Only proteins from a natural source can be analyzed

    The complexities of the proteome arise because most proteins seem to be processed and modified in complex ways and can be the products of differential splicing;

    in addition; protein abundance spans a range estimated to be 5 to 6 orders of magnitude in yeast and 10 orders of magnitude in humans.

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  • challengesComplexity some proteins have >1000 variantsNeed for a general technology for targeted manipulation of gene expressionLimited throughput of todays proteomic platformsLack of general technique for absolute quantitation of proteins

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