Ultrahighly Sensitive in Situ Metabolomic Imaging for Visualizing

Nov 2, 2010 - Daisuke Miura,*,† Yoshinori Fujimura,† Mayumi Yamato,† Fuminori Hyodo,† Hideo Utsumi,†. Hirofumi Tachibana,†,‡,§ and Hiro...
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Anal. Chem. 2010, 82, 9789–9796

Ultrahighly Sensitive in Situ Metabolomic Imaging for Visualizing Spatiotemporal Metabolic Behaviors Daisuke Miura,*,† Yoshinori Fujimura,† Mayumi Yamato,† Fuminori Hyodo,† Hideo Utsumi,† Hirofumi Tachibana,†,‡,§ and Hiroyuki Wariishi*,†,‡,§ Innovation Center for Medical Redox Navigation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan, and Faculty of Agriculture and Bio-Architecture Center, Kyushu University, 6-10-1 Hakozaki, Higashi-ku, Fukuoka 812-8581, Japan A sensitive and simultaneous analytical technique for visualizing multiple endogenous molecules is now strongly required in biological science. Here, we show the applicability of a matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) system for getting chemically diverse metabolite profiles on a single-mammalian cell. This ultrahighly sensitive MALDI-MS technique enabled a spatially resolved detection of a broad range of metabolites including nucleotides, cofactors, phosphorylated sugars, amino acids, lipids, and carboxylic acids in normal mouse brain tissue with their unique distributions. Furthermore, a combination of MS imaging and metabolic pathway analysis of a rat transient middle cerebral artery occlusion model visualized a spatiotemporal behavior of metabolites in the central metabolic pathway regulated by an ischemia reperfusion. These findings highlight potential applications of an in situ metabolomic imaging technique to visualize spatiotemporal dynamics of the tissue metabolome, which will facilitate biological discovery in both preclinical and clinical settings. Understanding the complex biochemical processes that occur within living organisms requires not only the elucidation of the molecular entities involved in these processes but also their spatial distribution within the organism. Analytical technologies for elucidating multiple molecular dynamics in the microregion with spatial information of tissue are thought to be an important subject for understanding biological complexity of disease progress. Chemical staining, immunohistochemical tagging, and radiolabeling are common methods for visualizing and identifying molecular targets. However, there are limits to the sensitivity and specificity of these methods and to the number of target compounds that can be monitored simultaneously. Metabolomics, the measurement of a global endogenous metabolite profile from a biological sample under different conditions, can lead us to an enhanced understanding of disease mechanisms, the discovery of diagnostic biomarkers, the elucida* Corresponding author. D.M: tel, +81-92-642-6091; fax, +81-92-642-6285; e-mail, [email protected]. H.W.: tel/fax, +81-92-642-2992; e-mail, hirowari@ agr.kyushu-u.ac.jp. † Innovation Center for Medical Redox Navigation. ‡ Faculty of Agriculture. § Bio-Architecture Center. 10.1021/ac101998z  2010 American Chemical Society Published on Web 11/02/2010

tion of mechanisms for drug action, and an increased ability to predict individual variation in drug response phenotypes.1,2 Thus, this rapidly developing discipline has important potential implications for the biomedical research field. To date, mass spectrometry (MS) coupled with preseparation techniques such as liquid chromatography (LC-MS) or gas chromatography (GC-MS) has been known to be a conventional strategy for metabolomics.3-5 However, these methods have a drawback in analysis of tissue samples due to a requirement of metabolite extraction, which causes the loss of information on spatial localization of the metabolites. In contrast, imaging techniques capable of determining spatial localization of molecules have revolutionized our approach to diseases by allowing us to directly examine the pathological process, thus giving us a better understanding of the pathophysiology. However, in most cases, there is a trade-off among sensitivity, molecular coverage, spatial resolution, and temporal resolution. For example, magnetic resonance imaging (MRI), positron emission tomography (PET), and fluorescence microscopy are available for visualizing the spatial localization of targeted molecules with high sensitivity, but they have low molecular coverage (only a few molecules at a time).6 The simultaneous and spatially resolved detection of a broad range of molecules with high sensitivity is still a challenging issue. Mass spectrometry imaging (MSI) is a remarkable new technology that enables us to determine the distribution of biological molecules present in tissue sections by direct ionization (1) Soga, T.; Baran, R.; Suematsu, M.; Ueno, Y.; Ikeda, S.; Sakurakawa, T.; Kakazu, Y.; Ishikawa, T.; Robert, M.; Nishioka, T.; Tomita, M. J. Biol. Chem. 2006, 281, 16768–16776. (2) Sreekumar, A.; Poisson, L. M.; Rajendiran, T. M.; Khan, A. P.; Cao, Q.; Yu, J.; Laxman, B.; Mehra, R.; Lonigro, R. J.; Li, Y.; Nyati, M. K.; Ahsan, A.; Kalyana-Sundaram, S.; Han, B.; Cao, X.; Byun, J.; Omenn, G. S.; Ghosh, D.; Pennathur, S.; Alexander, D. C.; Berger, A.; Shuster, J. R.; Wei, J. T.; Varambally, S.; Beecher, C.; Chinnaiyan, A. M. Nature 2009, 457, 910– 914. (3) Werner, E.; Croixmarie, V.; Umbdenstock, T.; Ezan, E.; Chaminade, P.; Tabet, J. C.; Junot, C. Anal. Chem. 2008, 80, 4918–4932. (4) Major, H. J.; Williams, R.; Wilson, A. J.; Wilson, I. D. Rapid Commun. Mass Spectrom. 2006, 20, 3295–3302. (5) Pohjanen, E.; Thysell, E.; Jonsson, P.; Eklund, C.; Silfver, A.; Carlsson, I. B.; Lundgren, K.; Moritz, T.; Svensson, M. B.; Antti, H. J. Proteome Res. 2007, 6, 2113–2120. (6) Judenhofer, M. S.; Wehrl, H. F.; Newport, D. F.; Catana, C.; Siegel, S. B.; Becker, M.; Thielscher, A.; Kneilling, M.; Lichy, M. P.; Eichner, M.; Klingel, K.; Reischl, G.; Widmaier, S.; Rocken, M.; Nutt, R. E.; Machulla, H. J.; Uludag, K.; Cherry, S. R.; Claussen, C. D.; Pichler, B. J. Nat. Med. 2008, 14, 459–465.

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and detection with matrix-assisted laser desorption ionization (MALDI)-MS.7 This technique is now widely used for in situ imaging of endogenous or exogenous molecules such as proteins, lipids, drugs, and their metabolites and is expected to be a potential tool for pathological analysis and understanding of disease mechanisms, but there are several issues on its limitation in technical application.7-9 One of the major problems is that many kinds of matrix and/or matrix-analyte cluster ion peaks are observed in the low-mass range (m/z < 700); therefore, the generation of these strong peaks interferes with the the detection of target low-molecular-weight compounds. We have recently reported that a matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) system with 9-aminoacridine (9-AA), a matrix that exhibits very few matrixderived interferences in the low-mass range, achieved great improvement for the sensitivity of metabolite analysis (detection potential with subfemtomole sensitivity for various endogenous metabolites) that is advantageous for the simultaneous detection of a variety of cellular metabolites.10,11 In the present study, we investigated the possibility of this technique as a multiple molecular imaging with high sensitivity. The MALDI-MS system was able to get metabolite profiles on a single mammalian cell. This ultrahighly sensitive imaging technique visualized the distribution of a broad range of metabolites simultaneously in normal mouse brain tissue. Furthermore, analysis of brain tissues from a transient middle cerebral artery occlusion (MCAO) rat model indicates that the present in situ metabolomic imaging technique can visualize the spatiotemporal distribution of a wide variety of tissue metabolites simultaneously. These findings are considered to be a promising imaging modality with great potential in pathological metabolomics and metabolic dynamics. MATERIALS AND METHODS Materials. 9-AA hydrochloride and indium tin oxide (ITO)coated slide glass were obtained from Sigma-Aldrich. 9-AA was recrystallized prior to use. Methanol and metabolite standards used in this study were purchased from Wako Pure Chemical Industries, Ltd. Preparation of Single Cell. HeLa cells, the human cervical cancer cell line (American Type Culture Collection), were maintained in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 100 U/mL penicillin G, 100 µg/mL streptomycin, 25 mM Hepes buffer, and 44 mM NaHCO3 in a humidified atmosphere with 5% CO2 at 37 °C. For a single cell experiment, a suspension of HeLa cells in DMEM was mounted on the ITO-coated slide glass marked with a scale of 50 µm (Kiriyama glass Co.). After a 6-h incubation, the cells were washed with ice-cold PBS twice, and an optical image of a single cell was obtained using a light microscope. This cell was subjected to the following mass spectrometry imaging experiment. (7) Caprioli, R. M.; Farmer, T. B.; Gile, J. Anal. Chem. 1997, 69, 4751–4760. (8) Shimma, S.; Sugiura, Y.; Hayasaka, T.; Zaima, N.; Matsumoto, M.; Setou, M. Anal. Chem. 2008, 80, 878–885. (9) Khatib-Shahidi, S.; Andersson, M.; Herman, J. L.; Gillespie, T. A.; Caprioli, R. M. Anal. Chem. 2006, 78, 6448–6456. (10) Miura, D.; Fujimura, Y.; Tachibana, H.; Wariishi, H. Anal. Chem. 2010, 82, 498–504. (11) Yukihira, D.; Miura, D.; Saito, K.; Takahashi, K.; Wariishi, H. Anal. Chem. 2010, 82, 4278–4282.

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Animal Protocol. Details of the protocol were described in the Supporting Information text. All animal experiments were approved by the animal Care and Use Committee of Kyushu University. MSI Experiment. Brain tissues were sectioned at 10 µm thickness with cryostat and, then, thaw-mounted onto an ITOcoated glass slide (Sigma-Aldrich). A matrix solution (5 mg/mL 9-AA in 100% methanol) was sprayed in the draft hood using an airbrush under room temperature (22 °C, 50% humidity). In this study, we used three types of MS instruments. For MSI, single reflectron-type MALDI-TOF-MS (AXIMA Confidence, Shimadzu) was used. The spot size for the laser of the instrument that we used for the imaging experiment, AXIMA Confidence from Shimadzu, is about 50-100 µm. For identification of metabolites by MS/MS analysis, quadrupole ion trap (QIT)-type (AXIMA QIT, Shimadzu) and TOF/TOF-type (AXIMA Performance, Shimadzu) instruments were used. These instruments were equipped with a 337 nm N2 laser. In the MSI experiment, data were acquired in negative ionization mode with 50 µm spatial resolution (10 laser shots/data point), and the signals between m/z ) 50 and 1000 were collected. Metabolites were identified or estimated by comparing MS/MS spectra with standard compounds or databases (METLIN, http://metlin.scripps.edu/; MassBank, http:// www.massbank.jp/; and Human Metabolome Database, http:// www.hmdb.ca/). Acquired MSI data were processed with the freely available software BioMap. For normalization of imaging data, first, we constructed an averaged mass spectrum image ranging from m/z ) 50 to 1000 over the whole region of the tissue section. Second, averaged mass intensity maps of overall mass range were created. Third, averaged mass intensity maps divided the intensity maps of each peak. This operation means that the intensity of each peak in each pixel was divided by the average of the total ion count of each pixel. This normalization process is critical for quantitative comparison of MSI data acquired from different tissue sections because MALDI ionization has been known to cause both spot-to-spot and sample-to-sample variances of signal intensities based on the heterogeneity of matrix crystals. The signal intensity of each imaging data in the figure was represented as the normalized intensity. Quantitative Analysis of Metabolites With LC-MS. Brain tissue samples were homogenized in 80% MeOH, including 10 µM sulfanilamide for evaluating the extraction efficiency, on ice (50 mg per tissue in 1 mL vials) using dounce tissue grinders. After centrifugation at 15 000g for 30 min, the supernatant was collected, and the equal volume of a 2:1 H2O/CHCl3 solution was added and further mixed vigorously for 30 s. Each sample was, then, centrifuged at 15 000g for 20 min at 4 °C. After centrifugation, the aqueous layers were collected. Furthermore, a speedVac instrument was used for solvent removal and sample concentration. The resultant samples were stored at -80 °C until assay. Samples were dissolved in 30 µL of 20% acetonitrile, including 10 µM 4-hydroxybenzophenone as an internal standard, prior to analysis by the high-performance liquid chromatography with time-of-flight MS (LCMS-IT-TOF, Shimadzu). The instrument was fitted with a Discovery HS-F5 column (250 mm × 4.6 mm i.d., 5 µm; Superco), ovened at 40 °C. Mobilephase conditions were as follows: linear gradient analysis with mobile-phase A, H2O (0.1% formic acid), and mobile-phase B,

Figure 1. Detection of endogenous metabolites from single cultured mammalian cells with MALDI-MS. (A) Optical image of HeLa cells adhered on an indium tin oxide (ITO)-coated slide glass. HeLa cells were incubated for 6 h on an ITO-coated slide glass, and then, the cells were washed with phosphate-buffered saline. Scale bar ) 50 µm. (B) After spray coating with matrix, mass imaging data were acquired with 25 µm-step laser rastering, and the signals from m/z ) 300 to 1000 were collected. For the ion image of the cell, m/z ) 505.99 was selected as the representative mass peak and the image was displayed as a red color density map. (C) Mass spectra of the site in (i) or out (ii) with a single HeLa cell. Each spectrum was acquired with 10 laser shots/point, and each profile was averaged. Asterisk shows background peaks. (D) Expanded mass spectrum ranging from m/z ) 460 to 540 in c (i).

acetonitrile. After a 4 min isocratic run at 100% of the eluting solvent A, the ratio of eluting solvent B was linearly increased to 35% from 4 to 8 min and to 50% from 8 to 12 min. The composition of 50% of the eluting solvent B was maintained for 5 min. The column was washed with 100% of the eluting solvent B for 5 min, and the column equilibration was carried out with 100% of the eluting solvent A for 7 min. A 3 µL aliquot of the sample solution filtered through a 0.2 µm PTFE filter was injected onto the column with a flow rate of 0.2 mL/min. For the MS condition, the instrument was operated using an electrospray ionization source in both positive and negative ionization modes. The ionization parameters were capillary voltage, 4.5 and -3.5 kV; the nebulizer gas flow, 1.5 L/min; the CDL temperature, 250 °C; and heat block temperature, 250 °C. Statistical Analysis. All the results are shown as the mean ± SD. The statistical significance was analyzed using the Tukey test (P < 0.05). RESULTS AND DISCUSSION Detection of Metabolites in Single Cells with MALDI-MS. Single-cell sensitive analysis has emerged as a key technology in the biomedical research field to elucidate fundamental mechanisms of biological processes that will lead to novel biochemical insights and advanced disease understanding.12 Typical biochemical cell studies focused on populations, averaging the response of all of the cells obscure subtle phenotypic differences among individual cells. Understanding the response of a single-cell level is necessary for identifying subtle cellular changes that may underlie complicated biological processes involved in cell-cell communication and system-generated behaviors. Several analytical techniques such as multiphoton, scanning near-field optical microscopy or UV confocal fluorescence were now widely applied (12) Prescher, J. A.; Bertozzi, C. R. Nat. Chem. Biol. 2005, 1, 13–21.

for single cell analysis. Although these methods have excellent sensitivity, available molecular information is still limited because these approaches most often detect chemical/physical properties of only one target molecule. To date, there is no report on spatially resolved analysis of cells by the MALDI method. Recently, we have shown that the MALDI system, using 9-AA as a matrix in negative ionization mode, was suitable for analyzing low-molecularweight metabolites with high sensitivity.10,11 To evaluate the detection sensitivity of this MALDI system for analyzing metabolites in tissue sections, we first prepared the indium tin oxide (ITO)-coated slide glass, which is used for mounting tissue sections onto a MALDI sample plate, marked with a 50 µm-wide meshwork, which enabled us to match optical and MS images, for a single-cell sensitive measurement. A suspension of HeLa cells in culture medium was mounted on the ITO-coated slide glass. After a 6 h incubation at 37 °C, the cells were washed with phosphate-buffered saline; the appearance of single cells adhered to ITO glass was observed by optical imaging (Figure 1A). We, then, set this single cell-adhered glass onto a MALDI sample plate and examined the feasibility of a single cell-sensitive MSI. A series of metabolite peaks (∼50) were detected at the position of the cell (Figure 1C). Adenosine triphosphate (ATP; m/z ) 505.99, identified by comparison with a standard sample) was found as the representative metabolite ion imaging, whereas metabolite peaks were not observed in the noncell region (Figure 1B(ii),C(ii)). The ATP peak also showed a good signal-to-noise ratio (Figure 1D). Such high-quality data were also obtained in other metabolites such as fructose-1,6-bisphosphate and citrate. These results indicated that this MALDI-MS system is sensitive enough for the detection of metabolites and for two-dimensional imaging with single-cell sensitivity. The present result is the first report showing single cell metabolite analysis by MALDI-MS. Previously, single cell analysis has been demonstrated by secondary ion mass spectrometry (SIMS) with submicrometer Analytical Chemistry, Vol. 82, No. 23, December 1, 2010

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spatial resolution, but the detection of the metabolites shown here have not been reported by SIMS.13 MALDI is still limited to about 50 µm spatial resolution; however, showing the development of this capability could well result in a report of sufficient importance. Analysis at the single-cell level may allow us to resolve the order of events in complicated pathways, understand network properties, and further, facilitate systems biological mining of complicated metabolic dynamics. In Situ Metabolomic Imaging of a Normal Mouse Brain Section. MSI has received considerable attention as a potential imaging technique for a molecular ex vivo review of tissue sections from an animal based on label-free tracking of endogenous molecules such as intact proteins, lipids, and also exogenously administrated drugs and their metabolites with spatial resolution and molecular specificity.14-16 For wider use of this technique, however, it is necessary to resolve several issues on the limitations of sensitive and quantitative analysis or of target coverage. To evaluate the utility of the highly sensitive MALDI-MS technique for in situ metabolomic imaging, analysis of a sagittally sectioned mouse brain was performed. The averaged mass spectrum data of a normal mouse brain section showed more than 100 metabolite peaks (see Supporting Information, Figure S1). Unlike other oftenutilized matrixes such as 2,5-dihydroxy benzoic acid or R-cyano4-hydroxycinnamic acid,17 there were only a few 9-AA derived peaks in the mass range of 200-500 (see Supporting Information, Figure S1, asterisk mark). As far as we have checked, 9-AA was the most suitable matrix for in situ metabolite analysis. Among metabolite peaks detected in the present study, more than 30 metabolites, including nucleotides, cofactors, phosphorylated sugars, amino acids, lipids, and carboxylic acid, were successfully identified by comparison with MS/MS spectra of standard compounds or with online databases. These metabolites were simultaneously detected, and their unique distributions were visualized with a 50 µm spatial resolution in a single run (Figure 2). In previous works, lipid molecules were a major focus of MSI research because these are highly abundant in tissue and are easily ionized for the presence of a polar head.14,18 However, there is little information about other endogenous tissue metabolites in MSI. In the recent study reported by Benabdellah et al., the location of 13 metabolites in the normal rat brain, although almost all were nucleotide derivatives, was observed by MSI experiment using 9-AA as a matrix.19 In contrast, we were able to simultaneously visualize more than 30 endogenous metabolites including nucleotide derivatives as well as central metabolic pathway metabolites, redox-related metabolites, and amino acids in an animal brain section. (13) Solon, E. G.; Schweitzer, A.; Stoeckli, M.; Prideaux, B. AAPS J. 2010, 12, 11–26. (14) Sugiura, Y.; Konishi, Y.; Zaima, N.; Kajihara, S.; Nakanishi, H.; Taguchi, R.; Setou, M. J. Lipid Res. 2009, 50, 1776–1788. (15) Cornett, D. S.; Frappier, S. L.; Caprioli, R. M. Anal. Chem. 2008, 80, 5648– 5653. (16) Stoeckli, M.; Chaurand, P.; Hallahan, D. E.; Caprioli, R. M. Nat. Med. 2001, 7, 493–496. (17) Rubakhin, S. S.; Jurchen, J. C.; Monroe, E. B.; Sweedler, J. V. Drug Discovery Today 2005, 10, 823–837. (18) Sun, G.; Yang, K.; Zhao, Z.; Guan, S.; Han, X.; Gross, R. W. Anal. Chem. 2008, 80, 7576–7585. (19) Benabdellah, F.; Touboul, D.; Brunelle, A.; Laprevote, O. Anal. Chem. 2009, 81, 5557–5560.

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In Situ Metabolomic Imaging of a Brain Section of an Ischemia-Reperfusion Rat Model. To further explore the potential usefulness of the MALDI-MS technique in pathological metabolomics, we generated a rat model of transient MCAO, which readily shows the pathological difference between an infarct and noninfarct region on the same brain section. Brain damage in the MACO rat was evaluated on the basis of the infarction areas in the rat brain tissues at 0, 3, and 24 h after reperfusion following 1 h MCAO. Figure 3A illustrates the typical triphenyltetrazolium chloride (TTC)-staining patterns of the rat brain tissues. The cerebral infarction region, which was unstained or faintly red, was clearly evident around the middle cerebral artery after 24 h of reperfusion, whereas no discernible infarction was observed after 0 and 3 h of reperfusion. MSI of MCAO rat brains visualized the spatial distribution of metabolites. N-Acetylaspartate (m/z ) 174.04), a well-known indicator of neuronal damage and mitochondrial dysfunction,20 was shown as the representative metabolite caused an altered distribution in the infarct region (Figure 3B). Averaged MS spectra (6 × 6 pixels; 1 pixel ) 50 µm) of the infarct region (i) and the noninfarct region (ii) is shown in Figure 3C. MS/MS spectra of N-acetylaspartate from the standard sample (a) and from a tissue section (b) are displayed in Figure 3D, indicating that fragment ions of the tissue section corresponded to those of the standard. At 3 h reperfusion, the amount of N-acetylaspartate was reduced in the cerebral cortex (CTX) of the ischemic hemisphere, and a further marked reduction was observed at 24 h reperfusion. Generally, MALDI ionization has been found to have unfavorable nature of spot-to-spot and sampleto-sample variances of signal intensities, caused by the heterogeneity of matrix crystals and resulting in a lowered reproducibility.21,22 Although the normalization process is critical for both analytical reproducibility and quantitative comparison of MSI data acquired from different tissue sections, the methodology is still not established. In this study, analytical reproducibility of MALDIMS-based MSI was evaluated, and all standard deviations (SD) of each metabolite were about 20% by spectral normalization (see Supporting Information, Figure S2 and see Materials and Methods for MSI). Usually, intersample reproducibility of MALDI-MS is quite low (around 50% RSD) compared with GC-MS (around 10% RSD).21,22 These findings indicate that the present MSI technique shows a good quantitative performance for comparing data acquired from different tissue sections. To further investigate a potential systematic role for metabolite data obtained by MSI, we intercalated data of N-acetylaspartate and its peripheral metabolites into metabolic maps. Several metabolite data were observed on the central metabolic pathway (Figure 4A). The amount of glutamate, a well-known neurotransmitter and an indicator of neuronal damage,23 decreased in the ischemic CTX compared with the contralateral CTX at 24 h of reperfusion. In the ischemic CTX, a reduced level of aspartate was also observed at 3 and 24 h reperfusion. Unlike the reduction in N-acetylaspartate, glutamate, and asparate between 3 and 24 h in the ischemic hemisphere, citrate accumulated in the corpus (20) Moffett, J. R.; Ross, B.; Arun, P.; Madhavarao, C. N.; Namboodiri, A. M. Prog. Neurobiol. 2007, 81, 89–131. (21) Edwards, J. L.; Kennedy, R. T. Anal. Chem. 2005, 77, 2201–2209. (22) Fiehn, O.; Kopka, J.; Dormann, P.; Altmann, T.; Trethewey, R. N.; Willmitzer, L. Nat. Biotechnol. 2000, 18, 1157–1161. (23) Graham, S. H.; Shiraishi, K.; Panter, S. S.; Simon, R. P.; Faden, A. I. Neurosci. Lett. 1990, 110, 124–130.

Figure 2. In situ metabolite MS imaging of normal mouse brain. C57BL/6N mouse brain was sagittally sectioned at 10 µm thickness with a cryostat and then thaw-mounted onto an ITO-coated glass slide. MS imaging data were acquired in negative ionization mode with 50 µm spatial resolution (8000 × 6000 µm, 10 shots/data point). A broad range of metabolites including (A) nucleotide derivatives, (B) redox-related metabolites, (C) lipids, and (D) central pathway metabolites were simultaneously visualized in a single MS imaging experiment. (E) Schematic illustration of the region of sagittally sectioned mouse brain. Scale bar ) 1.0 mm.

striatum (CPu) region after 3 h reperfusion, followed by massive accumulation at the infarct CTX and CPu at 24 h reperfusion. These observations correlated well with results of whole CTX extract (Figure 4C). Generally, ischemia is known to cause a depletion of glucose and oxygen in brain. In this study, a decline of glycolytic intermediates such as glucose-6-phosphate was observed after 1 h MCAO. Furthermore, in the contralateral hemisphere, dynamic temporal changes of glucose-6-phosphate and fructose-1-6-bisphosphate were induced by reperfusion. These changes in glycolysis may lead to a modification of the tricarboxylic acid (TCA) cycle. Functioning mitochondria depend on intact mitochondrial membrane, TCA enzymes, and respiratory chain proteins, all of which are vulnerable to ischemia attack. Ischemia has been reported to inactivate mitochondrial enzymes such as aconitase and 2-oxoglutarate dehydrogenase.24,25 In (24) Cantu, D.; Schaack, J.; Patel, M. PLoS One 2009, 4, e7095. (25) Tretter, L.; Adam-Vizi, V. J. Neurosci. 2000, 20, 8972–8979.

addition to the inhibition of such enzymes, the elevation of enzyme activity of citrate synthase was not observed upon treatment with ischemia reperfusion (Figure S3, Supporting Information). Therefore, the accumulation of citrate and the reduction of N-acetylaspartate, glutamate, and asparate at 24 h of reperfusion may be due to the arrest of the TCA cycle at the citrate position and the subsequent reduction of entry into the biosynthesis pathway of aspartate, N-acetylaspartate, and glutamate. Taken together, these findings indicate the usefulness of the present MALDI-MS technique for understanding spatiotemporal behavior of metabolites in brain tissue. Furthermore, the present result is the first report of metabolomic imaging capable of tracing spatiotemporal metabolic dynamics. The data clearly demonstrated that specific metabolites, even existing at neighboring positions in metabolic pathway, have quite different distributions in the tissue section. Metabolite imaging of central metabolic pathway in the MCAO Analytical Chemistry, Vol. 82, No. 23, December 1, 2010

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Figure 3. Visualization of the cerebral infract region of an ischemia-reperfusion rat model by in situ metabolite imaging. (A) Two millimeter thick sections were obtained using a brain slicer and stained with triphenyltetrazolium chloride (TTC). The rat brains were from (i) control or were acquired at (ii) 0 h, (iii) 3 h, and (iv) 24 h of reperfusion (Rep.) following 1 h of MCAO (Isc.). (B) MS imaging of the spatial distribution of m/z ) 174.04 in MCAO rat brain. (C) Comparison of averaged mass spectra in selected cerebral cortex (CTX) areas, after 24 h reperfusion in the b (i) ischemic and b (ii) contralateral hemisphere. (D) Identification of MS peak of m/z ) 174.04 as N-acetylaspartate by comparing MS/MS data. The MS/MS spectrum of N-acetylaspartate was acquired from the tissue sample (a) and standard sample (b). (E) A schematic illustration represents the structure of a coronally sectioned brain. Con. indicates contralateral hemisphere.

rat brain showed a good correlation with previously reported results of tissue extract analysis and magnetic resonance spectroscopy.26,27 To note, drastic changes in the distributions of glycolytic intermediates and accumulation of citrate in the ischemic hemisphere are newly observed findings. Previously, Benabdellah et al. reported that the imaging result of 13 metabolites in the normal rat brain, although almost all were nucleotide derivatives, was observed by the MSI experiment using 9-AA as a matrix. The results shown here, with extension (26) Lei, H.; Berthet, C.; Hirt, L.; Gruetter, R. J. Cereb. Blood Flow Metab. 2009, 29, 811–819. (27) Demougeot, C.; Marie, C.; Giroud, M.; Beley, A. J. Neurochem. 2004, 90, 776–783.

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of the coverage of molecular species from the report of Benabdellah et al. and simultaneous visualization of spatiotemporal distribution of several metabolites, may provide a new insight into the understanding of metabolic dynamics. In addition, the present MSI technique was able to sensitively detect the decline of N-acetylaspartate (Figure 3B), whose level correlates with neuronal health or integrity in the brain,20 even at an early stage (3 h) of infarct formation, although TTC histological staining and LC-MS-based metabolite analysis of CTX extracts could not detect the difference between the contralateral and ischemic CTX (Figures 3A and 4C). Thus, this MSI technique may be useful to facilitate the molecular

Figure 4. In situ metabolic pathway imaging visualizes drastic changes of spatiotemporal metabolite distribution in MCAO rat brain. Wistar rat brains of control (no operation) or from rats after various periods of reperfusion following 1 h of MCAO were extirpated and immediately frozen under -80 °C. Coronally sectioned brain slices (10 µm thickness) were then used for in situ metabolite imaging. Mass imaging data were acquired in negative ionization mode with 50 µm spatial resolution (14 000 µm × 11 000 µm, 10 shots/data point). All imaging data were normalized with the average mass spectrum for quantitative comparison of the concentration of each metabolite at different times. (a) These data were put on the central metabolic pathway map. (b) A schematic illustration represents the structure of coronally sectioned brain. (c) Relative changes in concetrations of metabolites extracted from whole CTX. Data is shown as the mean ( SD (n ) 5) and represents the relative concentration of each condition to the concentration of contralateral CTX in control (Con.). Asterisk mark indicates significant differences (P < 0.05) between contralateral (open bar) and ischemic (closed bar) CTXs. Analytical Chemistry, Vol. 82, No. 23, December 1, 2010

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understanding of pathogenesis at an earlier phase on the basis of spatiotemporal metabolic dynamics. Multivariate statistical analysis is known to be able to clarify the potential relationship among various samples on the basis of their specific metabolite profile data. For elucidating metabolite variance in an arbitrary microregion on tissue sections under different conditions (Figure S4A, Supporting Information), we performed principal component analysis (PCA), an unsupervised multivariate analysis, for holistic evaluation of each metabolic state by two-dimensional clustering. The result of PCA score plot demonstrated that independent clusters were clearly formed among four select microregions (Figure S4B, Supporting Information). This result indicates clear differences of metabolite pattern between the CTX and CPu or ischemic and contralateral hemispheres. Furthermore, orthogonal partial least-squares-discriminant analysis (OPLS-DA), a supervised multivariate analysis, was applied to pick up metabolites varied in an arbitrary microregion of CPu on different tissue sections, ischemic and contralateral hemispheres (Figure S4C-E, Supporting Information). This analysis allowed us to easily pick up metabolite accumulated or decreased in an arbitrary microregion even at an early stage (3 h) of infarct formation, indicating that this approach may have promising potential for the discovery of more sensitive and reliable biomarkers with high-spatial resolution. In the future, a combination of our proposed in situ multiple molecular imaging technique with other analytical platforms such as multivariate statistical analysis and in vivo noninvasive imaging techniques such as anatomic imaging, including MRI and computed tomography, or functional imaging, including functional MRI and PET, may

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become compulsory technology for the unraveling and understanding the molecular complexities of local tissues or for in situ pharmacometabolomics, biomarker discovery, early diagnosis, and cytodiagnosis. ACKNOWLEDGMENT This research was supported by the Science and Technology Incubation Program in Advanced Region from the funding program “Creation of Innovation Centers for Advanced Interdisciplinary Research Areas” from Japan Science and Technology Agency, commissioned by the Ministry of Education, Culture, Sports, Science, and Technology. We would like to specially thank Shimadzu Co. Ltd. (Kyoto, Japan) for their full cooperation. We also thank Mr. Takeshi Shiba for his technical assistance. SUPPORTING INFORMATION AVAILABLE Overview of the averaged mass spectrum acquired from the direct analysis of mouse brain section; analytical reproducibility of in situ metabolite MSI; temporal changes of citrate synthase activity in the ischemic and contralateral hemispheres of the cerebral cortex of the MCAO rat brain; multivariate analysis of in situ tissue mass spectra for discovering unique metabolites accumulated or reduced in a region-specific manner; and general methods. This material is available free of charge via the Internet at http://pubs.acs.org. Received for review July 28, 2010. Accepted October 18, 2010. AC101998Z