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Metodi post-genomici in biochimica cellulare

Metodi post-genomici in biochimica cellulare. Metodi post-genomici. Metodi post-genomici. Quantitative analysis of systems biology by taking advantage of available genomic information at the level of SNPs analysis associated to disease or drug response mRNA (transcriptomics)

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Metodi post-genomici in biochimica cellulare

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  1. Metodi post-genomici in biochimica cellulare

  2. Metodi post-genomici

  3. Metodi post-genomici • Quantitative analysis of systems biology by taking advantage of available genomic information at the level of • SNPs analysis associated to disease or drug response • mRNA (transcriptomics) • Protein (proteomics) • Post-translational modifications (aka “modificomics”) • Surface exposure (surfomics) • Protein-protein interactions (interactomics) • Small metabolites (metabolomics) and their relations (metabonomics) Manyother fantasy exercises (glycomics, lipidomics, allergenomics, degradomics, excluding – perhaps – comics...) G.B Smejkal, “I’m an –omics, you’re an -omics... ” Exp. Rev. Proteomics 3 (2006) 383-385

  4. Metodi post-genomici • Modelli cellulari e animali • Trascrittomica • Proteomica • Systems biology

  5. Modelli cellulari e animali(farmacologici e/o genetici)

  6. Modelli cellulari(farmacologici e/o genetici) • Facilità di mantenimento e trattamento • Possibilità di combinare trattamento farmacologico e manipolazione genetica • Utili per riprodurre un singolo meccanismo • Cellule umane (o murine)

  7. Modelli animali(farmacologici) • Intero organismo vs. cellule isolate • Trattamento sistemico o lesione chimica locale • Possibilità di valutare l’effetto anterogrado/retrogrado

  8. Modelli animali (e vegetali?!?)(genetici) • Organismi modello • Genoma noto • Non solo topo! • Vita breve • Invertebrati (e piante…)

  9. Trascrittomica

  10. Trascrittomica

  11. Trascrittomica

  12. Trascrittomica

  13. Trascrittomica • Distanza Euclidea • Correlazione di Pearson

  14. Proteomica • Non c’è correlazione tra quantità di mRNA e quantità di proteina (Gygi et al., 1999) • Il proteoma è un’istantanea del fenotipo a livello biochimico • Il proteoma tiene conto del processing delle proteine S.P.Gygiet al., Mol. Cell. Biol.19, 1720 (1999)

  15. Proteomica • Metodi basati su 2-DE • Metodi “gel-free”

  16. Two-dimensional electrophoresis (2-DE) Staining

  17. Vantaggi • Possibilità di caricare campioni non purificati • Risoluzione estremamente alta • I gel 2 –DE sono collettori di frazioni proteiche molto efficienti • Proteine sono protette all’interno della matrice del gel Problematiche • Gradiente di pH • Limiti nel determinare proteine poco rappresentate • Capacità di caricare campione • Proteine idrofobiche • Proteine ad alto peso molecolare Proteomica (2-DE)

  18. Proteomica (2-DE) • A global, unbiased approach • Hypothesis-generating rather than hypothesis-driven • A “find the difference” game between two conditions Control Treated

  19. Proteomica (2-DE) Francesca Marco Giovanni Maria

  20. Proteomica (2-DE) Proteine Colorazione Acquisizione Analisi di immagine

  21. Proteomica (2-DE) Find the difference… Controllo Esordio Precoce Esordio Tardivo

  22. Proteomica (2-DE) Find the difference…

  23. Proteomica (2-DE) Metodi statistici

  24. Proteomica (2-DE) Identificazione delle proteine • Peptide mass fingerprinting • LC-MS/MS • Western blot (non globale)

  25. Proteomica (2-DE) Peptide Mass Fingerprinting

  26. Proteomica (2-DE) Peptide Mass Fingerprinting

  27. Proteomica (2-DE) Peptide Mass Fingerprinting (Limiti) • La proteina non è presente nel database • La proteina è ricca di modificazioni co/post-traduzionali • Lo spot nasconde più di una proteina

  28. Proteomica (2-DE) Peptide Mass Fingerprinting (Limiti) • La proteina non è presente nel database • La proteina è ricca di modificazioni co/post-traduzionali • Lo spot nasconde più di una proteina

  29. Proteomica (2-DE) LC-MS/MS

  30. Differential in-gel electrophoresis (DIGE) • Matching not needed • Spatially accurate • Sensitive to small quantitative changes • High cost • Weak signal • Only binary comparison

  31. DIGE Control [Cy5]Pharmacological Treatment [Cy3]

  32. Gel-basedvs.Gel-free Webb-Robertson and Cannon, Brief Bioinform 2007;8:304-317. • Poor detection of acidic- basic- proteins • poor solubility of membrane proteins • limited loading capacity of gradient pH strips (crowding effect) • Low reproducibility of gels • relatively low throughput • 2D gels perform robust separations • 2D gels are well-suited for PTM analysis • Parallel, quantitative and label-free readout Monteoliva and Albar, BRIEFINGS IN FUNCTIONAL GENOMICS AND PROTEOMICS. VOL 3. NO 3. 220–239. Proteins do the job, not peptides

  33. Proteomica (gel-free) • Metodi quantitativi (ICAT, iTRAQ, …) • Protein arrays

  34. Gel-free

  35. MS & Proteomics

  36. Quantitative Proteomics • Labelling (ICAT, iTRAQ, SILAC, 18O enrichment, …) • Label free (AQUA, SRM/MRM, …)

  37. Isotope-codedaffinitytagging (ICAT)

  38. IsobaricTaggingfor Relative and AbsoluteQuantitation (iTRAQ)

  39. Selected/Multiple reaction monitoring (SRM/MRM)

  40. Proteomica (gel-free) • Protein arrays (e SELDI)

  41. What next? • You will call your preferred MS expert to ask her/him to identify your spots • You will get a list of protein names • What tells you that list?

  42. Systems Biology

  43. Systems Biology • Necessità di analizzare un elevato numero di informazioni (Network analysis) • Necessità di arricchire un ridotto numero di informazioni (Network enrichment)

  44. Systems Biology • Interazione fisica • Stesso pathway (KEGG) • Stessa Gene Ontology (GO)

  45. Protein Networks • Cellular processes are regulated by protein interaction networks • Protein networks: • control development programs • regulate signal transduction pathways • manage metabolic pathways • are based on physical interactions or cellular localization

  46. Protein networks Graph: a graphical representation of elements (nodes) connected by edges. Nodes are proteins, edges are interactions

  47. Protein networks Hub: connecting several nodes Subnetwork

  48. Protein networks Regulating interactions: Controls Inhibits Feedback Interacts with…

  49. Building protein networks • Co-occurrence in databases • Physical interactions • Genomic proximity • Expression • Proteomics • Literature (pubmed) • Pathways (KEGG, Reactome, …) • GO Terms

  50. Available Databases • • Free, online PPI data • – IntACT (EBI) http://www.ebi.ac.uk/intact/ • – DIP http://dip.doe‐mbi.ucla.edu/dip/Main.cgi • – MINT http://mint.bio.uniroma2.it/mint/Welcome.do • – BIND/BOND http://bond.unleashedinformatics.com/ • – HPID http://wilab.inha.ac.kr/hpid/ • – UniProt http://www.uniprot.org/ • – NCBI Entrez Gene http://www.ncbi.nlm.nih.gov/sites/entrez?db=gene • • Pathways • – Reactome http://www.reactome.org/ • – KEGG http://www.genome.jp/kegg/pathway.html • – Panther http://www.pantherdb.org/pathway/ • – NCI Nature PathwayInteractionDb http://pid.nci.nih.gov/ • – BioPATH http://www.molecular‐networks.com/biopath/index.html • • Commercial applications • – GeneGO, Ingenuity Pathway Analysis…

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