Imp rint | Research

MPIMG
I mp rint | R es earch R ep ort 2012
Publi shed by the Max Planck In stitut e for Mol ecular G en etic s (MPIMG) ,
B erlin , G ermany, Augu st 2012
E ditorial Board:
Coordination:
Photograp hy :
ScientiT c I llustrations:
P roduction:
Cop ies:
Bernhard G . H errmann , Han s L ehrach,
H.?Hilg er Rop er s, Martin Vingron
Patricia Marquardt
Katrin Ullrich, David Au sserhof er (p 14) ,
Norb ert Michalk e (p 2 11)
MPIMG
Thoma s Didi er , M eta Druck
1,000
Contact:
Max Planck In stitut e for Mol ecular G en etic s
Ihn estr. 63 – 73
14195 Berlin
G ermany
Phone:
Fax :
E mail:
+49 (0) 30 8413?0
+49 (0) 30 8413?1207
info @molg en .mpg.de
For furth er information about th e MPIMG , see http://www.molg en.mpg.d e
Otto Warburg Laboratory
(E stab lish ed: 06/2 007)
Scientists
Jon ath an Woodsm ith (sin ce 01/ 11)
N ouh ad B en lasfer (sin ce 05/ 10)
Anna Hegele∗ (06/07-04/12)
Petra Birth (06/08-12/11)
Reynaldo López-Mirabal*
(07/08-06/10)
PhD students
St efan ie J eh le (sin ce 05/ 12)
Th om as Corw in (sin ce 09/ 10)
Lu ise Ap elt (sin ce 07/ 10)
Mareike Weimann (12/07-02/12)
Josphine Worseck* (09/07-11/11)
Atanas Kamburov*
(01/10-12/11, part time)
Arndt Grossmann* (07/07-12/11)
254
Undergraduate students
F eder icoAp elt (sin ce 11/ 10, p art t im e)
Z iy a Özk an (sin ce 08/09, p art t ime)
Head
U lr ich St elz l (sin ce 06/ 07)
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Franziska Wachsmuth (10/11-06/12)
Chrysovalantis Sourlis (10/09-06/10)
Sylvia Wowro
(07/08-05/09, part time)
Secretary of the OWL
Cor du la Man cin i
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Figure 1: Molecular network information is required to predict genotype – phenotype
relationships. To strengthen predictions about the phenotype from genomic information
(a) cellular interaction networks will be useful (b) but remain probabilistic over groups
of phenotypes. Differential network analyses will discover relevant sets of key molecules
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cellular r esp on se e.g. dur in g dev elop ent or during th e pr ocessing of int ernal or
env ir on ent al cu es. ifferent ial int er act ion p att ern s i ply ech an ist ic ch an ges
th at are th e result of th ese r esp onses an d ill thu s e ost in for at iv e h en
stu dy in g gen otyp e t o phen otyp e r elat ion sh ip s igure c .
Otto WarburgLaboratory
protein interaction dynam ics and iii) exp er im ent al approach es t o dir ect ly inv estie
gate conditional protein eprotein interactions, such as interactions th at e.g. r equ ir e
tr igger ed ph osph ory lation of on e interaction partn er m ediating th e r esponse t o
ch anging conditions.
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ev era studies t o systematica y map protein eprotein interaction ( n etw or s
on a large scale h av e been successfu l and prov en v ery usefu l in furth er studies.
N ev erth eless, for most sp ecies including human on ly a small fraction of all pose
sib le interactions h as been mapp ed t oday. High quality PPI dat a collection and
indep endent assessm ent of dat a quality r emain import ant t ask s.
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and imp lem ented th is as a web t ool. Th e m eth od (CAPPI C) exp loit s th e modu lar
n etw ork arch itectur e indep endent ly ofpr ior param eters or r efer ence set s for con e
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n an international collab oration led by th e Vidal L ab (H arvard/ CCSB , B ost on)
we h av e assessedprotein interaction dat a emp ir ically demonstrating th at system e
atic Y2H interaction dat a, including th ose gen erated with our setup ar e of h igh
pr ecision . Th e study alsor ev ealed th at th e cov erage of th e dat a is low du et or elae
tiv ely low sensitiv ity of th e m eth od. To ov ercom eth is lim it ation , we dev elop ed a
Y2H eseq approach wh ich enab les v ery h igh PPI samp ling through a second gen e
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improv ed sensitiv ity and prov ides a quantit ativ e r eadout th at is indicativ e of th e
quality of th e PPI information . It will accelerate largeescale interact om e mapp ing
effort s.
A s Y2H eseq test case, we compr eh ensiv ely scr een ed proteins involv ed in m eth e
y lation and dem ethy lation , i.e. protein m ethy ltransferases and dem ethy lases such
as AOF2/LSD 1, for interacting partn ers. Protein m ethy lation of non eh ist on e
SURWHLQV LV D ODUJHO\ XQH[SORUHG SRVWWUDQVODWLRQDO PRGL¿FDWLRQ :H UHSRUW interactions between 22 m ethy ltransferases or dem ethy lases and 324 interact e
ing proteins. Th e m ethy ltransferase n etw ork is exp er im ent ally validated, com e
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commun ity and is t e b asis t o study m et y ation dep endent protein interactions
in th e lab in mor e det ail (see below) .
F ocusing on n eurodegen erativ e diseases, we gen erated a PPI n etw ork conn ect e
ing proteins imp licated in Alzh eim er’s disease (AD) with th e Aloy L ab (IRB ,
B arcelona) . Th e study suggest s nov el roles for central proteins in th e n etw ork
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in AD . With th e B ey er L ab (TU Dr esden) a map of human protein interactions
w as inferr ed using combin ed random for est / B ay esian n etw ork s t o distingu ish
functional from physical interactions. Th e map w as in part exp er im ent ally vale
idated and used t o exp lor e th e r elationsh ips of candidate gen es from GWAS of
n eurodegen erativ e diseases, such as AD .
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The go he e is to e e iffe e ti etwo k st tes th t esc ibe ch gi g ce
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lular pr ocesses in vivo. Su ccessful analy sis of n etwork dynam ics thr ou gh dat a
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Figure 2: PPI dynamics involving SF3b÷complex proteins and hPRP8 (Hegele ol ell
2 2 Selected interactions rom the ( 2 F3 2 F the (SF3b SF3b the
hPRP and the hPRP8 modules are sho n istinct PPI patterns or proteins are sug÷
gested or di erent stages (i e
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In a r ecent study, we focu sed on PPI dynam ics of the splicin g cy cle. Pr e³mRNA
splicin g is cat alyz ed by the spliceosom e, a high ly complex, dynam ic and pr o³
tein r ich r ibonu cleopr otein complex th at assemb les de novo on each intr on to
be spliced. Dur in g spliceosom e assemb ly, activation, cat aly sis and disassemb ly,
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descr ibin g 632 interaction s between 200 human spliceosomal pr otein s w as gen³
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sev eral inter estin g dynam ic PPI pattern s with r elevan ce for a better under st and³
in g of the splicin g cy cle. For example, ch an gin g PPIs dur in g B to C tran sition
(Figur e 2) with on e of the m ost central pr otein s, hPRP8, ar e found. Together
with interaction comp etition exp er im ents, these dat a su ggest th at dur in g step 1
of splicin g, hPRP8 interaction s with the SF3b49 pr otein is r eplaced by h SLU7,
p osition in g this essential second step factor close to the activ e site and th at the
DEAH ³box helicaseshPRP2 and hPRP 16 coop eratethr ou gh order ed interaction s
with the G³patch pr otein GPKOW.
257
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Figure 3: Inferring edge directions from PPI data (Vinayagam, Sci Signal 20 11). For each
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the edge direction from topological network properties as well as shortest PPI paths conr
necting membrane receptors and transcription factors. An activated signaling network
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was assembled from all nteract ons that had a d rect on ass gned
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pr oach es. F or ex amp le, w e u sed th e m odel t o ident ify pr ev iou sly un n own m od?
u lat or s of th e E GF/ERK p athw ay, of wh ich
18 w er e v alidat ed w ith cell?b ased
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assay s. It also en a led u s t o m odel E GF ?in du ced pr ot ein ph osph ory lat ion dyn am ?
ics. We cou ld corr elat e in vivo ph osph ory lat ion dyn am ics w ith th e output dist an ce
k e
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r solv in g glo al pr ot ein ph osph ory ?
lat ion ev ent s in a t im e?dep en dent m ann er.
In th e tw o pr oj ect s descr ib ed, w e ex emp lar ily addr essed PPI dyn am ics thr ou gh
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com in ed exp er im ent al an d comput at ion al appr oach es an d su ccessfu lly m odeled
h ow a sign al spr eads fr om an act iv at ed sign alin g p athw ay thr ou gh a den se PPI
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exp er im ent al appr oach t o an alyz e alt er at ion s of PPI p att ern s.
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ar e dyn am ically an d sp at ially con str ain ed t o sep ar at e simu lt an eou sly tr igger ed
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gen et ic v ar iat ion dat a in our int er act ion stu dies an d inv est igat e h ow disease cau s
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tions in T cells . PL oS On e 5(7) :e 11708
Vin ay agam A , St elz l U , Wank er EE
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l
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JM ,
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y ar A , V in ay agam A , Yu
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ot
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k e EE
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n i r J , Wan
r
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