Metodi post-genomici
Metodi post-genomici
Quantitative analysis of systems biology by taking advantage of
available genomic information at the level of
1.
2.
3.
4.
5.
6.
7.
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)
Many other 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
Metodi post-genomici
• Trascrittomica
• Proteomica
• Systems biology
Transcriptome
The transcriptional complement of the genome
Generazione di sequenze EST
Trascrittomica
DNA Microarrays
Trascrittomica
Metodi di Clustering
• Distanza Euclidea
• Correlazione di Pearson
Genomica e post-genomica
Genetica
Genomica
Bioinformatica
Trascrittomica
Proteomica
Altre “omiche”
Proteomics
• No correlation between mRNA and protein amounts (Gygi
et al., 1999)
• The proteome is an instant picture of the phenotype at
the biochemical level
• The proteome accounts for PTM
“the proteome is the complete set of
proteins of an organ or an organism at a
given time and under specific
physiological conditions” (Wilkins et al.,
1995).
Gygi et al., Mol. Cell. Biol. 19, 1720 (1999);
Wilkins et al., Biotechnol. Genet. Eng. Rev. 13, 19 (1995).
Gel-based vs. 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
Proteomica (2-DE)
• A global, unbiased approach
• Hypothesis-generating rather than hypothesis-driven
• A “find the difference” game between two conditions
Control
Treated
Esempio di 2-DE gel
Proteomica (2-DE)
Find the difference…
Proteomica (2-DE)
Metodi statistici
Differential in-gel electrophoresis (DIGE)
 Matching not needed
o High cost
 Spatially accurate
o Weak signal
 Sensitive to small
quantitative changes
o Only binary
comparison
DIGE
Control [Cy5]
Pharmacological Treatment [Cy3]
Identificazione delle proteine
• Immunoblot
• Peptide mass fingerprinting
• Sequenza interna
Peptide Mass
Fingerprinting
LC-MS/MS
Sequenze interne
Frammentazione dei peptidi
Peptide mass fingerprinting
Identificazione: Mascot
http://www.matrixscience.com/
Identificazione: Mascot
Identificazione: Mascot
Identificazione: Mascot
Gel-free: shotgun
Charged peptides
Issues:
•Ion intensity is not proportional to
quantity.
It depends on
peptides
physicochemical properties (charge,
hydrophobocity…)
•Spectra of the same ion in different
selected and
runs are influencedPeptides
by
external
fragmented
variables (e.g. chromatography)
which may casually alter ionization
efficiency
Reverse Phase Liquid
Chromatography
High pressure is used (High
Performance)
Peptides acelerated
by magnetic fields in
the analyzer and
separated by m/z
Systems Biology
• Necessità di analizzare
un elevato numero di
informazioni
(Network analysis)
• Necessità di arricchire
un ridotto numero di
informazioni
(Network enrichment)
Systems Biology
• Interazione fisica
• Stesso pathway
(KEGG)
• Stessa Gene Ontology
(GO)
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
Protein networks
Graph: a graphical representation
of elements (nodes) connected by
edges.
Nodes are proteins, edges are
interactions
Protein networks
Regulating interactions:
Controls
Inhibits
Feedback
Interacts with…
Building protein networks
•Co-occurrence in databases
•Physical interactions
•Genomic proximity
•Expression
•Proteomics
•Literature (pubmed)
•Pathways (KEGG, Reactome, …)
•GO Terms
How to deal with Complexes
•
Some experimental protocol do generate complex data:
Eg. Tandem affinity purification (TAP)
•
One may want to convert these complexes into sets of
binary interactions, 2 algorithms are available:
Bait
Preys
39
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…
Physical Interaction
Physical Interaction
KEGG Pathways, Reactome
Reactome
PMID:5555
Direct evidence PMID:4444
Direct evidence
human
PMID:8976
mouse
Indirect evidence
PMID:1234
cow
Reactome
REACT_945.4
GO enrichment
http://www.geneontology.org/
GO enrichment
http://www.geneontology.org/
GO enrichment
String 9.0
http://string-db.org/
String 9.0
BioProfiling
http://www.bioprofiling.de/
BioProfiling
R spider
Antonov A.V., Schmidt E., Dietmann S., Krestyaninova
M.,Hermjakob H. R spider: a network-based analysis of gene
lists by combining signaling and metabolic pathways from
Reactome and KEGG databases Nucleic Acids Research,
2010, Vol. 38, No. suppl_2 W118-W123
PPI spider
Antonov A.V., Dietmann S., Rodchenkov I., Mewes H.W. PPI
spider: A tool for the interpretation of proteomics data in the
context of protein protein interaction networks.
PROTEOMICS. Volume 9, Issue 10, 10 May 2009.
Just a (real) example