Comprehensive Imaging of Porcine Adrenal Gland Lipids by MALDI

University of Victoria - Genome British Columbia Proteomics Centre, ... Lipids such as sphingolipids have been shown to control the steroid ..... Tabl...
0 downloads 0 Views 657KB Size
Download PDF
Article pubs.acs.org/ac

Comprehensive Imaging of Porcine Adrenal Gland Lipids by MALDI-FTMS Using Quercetin as a Matrix Xiaodong Wang,† Jun Han,† Jingxi Pan,† and Christoph H. Borchers*,†,‡ †

University of Victoria - Genome British Columbia Proteomics Centre, Vancouver Island Technology Park, #3101-4464 Markham St., Victoria, BC V8Z 7X8, Canada ‡ Department of Biochemistry and Microbiology, University of Victoria, Petch Building Room 207, 3800 Finnerty Rd., Victoria, BC V8P 5C2, Canada S Supporting Information *

ABSTRACT: Adrenal glands synthesize and release functional zone-specific steroid and catecholamine hormones to regulate mammalian stress responses. Lipids such as sphingolipids have been shown to control the steroid hormone biosynthesis in adrenal glands, indicating their important roles in endocrine organs. Molecular imaging by matrix-assisted laser desorption/ ionization mass spectrometry (MALDI-MS) is a well-established analytical technique for determining both the spatial location and the relative abundances of various lipids on tissue. To better understand the overall roles of different lipid classes that play in the mammalian adrenal glands, it is necessary to comprehensively determine the spatial distributions of various lipids in the different functional zones of adrenal glands. However, the potential of this technique has not been fully reached, considering there are thousands of lipid species in a cell or tissue. To achieve this, we used quercetin as a MALDI matrix for negative ion detection of endogenous lipids on tissue sections of porcine adrenal glands by MALDIFourier-transform ion cyclotron resonance (FTICR) MS. As a result of these experiments, 409 endogenous compounds were detected in the negative ion mode. Combining both the positive and negative ion detection led to successful determination of the spatial distribution patterns of 555 unique endogenous compounds that were identified as 544 lipid entities and 11 nonlipid metabolites. Many classes of these lipids showed distinct distribution patterns in different functional zones of the adrenal gland. To the best of our knowledge, this work presents the largest group of lipid entities that have been analyzed in a single MS imaging study so far, and comprehensive profiles of the spatial distributions of lipids in porcine adrenal glands are shown here for the first time.

L

and it is subdivided into three distinct functional zones or layers, each with a characteristic steroidogenesis profile. The zona glomerulosa is the outer cortical region where the mineralocorticoid aldosterone is produced. The middle zone, the zona fasciculata, is the region where glucocorticoids such as 11-deoxycorticosterone, corticosterone, and cortisol in humans, are synthesized. The inner zone, zona reticularis, is the site of androgen biosynthesis. Each of the three cortical zones expresses a unique profile of steroidogenic genes, thereby enabling zone-specific cholesterol metabolism. The mechanisms that regulate and limit the expression of the key steroidogenic enzymes to specific zones of the adrenal cortex involve transcription factors, repressors, specific kinases, and/or phosphatases that are specific to each zone.6 Lipid such as sphingolipids have been identified as modulators of the steroidogenesis in human adrenal cortex via adrenocorticotrophin (ACTH)-activated cAMP/cAMP-dependent kinase (PKA) signaling pathway.7,8 To further decipher the biological

ipids are not only the essential constituents of biological membranes but also the important bioactive molecules that play multiple roles in biological processes such as energy storage, signal transduction, cell adhesion and migration, metabolism, homeostasis, and cell apoptosis.1 The alteration of lipid expression in vivo is often associated with disease.2,3 Lipidomics (i.e., the system level analysis of lipids) is a potentially valuable tool for biomarker discovery.4 Mammalian adrenal glands are the endocrine organs located on the top of kidneys. The main function of adrenal glands is the regulation of stress responses through the synthesis, storage, and delivery of steroid and catecholamine hormones.5 Anatomically, an adrenal gland consists of the peripheral adrenal capsule, the middle adrenal cortex, and the inner adrenal medulla. The capsule is a layer of connective tissue, encapsulating the adrenal gland and providing protection, attachment, and signal transduction. The medulla, the innermost part of the adrenal glands, consists of neuroendocrine cells (i.e., the well-known “chromaffin” cells), which synthesize catecholamines, including adrenaline and noradrenaline. The adrenal cortex is the site of adrenal steroid hormone biosynthesis, © 2013 American Chemical Society

Received: September 14, 2013 Accepted: December 16, 2013 Published: December 16, 2013 638

dx.doi.org/10.1021/ac404044k | Anal. Chem. 2014, 86, 638−646

Analytical Chemistry

Article

thick tissue slices in a Microm HM500 cryostat (Waldorf, Germany) which was operated at −20 °C. The sectioned tissue slices were thaw-mounted on ITO-coated microscopic glass slides obtained from Bruker Daltonics (Bremen, Germany). Hematoxylin and eosin (H&E) staining was performed to obtain standard histological optical images.33 Matrix Coating. MALDI matrices were coated with a Bruker Daltonics ImagePrep electronic matrix sprayer (Bremen, Germany), as described previously.30 Briefly, quercetin was prepared at a concentration of 2.6 mg/mL in 80:20 methanol:water, both containing 0.1% NH4OH. DHA was dissolved at a concentration of 20 mg/mL in 50:50 ethanol:water, both containing 0.05% formic acid. 2-MBT was prepared at a concentration of 20 mg/mL in 80:20 methanol:water, both containing 0.1% TFA. 9-AA was prepared at 20 mg/mL in 70:30 ethanol:water. After a short-time centrifugation (14000 rpm, 5 min), the saturated supernatant was collected and used as the matrix solution.14 The matrix coatings for each of the matrices were composed of a 3 s spray, a 60 s incubation, and a 90 s drying per spray cycle, and up to thirty cycles were applied to the tissue. The optical images of the tissue sections were captured on an Epson Perfection 4490 Photo Scanner, and saved as “tif” files. MALDI-MS. All MS data were recorded on an Apex-Qe 12T hybrid quadrupole-FTICR mass spectrometer (Bruker Daltonics, Billerica, MA). The instrument was equipped with an Apollo dual-mode electrospray ionization (ESI)/MALDI ion source, with a 355 nm and 200 Hz solid-state Smartbeam Nd:YAG UV laser (Azura Laser AG, Berlin, Germany). Mass spectra were acquired over the mass range from 150 to 2000 Da in both the positive and negative ion modes, with broadband detection and a data acquisition size of 1024 kilobytes per second. The diluted “ESI tuning mix” solution was prepared in 60:40 isopropyl alcohol:water, both containing 0.1% formic acid. During MALDI-MS data acquisitions, a 1:200 dilution of “ESI tuning mix” was infused from the ESI side of the ion source at a flow rate of 2 μL/min, so that each MALDI mass spectrum contained the reference mass peaks for internal mass calibration. For MALDI-MS profiling, the mass spectra were recorded by accumulating ten scans at 100 laser shots per scan. For the acquisition of imaging data, a 200 μm laser raster step size (the minimum possible for the laser source) was used, and 100 laser shots were summed per array position (i.e., per pixel). Data Analysis. MALDI tissue profiling data were viewed and processed using Bruker DataAnalysis 4.0. For batch internal mass calibration, peak deisotoping, monoisotopic “peak picking”, and peak alignment, a customized VBA script was used as described elsewhere.34 Two metabolome databases, METLIN35 and LIPID MAPS,36,37 were used for matching the measured m/z values to possible metabolite entities, within an allowable mass error of ±1 ppm. The [M + H]+, [M + Na]+, and [M + K]+ ion forms were allowed during database searching in the positive-ion mode; the [M − H]− and [M + Cl]− ion forms were allowed during database searching in the negative-ion mode data processing. The Bruker FlexImaging 2.1 was used to reconstruct the ion maps of the detected lipids. The mass filter width was set as 1 ppm for ion image generation within FlexImaging. Lipid Extraction and LC−MS/MS. A method, slightly modified from a previously described protocol,30 was introduced in this study for extraction of the total lipids from porcine adrenal glands. The details of the lipid extraction and LC−MS/MS method for compound identification and

roles and the localized metabolism of various lipids in adrenal gland pathophysiology, knowledge of the spatial distributions of various lipids in the different functional zones are important but are still largely unknown. A tissue imaging study using desorption electrospray ionization-mass spectrometry (DESI) has already been performed on porcine adrenal gland tissue, but only the spatial distributions of epinephrine, norepinephrine, and a few phospholipids were determined.9 Tissue imaging by matrixassisted laser desorption/ionization (MALDI)-MS is now a well-established technique for lipidomics and is of growing interest for simultaneously determining both the spatial localization and the relative abundances of a large number of various lipid species, determined by direct analysis of the surface of a sliced tissue section.10−13 Due to the continuing efforts in the screening and discovery of new MALDI matrices that are suitable for MS imaging, several dozen to about one hundred lipid compounds have been profiled in rat brain,10,14−19 rat liver,15,20 bovine lens,20,21 mouse uterus,22 the whole body of Xiphosphorus maculatus fish,18 and mouse pups23 in a single MS imaging experiment. MALDI matrices that have been employed for lipidomic tissue imaging include 4-para-nitroaniline (pNA),21,24 2,5-dihydroxyacetophenone (DHA),11,25−27 9-aminoacridine (9-AA),14 1,5-diaminonapthalene (DAN),18 2,5-dihydroxybenzoic acid (DHB),28 2-mercaptobenzothiazole (2-MBT),15 dithranol (DT),20 and curcumin.29 Recently, we introduced a family of hydroxyflavone compounds, which have been found to be useful MALDI matrices for the tissue imaging of up to 212 lipids in rat brain by Fourier-transform ion cyclotron resonance (FTICR) MS in the positive ion mode.30 Even with these advancements, however, the potential of MALDI-MS for lipidomic tissue imaging is still far from being fully reached, considering there are thousands of lipids existing in a cell or tissue.31,32 To determine a more comprehensive profile of the lipid spatial distributions in the adrenal glands, we used quercetin, a pentahydroxyflavone MALDI matrix, for both positive and negative ion detection, and an ultrahigh resolution FTICR-MS instrument to perform tissue imaging of porcine adrenal glands. In this study, the spatial distribution patterns of 544 unique lipids and several other endogenous compounds in the different functional zones of porcine adrenal glands were successfully determined.

■

EXPERIMENTAL SECTION Materials and Reagents. AR-grade matrices including quercetin, DHA, 9-AA, and 2-MBT were purchased from Sigma-Aldrich (St. Louris, MO). LC−MS-grade methanol, ethanol, isopropyl alcohol, acetonitrile, formic acid, trifluoroacetic acid (TFA), and ammonia hydroxide (NH4OH) were purchased from Sigma-Aldrich (St. Louis, MO). The “ESI tuning mix” standard solution was obtained from Agilent Technologies (Santa Clara, CA) for tuning and calibration of the FTICR instrument. Porcine adrenal glands were purchased from Pel-Freez Biologicals (Rogers, AR). In accordance with the accompanying sample information sheet, the porcine adrenal glands had been dissected from chloralose-anesthetized pigs, and after harvesting, they were flash-frozen by slow immersion in liquid nitrogen to avoid shattering. The use of the animal organs involved in this study was approved by the Ethics Committee of the University of Victoria. Tissue Sectioning and Histological Staining. The frozen porcine adrenal glands were cryosectioned into 12 μm 639

dx.doi.org/10.1021/ac404044k | Anal. Chem. 2014, 86, 638−646

Analytical Chemistry

Article

Figure 1. Comparison of lipids detected by FTICR MS using quercetin as the MALDI matrix. (A) MALDI mass spectra acquired from a porcine adrenal gland tissue section in both positive (red) and negative (blue) ion modes. The matrix-related signals are labeled ⧫. (B) Venn diagram showing the detection of lipids and their classification in both positive (red) and negative (blue) ion modes. The lipid classes mainly detected in the positive-ion mode are labeled with red asterisks; the lipid classes mainly detected in the negative-ion mode are labeled with blue asterisks, and the lipid classes detected by quercetin without a noticeable difference in the number of species detected in the positive and negative ion modes are labeled with white triangles.

(80:20:0.1%) solvent]30 was also found to be optimal for negative-ion detection of low molecular weight compounds in adrenal glands. Figure 1A shows two MALDI-FTICR mass spectra acquired in the positive and negative ion modes, respectively. Compounds detected in the positive ion mode were mainly observed in a relatively narrow mass range from m/z 300 to 900, while the compounds detected in the negative ion mode were observed over a broader mass range, from m/z 150 to 1600. In several studies, the identification of some of the imaged molecular species was done by in situ MALDI-MS/MS using collision-induced dissociation (CID).10,14,38 However, due to the relatively low sensitivity of MALDI-CID on the FTICR instrument used in this study,20,30 structural confirmation of

structural confirmation are described in the Supporting Information.

■

RESULTS AND DISCUSSION Lipid Detection by Positive and Negative ion MALDIFTICR MS. In this work, we used quercetin as the MALDI matrix for negative ion MALDI-MS detection of endogenous compounds in the porcine adrenal glands and combined both positive and negative ion detection on the 12-T ultrahigh resolution FTICR instrument for comprehensive characterization of the spatial distributions of these compounds on the surfaces of thinly cut porcine adrenal gland tissue sections. The matrix solution previously optimized for the positive ion mode [2.6 mg/mL of quercetin prepared in a methanol−water−NH4OH 640

dx.doi.org/10.1021/ac404044k | Anal. Chem. 2014, 86, 638−646

Analytical Chemistry

Article

chlorinated CL(18:2/18:2/18:1/18:1), and that this peak does not originate only from the M+2 isotope of [CL(18:2/18:2/ 18:2/18:1)+Cl]−. The majority of phospholipids that were detected in the negative ion mode had phosphoryl groups in their structures.10,11,14,22,40 Phosphatidylethanolamines (PEs) were detectable in both ion modes due to the amphoteric nature of their structures.10,11,14,18,22,30,39−41 Phosphatidic acids (PAs), which were previously thought to be detectable only in the negative ion mode due to their acidic nature,10,14 could be also detected in the positive ion mode as Na or K adduct ions using the quercetin matrix. This observation was consistent with our previous study.30 As shown in Figure 1B, there were 82 lipids detected in both ion modes. These lipids included 11 PCs, 21 PEs, 27 PAs, 1 PS, 3 PIs, 2 CLs, 4 cyclic phosphatidic acids (cPAs), 1 SM, 2 Cers, 1 monoacylglycerol (MAG), 3 diacylglycerols (DAGs), and 6 FAs. For most of the individual lipids, similar distribution patterns were observed in the ion maps of their different ion forms in both the positive and negative ion modes. Figure S3B of the Supporting Information shows the paired ion maps for 3 representative phospholipids, detected as [M + K]+ and [M − H]−. The 146 lipid entities that were uniquely detected in the positive ion mode included 58 PCs, 16 PEs, 17 PAs, 1 PG, 2 PSs, 1 Cer, 13 SMs, 3 n-GSLs, 5 MAGs, 24 DAGs, 3 triacylglycerols (TAGs), 1 FA, and 2 members of other lipid classes. In contrast, there were a total of 316 lipid entities that were uniquely detected in the negative ion mode, and these compounds were 2 PCs, 31 PEs, 11 PAs, 17 PGs, 29 PSs, 52 PIs, 10 PIPs, 14 PIP2s, 1 PIP3, 32 CLs, 9 CDPDGs, 1 GP, 2 Cers, 1 PE-Cer, 13 PI-Cers, 32 n-GSLs, 24 a-GSLs, 10 gangliosides, 1 glycosyldiradylglycerol, 3 DAGs, 3 TAGs, 9 sterol lipids, and 9 FAs. Ion maps for these compounds were generated. Some lipids were detected in different ion forms, such as [M + H]+, [M + Na]+, and/or [M + K]+ in the positive ion mode and [M − H]− and [M + Cl]− in the negative ion mode. For the majority of the individual lipids, these ion forms showed similar distribution patterns. However, some lipid species showed inconsistent distribution patterns among the observed adduction forms, as shown in Figure S3C of the Supporting Information. This phenomenon has been reported before10,42 and may be explained by the combined effects of the differential laser penetration depth, and different ionization efficiencies for individual adducts within the molecular microenvironment on the tissue sections during the MALDI process. In accordance with the numbers of detected lipids in each ion mode, the negative ion mode surpassed the positive ion mode for lipid detection when quercetin was used as the matrix. This result also indicates that the two ion detection modes are complementary and both are necessary to comprehensively characterize the lipid profiles in situ. Taking both positive and negative ion modes into consideration, there were a total of 544 lipid entities in 21 categories that were successfully detected in the porcine adrenal gland tissue sections. To the best of our knowledge, this is the largest group of lipids that has been identified and imaged so far in a single MALDI-MS tissue imaging study. This experiment also indicated that quercetin was a highly effective MALDI matrix suitable for MS imaging in the negative ion mode. Comparison of Quercetin and Other Matrices for Negative Ion Detection. Two commonly used MALDI matrices for negative ion MS tissue imaging, 2-MBT15 and 9AA,14 were compared with quercetin for in situ detection of lipids. As shown in Figure S4 of the Supporting Information, the signals of many low-abundance lipids were significantly enhanced

many of the imaged compounds in the adrenal gland tissue sections was performed by LC−MS/MS analysis of the lipid extracts. Other compounds were identified by querying the literature, and the metabolome databases using measured accurate masses of the MALDI-FTMS. As a result, 409 endogenous compounds were successfully identified from the mass spectra acquired in the negative ion mode. Of these compounds, 398 were assigned as lipid entities and 11 were assigned as nonlipid metabolites. In the positive ion mode, 228 lipid entities were successfully identified from the mass spectra acquired. There were 82 entities detected in both modes. Of the identified compounds, 78 compounds were assigned by querying the literature, 35 compounds were identified by LC−(+)ESI-MS/MS, 53 compounds were identified by LC−(−)ESI-MS/MS, and the remaining compounds were assigned by a metabolome database search using the measured accurate masses. Of the 83 compounds identified by LC−MS/ MS with (+) and (−) ESI, 78 were assigned by searching the METLIN or LIPID MAPS MS/MS libraries and the remaining 5 compounds were identified by manual mass spectral interpretation, as described in the Supporting Information. It should be mentioned that there could be potential ambiguities in assigning the molecular species in the MALDI images based on the LC−MS/MS analysis of the tissue extracts, since identical elemental compositions could result from different lipid molecular species which might or might not correlate with the observed peaks in the MALDI images. Tables S1 and S2 of the Supporting Information list those compounds assigned in this work. For compounds assigned on the basis of the metabolome database search only, when more than one candidate was matched, the identities are reported as one of these candidates “or its isomers”. The lipids that were detected mainly in the positive ion mode were in the phosphatidylcholine (PC) and sphingomyelin (SM) classes and have positively charged quaternary amine groups in their structures.10,39 The lipids in the phosphatidylglycerol (PG), phosphatidylserine (PS), phosphatidylinositol (PI), phosphatidylinositol phosphate (PIP), phosphatidylinositol bisphosphate (PIP2), phosphatidylinositol triphosphate (PIP3), cardiolipin (CL), CDP-diacylglycerol (CDP-DG), glycerophosphate (GP), ceramide PE (PE-Cer), ceramide PI (PI-Cer), neutral glycosphingolipid (n-GSL), acidic glycosphingolipid (a-GSL), ganglioside, glycosyldiradylglycerol, sterol, and fatty acyl (FA) classes were shown to be preferentially detected by negative-ion MALDIMS. As shown in Table S2 of the Supporting Information, many chlorinated ions were observed for some lipids such as PCs, PAs, and CLs in the negative ion mode, when quercetin was used. The reason for this is not well-understood. Figure S1 of the Supporting Information shows the detection and LC−MS/MS of chlorinated PC(38:4). In Figure S2 of the Supporting Information, three chlorinated CLs were assigned in the mass range from m/z 1485 to 1493. The mass resolution in this region under the described FTICR operation conditions was approximately 25000 fwhm, which is not enough to differentiate between the M + 2 isotopic peak of [CL(18:2/18:2/18:2/18:1) + Cl]− and the monoisotopic (M) peak of [CL(18:2/18:2/18:1/18:1) + Cl]−. A mass resolution of ∼127600 fwhm would be required to achieve the baseline separation of these two peaks, which is beyond the achievable mass resolution on the FTICR instrument used. However, a comparison of the theoretical and experimental isotopic distribution patterns of the chlorinated CL(18:2/18:2/ 18:2/18:1), in Figure S2 of the Supporting Information, indicates that the peak at m/z 1487.9727 was correctly assigned as the 641

dx.doi.org/10.1021/ac404044k | Anal. Chem. 2014, 86, 638−646

Analytical Chemistry

Article

Figure 2. Optical images of a sagittal porcine adrenal gland section and the ion maps of two detected phospholipids. (A) H&E stained images of a porcine adrenal gland tissue section. (B) Comparison of the positive-ion MALDI images of m/z 804.551 [PC(36:4) + Na]+ using quercetin and 2MBT as the matrices, respectively. (C) Comparison of the negative-ion MALDI images of m/z 901.497 [PI(40:10) − H]− using quercetin and DHA as the matrices, respectively. (D and E) Comparison of the negative-ion MALDI images for m/z 810.527 [PS(38:4) − H]− and m/z 1185.734 [CL(1′-[18:2/18:2],3′-[18:2/0:0])-H]− using quercetin and 9-AA as the matrices, respectively.

contrast, quercetin showed high stability under the same vacuum conditions, and DHA showed high volatility under the high-vacuum MALDI source condition, which was consistent with several previous studies,11,15,28 although it was reported that inclusion of ammonium sulfate and HFBA in the matrix solution for coating DHA onto tissue sections has been shown to be an efficient method for enhancing lipid detection on a MALDI-TOF/TOF instrument.25 Figure 2 (panels D and E) show a comparison of the negative-ion MALDI images of m/z 810.527 [PS(38:4) − H]− and m/z 1185.734 [CL(1′-[18:2/ 18:2],3′-[18:2/0:0])-H]− using quercetin and 9-AA as the matrices, respectively. The intensities of these two lipids detected by quercetin are significantly stronger than those detected by 9-AA. Lipid Distributions in Different Layers of Porcine Adrenal Gland. Figure 3A shows bar graphs of the identified and imaged 544 lipid species in the different functional zones of the porcine adrenal glands tested in this study, with 283, 320, 229, 101, and 531 lipids being detected in the capsule, zona glomerulosa, zona fasciculate, zona reticularis, and medulla regions, respectively. The medulla was the region of the porcine adrenal glands where the highest number of lipids were detected, followed by the outer cortex layer while Zona reticularis (i.e., the inner cortex region) had the smallest number of lipids detected. An interesting observation is that unsaturated lipids formed a larger group than the saturated lipids in all of the layers, particularly in the zona reticularis. The ratio of the number of detected unsaturated lipid species to saturated lipids in the zona reticularis is 15.8, while this ratio ranged from 5.9 to 7.3 in other layers. Glycerophospholipids. Glycerophospholipids are the major components of cellular membranes and are typically asymmetrically distributed across the membrane bilayer.47 As shown in Figure S5 of the Supporting Information, glycerophospholipids were the most numerous class of lipids that were detected in the porcine adrenal gland tissue sections, accounting for 372 of the identified 544 lipid species. Other classes of lipids were as

by the use of quercetin, by a factor of 2 to 5 on average. This enhanced sensitivity led to an increase in the total number of lipid entities that could be detected and mapped: 117 and 97 lipid entities were identified by the use of 2-MBT and 9-AA, respectively, which are significantly less than the 398 lipid entities that were detected with the quercetin matrix. In addition, quercetin gave higher sensitivities in the mass range above m/z 1100. In this on-tissue detection experiment, many lipids, including CLs, gangliosides, GSLs, and CDP-DGs, were more easily detectable by the use of quercetin. Some of these CLs were also detected from the lipid extracts of mouse heart in a previous MALDI-MS study with 9-AA as the matrix,43 but a higher number of CLs were observed during the imaging experiment when quercetin was used as the matrix. In addition, quercetin only showed one matrix-related ion (at m/z 301.0343, the [M − H]−), while many matrix-related matrix ions were observed for 2-MBT and 9-AA. Figure 2A shows an H&E-stained porcine adrenal gland tissue section, where different layers of the porcine adrenal glands, as previously reported,44−46 can clearly be seen in the tissue (tissue size ca. 1 × 1.7 cm). The ion map of PC (36:4), detected as the adduct ion, [M + Na]+, shows its distribution patterns in these different functional zones (Figure 2B). As shown in Figure 2B, the use of quercetin resulted in a better indication of the spatial distribution of this lipid in the five layers of the adrenal gland tissue section than when 2-MBT was used. The smaller particle size of quercetin (ca. 5 μm) compared with a larger crystal size of 2-MBT (up to 200 μm) and the higher ionization efficiency with the use of quercetin may also explain this phenomenon.30 Figure 2C compares the distributions of PI(40:10), detected as [M − H]−, with the use of quercetin and DHA, respectively. As shown in this figure, the use of DHA results in the fidelity of the distribution pattern of this lipid being lost because of matrix sublimation inside the MALDI source under the high vacuum source condition (10−7 mbar) of the FTICR instrument. In 642

dx.doi.org/10.1021/ac404044k | Anal. Chem. 2014, 86, 638−646

Analytical Chemistry

Article

Figure 3. Graphical display of the distribution of detectable lipids in different functional zones of porcine adrenal gland. (A) Distribution of total lipids detected in different layers of porcine adrenal gland. (B−F) Bar graphs showing the different distributions of glycerophospholipids, sphingolipids, neutral lipids, fatty acids, and other lipids in different layers of porcine adrenal gland. The symbol of “+” in parentheses shows the number of lipids detected in the positive ion mode, while “−” shows the number of lipids detected in the negative ion mode.

Figure 4 shows many specific distribution patterns for PCs, PEs, PAs, and cPAs in the porcine adrenal glands. As shown in Figure 4 (panels A and B), the saturated lipids of the PC and PE classes were detected mainly in the medulla of the adrenal glands, while many unsaturated PC and PE lipids were mainly detected in the outer layers (such as cortex and/or capsule). This distribution pattern could also be found for many PAs (Figure 4C). Additionally, as listed in Figure 4D and Figure S6H of the Supporting Information, cPAs were found only in the capsule, zona fasciculate, and medulla but not in the cortex regions of zona glomerulosa and zona reticularis. Figure 4E shows the MS/MS spectra of m/z 500.28 [PE(20:4) − H]− and m/z 701.51 [PA(18:0/18:1) − H]−, which were used to confirm the identities of these lipids. The tabulated MS/MS spectra of many other identified lipids are given in Tables S1 and S2 of the Supporting Information. Sphingolipids. In comparison to glycerophospholipids, sphingolipids have been less investigated using MALDI imaging. Our results indicated that 102 sphingolipid species were detected in either the positive or the negative ion mode (Figure S5 of the Supporting Information). The layers of the medulla (93 lipid entities) and zona glomerulosa (80 lipid entities) were the tissue regions where the most sphingolipids were detected, followed by the capsule (38 lipid entities), the zona fasciculate (29 lipid entities), and the zona reticularis (13 lipid entities), as shown in Figure 3C. Cers and SMs were detected in all five layers of the porcine adrenal glands

follows: 102 sphingolipids, 52 neutral lipids, 16 FAs, and 2 other lipids. Among the 372 glycerophospholipids, 182, 224, 165, 86, and 373 were detected in the capsule, zona glomerulosa, zona fasciculate, zona reticularis, and medulla layers, respectively (Figure 3B). As shown in Figure S6 (panels A−J) of the Supporting Information, PCs and PSs were mainly found in the medulla, compared to the other layers. In Figure S6 (panels D, F, and G) of the Supporting Information, the medulla and the zona glomerulosa were the main regions where PGs, PIs, and their phosphorylated analogues (PIP, PIP2, and PIP3) and CLs were detected. PEs and PAs were detected in each layer, and these two lipid classes showed distribution patterns similar to PCs. The medulla layer was the richest area for PE and PA distributions, but the difference between the medulla and other layers was less significant than for other classes of glycerophospholipids, except for CDP-DG. CDP-DG is a low-abundance class of the lipids that have been regarded as important branchpoint intermediates in phospholipid (PG, PI, and CL) biosynthesis, and these are the key regulatory molecules in phospholipid metabolism.10,48,49 In this study, CDP-DGs were detected mainly in the zona glomerulosa, zona fasciculate, and medulla layers of the porcine adrenal glands, as shown in Figures S6I and S7 of the Supporting Information. This class of lipids showed a similar distribution pattern to those of PGs, CLs, PIs, and their phosphorylated analogues (Figure S6, panels D, F, and G, of the Supporting Information). 643

dx.doi.org/10.1021/ac404044k | Anal. Chem. 2014, 86, 638−646

Analytical Chemistry

Article

Figure 4. Comparison of specific distribution patterns of selected (A) PCs, (B) PEs, (C) PAs, and (D) cPAs with positive and negative ion detection from a transverse porcine adrenal gland section. (E) Collision-induced dissociation mass spectra of m/z 500.28 [M − H]− and m/z 701.51 [M − H]− by LC−MS/MS. These two lipids were identified as PE(20:4) and PA(18:0/18:1), respectively. They were detected as the [M − H]− ions by negative-ion MALDI-FTICR MS using quercetin as the matrix. The asymmetric C-atom of PE(20:4) and PA(18:0/18:1) are labeled with asterisks.

MAGs, 30 DAGs, 6 TAGs, 1 glycosyldiradylglycerols, and 9 sterol compounds, were successfully detected using quercetin in both ion modes (Figure 1B). As shown in Figure 3D and Figure S6, panels P and Q, of the Supporting Information, the capsule, zona fasciculate, and medulla layers of the porcine adrenal glands were the main regions for detectable glycerolipids. In contrast, sterol lipids were mainly detected in the medulla and zona glomerulosa layers, similar to several classes of glycerophospholipid and sphingolipid, such as PG, PI, CL, n-GSL, a-GSL, and ganglioside. Fatty Acyls and Other Imaged Compounds. In the literature, there are only a few reports of FA imaging by MALDI-MS.50,51 The use of quercetin led to 16 FA species being successfully detected and imaged from porcine adrenal gland tissue sections, as shown in Figure 1B and Figure S5 of the Supporting Information. Figure 3E shows that the capsule, zona fasciculate, and medulla layers were the major regions where more FA species were detected, indicating that these

(Figure S6, panels K and L, of the Supporting Information). SMs were detected mainly as positively charged ions, and the layers of capsule and medulla were the main regions where SMs were detected. Many lipid classes, including PE-Cers, PI-Cers, n-GSLs, a-GSLs, and gangliosides, were also observed in this study. Because of the high efficiency of lipid ionization using the quercetin matrix, these lipids were observed for the first time using the MALDI-FTICR imaging. The main regions where these sphingolipids were found were the medulla and zona glomerulosa layers, particularly for n-GSLs and a-GSLs (Figures S6, panels M−O, and S8 of the Supporting Information). All of these lipids were detectable only in the negative ion mode, expect for n-GSL. Only 1 to 3 n-GSL lipids were detected in the different layers of adrenal gland in the positive ion mode. Neutral Lipids. Glycerolipids and sterols are neutral lipids and are hydrophobic, uncharged, and apolar-to-slightly polar molecules. In this study, 52 neutral lipid species, including 6 644

dx.doi.org/10.1021/ac404044k | Anal. Chem. 2014, 86, 638−646

Analytical Chemistry

Article

Notes

layers of adrenal gland might be the relatively active areas of fatty acid metabolism 52 and lipid metabolism. 10 Two metabolites, phosphocholine and glycerophosphocholine, which are the substrates for biosynthesis of phospholipids were also imaged. As shown in Figure S9 of the Supporting Information, the observed phosphocholine and glycerophosphocholine signals were from in situ detection, not from in-source decay, when quercetin was used. These compounds are important substrates for lipid biosynthesis. These compounds were observed only in the layers of capsule, medulla, and zona fasciculate as their adduct ions of [M + Na]+ and/or [M + K]+. This observation also indicates that these layers may be the main sites for lipid biosynthesis inside the porcine adrenal glands. In addition, several other endogenous compounds such as acyl coenzyme As (the intermediates in the Kennedy pathway for phospholipid synthesis53 and sphingolipid synthesis54), adenosine monophosphate (AMP), adenosine diphosphate (ADP), fucose-monophosphate,55 D-glycero-D-manno-heptose7-phosphate,56 and 6-(isopropylthio) purine (a substrate for nucleic acid synthesis), and two substrates for synthesis of CLs [phosphatidyl glycerol57 and bis(glycerophospho)-glycerol58] were also detected in the negative ion mode. These compounds were mainly distributed in the medulla and zona glomerulosa layers of the porcine adrenal glands. The ion maps of these detected compounds are shown in Figure S10 of the Supporting Information. Among these metabolites, detection and imaging of AMP and ADP were also achieved by 9-AA, in a previous study.59

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS This work was supported by the Genome Canada-funded “The Metabolomics Innovation Centre (TMIC)” for metabolomics research and funding from Genome Canada and Genome British Columbia through the Science and Technology Innovation Centre (S&TIC) mechanism. The MALDI source on the FTICR MS instrument used in this study was purchased with funding from the Western Economic Diversification of Canada. We thank Dr. Carol E. Parker for helpful discussions and careful review of this manuscript.

■

■

CONCLUSION Quercetin was used as the MALDI matrix for detection and imaging of endogenous compounds in the porcine adrenal glands by FTICR MS, with both the positive and negative ion detection. A total of 544 unique lipid entities and 11 nonlipid compounds were successfully assigned, and their spatial distributions in the endocrine glands were determined, due to the high chemical stability, the micrometer size of matrix crystals, uniform matrix coating, and high-efficiency lipid ionization of the quercitin matrix. This work also demonstrated the necessity for combining a robust MALDI matrix, both positive and negative ion detection, and an ultrahigh resolution MS instrument for comprehensive lipid imaging by MALDI-MS. This work represents the first comprehensive determination of the lipid distributions in the different functional zones of the mammalian adrenal gland. To the best of our knowledge, the 544 lipid entities found constitute the largest group of lipids that have been imaged so far using MALDI tissue imaging techniques. The characteristic distribution patterns of the different lipids provide a useful clue in the investigation of the molecular mechanisms underlying these features, which may help to decipher the biological roles that these lipids play in the physiological and pathological function of the adrenal glands.

■

ASSOCIATED CONTENT

S Supporting Information *

Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org.

■

REFERENCES

(1) Shevchenko, A.; Simons, K. Nat. Rev. Mol. Cell Biol. 2010, 11, 593−598. (2) Herber, D. L.; Cao, W.; Nefedova, Y.; Novitskiy, S. V.; Nagaraj, S.; Tyurin, V. A.; Corzo, A.; Cho, H. I.; Celis, E.; Lennox, B.; Knight, S. C.; Padhya, T.; McCaffrey, T. V.; McCaffrey, J. C.; Antonia, S.; Fishman, M.; Ferris, R. L.; Kagan, V. E.; Gabrilovich, D. I. Nat. Med. 2010, 16, 880−886. (3) Di Paolo, G.; Kim, T. W. Nat. Rev. Neurosci. 2011, 12, 284−296. (4) Wenk, M. R. Nat. Rev. Drug Discovery 2005, 4, 594−610. (5) Wood, J. G. Am. J. Anat. 1963, 112, 285−303. (6) Lucki, N. C.; Sewer, M. B. Subcell. Biochem. 2008, 49, 387−412. (7) Ozbay, T.; Merrill, A. H., Jr.; Sewer, M. B. Endocrine Res. 2004, 30, 787−794. (8) Ozbay, T.; Rowan, A.; Leon, A.; Patel, P.; Sewer, M. B. Endocrinology 2006, 147, 1427−1437. (9) Wu, C.; Ifa, D. R.; Manicke, N. E.; Cooks, R. G. Analyst 2010, 135, 28−32. (10) Zemski Berry, K. A.; Hankin, J. A.; Barkley, R. M.; Spraggins, J. M.; Caprioli, R. M.; Murphy, R. C. Chem. Rev. 2011, 111, 6491−6512. (11) Jackson, S. N.; Wang, H. Y.; Woods, A. S. J. Am. Soc. Mass Spectrom. 2007, 18, 17−26. (12) Meding, S.; Walch, A. Methods Mol. Biol. 2013, 931, 537−546. (13) Gode, D.; Volmer, D. A. Analyst 2013, 138, 1289−1315. (14) Cerruti, C. D.; Benabdellah, F.; Laprevote, O.; Touboul, D.; Brunelle, A. Anal. Chem. 2012, 84, 2164−2171. (15) Astigarraga, E.; Barreda-Gomez, G.; Lombardero, L.; Fresnedo, O.; Castano, F.; Giralt, M. T.; Ochoa, B.; Rodriguez-Puertas, R.; Fernandez, J. A. Anal. Chem. 2008, 80, 9105−9114. (16) Shanta, S. R.; Choi, C. S.; Lee, J. H.; Shin, C. Y.; Kim, Y. J.; Kim, K. H.; Kim, K. P. J. Lipid Res. 2012, 53, 1823−1831. (17) Hankin, J. A.; Murphy, R. C. Anal. Chem. 2010, 82, 8476−8484. (18) Thomas, A.; Charbonneau, J. L.; Fournaise, E.; Chaurand, P. Anal. Chem. 2012, 84, 2048−2054. (19) Puolitaival, S. M.; Burnum, K. E.; Cornett, D. S.; Caprioli, R. M. J. Am. Soc. Mass Spectrom. 2008, 19, 882−886. (20) Le, C. H.; Han, J.; Borchers, C. H. Anal. Chem. 2012, 84, 8391− 8398. (21) Rujoi, M.; Estrada, R.; Yappert, M. C. Anal. Chem. 2004, 76, 1657−1663. (22) Burnum, K. E.; Cornett, D. S.; Puolitaival, S. M.; Milne, S. B.; Myers, D. S.; Tranguch, S.; Brown, H. A.; Dey, S. K.; Caprioli, R. M. J. Lipid Res. 2009, 50, 2290−2298. (23) Chaurand, P.; Cornett, D. S.; Angel, P. M.; Caprioli, R. M. Mol. Cell. Proteomics 2011, 10, O110−004259. (24) Estrada, R.; Yappert, M. C. J. Mass Spectrom. 2004, 39, 412−422. (25) Colsch, B.; Woods, A. S. Glycobiology 2010, 20, 661−667. (26) Jackson, S. N.; Wang, H. Y.; Woods, A. S. J. Am. Soc. Mass Spectrom. 2005, 16, 2052−2056. (27) Jackson, S. N.; Wang, H. Y.; Woods, A. S. Anal. Chem. 2005, 77, 4523−4527. (28) Wang, H. Y.; Jackson, S. N.; Post, J.; Woods, A. S. Int. J. Mass Spectrom. 2008, 278, 143−149.

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: (250) 483-3221. Fax: (250) 483-3238. 645

dx.doi.org/10.1021/ac404044k | Anal. Chem. 2014, 86, 638−646

Analytical Chemistry

Article

(29) Francese, S.; Bradshaw, R.; Flinders, B.; Mitchell, C.; Bleay, S.; Cicero, L.; Clench, M. R. Anal. Chem. 2013, 85, 5240−5248. (30) Wang, X.; Han, J.; Chou, A.; Yang, J.; Pan, J.; Borchers, C. H. Anal. Chem. 2013, 85, 7566−7573. (31) Fahy, E.; Subramaniam, S.; Murphy, R. C.; Nishijima, M.; Raetz, C. R.; Shimizu, T.; Spener, F.; van Meer, G.; Wakelam, M. J.; Dennis, E. A. J. Lipid Res. 2009, 50 (Suppl), S9−14. (32) van Meer, G.; de Kroon, A. I. J. Cell Sci. 2011, 124, 5−8. (33) Casadonte, R.; Caprioli, R. M. Nat. Protocols 2011, 6, 1695− 1709. (34) Han, J.; Danell, R. M.; Patel, J. R.; Gumerov, D. R.; Scarlett, C. O.; Speir, J. P.; Parker, C. E.; Rusyn, I.; Zeisel, S.; Borchers, C. H. Metabolomics 2008, 4, 128−140. (35) Tautenhahn, R.; Cho, K.; Uritboonthai, W.; Zhu, Z.; Patti, G. J.; Siuzdak, G. Nat. Biotechnol. 2012, 30, 826−828. (36) Subramaniam, S.; Hsiao, G. Nat. Immunol. 2012, 13, 199−203. (37) Spann, N. J.; Garmire, L. X.; McDonald, J. G.; Myers, D. S.; Milne, S. B.; Shibata, N.; Reichart, D.; Fox, J. N.; Shaked, I.; Heudobler, D.; Raetz, C. R.; Wang, E. W.; Kelly, S. L.; Sullards, M. C.; Murphy, R. C.; Merrill, A. H., Jr.; Brown, H. A.; Dennis, E. A.; Li, A. C.; Ley, K.; Tsimikas, S.; Fahy, E.; Subramaniam, S.; Quehenberger, O.; Russell, D. W.; Glass, C. K. Cell 2012, 151, 138−152. (38) Shanta, S. R.; Zhou, L. H.; Park, Y. S.; Kim, Y. H.; Kim, Y.; Kim, K. P. Anal. Chem. 2011, 83, 1252−1259. (39) Norris, J. L.; Caprioli, R. M. Chem. Rev. 2013, 113, 2309−2342. (40) Sparvero, L. J.; Amoscato, A. A.; Dixon, C. E.; Long, J. B.; Kochanek, P. M.; Pitt, B. R.; Bayir, H.; Kagan, V. E. Chem. Phys. Lipids 2012, 165, 545−562. (41) Bligh, E. G.; Dyer, W. J. Can. J. Biochem. Physiol. 1959, 37, 911− 917. (42) Hankin, J. A.; Farias, S. E.; Barkley, R. M.; Heidenreich, K.; Frey, L. C.; Hamazaki, K.; Kim, H. Y.; Murphy, R. C. J. Am. Soc. Mass Spectrom. 2011, 22, 1014−1021. (43) Sun, G.; Yang, K.; Zhao, Z.; Guan, S.; Han, X.; Gross, R. W. Anal. Chem. 2008, 80, 7576−7585. (44) Rosol, T. J.; Yarrington, J. T.; Latendresse, J.; Capen, C. C. Toxicol. Pathol. 2001, 29, 41−48. (45) Fung, M. M.; Viveros, O. H.; O’Connor, D. T. Acta Physiol. 2008, 192, 325−335. (46) Kong, J. Y.; Thureson-Klein, A.; Klein, R. L. Neuroscience 1989, 28, 765−775. (47) Petkovic, M.; Schiller, J.; Muller, M.; Benard, S.; Reichl, S.; Arnold, K.; Arnhold, J. Anal. Biochem. 2001, 289, 202−216. (48) Carman, G. M.; Kersting, M. C. Biochem. Cell Biol. 2004, 82, 62−70. (49) Vance, J. E.; Vance, D. E. Biochem. Cell Biol. 2004, 82, 113−128. (50) Schiller, J.; Suss, R.; Arnhold, J.; Fuchs, B.; Lessig, J.; Muller, M.; Petkovic, M.; Spalteholz, H.; Zschornig, O.; Arnold, K. Prog. Lipid Res. 2004, 43, 449−488. (51) Ayorinde, F. O.; Garvin, K.; Saeed, K. Rapid Commun. Mass Spectrom. 2000, 14, 608−615. (52) Swinnen, J. V.; Van Veldhoven, P. P.; Timmermans, L.; De Schrijver, E.; Brusselmans, K.; Vanderhoydonc, F.; Van de Sande, T.; Heemers, H.; Heyns, W.; Verhoeven, G. Biochem. Biophys. Res. Commun. 2003, 302, 898−903. (53) Gibellini, F.; Smith, T. K. IUBMB Life 2010, 62, 414−428. (54) Merrill, A. H., Jr. J. Biol. Chem. 2002, 277, 25843−25846. (55) Quirk, S.; Seley, K. L. Biochemistry 2005, 44, 13172−13178. (56) McArthur, F.; Andersson, C. E.; Loutet, S.; Mowbray, S. L.; Valvano, M. A. J. Bacteriol. 2005, 187, 5292−5300. (57) Chang, Y. Y.; Kennedy, E. P. J. Lipid Res. 1967, 8, 447−455. (58) Homma, H.; Nojima, S. J. Biochem. 1982, 91, 1103−1110. (59) Benabdellah, F.; Touboul, D.; Brunelle, A.; Laprevote, O. Anal. Chem. 2009, 81, 5557−5560.

646

dx.doi.org/10.1021/ac404044k | Anal. Chem. 2014, 86, 638−646