Evaluation of Inlet Temperature with Three Sprayer Designs for Desorption Electrospray Ionization Mass Spectrometry Tissue Analysis.

Mass spectrometry imaging (MSI) allows for the spatially resolved detection of endogenous and exogenous molecules and atoms in biological samples, typically prepared as thin tissue sections. Desorption electrospray ionization (DESI) is one of the most commonly utilized MSI modalities in preclinical research. DESI ion source technology is still rapidly evolving, with new sprayer designs and heated inlet capillaries having recently been incorporated in commercially available systems. In this study, three iterations of DESI sprayer designs are evaluated: (1) the first, and until recently only, commercially available Waters sprayer; (2) a developmental desorption electro-flow focusing ionization (DEFFI)-type sprayer; and (3) a prototype of the newly released Waters commercial sprayer. A heated inlet capillary is also employed, allowing for controlled inlet temperatures up to 500 °C. These three sprayers are evaluated by comparative tissue imaging analyses of murine testes across this temperature range. Single ion intensity versus temperature trends are evaluated as exemplar cases for putatively identified species of interest, such as lactate and glutamine. A range of trends are observed, where intensities follow either increasing, decreasing, bell-shaped, or other trends with temperature. Data for all sprayers show approximately similar trends for the ions studied, with the commercial prototype sprayer (sprayer version 3) matching or outperforming the other sprayers for the ions investigated. Finally, the mass spectra acquired using sprayer version 3 are evaluated by uniform manifold approximation and projection (UMAP) and k-means clustering. This approach is shown to provide valuable insight that is complementary to the presented univariate evaluation for reviewing the parameter space in this study. Full spectral temperature optimization data are provided as supporting data to enable other researchers to design experiments that are optimal for specific ions.

Metabolic profiling stratifies colorectal cancer and reveals adenosylhomocysteinase as a therapeutic target.

The genomic landscape of colorectal cancer (CRC) is shaped by inactivating mutations in tumour suppressors such as APC, and oncogenic mutations such as mutant KRAS. Here we used genetically engineered mouse models, and multimodal mass spectrometry-based metabolomics to study the impact of common genetic drivers of CRC on the metabolic landscape of the intestine. We show that untargeted metabolic profiling can be applied to stratify intestinal tissues according to underlying genetic alterations, and use mass spectrometry imaging to identify tumour, stromal and normal adjacent tissues. By identifying ions that drive variation between normal and transformed tissues, we found dysregulation of the methionine cycle to be a hallmark of APC-deficient CRC. Loss of Apc in the mouse intestine was found to be sufficient to drive expression of one of its enzymes, adenosylhomocysteinase (AHCY), which was also found to be transcriptionally upregulated in human CRC. Targeting of AHCY function impaired growth of APC-deficient organoids in vitro, and prevented the characteristic hyperproliferative/crypt progenitor phenotype driven by acute deletion of Apc in vivo, even in the context of mutant Kras. Finally, pharmacological inhibition of AHCY reduced intestinal tumour burden in ApcMin/+ mice indicating its potential as a metabolic drug target in CRC.

Atmospheric-Pressure Infrared Laser-Ablation Plasma-Postionization Mass Spectrometry Imaging of Formalin-Fixed Paraffin-Embedded (FFPE) and Fresh-Frozen Tissue Sections with No Sample Preparation.

Mass spectrometry imaging (MSI) encompasses a powerful suit of techniques which provide spatially resolved atomic and molecular information from almost any sample type. MSI is now widely used in preclinical research to provide insight into metabolic phenotypes of disease. Typically, fresh-frozen tissue preparations are considered optimal for biological MSI and other traditional preservation methods such as formalin fixation, alone or with paraffin embedding (FFPE), are considered less optimal or even incompatible. Due to the prevalence of FFPE tissue storage, particularly for rare and therefore high-value tissue samples, there is substantial motivation for optimizing MSI methods for analysis of FFPE tissue. Here, we present a novel modality, atmospheric-pressure infrared laser-ablation plasma postionization (AP-IR-LA-PPI), with the first proof-of-concept examples of MSI for FFPE and fresh-frozen tissues, with no post-sectioning sample preparation. We present ion images from FFPE and fresh tissues in positive and negative ion modes. Molecular annotations (via the Metaspace annotation engine) and on-tissue MS/MS provide additional confidence that the detected ions arise from a broad range of metabolite and lipid classes from both FFPE and fresh-frozen tissues.

Modality Agnostic Model for Spatial Resolution in Mass Spectrometry Imaging: Application to MALDI MSI Data.

Image resolution in mass spectrometry imaging (MSI) is governed by the sampling probe, the motion of the stage relative to the probe, and the noise inherent for the sample and instrumentation employed. A new image formation model accounting for these variables is presented here. The model shows that the size of the probe, stage velocity, and the rate at which the probe consumes material from the surface govern the amount of blur present in the image. However, the main limiting factor for resolution is the signal-to-noise ratio (SNR). To evaluate blurring and noise effects, a new computational method for measuring lateral resolution in MSI is proposed. A spectral decomposition of the observed image signal and noise is used to determine a resolution number. To evaluate this technique, a silver step edge was prepared. This device was imaged at different pixels sizes using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI). A modulation transfer function (MTF) and a noise power spectrum (NPS) were computed for each single-ion image, and resolution was defined as the point of intersection between the MTF and the NPS. Finally, the algorithm was also applied to a MALDI MSI tissue data set.

The amino acid transporter SLC7A5 is required for efficient growth of KRAS-mutant colorectal cancer.

Oncogenic KRAS mutations and inactivation of the APC tumor suppressor co-occur in colorectal cancer (CRC). Despite efforts to target mutant KRAS directly, most therapeutic approaches focus on downstream pathways, albeit with limited efficacy. Moreover, mutant KRAS alters the basal metabolism of cancer cells, increasing glutamine utilization to support proliferation. We show that concomitant mutation of Apc and Kras in the mouse intestinal epithelium profoundly rewires metabolism, increasing glutamine consumption. Furthermore, SLC7A5, a glutamine antiporter, is critical for colorectal tumorigenesis in models of both early- and late-stage metastatic disease. Mechanistically, SLC7A5 maintains intracellular amino acid levels following KRAS activation through transcriptional and metabolic reprogramming. This supports the increased demand for bulk protein synthesis that underpins the enhanced proliferation of KRAS-mutant cells. Moreover, targeting protein synthesis, via inhibition of the mTORC1 regulator, together with Slc7a5 deletion abrogates the growth of established Kras-mutant tumors. Together, these data suggest SLC7A5 as an attractive target for therapy-resistant KRAS-mutant CRC.

Implications of Peak Selection in the Interpretation of Unsupervised Mass Spectrometry Imaging Data Analyses.

Mass spectrometry imaging can produce large amounts of complex spectral and spatial data. Such data sets are often analyzed with unsupervised machine learning approaches, which aim at reducing their complexity and facilitating their interpretation. However, choices made during data processing can impact the overall interpretation of these analyses. This work investigates the impact of the choices made at the peak selection step, which often occurs early in the data processing pipeline. The discussion is done in terms of visualization and interpretation of the results of two commonly used unsupervised approaches: t-distributed stochastic neighbor embedding and k-means clustering, which differ in nature and complexity. Criteria considered for peak selection include those based on hypotheses (exemplified herein in the analysis of metabolic alterations in genetically engineered mouse models of human colorectal cancer), particular molecular classes, and ion intensity. The results suggest that the choices made at the peak selection step have a significant impact in the visual interpretation of the results of either dimensionality reduction or clustering techniques and consequently in any downstream analysis that relies on these. Of particular significance, the results of this work show that while using the most abundant ions can result in interesting structure-related segmentation patterns that correlate well with histological features, using a smaller number of ions specifically selected based on prior knowledge about the biochemistry of the tissues under investigation can result in an easier-to-interpret, potentially more valuable, hypothesis-confirming result. Findings presented will help researchers understand and better utilize unsupervised machine learning approaches to mine high-dimensionality data.

Direct Tissue Mass Spectrometry Imaging by Atmospheric Pressure UV-Laser Desorption Plasma Postionization.

Matrix-assisted laser desorption ionization (MALDI) operated at atmospheric pressure has been shown to be a promising technique for mass spectrometry imaging of biological tissues at high spatial resolution. Recent studies have shown several orders of magnitude improvement in sensitivity afforded by coupling with a low-temperature plasma (LTP) for postionization. In this work we report the first results from "matrix-free" imaging using our atmospheric pressure (AP) transmission mode (TM) (MA)LDI source with LTP postionization. Direct MSI analysis of murine testis with no sample preparation after tissue sectioning enabled imaging of a range of lipid classes at pixel sizes of 25 µm. We compared results from the matrix-free methods with MALDI experiments in which the matrix was applied on top, underneath, or layered as a sandwich. The sandwich preparation was found to lead to ion yields approximately 2- or 3-fold higher than the other methods, indicating that the addition of a light absorbing matrix remains beneficial. Nonetheless, LDI methods confer a range of advantages, and the sensitivity improvements provided by postionization strategies are a promising step toward high-efficiency laser sampling under ambient conditions.

Atmospheric Pressure MALDI Mass Spectrometry Imaging Using In-Line Plasma Induced Postionization.

Atmospheric pressure ionization methods confer a number of advantages over more traditional vacuum based techniques, in particular ease of hyphenation to a range of mass spectrometers. For atmospheric pressure matrix assisted desorption/ionization (AP-MALDI), several ion sources, operating in a range of geometries have been reported. Most of these platforms have, to date, generally demonstrated relatively low ion yields and/or poor ion transmission compared to vacuum sources. To improve the detection of certain ions, we have developed a second-generation transmission mode (TM) AP-MALDI imaging platform with in-line plasma postionization using the commercially available SICRIT device, replacing the previously used low temperature plasma probe from our developmental AP-TM-MALDI stage. Both plasma devices produce a significant ionization enhancement for a range of compounds, but the overall higher enhancement obtained by the SICRIT device in addition to the ease of installation and the minimal need for optimization presents this commercially available tool as an attractive method for simple postionization in AP-MALDI MSI.

MALDI-2 at Atmospheric Pressure-Parameter Optimization and First Imaging Experiments.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a powerful label-free technique for mapping the spatial distribution of biomolecules directly from tissue. However, like most other MSI techniques, it suffers from low ionization yields and ion suppression effects for biomolecules that might be of interest for a specific application at hand. Recently, a form of laser postionization was introduced (coined MALDI-2) that critically boosts the ion yield for many glyco- and phospholipids by several orders of magnitude and makes the detection of further biomolecular species possible. While the MALDI-2 technique is being increasingly applied by the MSI community, it is still only implemented in fine vacuum ion sources in a pressure range of about 1-10 mbar. Here, we show the first implementation of the technique to a custom-built atmospheric pressure ion source coupled to an Orbitrap Elite system. We present results from parameter optimization of MALDI-2 at atmospheric pressure, compare our findings to previously published fine vacuum data, and show first imaging results from mouse cerebellum with a 20 µm pixel size. Our findings broaden the feasibility of the technique to overall more flexible atmospheric pressure ion sources.

Correlative Hyperspectral Imaging Using a Dimensionality-Reduction-Based Image Fusion Method.

Chemical imaging techniques are increasingly being used in combination to achieve a greater understanding of a sample. This is especially true in the case of mass spectrometry imaging (MSI), where the use of different ionization sources allows detection of different classes of molecules across a range of spatial resolutions. There has been significant recent effort in the development of data fusion algorithms that attempt to combine the benefits of multiple techniques, such that the output provides additional information that would have not been present or obvious from the individual techniques alone. However, the majority of the data fusion methods currently in use rely on image registration to generate the fused data and therefore can suffer from artifacts caused by interpolation. Here, we present a method for data fusion that does not incorporate interpolation-based artifacts into the final fused data, applied to data acquired from multiple chemical imaging modalities. The method is evaluated using simulated data and a model polymer blend sample, before being applied to biological samples of mouse brain and lung.

Imaging drugs, metabolites and biomarkers in rodent lung: a DESI MS strategy for the evaluation of drug-induced lipidosis.

Within drug development and pre-clinical trials, a common, significant and poorly understood event is the development of drug-induced lipidosis in tissues and cells. In this manuscript, we describe a mass spectrometry imaging strategy, involving repeated analysis of tissue sections by DESI MS, in positive and negative polarities, using MS and MS/MS modes. We present results of the detected distributions of the administered drug, drug metabolites, lipid molecules and a putative marker of lipidosis, di-docosahexaenoyl (22:6)-bis(monoacylglycerol) phosphate (di-22:6-BMP). A range of strategies have previously been reported for detection, isolation and identification of this compound, which is an isomer of di-docosahexaenoic (22:6 n-3) phosphatidylglycerol (di-22:6 PG), a commonly found lipid that acts as a surfactant in lung tissues. We show that MS imaging using MS/MS can be used to differentiate these compounds of identical mass, based upon the different distributions of abundant fragment ions. Registration of images of these fragments, and detected drugs and metabolites, is presented as a new method for studying drug-induced lipidosis in tissues. Graphical abstract.

Comparison of Oral, Intranasal and Aerosol Administration of Amiodarone in Rats as a Model of Pulmonary Phospholipidosis.

'Foamy' alveolar macrophages (FAM) observed in nonclinical toxicology studies during inhaled drug development may indicate drug-induced phospholipidosis, but can also derive from adaptive non-adverse mechanisms. Orally administered amiodarone is currently used as a model of pulmonary phospholipidosis and it was hypothesized that aerosol administration would produce phospholipidosis-induced FAM that could be characterized and used in comparative inhalation toxicology. Han-Wistar rats were given amiodarone via (1) intranasal administration (6.25 mg/kg) on two days, (2) aerosol administration (3 mg/kg) on two days, (3) aerosol administration (10 mg/kg) followed by three days of 30 mg/kg or (4) oral administration (100 mg/kg) for 7 days. Alveolar macrophages in bronchoalveolar lavage were evaluated by differential cell counting and high content fluorescence imaging. Histopathology and mass-spectrometry imaging (MSI) were performed on lung slices. The higher dose aerosolised amiodarone caused transient pulmonary inflammation (p < 0.05), but only oral amiodarone resulted in FAM (p < 0.001). MSI of the lungs of orally treated rats revealed a homogenous distribution of amiodarone and a putative phospholipidosis marker, di-22:6 bis-monoacylglycerol, throughout lung tissue whereas aerosol administration resulted in localization of both compounds around the airway lumen. Thus, unlike oral administration, aerosolised amiodarone failed to produce the expected FAM responses.

The Influence of MS Imaging Parameters on UV-MALDI Desorption and Ion Yield.

Ultraviolet matrix-assisted laser desorption/ionization mass spectrometry imaging (UV-MALDI MSI) is a widely used technique for imaging molecular distributions within biological systems. While much work exists concerning desorption in UV-MALDI MS, the effects of commonly varied parameters for imaging applications (repetition rate, use of continuous raster mode and raster speed), which determine spatial resolution and limits of detection for the technique, remain largely unknown. We use multiple surface characterization modalities to obtain quantitative measurements of material desorption and analyte ion yield in thin film model systems of two matrix compounds, arising from different UV-MALDI MSI sampling conditions. Observed changes in resulting ablation feature point to matrix-dependent spatial resolution and laser-induced matrix modification effects. Analyte ion yields of 10-9 to 10-6 are observed. Complex changes in ion yield, between spot and raster sampling and arising from varied laser repetition rate and raster speed, are observed. Graphical Abstract.

Construction and testing of an atmospheric-pressure transmission-mode matrix assisted laser desorption ionisation mass spectrometry imaging ion source with plasma ionisation enhancement.

Matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) at atmospheric pressure (AP) is, with a few notable exceptions, overshadowed by its vacuum based forms and AP transmission mode (TM) MALDI-MS lacks the up-take its potential benefits might suggest. The reasons for this are not fully understood and it is clear further development is required to realise the flexibility and power of this ionisation method and geometry. Here we report the build of a new AP-TM-MALDI-MSI ion source with plasma ionisation enhancement. This novel ion source is used to analyse a selection of increasingly complex systems from molecular standards to murine brain tissue sections. Significant enhancement of detected ion intensity is observed in both positive and negative ion mode in all systems, with up to 2000 fold increases observed for a range of tissue endogenous species. The substantial improvements conferred by the plasma enhancement are then employed to demonstrate the acquisition of proof of concept tissue images, with high quality spectra obtained down to 10 × 10 µm pixel size.

A methodological inter-comparison study on the detection of surface contaminant sodium dodecyl sulfate applying ambient- and vacuum-based techniques.

Biomedical devices are complex products requiring numerous assembly steps along the industrial process chain, which can carry the potential of surface contamination. Cleanliness has to be analytically assessed with respect to ensuring safety and efficacy. Although several analytical techniques are routinely employed for such evaluation, a reliable analysis chain that guarantees metrological traceability and quantification capability is desirable. This calls for analytical tools that are cascaded in a sensible way to immediately identify and localize possible contamination, both qualitatively and quantitatively. In this systematic inter-comparative approach, we produced and characterized sodium dodecyl sulfate (SDS) films mimicking contamination on inorganic and organic substrates, with potential use as reference materials for ambient techniques, i.e., ambient mass spectrometry (AMS), infrared and Raman spectroscopy, to reliably determine amounts of contamination. Non-invasive and complementary vibrational spectroscopy techniques offer a priori chemical identification with integrated chemical imaging tools to follow the contaminant distribution, even on devices with complex geometry. AMS also provides fingerprint outputs for a fast qualitative identification of surface contaminations to be used at the end of the traceability chain due to its ablative effect on the sample. To absolutely determine the mass of SDS, the vacuum-based reference-free technique X-ray fluorescence was employed for calibration. Convex hip liners were deliberately contaminated with SDS to emulate real biomedical devices with an industrially relevant substance. Implementation of the aforementioned analytical techniques is discussed with respect to combining multimodal technical setups to decrease uncertainties that may arise if a single technique approach is adopted. Graphical abstract ᅟ.

Matrix Optical Absorption in UV-MALDI MS.

In ultraviolet matrix-assisted laser desorption/ionization mass spectrometry (UV-MALDI MS) matrix compound optical absorption governs the uptake of laser energy, which in turn has a strong influence on experimental results. Despite this, quantitative absorption measurements are lacking for most matrix compounds. Furthermore, despite the use of UV-MALDI MS to detect a vast range of compounds, investigations into the effects of laser energy have been primarily restricted to single classes of analytes. We report the absolute solid state absorption spectra of the matrix compounds α-cyano-4-hydroxycinnamic acid (CHCA), para-nitroaniline (PNA), 2-mercaptobenzothiazole (MBT), 2,5-dihydroxybenzoic acid (2,5-DHB), and 2,4,6-trihydroxyacetophenone (THAP). The desorption/ionization characteristics of these matrix compounds with respect to laser fluence was investigated using mixed systems of matrix with either angiotensin II, PC(34:1) lipid standard, or haloperidol, acting as representatives for typical classes of analyte encountered in UV-MALDI MS. The first absolute solid phase spectra for PNA, MBT, and THAP are reported; additionally, inconsistencies between previously published spectra for CHCA are resolved. In light of these findings, suggestions are made for experimental optimization with regards to matrix and laser wavelength selection. The relationship between matrix optical cross-section and wavelength-dependant threshold fluence, fluence of maximum ion yield, and R, a new descriptor for the change in ion intensity with fluence, are described. A matrix cross-section of 1.3 × 10-17 cm-2 was identified as a potential minimum for desorption/ionization of analytes. Graphical Abstract ᅟ.

Two-Phase and Graph-Based Clustering Methods for Accurate and Efficient Segmentation of Large Mass Spectrometry Images.

Clustering is widely used in MSI to segment anatomical features and differentiate tissue types, but existing approaches are both CPU and memory-intensive, limiting their application to small, single data sets. We propose a new approach that uses a graph-based algorithm with a two-phase sampling method that overcomes this limitation. We demonstrate the algorithm on a range of sample types and show that it can segment anatomical features that are not identified using commonly employed algorithms in MSI, and we validate our results on synthetic MSI data. We show that the algorithm is robust to fluctuations in data quality by successfully clustering data with a designed-in variance using data acquired with varying laser fluence. Finally, we show that this method is capable of generating accurate segmentations of large MSI data sets acquired on the newest generation of MSI instruments and evaluate these results by comparison with histopathology.

Chemical intervention in plant sugar signalling increases yield and resilience.

The pressing global issue of food insecurity due to population growth, diminishing land and variable climate can only be addressed in agriculture by improving both maximum crop yield potential and resilience. Genetic modification is one potential solution, but has yet to achieve worldwide acceptance, particularly for crops such as wheat. Trehalose-6-phosphate (T6P), a central sugar signal in plants, regulates sucrose use and allocation, underpinning crop growth and development. Here we show that application of a chemical intervention strategy directly modulates T6P levels in planta. Plant-permeable analogues of T6P were designed and constructed based on a 'signalling-precursor' concept for permeability, ready uptake and sunlight-triggered release of T6P in planta. We show that chemical intervention in a potent sugar signal increases grain yield, whereas application to vegetative tissue improves recovery and resurrection from drought. This technology offers a means to combine increases in yield with crop stress resilience. Given the generality of the T6P pathway in plants and other small-molecule signals in biology, these studies suggest that suitable synthetic exogenous small-molecule signal precursors can be used to directly enhance plant performance and perhaps other organism function.

SpectralAnalysis: Software for the Masses.

The amount of data produced by spectral imaging techniques, such as mass spectrometry imaging, is rapidly increasing as technology and instrumentation advances. This, combined with an increasingly multimodal approach to analytical science, presents a significant challenge in the handling of large data from multiple sources. Here, we present software that can be used through the entire analysis workflow, from raw data through preprocessing (including a wide range of methods for smoothing, baseline correction, normalization, and image generation) to multivariate analysis (for example, memory efficient principal component analysis (PCA), non-negative matrix factorization (NMF), maximum autocorrelation factor (MAF), and probabilistic latent semantic analysis (PLSA)), for data sets acquired from single experiments to large multi-instrument, multimodality, and multicenter studies. SpectralAnalysis was also developed with extensibility in mind to stimulate development, comparisons, and evaluation of data analysis algorithms.

Probing the Relationship Between Detected Ion Intensity, Laser Fluence, and Beam Profile in Thin Film and Tissue in MALDI MSI.

Matrix assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) is increasingly widely used to provide information regarding molecular location within tissue samples. The nature of the photon distribution within the irradiated region, the laser beam profile, and fluence, will significantly affect the form and abundance of the detected ions. Previous studies into these phenomena have focused on circular-core optic fibers or Gaussian beam profiles irradiating dried droplet preparations, where peptides were employed as the analyte of interest. Within this work, we use both round and novel square core optic fibers of 100 and 50 µm diameter to deliver the laser photons to the sample. The laser beam profiles were recorded and analyzed to quantify aspects of the photon distributions and their relation to the spectral data obtained with each optic fiber. Beam profiles with a relatively small number of large beam profile features were found to give rise to the lowest threshold fluence. The detected ion intensity versus fluence relationship was investigated, for the first time, in both thin films of α-cyano-4-hydroxycinnamic acid (CHCA) with phosphatidylcholine (PC) 34:1 lipid standard and in CHCA coated murine tissue sections for both the square and round optic fibers in continuous raster imaging mode. The fluence threshold of ion detection was found to occur at between ~14 and ~64 J/m(2) higher in tissue compared with thin film for the same lipid, depending upon the optic fiber employed. The image quality is also observed to depend upon the fluence employed during image acquisition. Graphical Abstract ᅟ.