An external matrix-assisted laser desorption ionization source for flexible FT-ICR Mass spectrometry imaging with internal calibration on adjacent samples

ADVANCES IN HIGH-RESOLUTION MALDI MASS SPECTROMETRY FOR NEUROBIOLOGY

Research in the field of neurobiology and neurochemistry has seen a rapid expansion in the last several years due to advances in technologies and instrumentation, facilitating the detection of biomolecules critical to the complex signaling of neurons. Part of this growth has been due to the development and implementation of high-resolution Fourier transform (FT) mass spectrometry (MS), as is offered by FT ion cyclotron resonance (FTICR) and Orbitrap mass analyzers, which improves the accuracy of measurements and helps resolve the complex biological mixtures often analyzed in the nervous system. The coupling of matrix-assisted laser desorption/ionization (MALDI) with high-resolution MS has drastically expanded the information that can be obtained with these complex samples. This review discusses notable technical developments in MALDI-FTICR and MALDI-Orbitrap platforms and their applications toward molecules in the nervous system, including sequence elucidation and profiling with de novo sequencing, analysis of post-translational modifications, in situ analysis, key advances in sample preparation and handling, quantitation, and imaging. Notable novel applications are also discussed to highlight key developments critical to advancing our understanding of neurobiology and providing insight into the exciting future of this field. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Capillary electrophoresis coupled to MALDI mass spectrometry imaging with large volume sample stacking injection for improved coverage of C. borealis neuropeptidome

Neuropeptides are important signaling molecules responsible for a wide range of functions within the nervous and neuroendocrine system. However, they are difficult to study due to numerous challenges, most notably their large degree of variability and low abundance in vivo. As a result, effective separation methods with sensitive detection capabilities are necessary for profiling neuropeptides in tissue samples, particularly those of simplified model organisms such as crustaceans. In order to address these challenges, this study utilized a capillary electrophoresis (CE)-matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) platform, building upon our previous design for improved neuropeptidomic coverage. The capillary was coated with polyethylenimine (PEI) to reduce peptide adsorption and reverse the electroosmotic flow, and large volume sample stacking (LVSS) was used to load and pre-concentrate 1 μL of sample. The method demonstrated good reproducibility, with lower than 5% relative standard deviation for standards, and a limit of detection of approximately 100 pM for an allatostatin III peptide standard. The method was tested on brain and sinus gland (SG) tissue extracts and enabled detection of over 200 neuropeptides per run. When comparing the number detected in brain extracts in a direct spot, 60-second fractions, and 30-second fractions, the continuous trace collection afforded by the CE-MALDI-MSI platform yielded the largest number of detected neuropeptides. The method was compared to conventional LC-ESI-MS, and though the number of neuropeptides detected by LC-ESI-MS was slightly larger, the two methods were highly complementary, indicating the potential for the CE-MALDI-MSI method to uncover previously undetected neuropeptides in the crustacean nervous system. These results indicate the potential of CE-MALDI-MSI for routine use in neuropeptide research.

Unsupervised machine learning using an imaging mass spectrometry dataset automatically reassembles grey and white matter

Current histological and anatomical analysis techniques, including fluorescence in situ hybridisation, immunohistochemistry, immunofluorescence, immunoelectron microscopy and fluorescent fusion protein, have revealed great distribution diversity of mRNA and proteins in the brain. However, the distributional pattern of small biomolecules, such as lipids, remains unclear. To this end, we have developed and optimised imaging mass spectrometry (IMS), a combined technique incorporating mass spectrometry and microscopy, which is capable of comprehensively visualising biomolecule distribution. We demonstrated the differential distribution of phospholipids throughout the cell body and axon of neuronal cells using IMS analysis. In this study, we used solarix XR, a high mass resolution and highly sensitive MALDI-FT-ICR-MS capable of detecting higher number of molecules than conventional MALDI-TOF-MS instruments, to create a molecular distribution dataset. We examined the diversity of biomolecule distribution in rat brains using IMS and hypothesised that unsupervised machine learning reconstructs brain structures such as the grey and white matters. We have demonstrated that principal component analysis (PCA) can reassemble the grey and white matters without assigning brain anatomical regions. Hierarchical clustering allowed us to classify the 10 groups of observed molecules according to their distributions. Furthermore, the group of molecules specifically localised in the cerebellar cortex was estimated to be composed of phospholipids.

Enhanced Ion Transmission Efficiency up to m/ z 24 000 for MALDI Protein Imaging Mass Spectrometry

The molecular identification of species of interest is an important part of an imaging mass spectrometry (IMS) experiment. The high resolution accurate mass capabilities of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) have recently been shown to facilitate the identification of proteins in matrix-assisted laser desorption/ionization (MALDI) IMS. However, these experiments are typically limited to proteins giving rise to ions of relatively low m/ z due to difficulties transmitting and measuring large molecular weight ions of low charge states. Herein we have modified the source gas manifold of a commercial MALDI FT-ICR MS to regulate the gas flow and pressure to maximize the transmission of large m/ z protein ions through the ion funnel region of the instrument. By minimizing the contribution of off-axis gas disruption to ion focusing and maximizing the effective potential wall confining the ions through pressure optimization, the signal-to-noise ratios (S/N) of most protein species were improved by roughly 1 order of magnitude compared to normal source conditions. These modifications enabled the detection of protein standards up to m/ z 24 000 and the detection of proteins from tissue up to m/ z 22 000 with good S/N, roughly doubling the mass range for which high quality protein ion images from rat brain and kidney tissue could be produced. Due to the long time-domain transients (>4 s) required to isotopically resolve high m/ z proteins, we have used these data as part of an FT-ICR IMS-microscopy data-driven image fusion workflow to produce estimated protein images with both high mass and high spatial resolutions.

Method development for the analysis of resinous materials with MALDI-FT-ICR-MS: novel internal standards and a new matrix material for negative ion mode

Matrix-assisted laser desorption/ionization (MALDI) is a mass spectrometry (MS) ionization technique suitable for a wide variety of sample types including highly complex ones such as natural resinous materials. Coupled with Fourier transform ion cyclotron resonance (FT-ICR) mass analyser, which provides mass spectra with high resolution and accuracy, the method gives a wealth of information about the composition of the sample. One of the key aspects in MALDI-MS is the right choice of matrix compound. We have previously demonstrated that 2,5-dihydroxybenzoic acid is suitable for the positive ion mode analysis of resinous samples. However, 2,5-dihydroxybenzoic acid was found to be unsuitable for the analysis of these samples in the negative ion mode. The second problem addressed was the limited choice of calibration standards offering a flexible selection of m/z values under m/z 1000. This study presents a modified MALDI-FT-ICR-MS method for the analysis of resinous materials, which incorporates a novel matrix compound, 2-aminoacridine for the negative ion mode analysis and extends the selection of internal standards with m/z <1000 for both positive (15 different phosphazenium cations) and negative (anions of four fluorine-rich sulpho-compounds) ion mode. The novel internal calibration compounds and matrix material were tested for the analysis of various natural resins and real-life varnish samples taken from cultural heritage objects. Copyright © 2017 John Wiley & Sons, Ltd.

Mass recalibration of FT-ICR mass spectrometry imaging data using the average frequency shift of ambient ions

Achieving and maintaining high mass measurement accuracy (MMA) throughout a mass spectrometry imaging (MSI) experiment is vital to the identification of the observed ions. However, when using FTMS instruments, fluctuations in the total ion abundance at each pixel due to inherent biological variation in the tissue section can introduce space charge effects that systematically shift the observed mass. Herein we apply a recalibration based on the observed cyclotron frequency shift of ions found in the ambient laboratory environment, polydimethylcyclosiloxanes (PDMS). This calibration method is capable of achieving part per billion (ppb) mass accuracy with relatively high precision for an infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) MSI dataset. Comparisons with previously published mass calibration approaches are also presented.

Multiplex mass spectrometric imaging with polarity switching for concurrent acquisition of positive and negative ion images

We have recently developed a multiplex mass spectrometry imaging (MSI) method which incorporates high mass resolution imaging and MS/MS and MS(3) imaging of several compounds in a single data acquisition utilizing a hybrid linear ion trap-Orbitrap mass spectrometer (Perdian and Lee, Anal. Chem. 82, 9393-9400, 2010). Here we extend this capability to obtain positive and negative ion MS and MS/MS spectra in a single MS imaging experiment through polarity switching within spiral steps of each raster step. This methodology was demonstrated for the analysis of various lipid class compounds in a section of mouse brain. This allows for simultaneous imaging of compounds that are readily ionized in positive mode (e.g., phosphatidylcholines and sphingomyelins) and those that are readily ionized in negative mode (e.g., sulfatides, phosphatidylinositols and phosphatidylserines). MS/MS imaging was also performed for a few compounds in both positive and negative ion mode within the same experimental set-up. Insufficient stabilization time for the Orbitrap high voltage leads to slight deviations in observed masses, but these deviations are systematic and were easily corrected with a two-point calibration to background ions.

Correlated imaging--a grand challenge in chemical analysis

Correlated chemical imaging is an emerging strategy for acquisition of images by combining information from multiplexed measurement platforms to track, visualize, and interpret in situ changes in the structure, organization, and activities of interesting chemical systems, frequently spanning multiple decades in space and time. Acquiring and correlating information from complementary imaging experiments has the potential to expose complex chemical behavior in ways that are simply not available from single methods applied in isolation, thereby greatly amplifying the information gathering power of imaging experiments. However, in order to correlate image information across platforms, a number of issues must be addressed. First, signals are obtained from disparate experiments with fundamentally different figures of merit, including pixel size, spatial resolution, dynamic range, and acquisition rates. In addition, images are often acquired on different instruments in different locations, so the sample must be registered spatially so that the same area of the sample landscape is addressed. The signals acquired must be correlated in both spatial and temporal domains, and the resulting information has to be presented in a way that is readily understood. These requirements pose special challenges for image cross-correlation that go well beyond those posed in single technique imaging approaches. The special opportunities and challenges that attend correlated imaging are explored by specific reference to correlated mass spectrometric and Raman imaging, a topic of substantial and growing interest.

Memory efficient principal component analysis for the dimensionality reduction of large mass spectrometry imaging data sets

A memory efficient algorithm for the computation of principal component analysis (PCA) of large mass spectrometry imaging data sets is presented. Mass spectrometry imaging (MSI) enables two- and three-dimensional overviews of hundreds of unlabeled molecular species in complex samples such as intact tissue. PCA, in combination with data binning or other reduction algorithms, has been widely used in the unsupervised processing of MSI data and as a dimentionality reduction method prior to clustering and spatial segmentation. Standard implementations of PCA require the data to be stored in random access memory. This imposes an upper limit on the amount of data that can be processed, necessitating a compromise between the number of pixels and the number of peaks to include. With increasing interest in multivariate analysis of large 3D multislice data sets and ongoing improvements in instrumentation, the ability to retain all pixels and many more peaks is increasingly important. We present a new method which has no limitation on the number of pixels and allows an increased number of peaks to be retained. The new technique was validated against the MATLAB (The MathWorks Inc., Natick, Massachusetts) implementation of PCA (princomp) and then used to reduce, without discarding peaks or pixels, multiple serial sections acquired from a single mouse brain which was too large to be analyzed with princomp. Then, k-means clustering was performed on the reduced data set. We further demonstrate with simulated data of 83 slices, comprising 20,535 pixels per slice and equaling 44 GB of data, that the new method can be used in combination with existing tools to process an entire organ. MATLAB code implementing the memory efficient PCA algorithm is provided.

Advanced mass calibration and visualization for FT-ICR mass spectrometry imaging

Mass spectrometry imaging by Fourier transform ion cyclotron resonance (FT-ICR) yields hundreds of unique peaks, many of which cannot be resolved by lower performance mass spectrometers. The high mass accuracy and high mass resolving power allow confident identification of small molecules and lipids directly from biological tissue sections. Here, calibration strategies for FT-ICR MS imaging were investigated. Sub-parts-per-million mass accuracy is demonstrated over an entire tissue section. Ion abundance fluctuations are corrected by addition of total and relative ion abundances for a root-mean-square error of 0.158 ppm on 16,764 peaks. A new approach for visualization of FT-ICR MS imaging data at high resolution is presented. The "Mosaic Datacube" provides a flexible means to visualize the entire mass range at a mass spectral bin width of 0.001 Da. The high resolution Mosaic Datacube resolves spectral features not visible at lower bin widths, while retaining the high mass accuracy from the calibration methods discussed.

Localization and imaging of gangliosides in mouse brain tissue sections by laserspray ionization inlet

A new ionization method for the analysis of fragile gangliosides without undesired fragmentation or salt adduction is presented. In laserspray ionization inlet (LSII), the matrix/analyte sample is ablated at atmospheric pressure, and ionization takes place in the ion transfer capillary of the mass spectrometer inlet by a process that is independent of a laser wavelength or voltage. The softness of LSII allows the identification of gangliosides up to GQ1 with negligible sialic acid loss. This is of importance to the field of MS imaging, as undesired fragmentation has made it difficult to accurately map the spatial distribution of fragile ganglioside lipids in tissue. Proof-of-principle structural characterization of endogenous gangliosides using MS(n) fragmentation of multiply charged negative ions on a LTQ Velos and subsequent imaging of the GD1 ganglioside is demonstrated. This is the first report of multiply charged negative ions using inlet ionization. We find that GD1 is detected at higher levels in the mouse cortex and hippocampus compared with the thalamus. In LSII with the laser aligned in transmission geometry relative to the inlet, images were obtained in approximately 60 min using an inexpensive nitrogen laser.

A gain and bandwidth enhanced transimpedance preamplifier for Fourier-transform ion cyclotron resonance mass spectrometry

The nature of the ion signal from a 12-T Fourier-transform ion cyclotron resonance mass spectrometer and the electronic noise were studied to further understand the electronic detection limit. At minimal cost, a new transimpedance preamplifier was designed, computer simulated, built, and tested. The preamplifier design pushes the electronic signal-to-noise performance at room temperature to the limit, because of its enhanced tolerance of the capacitance of the detection device, lower intrinsic noise, and larger flat mid-band gain (input current noise spectral density of around 1 pA/√Hz when the transimpedance is about 85 dBΩ). The designed preamplifier has a bandwidth of ~3 kHz to 10 MHz, which corresponds to the mass-to-charge ratio, m/z, of approximately 18 to 61 k at 12 T. The transimpedance and the bandwidth can be easily adjusted by changing the value of passive components. The feedback limitation of the circuit is discussed. With the maximum possible transimpedance of 5.3 MΩ when using an 0402 surface mount resistor, the preamplifier was estimated to be able to detect ~110 charges in a single scan.

Vacuum compatible sample positioning device for matrix assisted laser desorption∕ionization Fourier transform ion cyclotron resonance mass spectrometry imaging

The high mass accuracy and resolving power of Fourier transform ion cyclotron resonance mass spectrometers (FT-ICR MS) make them ideal mass detectors for mass spectrometry imaging (MSI), promising to provide unmatched molecular resolution capabilities. The intrinsic low tolerance of FT-ICR MS to RF interference, however, along with typically vertical positioning of the sample, and MSI acquisition speed requirements present numerous engineering challenges in creating robotics capable of achieving the spatial resolution to match. This work discusses a two-dimensional positioning stage designed to address these issues. The stage is capable of operating in ∼1 × 10(-8) mbar vacuum. The range of motion is set to 100 mm × 100 mm to accommodate large samples, while the positioning accuracy is demonstrated to be less than 0.4 micron in both directions under vertical load over the entire range. This device was integrated into three different matrix assisted laser desorption∕ionization (MALDI) FT-ICR instruments and showed no detectable RF noise. The "oversampling" MALDI-MSI experiments, under which the sample is completely ablated at each position, followed by the target movement of the distance smaller than the laser beam, conducted on the custom-built 7T FT-ICR MS demonstrate the stability and positional accuracy of the stage robotics which delivers high spatial resolution mass spectral images at a fraction of the laser spot diameter.