The impact of high-resolution mass
spectrometry in shotgun proteomics :
two case studies
Maarten Aerts
Promotor : Prof. Dr. B. Devreese
Co-Promotor : Prof. Dr. Em. J. Van Beeumen
PhD. defense : Maarten Aerts, May 6th 2010
Presentation Outline
• Proteomics : an introduction
–
–
–
–
–
Definitions
Mass Spectrometry
Protein/Peptide Identification
Impact of High-Resolution MS
Shotgun Approach
PhD. defense : Maarten Aerts, May 6th 2010
Outline
Presentation Outline
• Proteomics : an introduction
• Case study 1 : N. vitripennis venomics
– Biological objectives
– Experimental set-up
– Results
PhD. defense : Maarten Aerts, May 6th 2010
Outline
Presentation Outline
• Proteomics : an introduction
• Case study 1 : N. vitripennis venomics
• Case study 2 : Comparative proteomics on
ciprofloxacin resistance
–
–
–
–
Comparative proteomics
Medicinal objectives
Experimental set-up
Results
PhD. defense : Maarten Aerts, 6th may 2010
Outline
Presentation Outline
• Proteomics : an introduction
• Case study 1 : N. vitripennis venomics
• Case study 2 : Comparative proteomics on
ciprofloxacin resistance
• Conclusions and future perspectives
PhD. defense : Maarten Aerts, May 6th 2010
Outline
Proteomics : Introduction
Central Dogma
DNA
P
Transcription
Duplication
mRNA
Translation
Protein
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Proteomics : Introduction
• Proteins :
- amino acid polymer  structure and function
- define a cell’s phenotype
- molecular ‘active’ molecules
Structural proteins
Transport proteins
Enzymes
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Proteomics : Introduction
• Proteins :
• Proteome : total complement of all proteins present in
a particular cell
at a given time
in a given environment
 Dynamic : alteration due to intra- and extracellular signals
• Genome : total complement of all the genes present in an organism
 Static : identical in all cells
• Gene expression (mRNA or proteins) = Gene function prediction
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Proteomics : Introduction
Gene prediction
Gene function
Transcriptomics
Gene function
Gene prediction
Genomics
Proteomics
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Proteomics : Introduction
Gene prediction
Gene function
Gene prediction
Genomics
Gene function
Transcriptomics
micro array : fast and complete
slow and incomplete coverage
Proteomics
PhD. defense : Maarten Aerts, May 6th 2010
?
Introduction
Proteomics : Introduction
Central Dogma
R
DNA
P
Transcription
Duplication
R
mRNA
R
PTM
Localization
Translation
Protein
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Proteomics : Introduction
Gene prediction
Gene function
Gene prediction
Genomics
Gene function
Transcriptomics
micro array : fast and complete
slow and incomplete coverage
Proteomics
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Proteomics : mass spectrometry
• High-throughput analyses on proteomes, sub-proteomes or
protein complexes based on mass spectrometry to identify,
quantify and/or characterize proteins.
• analytical technique to determine the molecular weight of
molecules, including peptides or proteins
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Proteomics : mass spectrometry
Sample
PhD. defense : Maarten Aerts, May 6th 2010
Peptides
Proteins
Introduction
Proteomics : mass spectrometry
Sample
Ionization
PhD. defense : Maarten Aerts, May 6th 2010
Peptides
Proteins
ESI
MALDI
Introduction
Proteomics : mass spectrometry
Sample
Ionization
Mass analyzer
Detector
PhD. defense : Maarten Aerts, May 6th 2010
Peptides
Proteins
ESI
MALDI
Quadrupole
Ion Trap
TOF
FT-ICR
Orbitrap
Ion Mobility
Introduction
Proteomics : mass spectrometry
Sample
Ionization
Mass analyzer
Detector
PhD. defense : Maarten Aerts, May 6th 2010
Peptides
Proteins
ESI
MALDI
Quadrupole
Ion Trap
TOF
FT-ICR
Orbitrap
Ion Mobility
Introduction
Proteomics : mass spectrometry
GLV12microliter #641-677 RT: 12.93-13.18 AV: 11 NL: 1.07E5
F: FTMS + p NSI Full ms [300.00-2000.00]
837.87141
z=2
100
95
90
85
608.61425
z=3
80
903.89384
z=2
75
70
65
60
55
50
45
970.07498
z=3
40
35
30
1014.08962
z=3
445.12327
z=1
702.30586
z=3
797.37345
z=3
25
527.23200
z=4
20
1058.10497
z=3
15
10
1322.56773
z=2
1492.51834
z=?
1262.41852
z=1
5
1629.64893 1732.00378
z=2
z=1
1906.65597
z=?
0
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
m/z
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Proteomics : Protein/Peptide Identification
Trypsin : K/R
MS
m/z
m/z
Protein database  prediction PMF Unique Peptide Mass Fingerprint
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Proteomics : Protein/Peptide Identification
Trypsin : K/L
MS
Unique Peptide
Fragment Fingerprint
m/z
MS/MS
m/z
Unique Peptide Mass Fingerprint
m/z
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Proteomics : Protein/Peptide Identification
Sample
Ionization
Tandem MS
CID
ECD
ETD
Mass analyzer
Detector
PhD. defense : Maarten Aerts, May 6th 2010
Peptides
Proteins
ESI
MALDI
Quadrupole
Ion Trap
TOF
FT-ICR
Orbitrap
Ion Mobility
Introduction
Proteomics : Protein/Peptide Identification
PMF
• Peptide Mass Fingerprint
• Single protein
• Database searching
 Unique MS fingerprint
PFF
• Peptide Fragment Fingerprint
• Peptide selection
• Database searching
 Amino acid sequence
(MS/MS)
m/z
PhD. defense : Maarten Aerts, May 6th 2010
m/z
Introduction
High-Resolution Mass Spectrometry
• High-throughput analyses on proteomes, sub-proteomes or
protein complexes based on mass spectrometry to identify,
quantify and/or characterize proteins.
• analytical technique to determine the molecular masses of
molecules, including peptides or proteins
• High-Resolution MS
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
GLV12microliter #641-677 RT: 12.93-13.18 AV: 11 NL: 8.47E4
F: FTMS + p NSI Full ms [300.00-2000.00]
608.61425
z=3
100
• Rs : peak width at half peak intensity
 Sharp peaks
608.94852
z=3
95
90
85
80
75
70
•
•
•
•
Peak capacity
Peak detection
Peak selection
Charge state determination
Relative Abundance
65
60
55
50
609.28276
z=3
45
609.33236
z=?
40
35
30
25
20
609.61696
z=3
15
608.54780
z=?
10
5
0
607.6
607.93967
z=?
607.8
608.0
608.40727
z=?
608.2
608.4
608.73901
z=?
608.6
608.8
609.95001
z=3
609.02620
z=?
609.0
609.2
m/z
609.4
609.6
609.8
610.0
610.28283
z=3
610.2
610.4
610.6
610.8
• Mass accuracy
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
GLV12microliter #641-677 RT: 12.93-13.18 AV: 11 NL: 8.47E4
F: FTMS + p NSI Full ms [300.00-2000.00]
608.61425
z=3
100
• Rs : peak width at half peak intensity
 Sharp peaks
608.94852
z=3
95
90
85
80
75
70
•
•
•
•
Relative Abundance
65
Peak capacity : isobaric peptides
Peak detection
Peak selection
Charge state determination
60
55
50
609.28276
z=3
45
609.33236
z=?
40
35
30
25
20
609.61696
z=3
15
608.54780
z=?
10
5
0
607.6
607.93967
z=?
607.8
608.0
608.40727
z=?
608.2
608.4
608.73901
z=?
608.6
608.8
609.95001
z=3
609.02620
z=?
609.0
609.2
m/z
609.4
609.6
609.8
610.0
610.28283
z=3
610.2
610.4
610.6
610.8
• Mass accuracy
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
GLV12microliter #641-677 RT: 12.93-13.18 AV: 11 NL: 8.47E4
F: FTMS + p NSI Full ms [300.00-2000.00]
608.61425
z=3
100
• Rs : peak width at half peak intensity
 Sharp peaks
608.94852
z=3
95
90
85
80
75
70
•
•
•
•
Peak capacity
Peak detection
Peak selection
Charge state determination
Relative Abundance
65
60
55
50
609.28276
z=3
45
609.33236
z=?
40
35
30
25
20
609.61696
z=3
15
608.54780
z=?
10
5
0
607.6
607.93967
z=?
607.8
608.0
608.40727
z=?
608.2
608.4
608.73901
z=?
608.6
608.8
609.95001
z=3
609.02620
z=?
609.0
609.2
m/z
609.4
609.6
609.8
610.0
610.28283
z=3
610.2
610.4
610.6
610.8
• Mass accuracy
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
GLV12microliter #641-677 RT: 12.93-13.18 AV: 11 NL: 8.47E4
F: FTMS + p NSI Full ms [300.00-2000.00]
608.61425
z=3
100
• Rs : peak width at half peak intensity
 Sharp peaks
608.94852
z=3
95
90
85
80
75
70
•
•
•
•
Peak capacity
Peak detection
Peak selection
Charge state determination :
z
m
• Mass accuracy
Relative Abundance
65
60
55
50
609.28276
z=3
45
609.33236
z=?
40
35
30
25
20
609.61696
z=3
15
608.54780
z=?
10
5
0
607.6
607.93967
z=?
607.8
608.0
PhD. defense : Maarten Aerts, May 6th 2010
608.40727
z=?
608.2
608.4
608.73901
z=?
608.6
608.8
609.95001
z=3
609.02620
z=?
609.0
609.2
m/z
609.4
609.6
609.8
610.0
610.28283
z=3
610.2
610.4
610.6
610.8
Introduction
High-Resolution Mass Spectrometry
GLV12microliter #641-677 RT: 12.93-13.18 AV: 11 NL: 8.47E4
F: FTMS + p NSI Full ms [300.00-2000.00]
608.61425
z=3
100
• Rs : peak width at half peak intensity
 Sharp peaks
608.94852
z=3
95
90
85
80
75
70
•
•
•
•
Peak capacity
Peak detection
Peak selection
Charge state determination
Relative Abundance
65
60
55
50
609.28276
z=3
45
609.33236
z=?
40
35
30
25
20
609.61696
z=3
15
608.54780
z=?
10
5
0
607.6
607.93967
z=?
607.8
608.0
608.40727
z=?
608.2
608.4
608.73901
z=?
608.6
608.8
609.95001
z=3
609.02620
z=?
609.0
609.2
m/z
609.4
609.6
609.8
610.0
610.28283
z=3
610.2
610.4
610.6
610.8
• Mass accuracy : database searching
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
GLV12microliter #641-677 RT: 12.93-13.18 AV: 11 NL: 8.47E4
F: FTMS + p NSI Full ms [300.00-2000.00]
608.61425
z=3
100
• Rs : peak width at half peak intensity
 Sharp peaks
608.94852
z=3
95
90
85
80
75
70
•
•
•
•
Peak capacity
Peak detection
Peak selection
Charge state determination
Relative Abundance
65
60
55
50
609.28276
z=3
45
609.33236
z=?
40
35
30
25
20
609.61696
z=3
15
608.54780
z=?
10
5
0
607.6
607.93967
z=?
607.8
608.0
608.40727
z=?
608.2
608.4
608.73901
z=?
608.6
608.8
609.95001
z=3
609.02620
z=?
609.0
609.2
m/z
609.4
609.6
609.8
610.0
610.28283
z=3
610.2
610.4
610.6
610.8
• Mass accuracy : database searching
 peptide identification
 peptide quantification
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
• Rs : peak width at half peak intensity
• FT-ICR : Fourier Transformation Ion Cyclotron Resonance
Magnetic field, B
Cyclotron frequency,
z
 =  B0
m
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
• Rs : peak width at half peak intensity
• FT-ICR : Fourier Transformation Ion Cyclotron Resonance
Magnetic field, B
Cyclotron frequency,
z
 =  B0
m
PhD. defense : Maarten Aerts, May 6th 2010
~ m/z
Introduction
High-Resolution Mass Spectrometry
• Rs : peak width at half peak intensity
• FT-ICR : Fourier Transformation Ion Cyclotron Resonance
Magnetic field, B
Cyclotron frequency,
Multiple m/z
z
 =  B0
m
~ m/z
complex waveform
FT
m/z
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
• Rs : peak width at half peak intensity
• FT-ICR : Fourier Transformation Ion Cyclotron Resonance
Magnetic field, B
Cyclotron frequency,
Multiple m/z
Resolution :
z
 =  B0
m
complex waveform
m
1
~
 B0  Tacq
m50% m z
Slow
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
• Rs : peak width at half peak intensity
• FT-ICR : Fourier Transformation Ion Cyclotron Resonance
• LTQ-FTUltra MS
FT-MS
LTQ
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
• Rs : peak width at half peak intensity
• FT-ICR : Fourier Transformation Ion Cyclotron Resonance
• LTQ-FTUltra MS
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
High-Resolution Mass Spectrometry
• Rs : peak width at half peak intensity
• FT-ICR : Fourier Transformation Ion Cyclotron Resonance
• LTQ-FTUltra MS
• Data-Dependent Acquisition
 Ideal LC-MS platform
high quality MS
high quantity MS/MS
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Protein/Peptide separation
• High-throughput analyses on proteomes, sub-proteomes or
protein complexes based on mass spectrometry to identify,
quantify and/or characterize proteins.
• analytical technique to determine the molecular masses of
molecules, including peptides or proteins
• High-Resolution MS
• Sample complexity  fractionation strategies
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Protein mixture
2D-PAGE
pI / MW
Digest on single
spot containing
one protein
MS and MS/MS
PMF or PFF
Protein mixture
2D-PAGE
Digest on single
spot containing
one protein
MS and MS/MS
PMF or PFF
Protein mixture
2D-PAGE
n x Dim-LC
- SEC
- SCX
- RP
- CF
Digest on single
MS and MS/MS
spot containing Digest on single on intact protein
protein
one protein
(Top-Down)
MS and MS/MS MS and MS/MS
PMF or PFF PMF or PFF
Protein mixture
2D-PAGE
n x Dim-LC
- SEC
- SCX
- RP
- CF
Limitations :
Dynamic range : low abundant
Range physicochemical properties
pI, MW and hydrophobicity
Digest on single
MS and MS/MS
spot containing Digest on single on intact protein
protein
one protein
(Top-Down)
MS and MS/MS MS and MS/MS
PMF or PFF PMF or PFF
Protein mixture
2D-PAGE
n x Dim-LC
GeLC
- SEC
- SCX
- RP
- CF
Digest on single
MS and MS/MS
Digest
on
single
spot containing
on intact protein
protein
one protein
(Top-Down)
Digest on gel band
containing few
proteins
MS and MS/MS MS and MS/MS
LC-MS/MS
PMF or PFF PMF or PFF
PFF
Protein mixture
2D-PAGE
n x Dim-LC
GeLC
- SEC
- SCX
- RP
- CF
Shotgun
proteomics
Digest on complete
protein mixture
Digest on single
MS and MS/MS Digest on gel band
spot containing Digest on single on intact protein containing few
protein
proteins
one protein
(Top-Down)
Enrichment of
targeted peptides
MS and MS/MS MS and MS/MS
LC-MS/MS
2D LC-MS/MS
- SCX
- RP
PMF or PFF PMF or PFF
PFF
PFF
Protein mixture
Shotgun proteomics
• Tryptic digest :
 complexity
 multidimensional LC
Peptide sequencing : MS/MS
• Analyzable peptides represent
proteins
 Proteome coverage
GeLC
Shotgun
proteomics
Digest on complete
protein mixture
Digest on gel band
containing few
proteins
Enrichment of
targeted peptides
LC-MS/MS
2D LC-MS/MS
- SCX
- RP
PFF
PFF
Shotgun Proteomics
LC-MS platform :
- Multi-dimensional LC
- High-Resolution MS
- MS/MS database searching
 Application :
1. Venom proteins of Nasonia vitripennis (parasitoid wasp)
2. Drug resistance mechanism on mouse macrophages
PhD. defense : Maarten Aerts, May 6th 2010
Introduction
Nasonia Venomics : Introduction
• Nasonia vitripennis
• Ectoparasitoid wasp
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Nasonia Venomics : Introduction
• Nasonia vitripennis
• Ectoparasitoid wasp
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Nasonia Venomics : Introduction
• Nasonia vitripennis
• Ectoparasitoid wasp
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Nasonia Venomics : Introduction
• Nasonia vitripennis
• Ectoparasitoid wasp
Venom proteins :
- Host behavior
- Growth alteration
- Immune suppression
- Nutrient metabolism
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Nasonia Venomics : Introduction
•
•
•
•
Nasonia vitripennis
Ectoparasitoid wasp
50 years scientific history
Biological model organism : parasitoids
- controller of insect populations
crop pests
disease vectors
- commercialized
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Nasonia Venomics : Introduction
•
•
•
•
•
Nasonia vitripennis
Ectoparasitoid wasp
50 years scientific history
Biological model organism : parasitoids
Genetic model organism
- Ease of breeding
- Haplodiploidy (recessive vs. dominance)
- Inter-fertility : N. giraulti, N. longcornis
(Complex trait analyses)
 Genome sequence
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Nasonia Venomics : Introduction
 Genome sequence
 Characterization of Venom
- Venom experience (bee)
- Function during reproduction :
- Host behavior
- Growth alteration
- Immune suppression
- Nutrient metabolism
Bee venom : defensive
- Bioinformatic approach : venom protein prediction
 candidate gene list
 confirmation at mRNA
- Proteomic approach
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Nasonia Venomics : Proteomic analysis
10 venom
reservoirs
Trypsin
Shotgun proteomic approach via LC-MS platform
- 2D-LC : first dimension SCX (charge)
second dimension RP (hydrophobicity)
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Nasonia Venomics : Proteomic analysis
10 venom
reservoirs
Trypsin
Shotgun proteomic approach via LC-MS platform
- 2D-LC : first dimension SCX (charge)
second dimension RP (hydrophobicity)
14 proteins
- MALDI TOF-TOF
29 peptides
- ESI FT-MS
258 peptides 76 proteins
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Nasonia Venomics : Results
76 proteins :
61 secretion signal
limited overlap with bioinformatic approach
 complexity
 venom reservoir ≠ venom gland
 23 unknown function
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Nasonia Venomics : Future directions
• First identification of venom proteins
• Characterization of the molecular mechanism behind venom activity :
 efficiency as pest controller : agriculture and human health
 pharmaceutical applications
 transgenic plants or viruses
PhD. defense : Maarten Aerts, May 6th 2010
Nasonia Venomics
Case Study 2 : Ciprofloxacin resistance
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
 intracellular infections e.g. Listeria monocytogenes
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
 intracellular infections e.g. Listeria monocytogenes
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
 intracellular infections e.g. Listeria monocytogenes
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
• Long-term exposure to ciprofloxacin  eukaryotic resistance
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
• Long-term exposure to ciprofloxacin  eukaryotic resistance
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
• Long-term exposure to ciprofloxacin  eukaryotic resistance
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
• Long-term exposure to ciprofloxacin  eukaryotic resistance
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
• Long-term exposure to ciprofloxacin  eukaryotic resistance
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
• Long-term exposure to ciprofloxacin  eukaryotic resistance
ATP
ATP
ATP
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
• Long-term exposure to ciprofloxacin  eukaryotic resistance
ATP
ATP
ATP
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
• Long-term exposure to ciprofloxacin  eukaryotic resistance
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
• Intracellular accumulating antibiotic
• Long-term exposure to ciprofloxacin  eukaryotic resistance
 life-threatening infections
 ATP-driven
 Inhibitors
 Multidrug Resistance Proteins
• Comparative proteomic analysis on membrane proteomes
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Comparative proteomics
PhD. defense : Maarten Aerts, May 6th 2010
Comparative proteomics
WT
CIP
Heavy labeled
Light labeled
Tryptic digest
LC-MS
PhD. defense : Maarten Aerts, May 6th 2010
Comparative proteomics
WT
CIP
Heavy labeled
Light labeled
Tryptic digest
LC-MS
m/z
PhD. defense : Maarten Aerts, May 6th 2010
Comparative proteomics
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Comparative proteomics
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Results
LC-MS (FT-MS)
 900 protein identified and (relatively) quantified
136 proteins with significant
abundance difference between
WT and CIP macrophages
 MRP4 (ABCC4)
- Multidrug Resistance protein
- ATP
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Discussion
MRP4
Confirmed :
- RT-PCR (mRNA)
- Western blot (protein)
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Discussion
 MRP4 (ABCC4)
 p58IPK : Negative regulator of UPR evoked by ER stress
 CIP resistance ~ Stress resistance
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Discussion
 MRP4 (ABCC4)
 p58IPK : Negative regulator of UPR evoked by ER stress
 CIP resistance ~ Stress resistance
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Discussion
 MRP4 (ABCC4)
 p58IPK : Negative regulator of UPR evoked by ER stress
 CIP resistance ~ Stress resistance
?
?
!
MRP4 over-expression  ER stress
No other UPR proteins are differentially expressed
Genome organization
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Discussion
Chr. 14
mrp4
p58IPK
 Gene duplication
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Discussion
 MRP4 (ABCC4)
 p58IPK : Negative regulator of UPR evoked by ER stress
 Remaining proteins :
 related to drug resistance ?
 secondary effects ?
MRP4 : cAMP, Leukotriens, etc.
p58IPK : regulator of Transcription Factors
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
Conclusion
• Identified ciprofloxacin efflux pump : MRP4
• mode of induction : gene duplication
• A model for in vivo drug resistance mechanism
- MRP family : broad substrate specificity
 Antibiotics
 Anti-viral drug
 Chemotherapeutics
- Secondary effects
 Stress resistance
 cell motility and adherence
 creating an environment for new resistance mechanism
PhD. defense : Maarten Aerts, May 6th 2010
Ciprofloxacin resistance
General Conclusions
PhD. defense : Maarten Aerts, May 6th 2010
Conclusions
General Conclusions
• Shotgun proteomics : relevant biological and medicinal problems
 LC-MS platform :
2D-LC or GeLC
Database searching
Automated statistical validation software
High-Resolution MS : FT-ICR
 mass accuracy
 peptide coverage
 protein coverage
 peak detection
 quantification
PhD. defense : Maarten Aerts, May 6th 2010
Conclusions
General Conclusions
• Shotgun proteomics : relevant biological and medicinal problems
 LC-MS platform :
 Nasonia venomics : new venom proteins
 Ciprofloxacin resistance mechanism : MRP4, gene duplication
 Start of new discovery phase
PhD. defense : Maarten Aerts, May 6th 2010
Conclusions
Future perspectives
• Holy grail : sensitivity
• LC-MS platforms
- Mass spectrometry :
mass analyzers
ionization
- Peptide fractionation :
chip-based LC
- Data analysis :
MS/MS homology
Complete proteome coverage
Estimation of FPR
MS/MS independent identification
PhD. defense : Maarten Aerts, May 6th 2010
Future perspectives
Acknowledgement
Promotor : Prof. Dr. B. Devreese
Co-Promotor : Prof. Dr. J. Van Beeumen
Laboratory of Zoophysiology :
prof. Dr. D. de Graaf
Marleen Brunain
Ellen Danneels
Ellen Formesyn
Unité de Pharamcologie Cellulaire et Moléculaire (UCL) :
prof. Dr. P. Tulkens
prof. Dr. F. Van Bambeke
Nancy Caceres
Beatrice Marquez
Friends and Family
L-ProBE colleagues
PhD. defense : Maarten Aerts, May 6th 2010
Acknowlegment
?
PhD. defense : Maarten Aerts, May 6th 2010
Questions