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Imaging mass spectrometry of intact biomolecules in tissue sections
C H A P T E R
19 Imaging mass spectrometry of intact biomolecules in tissue sections Erin H. Seeley, Richard M. Caprioli Mass Spectrometry Research Center, Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN, United States
O U T L I N E Introduction
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Three-dimensional imaging
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Matrix application
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High-speed imaging
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Protein analysis
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Conclusions and perspectives
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Peptides and protein digests
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Acknowledgments
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Lipid analysis
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References
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Drug analysis
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Introduction Imaging mass spectrometry (IMS) technology enables the in situ analysis of biomolecules and pharmaceutical compounds directly from thin tissue sections.1–3 Thin sections (typically 5–20 μm) are taken from a block of tissue and collected onto a target in a fashion similar to histological analysis. After collection, sections are processed by one of several methods depending on the class of molecules to be analyzed. These steps may include dehydration,
Proteomic and Metabolomic Approaches to Biomarker Discovery https://doi.org/10.1016/B978-0-12-818607-7.00019-0
washing with organic solvents or buffers, and matrix application. Mass spectral data are generated using an ionization probe passed over the tissue surface in a raster pattern, where each ablated spot or pixel gives rise to an individual mass spectrum. Traditional proteomic techniques for the analysis of molecules from tissue specimens, such as liquid chromatography-mass spectrometry (LC-MS) or two-dimensional (2D) gel analysis, require the tissue be homogenized prior to analysis, eliminating the spatial localization of
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Copyright # 2013 Elsevier Inc. All rights reserved.
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analytes. Immunohistochemistry (IHC) allows for the localization of specific molecules within a tissue section but requires that the specific analyte of interest be known in advance and an antibody-based reagent against it must exist. Additionally, only a few molecules can be probed from a single tissue section. Conversely, IMS is carried out without the need for homogenization, allowing for the analysis of hundreds to thousands of biomolecules in their native locations within a single tissue specimen. This technology is excellent for discovery because no target-specific reagents such as antibodies are required. Several surface ionization techniques can be used to generate data for IMS applications. One of the earliest approaches was secondary ion mass spectrometry (SIMS), in which a surface is bombarded with a primary ion beam, leading to desorption of molecules and generation of secondary ions.4–6 Although the SIMS approach allows for very high spatial resolution imaging (<1 μm), the high-energy primary ion beam is destructive to the surface biomolecules generated, effectively limiting the practical mass range of analysis to <1000 Da. Desorption electrospray ionization (DESI) uses a capillary spray of solvent onto the surface of the tissue to desorb ions from a tissue surface that are introduced into a mass spectrometer through a second inlet capillary.7–9 Advantages of the DESI technique are that it can be performed at ambient pressure and requires minimal sample preparation. However, it is most effective in analyzing small molecules such as drugs and lipids and spatial resolution is typically greater than 100 μm. Liquid extraction surface analysis (LESA) uses a small volume of solvent applied to an area of interest on a tissue section using a pipet, which is then drawn back up into the tip.10 The extracted molecules are analyzed using rapid LC-MS, often employing selected reaction monitoring (SRM). The LESA technique is limited by low spatial resolution; targeted areas are often on the order of 1 to 2 mm but could be applicable
to any type of molecule that can be extracted from the tissue surface. Other lesser-used approaches include laser ablation electrospray ionization,11 matrix-assisted laser desorption electrospray ionization,12 and jet desorption electrospray ionization.13 These latter techniques will not be discussed in detail in this chapter and the reader is referred to reviews that describe these methods in detail.14,15 In the present chapter, we focus on the use and application of matrix-assisted laser desorption/ionization (MALDI) IMS as the most broadly applicable approach for the analysis of a wide variety of biomolecules. MALDI IMS has been used for the analysis of proteins, peptides, lipids, drugs, and metabolites from tissue specimens ranging in size from cell clusters16 to whole animal sections.17 In the MALDI approach, a matrix (typically a small organic molecule) is applied to the surface of a tissue section in a solvent that aids in the extraction of analytes. The specific matrix and solvent used can be optimized for different classes of molecules.15 A raster of the tissue surface using a laser induces the desorption and ionization of molecules from the tissue surface (Fig. 1). Commercial instruments allow for achievable spatial resolutions of approximately 20 μm, and custom modifications through use of specialized optics have allowed for spatial resolutions of approximately 1 μm.18 As usual, the tradeoff between spatial resolution and sensitivity ultimately determines the actual resolution employed in a given experiment.
Matrix application A variety of techniques can be used to apply matrix to the tissue surface and the method of choice depends on the imaging task that is to be done. Wet extraction methods such as spotting19 and spraying20 result in a higher degree of analyte extraction, especially for larger polar molecules such as proteins, but may cause large
Matrix application
FIG. 1 Workflow for MALDI IMS. Sections are taken from a tissue specimen and collected onto a target plate or a microscope slide for histological staining. Matrix is applied via spray coating, sublimation, or robotic spotting. Spectra are collected in an ordered array from the surface of the tissue section. Ion images can be generated from any of the signals in the mass spectra.
crystals to form, somewhat limiting the attainable spatial resolution. Drier matrix application methods such as sublimation21,22 are less efficient at extracting larger biomolecules but result in much smaller matrix crystals on the sample surface, allowing higher spatial resolution to be achieved. The simplest and most inexpensive approach is the use of an airbrush sprayer to manually apply matrix.23 This approach has been used successfully for imaging applications but leads
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to the production of moderately large crystals (20–100 μm) and suffers from a lower degree of reproducibility between different spray devices and individuals. Automated spray devices such as the TM Sprayer from HTX Technologies and the ImagePrep from Bruker Daltonics allow more homogeneous and reproducible coatings to be achieved. Spray coatings can be used for imaging any class of molecules at relatively high spatial resolution; however, care must be taken with any spraying technique to ensure that the surface is not made too wet, which can lead to delocalization of analytes. Very high spatial resolution can be achieved using sublimation to deposit matrix onto the tissue section. Powdered matrix is heated under vacuum and is redeposited onto a cooler sample target that is suspended above the matrix. Crystals formed are typically <1 μm and the coating is very homogeneous. When conditions such as temperature, pressure, and time are carefully controlled, sublimated coatings are highly reproducible and applicable for the analysis of most classes of lipids, as no solvent is needed for extraction. If larger molecules such as peptides and proteins are to be analyzed, the use of a rehydration/recrystallization step is employed to help cocrystallize these molecules with the matrix.24 Matrix and other reagents can also be applied to the tissue through the use of robotics such as acoustic spotters (Labcyte Portrait)19 and chemical inkjet printers.9 Although these spotters cannot achieve the spatial resolution of the uniform coating technologies described previously (i.e., they are typically limited to 150–200 μm spot size), they tend to have the highest reproducibility due to the tight control of the exact volume of reagent applied to a specific location on a surface. Spotting generally leads to the most robust analyte signal due to the ability to thoroughly wet small areas of a tissue section for increased extraction without the risk of delocalization that occurs with spray or rehydration techniques.
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Because of the small reservoir volume (hundreds of microliters) of commercial spotters, they may also be employed for the application of relatively costly reagents to the tissue section, including enzymes for proteolytic digestion and internal standards for drug analysis and quantitation. An additional benefit of robotic spotters is the ability to deposit matrix or other reagents at very specific locations within a tissue section, allowing for an approach known as histology directed profiling.25 In this type of experiment, two sections of a tissue specimen are collected, one on a MALDI target and a second serial section on a standard microscope slide for histological staining. After a photomicrograph of the stained section is taken, the image is annotated by a pathologist or biologist to indicate areas of interest. The annotated image is then merged with an image of the unstained serial section using photo processing software and the coordinates of the annotations are determined. These coordinates are transferred to the robotic spotter and matrix is applied only to those specific locations. Typically 10 to 20 areas are targeted per cell type per tissue, with 10 or more samples analyzed in a single experiment. This directed analysis greatly reduces the volume of data collected, increases the throughput, and enables more facile statistical analysis. Histology directed profiling can be thought of as a type of low-resolution imaging through correlation with a microscopy image. In this way, the spatial localization of analytes is preserved while generating highquality data.
Protein analysis Imaging mass spectrometry has been used for the analysis of proteins in cancer tissue, prostate,10,31,32 including breast,26–30 33 34 35 36–40 kidney, skin, colon, lung, ovarian,41 42,43 and gastric as well as other diseases such as inflammatory bowel diseases,44 S. aureus infection,45 and sarcoidosis.46 The aim of most
of these investigations is to identify proteins and protein signatures for improved diagnosis, prognosis, prediction of response to treatment, as well as determination of potential drug targets. Imaging mass spectrometry has been used in the classification of papillary bladder tumors into high grade (HG) and low grade (LG).47 These types of tumors had previously been classified into three groups—G1, G2, and G3— according to histology, but in 2004 the World Health Organization eliminated the middle grade group. Although high- and low-grade tumors could be easily differentiated based on histological characteristics, the formerly classified grade G2 tumors proved more challenging. To better differentiate this group, a support vector machine algorithm was generated using IMS data obtained for 27 LG tumors and 21 HG tumors. The results of this data were applied to a set of 31 G2 tumors. In the initial training set, cross-validation accuracies of 97.82% and 96.54% were obtained for the LG and HG groups, respectively. Classification of the G2 samples designated 23 samples as LG and 8 as HG. Samples were blindly classified by two uropathologists and the results compared to the IMS classifications. Of these, 78.3% of the LG and 87.5% of the HG were correctly classified based on the IMS results. Follow-up analyses of the five misclassified LG samples showed that the tumors in three of these patients progressed to HG within 5 years. The one misclassified HG sample showed no tumor recurrence within 5 years of follow-up. Imaging mass spectrometry has also been applied to a study of gastric cancer biopsies for proteins that correlated with patient outcome.42 A cohort of 63 samples were used for a training set, 47 with good prognosis and 16 with poor prognosis. All samples were subjected to MALDI IMS and regions of interest corresponding to tumor were extracted and a subset of these spectra used for statistical analysis. Analyses were carried out
Peptides and protein digests
using ClinProTools (Bruker) and the Statistical Analysis of Microarrays plugin for Microsoft Excel. A signature of seven proteins—m/z 3445, m/z 6278, m/z 8406, m/z 8453, m/z 10,098, m/z 11,353, and m/z 11,613—was found that correlated with a nonfavorable outcome of patient survival and could not be definitively attributed to any other patient or tumor characteristics. Three of these signals—m/z 3445, m/z 8406, and m/z 10,098—were identified as human neutrophil peptide-1, cysteinerich intestinal protein-1 (CRIP1), and S100A6, respectively. These three proteins were used to validate an independent set of 118 samples using IHC. Of the three proteins, CRIP1 showed the strongest correlation with patient survival. Additionally, a support vector machine algorithm was generated using the seven proteins that resulted in 98% classification accuracy.
Peptides and protein digests Endogenous or enzymatically produced peptides can be analyzed directly from tissue sections. The latter technique has allowed for the analysis of formalin-fixed, paraffinembedded biopsies,48 opening a vast bank of tissues for IMS analysis as most clinical samples are preserved and stored in this manner. This analysis is accomplished by first subjecting tissue sections to deparaffinization using xylene and graded alcohols before applying heat-induced antigen retrieval, commonly performed in histology laboratories. Trypsin (or another proteolytic enzyme) is applied to the surface of the tissue by either spraying or spotting before application of matrix. Peptides can be analyzed from these microdigestion spots and serve as sequence tags for the parent proteins, thus allowing for analysis of higher molecular weight proteins than those that are typically accessible by traditional protein imaging.49 Additionally in many cases,
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peptides—either endogenous or enzymatically produced—can be sequenced and identified directly from tissue sections using tandem mass spectrometry (MS/MS) without further isolation or purification. We demonstrated the application of the combination of histology-directed profiling and tissue tryptic digestion in the study of Spitzoid skin lesions.50 Spitz nevi (SN) are benign skin lesions that often occur on the face or lower leg of young children, whereas Spitzoid melanomas (SM) are malignant tumors with Spitzoid features. These types of lesions can sometimes be difficult to differentiate. Differentiating them, however, is critical as the treatments for the two disease types are quite different. To provide a better molecular diagnosis, we profiled a total of 114 Spitzoid lesions. Areas of tumor and surrounding stroma (dermis) were targeted from each sample when sufficient tissue was available (Fig. 2). These samples were subdivided into 26 SN and 25 SM in a training set and 30 SN and 29 SM in an independent validation set. After analysis of tryptic peptides from the tumor in the training set, a genetic algorithm model was generated using ClinProTools, consisting of five peptides that could correctly diagnose all samples in the training set. This algorithm was applied to the independent validation set with 29 out of 30 SN and 26 out of 29 SM correctly classified. Two of the peptides that made up the signature were identified using MS/MS directly from the tissue sections. A peptide at m/z 976.5 was identified as originating from actin and one at m/z 1428.6 as being from vimentin. In addition to traditional biopsies, tissue microarrays (TMA) have been analyzed using these techniques allowing for the analysis of a hundred or more samples in a single experiment. This method was first demonstrated by Groseclose et al.51 in the analysis of a lung carcinoma TMA comprised of 112 cores from 50 different patients. The patient diagnoses could be subdivided into adenocarcinoma (n ¼ 21),
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FIG. 2 Analysis of Spitzoid lesions. (A) Spitzoid melanoma (top) and Spitz nevi (bottom) were annotated for areas of tumor (blue) and dermis (yellow) and targeted for on-tissue tryptic digestion and mass spectrometry. (B) Portion of average spectra from tumor regions from Spitzoid melanoma (red) and Spitz nevi (green). Peptides that are part of the classifier are marked with an asterisk.
squamous cell carcinoma (n ¼ 21), bronchioloalveolar carcinoma (n ¼ 4), metastatic colon cancer (n ¼ 2), carcinoid biopsy (n ¼ 1), and plasma cell granuloma (n ¼ 1), with a focus on adenocarcinoma and squamous cell carcinoma for clinical analysis. After on-tissue tryptic digestion and IMS, statistical analyses were carried out and a support vector machine algorithm made up of 73 peaks was generated that could accurately classify all of the cancerous cores into their designated subtypes. It was discovered that there was a subset of squamous cell carcinoma cores that could be differentiated from the others based on the expression of a peptide identified as originating from cytokeratin 5. Tissue microarray analysis using IMS has also been demonstrated in pancreatic,52 gastric,53 and prostate54 cancers.
Endogenous peptide level variations were shown in a rat model of Parkinson’s disease (PD).55 Parkinson’s disease was induced in rats through the unilateral injection of 6-OHDA-HCl into the substantia nigra with saline administered to control animals followed by treatment with L-DOPA to alleviate PD symptoms and induce levels of dyskinesia. Coronal sections of the ventral midbrain containing the substantia nigra were coated with 2,5-dihydroxybenzoic acid (DHB) using a chemical inkjet printer and imaged. Two peptides, dynorphin B and alpha-neoendorphin (α-Neo), were found to be significantly elevated in the lesioned substantia nigra in the animals with high dyskinesia as compared to animals with low dyskinesia and controls. In particular, these peptides showed considerably higher levels (1.75 fold higher for
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Drug analysis
dynorphin B and 2 fold higher for α-Neo) in the lateral portion of the lesioned substantia nigra as compared to the contralateral side. Additionally, the peptide metabolites Leu-Enk-Arg, Leu-Enk-Arg-Arg, and α-Neo (1–7) showed similar trends in expression of being higher in the lateral portion of the substantia nigra in the lesioned side of the brain as compared to intact but did not show a strong correlation with dyskinesia. LeuEnk-Arg showed opposite trends with dynorphin B with respect to spatial localization indicating that it is being produced by the metabolism of dynorphin B. Other peptides, such as dynorphin A (1–8), dynorphin A (1–17), and substance P, showed no treatment-induced changes.
Lipid analysis Lipids are an emerging area of interest to the IMS community as they have been associated with a variety of biological and disease processes, including signal transduction,56 kinase pathways,57 cancer,58,59 Alzheimer’s disease,60 and embryo implantation,22 as well as being highly expressed in every organ of the body, especially the brain.61 Sample preparation protocols have helped to improve ionization of lipids while decreasing ambiguity due to coordination with multiple cations. Addition of lithium to the matrix solution has been used to drive lipids to their lithiated form enhancing sensitivity while improving fragmentation efficiency.62 Washing tissue with ammonium formate prior to matrix application and mass spectral analysis enhances lipid signals particularly in negative ion mode.63 Menger et al. demonstrated the role that lipids play in myocardial infarction.64 A rat model of infarction was generated by surgically ligating the left anterior descending coronary artery. The rats were sacrificed and the hearts dissected 24 h later. Transverse sections were collected from the infarcted heart containing the damaged area. Areas of damage
were confirmed by staining with 2,3,5-triphenyltetrazolium chloride (TTC) as infarcted tissue lacks the dehydrogenase that converts TTC to formazan. Samples were coated with DHB containing alkali metals to help drive the ionization of lipids to a single species. Mass spectrometry and MS/MS imaging were carried out using a Thermo Scientific LTQ XL in positive ion mode. Infarcted areas could be clearly differentiated from normal areas based on the absence of creatine and increased presence of lysophospholipids in the damaged tissue. Lysophospholipids LPC 16:0 [M + H]+ (m/z 496), LPC 16:0 [M + Na]+ (m/z 518), LPC 18:0 [M + H]+ or unidentified LPE (m/z 524), LCP 18:1 [M + Na]+ or LPC 20:4 [M + H]+ (m/z 544) and LPC 18:0 [M + Na]+ (m/z 546) were found to be at significantly greater levels in the infarcted tissue than in the surrounding unaffected tissue. Conversely, intact phospholipids PC (18:0/20:4) [M + Na]+ (m/z 832) and PC (18:0/20:4) [M + K]+ (m/z 848) were found to be in high abundance in the normal tissue but absent from the infarcted tissue (Fig. 3). The presence of increased levels of lysophospholipids along with decreased levels of intact lipids indicated increased activity of phospholipase A2, which hydrolyzes the SN-2 acyl bond of intact phospholipids, within the infarcted tissue area. This finding is in accordance with previous reports65 that phospholipase A2 acts on lipids containing arachidonic acid to protect against ischemic cell death.
Drug analysis Imaging mass spectrometry has been employed in the pharmaceutical industry for determination of the spatial distribution and quantitation of drugs and their metabolites in tissue sections.66–68 Traditional drug
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(A)
(B)
(C)
(D)
Mass spectrometry images for the [M+ K]+ of LPE 18:0 at m/z 520 (A), the [M+Na]+ of LPC 18:0 at m/z 546 (B), the [M+Na]+ of LPC 16:0 at m/z 518 (C), and the [M+ K]+ of PC (18:0/20:4) at m/z 848 (D) from a heart following [left anterior descending] coronary artery ligation. All images were generated by plotting the ion intensity divided by the TIC. Reprinted with permission from Menger RF, Stutts WL, Anbukumar DS, Bowden JA, Ford DA, Yost RA. MALDI mass spectrometric imaging of cardiac tissue following myocardial infarction in a rat coronary artery ligation model. Anal Chem 2012;84(2):1117-25. Copyright 2012 American Chemical Society.
FIG. 3
analyses have been carried out using quantitative whole-body autoradiography that allows for the visualization of radiolabeled compounds throughout thin sections of dosed animals.69 This technology, however, shows only the location of the label and does not identify the either the parent compound or its metabolites. Alternatively, LC-MS-based approaches can easily distinguish different metabolites, but spatial localization is lost due to the homogenization of the tissue prior to analysis. Imaging mass spectrometry is ideal for this purpose because it allows the drug and its
metabolites to be distinguished while maintaining the spatial localization of these compounds. Imaging mass spectrometry of drugs and other small molecules has the added challenge in that there is redundancy of nominal masses observed in the lower-molecular-weight region of the spectrum. Often several compounds within a tissue section can have the same nominal mass as the molecule of interest and may not be resolved by lower mass resolution analyzers such as quadrupole or even time-of-flight-based analyzers. Three different approaches can be taken to circumvent
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this issue. The first is to use a much higher resolution mass analyzer such as a Fourier transform ion cyclotron resonance (FT-ICR) instrument that can easily distinguish compounds separated by fractions of a mass unit and confidently validate the identity of a compound using accurate mass.68,70 A second approach is to carry out the imaging using an MS/MS mode by following a specific transition from the parent mass to a fragment ion of the compound.17,71 A third approach is to use ion mobility MS to separate molecules of interest from other isobaric compounds based on their gas-phase conformations and capture crosssectional areas.11,72 Castellino et al. have shown the applicability of the FT-ICR approach in the imaging of several drugs and metabolites in animal tissue.68 Organs were collected from dogs dosed with lapatinib (which is used to treat breast cancer and other solid tumors) and subjected to IMS using a Bruker solariX 12T FT-ICR mass spectrometer. By using this highresolution instrument, investigators were able to distinguish two different metabolites, GW006 and M2, which differ in mass by only 0.013 amu and display different spatial distributions within the liver of the dosed dog. This work has led to the identification of a total of 21 different metabolites in dog liver sections.68 Alternatively, SRM through the application of MS/MS imaging can be used to accurately determine the spatial localization and quantitation of drug compounds in tissue sections. Goodwin et al. have employed this approach in the analysis of positron emission tomography (PET) tracers in the brains and kidneys of mice.73 Two compounds, 3,5-dichloro-N-[(2S)-1-ethylpyrrolidin-2-yl] methyl-2-hydroxy-6-methoxybenzamide (raclopride) or 7-cholor-3-methyl-1-phenyl-1,2,4,5tetrahydro-3-benzazepin-8-ol (Scheme 23390), were administered by injection at different doses through the tail veins of rats. Animals were sacrificed at 1, 5, or 30 min post dose and
the brains and kidneys dissected and snap frozen. Midpoint sections of the organs were collected and α-cyano-4-hydroxycinnamic acid matrix was deposited by dry coating, which allowed for desorption and ionization of both compounds without the delocalization that can occur with wet, solvent-based matrix application. Both compounds were imaged as intact parent masses along with MS/MS imaging. Raclopride was imaged by monitoring the transition m/z 347 to m/z 129 and m/z 111, while Scheme 23390 was imaged by monitoring the transition m/z 288 to m/z 179. Images of parent compounds collected using both qTOF and FT-ICR instruments showed excellent correlation with MS/MS images of the compounds confirming their localization and identities (Fig. 4). Raclopride was found to be at highest levels in the brain 1 min post dose with an 80% drop in concentration after 30 min as evidenced by decreased signal intensity. Similar results were obtained in the kidney. This method was also used to quantitate raclopride in the tissue sections by use of a serial dilution of the compound on control tissue section to a generated calibration curve based on signal response. Raclopride was determined to be at a concentration of 60nM 1 min post 7.5 mg/kg dose and a concentration of 15nM at 1 min post 2 mg/kg dose.
Three-dimensional imaging An exciting application of IMS is the ability to generate three-dimensional (3D) volumes of biomolecules within an organ or animal often with coregistration to other imaging modalities. This approach has been used to create 3D volumes of the corpus callosum74 and the substantia nigra within the rodent brain.75 Coregistration of IMS with magnetic resonance imaging (MRI) was shown using a xenograph model of a human glioma in a rat brain.76 Proteomic data from imaged brain sections could be correlated with data from noninvasive MRI data.
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FIG. 4 Imaging mass spectrometry abundance distributions obtained on a range of MALDI mass spectrometers for rat brain tissue sections (14 μm thick) coated with a solvent free dry matrix (CHCA). Raclopride brain tissue sections (i.v. 2.5 mg/kg) dose tissues (A) analyzed by MALDI q-TOF at a spatial resolution of 100 μm. Abundance displayed on a heat-map scale. (B) Analyzed by MALDI FT ICR at a spatial resolution of 100 μm. (C) Pseudo-SRM images produced by mapping the distribution of the MSMS fragmentation masses for raclopride m/z 347.0 to 129.1 (C.i) and 111.9 (C.ii) at a spatial resolution of 200 μm performed on a MALDI q-TOF. Scheme 23390 brain tissue sections (i.v. 5 mg/kg) (D) analyzed by MALDI q-TOF at a spatial resolution of 100 μm. Abundance displayed on a heat-map scale. (E) Analyzed by MALDI TOF at a spatial resolution of 200 μm. (F) Pseudo-SRM image produced by mapping the distribution of the MSMS fragmentation masses for Scheme 23390 m/z 289.1 to 179.0 abundance as heat-map scale (F.i) and monochrome red scale (F.ii) at a spatial resolution of 200 μm performed on a MALDI q-TOF. Reprinted with permission from Goodwin RJ, Mackay CL, Nilsson A, et al. Qualitative and quantitative MALDI imaging of the positron emission tomography ligands raclopride (a D2 dopamine antagonist) and SCH 23390 (a D1 dopamine antagonist) in rat brain tissue sections using a solvent-free dry matrix application method. Anal Chem 2011;83(24):9694–9701. Copyright 2011 American Chemical Society.
Applications of IMS involving 3D imaging require that many sections must be registered to each other to construct a molecular volume. Thus, it is necessary to minimize any physical distortion of the samples during sectioning of the tissue.70,77 It is also important that all sample preparation and data collection parameters are kept constant throughout the experiment to minimize nonbiological variability.
We have shown the coregistration of IMS and MRI in a murine model of staphylococcus infection and treatment with linezolid.77 Animals were infected retro-orbitally and the infection allowed to progress for 96 h before treatment with 0.2 mg/mL of linezolid for 96 h. The animals were splinted to prevent movement and subjected to MRI measurements of the abdomen. Large abscesses were observed in the kidneys of untreated animals45
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References
with smaller abscesses found in the treated animals. Animals were then sacrificed, snap frozen, and sectioned in a whole body cryomacrotome. Prior to each section being cut, a photograph of the blockface was taken. About 40 sections were collected per animal in the region encompassing the kidneys and subjected to protein IMS. Three-dimensional volumes were generated of proteins that localized to the abscesses and normal kidney structures and were then coregistered through the use of the optical blockface intermediary to the MRI volumes. Calgranulin A showed localization to the abscesses in the IMS volume and corresponded to the observed abscesses in the MRI volume. A second protein fragment, α-globin residues 2–47, was found to localize to the cortex of the kidney. This study clearly showed the ability of IMS to monitor the infection process and treatment through multimodality imaging using MRI and IMS.
High-speed imaging One of the major challenges when moving to higher spatial resolutions and higher data volumes required for 3D imaging is the time necessary to acquire the data. The use of high-repetition-rate lasers12 and continuous raster sample stages are highly beneficial in achieving high-speed imaging. This benefit has been shown in images acquired using the instrument from SimulTOF (Virgin Instruments, Inc.).78 This mass spectrometer couples a 5-kHz laser repetition rate with continuous raster. Pixel dimensions are determined by the number of shots per pixel, the stage speed, and the repetition rate of the laser. By operating the laser at 3 kHz, a stage speed of 5 mm/s, and acquiring 60 shots per pixel, an image of a sagittal rat brain section (185 mm2) consisting of approximately 19,000 pixels can be acquired in under 10 min. Such technological advances are imperative as IMS moves to
higher numbers of samples and higher spatial resolution.
Conclusions and perspectives Imaging mass spectrometry has shown wide applicability in the study of biological systems allowing for the in situ analysis of many classes of biomolecules, including proteins, peptides, lipids, and drugs/metabolites. The ability to identify these biomolecules both spatially and quantitatively provides valuable insight into their involvement in biological and disease processes. Although relative quantitation has been clearly demonstrated, processes necessary to achieve absolute quantitation are just beginning. Imaging mass spectrometry has provided insights into better diagnostics, outcomes, and treatment response, especially in areas where traditional histology has not been effective. As the technology and sample preparation methods advance, IMS is becoming easier to use in a wide variety of applications in the biological and medical fields. The molecular specificity of this imaging technology brings a very powerful and enabling tool to these disciplines.
Acknowledgments The authors acknowledge funding from NIH/NIGMS 8P41 GM103391-02 (formerly NIH/NCRR 8P41 RR031461-02), NIH/NIGMS 5R01 GM058008-13, and the DOD grant W81XWH-05-1-0179.
References 1. Caprioli RM, Farmer TB, Gile J. Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS. Anal Chem 1997;69(23):4751–60. 2. Seeley EH, Schwamborn K, Caprioli RM. Imaging of intact tissue sections: moving beyond the microscope. J Biol Chem 2011;286(29):25459–66. 3. McDonnell LA, Heeren RMA. Imaging mass spectrometry. Mass Spectrom Rev 2007;26(4):606–43.
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4. Fletcher JS, Vickerman JC, Winograd N. Label free biochemical 2D and 3D imaging using secondary ion mass spectrometry. Curr Opin Chem Biol 2011;15(5):733–40. 5. Lorey II DR, Morrison GH, Chandra S. Dynamic secondary ion mass spectrometry analysis of boron from boron neutron capture therapy drugs in co-cultures: single-cell imaging of two different cell types within the same ion microscopy field of imaging. Anal Chem 2001;73(16):3947–53. 6. Yokoyama K, Miyatake S-I, Kajimoto Y, et al. Analysis of boron distribution in vivo for boron neutron capture therapy using two different boron compounds by secondary ion mass spectrometry. Radiat Res 2007;167(1):102–9. 7. Takats Z, Wiseman JM, Gologan B, Cooks RG. Mass spectrometry sampling under ambient conditions with desorption electrospray ionization. Science 2004;306(5695):471–3. 8. Wiseman JM, Puolitaival SM, Takats Z, Cooks RG, Caprioli RM. Mass spectrometric profiling of intact biological tissue by using desorption electrospray ionization. Angew Chem Int Ed Engl 2005;44(43):7094–7. 9. Baluya DL, Garrett TJ, Yost RA. Automated MALDI matrix deposition method with inkjet printing for imaging mass spectrometry. Anal Chem 2007;79(17):6862–7. 10. Cazares LH, Troyer D, Mendrinos S, et al. Imaging mass spectrometry of a specific fragment of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase kinase 2 discriminates cancer from uninvolved prostate tissue. Clin Cancer Res 2009;15(17):5541–51. 11. Harris GA, Graf S, Knochenmuss R, Fernandez FM. Coupling laser ablation/desorption electrospray ionization to atmospheric pressure drift tube ion mobility spectrometry for the screening of antimalarial drug quality. Analyst (Lond) 2012;137(13):3039–44. 12. Trim PJ, Djidja MC, Atkinson SJ, et al. Introduction of a 20 kHz Nd:YVO4 laser into a hybrid quadrupole time-offlight mass spectrometer for MALDI-MS imaging. Anal Bioanal Chem 2010;397(8):3409–19. 13. Harris GA, Falcone CE, Fernandez FM. Sensitivity “hot spots” in the direct analysis in real time mass spectrometry of nerve agent simulants. J Am Soc Mass Spectrom 2012;23(1):153–61. 14. Dill AL, Eberlin LS, Ifa DR, Cooks RG. Perspectives in imaging using mass spectrometry. Chem Commun (Camb) 2011;47(10):2741–6. 15. Greer T, Sturm R, Li L. Mass spectrometry imaging for drugs and metabolites. J Proteomics 2011;74(12):2617–31. 16. Amann JM, Chaurand P, Gonzalez A, et al. Selective profiling of proteins in lung cancer cells from fine-needle aspirates by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Clin Cancer Res 2006;12(17):5142–50. 17. Khatib-Shahidi S, Andersson M, Herman JL, Gillespie TA, Caprioli RM. Direct molecular analysis of
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
whole-body animal tissue sections by imaging MALDI mass spectrometry. Anal Chem 2006;78(18):6448–56. Zavalin A, Yang J, Caprioli RM. Tissue imaging at submicron spatial resolution using direct transmission geometry MALDI MS, In: 60th ASMS conference on mass spectrometry and allied topics, Vancouver, BC; 2012. Aerni HR, Cornett DS, Caprioli RM. Automated acoustic matrix deposition for MALDI sample preparation. Anal Chem 2006;78(3):827–34. Chaurand P, Fouchecourt S, DaGue BB, et al. Profiling and imaging proteins in the mouse epididymis by imaging mass spectrometry. Proteomics 2003; 3(11):2221–39. Hankin JA, Barkley RM, Murphy RC. Sublimation as a method of matrix application for mass spectrometric imaging. J Am Soc Mass Spectrom 2007;18(9):1646–52. Burnum KE, Cornett DS, Puolitaival SM, et al. Spatial and temporal alterations of phospholipids determined by mass spectrometry during mouse embryo implantation. J Lipid Res 2009;50(11):2290–8. Schwartz SA, Reyzer ML, Caprioli RM. Direct tissue analysis using matrix-assisted laser desorption/ionization mass spectrometry: practical aspects of sample preparation. J Mass Spectrom 2003;38(7):699–708. Yang J, Caprioli RM. Matrix sublimation/recrystallization for imaging proteins by mass spectrometry at high spatial resolution. Anal Chem 2011;83(14):5728–34. Cornett DS, Mobley JA, Dias EC, et al. A novel histologydirected strategy for MALDI-MS tissue profiling that improves throughput and cellular specificity in human breast cancer. Mol Cell Proteomics 2006;5(10):1975–83. Bauer JA, Chakravarthy AB, Rosenbluth JM, et al. Identification of markers of taxane sensitivity using proteomic and genomic analyses of breast tumors from patients receiving neoadjuvant paclitaxel and radiation. Clin Cancer Res 2010;16(2):681–90. Reyzer ML, Caldwell RL, Dugger TC, et al. Early changes in protein expression detected by mass spectrometry predict tumor response to molecular therapeutics. Cancer Res 2004;64(24):9093–100. Rauser S, Marquardt C, Balluff B, et al. Classification of HER2 receptor status in breast cancer tissues by MALDI imaging mass spectrometry. J Proteome Res 2010;9(4):1854–63. Xu BJ, Caprioli RM, Sanders ME, Jensen RA. Direct analysis of laser capture microdissected cells by MALDI mass spectrometry. J Am Soc Mass Spectrom 2002;13(11):1292–7. Drake RR, Cazares LH, Jones EE, Fuller TW, Semmes OJ, Laronga C. Challenges to developing proteomic-based breast cancer diagnostics. OMICS 2011;15(5):251–9. Schwamborn K, Krieg RC, Reska M, Jakse G, Knuechel R, Wellmann A. Identifying prostate carcinoma by MALDIimaging. Int J Mol Med 2007;20(2):155–9.
References
32. Cazares LH, Troyer D, Mendrinos S, et al. Imaging mass spectrometry of a specific fragment of mitogenactivated protein kinase/extracellular signal-regulated kinase kinase kinase 2 discriminates cancer from uninvolved prostate tissue. Clin Cancer Res 2009;15 (17):5541–51. 33. Oppenheimer SR, Mi D, Sanders ME, Caprioli RM. Molecular analysis of tumor margins by MALDI mass spectrometry in renal carcinoma. J Proteome Res 2010; 9(5):2182–90. 34. Hardesty WM, Kelley MC, Mi D, Low RL, Caprioli RM. Protein signatures for survival and recurrence in metastatic melanoma. J Proteomics 2011;74(7):1002–14. 35. Chaurand P, DaGue BB, Pearsall RS, Threadgill DW, Caprioli RM. Profiling proteins from azoxymethaneinduced colon tumors at the molecular level by matrixassisted laser desorption/ionization mass spectrometry. Proteomics 2001;1(10):1320–6. 36. Rahman SM, Gonzalez AL, Li M, et al. Lung cancer diagnosis from proteomic analysis of preinvasive lesions. Cancer Res 2011;71(8):3009–17. 37. Rahman SM, Shyr Y, Yildiz PB, et al. Proteomic patterns of preinvasive bronchial lesions. Am J Respir Crit Care Med 2005;172(12):1556–62. 38. Taguchi F, Solomon B, Gregorc V, et al. Mass spectrometry to classify non-small-cell lung cancer patients for clinical outcome after treatment with epidermal growth factor receptor tyrosine kinase inhibitors: a multicohort cross-institutional study. J Natl Cancer Inst 2007;99(11):838–46. 39. Yanagisawa K, Shyr Y, Xu BJ, et al. Proteomic patterns of tumour subsets in non-small-cell lung cancer. Lancet 2003;362(9382):433–9. 40. Yanagisawa K, Xu BJ, Carbone DP, Caprioli RM. Molecular fingerprinting in human lung cancer. Clin Lung Cancer 2003;5(2):113–8. 41. Gustafsson JO, Oehler MK, Ruszkiewicz A, McColl SR, Hoffmann P. MALDI imaging mass spectrometry (MALDI-IMS)-application of spatial proteomics for ovarian cancer classification and diagnosis. Int J Mol Sci 2011;12(1):773–94. 42. Balluff B, Rauser S, Meding S, et al. MALDI imaging identifies prognostic seven-protein signature of novel tissue markers in intestinal-type gastric cancer. Am J Pathol 2011;179(6):2720–9. 43. Kim HK, Reyzer ML, Choi IJ, et al. Gastric cancer-specific protein profile identified using endoscopic biopsy samples via MALDI mass spectrometry. J Proteome Res 2010;9(8):4123–30. 44. M’Koma AE, Seeley EH, Washington MK, et al. Proteomic profiling of mucosal and submucosal colonic tissues yields protein signatures that differentiate the inflammatory colitides. Inflamm Bowel Dis 2011;17(4): 875–83.
351
45. Corbin BD, Seeley EH, Raab A, et al. Metal chelation and inhibition of bacterial growth in tissue abscesses. Science 2008;319(5865):962–5. 46. Oswald-Richter KA, Beachboard DC, Seeley EH, et al. Dual analysis for mycobacteria and propionibacteria in sarcoidosis BAL. J Clin Immunol 2012;. 47. Oezdemir RF, Gaisa NT, Lindemann-Docter K, et al. Proteomic tissue profiling for the improvement of grading of noninvasive papillary urothelial neoplasia. Clin Biochem 2012;45(1–2):7–11. 48. Lemaire R, Desmons A, Tabet JC, Day R, Salzet M, Fournier I. Direct analysis and MALDI imaging of formalin-fixed, paraffin-embedded tissue sections. J Proteome Res 2007;6(4):1295–305. 49. Casadonte R, Caprioli RM. Proteomic analysis of formalin-fixed paraffin-embedded tissue by MALDI imaging mass spectrometry. Nat Protoc 2011; 6(11):1695–709. 50. Lazova R, Seeley EH, Keenan M, Gueorguieva R, Caprioli RM. Imaging mass spectrometry – a new and promising method to differentiate Spitz nevi from Spitzoid malignant melanomas. Am J Dermatopathol 2012; 34(1):82–90. 51. Groseclose MR, Massion PP, Chaurand P, Caprioli RM. High-throughput proteomic analysis of formalin-fixed paraffin-embedded tissue microarrays using MALDI imaging mass spectrometry. Proteomics 2008; 8(18):3715–24. 52. Djidja MC, Claude E, Snel MF, et al. Novel molecular tumour classification using MALDI-mass spectrometry imaging of tissue micro-array. Anal Bioanal Chem 2010;397(2):587–601. 53. Morita Y, Ikegami K, Goto-Inoue N, et al. Imaging mass spectrometry of gastric carcinoma in formalin-fixed paraffin-embedded tissue microarray. Cancer Sci 2010;101(1):267–73. 54. Schwamborn K, Wild P, Caprioli RM. Uncovering the proteome of late state prostate cancer by imaging mass spectrometry, In: 58th ASMS conference on mass spectrometry and allied topics, Salt Lake City, UT; 2010. 55. Hanrieder J, Ljungdahl A, Andersson M. MALDI imaging mass spectrometry of neuropeptides in Parkinson’s disease. J Vis Exp 2012;(60):3445. 56. Berridge MJ, Irvine RF. Inositol trisphosphate, a novel second messenger in cellular signal transduction. Nature 1984;312(5992):315–21. 57. Khan WA, Blobe GC, Hannun YA. Arachidonic acid and free fatty acids as second messengers and the role of protein kinase C. Cell Signal 1995;7(3):171–84. 58. Liu Y, Chen Y, Momin A, et al. Elevation of sulfatides in ovarian cancer: an integrated transcriptomic and lipidomic analysis including tissue-imaging mass spectrometry. Mol Cancer 2010;9:186–99. 59. Katz-Brull R, Seger D, Rivenson-Segal D, Rushkin E, Degani H. Metabolic markers of breast cancer: enhanced
352
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
19. Imaging mass spectrometry of intact biomolecules in tissue sections
choline metabolism and reduced choline-etherphospholipid synthesis. Cancer Res 2002;62(7):1966–70. Han X, Cheng H, Fryer JD, Fagan AM, Holtzman DM. Novel role for apolipoprotein E in the central nervous system. Modulation of sulfatide content. J Biol Chem 2003;278(10):8043–51. Woods AS, Jackson SN. Brain tissue lipidomics: direct probing using matrix-assisted laser desorption/ionization mass spectrometry. AAPS J 2006;8(2):E391–5. Jackson SN, Wang HY, Woods AS. In situ structural characterization of phosphatidylcholines in brain tissue using MALDI-MS/MS. J Am Soc Mass Spectrom 2005; 16(12):2052–6. Angel PM, Spraggins JM, Baldwin HS, Caprioli R. Enhanced sensitivity for high spatial resolution lipid analysis by negative ion mode matrix assisted laser desorption ionization imaging mass spectrometry. Anal Chem 2012;84(3):1557–64. Menger RF, Stutts WL, Anbukumar DS, Bowden JA, Ford DA, Yost RA. MALDI mass spectrometric imaging of cardiac tissue following myocardial infarction in a rat coronary artery ligation model. Anal Chem 2012; 84(2):1117–25. Starkopf J, Andreasen TV, Bugge E, Ytrehus K. Lipid peroxidation, arachidonic acid and products of the lipoxygenase pathway in ischaemic preconditioning of rat heart. Cardiovasc Res 1998;37(1):66–75. Reyzer ML, Caprioli RM. MALDI-MS-based imaging of small molecules and proteins in tissues. Curr Opin Chem Biol 2007;11(1):29–35. Stoeckli M, Staab D, Schweitzer A. Compound and metabolite distribution measured by MALDI mass spectrometric imaging in whole-body tissue sections. Int J Mass Spectrom 2007;260(2–3):195–202. Castellino S, Groseclose MR, Wagner D. MALDI imaging mass spectrometry: bridging biology and chemistry in drug development. Bioanalysis 2011;3(21):2427–41. Takai N, Tanaka Y, Inazawa K, Saji H. Quantitative analysis of pharmaceutical drug distribution in multiple organs by imaging mass spectrometry. Rapid Commun Mass Spectrom 2012;26(13):1549–56.
70. Goodwin RJ, Nilsson A, Borg D, et al. Conductive carbon tape used for support and mounting of both whole animal and fragile heat-treated tissue sections for MALDI MS imaging and quantitation. J Proteomics 2012; 75:4912–20. 71. Chacon A, Zagol-Ikapitte I, Amarnath V, et al. On-tissue chemical derivatization of 3-methoxysalicylamine for MALDI-imaging mass spectrometry. J Mass Spectrom 2011;46(8):840–6. 72. Trim PJ, Henson CM, Avery JL, et al. Matrix-assisted laser desorption/ionization-ion mobility separationmass spectrometry imaging of vinblastine in whole body tissue sections. Anal Chem 2008;80(22):8628–34. 73. Goodwin RJ, Mackay CL, Nilsson A, et al. Qualitative and quantitative MALDI imaging of the positron emission tomography ligands raclopride (a D2 dopamine antagonist) and SCH 23390 (a D1 dopamine antagonist) in rat brain tissue sections using a solvent-free dry matrix application method. Anal Chem 2011; 83(24):9694–701. 74. Crecelius AC, Cornett DS, Caprioli RM, Williams B, Dawant BM, Bodenheimer B. Three-dimensional visualization of protein expression in mouse brain structures using imaging mass spectrometry. J Am Soc Mass Spectrom 2005;16(7):1093–9. 75. Andersson M, Groseclose MR, Deutch AY, Caprioli RM. Imaging mass spectrometry of proteins and peptides: 3D volume reconstruction. Nature Met 2008;5(1):101–8. 76. Sinha TK, Khatib-Shahidi S, Yankeelov TE, et al. Integrating spatially resolved three-dimensional MALDI IMS with in vivo magnetic resonance imaging. Nature Met 2008;5(1):57–9. 77. Attia AS, Schroeder KA, Seeley EH, et al. Monitoring the inflammatory response to infection through the integration of MALDI IMS and MRI. Cell Host Microbe 2012; 11(6):664–73. 78. Spraggins JM, Caprioli RM. High-speed MALDITOF imaging mass spectrometry: rapid ion image acquisition and considerations for next generation instrumentation. J Am Soc Mass Spectrom 2011; 22(6):1022–31.
19 Imaging mass spectrometry of intact biomolecules in tissue sections Erin H. Seeley, Richard M. Caprioli Mass Spectrometry Research Center, Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN, United States
O U T L I N E Introduction
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Three-dimensional imaging
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High-speed imaging
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Conclusions and perspectives
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Peptides and protein digests
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Acknowledgments
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Lipid analysis
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References
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Introduction Imaging mass spectrometry (IMS) technology enables the in situ analysis of biomolecules and pharmaceutical compounds directly from thin tissue sections.1–3 Thin sections (typically 5–20 μm) are taken from a block of tissue and collected onto a target in a fashion similar to histological analysis. After collection, sections are processed by one of several methods depending on the class of molecules to be analyzed. These steps may include dehydration,
Proteomic and Metabolomic Approaches to Biomarker Discovery https://doi.org/10.1016/B978-0-12-818607-7.00019-0
washing with organic solvents or buffers, and matrix application. Mass spectral data are generated using an ionization probe passed over the tissue surface in a raster pattern, where each ablated spot or pixel gives rise to an individual mass spectrum. Traditional proteomic techniques for the analysis of molecules from tissue specimens, such as liquid chromatography-mass spectrometry (LC-MS) or two-dimensional (2D) gel analysis, require the tissue be homogenized prior to analysis, eliminating the spatial localization of
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analytes. Immunohistochemistry (IHC) allows for the localization of specific molecules within a tissue section but requires that the specific analyte of interest be known in advance and an antibody-based reagent against it must exist. Additionally, only a few molecules can be probed from a single tissue section. Conversely, IMS is carried out without the need for homogenization, allowing for the analysis of hundreds to thousands of biomolecules in their native locations within a single tissue specimen. This technology is excellent for discovery because no target-specific reagents such as antibodies are required. Several surface ionization techniques can be used to generate data for IMS applications. One of the earliest approaches was secondary ion mass spectrometry (SIMS), in which a surface is bombarded with a primary ion beam, leading to desorption of molecules and generation of secondary ions.4–6 Although the SIMS approach allows for very high spatial resolution imaging (<1 μm), the high-energy primary ion beam is destructive to the surface biomolecules generated, effectively limiting the practical mass range of analysis to <1000 Da. Desorption electrospray ionization (DESI) uses a capillary spray of solvent onto the surface of the tissue to desorb ions from a tissue surface that are introduced into a mass spectrometer through a second inlet capillary.7–9 Advantages of the DESI technique are that it can be performed at ambient pressure and requires minimal sample preparation. However, it is most effective in analyzing small molecules such as drugs and lipids and spatial resolution is typically greater than 100 μm. Liquid extraction surface analysis (LESA) uses a small volume of solvent applied to an area of interest on a tissue section using a pipet, which is then drawn back up into the tip.10 The extracted molecules are analyzed using rapid LC-MS, often employing selected reaction monitoring (SRM). The LESA technique is limited by low spatial resolution; targeted areas are often on the order of 1 to 2 mm but could be applicable
to any type of molecule that can be extracted from the tissue surface. Other lesser-used approaches include laser ablation electrospray ionization,11 matrix-assisted laser desorption electrospray ionization,12 and jet desorption electrospray ionization.13 These latter techniques will not be discussed in detail in this chapter and the reader is referred to reviews that describe these methods in detail.14,15 In the present chapter, we focus on the use and application of matrix-assisted laser desorption/ionization (MALDI) IMS as the most broadly applicable approach for the analysis of a wide variety of biomolecules. MALDI IMS has been used for the analysis of proteins, peptides, lipids, drugs, and metabolites from tissue specimens ranging in size from cell clusters16 to whole animal sections.17 In the MALDI approach, a matrix (typically a small organic molecule) is applied to the surface of a tissue section in a solvent that aids in the extraction of analytes. The specific matrix and solvent used can be optimized for different classes of molecules.15 A raster of the tissue surface using a laser induces the desorption and ionization of molecules from the tissue surface (Fig. 1). Commercial instruments allow for achievable spatial resolutions of approximately 20 μm, and custom modifications through use of specialized optics have allowed for spatial resolutions of approximately 1 μm.18 As usual, the tradeoff between spatial resolution and sensitivity ultimately determines the actual resolution employed in a given experiment.
Matrix application A variety of techniques can be used to apply matrix to the tissue surface and the method of choice depends on the imaging task that is to be done. Wet extraction methods such as spotting19 and spraying20 result in a higher degree of analyte extraction, especially for larger polar molecules such as proteins, but may cause large
Matrix application
FIG. 1 Workflow for MALDI IMS. Sections are taken from a tissue specimen and collected onto a target plate or a microscope slide for histological staining. Matrix is applied via spray coating, sublimation, or robotic spotting. Spectra are collected in an ordered array from the surface of the tissue section. Ion images can be generated from any of the signals in the mass spectra.
crystals to form, somewhat limiting the attainable spatial resolution. Drier matrix application methods such as sublimation21,22 are less efficient at extracting larger biomolecules but result in much smaller matrix crystals on the sample surface, allowing higher spatial resolution to be achieved. The simplest and most inexpensive approach is the use of an airbrush sprayer to manually apply matrix.23 This approach has been used successfully for imaging applications but leads
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to the production of moderately large crystals (20–100 μm) and suffers from a lower degree of reproducibility between different spray devices and individuals. Automated spray devices such as the TM Sprayer from HTX Technologies and the ImagePrep from Bruker Daltonics allow more homogeneous and reproducible coatings to be achieved. Spray coatings can be used for imaging any class of molecules at relatively high spatial resolution; however, care must be taken with any spraying technique to ensure that the surface is not made too wet, which can lead to delocalization of analytes. Very high spatial resolution can be achieved using sublimation to deposit matrix onto the tissue section. Powdered matrix is heated under vacuum and is redeposited onto a cooler sample target that is suspended above the matrix. Crystals formed are typically <1 μm and the coating is very homogeneous. When conditions such as temperature, pressure, and time are carefully controlled, sublimated coatings are highly reproducible and applicable for the analysis of most classes of lipids, as no solvent is needed for extraction. If larger molecules such as peptides and proteins are to be analyzed, the use of a rehydration/recrystallization step is employed to help cocrystallize these molecules with the matrix.24 Matrix and other reagents can also be applied to the tissue through the use of robotics such as acoustic spotters (Labcyte Portrait)19 and chemical inkjet printers.9 Although these spotters cannot achieve the spatial resolution of the uniform coating technologies described previously (i.e., they are typically limited to 150–200 μm spot size), they tend to have the highest reproducibility due to the tight control of the exact volume of reagent applied to a specific location on a surface. Spotting generally leads to the most robust analyte signal due to the ability to thoroughly wet small areas of a tissue section for increased extraction without the risk of delocalization that occurs with spray or rehydration techniques.
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Because of the small reservoir volume (hundreds of microliters) of commercial spotters, they may also be employed for the application of relatively costly reagents to the tissue section, including enzymes for proteolytic digestion and internal standards for drug analysis and quantitation. An additional benefit of robotic spotters is the ability to deposit matrix or other reagents at very specific locations within a tissue section, allowing for an approach known as histology directed profiling.25 In this type of experiment, two sections of a tissue specimen are collected, one on a MALDI target and a second serial section on a standard microscope slide for histological staining. After a photomicrograph of the stained section is taken, the image is annotated by a pathologist or biologist to indicate areas of interest. The annotated image is then merged with an image of the unstained serial section using photo processing software and the coordinates of the annotations are determined. These coordinates are transferred to the robotic spotter and matrix is applied only to those specific locations. Typically 10 to 20 areas are targeted per cell type per tissue, with 10 or more samples analyzed in a single experiment. This directed analysis greatly reduces the volume of data collected, increases the throughput, and enables more facile statistical analysis. Histology directed profiling can be thought of as a type of low-resolution imaging through correlation with a microscopy image. In this way, the spatial localization of analytes is preserved while generating highquality data.
Protein analysis Imaging mass spectrometry has been used for the analysis of proteins in cancer tissue, prostate,10,31,32 including breast,26–30 33 34 35 36–40 kidney, skin, colon, lung, ovarian,41 42,43 and gastric as well as other diseases such as inflammatory bowel diseases,44 S. aureus infection,45 and sarcoidosis.46 The aim of most
of these investigations is to identify proteins and protein signatures for improved diagnosis, prognosis, prediction of response to treatment, as well as determination of potential drug targets. Imaging mass spectrometry has been used in the classification of papillary bladder tumors into high grade (HG) and low grade (LG).47 These types of tumors had previously been classified into three groups—G1, G2, and G3— according to histology, but in 2004 the World Health Organization eliminated the middle grade group. Although high- and low-grade tumors could be easily differentiated based on histological characteristics, the formerly classified grade G2 tumors proved more challenging. To better differentiate this group, a support vector machine algorithm was generated using IMS data obtained for 27 LG tumors and 21 HG tumors. The results of this data were applied to a set of 31 G2 tumors. In the initial training set, cross-validation accuracies of 97.82% and 96.54% were obtained for the LG and HG groups, respectively. Classification of the G2 samples designated 23 samples as LG and 8 as HG. Samples were blindly classified by two uropathologists and the results compared to the IMS classifications. Of these, 78.3% of the LG and 87.5% of the HG were correctly classified based on the IMS results. Follow-up analyses of the five misclassified LG samples showed that the tumors in three of these patients progressed to HG within 5 years. The one misclassified HG sample showed no tumor recurrence within 5 years of follow-up. Imaging mass spectrometry has also been applied to a study of gastric cancer biopsies for proteins that correlated with patient outcome.42 A cohort of 63 samples were used for a training set, 47 with good prognosis and 16 with poor prognosis. All samples were subjected to MALDI IMS and regions of interest corresponding to tumor were extracted and a subset of these spectra used for statistical analysis. Analyses were carried out
Peptides and protein digests
using ClinProTools (Bruker) and the Statistical Analysis of Microarrays plugin for Microsoft Excel. A signature of seven proteins—m/z 3445, m/z 6278, m/z 8406, m/z 8453, m/z 10,098, m/z 11,353, and m/z 11,613—was found that correlated with a nonfavorable outcome of patient survival and could not be definitively attributed to any other patient or tumor characteristics. Three of these signals—m/z 3445, m/z 8406, and m/z 10,098—were identified as human neutrophil peptide-1, cysteinerich intestinal protein-1 (CRIP1), and S100A6, respectively. These three proteins were used to validate an independent set of 118 samples using IHC. Of the three proteins, CRIP1 showed the strongest correlation with patient survival. Additionally, a support vector machine algorithm was generated using the seven proteins that resulted in 98% classification accuracy.
Peptides and protein digests Endogenous or enzymatically produced peptides can be analyzed directly from tissue sections. The latter technique has allowed for the analysis of formalin-fixed, paraffinembedded biopsies,48 opening a vast bank of tissues for IMS analysis as most clinical samples are preserved and stored in this manner. This analysis is accomplished by first subjecting tissue sections to deparaffinization using xylene and graded alcohols before applying heat-induced antigen retrieval, commonly performed in histology laboratories. Trypsin (or another proteolytic enzyme) is applied to the surface of the tissue by either spraying or spotting before application of matrix. Peptides can be analyzed from these microdigestion spots and serve as sequence tags for the parent proteins, thus allowing for analysis of higher molecular weight proteins than those that are typically accessible by traditional protein imaging.49 Additionally in many cases,
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peptides—either endogenous or enzymatically produced—can be sequenced and identified directly from tissue sections using tandem mass spectrometry (MS/MS) without further isolation or purification. We demonstrated the application of the combination of histology-directed profiling and tissue tryptic digestion in the study of Spitzoid skin lesions.50 Spitz nevi (SN) are benign skin lesions that often occur on the face or lower leg of young children, whereas Spitzoid melanomas (SM) are malignant tumors with Spitzoid features. These types of lesions can sometimes be difficult to differentiate. Differentiating them, however, is critical as the treatments for the two disease types are quite different. To provide a better molecular diagnosis, we profiled a total of 114 Spitzoid lesions. Areas of tumor and surrounding stroma (dermis) were targeted from each sample when sufficient tissue was available (Fig. 2). These samples were subdivided into 26 SN and 25 SM in a training set and 30 SN and 29 SM in an independent validation set. After analysis of tryptic peptides from the tumor in the training set, a genetic algorithm model was generated using ClinProTools, consisting of five peptides that could correctly diagnose all samples in the training set. This algorithm was applied to the independent validation set with 29 out of 30 SN and 26 out of 29 SM correctly classified. Two of the peptides that made up the signature were identified using MS/MS directly from the tissue sections. A peptide at m/z 976.5 was identified as originating from actin and one at m/z 1428.6 as being from vimentin. In addition to traditional biopsies, tissue microarrays (TMA) have been analyzed using these techniques allowing for the analysis of a hundred or more samples in a single experiment. This method was first demonstrated by Groseclose et al.51 in the analysis of a lung carcinoma TMA comprised of 112 cores from 50 different patients. The patient diagnoses could be subdivided into adenocarcinoma (n ¼ 21),
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FIG. 2 Analysis of Spitzoid lesions. (A) Spitzoid melanoma (top) and Spitz nevi (bottom) were annotated for areas of tumor (blue) and dermis (yellow) and targeted for on-tissue tryptic digestion and mass spectrometry. (B) Portion of average spectra from tumor regions from Spitzoid melanoma (red) and Spitz nevi (green). Peptides that are part of the classifier are marked with an asterisk.
squamous cell carcinoma (n ¼ 21), bronchioloalveolar carcinoma (n ¼ 4), metastatic colon cancer (n ¼ 2), carcinoid biopsy (n ¼ 1), and plasma cell granuloma (n ¼ 1), with a focus on adenocarcinoma and squamous cell carcinoma for clinical analysis. After on-tissue tryptic digestion and IMS, statistical analyses were carried out and a support vector machine algorithm made up of 73 peaks was generated that could accurately classify all of the cancerous cores into their designated subtypes. It was discovered that there was a subset of squamous cell carcinoma cores that could be differentiated from the others based on the expression of a peptide identified as originating from cytokeratin 5. Tissue microarray analysis using IMS has also been demonstrated in pancreatic,52 gastric,53 and prostate54 cancers.
Endogenous peptide level variations were shown in a rat model of Parkinson’s disease (PD).55 Parkinson’s disease was induced in rats through the unilateral injection of 6-OHDA-HCl into the substantia nigra with saline administered to control animals followed by treatment with L-DOPA to alleviate PD symptoms and induce levels of dyskinesia. Coronal sections of the ventral midbrain containing the substantia nigra were coated with 2,5-dihydroxybenzoic acid (DHB) using a chemical inkjet printer and imaged. Two peptides, dynorphin B and alpha-neoendorphin (α-Neo), were found to be significantly elevated in the lesioned substantia nigra in the animals with high dyskinesia as compared to animals with low dyskinesia and controls. In particular, these peptides showed considerably higher levels (1.75 fold higher for
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Drug analysis
dynorphin B and 2 fold higher for α-Neo) in the lateral portion of the lesioned substantia nigra as compared to the contralateral side. Additionally, the peptide metabolites Leu-Enk-Arg, Leu-Enk-Arg-Arg, and α-Neo (1–7) showed similar trends in expression of being higher in the lateral portion of the substantia nigra in the lesioned side of the brain as compared to intact but did not show a strong correlation with dyskinesia. LeuEnk-Arg showed opposite trends with dynorphin B with respect to spatial localization indicating that it is being produced by the metabolism of dynorphin B. Other peptides, such as dynorphin A (1–8), dynorphin A (1–17), and substance P, showed no treatment-induced changes.
Lipid analysis Lipids are an emerging area of interest to the IMS community as they have been associated with a variety of biological and disease processes, including signal transduction,56 kinase pathways,57 cancer,58,59 Alzheimer’s disease,60 and embryo implantation,22 as well as being highly expressed in every organ of the body, especially the brain.61 Sample preparation protocols have helped to improve ionization of lipids while decreasing ambiguity due to coordination with multiple cations. Addition of lithium to the matrix solution has been used to drive lipids to their lithiated form enhancing sensitivity while improving fragmentation efficiency.62 Washing tissue with ammonium formate prior to matrix application and mass spectral analysis enhances lipid signals particularly in negative ion mode.63 Menger et al. demonstrated the role that lipids play in myocardial infarction.64 A rat model of infarction was generated by surgically ligating the left anterior descending coronary artery. The rats were sacrificed and the hearts dissected 24 h later. Transverse sections were collected from the infarcted heart containing the damaged area. Areas of damage
were confirmed by staining with 2,3,5-triphenyltetrazolium chloride (TTC) as infarcted tissue lacks the dehydrogenase that converts TTC to formazan. Samples were coated with DHB containing alkali metals to help drive the ionization of lipids to a single species. Mass spectrometry and MS/MS imaging were carried out using a Thermo Scientific LTQ XL in positive ion mode. Infarcted areas could be clearly differentiated from normal areas based on the absence of creatine and increased presence of lysophospholipids in the damaged tissue. Lysophospholipids LPC 16:0 [M + H]+ (m/z 496), LPC 16:0 [M + Na]+ (m/z 518), LPC 18:0 [M + H]+ or unidentified LPE (m/z 524), LCP 18:1 [M + Na]+ or LPC 20:4 [M + H]+ (m/z 544) and LPC 18:0 [M + Na]+ (m/z 546) were found to be at significantly greater levels in the infarcted tissue than in the surrounding unaffected tissue. Conversely, intact phospholipids PC (18:0/20:4) [M + Na]+ (m/z 832) and PC (18:0/20:4) [M + K]+ (m/z 848) were found to be in high abundance in the normal tissue but absent from the infarcted tissue (Fig. 3). The presence of increased levels of lysophospholipids along with decreased levels of intact lipids indicated increased activity of phospholipase A2, which hydrolyzes the SN-2 acyl bond of intact phospholipids, within the infarcted tissue area. This finding is in accordance with previous reports65 that phospholipase A2 acts on lipids containing arachidonic acid to protect against ischemic cell death.
Drug analysis Imaging mass spectrometry has been employed in the pharmaceutical industry for determination of the spatial distribution and quantitation of drugs and their metabolites in tissue sections.66–68 Traditional drug
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(A)
(B)
(C)
(D)
Mass spectrometry images for the [M+ K]+ of LPE 18:0 at m/z 520 (A), the [M+Na]+ of LPC 18:0 at m/z 546 (B), the [M+Na]+ of LPC 16:0 at m/z 518 (C), and the [M+ K]+ of PC (18:0/20:4) at m/z 848 (D) from a heart following [left anterior descending] coronary artery ligation. All images were generated by plotting the ion intensity divided by the TIC. Reprinted with permission from Menger RF, Stutts WL, Anbukumar DS, Bowden JA, Ford DA, Yost RA. MALDI mass spectrometric imaging of cardiac tissue following myocardial infarction in a rat coronary artery ligation model. Anal Chem 2012;84(2):1117-25. Copyright 2012 American Chemical Society.
FIG. 3
analyses have been carried out using quantitative whole-body autoradiography that allows for the visualization of radiolabeled compounds throughout thin sections of dosed animals.69 This technology, however, shows only the location of the label and does not identify the either the parent compound or its metabolites. Alternatively, LC-MS-based approaches can easily distinguish different metabolites, but spatial localization is lost due to the homogenization of the tissue prior to analysis. Imaging mass spectrometry is ideal for this purpose because it allows the drug and its
metabolites to be distinguished while maintaining the spatial localization of these compounds. Imaging mass spectrometry of drugs and other small molecules has the added challenge in that there is redundancy of nominal masses observed in the lower-molecular-weight region of the spectrum. Often several compounds within a tissue section can have the same nominal mass as the molecule of interest and may not be resolved by lower mass resolution analyzers such as quadrupole or even time-of-flight-based analyzers. Three different approaches can be taken to circumvent
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this issue. The first is to use a much higher resolution mass analyzer such as a Fourier transform ion cyclotron resonance (FT-ICR) instrument that can easily distinguish compounds separated by fractions of a mass unit and confidently validate the identity of a compound using accurate mass.68,70 A second approach is to carry out the imaging using an MS/MS mode by following a specific transition from the parent mass to a fragment ion of the compound.17,71 A third approach is to use ion mobility MS to separate molecules of interest from other isobaric compounds based on their gas-phase conformations and capture crosssectional areas.11,72 Castellino et al. have shown the applicability of the FT-ICR approach in the imaging of several drugs and metabolites in animal tissue.68 Organs were collected from dogs dosed with lapatinib (which is used to treat breast cancer and other solid tumors) and subjected to IMS using a Bruker solariX 12T FT-ICR mass spectrometer. By using this highresolution instrument, investigators were able to distinguish two different metabolites, GW006 and M2, which differ in mass by only 0.013 amu and display different spatial distributions within the liver of the dosed dog. This work has led to the identification of a total of 21 different metabolites in dog liver sections.68 Alternatively, SRM through the application of MS/MS imaging can be used to accurately determine the spatial localization and quantitation of drug compounds in tissue sections. Goodwin et al. have employed this approach in the analysis of positron emission tomography (PET) tracers in the brains and kidneys of mice.73 Two compounds, 3,5-dichloro-N-[(2S)-1-ethylpyrrolidin-2-yl] methyl-2-hydroxy-6-methoxybenzamide (raclopride) or 7-cholor-3-methyl-1-phenyl-1,2,4,5tetrahydro-3-benzazepin-8-ol (Scheme 23390), were administered by injection at different doses through the tail veins of rats. Animals were sacrificed at 1, 5, or 30 min post dose and
the brains and kidneys dissected and snap frozen. Midpoint sections of the organs were collected and α-cyano-4-hydroxycinnamic acid matrix was deposited by dry coating, which allowed for desorption and ionization of both compounds without the delocalization that can occur with wet, solvent-based matrix application. Both compounds were imaged as intact parent masses along with MS/MS imaging. Raclopride was imaged by monitoring the transition m/z 347 to m/z 129 and m/z 111, while Scheme 23390 was imaged by monitoring the transition m/z 288 to m/z 179. Images of parent compounds collected using both qTOF and FT-ICR instruments showed excellent correlation with MS/MS images of the compounds confirming their localization and identities (Fig. 4). Raclopride was found to be at highest levels in the brain 1 min post dose with an 80% drop in concentration after 30 min as evidenced by decreased signal intensity. Similar results were obtained in the kidney. This method was also used to quantitate raclopride in the tissue sections by use of a serial dilution of the compound on control tissue section to a generated calibration curve based on signal response. Raclopride was determined to be at a concentration of 60nM 1 min post 7.5 mg/kg dose and a concentration of 15nM at 1 min post 2 mg/kg dose.
Three-dimensional imaging An exciting application of IMS is the ability to generate three-dimensional (3D) volumes of biomolecules within an organ or animal often with coregistration to other imaging modalities. This approach has been used to create 3D volumes of the corpus callosum74 and the substantia nigra within the rodent brain.75 Coregistration of IMS with magnetic resonance imaging (MRI) was shown using a xenograph model of a human glioma in a rat brain.76 Proteomic data from imaged brain sections could be correlated with data from noninvasive MRI data.
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FIG. 4 Imaging mass spectrometry abundance distributions obtained on a range of MALDI mass spectrometers for rat brain tissue sections (14 μm thick) coated with a solvent free dry matrix (CHCA). Raclopride brain tissue sections (i.v. 2.5 mg/kg) dose tissues (A) analyzed by MALDI q-TOF at a spatial resolution of 100 μm. Abundance displayed on a heat-map scale. (B) Analyzed by MALDI FT ICR at a spatial resolution of 100 μm. (C) Pseudo-SRM images produced by mapping the distribution of the MSMS fragmentation masses for raclopride m/z 347.0 to 129.1 (C.i) and 111.9 (C.ii) at a spatial resolution of 200 μm performed on a MALDI q-TOF. Scheme 23390 brain tissue sections (i.v. 5 mg/kg) (D) analyzed by MALDI q-TOF at a spatial resolution of 100 μm. Abundance displayed on a heat-map scale. (E) Analyzed by MALDI TOF at a spatial resolution of 200 μm. (F) Pseudo-SRM image produced by mapping the distribution of the MSMS fragmentation masses for Scheme 23390 m/z 289.1 to 179.0 abundance as heat-map scale (F.i) and monochrome red scale (F.ii) at a spatial resolution of 200 μm performed on a MALDI q-TOF. Reprinted with permission from Goodwin RJ, Mackay CL, Nilsson A, et al. Qualitative and quantitative MALDI imaging of the positron emission tomography ligands raclopride (a D2 dopamine antagonist) and SCH 23390 (a D1 dopamine antagonist) in rat brain tissue sections using a solvent-free dry matrix application method. Anal Chem 2011;83(24):9694–9701. Copyright 2011 American Chemical Society.
Applications of IMS involving 3D imaging require that many sections must be registered to each other to construct a molecular volume. Thus, it is necessary to minimize any physical distortion of the samples during sectioning of the tissue.70,77 It is also important that all sample preparation and data collection parameters are kept constant throughout the experiment to minimize nonbiological variability.
We have shown the coregistration of IMS and MRI in a murine model of staphylococcus infection and treatment with linezolid.77 Animals were infected retro-orbitally and the infection allowed to progress for 96 h before treatment with 0.2 mg/mL of linezolid for 96 h. The animals were splinted to prevent movement and subjected to MRI measurements of the abdomen. Large abscesses were observed in the kidneys of untreated animals45
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with smaller abscesses found in the treated animals. Animals were then sacrificed, snap frozen, and sectioned in a whole body cryomacrotome. Prior to each section being cut, a photograph of the blockface was taken. About 40 sections were collected per animal in the region encompassing the kidneys and subjected to protein IMS. Three-dimensional volumes were generated of proteins that localized to the abscesses and normal kidney structures and were then coregistered through the use of the optical blockface intermediary to the MRI volumes. Calgranulin A showed localization to the abscesses in the IMS volume and corresponded to the observed abscesses in the MRI volume. A second protein fragment, α-globin residues 2–47, was found to localize to the cortex of the kidney. This study clearly showed the ability of IMS to monitor the infection process and treatment through multimodality imaging using MRI and IMS.
High-speed imaging One of the major challenges when moving to higher spatial resolutions and higher data volumes required for 3D imaging is the time necessary to acquire the data. The use of high-repetition-rate lasers12 and continuous raster sample stages are highly beneficial in achieving high-speed imaging. This benefit has been shown in images acquired using the instrument from SimulTOF (Virgin Instruments, Inc.).78 This mass spectrometer couples a 5-kHz laser repetition rate with continuous raster. Pixel dimensions are determined by the number of shots per pixel, the stage speed, and the repetition rate of the laser. By operating the laser at 3 kHz, a stage speed of 5 mm/s, and acquiring 60 shots per pixel, an image of a sagittal rat brain section (185 mm2) consisting of approximately 19,000 pixels can be acquired in under 10 min. Such technological advances are imperative as IMS moves to
higher numbers of samples and higher spatial resolution.
Conclusions and perspectives Imaging mass spectrometry has shown wide applicability in the study of biological systems allowing for the in situ analysis of many classes of biomolecules, including proteins, peptides, lipids, and drugs/metabolites. The ability to identify these biomolecules both spatially and quantitatively provides valuable insight into their involvement in biological and disease processes. Although relative quantitation has been clearly demonstrated, processes necessary to achieve absolute quantitation are just beginning. Imaging mass spectrometry has provided insights into better diagnostics, outcomes, and treatment response, especially in areas where traditional histology has not been effective. As the technology and sample preparation methods advance, IMS is becoming easier to use in a wide variety of applications in the biological and medical fields. The molecular specificity of this imaging technology brings a very powerful and enabling tool to these disciplines.
Acknowledgments The authors acknowledge funding from NIH/NIGMS 8P41 GM103391-02 (formerly NIH/NCRR 8P41 RR031461-02), NIH/NIGMS 5R01 GM058008-13, and the DOD grant W81XWH-05-1-0179.
References 1. Caprioli RM, Farmer TB, Gile J. Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS. Anal Chem 1997;69(23):4751–60. 2. Seeley EH, Schwamborn K, Caprioli RM. Imaging of intact tissue sections: moving beyond the microscope. J Biol Chem 2011;286(29):25459–66. 3. McDonnell LA, Heeren RMA. Imaging mass spectrometry. Mass Spectrom Rev 2007;26(4):606–43.
350
19. Imaging mass spectrometry of intact biomolecules in tissue sections
4. Fletcher JS, Vickerman JC, Winograd N. Label free biochemical 2D and 3D imaging using secondary ion mass spectrometry. Curr Opin Chem Biol 2011;15(5):733–40. 5. Lorey II DR, Morrison GH, Chandra S. Dynamic secondary ion mass spectrometry analysis of boron from boron neutron capture therapy drugs in co-cultures: single-cell imaging of two different cell types within the same ion microscopy field of imaging. Anal Chem 2001;73(16):3947–53. 6. Yokoyama K, Miyatake S-I, Kajimoto Y, et al. Analysis of boron distribution in vivo for boron neutron capture therapy using two different boron compounds by secondary ion mass spectrometry. Radiat Res 2007;167(1):102–9. 7. Takats Z, Wiseman JM, Gologan B, Cooks RG. Mass spectrometry sampling under ambient conditions with desorption electrospray ionization. Science 2004;306(5695):471–3. 8. Wiseman JM, Puolitaival SM, Takats Z, Cooks RG, Caprioli RM. Mass spectrometric profiling of intact biological tissue by using desorption electrospray ionization. Angew Chem Int Ed Engl 2005;44(43):7094–7. 9. Baluya DL, Garrett TJ, Yost RA. Automated MALDI matrix deposition method with inkjet printing for imaging mass spectrometry. Anal Chem 2007;79(17):6862–7. 10. Cazares LH, Troyer D, Mendrinos S, et al. Imaging mass spectrometry of a specific fragment of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase kinase 2 discriminates cancer from uninvolved prostate tissue. Clin Cancer Res 2009;15(17):5541–51. 11. Harris GA, Graf S, Knochenmuss R, Fernandez FM. Coupling laser ablation/desorption electrospray ionization to atmospheric pressure drift tube ion mobility spectrometry for the screening of antimalarial drug quality. Analyst (Lond) 2012;137(13):3039–44. 12. Trim PJ, Djidja MC, Atkinson SJ, et al. Introduction of a 20 kHz Nd:YVO4 laser into a hybrid quadrupole time-offlight mass spectrometer for MALDI-MS imaging. Anal Bioanal Chem 2010;397(8):3409–19. 13. Harris GA, Falcone CE, Fernandez FM. Sensitivity “hot spots” in the direct analysis in real time mass spectrometry of nerve agent simulants. J Am Soc Mass Spectrom 2012;23(1):153–61. 14. Dill AL, Eberlin LS, Ifa DR, Cooks RG. Perspectives in imaging using mass spectrometry. Chem Commun (Camb) 2011;47(10):2741–6. 15. Greer T, Sturm R, Li L. Mass spectrometry imaging for drugs and metabolites. J Proteomics 2011;74(12):2617–31. 16. Amann JM, Chaurand P, Gonzalez A, et al. Selective profiling of proteins in lung cancer cells from fine-needle aspirates by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Clin Cancer Res 2006;12(17):5142–50. 17. Khatib-Shahidi S, Andersson M, Herman JL, Gillespie TA, Caprioli RM. Direct molecular analysis of
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
whole-body animal tissue sections by imaging MALDI mass spectrometry. Anal Chem 2006;78(18):6448–56. Zavalin A, Yang J, Caprioli RM. Tissue imaging at submicron spatial resolution using direct transmission geometry MALDI MS, In: 60th ASMS conference on mass spectrometry and allied topics, Vancouver, BC; 2012. Aerni HR, Cornett DS, Caprioli RM. Automated acoustic matrix deposition for MALDI sample preparation. Anal Chem 2006;78(3):827–34. Chaurand P, Fouchecourt S, DaGue BB, et al. Profiling and imaging proteins in the mouse epididymis by imaging mass spectrometry. Proteomics 2003; 3(11):2221–39. Hankin JA, Barkley RM, Murphy RC. Sublimation as a method of matrix application for mass spectrometric imaging. J Am Soc Mass Spectrom 2007;18(9):1646–52. Burnum KE, Cornett DS, Puolitaival SM, et al. Spatial and temporal alterations of phospholipids determined by mass spectrometry during mouse embryo implantation. J Lipid Res 2009;50(11):2290–8. Schwartz SA, Reyzer ML, Caprioli RM. Direct tissue analysis using matrix-assisted laser desorption/ionization mass spectrometry: practical aspects of sample preparation. J Mass Spectrom 2003;38(7):699–708. Yang J, Caprioli RM. Matrix sublimation/recrystallization for imaging proteins by mass spectrometry at high spatial resolution. Anal Chem 2011;83(14):5728–34. Cornett DS, Mobley JA, Dias EC, et al. A novel histologydirected strategy for MALDI-MS tissue profiling that improves throughput and cellular specificity in human breast cancer. Mol Cell Proteomics 2006;5(10):1975–83. Bauer JA, Chakravarthy AB, Rosenbluth JM, et al. Identification of markers of taxane sensitivity using proteomic and genomic analyses of breast tumors from patients receiving neoadjuvant paclitaxel and radiation. Clin Cancer Res 2010;16(2):681–90. Reyzer ML, Caldwell RL, Dugger TC, et al. Early changes in protein expression detected by mass spectrometry predict tumor response to molecular therapeutics. Cancer Res 2004;64(24):9093–100. Rauser S, Marquardt C, Balluff B, et al. Classification of HER2 receptor status in breast cancer tissues by MALDI imaging mass spectrometry. J Proteome Res 2010;9(4):1854–63. Xu BJ, Caprioli RM, Sanders ME, Jensen RA. Direct analysis of laser capture microdissected cells by MALDI mass spectrometry. J Am Soc Mass Spectrom 2002;13(11):1292–7. Drake RR, Cazares LH, Jones EE, Fuller TW, Semmes OJ, Laronga C. Challenges to developing proteomic-based breast cancer diagnostics. OMICS 2011;15(5):251–9. Schwamborn K, Krieg RC, Reska M, Jakse G, Knuechel R, Wellmann A. Identifying prostate carcinoma by MALDIimaging. Int J Mol Med 2007;20(2):155–9.
References
32. Cazares LH, Troyer D, Mendrinos S, et al. Imaging mass spectrometry of a specific fragment of mitogenactivated protein kinase/extracellular signal-regulated kinase kinase kinase 2 discriminates cancer from uninvolved prostate tissue. Clin Cancer Res 2009;15 (17):5541–51. 33. Oppenheimer SR, Mi D, Sanders ME, Caprioli RM. Molecular analysis of tumor margins by MALDI mass spectrometry in renal carcinoma. J Proteome Res 2010; 9(5):2182–90. 34. Hardesty WM, Kelley MC, Mi D, Low RL, Caprioli RM. Protein signatures for survival and recurrence in metastatic melanoma. J Proteomics 2011;74(7):1002–14. 35. Chaurand P, DaGue BB, Pearsall RS, Threadgill DW, Caprioli RM. Profiling proteins from azoxymethaneinduced colon tumors at the molecular level by matrixassisted laser desorption/ionization mass spectrometry. Proteomics 2001;1(10):1320–6. 36. Rahman SM, Gonzalez AL, Li M, et al. Lung cancer diagnosis from proteomic analysis of preinvasive lesions. Cancer Res 2011;71(8):3009–17. 37. Rahman SM, Shyr Y, Yildiz PB, et al. Proteomic patterns of preinvasive bronchial lesions. Am J Respir Crit Care Med 2005;172(12):1556–62. 38. Taguchi F, Solomon B, Gregorc V, et al. Mass spectrometry to classify non-small-cell lung cancer patients for clinical outcome after treatment with epidermal growth factor receptor tyrosine kinase inhibitors: a multicohort cross-institutional study. J Natl Cancer Inst 2007;99(11):838–46. 39. Yanagisawa K, Shyr Y, Xu BJ, et al. Proteomic patterns of tumour subsets in non-small-cell lung cancer. Lancet 2003;362(9382):433–9. 40. Yanagisawa K, Xu BJ, Carbone DP, Caprioli RM. Molecular fingerprinting in human lung cancer. Clin Lung Cancer 2003;5(2):113–8. 41. Gustafsson JO, Oehler MK, Ruszkiewicz A, McColl SR, Hoffmann P. MALDI imaging mass spectrometry (MALDI-IMS)-application of spatial proteomics for ovarian cancer classification and diagnosis. Int J Mol Sci 2011;12(1):773–94. 42. Balluff B, Rauser S, Meding S, et al. MALDI imaging identifies prognostic seven-protein signature of novel tissue markers in intestinal-type gastric cancer. Am J Pathol 2011;179(6):2720–9. 43. Kim HK, Reyzer ML, Choi IJ, et al. Gastric cancer-specific protein profile identified using endoscopic biopsy samples via MALDI mass spectrometry. J Proteome Res 2010;9(8):4123–30. 44. M’Koma AE, Seeley EH, Washington MK, et al. Proteomic profiling of mucosal and submucosal colonic tissues yields protein signatures that differentiate the inflammatory colitides. Inflamm Bowel Dis 2011;17(4): 875–83.
351
45. Corbin BD, Seeley EH, Raab A, et al. Metal chelation and inhibition of bacterial growth in tissue abscesses. Science 2008;319(5865):962–5. 46. Oswald-Richter KA, Beachboard DC, Seeley EH, et al. Dual analysis for mycobacteria and propionibacteria in sarcoidosis BAL. J Clin Immunol 2012;. 47. Oezdemir RF, Gaisa NT, Lindemann-Docter K, et al. Proteomic tissue profiling for the improvement of grading of noninvasive papillary urothelial neoplasia. Clin Biochem 2012;45(1–2):7–11. 48. Lemaire R, Desmons A, Tabet JC, Day R, Salzet M, Fournier I. Direct analysis and MALDI imaging of formalin-fixed, paraffin-embedded tissue sections. J Proteome Res 2007;6(4):1295–305. 49. Casadonte R, Caprioli RM. Proteomic analysis of formalin-fixed paraffin-embedded tissue by MALDI imaging mass spectrometry. Nat Protoc 2011; 6(11):1695–709. 50. Lazova R, Seeley EH, Keenan M, Gueorguieva R, Caprioli RM. Imaging mass spectrometry – a new and promising method to differentiate Spitz nevi from Spitzoid malignant melanomas. Am J Dermatopathol 2012; 34(1):82–90. 51. Groseclose MR, Massion PP, Chaurand P, Caprioli RM. High-throughput proteomic analysis of formalin-fixed paraffin-embedded tissue microarrays using MALDI imaging mass spectrometry. Proteomics 2008; 8(18):3715–24. 52. Djidja MC, Claude E, Snel MF, et al. Novel molecular tumour classification using MALDI-mass spectrometry imaging of tissue micro-array. Anal Bioanal Chem 2010;397(2):587–601. 53. Morita Y, Ikegami K, Goto-Inoue N, et al. Imaging mass spectrometry of gastric carcinoma in formalin-fixed paraffin-embedded tissue microarray. Cancer Sci 2010;101(1):267–73. 54. Schwamborn K, Wild P, Caprioli RM. Uncovering the proteome of late state prostate cancer by imaging mass spectrometry, In: 58th ASMS conference on mass spectrometry and allied topics, Salt Lake City, UT; 2010. 55. Hanrieder J, Ljungdahl A, Andersson M. MALDI imaging mass spectrometry of neuropeptides in Parkinson’s disease. J Vis Exp 2012;(60):3445. 56. Berridge MJ, Irvine RF. Inositol trisphosphate, a novel second messenger in cellular signal transduction. Nature 1984;312(5992):315–21. 57. Khan WA, Blobe GC, Hannun YA. Arachidonic acid and free fatty acids as second messengers and the role of protein kinase C. Cell Signal 1995;7(3):171–84. 58. Liu Y, Chen Y, Momin A, et al. Elevation of sulfatides in ovarian cancer: an integrated transcriptomic and lipidomic analysis including tissue-imaging mass spectrometry. Mol Cancer 2010;9:186–99. 59. Katz-Brull R, Seger D, Rivenson-Segal D, Rushkin E, Degani H. Metabolic markers of breast cancer: enhanced
352
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
19. Imaging mass spectrometry of intact biomolecules in tissue sections
choline metabolism and reduced choline-etherphospholipid synthesis. Cancer Res 2002;62(7):1966–70. Han X, Cheng H, Fryer JD, Fagan AM, Holtzman DM. Novel role for apolipoprotein E in the central nervous system. Modulation of sulfatide content. J Biol Chem 2003;278(10):8043–51. Woods AS, Jackson SN. Brain tissue lipidomics: direct probing using matrix-assisted laser desorption/ionization mass spectrometry. AAPS J 2006;8(2):E391–5. Jackson SN, Wang HY, Woods AS. In situ structural characterization of phosphatidylcholines in brain tissue using MALDI-MS/MS. J Am Soc Mass Spectrom 2005; 16(12):2052–6. Angel PM, Spraggins JM, Baldwin HS, Caprioli R. Enhanced sensitivity for high spatial resolution lipid analysis by negative ion mode matrix assisted laser desorption ionization imaging mass spectrometry. Anal Chem 2012;84(3):1557–64. Menger RF, Stutts WL, Anbukumar DS, Bowden JA, Ford DA, Yost RA. MALDI mass spectrometric imaging of cardiac tissue following myocardial infarction in a rat coronary artery ligation model. Anal Chem 2012; 84(2):1117–25. Starkopf J, Andreasen TV, Bugge E, Ytrehus K. Lipid peroxidation, arachidonic acid and products of the lipoxygenase pathway in ischaemic preconditioning of rat heart. Cardiovasc Res 1998;37(1):66–75. Reyzer ML, Caprioli RM. MALDI-MS-based imaging of small molecules and proteins in tissues. Curr Opin Chem Biol 2007;11(1):29–35. Stoeckli M, Staab D, Schweitzer A. Compound and metabolite distribution measured by MALDI mass spectrometric imaging in whole-body tissue sections. Int J Mass Spectrom 2007;260(2–3):195–202. Castellino S, Groseclose MR, Wagner D. MALDI imaging mass spectrometry: bridging biology and chemistry in drug development. Bioanalysis 2011;3(21):2427–41. Takai N, Tanaka Y, Inazawa K, Saji H. Quantitative analysis of pharmaceutical drug distribution in multiple organs by imaging mass spectrometry. Rapid Commun Mass Spectrom 2012;26(13):1549–56.
70. Goodwin RJ, Nilsson A, Borg D, et al. Conductive carbon tape used for support and mounting of both whole animal and fragile heat-treated tissue sections for MALDI MS imaging and quantitation. J Proteomics 2012; 75:4912–20. 71. Chacon A, Zagol-Ikapitte I, Amarnath V, et al. On-tissue chemical derivatization of 3-methoxysalicylamine for MALDI-imaging mass spectrometry. J Mass Spectrom 2011;46(8):840–6. 72. Trim PJ, Henson CM, Avery JL, et al. Matrix-assisted laser desorption/ionization-ion mobility separationmass spectrometry imaging of vinblastine in whole body tissue sections. Anal Chem 2008;80(22):8628–34. 73. Goodwin RJ, Mackay CL, Nilsson A, et al. Qualitative and quantitative MALDI imaging of the positron emission tomography ligands raclopride (a D2 dopamine antagonist) and SCH 23390 (a D1 dopamine antagonist) in rat brain tissue sections using a solvent-free dry matrix application method. Anal Chem 2011; 83(24):9694–701. 74. Crecelius AC, Cornett DS, Caprioli RM, Williams B, Dawant BM, Bodenheimer B. Three-dimensional visualization of protein expression in mouse brain structures using imaging mass spectrometry. J Am Soc Mass Spectrom 2005;16(7):1093–9. 75. Andersson M, Groseclose MR, Deutch AY, Caprioli RM. Imaging mass spectrometry of proteins and peptides: 3D volume reconstruction. Nature Met 2008;5(1):101–8. 76. Sinha TK, Khatib-Shahidi S, Yankeelov TE, et al. Integrating spatially resolved three-dimensional MALDI IMS with in vivo magnetic resonance imaging. Nature Met 2008;5(1):57–9. 77. Attia AS, Schroeder KA, Seeley EH, et al. Monitoring the inflammatory response to infection through the integration of MALDI IMS and MRI. Cell Host Microbe 2012; 11(6):664–73. 78. Spraggins JM, Caprioli RM. High-speed MALDITOF imaging mass spectrometry: rapid ion image acquisition and considerations for next generation instrumentation. J Am Soc Mass Spectrom 2011; 22(6):1022–31.