Notes and Acknowledgements
This chapter was published as an original research article in Analytical Chemistry 2017, DOI: 10.1021/acs.analchem.6b04819, coauthored by T.D. Do, S.J.B. Dunham, S.S. Rubakhin and J.V. Sweedler. The article is adapted and reprinted here with permission from the American Chemical Society, copyright 2017. T.D. Do and T.J. Comi authored the manuscript, designed the hardware modifications and programmed the Arduino microcontroller. T.J. Comi performed data analysis and T.D. Do acquired data. The project was supported by the National Institutes of Health, Award Number P30 DA018310 from the National Institute on Drug Abuse, and Award Number 1U01 MH109062 from the National Institute of Mental Health. The authors also acknowledge Xiying Wang for help with sample preparation, and Joseph Ellis and Elizabeth Neumann for assistance with instrumentation and useful discussions.
Introduction
Single cell heterogeneity appears in seemingly homogeneous cell populations, even when derived from identical genetic blueprints. Adjacent cells within tissues have distinct identities and chemical contents; probing these differences aids in our understanding of the interplay between chemistry, cell activity, and function in complex tissues. As a single cell divides and differentiates into distinct subpopulations or into a malignant tumor, fluctuations in chemical composition and changes in cellular state manifest as diverging cell lineages, confounded with decisions related to cell fate from environmental cues.1 Cell populations appear only as homogeneous as our ability to detect differences in their chemical composition. Newly
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developed techniques measure heterogeneity in genetic materials, proteins, peptides, lipids, and metabolites.2-11 Recent successes in single cell studies help address confounding questions in cell biology and shape the next generation of drug discovery and development efforts.1,12 Even so, there remains a need for single cell techniques that are capable of simultaneously detecting many classes of biological molecules in populations of cells.13 The search for rare cells, which for decades was akin to finding a needle in a haystack, has become tractable with the emergence of high-throughput and sensitive measurement techniques.
Typical mammalian cells contain a few picoliters of volume, with analyte concentrations ranging from picomolar to millimolar. Thus, a successful single cell analytical technique should provide a low absolute detection limit, a high dynamic range, and multiplexed coverage of analyte classes.5 Mass spectrometry (MS) has become a versatile and robust method for
performing volume-limited biological measurements. Mass spectrometry imaging (MSI) is at the forefront of MS-based, label-free platforms for analyzing single cells,6,14-18 demonstrating cellular and subcellular spatial resolution19-21 and untargeted detection of biological molecules.5,8 If cellular analytes are efficiently desorbed and ionized, the gas phase ions can be further interrogated with hybrid MS instrumentation for structural fragmentation,22,23 ion sizes and
shapes,23-26 secondary structures,27,28 and thermodynamic properties.29,30
Secondary ion mass spectrometry (SIMS) and matrix-assisted laser desorption/ionization (MALDI) are two common MS ionization microprobes that are suitable for spatially-resolved surface analysis of single cells.31-34 MALDI uses focused laser light to desorb and ionize sample analytes incorporated into a suitable matrix. In contrast, SIMS utilizes a beam of accelerated primary ions or larger clusters that bombards the sample surface to sputter and generate
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secondary ions in the gas phase for mass-to-charge (m/z) analysis. Since the primary ion beam can be tightly focused, SIMS can achieve subcellular spatial resolution.31
Previous SIMS imaging investigations have established sample preparation methods that improve the limits of detection and molecular coverage of biological samples, including metal assisted35-37 and ionic liquid (IL) matrix-enhanced SIMS.38-40 Many IL mixtures have unique physical and chemical properties that can be optimized for SIMS- and MALDI-based detection.40,41
Recently, we demonstrated the capability of a high-throughput, microscopy-guided MALDI MS profiling method to classify dissociated rat pituitary cells, including rare cells, as well as elucidate the cellular heterogeneity of rat islets of Langerhans.32,33 The approach circumvents the need for MS raster imaging42,43 of a large region of interest, which is time
consuming and often splits cell signals over multiple pixels. However, most single cell SIMS studies also utilize raster imaging22,34,35,44-50 to fully leverage the subcellular spatial resolution of the method and localize analytes within single cells, albeit at low throughput and reduced sensitivity.
Establishing optically-guided single cell SIMS profiling should facilitate lipidomics and metabolomics studies on large populations of cells. Here we report a combination of matrix- enhanced SIMS (ME-SIMS) and multivariate statistical analysis to profile single cells from the Aplysia californica central nervous system, the rat dorsal root ganglion (DRG), and the rat cerebellum. These neuronal cell types were chosen because they represent well-characterized large (>75 µm in diameter), medium (10–50 µm), and small (5–10 µm) cells, respectively. The A. californica samples included large neurons with well-studied metabolite and lipid contents,22,35,42,46,49 and are therefore suitable for our method validation experiments. The DRG
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contains the cell bodies of sensory neurons actively participating in neuropathic pain.51 DRGs are traditionally classified based their on size,52 electrophysiological properties,53 and peptide content.54 Cellular heterogeneity within the DRG was previously shown to affect opioid peptide sensitivity55 and produce differential responses to neuropathic pain.56 The cerebellar cells are critical to cognitive function and motor control,57 and were chosen as small cell targets for this study.
Here we performed ME-SIMS utilizing three different IL matrixes to determine their ability to enhance the sputtering/ionization efficiency and chemical signals for single cell SIMS profiling. In addition, ME-SIMS tandem MS was performed to identify and characterize metabolites, including lipids, from single cells. Data sets acquired from populations of DRG and cerebellar cells were classified by t-distributed stochastic neighbor embedding (t-SNE). Each cellular population was further sub-divided by the same method, revealing their heterogeneity based on lipid content.
Methods
Chemicals
All chemicals were purchased from Sigma Aldrich (St. Louis, MO) and used without further purification.
Matrix Preparation
Three IL matrix solutions were evaluated. The first, MI-CHCA, was prepared by dissolving 250 mg of α-cyano-4-hydroxycinnamic acid (CHCA; > 98% purity) in 10 mL LC-grade methanol, followed by an addition of 105 µL of 1-methylimidazole (MI; Reagent Plus, 99%), with 10 mL of LC-grade acetonitrile added to the total volume of 20 mL. The second, TRIP-CHCA, was similarly prepared using 252 µL of tripropylamine (TRIP; > 98% purity). The third, Mix-CHCA,
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was prepared by mixing equal volumes of the MI-CHCA and TRIP-CHCA solutions. DHB matrix was prepared by dissolving DHB (99% purity) to 50 mg/mL in 1:1 (v/v) LC-grade ethanol:water and 0.1% trifluoroacetic acid solvent.
Sample Preparation
Aplysia californica. Two Aplysia californica (100–250 g body weight ) were purchased from the National Resource for Aplysia (Rosenstiel School of Marine and Atmospheric Science University of Miami, FL). The mollusks were kept in aerated, circulated, filtered and chilled to 20 °C sea water prepared from Instant Ocean Sea Salt (Instant Ocean, Aquarium Systems Inc., Mentor, OH) dissolved in purified water. Animals were anesthetized by injection of isotonic MgCl2 (~30% to 50% of body weight) into the body cavity. Central nervous system ganglia were
dissected and placed in artificial sea water (ASW) containing 460 mM NaCl, 10 mM KCl, 10 mM CaCl2, 22 mM MgCl2, 26 mM MgSO4 and 10 mM HEPES in Milli-Q water (Millipore,
Billerica, MA), with the pH adjusted to 7.8 using 1 M NaOH in Milli-Q water. Ganglia were treated with enzyme solution consisting of 1% (wt/vol) protease type IX (Sigma Aldrich, St. Louis, MO) in ASW supplemented with 100 units/mL penicillin G, 100 µg/mL streptomycin, and 100 µg/mL gentamicin for 45 min at 34.4 °C. The connective tissue surrounding neurons and neuropil was surgically removed and multiple individual neurons mechanically isolated. Cells were deposited on indium-titanium oxide (ITO)-coated glass slides, 70–100 ohms, 25 × 75 × 1.1 mm (Delta Technologies, Loveland, CO), which were washed with Milli-Q water and ethanol before use. ITO-coated glass slides were placed in ASW and cells were allowed to adhere for 30 min. Next, ASW was replaced with a 33% glycerol 67% ASW (v/v) solution that was decanted after a 5 min incubation. Cells were left to dry overnight.
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Rattus norvegicus. Seven 2.5–3 month old male Sprague-Dawley outbred rats (Rattus norvegicus) (www.envigo.com) were housed on a 12-h light cycle and fed ad libitum. Animal euthanasia was performed in accordance with the appropriate institutional animal care guidelines (the Illinois Institutional Animal Care and Use Committee), and in full compliance with federal guidelines for the humane care and treatment of animals. The studies were planned in accordance with the ARRIVE guidelines.58
Rats were killed by quick decapitation using a sharp guillotine. Rat trunks were placed on ice, where all surgical procedures were performed. Dorsal root ganglia (DRG) were surgically isolated during the ~10-min dissection procedure and placed into ~5 mL of cold Modified Gey’s balanced salt solution (mGBSS) containing 1.5 mM CaCl2, 4.9 mM KCl, 0.2 mM KH2PO4, 11
mM MgCl2, 0.3 mM MgSO4, 138 mM NaCl, 27.7 mM NaHCO3, 0.8 mM NaH2PO4, and 25 mM
HEPES dissolved in Milli-Q water, with the pH adjusted to 7.2 using 1 M NaOH in Milli-Q water.
To remove the surrounding connective tissue and isolate individual neurons, the DRG were incubated in 2.5% collagenase in oxygenated mGBSS for 25 min. All steps in the protocol were carried out at 37 °C, and oxygenated mGBSS was used in all cases. The DRG were then washed with 1% bovine serum albumin (BSA) in mGBSS for 7 min. The BSA solution was replaced with mGBSS and the DRG were incubated for an additional 20 min. Next, the DRG were treated with 0.65% trypsin in mGBSS for 20 min, followed by a 1% BSA solution wash for 7 min. The BSA solution was replaced with mGBSS containing Hoechst 33342 nuclear stain (Thermo Fisher Scientific, Waltham, MA) (1 mg/mL Hoechst 33342 stock solution, stored at 14 °C, diluted 1:500 in mGBSS) in which the DRG were incubated for 10 min. The Hoechst nuclear stain solution was then replaced with mGBSS and the DRG were mechanically dissociated by
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trituration. Cells were stabilized using a 40% glycerol, 60% mGBSS (v/v) mixture and after 5–10 min, plated on ITO-coated glass slides. The samples were then stored in the dark overnight to allow the cells to adhere onto the glass surface. On the next day, excess glycerol-containing media was removed from the preparations. At this stage, the cells were either subjected to immediate SIMS or MALDI analysis, or left to adhere to the ITO-coated glass surface in a nitrogen-purged dry box for 24 h before the MS measurements. Before analysis, the sample slides were rinsed with 2 mL of 150 mM ammonium acetate buffer (pH 10). This step helped remove the excess glycerol and did not induce observable damage to the cells.32,33,59
Instrumentation
The single cell profiling experiments were performed on two instruments. The first, a customized hybrid MALDI/C60-SIMS Q-TOF mass spectrometer, described in detail elsewhere,46 was
operated in positive ion mode for all SIMS measurements. Negative ion mode on the custom instrument did not provide sufficient ion current during single cell experiments. The 40-μm diameter, 20 kV C60+ ion beam (Ionoptika, Ltd., Hampshire, UK) was operated in continuous
mode with 500 pA sample current to yield an ion dose of 2.5 × 1014 ions/cm2. Positive secondary ions were collected from m/z 60–850 using a Q1 bias of 5%, 5%, 20%, 35% and 35% at m/z 100, 180, 300, 500 and 700, respectively. The signal accumulation time was set to 2 s. The time-bins- to-sum was set to 10. Tandem MS spectra were collected in product-ion mode with the argon collision gas and collision-induced dissociation energy set at 35 eV. The C60-SIMS instrument
required minor hardware modifications to utilize the previously-reported cell finding software32,33 for single cell measurements.
Several modifications were made to the cell coordinate registration protocol and hardware of the previously-reported C60 SIMS instrument.46 For the registration protocol, three
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types of coordinate systems were utilized to interface with the instrument and optical images. The first system was in pixel coordinates in the microscopy image such that each dispersed cell had a unique (X, Y) pixel location. The second coordinate system was the stepper motor location (Xmotor, Ymotor) of the instrument x,y-translation stage. When the ITO-coated glass slide was
loaded into the instrument stage, the fiducial markers were used to calculate the transformation from (X, Y) to (Xmotor, Ymotor) for each cell. These steps were identical to the previously reported
coordinate registration protocol.32,33 Unfortunately, the oMALDI Server software (AB Sciex, Framingham, MA) does not accept motor coordinates as direct inputs. The “Search Pattern” feature directed the stage to dwell at a series of points relative to a pre-set origin dictated by a separate coordinate system, which we refer to as the “Pattern” (PTN) coordinate system. One PTN unit is equivalent to 0.5 mm. The origin was set at the point Xmotor, Ymotor = (8,000, 17,600)
which was equal to XPTN, YPTN = (5, 5) in the PTN coordinate system. Through two coordinate
transformations, each cell from the optical image was mapped to a PTN coordinate readable by oMALDI Server. Cells were then analyzed with the 20kV C60+ ion beam as the stage traveled
through the locations in the "Search Pattern" inputs.
An Arduino Atmega 2560 board (https://www.arduino.cc/) was programmed by the Arduino Software, v1.6.9, to do the described tasks (Figure 7.1A). Since each stepper motor was tracked by a linear encoder, its signals from the quadrature channels A/B were tapped out and connected to two interrupt pins on the Arduino board, which provide fast response times. A 4x decoding method was used to determine when the stage was moving (i.e., changes in signals of either encoder) and when the stage stopped (i.e., no changes in both encoders). As the data acquisition on the mass spectrometer was initiated by Analyst (AB Sciex), a 5 V signal from the mass spectrometer control board was received by interrupt pin 19 on the Arduino board to
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activate stage monitoring and synchronize the start times of the stage and mass spectrometer. When the stage stopped at a cell, the Arduino board would delay for 3 s and then send a 5 V signal through pin 13 to a relay controlling the C60+ beam, initiating desorption for 1 s (see
Figure 7.1B). Longer beam “On” times cause damage on the sample surface and generate more chemical noise. The beam “Off” delays ensured no contamination occurred between cells of interest and surrounding neighbors. Data from the Arduino, including clock time, elapsed time, encoder position and ion beam status, were recorded with the PLX-DAQ add-on for Excel 2010 (https://www.parallax.com/downloads/plx-daq).
Single cell SIMS profiling was accomplished by registering the x,y translation stage of the oMALDI server (AB Sciex, Framingham, MA) with whole-slide, bright-field, and fluorescence images. Cells deposited onto indium-titanium oxide (ITO)-coated glass slides were placed into a custom sample holder that can accommodate slides as large as 40 × 25 mm2 (about one-half of a standard microscope slide). Several mechanically-etched fiducial markers facilitated point-based similarity registration to map cell locations back to their stage coordinates. Because of the limitations with the SIMS instrument control, mass spectral data were continuously acquired as the stage moved. Because the sample stage repeatedly travels and stops at cell locations, it is critical to synchronize its movements with the primary C60+ ion beam
activity and record when a cell is reached. The ion beam should only be “On” when the cell location is reached, and "Off" during sample stage movement, to ensure that only targeted cells are bombarded with primary ions. The dwell time of the translation stage was set to 6 s per cell. For each cell, the C60+ ion beam was signaled to turn on for 1 s after a 3 s delay. The 1 s
sputtering time was found to be optimal, as shorter times yielded inadequate signals whereas longer beam exposure caused IL matrix depletion and complication of the mass spectra with
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additional background ion signals. The acquisition rate on the mass spectrometer was set to 2 s to improve the likelihood that the entire analyte sputtering event was captured in a single scan. In ~20% of scans, the analyte sputtering event was split between two acquisition windows, resulting in a separation of low mass and high mass ions between two mass spectra (see Figure 7.1C).
The second instrument used was a Bruker ultrafleXtreme MALDI TOF/TOF mass spectrometer with a frequency tripled Nd:YAG solid state laser. Single cell MALDI MS analysis was performed as previously reported.32,33 The molecular mass scan window was set to m/z 400−8000 and the laser was operated in the “Ultra” mode, producing a ∼100-μm diameter footprint. The ultrafleXtreme AutoXecute feature (Bruker Daltonics, Billerica, MA) was utilized with the custom geometry file as previously reported.33 Each spectrum represents the summed signals acquired during 1,000 laser shots fired at 1 kHz.
Optical Imaging and Determination of Pixel Coordinates for Individual Cells
Each dispersed cell population on an ITO-coated glass slide was imaged using an Axio Imager M2 (Carl Zeiss, Oberkochen, Germany) in fluorescence and bright-field modes. An X-CITE 120 mercury lamp (Lumen Dynamics, Mississauga, Canada) and a 31000v2 DAPI filter set (Chroma Technology, Irvine, CA) were employed for fluorescence imaging. Because the ITO glass slides are transparent and conductive, they are compatible for both MALDI-MS and SIMS single cell profiling experiments. A 10× objective was used to obtain a mosaic image of the targeted surface with 13% overlap between neighboring images. Images were taken using an AxioCam 503 Mono camera (Carl Zeiss) with a resolution of 1936 × 1460 pixels. All mosaic optical images were stitched with a minimum overlap of 5% and maximum shift of 10%. The stitched image was loaded into microMS32 for either manual or automatic cell finding. The fiducial marks were used
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to register the image coordinates to the x,y translation stage coordinate of the mass spectrometers. On the basis of the registration, the cell coordinates were saved in either a pattern coordinate file-format readable by the oMALDI server for SIMS experiments or a custom geometry file for the MALDI-MS FlexControl software for mass spectral acquisition.
Matrix Application
ITO-coated glass slides were affixed onto a rotating plate for automatic matrix application, as described elsewhere.32 Spraying conditions were optimized for each MS system. The distance between the spray tip and the rotating plate was 5 cm for SIMS and 2 cm for MALDI MS, with a nitrogen gas pressure of 50 psi. The solution flow rate was set to 30 mL/h for SIMS and 10 mL/h for MALDI MS, resulting in a matrix coating of 6 mg/cm2 and 15 mg/cm2, respectively. DHB matrix was also employed for MALDI MS for comparison with the IL matrixes. The same spraying conditions were used for DHB as in IL MALDI-MS.
Multivariate Statistical Analysis
Data analysis was performed with custom scripts written in MATLAB (R2015b). MALDI MS data were read directly with the readbrukermaldi function (https://github.com/AlexHenderson/ readbrukermaldi), resampled to 10,000 m/z values in the range m/z 500–1000, background corrected, smoothed, and normalized by standardizing the area under each spectrum to the median of the data set. SIMS data was first converted from the native wiff format into mzXML with msconvert60 for import into MATLAB. The cell coordinates, diameters, and the corresponding log file from the instrument microcontroller were also utilized to parse continuous SIMS acquisition files. As the Arduino monitors when an acquisition begins, the start time for mass spectral acquisition and stage movement were synchronized. In MATLAB, the x,y translational stage stop events were recorded and used to delineate mass spectra corresponding to
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target cell positions. Stage dwell events shorter than 3 s or longer than 7 s were discarded as noise in the stage or encoders. As the ion beam is only “On” for 1 s within the 6 s dwell time, the spectrum with the highest intensity phosphocholine head group (m/z 184.07) and PC(34:1) (m/z 760.56) signal was selected as the single cell spectrum. Dwell events of single cell signals that occurred in two adjacent acquisition windows were discarded as “split cells”. Finally, all mass spectra acquired from DRG and cerebellar cells were filtered for an intensity of the m/z 184.07 signal greater than 250 counts.
Statistical significance was established with a Wilcoxon rank sum test as intensity