Evgeny nikolaev proteomics of body liquids as a source for potential methods for medical diagnostics...
Transcript of Evgeny nikolaev proteomics of body liquids as a source for potential methods for medical diagnostics...
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Proteomics of body liquids as a source for potential methods for medical diagnostics
and mass spectrometry
Prof. Dr. Evgeny Nikolaev
Institute for Energy Problems of Chemical Physics and Institute for biochemical physicsRus. Acad. Sci., Moscow, Russia.
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Modern biological mass spectrometers are mainly
ESI- TOF Measuring time of ion flights in vacuumMALDI-TOF
Orbitraps Measuring frequencies of ion oscillations
Ion traps Measuring ion motion stability parameters
FT ICR Measuring frequencies of ion oscillations in magnetic field
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Ortho – ESI TOFBruker, Thermo, Applied Biosystems, Agilent, Waters…….
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OrthogonalTOF Dodonov 1986
Reflectron Mamyrin 1973
Electrospray Gall 1984
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API Ion source Linear Ion Trap C-Trap
Orbitrap
differential pumping
differential pumping
The Thermo Scientific* LTQ Orbitrap XL* hybrid FTMS
Alexander Makarov Electrostatic axially harmonic orbital trapping: a high-performance technique of mass analysis. Anal. Chem. 2000;72: 1156.
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The main goal of our research is to connect the level of protein expression with diseases or to find disease biomarkers.
Our Project:
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Protein
enzym Mass analysesfragmentation
Isolated peptide
Masses of peptide fragments
Search in database
scoringProtein and DND sequence database
Mass analyses
High throughput proteome analyses by
tandem mass spectrometry methodsBottom-up method
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Protein
энзим анализ масс 1
Массы фрагментовпептидов
Поиск в базе
Tор-down method - direct mass spectrometry of proteins and peptides
Ion transportation
Mass analyses
Masses of peptide fragments
Search in database
scoringProtein and DND sequence database
fragmentation
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KETAAAKFERQYL
K ETAAAKFERQYLKE TAAAKFERQYLKET AAAKFERQYLKETA AAKFERQYLKETAA AKFERQYLKETAAA KFERQYLKETAAAK FERQYLKETAAAKF ERQYLKETAAAKFE RQYLKETAAAKFER QYLKETAAAKFERQ YLKETAAAKFERQY L
Sequencing by MS/MS
For unambiguous sequencing all peptide bonds should be
broken
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…-CHR – C(O) – NH – CHR’-…
Polypeptide backbone fragmentation
b
y
c
z
a
x
CollisionallyActivatedDissociation (CAD)
ElectronCaptureDissociation (ECD)
1960s, 1990s
1998ElectronDetachmentDissociation (EDD)
ElectronTransferDissociation (ETD)
2004
2004
InfraredMultiphotonDissociation (IRMPD)
1960s, 1995
157 nmUV Photodissociation
Metastable-atomInduced Dissociation(MAID)
2004
2005
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ECD spectrum of 11+ ions from bovine ubiquitin
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Problem of methods based on MS/MS identification
- Sensitivity lost –informative are only MS/MS spectra, whose intensity is at least ~10-fold lower than intensity of MS spectra
- There is no possibility to detect all peptides in one run
- Extra time for fragment spectra measurements causes longer chromatography time (application of UPLC is questionable for some types of MS instruments)
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The other possibility in proteomics – usage of high mass measurement
accuracy mass spectrometry
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(From Alan Marshall NHMFL)
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Линейная ионная ловушка
FTMS Data
Магнит7 T
Электронная пушка
ИК-лазер
Linear ion trap
IR laser
Electron gun
Magnet
Ion cyclotron resonance mass spectrometer can measure masses with sub ppm accuracy
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Other mass spectrometers with high accuracy of mass measurements are available nowOrbitrapsQ-TOFs…….
Mass accuracy 1-2 ppm (intern. calib.), 5 ppm (extern. calib.)Resolution 20 000-60 000 FWHM Rate of mass spectra measurements >20 Hz
BRUKER micrOTOF-QII
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At accuracy level of 1 ppm elementary composition of peptide with mass up to 600 Da and amino acid composition of peptide with mass up to 500 Da could be determined almost unambiguously
It is not enough for peptide identification!
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.
If we are using liquid chromatography (LC) or
Capillary electrophoreses (CE) we have another tag
- LC retention time or CE retention time
Accurate mass tag together with retention time Can identify peptide practically unambiguously!
Accurate mass tag retention timeDick Smith group (PNNL)
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RT: 46.10 - 80.40
48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80
Tim e (m in)
0
20
40
60
80
100
120
0
20
40
60
80
100
120
0
20
40
60
80
100
120
Re
lativ
e A
bu
nd
an
ce
0
20
40
60
80
100
120
55.89
60.7364.54
65.9757.46 75.4258.0246.69 49.23 49.88 69.41 72.7954.17 68.8162.5378.2976.66
55.66
60.45
64.35
57.23 65.7857.9149.02 75.2446.48 49.68 55.05 68.6551.57 69.41 72.6166.7762.37
78.1476.47
55.65
60.64
64.33
65.9357.2557.9446.56 49.09 75.2669.2351.54 55.18 68.73 69.52 72.6162.38
78.1776.43
55.90
60.93
64.46
58.17 66.16 75.4246.66 49.97 60.13 68.81 72.7654.27 69.3551.5847.48 64.00 78.4474.20 76.56
NL: 1.07E6
Base Peak F: FTMS + p ESI Full m s [ 350.00-2000.00] MS urine_1-5_0-1ul_150m in
NL: 1.44E6
Base Peak F: FTMS + p ESI Full m s [ 350.00-2000.00] MS urine2nd
NL: 1.83E6
Base Peak F: FTMS + p ESI Full m s [ 350.00-2000.00] MS urine3thd
NL: 5.89E5
Base Peak MS urine4th
LC reproducibility-Agilent 1100LC reproducibility-Agilent 1100
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Thus, there is a possibility in bottom-up approach to proteomics is to create using MS/MS a database for accurate mass tags and retention times as a reference base for fast quantitative measurements ofproteins and peptides concentration in a sample
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VGLQR YVQLR SLR
450 500 550 600 650m/z
522.5 525.0m/z
LC- FTICR
Accurate measured mass: 1568.8768
Validated accurate mass tag (SLTLGIEPVSPTSLR)
...TGLYCESQTPRSLTLGIEPVSPTSLRVGLQRYVQLRSLR ...
…TGLYCESQTPR SLTLGIEPVSPTSLR
trypsinolyses
Fragment (463-477) from Vasorin
Putative mass tag from Homo Sapiens: SLTLGIEPVSPTSLRCalculated mass (1568.8773)And measured retention time
200 600 1,000 1,400 1,800m/z
y9
y8
b10
y7
b9b8
y6
y12
y10
y11b12
b6y5
b7
b11
y13b14b13
y4
LC-MS/MS (e.g. with ion trap)
identification
validation
Vasorin (Homo Sapiens protein)
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FT ICR
I.Boldin, E.Nikolaev
ASMS May 2010Dynamicaly harmonized FT ICR cell
Pressure limited(practically unlimited mass resolution)
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0 40 80 120 160 t (s)-1.5
-1.0
-0.5
0.0
0.5
x103
1.0
I(a.u.)
0 40 80 120 160 t (s)-1.5
-1.0
-0.5
0.0
0.5
x103
1.0
I(a.u.)
609.284060
609.2834 609.2838 609.2842 609.2846 m/z
R = 22,000,000
609.284060
609.2834 609.2838 609.2842 609.2846 m/z
609.284060
609.2834 609.2838 609.2842 609.2846 m/z
R = 22,000,000
Reserpine, Resolving Power 22,000,000 without apodization, 180 s transient
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1072.50
1127.02
1166.53
1208.92
1231.27
1278.60
1303.64
1356.82
1414.48
1445.22
1510.87
1582.751621.38
1661.841704.40
1796.58
1100 1300 1500 1700 1900 m/z
1.0
2.0
x108
3.0
BSA, 0.3mg/ml, 100scans accumulated, accumulation time in collision cell 50ms (7 Tesla)
M Hn+
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1384.246
1384.3701384.454
1384.495 1384.641
1384.767
1384.829
1384.9331384.975
1385.058
1385.142
1385.246
1385.371
1385.4961385.517
1385.6211385.704
1385.7871385.870
1385.9751386.0791386.162
1386.267 1386.4131386.433 1386.5791386.6411386.767
1386.8911386.9741387.1001387.225
1387.329
1387.350
1387.5171387.5791387.642
1387.726
1387.830 1387.9961388.079
1388.1631388.288
1388.372
1388.4761388.5591388.622
1388.7471388.851
1388.9541389.039 1389.2261389.3091389.3501389.475 1389.6431389.7671389.810 1389.9981390.081 1390.2661390.288 1390.415 1390.5791390.581 1390.809 1390.9981391.080 1392.2931392.309 1393.1061393.210 1413.847 1413.997 1414.1881414.2731414.3801414.486 1414.6141414.6991414.784 1414.996 1415.209
1384.6 1385.1 1385.6 1386.1 m/z
1.0
2.0
x108
22s
R = 1.3*106
BSA (65 kD) high resolution mode on 7 Tesla magnet
1208.9803
1208.72 1208.77 1208.82 1208.87 1208.92 m/z
0.5
1.0
1.5
2.0
x108
R = 0.9*106
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Nb3SnCoils
NbTiCoils
21 Tesla FT-ICR Magnet
Field Center to Flange600 - 1100 mm
110 mm Bore
Current Leads, Cryocooler, and
Quench relief for Zero-Loss
2.2 °K Cryostat
D. Markiewicz, NHMFLT. Painter, NHMFLJ. Miller, NHMFLY. S. Choi, KBSI
Slide from Alan Marshall
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FT MS
ESI Q-TOF
ESI TOF
Lab
Lab
Clinic
Accurate mass tag retention time approach
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The most attractive is human plasma, which contains practically all proteins (around 20000 non modified forms)
Human Proteome Detection and Quantitation Project:hPDQ
N. Leigh Anderson, Norman G. Anderson, Terry W. Pearson, Christoph H.Borchers, Amanda G. Paulovich, Scott D. Patterson, Michael Gillette, Ruedi Aebersold and Steven A. CarrMol Cell Proteomics Jan.2009
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Proteins in bloodN. Leigh Anderson‡ and Norman G. Andersn
Protein concentrations are different by 11 orders of magnitude!!!There is no method to solve this analytical problem!
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The main task is searching for proteinbiomarker of early stages of diseases
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Alzheimer’s disease is a progressive brain disorder of elderly people that gradually destroys a person’s memory and ability to learn, reason, make judgments, communicate and carry out daily activities.
Alois Alzheimer (1864-1915)
1906 - 2006
Alzheimer disease
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tangles
Plaques
Aβ – Amyloid A 1-42,
Beta-amyloid peptide
The main component of Alzheimer’s plaques (1984)
Sequenced in 1987
1DAEFRHDSGYEVHHQKLVFFAEDVGSNKGAIIGLMVGGVVIA42
Anomalous accumulation of Beta-amyloid in the form of polymeric aggregates (plaques, tangles) causes Alzheimer
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• Why normal protein (monomeric Beta-amyloid) aggregates to form pathogenic plaques?
• What molecular event is triggering this process?
• Which part of the molecule is subjected to changing?
• How to detect these changes?
Questions to answer
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Pro19
Substitution by prolineAbolishes fibril formation
Met35(O)Oxidation may be Important for toxicity and/or oligomerization
Asp7
Isomerized by 75%In plaques
Essential residues for self-association
Primary structure elements controlling Aβ oligomerization
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The goal is to develop mass spectrometric methodology to distinguish peptides containing
different isomeric forms of individual amino acids and to apply this methodology to fragments
of Alzheimer disease Beta-amyloid
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f
ECD of 1-16 Аβ
z10
z10
z9
z9
Z10 -57(Cα-Cβ bond destruction)
c9
c9
y9
C
Aβ 1-16(isoAsp7)
Aβ 1-16 (Asp7)
Distinguishing aspartate/iso-aspartate in Aβ – Amyloid by ECD
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Y10
1200 1300 1400 1500 1600 1700 1800 1900 2000m/z
0102030405060708090
1000
102030405060708090
100
Rela
tive
Abun
danc
e
1198.45
1585.55
1349.451448.55
1722.73
1585.55
1349.451448.45
1220.271722.45
m/z
B6
700 710 720 730 740 750 760 770 780 790 800 810 820 830 840 850 8600
102030405060708090
1000
102030405060708090
100
Rela
tive
Abun
danc
e
798.36 819.91
756.36
811.36 861.82
847.91
793.36
819.91
861.91847.91811.36
793.36756.27
Iso-aspartate
aspartate
aspartate
776.27
Y6 - H2O
Y6 - H2OY6
B11 B12 B13
B14
B10
DAEFRH DSGYEVHHQK b6
y10
CID
Iso-aspartate
B6+H2O
Distinguishing aspartate/iso-aspartate in Aβ – Amyloid by CID
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Quantitative analyses
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1020 1040 1060 1080 1100 1120 1140 1160 1180 1200 1220 1240
m/z
0
50
100
0
50
100
0
50
100
0
50
100
Re
lativ
e A
bu
nd
an
ce
0
50
100
0
50
100
0
50
1001237.53
1067.52
1182.551017.44
1198.561083.541047.49 1138.561030.45
1185.51
1234.251112.90
1059.40
1237.53
1074.461182.54
1017.44
1198.561083.531047.49 1138.551125.551020.67
1150.821100.60
1237.53
1067.521182.55
1017.44
1083.54 1198.561114.001047.49 1125.55
1061.17
1237.53
1074.47
1182.551017.45
1083.54 1125.551047.49 1198.571029.67 1213.811171.70
1237.53
1074.47
1182.551017.44
1125.551083.54 1198.571029.67 1163.481148.47 1210.531111.66
1237.53
1074.46
1182.541017.44
1125.551198.561083.531030.45 1047.49
1185.56
1112.59 1132.55
1059.67
1164.54
1237.53
1074.46
1067.52 1182.541017.44
1125.551083.54 1198.561030.45 1047.49 1104.34 1227.29
1063.07
NL: 1.04E3
Asp_ECD666.5_FT#1 RT: 25.09 AV: 1 T: FTMS + p ESI Full ms2 [email protected] [email protected] [ [email protected] [email protected] ]
NL: 8.13E2
10isoasp-90asp_ecd666.5_ft#1 RT: 53.31 AV: 1 T: FTMS + p ESI Full ms2 [email protected] [email protected] [ [email protected] [email protected] ]
NL: 7.30E2
15isoasp-85asp_ecd666.5_ft#1 RT: 16.50 AV: 1 T: FTMS + p ESI Full ms2 [email protected] [email protected] [ [email protected] [email protected] ]
NL: 3.87E2
30isoasp-70asp_ecd666.5_ft#1 RT: 29.90 AV: 1 T: FTMS + p ESI Full ms2 [email protected] [email protected] [ [email protected] [email protected] ]
NL: 7.22E2
asp-isoasp_1-1_ecd666.5_ft#1 RT: 131.70 AV: 1 T: FTMS + p ESI Full ms2 [email protected] [email protected] [ [email protected] [email protected] ]
NL: 1.54E3
70isoasp-30asp_ecd666.5_ft#1 RT: 43.08 AV: 1 T: FTMS + p ESI Full ms2 [email protected] [email protected] [ [email protected] [email protected] ]
NL: 1.01E3
isoasp_ecd666.5_ft#1 RT: 59.86 AV: 1 T: FTMS + p ESI Full ms2 [email protected] [email protected] [ [email protected] [email protected] ]
z10-57 z10 c10
z9 c9c8
Relative abundance of 1125.55(z10-57) peak(reference peak 1182.55(z10))
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0 20 40 60 80 100
concentrationab
unda
nce
ratio
ECD mass spectra of six Аβ1-16(α-Asp) and Аβ1-16(β-Asp) peptide mixtures with different relative concentrations
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Our recent results on detection of Aβ1-16, extracted from human blood
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Prototype of molecular diagnostics method
• Extraction of Aβ fraction (~ 500 ng) from 5 ml of human plasma
• Preparation and extraction of Aβ1-16 probe from Aβ pool
• MS analysis of isoD7- to D7- Aβ1-16 ratio in the probe
The next goal is to see this peptide in urine!
42
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Body liquids available noninvasively
Exhaled breath condensateUrineSalivaTearSweat
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Noninvasive diagnostic of human breath system by mass spectrometry monitoring
of exhaled breath condensate
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Breath condenser ECoScreen Jaeger from
VIASYSHealthcare (Germany)
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KERATINS in individual EBC of young healthy nonsmoking donors
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Other proteinsin individual EBC of young healthy nonsmoking donors
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Proteins overexpressed in samples of patients with COPD (Chronic obstructive pulmonary disease) and pneumonia
COPD (n = 17) pneumonia (n = 13)1. Proteins of cytosceleton
Keratins 3, 4, 8 Keratins 4/13, 7/19, 8/18 and 15
Junction plakoglobin Hornerin Desmoplakin
2. Proteases inhibitors
Cystatin А Cystatin А Kininogen-1 Kininogen-1
Cystatins В, МAlpha-1-antitrypsin
3. Other Osteopontin Cytoplasmic actin
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Monitoring of exhaled protein composition after human lung transplantation
Before surgery (artificial lung ventilation)
1st month after surgery 15 months after surgery
Pure protein spectrum because of disturbance of breathDermcidin, Keratin 9, Lysozyme, Ubiquitin
Allograft adoptation and medical treatment Annexin 1, Proteinases inhibitor,Bleomicine-hydrolase, keratin 8Damaged epithelium removal Desmosomal proteins (desmoglein, desmoplakin)Epithelium healing Hornerin, filaggrin
“Normal” proteinsDermcidin, “normal” keratins, Cystatin A, Ubiquitin
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Analyses of urine proteom
SickHealthy
Urine is available in large quantities – ideal analyte for noninvasive diagnostic.
Possibility of biomarker discovery is attracting big attention.1500 proteins (from Mann’s group Adachi et al. Genome Biology 2006, V7, 9, R80) ; 2,362 proteins (Kentsis , A. et al. Proteomics Clinical Applications 2009, 3, (9), 1052-1061).
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Three fractions of voided urine is under investigation
1.Proteome (masses of 3-60 kDa)
2.Peptidome (masses of 0.8-17 kDa)
3.Exosoms (50-90 nm vesicles secreted by a wide range of cell types)
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Before use some proteins as biomarker we need to know its temporal variability and polymorphism(how different is its concentration in body liquids of different individuals)
To clarify this we need to investigate proteomes of hundreds of healthy individuals
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Two kinds of sample donors
People “from street” (blood donation center)and
people in “special conditions”.
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Decision to include a person to the study group
Current control for urogenital and other pathology including kidney
pathology, prostatitis, arterial hypertension, diabetes
Analysis of archival information from medical records
General blood analysis
Examination of internist
Blood pressure measurement
Control for treatment with diuretics and excessive consumption of fluids
For “people from street”
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For “healthy people data base” subsetwe need urine samples from persons under well controlled diet and having healthy lifestyle?
In this case we can test urine temporal variability and polymorphism
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Those are people participating In long term isolation experiments in the frame of space research programs. April- July 2009. March 2010 + 500 days. (The Institute for medical & biological problems RAS)
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Ground based experimental facility
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April- July 2009
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Sample concentration Amicon Ultra Ultracel-15 3 k
Desalting and major protein removal
Urine collection
Centrifugation
LC MS analyses
Carboxymethylation and trypsinolyses
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Database: IPI.Human v.3.52Parent Tolerance: ± 5.0 PPM (Monoisotopic)Fragment Tolerance: ± 0.50 Da (Monoisotopic)Fixed Modifications: Carbamidomethyl (C)Variable Modifications: Oxidation(M) Digestion Enzyme: TrypsinMax Missed Cleavages: 2Instrument type: Ion-trap
Search engine: Mascot
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What is in the DB (Structured Query Language database)
• Run, in which this peptide was identified• Peptide sequence• What protein does this sequence belong to• Mascot score• Modifications• Measured mass• Theoretical mass• Measured charge• RT, when the peptide began to elute from the column• RT, when the peptide finished elution
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Our statistics of the collected AMT tags in the long term isolation experiment
447 LC-MS (liquid chromatography coupled with mass spectrometry) runs totally:
among them
25 samples from each of 6 volunteers have been collected during105 days of isolation experiment.
The number of peptides in the database 3468The number of urine proteins in the database 1055
443 core proteins (all patients have them in their urine)
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Smokers (41 sample) and non-smokers(46 samples)
Peptides Proteins
Total 2758 840
Current statistics of urinary proteome database for ordinary healthy people
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Current statistics of urinary proteome database
233 LC-MS (liquid chromatography coupled with mass spectrometry) runs totally: 102 with samples from smokers, 131 with samples from non-smokers.
Using all peptides
Peptides Proteins
Non-smokers 2527 762
Smokers 1893 627
Total 2758 840
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Influence of life stile on urine proteome
Smokers vs. non-smokers urine proteome
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Using all peptidesPeptides Proteins
Non-smokers 2527 762Smokers 1893 627Total 2758 840
Peptides Proteins
785492132311662865
40% 35%
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Using all peptidesPeptides Proteins
Odd 2232 445Even 2306 467Non-smokers 2535 506
Peptides Proteins
61406493032003229
20% 21%
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Using all peptidesPeptides Proteins
Selection1 1723 365Selection2 1588 337Smokers 1894 400
Peptides Proteins
35302633061417171
25% 25%
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!!
!!!
!
Differences in the numbers of observed proteins participating in particular biological process in urine of smokers and
nonsmokers
Transport, homophilic cell adhesion, lipid metabolic process, inflammatory response, innate immune response, epidermis development, defense response
!
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This type of proteome analyses should be personalized !!
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Quantitative analyses by 18O labeling
25 25
25
Ind
ivid
ual
no
n-l
abel
ed s
amp
les
Pool of labeled Pool of non- labeled
25 I
nd
ivid
ual
lab
eled
sam
ple
s
MS
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C:\
RT: 69.40 - 87.80
70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87
Time (min)
0
20
40
60
80
100
0
20
40
60
80
10076.66
80.0974.97
76.7880.21
76.5774.88 86.1181.4378.59
80.0071.17 78.53 86.9072.80 81.5778.7375.99 85.9972.69 84.6582.53 83.1370.85 73.47 74.80 78.44
76.74
80.0174.96
86.0476.8881.29
79.8971.40 78.5575.10 86.8079.3172.8371.46 76.07 80.1877.00 82.31 82.4373.9472.48 84.7971.26 80.4269.45 77.73 87.41
NL:
1.43E6
Base Peak MS
53_1-10_1ul
NL:
1.36E6
Base Peak MS
53_o18_1-
10_1ul
574 575 576 577 578 579 580 581 582
m/z
0
20
40
60
80
100
0
20
40
60
80
100
575.31
z=2
575.81
z=2
576.32
z=2
577.32
z=2
577.82
z=2
578.32
z=2
NL: 1.43E6
53_1-10_1ul#5161
RT: 76.66 AV: 1 T:
FTMS + p ESI Full
ms [
300.00-1600.00]
NL: 1.34E6
53_o18_1-
10_1ul#5122 RT:
76.74 AV: 1 T:
FTMS + p ESI Full
ms [
300.00-1600.00]
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A List of Candidate Cancer Biomarkers for Targeted ProteomicsMalu Polanski and N. Leigh AndersonBiomark Insights. 2006; 1: 1–48. The Plasma Proteome Institute
list of 1261 proteins believed to be differentially expressed in human cancerAs an initial approach, we have selected a subset of the candidates based on a set of criteria including number of total citations, number of recent citations, proportion of recent citations, known plasma concentration (implying existence of an assay) and clinical use in any context. This subset of 260 candidates88 are detected in urine (Mann’s database) 75 (our database)
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Our partners
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Molecular & Cellular Proteomics 9:2424–2437, 2010.
Prof. Harald Mischak Mosaiques DiagnosticsGmbH, Mellendorfer Strasse 7–9, 30625 Hannover, Germany.
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ROC curves for classificationof patient cohorts with “CKD pattern.”ROC analysis for CKD diagnosis of the training set and the test set after unblinding is shown. 85.5% sensitivity and 100% specificity
Peptide (800 to 17,000 Da) patterns distinguishingpatients with CKD from HC
230 patients 379 healthy
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Samples from 3,600 individuals analyzed by capillary electrophoresis coupled to MS. All processed data were deposited in an Structured Query Language (SQL) database. This database currently contains5,010 relevant unique urinary peptides that serve as a pool of potential classifiers for diagnosis and monitoring of various diseases.
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HPLC-MS run duration is about 1.5-2 hoursUPLC-MS duration is about 10-15 minutes
We need faster technology!!
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• Efficient ion accumulation prior to IMS
• High mass accuracy, high dynamic range data acquisition system
• High IMS-TOF sensitivity due to ion trapping and multiplexing
ION MOBILITY SEPARATIONS IN HIGH THROUGHPUT ROTEOMICS: A NOVEL APROACH TO PROTEIN DETECTION AND IDENTIFICATION
PERIMENTAL PLATFORM
Mikhail BelovBiological Sciences DivisionPacific Northwest National Laboratory
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TkdensityN
ZeK
bav _216
3
Mobility
K ELtdrift Drift time
Thermal diffusion-limited maximum resolution
Temporal spread
2ln16 Tk
LEZeR
bd
2
2
2sc
driftinit t
R
ttt
ION MOBILITY SPECTROMETRY (IMS)
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ADDITIONAL ANALYTICAL PEAK CAPACITY DUE TO IMS
Only 3 features discerned without drift time dimension (*)
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Conclusions
1.Accurate mass tag/retention time databases for human urine proteome and peptidome were created
2.Subset of the database contains data from healthy people leaving in long term isolation conditions under the same diet
3.The new approach is developed for rapid analyses of urine proteome using AMT/RT database
4.Significant difference in protein and peptide content of urine of people with kidney diseases has been found inside some groups of proteins and peptides responsible for particular pathways