imaging mass spectrometry - a deeper view of biology
TRANSCRIPT
Oak Ridge Conference
Imaging Mass Spectrometry – A Deeper View of Biology
Erin H SeeleyMass Spectrometry Research Center
Vanderbilt UniversityApril 19, 2012
Imaging/Profiling: MALDI TOF, TOF/TOF, LTQ, IM QTOF, FTICR( Bruker TOFs, 9.4T FTICR; Thermo LTQ; Waters IM QTOF; AB TOF )
MALDI Mass Spectrometry Technology
Laser Detector
Sample Plate
MALDI -TOF MS (linear)
Whole Body Drug and Metabolite Imaging
Sheerin Khatib-Shahidi et al.
Whole Body Protein Imaging•Correlate protein expression changes with drug distribution
Sheerin Khatib-Shahidi et al.
Phospholipid Imaging
Kristin Burnum et al.
In Situ Proteomics (Peptide Imaging)•In situ enzymatic digestion prior to IMS analysis
Reid Groseclose et al.
3D Protein Imaging of a Glioma Tumor Mouse Brain•Integrated 3D IMS with in vivo MRI
Tuhin K Sinha et al.
Imaging Mass Spectrometry (IMS) can visualize the spatial localization of numerous
biomolecules directly from tissue sections without any prior knowledge of the specific molecules being analyzed
Combine Phospholipid and Proteins imaging to Visualize Molecular Changes during Embryo Implantation
Kristin Burnum et al.
MALDI Imaging
Molecular images
Section tissue & apply matrix
Raster of tissue
m/z
Laser
Ion images from a single raster of a mouse brain section– each image is of a different m/z (this set ~1/10 of data set)
MALDI MS Profiling(Histology Directed Molecular Analysis)
sectionHistology & targetedmatrix spotting
MALDI MS of targeted areas
5000 10,0000
rela
tive
inte
nsity
m/z
striatumcortex
Workflow for Histology Directed MS Profiling
Tissue section on MALDI target
Histological areas marked by a biologist / pathologist
1 cm
Coordinates transferred to instrumentation
Matrix deposited on tissue at points of interest from histology
1 mm
5000 10000 15000
0
1000
2000
3000
4000
Inte
nsity
m /z
normal lobular units normal stroma tumor stroma DCIS IMC
Mass spectra from profiled spots
Melinda Sanders
Correlating Histology and MS
-- Fresh frozen tissue
-- Formalin fixed paraffin embedded
Reid Groseclose
FFPE Mouse Brain
Serial Tissues SectionsMounted onto MALDI targets
Antigen Retrieval
On-Tissue TrypsinDigestion
MALDI Imaging /Profiling Mass Spectrometry
Working with Formalin Fixed Paraffin Embedded Tissue
Spitz nevus
Spitzoid Melanoma
Lymph Node with metastasis
Rossitza Lazova (Yale)
MS Analysis of Spitzoid Lesions in FFPE Biopsies
Training set # Patients Classification Accuracy (%)
Spitz nevi (SN) 26 100
Spitzoid Malignant Melanoma (SMM)
25 96
Classification of Spitzoid Lesions based on a 5 peptide feature signature
Validation (test) set # Patients Classification Accuracy (%)
Spitz nevi (SN) 30 97
Spitzoid Malignant Melanoma (SMM)
29 90
56 SN and 54 SMM from Yale University Spitzoid Neoplasm Repository
Melanoma
Spitz Nevus0
20
40
60
80
Inte
ns. [
a.u.
]
800 900 1000 1100 1200 1300 1400 1500m/z
SpitzoidMelanomaSpitz Nevi
HighGrade
LowGrade
5 mm
m/z 8451
m/z 5171
Soft Tissue Sarcomasfrozen tissue
Ginger Holt
High Grade STS; Tumor Necrosis; Normal Tissue Adjacent to High Grade STS; Low Grade STS; Normal Tissue Adjacent to Low Grade STS
Protein Class Imaging Results
m/z 4747
Distance from Margin (µm)
Rel
ativ
e In
tens
ity
HG TumorNormal
10000-5000 5000-10000
Histological Margin
protein
lipidm/z 725
LG TumorHG TumorNormal
Normal
NORMAL
Histology margin
Feature amplitude
Relative Protein Distributions
Potential molecular margin
TUMOR
1 2 3 4 5 6 7 8 9 10 11 12 13 14
A
B
C
D
EF
G
H
IJ
1 2 3 4 5 6 7 8 9 10 11 12 13 14
A
B
C
D
E
F
G
H
I
J
Mass Spectrometry Class Image12 peptide signature Histological Designation
Clear Cell Renal Cell CarcinomaFFPE TMA
TumorNormal
Todd Morgan, Peter Clark
Internal classification accuracy = 99%External validation accuracy = 90%
Profiling / Imaging of Drugs, Drug Metabolitesand Other Small molecules
Imaging Low MW Molecules
250 300 350 400 450 500 550 600m/z
1
2
3
5x10
• MS/MS (e.g.: LTQ, TOF/TOF)• High resolution (e.g.: FTICR, Orbitrap, TOF)• Ion mobility (e.g.: QqTOF)
Principle of CASI (continuous accumulation of selected ions) to enhance dynamic range
courtesy Bruker application note FTMS-37
StorageHexapole
Mass spectrum from lung tissue biopsy obtained on a low res MS (LTQ)
Study of Rifampicin Treated Rabbit Infected with TB
Quad Selection mass: 821.5Quad window: 7 DaCASI fills: 300
Spectrum from Rif Treated TB Lung Tissue by FT-ICR MS (CASI)
Microscopic image
Matrixm/z 821.169
Rifampicinm/z 821.401Accuracy: 3 ppm
Bacterial Lipid*PI(33:1)m/z 821.521Accuracy: 2.7 ppm
LipidPG(40:6)m/z 821.536Accuracy: 2.2 ppm
*predicted Mycobacterium tuberculosis lipid from the species-specific LipidMaps Database.
New Technology Initiatives
Increased Imaging Speed (<< 1 sec/pixel)
High Spatial Resolution Imaging (1-2 μm)
Increased Sensitivity – Derivatization and Targeted Analyses
Ease of Use: Matrix Pre-Coated Targets
MALDI (TOF) IMS using a 5 kHz Nd: YAG continuous laser
m/z 734.4 ( PC 32:0)m/z 788.5 (PC 36:1)m/z 806.5 (PC 38:6)
lipid images acquired at a rate of 30 pixels/s Total image time: < 10 min
Jeff Spraggins
Yellow – m/z 5020; Blue – m/z 8396; White – m/z 8441; Magenta – m/z 8776; Red – m/z 10165; Purple – m/z 10883; Green – m/z 11838; Pink – m/z 21010
3D volume of m/z 5020alpha globing residues 2-47
Perspectives
Instrumental / Methodology Challenges and Needs
Sensitivity - achieve more global coverage (fraction of proteome now observed)
Resolution - better lateral resolution (routine single cell imaging)- higher MS resolution (better resolve isoforms, PTMs, isobars)
Mass Range - routinely beyond 100 kd
Identification - in situ - fast, simple, accurate
Quantitation - reagents and methods - isotope based, relative and absolute
Validation - cross-lab (std protocols), cross-platform reproducibility/standardization
Availability - single manufacturer must provide entire technology ‘solution’
Major Advantages of Direct Tissue Analysis by MS
Molecular images and patterns easily correlate with histopathology
Native molecular distributions provide new biological insights
Excellent discovery technology (no target specific reagents needed)
MS gives exceptionally high throughput (seconds per sample)
Multiple images produced simultaneously at discrete MW values
Mass SpectrometryResearch Center
Richard CaprioliMichelle ReyzerKen ShriverAndrey ZavalinJeff SpragginsPeggi AngelHans Reudolf AerniSara FrappierLisa ManierEduardo DiasJunhai YangKerri GroveJamie AllenBao TranJosh NicklayKristie RoseGlenn Harris
Vanderbilt Collaborators
David HacheyKevin ScheyPaul LaibinisJohn GorePierre MassionEric SkaarReid ThompsonBilly HudsonJohn OatesOlivier BoutaudNancy BrownMark MagnusonRandy BlakelyAnna CarneiroAriel DeutchLynn MatrisianRay Mernaugh
FundingNIH (GMS, NCI, NCRR)Department of DefenseThe Robert and Helen Kleberg
FoundationThe T.J. Martell FoundationThe Gates Foundation
OthersPeter Wild, U ZurichAlan Soloman , U TennesseeJohn Mayer, HarvardReid Groseclose, GlazoSmithKlineKristin Herring, Dept of DefenseKristin Burnham, Batelle PNW LabsPierre Chaurand, U MontrealShannon Cornett, Bruker DaltonicsSK Dey, U CincinnatiGiovanni Sindona, U CalabriaAmosy M’Koma, MeharryGwendoline Thiery, HarvardKristina Schwamborn, Univ. Munich