Research questions
Regulation of eukaryotic signal transduction: focussing on protein phosphorylation and protein-protein interactions (in the context of cancer cells invasion and metastasis)
Genome-scale protein expression profiling of tumour tissue to discover novel drug target candidates
New biomarkers and protein-based assays
New approaches to proteomics and phosphoproteomics data analysis (in collaboration with Math Sci.)
Methodology
Applications of high-resolution hybrid mass spectrometry for quantitative genome-scale studies of protein abundance and post-translational modifications
Cell-based models of specific pathways involved in metastasis: mutagenesis, overexpression, stable lines
Structure/function studies in the context of protein phosphorylation and protein-protein interactions
Trypsindigestion
SDS-PAGE or membrane isolationNano-LC-MS/MSa
b c
0 5 10 15 20 250
5
10
15
20
25
30
R² = 0.931513752706484
Spectral count
Norm
alize
d AQ
UA
1 10 100 10001
10
100
1000
10000R² = 0.974789037975781
Spectral counts of replicate 1
Spec
tral
cou
nts o
f rep
licat
e 2
High-definition tumor proteomics using the LTQ/Orbitrap Velos
25,000+ peptide fragmentation spectra in one LC/MS run that takes 90 min. 2000+ proteins can be identified and quantified.
CD74 overexpressed in metastatic TNBC: potential biomarker?C
D74
IHC
sco
re
Node-negative Node-positive0
2
4
6
8
10 p-value = 0.04
IHC staining of CD74 in 19 TNBC specimens CD74 and Scribble spectral counts by LC-MS/MS
IHC staining of CD74 in TNBC
Metodieva et al. 2013, Neoplasia
Quantitative phosphoproteomics and interaction analysis to elucidate mechanisms contributing to metastasis in the context of TNBC.
1. Generate stable lines that express CD74 under the control of highly-regulated inducible promoter
2. Label cells with stable isotopes to allow quantitative analysis of global protein phosphorylation.
3. Identify phosphorylation “hot spots”: protein phosphorylation sites that respond to CD74 overexpression.
Clone 1 Clone 2
Tetracycline - + - +
CD74
We use SILAC (stable isotope labelling by aminoacids in culture). We label both the arginines and the lysines to allow comprehensive phosphopeptide quantitation.
CD74 has been implicated in several kinase-regulated pathways. Therefore we want to identify not only changes in total protein abundance but also phosphorylation site changes in response to CD74 overexpression. For this we use phospho-affinity approaches and quantitative MS.
-2 -1.5 -1 -0.5 0 0.5 1 1.5 20
50
100
150
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LOG2(Ratio H/L Normalized)
Andr
omed
a sc
ore
1: MAESPCSPSGQQPPSPPSPDEIPANVK2: MAESPCSPSGQQPPSPPSPDEIPANVK3: AFAAVPTSHPPEDAPAQPPTPGPAASPEQISFR4: QSPASPPPIGGGAPVR
1
23
4
B C
TetO_SILAC_MEMBR_Phos_1_120716200848 #6764 RT: 49.18 AV: 1 NL: 8.55E3T: FTMS + p NSI Full ms [400.00-2000.00]
988.5 989.0 989.5 990.0 990.5 991.0 991.5 992.0m/z
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
Rel
ativ
e A
bund
ance
989.08
989.41
989.75988.75
990.08
991.42991.08
992.10990.75
991.76 992.46988.96
990.42992.20
989.20
MAESPCSPSGQQPPSPPSPDEIPANVK
Light
Heavy
TetO_SILAC_MEMBR_Phos_1_120716200848 #7780 RT: 55.02 AV: 1 NL: 1.30E4T: FTMS + p NSI Full ms [400.00-2000.00]
1140 1141 1142 1143 1144 1145m/z
0
5
10
15
20
25
30
35
40
45
50
55
60
65
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Rel
ativ
e Ab
unda
nce
1140.88
1140.54
1141.21
1140.21
1141.55
1144.551143.88
1144.21
1143.551141.88
1145.211142.21 1144.88
1143.24
Light
Heavy
AFAAVPTSHPPEDAPAQPPTPGPAASPEQISFR
AS1306S1309
S1348
S1448
Scribble serine phosphorylation hot spots affected by CD74 overexpression in MCF7 and HEK293 cells
Normalized H/L ratios for detected Scribble phosphopeptides
High-resolution MS scans
p-value=0.00068
Metodieva et al. 2013. Neoplasia
Metodieva et al. 2013. Neoplasia
CD74-dependent deregulation of Scribble - confocal imaging
ScribbleBeta-Pix
GIT2GIT1
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
-7 -2 3 8 13
-Log
t-t
est p
val
ue
T-test difference
GFP-Scribble co-IP/MS assay. IPs with anti-GFP and non-specific Ab as a negative control were performed on aliquots of lysate obtained from transfected HEK293 cells and analysed in triplicate by nano-LC-MS/MS. The label-free intensities for all proteins were log-transformed and specific interactors identified by the volcano plot approach . Scribble and the known interactors Beta-Pix, Git1 and Git2 are shown on the plot. Other significant proteins are shown with black symbols.
Protein-protein interaction analysis by GFP co-IP and quantitative LC-MS/MS
External
Rick Bucala, Yale University, USA
Lin Leng, Yale University, USA
David Stone, University of Illinois at Chicago, USA
Louise Aldridge, Griffith University, Australia
Roland Croner, University of Erlangen, Germany
Christina Greenwood, The Helen Rollason Heal Cancer Care Laboratory, Anglia Ruskin University, UK
Khalid Al-Janabi, Histopathology Department, Broomfield Hospital, UK
Collaborations
Internal
Berthold Lausen
Nelson Fernandez
Elena Klenova
Phil Reeves