Kevin R.
Tucker
,
Leonid A.
Serebryannyy
,
Tyler A.
Zimmerman
,
Stanislav S.
Rubakhin
and
Jonathan V.
Sweedler
*
Department of Chemistry and the Beckman Institute, University of Illinois, 600 South Mathews Ave. 63-5, Urbana, IL 61801, USA. E-mail: jsweedle@illinois.edu; Fax: +217-265-6290; Tel: +217-244-7359
First published on 1st February 2011
Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been used to create spatial distribution maps from lipids, peptides, and proteins in a variety of biological tissues. MALDI-MSI often involves trade-offs between the extent of analyte extraction and desired spatial resolution, compromises that can adversely affect detectability. For example, increasing the extraction time can lead to unwanted analyte spatial redistribution. With the stretched sample method (SSM), the extraction period can be extended, resulting in reduced analyte redistribution while suppressing detection of cationic salt adducts. The SSM involves thaw-mounting a thin tissue section onto a substrate of small glass beads embedded in Parafilm M and then stretching the membrane to fragment the tissue into thousands of bead-sized pieces. Here, we applied the SSM method to MALDI-MSI using rat spinal cord as a model. We used surface-modified beads coated with trypsin or chymotrypsin in order to facilitate controlled digestion and detection of proteins. The enzymatic reactions were maintained by repeatedly condensing water on the stretched sample surface. As a result, new peptides formed by tryptic or chymotryptic protein digestion were detected and identified using a combination of MALDI-MSI and offline liquid chromatography tandem mass spectrometric analysis. Localization of these peptides indicated the distribution of their proteins of origin, including myelin basic protein, actin beta, and tubulin alpha chain. Additionally, we used uncoated beads to create distribution maps of many endogenous lipids and small peptides. The extension of the SSM using modified beads resulted in the creation of mosaic bead surfaces where adjacent beads were coated with different enzymes or other reactive chemicals, permitting investigation of the distributions of a wider range of analytes in biological samples within a single experiment.
Spatial resolution and analyte extraction can be competing interests in MALDI MSI, with various parameters affecting spatial resolution such as laser spot size and analyte migration and abundance.11 In MALDI MS, a laser is used to ionize analytes directly from a matrix-coated sample surface, so the minimum spatial resolution is defined by the laser spot size, except in cases when the oversampling approach12 or localized application of MALDI matrix are used. More recently, with the incorporation of appropriate optics into the instruments, laser spot sizes are now small enough (≤10 μm) to detect analytes in a single mammalian cell.13 The minimum spatial resolution may be limited by analyte concentration and/or interference during detection from other analytes. An analyte must be present in detectable levels within the effective sample used for analysis; therefore, increasing resolution (decreasing spot size) may bring an analyte below the detection limit. For example, by reducing the illuminated spot size from 200 μm to 10 μm, only 0.25% of the area will be sampled, normally with a concomitant reduction in signal intensity. In most cases, spatial resolution is constrained by the intertwined relationship between sample characteristics/preparation and instrumental figures of merit.
In order to use MALDI for MSI, typically a thin tissue section is collected using a cryostat, thaw-mounted to a conductive surface, and then a matrix is deposited onto the tissue.14 There are a number of ways to apply MALDI matrix onto the sample, either by printing,9 spraying,5 or sublimation.15 Each of these techniques has a number of advantages but represent a compromise between spatial resolution and analyte extraction. The longer a sample is covered with the matrix solution, the larger the fraction of analytes that will be incorporated into the MALDI matrix layer and hence, the more efficiently they will be detected. However, longer extraction times tend to lead to lateral analyte redistribution, thereby reducing the effective spatial resolution obtainable. Several matrix-free approaches alleviate several of these issues with these including laser desorption/ionization16 and nano-assisted laser desorption/ionization,16 although these techniques have been used primarily for analysis of small molecules rather than peptides and proteins. Printing an array of MALDI matrix spots allows for extended analyte extraction times because the matrix spots are separated from each other and so the analytes do not blend together. Due to the drop size of currently available chemical printers,17–19 this approach often results in MSI with a spatial resolution of >100 μm. An alternative is to coat the entire sample surface with a MALDI matrix solution using airbrush- or piezo-assisted spraying, which produces small droplets on impact, forming a thin layer of the solution on the sample surface. Depending on the solvent system used, the solution will evaporate at different rates, with the solvent evaporating more slowly as the fraction of water is increased. Because of the small droplet size, spraying provides a moderate amount of analyte extraction with relatively high spatial resolution and low analyte redistribution. In a recently described, elegant approach known as matrix sublimation, a dry MALDI matrix is applied onto the sample surface,15 and has proven effective for analysis of abundant, low molecular-weight species.20 The stretched sample method (SSM) aims to decouple this relationship between matrix application and the obtainable spatial resolution.21–23
The SSM was originally created as a method to simultaneously prepare many small tissue samples for profiling peptide content.21 Briefly, a thin tissue section is thaw-mounted onto a substrate consisting of ∼38 μm-diameter glass beads that have been embedded in a stretchable membrane. As the membrane is stretched, the tissue section fragments into thousands of bead-sized tissue regions, each spatially isolated by the nonpolar membrane between the beads. The size of the tissue fragmentation is directly linked to the size of the glass beads; the use of larger or smaller glass beads results in larger or smaller tissue fragment pieces, respectively. Furthermore, tissue fragment size is believed to relate only to the size of the bead and to be independent of chemical modifications made to the bead surface, although this was not validated here. Taking advantage of this isolation, samples can be spray coated with matrix and have water condensed on the surface without causing analyte redistribution between the tissue pieces. This allows extended analyte extraction periods, prevents analyte spreading, and even reduces inorganic cation adducts.22,24 Using bright field microscopy and light thresholding to identify the location of each bead, a sample-specific geometry file for automated data acquisition can be generated; a mass spectrum is acquired from each bead location rather than in an ordered pattern. By recording the location where each mass spectrum was acquired, an image can be (re)created from the stretched sample.25 More recently, using several computer algorithms to realign the stretched individual bead/tissue piece positions with their original positions, reconstructed mass spectral images can be generated that map each bead's pre-stretched position in accurate scale and proportion.22
Recognizing the opportunities that the glass bead substrates provide, we chemically modified the bead surfaces to enable a number of applications, including protein investigation. By performing in situ digestion of proteins from stretched tissue samples using enzyme-modified beads, peptides from proteins were identified and localized. Importantly, compared to the larger proteins, peptides are more efficiently ionized and detected. Furthermore, by covalently attaching the enzyme to the beads, we observed a decrease in autolysis, which is assumed to result from steric hindrance due to the enzyme being bound to a solid support.26,27 Additionally, multiple enzyme digestions in situ, as well as analysis of the native tissue, became feasible when using mixed bead substrates consisting of unmodified glass beads as well as enzyme-modified beads. Here, we demonstrate the imaging of lipids, endogenous peptides and proteins via their peptide digestion products from rat spinal cord tissue using the modified bead stretched sample method (MBSSM).
An overview of the MBSSM is depicted in Fig. 1. A substrate is generated by placing 5–10 mg of approximately equal portions of chemically modified and unmodified bead types on top of a square of Parafilm M (25 cm2) and applying heat and pressure to embed the beads into the membrane. After thaw-mounting a thin (14 μm) tissue section, the membrane is stretched over 5-fold in both the x and y directions and then mounted over an indium-tin oxide (ITO)-coated glass slide to reduce sample charging during analysis.22 Individual mass spectra are then collected from each bead position and analyzed according to bead type.
![]() | ||
| Fig. 1 Schematic showing the modified bead stretched sample method (clockwise from upper left). A substrate is generated by placing 5–10 mg of glass beads, consisting of approximately equal portions of each bead type, on top of a square of Parafilm M (25 cm2) and applying heat and pressure to embed the beads into the Parafilm M (upper left). After thaw-mounting a thin (14 μm) tissue section onto the Parafilm M, the membrane is stretched over 5-fold in both the x and y directions and then mounted over an indium-tin oxide coated glass slide to reduce charging of the sample during MALDI-MSI analysis (right).22 Individual mass spectra are then collected from each bead position and analyzed according to bead type (lower left). | ||
![]() | ||
| Fig. 2 Glass beads, prior to modification and following steps (1) and (2), were analyzed using a TOF-SIMS instrument equipped with a 22 keV Au ion source. The images shown here are 500 × 500 μm. The reactions were monitored in positive ion mode by the disappearance of the sodium signal (m/z 23) occurring after the first reaction. There is a single visible bead in the TESBA bead image that was not successfully modified as shown by the remaining sodium signal from its surface. Additionally, a common signal observed from the biological species C2H3O+ (m/z 43), a fragment that arises from the reagents and not the unmodified beads, can be used to monitor the reaction progress. The reactions were also monitored in negative ion mode. The chlorine signal (m/z 35) disappeared after the first reaction, similar to the sodium signal. The CN− (m/z 26) signal is a characteristic signal from proteins having a large number of nitrogen-carbon bonds, and can be used to monitor formation of the protein coating on the bead surface of the trypsin (Trp)-modified beads. | ||
![]() | ||
| Fig. 3 MALDI-MS imaging of rat spinal cord. A tissue section was spotted with matrix by a chemical inkjet printer with center-to-center distances of 250 μm, generating an array of 14 pixels × 23 pixels. Masses here are displayed as (M + H)+. (A) Lipids, including phosphatidylcholines (PC) and phosphatidylethanolamine (PE) were mapped via MSI, with the analyte identifications based on previously published data.34(B) Proteins were mapped by performing in situ tryptic digest and detection of resulting peptides as described previously.9 Proteins identified include tubulin alpha chain, glial fibrillary protein (GFAP), actin, neurofilament triplet L protein (NFTLPa), and myelin basic protein. These molecular distribution maps are provided as a reference for comparison of the lipid and protein data presented in this work using the modified bead stretched sample method. | ||
Following analyte detection and identification (see following section), in-house software was used to generate an ion distribution map in pseudo-color representing the relative ion intensity with respect to the maximum ion intensity observed within that sample for each specified mass-to-charge (m/z) range. Lipid and endogenous peptide ion distribution maps, generated from data collected from the unmodified glass beads, are presented in Fig. 4A. The lipid identifications, based on mass matches to previously published data from the rat nervous system,31–35 are from the analysis of the unmodified beads within the mixed-bead substrate. A variety of distributions are present for lipids, including analytes that are concentrated in the grey and white matter, in addition to several that are present ubiquitously. The identified lipids include those from the phosphatidylcholine and phosphatidylethanolamine families. Additionally, endogenous peptides were identified, using LC-ESI-IT-MS/MS in addition to previously published work,5 and included fragments of myelin basic protein (MBP) and complexin, as well as neuropeptides such as little SAAS and somatostatin. In the spinal cord, MBP is a heterogeneous set of proteins that increases the electrical signal propagation rate along axons; here it is detected via several characteristic ions. Panels B and C in Fig. 4 depict ion distribution maps from digest products that were identified from the trypsin- and chymotrypsin-modified glass beads, respectively. Each analyte was mass-matched to confirm MS/MS data from the LC-ESI-IT-MS/MS experiments discussed below. While each protein identified using the ChIP in situ method was also identified using the MBSSM, the specific ions that were detected varied in several cases. This variation may be due to differences in digestion; for example, steric effects created by attaching trypsin to a solid support.
![]() | ||
| Fig. 4 Molecular distribution maps collected from unmodified and trypsin- and chymotrypsin-modified glass beads for peptides detected in spinal cord sections using MALDI-MSI. Masses are (M + H)+. (A) Lipid maps based on mass matches with reported masses34 and maps of endogenous peptides identified using LC-MS/MS and previously reported work.5(B, C) Distribution of peptides formed during protein digest. The peptides are identified by molecular mass matching to the LC-MS/MS data. Overall, the peptide and lipid distributions are consistent among the different bead types and also with previous studies. | ||
After compiling the images from each dataset, ion distribution maps that were related to the same analyte (e.g., MBP) were overlaid, as shown in Fig. 5A. Each color represents a corresponding glass bead analyte signal, red for unmodified, blue for trypsin-modified, and green for chymotrypsin-modified. Fig. 5A details the overlay process for all analyte signals from MBP. By overlaying these maps, an analyte's distribution can be further confirmed because the distributions from each image should correlate. The lipid distributions observed from the unmodified glass beads (individual images shown in Fig. 4A) during the stretched sample analysis were overlaid with signals that were observed in the trypsin- and chymotrypsin-modified glass bead signals (individual images not shown), as shown in Fig. 5B. These overlaid images are intended to provide a total map for each lipid type because the lipids would not be digested on the enzyme-modified beads; thus, for the lipids, the three maps include the same m/z signals. While these images have some variation in distribution by bead type, there is signal from all types of beads throughout each image. Once again, the identified lipids include those from the phosphatidylcholine and phosphatidylethanolamine families. These lipids have been imaged using other mass spectrometric techniques. For example, Monroe et al.5 used SIMS to image the choline head group from phosphatidylcholine and a fragment of phosphatidylethanolamine, both of which were shown to be present in higher levels in the central grey matter than the surrounding white matter. Further, in the reported SIMS results, the observed lipid class distributions of different classes of lipids can be significantly different than the results from examining each individual lipid species. In another study, desorption electrospray ionization (DESI)32 was used to detect many of the same lipid species, but the molecular distributions were not presented. In Fig. 5C, composite images from various protein signals from the spinal cord, including MBP, glial fibrillary acidic protein, and actin beta protein, are displayed. Here, the images consist of multiple overlaid maps from each bead type, and hence correspond to particular analytes. These maps contain different m/z values that are identified as the same analyte (e.g., MBP). Generating composite analyte maps therefore provides an additional degree of certainty in the identification of specific proteins because the overlapping images correlate to each other. An advantage of the MBSSM is its ability to image molecular distributions for proteins, endogenous peptides, and lipids using a single tissue section and a single data acquisition.
![]() | ||
| Fig. 5 Composite molecular distribution maps collected using the modified bead stretched sample method to analyze rat spinal cord. Composite images are used to provide the summed distribution from all signals detected with three bead types. (A) Schematic showing the process used to generate the composite images. The unmodified, trypsin-modified and chymotrypsin-modified bead images that correlate to a single analyte signal are overlaid, producing a composite image where the red dots represent unmodified glass beads, the blue dots represent trypsin-modified beads, and the green dots represent chymotrypsin-modified beads. (B) Composite images for lipid signals from a trypsin- and chymotrypsin-modified, and unmodified bead substrate that was analyzed using MALDI-MS. Lipid identification was based on mass matches to literature values. (C) Composite images from the same mixed-bead substrate that correspond to the protein signals that were observed. All protein identifications were based on mass matches to LC-MS/MS data. | ||
| ESI-MS/MS m/z | Theoretical m/z | Sequence | Protein |
|---|---|---|---|
| 931.1 | 930.5 | D.TGILDSIGR.F | Myelin Basic Protein |
| 1046.1 | 1045.5 | DTGILDSIGR | Myelin Basic Protein |
| 1110.0 | 1109.5 | K.GAYDAQGTLSK.I | Myelin Basic Protein |
| 1185.3 | 1184.5 | R.TQDENPVVHF.F | Myelin Basic Protein |
| 1335.1 | 1335.6 | K.YLATASTMDHAR.H | Myelin Basic Protein |
| 1460.2 | 1459.7 | R.TQDENPVVHFFK.N | Myelin Basic Protein |
| 1129.5 | 1129.5 | R.SYASSETMVR.G | Glial Fibrillary Acidic Protein |
| 1245.2 | 1244.6 | R.DNLTQDLGTLR.Q | Glial Fibrillary Acidic Protein |
| 2044.2 | 2044.6 | K.EPTKLADVYQAELRELR.L + pyro - Glu (P) | Glial Fibrillary Acidic Protein |
| 3060.1 | 3059.6 | R.ELQEQLAQQQVHVEMDVAKPDLTAALR.E | Glial Fibrillary Acidic Protein |
| 1161.1 | 1160.6 | K.EITALAPSTMK.I | Actin Beta |
| 1170.0 | 1170.6 | R.HQGVMVGMGQK.D | Actin Beta |
| 1515.6 | 1515.7 | K.QEYDESGPSIVHR.K | Actin Beta |
| 1790.5 | 1789.9 | K.SYELPDGQVITIGNER.F | Actin Beta |
| 1960.0 | 1959.9 | K.YPIEHGIVTNWDDMEK.I + pyro-Glu (P) | Actin Beta |
| 1085.0 | 1084.6 | K.EIIDLVLDR.I | Tubulin Alpha Chain |
| 1701.6 | 1700.9 | R.AVFVDLEPTVIDEVR.T | Tubulin Alpha Chain |
| 1823.2 | 1824.0 | K.VGINYQPPTVVPGGDLAK.V | Tubulin Alpha Chain |
| 1295.2 | 1295.6 | K.NMQNAEEWFK.S | Neurofilament Triplet L Protein |
| 1548.1 | 1547.7 | K.QNADISAMQDTINK.L | Neurofilament Triplet L Protein |
| 1159.3 | 1158.6 | R.LRDDTEAAIR.A | Neurofilament Triplet M Protein |
| 1904.2 | 1903.9 | K.AQVQLDSDHLEEDIHR.L | Neurofilament Triplet M Protein |
| 2588.4 | 2588.3 | R.SNHEEEVADLLAQIQASHITVER.K | Neurofilament Triplet M Protein |
| ESI-MS/MS m/z | Theoretical m/z | Sequence | Protein |
|---|---|---|---|
| 1038.2 | 1037.5 | R.TQDENPVVH.F | Myelin Basic Protein |
| 1078.5 | 1077.6 | D.TGILDSIGRF.F | Myelin Basic Protein |
| 1194.3 | 1193.6 | Q.RTQDENPVVH.F | Myelin Basic Protein |
| 1699.2 | 1698.9 | F.KNIVTPRTPPPSQGK.G + Phospho (ST) | Myelin Basic Protein |
| 1130.5 | 1130.6 | L.ARLEEEGQSL.K | Glial Fibrillary Acidic Protein |
| 1291.4 | 1290.7 | L.RLEAENNLAVY.R | Glial Fibrillary Acidic Protein |
| 1437.1 | 1436.8 | L.RKIHEEEVREL.Q | Glial Fibrillary Acidic Protein |
| 1485.1 | 1484.8 | L.ALDIEIATYRKL.L + Phospho (TY) | Glial Fibrillary Acidic Protein |
| 1822.9 | 1823.9 | L.LEGEENRITIPVQTF.S + Amide (C-term); Phospho (T) | Glial Fibrillary Acidic Protein |
| 1192.5 | 1191.6 | F.IGNSTAIQELF.K | Tubulin Beta Chain |
| 1193.3 | 1192.6 | L.TVPELTQQMF.D | Tubulin Beta Chain |
| 1534.2 | 1533.7 | L.SVHQLVENTDETY.C | Tubulin Beta Chain |
| 1571.3 | 1571.5 | L.THSLGGGTGSGMGTL.L + 3 Phospho (ST) | Tubulin Beta Chain |
| 1811.4 | 1810.6 | F.QLTHSLGGGTGSGMGTL.L + Amide (C-term); Oxidation (M); 3 Phospho (ST); Pyro-glu (N-term Q) | Tubulin Beta Chain |
| 2719.6 | 2720.1 | L.TQQMFDSKNMMAACDPRHGRYL.T + Acetyl (N-term); Amide (C-term); Phospho (STY) | Tubulin Beta Chain |
| 1408.2 | 1407.7 | Y.SSSSGSLMPSLENL.D | Neurofilament Triplet L Protein |
| 1529.3 | 1528.8 | L.RLAAEDATNEKQAL.Q | Neurofilament Triplet L Protein |
| 935.6 | 935.5 | L.REYQDLL.N | Neurofilament Triplet M Protein |
| 1376.5 | 1376.7 | Y.RKLLEGEETRF.S | Neurofilament Triplet M Protein |
| 1540.2 | 1539.9 | M.AIKEEIKVEKPEK.A | Neurofilament Triplet M Protein |
| 1671.2 | 1670.9 | Y.AKLTEAAEQNKEAIR.S | Neurofilament Triplet M Protein |
| 1688.1 | 1687.8 | W.ISKQEYDESGPSIVH.R | Actin Beta Protein |
:
1 methanol–water, spotted at a 250 μm center-to-center spacing between each spot (these spots were printed directly on top of the trypsin spots for the first section) with no delay time between printing iterations needed because the spots were dry prior to the conclusion of each printing pass.
:
50 acetone/water, propelled by purified nitrogen. Multiple coats were quickly applied until the sample exhibited homogeneous DHB crystal formation, as monitored using a low-power light microscope.
:
50 enzyme
:
substrate mass ratio was calculated using several milligrams of sectioned rat spinal cord. The enzyme was suspended in a 25 mM ammonium bicarbonate solution, pH 8.0, and quickly shaken. The substrate and enzyme solutions were then agitated for 2 h and allowed to react. Undigested samples were treated similarly without the addition of an enzyme to the buffer solution. The samples were centrifuged (5804R multipurpose centrifuge, Eppendorf) at 10
000 rpm for 20 min to pellet insoluble species. Then 5.0 μL of the digest solution was manually injected onto a capillary column (PepMap, C18, 3 μm, 100 Å, 300 μm inner diameter, 15 cm, Dionex, Sunnyvale, CA) using a solvent gradient at 2.5 μL min−1 flow rate. The solvent system was composed of two solutions: solution A (95% H2O, 5% acetonitrile (ACN), 0.1% formic acid (FA) and 0.01% trifluoroacetic acid (TFA)) and solution B (5% H2O, 95% ACN, 0.1% FA, and 0.01% TFA). The 50 min gradient LC separation included 6 steps: 97–80% solvent A in 0–5 min (linear); 80–50% solvent A for 5–30 min (linear); 50–20% solvent A for 30–35 min (linear); 20% solvent A for 35–38 min (isocratic); 20–95% solvent A for 38–40 min; 95–97% solvent A for 40–50 min. The ESI-MS data acquisition of selected analytes was performed in a data-dependent manner using the Esquire software (Bruker Daltonics). Following each MS scan, two peptides were selected to be fragmented based on their intensity. Dynamic exclusion of previously selected peaks was used to limit redundant data acquisition over a short period of time. Tandem mass spectra were used for Mascot searches and then sequences were confirmed manually to verify analyte identities using the BioTools software package (Bruker Daltonics).
| This journal is © The Royal Society of Chemistry 2011 |