Rob Russell Cell Networks University of Heidelberg

Russell Group, Protein Evolution

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Rob RussellCell Networks

University of Heidelberg

Interactions and more interactions


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Aloy & Russell Nature Rev Mol Cell Biol 2006


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But instead of a cell dominated by randomly colliding individual protein molecules, we now know that nearly every major process in a cell is carried out by assemblies of 10 or more protein molecules

Bruce Alberts, Cell 1998


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UASG GAL1-lacZ

aNative GAL4

UASG GAL1-lacZ

X

YUASG GAL1-lacZ

bIndividual hybrids with GAL4 domains

GAL4 DNA-binding domain

GAL4 activating region

UASG GAL1-lacZ

XGAL4 DNA-binding domain

Y

cInteraction between hybrids reconstitutes GAL4 activity

Yeast two-hybrid systemFields & Song, Nature, 340, 245, 1989

Applied to whole Yeast genomeUetz et al, Nature, 403, 623, 2000.Ito et al, PNAS, 98, 4569, 2001.


_________ ____Interaction discovery IThe two-hybrid system

Uetz et al, Nature, 2000. (Yeast)Ito et al, PNAS, 2001. (Yeast)Rain et al, Nature, 2002. (H.pylori)Giot et al, Science, 2003 (D. melanogaster)Li et al, Science, 2004 (C. elegans)

Binary interactions:Bait PreyFUS3 DIG2DIG2 FUS3LSM2 PAT1CKS1 CLB1NPL4 UFD1NPL4 CDC48NPL4 FUC1NPL4 SUA7 . . . . . .

x1000s


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CDC28

CKS

Cyclin A

Gal-4 (N)

Gal-4 (C)(hypothetical)

S12

L22

UASG GAL1-lacZ

XGAL4 DNA-binding domain

Y

cInteraction between hybrids reconstitutes GAL4 activity

Native GAL4

The system works, but how?


_________ ____Two datasets in Yeast

See:Ito et al, PNAS, 2001(comparing to Uetz et al, Nature, 2000)


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50

100

Rel

ativ

e In

tens

ity [%

]

1000 1500 2000 2500 3000 m/z

M

*

*

l M

ll

l l

l

l

l

ll

ll

ll

l

l

Interaction discovery IIAffinity purification (e.g. TAP/MS)

x1000sComplexes:Bait Co-purification partnersFUS3 DIG2 DIG1 DIG3DIG2 FUS3 DIG2NPL4 UFD1 CDC48 FUC1…(Etc.)

Gavin et al, Nature, 2002. (Yeast)Ho et al, Nature, 180, 2002. (Yeast)


_________ ____Trying to define binary interactions from purification data

Hakes et al, Comp Funct Genomics, 2006

Purifications only report a collection of proteins and don’t provide any information about precisely who interacts with whom.

There are thus two models for representing binary interactions from complexes, neither of which are real.

Spoke

Matrix

Reality

Purification


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Total Intersection with 3D ( Transient Total Complexes )

3D structure Two-hybrids Affinity purification Homology Aloy Ito Uetz Ho Gavin

Homology 8597 420 499 79 7 8 1 23 25 2 69 130 61 12 138 126 Aloy 499 499 0 1 1 5 6 1 10 27 17 6 23 17 Ito 8 1 4475 2 3 1 3 3 0 0 1 1

Uetz 25 6 199 1447 9 10 1 3 5 2 Ho 130 27 106 92 72690 3 31 28

Gavin 138 23 113 97 4197 48751

Intersection with each other Total

Different worlds

Comparing interactions to known 3D structures shows that original yeast two-hybrid datasets contain more transient interactions, compared to affinity purification datasets that contain more stable complexes(e.g. of 25 Uetz et al interactions with structures, 23 are transient, 2 are dedicated or stable)

Aloy & Russell, Trends Biochem Sci, 2003


_________ ____Error rates in interaction discovery

Von Mering et al, Nature, 2002

False negatives: interactions known to occur that are missed by a screen - To asses this one needs a reference set of positives (i.e. known interactions) among a set of proteins being screened. The fraction of these missed is the false-negative rate. Relatively simple - normally one has a set of previously determined interactions or “gold standard”

False positives: interactions reported by a screen that are incorrect - To assess this one needs a set of interactions that are known not to occur that are seen in a screen. Very difficult to obtain – how can you know that two proteins definitely do not interact? - tricks include taking pairs of proteins presumed to never see each other (i.e. different cellular compartment, etc.)


_________ ____Error rates in interaction discovery: the old view

Von Mering et al, Nature, 2002


_________ ____Error rates in interaction discovery: the new view

Yu et al, Nature, 2002


_________ ____Sociological bias affects the perceived performance

Braun et al, Nature Methods, 2008

Interactions determined on a protein by protein basis are focused around what the investigator wants to study, and thus biased towards particular areas of biology that are hot.

High-throughput techniques are used precisely to find new interactions.

Thus using the previously determined networks as a “gold standard” is likely to be unfair.


_________ ____Interaction data: predictions I

Aloy & Russell, Nature Rev Mol Cell Biol 2006

Groups of proteins entirely absent in one or more organisms among a closely related set are often functionally/physically associated

Proteins in the same bacterial operon are typically functionally associated, and often physically interacting.

Proteins that are separate in some organisms and fused in others are likely interacting physically.


_________ ____Interaction data: predictions II

Aloy & Russell, Nature Rev Mol Cell Biol 2006

Pairs of proteins homologous to pairs of proteins seen to interact in known 3D structures can interact in the same way.

Pairs of proteins containing a pair of domains often seen in interacting proteins can be used to infer interactions in proteins where interactions have not been observed.

The presence of a linear motif can indicate interactions with proteins known to bind this motif..


_________ ____Interaction databases

Resources are very different in appearance and contentEfforts are underway to make a unified search/view, but not completeThus one needs currently to look at several sites to check if an interaction is knownSome are content (e.g. IntAct, MINT) others are processed and augmented (e.g. STRING) with additional predicted/inferred interactions


_________ ____Interaction networks

Sos-1

Grb-2

RGS-4

RGS-3

Ga/q

Node

Node

Edge


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NodeNode

Edge

Biological interaction networks

Nodes:• Proteins• Genes• Chemicals• Effects(?)

Edges:• Physical interaction (e.g. yeast two-hybrid)• Co-expression (e.g. microarrays)• Same operon• Regulation of gene expression (protein to gene)• Catalysis (e.g. metabolic networks)


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Jeong et al, Nature, 2001.

Interaction networks

Biological networks tend to be scale free: most nodes (e.g. proteins) are connected to only a few others with a handful of “hubs” making many more interactions.

They are also “small-world” in that any pair of nodes tends to be connected via a relatively small number of intermediate nodes.


_________ ____“Hubs” in networks

Hubs are more likely to be lethal when deletedJeong et al, Nature, 2001

Hubs are more likely to be disordered.Haynes et al, PLoS Comp Biol, 2006


_________ ____p53 – the promiscuous transcription factor


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Russell & Gibson, FEBS Lett. 2008

Linear motifs in p53

MDM2

USP7

DNA binding domain (95-289)

CYCLIN

P

P

15:DNA-PK,RSK2,ATM

S

NES

P9:Unknown

37:DNA-PK/ATM

18:CK1sP

P 20:CHK2

P

33:GSK-3s,CDK7,CDKs

46:HIPK2

55:MAPKs P215:AuroraA

P

P

386

P315:AuroraA,CDKs

P

371,376,378:CDK7

P P

P392:CDK2s,CDK7,EIF2AK2

Tetramerization domain (323-356)

IUPred disorder prediction

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Rob Russell Cell Networks University of Heidelberg