The Plasma Proteome: Enabling a Revolution in Diagnostics Feb 2004 web.pdf · PPI ©Plasma Proteome...
Transcript of The Plasma Proteome: Enabling a Revolution in Diagnostics Feb 2004 web.pdf · PPI ©Plasma Proteome...
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PPI© Plasma Proteome Institute
The Plasma Proteome:Enabling a Revolution in Diagnostics
Leigh Anderson Ph.D.Founder & CEO, Plasma Proteome Institute
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PPI© Plasma Proteome Institute
Introduction to the PlasmaProteome
• Why the plasma proteome representssuch an enduring technical challenge
• What it takes to develop a comprehensivelist of candidate markers in plasma
• The next step: what we need to carry outsystematic validation of markers tosupport a revolution in diagnostics
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Plasma is the largestand deepest version of the
human proteome
• Largest = Most proteins
• Deepest = Widest dynamic range
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Major Components of thePlasma Proteome
Immunoglobulins
Cellular Proteins(Leakage)
“Plasma
Proteins”
• ~40,000 forms of proteinssecreted to function inplasma, most glycoproteins– Assume 500 gene products x 2
splice variants x 20 glycoforms x2 clip forms
• ~500,000 forms of tissueproteins– Essentially all tissue proteins x
splice and PTM variants
• ~10,000,000 clonal forms ofimmunoglobulin
Total: the largest version ofthe human proteome
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Major Plasma Proteins99% of plasma protein mass
Albumin
IgG Total
Transferrin
Fibrinogen
IgA Total
Alpha-2-MacroglobulinIgM Total
Alpha-1-Antitrypsin
C3 Complement
Haptoglobin
Apolipoprotein A-1
Apolipoprotein B
Alpha-1-acid Glycoprotein
Lipoprotein(a)
Factor H
Ceruloplasmin
C4 Complement Complement Factor B
Prealbumin
C9 Complement
C1q Complement
C8 Complement
1%10%
0 - 90% 90 - 99%
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Fac
tor
H
*He
mo
glo
bin
*A
lbum
inIg
G T
otal
Tra
nsfe
rrin
Fib
rino
gen
IgA
Tot
alA
lpha
-2-M
acro
glob
ulin
IgM
Tot
alA
lpha
-1-A
ntitr
ypsi
nC
3 C
ompl
emen
tH
apto
glob
inA
polip
opro
tein
A-1
Apo
lipop
rote
in B
Alp
ha-1
-aci
d G
lyco
pro
tLi
popr
otei
n(a)
Cer
ulop
lasm
inC
4 C
ompl
emen
tC
ompl
emen
t F
acto
r B
Pre
albu
min
C9
Com
plem
ent
C1q
Com
plem
ent
C8
Com
plem
ent
C5
Com
plem
ent
Pla
smin
og
en
IgD
C1
Inhi
bito
rC
6 C
ompl
emen
tC
7 C
ompl
emen
tC
ompl
emen
t F
acto
r I
Ret
inol
Bin
ding
Pro
tein
iC3b
Thy
roxi
n B
indi
ng G
lobu
linC
2 C
ompl
emen
t P
rote
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hrom
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Pre
curs
or P
rote
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-rea
ctiv
e P
rote
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b F
ragm
ent
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Com
plem
ent
Pro
tein
Fer
ritin
Ran
tes
SC
5b-9
Com
plex
Myo
glob
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glob
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AC
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ompl
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tein
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ng P
rote
ins
Pro
stat
e-S
peci
fic A
ntig
enP
rost
atic
Aci
d P
ho
sph
ata
seC
EA
Mye
lin B
asic
Pro
tein
Tro
poni
n I
Inte
rleu
kin-
1ra
MIP
-1 b
eta
Tro
poni
n T
Inte
rleu
kin-
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alp
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e F
acto
rG
CS
FIn
terf
eron
Alp
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terl
euki
n-2
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rleu
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-Alp
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eron
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eta
Inte
rleu
kin-
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n-10
Inte
rleu
kin-
5In
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n-6
Proteins Measured Clinically in Plasma Span> 10 Orders of Magnitude in Abundance
(Human male 50yr - from Specialty Laboratories Books)
Nor
mal
Ran
ge A
bund
ance
sLo
g10
Con
cent
ratio
n in
pg/
mL
0
2
4
6
8
10
12
1
3
5
7
9
11
Interleukins & Cytokines
Classical Plasma ProteinsTissue Leakage
Other
Dynamic range of2-D gels or LC/MS
Total Cost: $10,695per sample (clinical
assays)
From:The human plasma proteome: history, character,and diagnostic prospects. Anderson, N. L.Anderson, N. G., Mol Cell Proteomics (2002) 1:845-67.
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Nucleic Acids Exist Free in Plasma• Genomic DNA is present in plasma (~1ug/ml)
– Released by apoptosis & necrosis, e.g., by tumorcells
– Mutations (e.g., in P53) can be detected
• mRNA can be detected in plasma– Fetal mRNA can be found free in maternal circulation
• Current and likely future utility confined toqualitative tests (genotyping)– mRNA concentrations are very poor indicators of the
amount of protein products
• Proteins remain the focus of the search fordisease and response markers
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Genetic Component of Variation inAbundance of 15 Proteins in Plasma
0%
20%
40%
60%
80%
100%
C-pe
ptide
Facto
r XIIa
* Ins
ulin-
like
grow
th fa
ctor I
Lept
in
Pros
tate
-spe
cific
antig
en
IGFB
P-3
von
Wille
bran
d fa
ctor
Insu
lin-lik
e gr
owth
facto
r II
Histi
dine-
rich
glyco
prot
ein
Gc (g
roup
-spe
cific
com
pone
nt)
IgE
Facto
r XIII
acti
vity
* Ins
ulin-
like
grow
th fa
ctor-I
PAI-1
ant
igen
Lipop
rote
in(a)P
rop
ort
ion
of
Var
iati
on
Att
rib
ute
d t
o G
enet
ics
(Published values from many sources*= two discordant studies)
Genotype
Phenotype
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Plasma Proteomics Began in SwedenSvedberg, Tiselius, Laurell, et al
Year
1
10
100
1000
10000
1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Lo
g10
Nu
mb
er o
f R
eso
lved
S
pec
ies Number of Zones/Spots
Sequence Identified Unique Proteins
“1-D”
From:The human plasma proteome: history, character,and diagnostic prospects. Anderson, N. L.Anderson, N. G., Mol Cell Proteomics (2002) 1:845-67.
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The Second Phase of Plasma ExplorationBegan with 2-D Gels (c. 1976)
2-D Electrophoresis
300+ resolved spots
40 identified proteins
Anderson,L., Anderson,N. G. High resolution two-dimensionalelectrophoresis of human plasma proteins. (1977) PNAS 74, 5421-5
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2-D Electrophoresis Continued the Growth inNumber of “Spots” but Not Many New Proteins
Year
1
10
100
1000
10000
1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Lo
g10
Nu
mb
er o
f R
eso
lved
S
pec
ies Number of Zones/Spots
Sequence Identified Unique Proteins
“1-D”
“2-D”
40*49+ 60†
From:The human plasma proteome: history, character,and diagnostic prospects. Anderson, N. L.Anderson, N. G., Mol Cell Proteomics (2002) 1:845-67.
* L. Anderson and N. G. Anderson. (1977) PNAS 74,5421-5.+ G. J. Hughes, et al (1992) Electrophoresis 13, 707-14.† Swiss 2DPage website
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>2 Dimensions of Separation RadicallyIncreases the Number of Detected Proteins
Year
1
10
100
1000
10000
1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Lo
g10
Nu
mb
er o
f R
eso
lved
S
pec
ies Number of Zones/Spots
Sequence Identified Unique Proteins
“1-D”
“3+-D”
“2-D”
4049 60
341b607a
From:The human plasma proteome: history, character,and diagnostic prospects. Anderson, N. L.Anderson, N. G., Mol Cell Proteomics (2002) 1:845-67.
a. J. N. Adkins, et al, Mol Cell Proteomics 1, 947-55.b. R. S. Tirumalai, et al, Mol Cell Proteomics 2, 1096-103.c. R. Pieper, et al, Proteomics 3, 422-32.d. H_Plasma_NR-v2
319c
1175d
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Serum
High Abundance Proteins in Plasma or SerumLimit Detection of Minor Components
A: Albumin
B: Transferrin
C: Apo A-I lipoprotein
D: Haptoglobin β-chain
E: α1-Antitrypsin
AE
D
C
B
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Fibrinogen-β
Fibrinogen-α
Fibrinogen-γ
pH 7.5
Mr 200 kD
10 kD
pH 4
Polyclonal Antibodies Specifically and RepeatablyRemove Target Proteins from Serum/Plasma
Proteins Bound from Plasma by Affinity-Purified anti-Fibrinogen Ab
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A: anti-albumin, anti-transferrin,anti-haptoglobin, anti-α-1-antitrypsin, anti-α-1-acidglycoprotein, anti-α-2-HSglycoprotein, anti-hemopexin,anti-transthyretin, anti-antithrombin-III.
B: 50% anti-IgA and 50% anti-IgMC: anti-α-2-macroglobulin
D: anti-apolipoprotein A1
Scout: switching valve 1
Scout: switching valve 2
A B C D
Multicolumn Implementation ofPlasma Immunosubtraction
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Serum Bound Unbound
Multi-Component Immunoaffinity Subtraction Chromatography, AnInnovative Step Towards A Comprehensive Survey Of The Human PlasmaProteome, Rembert Pieper, et al, Proteomics, (2003) Proteomics 3, 422-32.
Antibody Affinity Subtraction of10 High Abundance Proteins from Serum
SubtractedSubtractedAlbuminAlbuminIgGIgGIgA IgA αα11 antitrypsin antitrypsinαα11 acid glycoprotein acid glycoproteinαα22 HS glycoprotein HS glycoproteinHemopexinHemopexinAntithrombin Antithrombin IIIIIITransferrinTransferrinHaptoglobinHaptoglobinTransthyretinTransthyretinIgMIgMαα22 macroglobulin macroglobulin
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PPI© Plasma Proteome InstituteThe Human Serum Proteome: Display Of Approximately 3,500 Chromatographically
Separated Distinct Protein Spots On 2-DE Gels And Identification Of 307 UniquelyAnnotated Proteins, Rembert Pieper, et al, Proteomics 3(7): 1345-64. (2003)
The Current Phase of Plasma ProteomicsEmploys Multi-Dimensional (>2D) Approaches
(e.g., 3-D Chromatography + 2-DE + LC/MS)
66 2-D gels
wholeserum
2 4,5
IASC-serum
6X 11 SEC-serumfractions each
6 AEC-serumfractions
1 3D:
>300 distinct proteingene products
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F4F3
F2 F1
100
100100
50
100
5050
25
50
25
25
25
6.5
6.5
6.5
6.5
5
5
5
5
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So How Many Proteins Are Therein Plasma?
• Different methods yield different sets of proteins– Reasons include physicochemical biases of techniques, and
statistics of peptide choice in MS/MS
• The most comprehensive approach is therefore tocombine data from different approaches– We used four input datasets:
• Base list of ~450 proteins reported in “non-proteomics” literatureas measured/detected in plasma or serum
• Three sets of 300-600 proteins each from proteomics surveys (2-Dgels + MS/MS; LC/LC-MS/MS)
• Combined data can be made non-redundant usingmethods of genomics– Redundancy definition: >95% homology over >=15 amino acid
subsequence• Results from: The Human Plasma Proteome: A Non-Redundant List
Developed by Combination of Four Separate Sources, Anderson etal, Molec. Cell Proteomics, in press
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HAPTOGLOBIN
Achieving Non-Redundancy: MS Identifications ofHaptoglobin in Plasma Proteome Datasets
LCMS1
Fragment
Splice Variant
SwissProtAccessionNumberP00737
P00738
Related Protein P00739
NCBI GI Accession
NumberGI123507GI123510
GI4826762
RefSeqNP_005134
LCMS1LIT
LIT
LIT
2DEMS
2DEMS
2DEMS
LCMS2
LCMS1
From: The Human Plasma Proteome: A Non-Redundant List Developed by Combinationof Four Separate Sources, N. L. Anderson et al, Molec. Cell Proteomics, in press
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Sources of H_Plasma_NR_v2Lit LCMS1 LCMS2 2DEMS Total
Beginning Accessions 468 607 341 319 1735Minus non-human 458 580 330 312 1680Minus intra-source
redundancy and nonhuman accessions
433 475 318 283 1509
Unique to source in NR 284 334 221 141 980Total combined NR list - - - - 1175
• Lit: N.L. Anderson and M. Polanski, result of literature search for proteins detected in plasma or serum.
• LCMS1: J. N. Adkins, S. M. Varnum, K. J. Auberry, R. J. Moore, N. H. Angell, R. D. Smith, D. L.Springer and J. G. Pounds. (2002) Toward a human blood serum proteome: Analysis bymultidimensional separation coupled with mass spectrometry. Mol Cell Proteomics 1, 947-55.
• LCMS2: R. S. Tirumalai, K. C. Chan, D. A. Prieto, H. J. Issaq, T. P. Conrads and T. D. Veenstra. (2003)Characterization of the low molecular weight human serum proteome. Mol Cell Proteomics 2, 1096-103.
• 2DEMS: R. Pieper, Q. Su, C. L. Gatlin, S. T. Huang, N. L. Anderson and S. Steiner. (2003) Multi-component immunoaffinity subtraction chromatography: An innovative step towards a comprehensivesurvey of the human plasma proteome. Proteomics 3, 422-32.
From: The Human Plasma Proteome: A Non-Redundant List Developed by Combinationof Four Separate Sources, N. L. Anderson et al, Molec. Cell Proteomics, in press
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Overlap of Four Plasma Proteome Datasets(Number of NR proteins)
284
141
221
46
5
17
17
7
32
21
32
3
5
334
10
LCMS2
LCMS1Lit
2DEMS• 46 proteins in
all four lists
• 195 proteins in2 or more lists
• 1175 NRproteins total
From: The Human Plasma Proteome: A Non-Redundant List Developed by Combinationof Four Separate Sources, N. L. Anderson et al, Molec. Cell Proteomics, in press
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Some Proteins of H_Plasma_195• adiponectin (involved in the control of fat metabolism and insulin
sensitivity),
• atrial natriuretic factor (a potent vasoactive substance synthesized inmammalian atria and thought to play a key role in cardiovascularhomeostasis),
• various cathepsins (D, L, S),
• centromere protein F (involved in chromosome segregation duringmitosis),
• creatine kinase M chain (an abundant muscle enzyme),
• glial fibrilary acid protein (GFAP: distinguishes astrocytes from otherglial cells),
• psoriasin (S-100 family, highly up-regulated in psoriatic epidermis),
• interferon-induced viral-resistance protein MxA (confers resistance toinfluenza virus and vesicular stomatitis virus),
• melanoma-associated antigen p97 (a proposed cancer marker alsoexpressed in multiple normal tissues),
• mismatch repair protein MSH2 (involved in post-replication mismatchrepair, and whose defective forms are the cause of hereditary non-polyposis colorectal cancer type 1),
From: The Human Plasma Proteome: A Non-Redundant List Developed by Combinationof Four Separate Sources, N. L. Anderson et al, Molec. Cell Proteomics, in press
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Some Proteins of H_Plasma_195
• oxygen regulated protein (which plays a pivotal role in cytoprotectivecellular mechanisms triggered by oxygen deprivation),
• peroxisome proliferator-activated receptor (PPAR) binding protein(which plays a role in transcriptional coactivation),
• prostate-specific antigen (a protease involved in the liquefaction of theseminal coagulum, and one of the few successful cancer diagnostics),
• selenoprotein P (contains selenocyteines encoded by the opal codon,UGA),
• signal recognition particle receptor alpha subunit (an integralmembrane protein ensuring, in conjunction with srp, the correcttargeting of the nascent secretory proteins to the endoplasmic reticulummembrane system),
• squamous cell carcinoma antigen 1 (which may act as a proteaseinhibitor to modulate the host immune response against tumor cells),
• V-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog (thereceptor for stem cell factor).
From: The Human Plasma Proteome: A Non-Redundant List Developed by Combinationof Four Separate Sources, N. L. Anderson et al, Molec. Cell Proteomics, in press
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Signal Sequences in the Plasma Proteome
2DEMS
LCMS2
LCMS1
Lit
no possiblesignal
signal signalconfident
Num
ber o
f Occ
urre
nces
0
200
400
0
400
no possiblesignal
signal signalconfident
Signal Prediction
H_Plasma_195
H_Plasma_NR
From: The Human Plasma Proteome: A Non-Redundant List Developed by Combinationof Four Separate Sources, N. L. Anderson et al, Molec. Cell Proteomics, in press
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PPI© Plasma Proteome Institute
Predicted TransmembraneSegments
0 4 8 12 16 200
50100150200250300350400
0
10
20
30
40
B
Occ
urre
nces
(num
ber,
0-1
Segm
ents
)
Occ
urre
nces
(num
ber,
2-21
Seg
men
ts)
A
0
20
40
60
80
100
120
140
0
5
10
15
Transmembrane Segments (number)
H_Plasma_195
H_Plasma_NR 2DEMSLCMS2
LCMS1
Lit
From: The Human Plasma Proteome: A Non-Redundant List Developed by Combinationof Four Separate Sources, N. L. Anderson et al, Molec. Cell Proteomics, in press
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PPI© Plasma Proteome Institute
GO Component Annotations forSubsets of the Human Proteome
Extracellular7%
Membrane39%
Cytoskeletal3%
Golgi2%
Mitochondrial4%
Nuclear30%
Kinesin complex0%
Intracellular8%
Endoplasmic Reticulum
3%
Lysosomal1%
Cytoplasmic3%
Extracellular27%
Membrane27%Intracellular
2%
Cytoplasmic13%
Cytoskeletal4%
Endoplasmic Reticulum
3%
Golgi2%
Lysosomal2%
Mitochondrial3%
Kinesin complex6%
Nuclear11%
Extracellular
Membrane
Intracellular
Cytoplasmic
Cytoskeletal
Endoplasmic Reticulum
Golgi
Lysosomal
Mitochondrial
Kinesin complex
Nuclear
Extracellular
Membrane
Intracellular
Cytoplasmic
Cytoskeletal
Endoplasmic Reticulum
GolgiLysosomal
Mitochondrial
Kinesin complex
Nuclear
Plasma4 of 4 (46)
Plasma2 of 4 (195)
Plasma 1 of 4 (1,175)
Human Proteome (10,911)
From: The Human Plasma Proteome: A Non-Redundant List Developed by Combinationof Four Separate Sources, N. L. Anderson et al, Molec. Cell Proteomics, in press
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PPI© Plasma Proteome Institute
GO Component Annotations forFour Data Sources
Extracellular
Membrane
Kinesin complex
Intracellular
Endoplasmic Reticulum
Lysosomal
Cytoplasmic
Nuclear
Mitochondrial
Golgi
CytoskeletalExtracellular
Membrane
Intracellular
Cytoplasmic
Cytoskeletal
Endoplasmic Reticulum
Golgi
Lysosomal
Mitochondrial
Kinesin complex
Nuclear
Extracellular
MembraneIntracellular
Cytoplasmic
Cytoskeletal
Endoplasmic Reticulum
Golgi
Lysosomal
Mitochondrial
Kinesin complex
NuclearExtracellular
Membrane
IntracellularCytoplasmic
Cytoskeletal
Endoplasmic Reticulum
Golgi
Lysosomal
Mitochondrial
Kinesin complex
Nuclear
LCMS2
Lit 2DEMS
LCMS1
From: The Human Plasma Proteome: A Non-Redundant List Developed by Combinationof Four Separate Sources, N. L. Anderson et al, Molec. Cell Proteomics, in press
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PPI© Plasma Proteome Institute
GO Functional Categories of Proteins inH_Plasma_NR
0
50
100
150
200
250
Calc
ium
bin
ding
Cyto
kine
DN
A bi
ndin
g
Hor
mon
e
Inhi
bito
r
Prot
ease
Rec
epto
r
Tran
spor
t
Num
ber o
f Occ
urre
nces
Go:Function Assignments
2DEMS
LCMS2
LCMS1
Lit
From: The Human Plasma Proteome: A Non-Redundant List Developed by Combinationof Four Separate Sources, N. L. Anderson et al, Molec. Cell Proteomics, in press
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PPI© Plasma Proteome Institute
Reasons for Optimism re Discoveryof Protein Disease Markers
• Discovery-type proteomics can now detect 500-1,000distinct proteins in serum– Steady improvements in LC-LC/MS-MS
• Many of these proteins fall in classes likely to beinformative re tissue status– Secreted proteins, extracellular domains of plasma
membrane proteins, leaked intracellular proteins
• An open-source database of proteins of proteinsobserved in plasma is emerging
• Single protein markers are not required– Disease associated panels exist where no accurate single-
protein disease marker is available
• A series of measurements over time detects changemore accurately than comparison with simplereference interval
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0
1
2
3
4
1992 1994 1996 1998 2000 2002 2004
Year
Nu
mb
er o
f N
ew P
rote
ins
in P
lasm
a/Y
r Year
1
10
100
1000
10000
1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Lo
g10
Nu
mb
er o
f R
eso
lved
Sp
ecie
s
Number of Zones/SpotsSequence Identified Unique Proteins
“1-D”
“3+-D”
“2-D”
4049 60
305*490+
More New Proteins =Fewer New Diagnostics?
• The gap between what canbe measured on a lab scaleand what can be usedeffectively in clinicaldiagnostics is widening
• The number of tests for newproteins in plasma approvedby US FDA over the lastdecade has declined, andnow approaches zero
• Problems include– Technology mismatch– Regulatory costs– Demonstration of medical
value– Medical economics
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Challenges Facing Marker/DiagnosticProteomics: Translation into
Diagnostic Tests
• Lack of protein measurement platforms gearedto validation (high-throughput, low-cost)
• Access to large, well-organized sample sets forvalidation
• Falling rate of new protein tests over last decade
• Low expectation of diagnostic profitability impairscommercial investment
• Potential IP traffic jam
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A Major Technology Gap Exists BetweenDiscovery and Routine Diagnostic Proteomics
Routine IVDDiscovery
100-10,000# samples2-50~15 mintime required4-52 wks
3-5%CV25-50%$2-100$ per analysis$1,000-$10M1-20# proteins50-700
?
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PPI© Plasma Proteome Institute
“The appealing notion that research advancestravel from bench to bedside is laudable, butconceptually flawed. Even though the U.S.
Congress fully anticipates that funding to theNational Institutes of Health (NIH) will result in
advances in clinical medicine and that otherforces, presumably non-governmental, willtranslate the latest in exciting science intohealth technologies, under the system of
healthcare we have today, this advancement isnot likely to happen.”
Floyd BloomPresident, AAAS
Science 300:1680-1685 (2003)
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Towards a Flexible, High-ThroughputQuantitative MS Platform
• Goals– Assay pre-selected proteins, i.e., identified
candidate disease markers for validationstudies
– Combine specific enrichment with MSquantitation
– Increase speed and throughput bydecreasing reliance on gradient LC
– Avoid method bias towards a class ofproteins
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SISCAPA*: A New Method Combining The Specificity ofMS Detection with Sensitivity of Antibody Capture
(SISCAPA = Stable Isotope Standards with Capture by Anti-Peptide Antibody)
* patent pending
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Selection of Peptides and Anti-Peptide Antibodies
Identification code
Protein Peptide Immunogen RabbitAntibody
Interleukin-6 (IL-6) EALAENNLNLPKGSGC IMM2 Ab 2
Hemopexin (Hx) NFPSPVDAAFRGSGC IMM3 Ab 3
α1-Antichymotrypsin (AAC) EIGELYLPKGSGC IMM4 Ab 4
Tumor necrosis factor alpha(TNFα)
DLSLISPLAQAVRGSGC IMM5 Ab 5
Tumor necrosis factor alpha(TNFα)
CGSGDLSLISPLAQAVR IMM6 Ab 6
• 10,203 peptides generated in silico from 237 known plasmasequences
• Monitor peptides selected based on physical/antigenicityparameters. >80% of proteins had 1 or more “good” peptides.
• Selected peptides synthesized, coupled to albumin carrier, usedin 38-day rabbit immunization protocol. Ab’s affinity purified onsame peptide immobilized on agarose.
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Flow cytometric detection of rabbit anti-peptideantibodies coupled to POROS® –Protein G beads
• A: Black profile; POROS® protein Gbeads incubated with biotinylatedprotein L and fluorescein-labeledstreptavidin (negative control).Green profile; POROS® Streptavidinbeads incubated with biotinylatedProtein L and detected withfluorescein-conjugated streptavidin(positive control).
• B: Detection of covalently coupledrabbit anti-peptide antibodies onPOROS® Protein G beads. Beadscovalently coupled with 5 rabbitaffinity-purified Abs incubated firstwith biotinylated Protein L, followedby detection with fluorescein-conjugated streptavidin.
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PPI© Plasma Proteome Institute
Relative binding of Alexa Fluor®488-labeled peptides tofive affinity purified anti-peptide antibodies
• The binding of fourpeptides, ALX 2-6, byPOROS® affinity matricescontaining either theirhomologous (specific) orheterologous (non-specific)antibodies was analysed.The values for eachantibody are normalized tothe maximum fluorescenceintensity for that antibody.Each value is the medianfluorescence intensity for1200 flow cytometerevents. Ab’s 5 and 6 areagainst opposite ends ofthe same peptide.
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PPI© Plasma Proteome Institute
SISCAPA: Initial LC-MS Experiments
• 100nl Ab-POROS columns(100u ID x 1cm)
• Acid-eluted peptide (fromAb column) captured onC18 and eluted into MSby gradient LC
• N. L. Anderson et al,Mass SpectrometricQuantitation of Peptidesand Proteins Using StableIsotope Standards andCapture by Anti-PeptideAntibodies (SISCAPA), J.Proteome Research, inpress
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PPI© Plasma Proteome Institute
Time, min
31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
SIS2666.34
SIS3615.79 SIS5
694.90
554.78
SIS4534.33
0.0
5000.0
1.0e4
0.0
5000.0
1.0e4
A
B
C
Intensity, cps
3.5e4
4.0e4
4.5e4
5.0e4
5.5e4
6.0e4
6.5e4
7.0e4
Ab Capture from SIS Peptide Mixturewith Selected Ion Monitoring
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PPI© Plasma Proteome Institute
)
40 41 42 43 44 45 46 47 48 49 50 51 52
Time, min
950.46
610.83767.92 472.23
507.28871.97
516.28.
767.9
610.8
615.8
A
B
C D
959.5233
1220.66091107.6035
862.4561775.4235
959.5220
775.4199862.4642
969.5465
785.4437
872.4988
750 850 950 1050 1150 1250m/z, amu
819.4783
932.5742
A
B
C
D
SIS3: NFPSPVDAAFR
Nat3: NFPSPVDAAFR
Nat3+: WKNFPSPVDAAFR
Apo A-I: QGLLPVLESFK
Enrichment and Quantitation of a HemopexinMonitor Peptide by SISCAPA
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PPI© Plasma Proteome Institute
Ab2Ab3
Ab4Ab5
SIS2
SIS3
SIS4
SIS5
0
0.2
0.4
0.6
0.8
1
Relative Quantities of Four SIS Peptides Bound by Four Anti-Peptide Antibodies, Using Two-stage MS Selection (SRM)
Average Peptide Enrichment by Ab > 100-fold
The signals (vertical axis) for each antibody are normalized to the largest signal for that antibody
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PPI© Plasma Proteome Institute
Cycle 1Cycle 2
Cycle 3Cycle 4
Cycle 5
SIS2
SIS3
SIS4
SIS5
0.0
2,000.0
4,000.0
6,000.0
8,000.0
10,000.0
12,000.0
SRM integrated ion current measurements of four SIS peptides eluted on five successive cycles from Ab 3.
Rabbit Polyclonal Anti-Peptide Ab’sCan Be Recycled After Acid Elution
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PPI© Plasma Proteome Institute
Targeted Proteomics (e.g., SISCAPA)Enables Marker Validation
• Focus onmeasurement ofidentified proteins
• Accepts input fromboth proteomicsand genomics
• Bridges gapbetween discoveryand routinediagnostic use
• Hybrid methods,e.g., SISCAPA
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PPI© Plasma Proteome Institute
PPI’s Plasma Marker Validation Project
• Identify marker protein candidates from anysource (literature, proteomics, genomics)
• Develop high-throughput MS-based validationassays
• Assay candidates in large well-characterizedplasma/serum sample sets (disease vs controland population studies)
• Place validation data in public domain• Advance protein measurement technology for
plasma
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PPI© Plasma Proteome Institute
Acknowledgements
• SISCAPA Experiments– Bob Olafson, Derryl Hardy, UVIC-Genome B.C.
Proteomics Centre– Terry Pearson, Lee Haines, Department of
Biochemistry and Microbiology, University of Victoria,B.C, Canada
– John Rush, Cell Signaling
• Plasma Proteome Database– Malu Polanski (PPI)– Richard Fagan, Anna Lobley, Inpharmatica Ltd.,
London– Rembert Pieper, Tina Gatlin, present address: The
Institute for Genomic Research – Radhakrishna S. Tirumalai, Timothy D. Veenstra, Mass
Spectrometry Center, U. S. National Cancer Institute– Joshua N. Adkins, Joel G. Pounds, Biological Sciences
Department, Pacific Northwest National Laboratory
• Graphics– Arkitek Studios, Seattle
Ahmed, NAnderson, N GAponte, AAponte, JBraatz, JBrooke, EDas, TDavis, TEidbo, EEsquer, RField, EGatlin, CGoodman, JHardin, RHofmann, J-PHuang, S-TJett, G
Kho, KKiersarsky, KLennon, JLove, CMakusky, JMatthews, JMcGrath, AMcCrea, CMichael, SMiller, SMondal, MMontgomery, RMyers, TNorouzi, TParmar, PPiasecki, M
Russo, PSchatz, CSeonarain, MSims, CSteiner, SStewart, DSu, QSun, QTaylor, ATaylor, JTran, MVizzi, BWallgren, LWang, FWannberg, SZhou, J
• LSBC Proteomics Alumni