Dit is de samenvatting van Les 4 (protein protein interactions) van Xaveer van Ostade. Ik heb ook lesnotities van de lessen van Kurt Boonen, maar dan bij de slides. Je mag me hiervoor ook contacteren via messenger tegen een bepaalde prijs natuurlijk ;)
Les 4: 20/12
Examen
- Geen vraag over het ar-kel
- Principes van concepts kennen voor advanced
- Deel 1; Boonen -> inzichtsvragen, werking en oefeningen
- Deel 2: Van Ostade
Protein-protein interactomes – techniques
Defini&ons
Interactome:
The set of molecular interac-ons in a par-cular cell, organelle or complex
- Physical interac-ons among molecules, in these case proteins
- Indirect interac-ons among genes (gene-c interac-ons)
o Two genes are involved in the same pathway
Interactomics:
- Studying both the interac-ons and the consequences of those interac-ons between
and among proteins and other molecules within a cell
- Compare such networks between and within species in order to find how such
networks are either preserved or varied.
- “Top-down" systems biology, which takes a global view of a biosystem: collec-on of
large sets of genome-wide and proteomic data
o We are going to collect large set of data, large data like transcriptomics,
metabolomics…, and the proteomic data
- From these data: new hypotheses are formulated that can then be tested by new
experiments: data-driven research (vs. hypothesis-driven research).
o We bring together a whole bunch of data -> how does the data interact with each
other -> from this we can form a new hypothesis and test this hypothesis.
Molecules involved
- Interac-ons between proteins, nucleic acids, lipids, carbohydrates, small molecules,
and between molecules within these families
- Some examples:
o Protein-protein interac-on networks (PPIs) or subsets thereof
o Protein–DNA interactome (gene-regulatory network): formed by transcrip-on
factors, chroma-n regulatory proteins, and their target genes.
o Metabolic networks: chemical compounds in a cell, converted into each other by
enzymes, which have to bind their substrates physically.
- All interactome types are interconnected. For instance:
o Protein interactomes contain many enzymes which in turn form biochemical
networks.
§ Connec-ons between proteins ac-ves and disac-vates enzymes that
transform substrates into products
o Gene regulatory networks overlap substan-ally with protein interac-on networks
and signaling networks.
- Systems biology where we want to have an insight in the whole system
, o Different levels; genomics level, phenomics level (effects that you see under the
microscope), metabolomics, transcriptomics and proteomics -> these interact
which each other -> be[er insight in the working mechanism of the cell
o Bioinforma-cs are important
Size
- The size of an organism's interactome correlates be[er than genome size with the
biological complexity of the organism.
- Although protein–protein interac-on maps containing several thousands of binary
interac-ons are now available for several species, none of them is presently complete
and the size of interactomes is s-ll a ma[er of debate.
- The size is variable, depends on the size of the organism
- The interactome is a be[er reflec-on of the complicity of a organism
- It is impossible to say that an interac-on set is now complete for 100% > you are not
sure that you miss an interac-on
Defining PPIs
- We want to do this on a large scale
- Basic unit of a protein network = protein–protein interac-on (PPI).
Experimental methods: general
- Two frequently used large-scale methods:
- Yeast two hybrid system (Y2H): define the binary interac-ons among two proteins at a
-me.
o Drawback: interac-on in yeast nucleus, ocen no correct protein localiza-on, PTM
etc. -> false posi-ves and even more false nega-ves
§ You will lose a lot of interac-ons
o Advantage: binary interac-ons
§ You know that A interacts with B
- Affinity purifica-on followed by mass spectrometry: iden-fy a protein complex.
o Tag protein, fish out the protein with partners a[ached to this and we inves-gate
the partners
o Drawback: only complexes, no binary interac-ons, LC-MS required
o Advantage: be[er indica-on for func-onal in vivo PPIs
- Proximity labeling followed by mass spectrometry: iden-fy proteins in each other’s
neighbourhood
o Further away from the target proteins, we go broader, and we look at proteins
that are a[ached to the bait protein
o Drawback: how far is neighbourhood?
o Advantage: weak and/or transient interac-ons
Computa7onal methods: predic7on -> Bio-informa7cs
- Make use from the data that comes out of the experiment.
Large scale protein-protein interac0on determina0on
Yeast-two-hybrid and variants
Principle:
A bait protein of interest (red) is fused to the DNA-binding domain (DBD) of a transcrip-onal
ac-vator, whereas a prey protein or a library of prey proteins (blue) is fused to the ac-va-on
domain (AD).
- Bait proteins is the protein of interest
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