Advanced Protein technology and proteome analysis (2079FBDBMW)
Institution
Universiteit Antwerpen (UA)
This is the summary of Lesson 4 (protein protein interactions) by Xaveer van Ostade. I also have lesson notes from Kurt Boonen's lessons, but with the slides. You can also contact me via messenger for this at a certain price, of course;)
Advanced Protein technology and proteome analysis (2079FBDBMW)
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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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