Mass spectrometric imaging for biomedical tissue analysis

A patch-based super resolution algorithm for improving image resolution in clinical mass spectrometry

Mass spectrometry imaging (MSI) and histology are complementary analytical tools. Integration of the two imaging modalities can enhance the spatial resolution of the MSI beyond its experimental limits. Patch-based super resolution (PBSR) is a method where high spatial resolution features from one image modality guide the reconstruction of a low resolution image from a second modality. The principle of PBSR lies in image redundancy and aims at finding similar pixels in the neighborhood of a central pixel that are then used to guide reconstruction of the central pixel. In this work, we employed PBSR to increase the resolution of MSI. We validated the proposed pipeline by using a phantom image (micro-dissected logo within a tissue) and mouse cerebellum samples. We compared the performance of the PBSR with other well-known methods: linear interpolation (LI) and image fusion (IF). Quantitative and qualitative assessment showed advantage over the former and comparability with the latter. Furthermore, we demonstrated the potential applicability of PBSR in a clinical setting by accurately integrating structural (i.e., histological) and molecular (i.e., MSI) information from a case study of a dog liver.

Function of complement factor H and imaging of small molecules by MALDI-MSI in a methamphetamine behavioral sensitization model

BACKGROUND

At present, the harm of new-type drug, methamphetamine (METH), has gradually exceeded that of the traditional opioid drugs, and METH abuse has become a serious public health and social problem. In our previous study, complement factor H (CFH) was found to be upregulated in the sera of METH-addicted patients and rats and in certain brain regions in the rats.

METHODS

We used ELISA and immunofluorescence to confirm the changes in CFH in the serum and hippocampus of a METH behavioral sensitization mouse model, and C1q expression was also detected by immunofluorescence in the hippocampus. We aimed to elucidate the involvement of CFH and C1q in the mechanism of METH addiction. We also detected the distribution of various small molecules by matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) in select brain regions: the nucleus accumbens, the hippocampus and the ventral tegmental area.

RESULTS

The expression of CFH was upregulated in the serum and hippocampus of METH behavioral sensitization model mice, consistent with our previous research on conditioned place preference rats. In contrast, C1q decreased dramatically in the mossy fibers of the hippocampus. The results of small-molecule imaging by MALDI-MSI showed that the levels of K⁺, antioxidants, neurotransmitters, and ATP metabolism-related molecules were altered in different regions.

CONCLUSIONS

These results indicate the involvement of the complement system in the mechanism of METH addiction and validate the presence of oxidative stress, energy metabolism changes during addiction. This suggests the utility of further investigation into the above aspects.

Quantitative MALDI Imaging of Spatial Distributions and Dynamic Changes of Tetrandrine in Multiple Organs of Rats

Detailed spatio-temporal information on drug distribution in organs is of paramount importance to assess drug clinically-relevant properties and potential side-effects. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) as a label-free and sensitive imaging modality provides an additional means of accurately visualizing drug and its metabolites distributions in tissue sections. However, technical limitations, complex physiochemical environment of surface and low abundance of target drugs make quantitative MALDI imaging of drug and its metabolites quite challenging.

Methods: In this study, an internal standard correction strategy was applied for quantitative MALDI imaging of tetrandrine in multiple organs of rats including lung, liver, kidney, spleen, and heart. The feasibility and reliability of the developed quantitative MSI method were validated by conventional liquid chromatography-tandem MS (LC-MS/MS) analysis, and the two methods showed a significant correlation.

Results: The quantitative MALDI imaging method met the requirements of specificity, sensitivity and linearity. Tissue-specific spatio-temporal distribution patterns of tetrandrine in different organs were revealed after intravenous administration in the rat. Moreover, demethylated metabolite was detected in liver tissues.

Conclusions: The current work illustrates that quantitative MALDI imaging provides an alternative means of accurately addressing the problem of drug and its metabolites distribution in tissues, complementary to traditional LC-MS/MS of tissue homogenates and whole-body autoradiography (WBA). Quantitative spatio-chemical information obtained here can improve our understanding of pharmacokinetics (PK), pharmacodynamics (PD), and potential transient toxicities of tetrandrine in organs, and possibly direct further optimization of drug properties to reduce drug-induced organ toxicity.

Proteome Imaging: From Classic to Modern Mass Spectrometry-Based Molecular Histology

In order to overcome the limitations of classic imaging in Histology during the actually era of multiomics, the multi-color "molecular microscope" by its emerging "molecular pictures" offers quantitative and spatial information about thousands of molecular profiles without labeling of potential targets. Healthy and diseased human tissues, as well as those of diverse invertebrate and vertebrate animal models, including genetically engineered species and cultured cells, can be easily analyzed by histology-directed MALDI imaging mass spectrometry. The aims of this review are to discuss a range of proteomic information emerging from MALDI mass spectrometry imaging comparative to classic histology, histochemistry and immunohistochemistry, with applications in biology and medicine, concerning the detection and distribution of structural proteins and biological active molecules, such as antimicrobial peptides and proteins, allergens, neurotransmitters and hormones, enzymes, growth factors, toxins and others. The molecular imaging is very well suited for discovery and validation of candidate protein biomarkers in neuroproteomics, oncoproteomics, aging and age-related diseases, parasitoproteomics, forensic, and ecotoxicology. Additionally, in situ proteome imaging may help to elucidate the physiological and pathological mechanisms involved in developmental biology, reproductive research, amyloidogenesis, tumorigenesis, wound healing, neural network regeneration, matrix mineralization, apoptosis and oxidative stress, pain tolerance, cell cycle and transformation under oncogenic stress, tumor heterogeneity, behavior and aggressiveness, drugs bioaccumulation and biotransformation, organism's reaction against environmental penetrating xenobiotics, immune signaling, assessment of integrity and functionality of tissue barriers, behavioral biology, and molecular origins of diseases. MALDI MSI is certainly a valuable tool for personalized medicine and "Eco-Evo-Devo" integrative biology in the current context of global environmental challenges.

IR-MALDESI mass spectrometry imaging of underivatized neurotransmitters in brain tissue of rats exposed to tetrabromobisphenol A

There is a pressing need to develop tools for assessing possible neurotoxicity, particularly for chemicals where the mode of action is poorly understood. Tetrabromobisphenol A (TBBPA), a highly abundant brominated flame retardant, has lately been targeted for neurotoxicity analysis by concerned public health entities in the EU and USA because it is a suspected thyroid disruptor and neurotoxicant. In this study, infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) coupled to a Q Exactive Plus mass spectrometer was used for the analysis of neurotransmitters in the brains of rats exposed to TBBPA in gestation and lactation through their mothers. Three neurotransmitters of interest were studied in three selected regions of the brain: caudate putamen, substantia nigra (SN), and dorsal raphe. Stable isotope labeled (SIL) standards were used as internal standards and a means to achieve relative quantification. This study serves as a demonstration of a new application of IR-MALDESI, namely that neurotransmitter distributions can be confidently and rapidly imaged without derivatization.

Toward Higher Sensitivity in Quantitative MALDI Imaging Mass Spectrometry of CNS Drugs Using a Nonpolar Matrix

Tissue-specific ion suppression is an unavoidable matrix effect in MALDI mass spectrometry imaging (MALDI-MSI), the negative impact of which on precision and accuracy in quantitative MALDI-MSI can be reduced to some extent by applying isotope internal standards for normalization and matrix-matched calibration routines. The detection sensitivity still suffers, however, often resulting in significant loss of signal for the investigated analytes. An MSI application considerably affected by this phenomenon is the quantitative spatial analysis of central nervous system (CNS) drugs. Most of these drugs are low molecular weight, lipophilic compounds, which exhibit inefficient desorption and ionization during MALDI using conventional polar acidic matrices (CHCA, DHB). Here, we present the application of the (2-[(2 E)-3-(4- tert-butylphenyl)-2-methylprop-2-enylidene]malononitrile) matrix for high sensitivity imaging of CNS drugs in mouse brain sections. Since DCTB is usually described as an electron-transfer matrix, we provide a rationale (i.e., computational calculations of gas-phase proton affinity and ionization energy) for an additional proton-transfer ionization mechanism with this matrix. Furthermore, we compare the extent of signal suppression for five different CNS drugs when employing DCTB versus CHCA matrices. The results showed that the signal suppression was not only several times lower with DCTB than with CHCA but also depended on the specific tissue investigated. Finally, we present the application of DCTB and ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry to quantitative MALDI imaging of the anesthetic drug xylazine in mouse brain sections based on a linear matrix-matched calibration curve. DCTB afforded up to 100-fold signal intensity improvement over CHCA when comparing representative single MSI pixels and >440-fold improvement for the averaged mass spectrum of the adjacent tissue sections.

Biological tissue sample preparation for time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging is an analytical technique rapidly expanding in use in biological studies. This technique is based on high spatial resolution (50-100 nm), high surface sensitivity (1-2 nm top-layer), and statistical analytic power. In mass spectrometry imaging (MSI), sample preparation is a crucial step to maintaining the natural state of the biomolecules and providing accurate spatial information. However, a number of problems associated with temperature changes in tissue samples such as loss of original distribution due to undesired molecular migration during the sample preparation or reduced ionization efficiency make it difficult to accurately perform MSI. Although frozen hydrate analysis is the ideal sample preparation method to eliminate the effects of temperature, this approach is hindered by mechanical limitations. Alternatively, an adhesive-tape-supported mounting and freeze-drying preparation has been proposed. This paper provides a concise review of the sample preparation procedures, a review of current issues, and proposes efficacious solutions for ToF-SIMS imaging in biological research.

Strategy for marker-based differentiation of pro- and anti-inflammatory macrophages using matrix-assisted laser desorption/ionization mass spectrometry imaging

Macrophages are large phagocytes playing a crucial role in the development and progression of atherosclerosis. The phenotypic polarization and activation of macrophages in atherosclerotic plaques depends on their complex micro-environment and at the same time has a major impact on the vulnerability or stability of advanced atherosclerotic lesions. Many in vitro and in vivo studies have been designed to define markers for macrophage subtypes to better understand the mechanism of plaque progression but they have rather added to the confusion. Nonetheless, some of the in vitro defined macrophage subtypes, like the pro-inflammatory M1 or the anti-inflammatory M2a/b/c macrophage, have been shown to be present in atherosclerotic plaques. Herein, we developed a comprehensive workflow to distinguish between human in vitro differentiated pro-inflammatory M1 and anti-inflammatory M2a and M2c macrophages. The cells were analyzed using qPCR and FACS analyses for defining suitable markers on the transcript (mRNA) and protein level as well as MALDI MSI for the assignment of metabolic markers, which can be used for the identification of the corresponding macrophage subtypes in atherosclerotic plaques. Data obtained using both qPCR and FACS analyses were in agreement with the literature. For the analysis of the macrophages with MALDI MSI, a comprehensive workflow was developed and the obtained data were subjected to different statistical analysis methods like principal component analysis (PCA) to define markers for each macrophage type. Our MALDI MSI results revealed that the method produces reliable and reproducible results but that the heterogeneity of the monocytes derived from different donors is too high to define universal markers on the metabolic level. Moreover, the results show that a sample set of three biological replicates is not sufficient to obtain representative data and therefore we recommend performing ring experiments in which the samples are measured by different laboratories.

Lipid imaging for visualizing cilastatin amelioration of cisplatin-induced nephrotoxicity

Nephrotoxicity is a major limitation to cisplatin antitumor therapies. Cilastatin, an inhibitor of renal dehydropeptidase-I, was recently proposed as a promising nephroprotector against cisplatin toxicity, preventing apoptotic cell death. In this work, cilastatin nephroprotection was further investigated in a rat model, with a focus on its effect on 76 renal lipids altered by cisplatin, including 13 new cisplatin-altered mitochondrial cardiolipin species. Lipid imaging was performed with MALDI mass spectrometry imaging (MALDI-MSI) in kidney sections from treated rats. Cilastatin was proved to significantly diminish the lipid distribution alterations caused by cisplatin, lipid levels being almost completely recovered to those of control samples. The extent of recovery of cisplatin-altered lipids by cilastatin turned out to be relevant for discriminating direct or secondary lipid alterations driven by cisplatin. Lipid peroxidation induced by cisplatin was also shown to be reduced when cilastatin was administered. Importantly, significant groups separation was achieved during multivariate analysis of cortex and outer-medullary lipids, indicating that damaged kidney can be discerned from the nephroprotected and healthy groups and classified according to lipid distribution. Therefore, we propose MALDI-MSI as a powerful potential tool offering multimolecule detection possibilities to visualize and evaluate nephrotoxicity and nephroprotection based on lipid analysis.

Approaching cellular resolution and reliable identification in mass spectrometry imaging of tryptic peptides

On-tissue digestion has become the preferred method to identify proteins in mass spectrometry (MS) imaging. In this study, we report advances in data acquisition and protein identification for MS imaging after on-tissue digestion. Tryptic peptides in a coronal mouse brain section were measured at 50 μm pixel size and revealed detailed histological structures, e.g., the ependyma (consisting of one to two cell layers), which was confirmed by H&E staining. This demonstrates that MS imaging of tryptic peptides at or close to cellular resolution is within reach. We also describe a detailed identification workflow which resulted in the identification of 99 proteins (with 435 corresponding peptides), based on comparison with LC-MS/MS data and in silico digest. These results were obtained with stringent parameters, including high mass accuracy in imaging mode (RSME < 3 ppm) and at least two unique peptides per protein showing consistent spatial distribution. We identified almost 50% of proteins with at least four corresponding peptides. As there is no agreed approach for identification of proteins after on-tissue digestion yet, we discuss our workflow in detail and make the corresponding mass spectral data available as “open data” via ProteomeXchange (identifier PXD003172). With this, we would like to contribute to a more effective discussion and the development of new approaches for tryptic peptide identification in MS imaging. From an experimental point of view, we demonstrate the improvement due to the combination of high spatial resolution and high mass resolution/mass accuracy on a measurement at 25 μm pixel size in mouse cerebellum tissue. A whole body section of a mouse pub imaged at 50 μm pixel size (40 GB, 230,000 spectra) demonstrates the stability of our protocol. For this data set, we developed a workflow that is based on conversion to the common data format imzML and sequential application of freely available software tools. In combination, the presented results for spatial resolution, protein identification, and data processing constitute significant improvements for the field of on-tissue digestion.

Graphical abstract

Targeted Molecular Imaging Using Aptamers in Cancer

Imaging is not only seeing, but also believing. For targeted imaging modalities, nucleic acid aptamers have features such as superior recognition of structural epitopes and quick uptake in target cells. This explains the emergence of an evolved new class of aptamers into a wide spectrum of imaging applications over the last decade. Genetically encoded biosensors tagged with fluorescent RNA aptamers have been developed as intracellular imaging tools to understand cellular signaling and physiology in live cells. Cancer-specific aptamers labeled with fluorescence have been used for assessment of clinical tissue specimens. Aptamers conjugated with gold nanoparticles have been employed to develop innovative mass spectrometry tissue imaging. Also, use of chemically conjugated cancer-specific aptamers as probes for non-invasive and high-resolution imaging has been transformative for in vivo imaging in multiple cancers.

The metabolic axis of macrophage and immune cell polarization

The extracellular space of solid tumors ranges from being well-nurtured to being completely ischemic and can serve as a source of intratumoral heterogeneity, determining the behavior and molecular profiles of malignant and stromal cells. Here, we discuss how the metabolic tumor microenvironment modulates the phenotypes of the immune cells that infiltrate tumors, with an emphasis on tumor-associated macrophages. These cells constitute a diverse population that has pro-tumoral and anti-inflammatory properties, and are likened to anti-inflammatory ‘M2’ macrophages. Recent findings show how different metabolic microenvironments specify an array of phenotypic changes in macrophages. In tumors, extracellular metabolite levels vary predictably according to proximity to the vasculature, and phenotypic changes in tumor-associated macrophages and in other immune cells are also predictable. We speculate that this ‘metabolic axis’ of macrophage polarization modulates – and is modulated by – the response to inflammatory cues, creating a wide variety of possible phenotypic states. Understanding how extracellular metabolites influence cell phenotypes allows us to predict how tumor-associated macrophages and other tumor cells might change, with the aim of harnessing this predictability for therapy. Overall, we describe an emerging picture in which chemokines, growth factors and the metabolic tumor microenvironment act together to determine the phenotypes of tumor-infiltrating immune cells.

Summary: Extracellular metabolites can mediate cell communication and change transcriptional and functional aspects of tumor and normal cells. This Review focuses on how these metabolic cues affect the immune system with a special focus on tumor-associated macrophages.

Molecular composition of the human primary visual cortex profiled by multimodal mass spectrometry imaging

The primary visual cortex (area V1) is an extensively studied part of the cerebral cortex with well-characterized connectivity, cellular and molecular architecture and functions (for recent reviews see Amunts and Zilles, Neuron 88:1086-1107, 2015; Casagrande and Xu, Parallel visual pathways: a comparative perspective. The visual neurosciences, MIT Press, Cambridge, pp 494-506, 2004). In humans, V1 is defined by heavily myelinated fibers arriving from the radiatio optica that form the Gennari stripe in cortical layer IV, which is further subdivided into laminae IVa, IVb, IVcα and IVcβ. Due to this unique laminar pattern, V1 represents an excellent region to test whether multimodal mass spectrometric imaging could reveal novel biomolecular markers for a functionally relevant parcellation of the human cerebral cortex. Here we analyzed histological sections of three post-mortem brains with matrix-assisted laser desorption/ionization mass spectrometry imaging and laser ablation inductively coupled plasma mass spectrometry imaging to investigate the distribution of lipids, proteins and metals in human V1. We identified 71 peptides of 13 different proteins by in situ tandem mass spectrometry, of which 5 proteins show a differential laminar distribution pattern revealing the border between V1 and V2. High-accuracy mass measurements identified 123 lipid species, including glycerolipids, glycerophospholipids and sphingolipids, of which at least 20 showed differential distribution within V1 and V2. Specific lipids labeled not only myelinated layer IVb, but also IVa and especially IVc in a layer-specific manner, but also and clearly separated V1 from V2. Elemental imaging further showed a specific accumulation of copper in layer IV. In conclusion, multimodal mass spectrometry imaging identified novel biomolecular and elemental markers with specific laminar and inter-areal differences. We conclude that mass spectrometry imaging provides a promising new approach toward multimodal, molecule-based cortical parcellation.

Matrix-assisted laser desorption/ionization imaging mass spectrometry of intraperitoneally injected danegaptide (ZP1609) for treatment of stroke-reperfusion injury in mice

RATIONALE

This work focuses on direct matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) detection of intraperitoneally (IP)-injected dipeptide ZP1609 in mouse brain tissue. Direct analysis of drug detection in intact tissue sections provides distribution information that can impact drug development. MALDI-IMS capabilities of uncovering drug transport across the blood-brain barrier are demonstrated.

METHODS

Successful peptide detection using MALDI-IMS was achieved using a MALDI TOF/TOF system. Upon optimization of sample preparation procedures for dipeptide ZP1609, an additional tissue acidification procedure was found to greatly enhance signal detection. The imaging data acquired was able to determine successful transport of ZP1609 across the blood-brain barrier. Data obtained from MALDI-IMS can help shape our understanding of biological functions, disease progression, and effects of drug delivery.

RESULTS

Direct detection of ZP1609 throughout the brain tissue sections was observed from MALDI-MS images. However, in cases where there was induction of stroke, a peak of lower signal intensity was also detected in the target m/z region. Although distinct differences in signal intensity can be seen between control and experimental groups, fragments and adducts of ZP1609 were investigated using MALDI-IMS to verify detection of the target analyte.

CONCLUSIONS

Overall, the data reveals successful penetration of ZP1609 across the blood-brain barrier. The benefits of tissue acidification in the enhancement of detection sensitivity for low-abundance peptides were demonstrated. MALDI-IMS has been shown to be a useful technique in the direct detection of drugs within intact brain tissue sections.

Imaging and spatially resolved quantification of drug distribution in tissues by mass spectrometry

Mass spectrometry imaging (MSI) is a powerful label-free technique for visualizing drug and metabolite distributions in biological tissues. In this review, we discuss recent developments in MSI and spatial profiling technologies to visualize and quantify drug distributions in tissues. We also present recent examples of applications of these technologies for assessing drug distribution within tissues and individual cells. Finally, we focus on an emerging technique coupling laser capture microdissection (LCM) to quantitative mass spectrometry, which combines the respective advantages of imaging and conventional liquid chromatography mass spectrometry, and thus enables spatially resolved drug quantification.

High Spatial Resolution Imaging of Mouse Pancreatic Islets Using Nanospray Desorption Electrospray Ionization Mass Spectrometry

Nanospray Desorption Electrospray Ionization mass spectrometry imaging (nano-DESI MSI) enables ambient imaging of biological samples with high sensitivity and minimal sample pretreatment. Recently, we developed an approach for constant-distance mode MSI using shear force microscopy to precisely control the distance between the sample and the nano-DESI probe. Herein, we demonstrate the power of this approach for robust imaging of pancreatic islets with high spatial resolution of ∼11 μm. Pancreatic islets are difficult to characterize using traditional mass spectrometry approaches due to their small size (∼100 μm) and molecular heterogeneity. Nano-DESI MSI was used to examine the spatial localization of several lipid classes including phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), phosphatidylinositol (PI), and phosphatidylserine (PS) along with fatty acids and their metabolites (e.g., prostaglandins) in the individual islets and surrounding tissue. Several lipids were found to be substantially enhanced in the islets indicating these lipids may be involved in insulin secretion. Remarkably different distributions were observed for several pairs of Lyso PC (LPC) and PC species differing only by one double bond, such as LPC 18:1 vs LPC 18:0, PC 32:1 vs PC 32:0, and PC 34:2 vs PC 34:1. These findings indicate that minor variations in the fatty acid chain length and saturation have a pronounced effect on the localization of PC and LPC species in pancreatic islets. Interestingly, oxidized PC species observed experimentally were found to be specifically localized to pancreatic islets. These PCs are potential biomarkers for reactive oxygen species in the islets, which could be harmful to pancreatic beta cells. The experimental approach presented in this study will provide valuable information on the heterogeneity of individual pancreatic islets, which is difficult to assess using bulk characterization techniques.

Nondestructive tissue analysis for ex vivo and in vivo cancer diagnosis using a handheld mass spectrometry system

Conventional methods for histopathologic tissue diagnosis are labor- and time-intensive and can delay decision-making during diagnostic and therapeutic procedures. We report the development of an automated and biocompatible handheld mass spectrometry device for rapid and nondestructive diagnosis of human cancer tissues. The device, named MasSpec Pen, enables controlled and automated delivery of a discrete water droplet to a tissue surface for efficient extraction of biomolecules. We used the MasSpec Pen for ex vivo molecular analysis of 20 human cancer thin tissue sections and 253 human patient tissue samples including normal and cancerous tissues from breast, lung, thyroid, and ovary. The mass spectra obtained presented rich molecular profiles characterized by a variety of potential cancer biomarkers identified as metabolites, lipids, and proteins. Statistical classifiers built from the histologically validated molecular database allowed cancer prediction with high sensitivity (96.4%), specificity (96.2%), and overall accuracy (96.3%), as well as prediction of benign and malignant thyroid tumors and different histologic subtypes of lung cancer. Notably, our classifier allowed accurate diagnosis of cancer in marginal tumor regions presenting mixed histologic composition. Last, we demonstrate that the MasSpec Pen is suited for in vivo cancer diagnosis during surgery performed in tumor-bearing mouse models, without causing any observable tissue harm or stress to the animal. Our results provide evidence that the MasSpec Pen could potentially be used as a clinical and intraoperative technology for ex vivo and in vivo cancer diagnosis.

Quantitative SIMS Imaging of Agar-Based Microbial Communities

After several decades of widespread use for mapping elemental ions and small molecular fragments in surface science, secondary ion mass spectrometry (SIMS) has emerged as a powerful analytical tool for molecular imaging in biology. Biomolecular SIMS imaging has primarily been used as a qualitative technique; although the distribution of a single analyte can be accurately determined, it is difficult to map the absolute quantity of a compound or even to compare the relative abundance of one molecular species to that of another. We describe a method for quantitative SIMS imaging of small molecules in agar-based microbial communities. The microbes are cultivated on a thin film of agar, dried under nitrogen, and imaged directly with SIMS. By use of optical microscopy, we show that the area of the agar is reduced by 26 ± 2% (standard deviation) during dehydration, but the overall biofilm morphology and analyte distribution are largely retained. We detail a quantitative imaging methodology, in which the ion intensity of each analyte is (1) normalized to an external quadratic regression curve, (2) corrected for isomeric interference, and (3) filtered for sample-specific noise and lower and upper limits of quantitation. The end result is a two-dimensional surface density image for each analyte. The sample preparation and quantitation methods are validated by quantitatively imaging four alkyl-quinolone and alkyl-quinoline N-oxide signaling molecules (including Pseudomonas quinolone signal) in Pseudomonas aeruginosa colony biofilms. We show that the relative surface densities of the target biomolecules are substantially different from values inferred through direct intensity comparison and that the developed methodologies can be used to quantitatively compare as many ions as there are available standards.

Signal preprocessing, multivariate analysis and software tools for MA(LDI)-TOF mass spectrometry imaging for biological applications

Mass spectrometry imaging (MSI) is a label-free analytical technique capable of molecularly characterizing biological samples, including tissues and cell lines. The constant development of analytical instrumentation and strategies over the previous decade makes MSI a key tool in clinical research. Nevertheless, most MSI studies are limited to targeted analysis or the mere visualization of a few molecular species (proteins, peptides, metabolites, or lipids) in a region of interest without fully exploiting the possibilities inherent in the MSI technique, such as tissue classification and segmentation or the identification of relevant biomarkers from an untargeted approach. MSI data processing is challenging due to several factors. The large volume of mass spectra involved in a MSI experiment makes choosing the correct computational strategies critical. Furthermore, pixel to pixel variation inherent in the technique makes choosing the correct preprocessing steps critical. The primary aim of this review was to provide an overview of the data-processing steps and tools that can be applied to an MSI experiment, from preprocessing the raw data to the more advanced strategies for image visualization and segmentation. This review is particularly aimed at researchers performing MSI experiments and who are interested in incorporating new data-processing features, improving their computational strategy, and/or desire access to data-processing tools currently available. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:281-306, 2018.

Spatial Systems Lipidomics Reveals Nonalcoholic Fatty Liver Disease Heterogeneity

Hepatocellular lipid accumulation characterizes nonalcoholic fatty liver disease (NAFLD). However, the types of lipids associated with disease progression are debated, as is the impact of their localization. Traditional lipidomics analysis using liver homogenates or plasma dilutes and averages lipid concentrations, and does not provide spatial information about lipid distribution. We aimed to characterize the distribution of specific lipid species related to NAFLD severity by performing label-free molecular analysis by mass spectrometry imaging (MSI). Fresh frozen liver biopsies from obese subjects undergoing bariatric surgery (n = 23) with various degrees of NAFLD were cryosectioned and analyzed by matrix-assisted laser desorption/ionization (MALDI)-MSI. Molecular identification was verified by tandem MS. Tissue sections were histopathologically stained, annotated according to the Kleiner classification, and coregistered with the MSI data set. Lipid pathway analysis was performed and linked to local proteome networks. Spatially resolved lipid profiles showed pronounced differences between nonsteatotic and steatotic tissues. Lipid identification and network analyses revealed phosphatidylinositols and arachidonic acid metabolism in nonsteatotic regions, whereas low–density lipoprotein (LDL) and very low–density lipoprotein (VLDL) metabolism was associated with steatotic tissue. Supervised and unsupervised discriminant analysis using lipid based classifiers outperformed simulated analysis of liver tissue homogenates in predicting steatosis severity. We conclude that lipid composition of steatotic and nonsteatotic tissue is highly distinct, implying that spatial context is important for understanding the mechanisms of lipid accumulation in NAFLD. MSI combined with principal component–linear discriminant analysis linking lipid and protein pathways represents a novel tool enabling detailed, comprehensive studies of the heterogeneity of NAFLD.

Three-beam double stimulated Raman scatterings: Cascading configuration

Two-beam stimulated Raman scattering (SRS) has been used in diverse label-free spectroscopy and imaging applications of live cells, biological tissues, and functional materials. Recently, we developed a theoretical framework for the three-beam double SRS processes that involve pump, Stokes, and depletion beams, where the pump-Stokes and pump-depletion SRS processes compete with each other. It was shown that the net Stokes gain signal can be suppressed by increasing the depletion beam intensity. The theoretical prediction has been experimentally confirmed recently. In the previous scheme for a selective suppression of one SRS by making it compete with another SRS, the two SRS processes occur in a parallel manner. However, there is another possibility of three-beam double SRS scheme that can be of use to suppress either Raman gain of the Stokes beam or Raman loss of the pump beam by depleting the Stokes photons with yet another SRS process induced by the pair of Stokes and another (second) Stokes beam. This three-beam double SRS process resembles a cascading energy transfer process from the pump beam to the first Stokes beam (SRS-1) and subsequently from the first Stokes beam to the second Stokes beam (SRS-2). Here, the two stimulated Raman gain-loss processes are associated with two different Raman-active vibrational modes of solute molecule. In the present theory, both the radiation and the molecules are treated quantum mechanically. We then show that the cascading-type three-beam double SRS can be described by coupled differential equations for the photon numbers of the pump and Stokes beams. From the approximate solutions as well as exact numerical calculation results for the coupled differential equations, a possibility of efficiently suppressing the stimulated Raman loss of the pump beam by increasing the second Stokes beam intensity is shown and discussed. To further prove a potential use of this scheme for developing a super-resolution SRS microscopy, we present a theoretical expression and numerical simulation results for the full-width-at-half-maximum of SRS imaging point spread function, assuming that the pump and Stokes beam profiles are Gaussian and the second Stokes beam has a doughnut-shaped spatial profile. It is clear that the spatial resolution with the present 3-beam cascading SRS method can be enhanced well beyond the diffraction limit. We anticipate that the present work will provide a theoretical framework for a super-resolution stimulated Raman scattering microscopy that is currently under investigation.

The quest for improved reproducibility in MALDI mass spectrometry

Reproducibility has been one of the biggest hurdles faced when attempting to develop quantitative protocols for MALDI mass spectrometry. The heterogeneous nature of sample recrystallization has made automated sample acquisition somewhat "hit and miss" with manual intervention needed to ensure that all sample spots have been analyzed. In this review, we explore the last 30 years of literature and anecdotal evidence that has attempted to address and improve reproducibility in MALDI MS. Though many methods have been attempted, we have discovered a significant publication history surrounding the use of nitrocellulose as a substrate to improve homogeneity of crystal formation and therefore reproducibility. We therefore propose that this is the most promising avenue of research for developing a comprehensive and universal preparation protocol for quantitative MALDI MS analysis. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:217-228, 2018.

Phospholipids as cancer biomarkers: Mass spectrometry-based analysis

Lipids, particularly phospholipids (PLs), are key components of cellular membrane. PLs play important and diverse roles in cells such as chemical-energy storage, cellular signaling, cell membranes, and cell-cell interactions in tissues. All these cellular processes are pertinent to cells that undergo transformation, cancer progression, and metastasis. Thus, there is a strong possibility that some classes of PLs are expected to present in cancer cells and tissues in cellular physiology. The mass spectrometric soft-ionization techniques, electrospray ionization (ESI), and matrix-assisted laser desorption/ionization (MALDI) are well-established in the proteomics field, have been used for lipidomic analysis in cancer research. This review focused on the applications of mass spectrometry (MS) mainly on ESI-MS and MALDI-MS in the structural characterization, molecular composition and key roles of various PLs present in cancer cells, tissues, blood, and urine, and on their importance for cancer-related problems as well as challenges for development of novel PL-based biomarkers. The profiling of PLs helps to rationalize their functions in biological systems, and will also provide diagnostic information to elucidate mechanisms behind the control of cancer, diabetes, and neurodegenerative diseases. The investigation of cellular PLs with MS methods suggests new insights on various cancer diseases and clinical applications in the drug discovery and development of biomarkers for various PL-related different cancer diseases. PL profiling in tissues, cells and body fluids also reflect the general condition of the whole organism and can indicate the existence of cancer and other diseases. PL profiling with MS opens new prospects to assess alterations of PLs in cancer, screening specific biomarkers and provide a basis for the development of novel therapeutic strategies. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:107-138, 2018.

MassImager: A software for interactive and in-depth analysis of mass spectrometry imaging data

Mass spectrometry imaging (MSI) has become a powerful tool to probe molecule events in biological tissue. However, it is a widely held viewpoint that one of the biggest challenges is an easy-to-use data processing software for discovering the underlying biological information from complicated and huge MSI dataset. Here, a user-friendly and full-featured MSI software including three subsystems, Solution, Visualization and Intelligence, named MassImager, is developed focusing on interactive visualization, in-situ biomarker discovery and artificial intelligent pathological diagnosis. Simplified data preprocessing and high-throughput MSI data exchange, serialization jointly guarantee the quick reconstruction of ion image and rapid analysis of dozens of gigabytes datasets. It also offers diverse self-defined operations for visual processing, including multiple ion visualization, multiple channel superposition, image normalization, visual resolution enhancement and image filter. Regions-of-interest analysis can be performed precisely through the interactive visualization between the ion images and mass spectra, also the overlaid optical image guide, to directly find out the region-specific biomarkers. Moreover, automatic pattern recognition can be achieved immediately upon the supervised or unsupervised multivariate statistical modeling. Clear discrimination between cancer tissue and adjacent tissue within a MSI dataset can be seen in the generated pattern image, which shows great potential in visually in-situ biomarker discovery and artificial intelligent pathological diagnosis of cancer. All the features are integrated together in MassImager to provide a deep MSI processing solution at the in-situ metabolomics level for biomarker discovery and future clinical pathological diagnosis.

Nanometer-scale molecular organization in lipid membranes studied by time-of-flight secondary ion mass spectrometry

The organization of lipid membranes plays an important role in a wide range of biological processes at different length scales. Herein, the authors present a procedure based on time-of-flight secondary ion mass spectrometry (ToF-SIMS) to characterize the nanometer-scale ordering of lipids in lipid membrane structures on surfaces. While ToF-SIMS is a powerful tool for label-free analysis of lipid-containing samples, its limited spatial resolution prevents in-depth knowledge of how lipid properties affect the molecular assembly of the membrane. The authors overcome this limitation by measuring the formation of lipid dimers, originating in the same nanometer-sized primary ion impact areas. The lipid dimers reflect the local lipid environment and thus allow us to characterize the membrane miscibility on the nanometer level. Using this technique, the authors show that the chemical properties of the constituting lipids are critical for the structure and organization of the membrane on both the nanometer and micrometer length scales. Our results show that even at lipid surface compositions favoring two-phase systems, lipids are still extracted from solid, gel phase, domains into the surrounding fluid supported lipid bilayer surrounding the gel phase domains. The technique offers a means to obtain detailed knowledge of the chemical composition and organization of lipid membranes with potential application in systems where labeling is not possible, such as cell-derived supported lipid bilayers.

Quantitative mass spectrometry imaging of glutathione in healthy and cancerous hen ovarian tissue sections by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI)

A quantitative mass spectrometry imaging (QMSI) method for absolute quantification of glutathione (GSH) in healthy and cancerous hen ovarian tissues using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is presented. Using this technique, the ion abundance of GSH was normalized to that of a structural analogue, which was sprayed on the slide prior to mounting the tissue sections. This normalization strategy significantly improved the voxel-to-voxel variability; the variability is attributed to the overall ionization process. Subsequently, a series of calibration spots of stable isotope-labeled (SIL) GSH were pipetted on top of the tissue to construct a spatial calibration curve, and calculate the concentration of GSH in both tissue sections. The QMSI results were verified by LC-MS/MS quantification of GSH for the same tissues. GSH was extracted from tissue sections in a slightly acidic buffer and was then alkylated using N-ethylmaleimide to minimize autoxidation of GSH to glutathione disulfide. The alkylated GSH was separated from other contaminants using reversed phase liquid chromatography (RPLC) coupled to a triple quadrupole mass spectrometer, and the z-ion transition of NEM-GSH was used to quantify GSH in each tissue section. While the absolute values obtained using IR-MALDESI QMSI and LC-MS/MS were different, a ∼2-fold increase in the concentration of GSH in cancer tissue compared to the healthy tissue was observed using both techniques. Possible reasons for the difference between absolute concentration values obtained using IR-MALDESI QMSI and LC-MS/MS are also discussed.

Optimal Preparation of Formalin Fixed Samples for Peptide Based Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging Workflows

The use of matrix-assisted laser desorption/ionization, mass spectrometry imaging (MALDI MSI) has rapidly expanded, since this technique analyzes a host of biomolecules from drugs and lipids to N-glycans. Although various sample preparation techniques exist, detecting peptides from formaldehyde preserved tissues remains one of the most difficult challenges for this type of mass spectrometric analysis. For this reason, we have created and optimized a robust methodology that preserves the spatial information contained within the sample, while eliciting the greatest number of ionizable peptides. We have also aimed to achieve this in a cost effective and simple way, thereby eliminating potential bias or preparation error, which can occur when using automated instrumentation. The end result is a reproducible and inexpensive protocol.

Selective suppression of CARS signal with three-beam competing stimulated Raman scattering processes

A switching-off of the CARS signal is achieved by using a three-beam double SRS scheme.

BASTet: Shareable and Reproducible Analysis and Visualization of Mass Spectrometry Imaging Data via OpenMSI

Mass spectrometry imaging (MSI) is a transformative imaging method that supports the untargeted, quantitative measurement of the chemical composition and spatial heterogeneity of complex samples with broad applications in life sciences, bioenergy, and health. While MSI data can be routinely collected, its broad application is currently limited by the lack of easily accessible analysis methods that can process data of the size, volume, diversity, and complexity generated by MSI experiments. The development and application of cutting-edge analytical methods is a core driver in MSI research for new scientific discoveries, medical diagnostics, and commercial-innovation. However, the lack of means to share, apply, and reproduce analyses hinders the broad application, validation, and use of novel MSI analysis methods. To address this central challenge, we introduce the Berkeley Analysis and Storage Toolkit (BASTet), a novel framework for shareable and reproducible data analysis that supports standardized data and analysis interfaces, integrated data storage, data provenance, workflow management, and a broad set of integrated tools. Based on BASTet, we describe the extension of the OpenMSI mass spectrometry imaging science gateway to enable web-based sharing, reuse, analysis, and visualization of data analyses and derived data products. We demonstrate the application of BASTet and OpenMSI in practice to identify and compare characteristic substructures in the mouse brain based on their chemical composition measured via MSI.

Recent progress and developments of iridium-based compounds as probes for environmental analytes

Metal complexes based on iridium metal centers have attracted attention as probes due to their tunable biological and chemical characteristics.

Advances in mass spectrometry-based metabolomics for investigation of metabolites

Metabolomics is the systematic study of all the metabolites present within a biological system, which consists of a mass of molecules, having a variety of physical and chemical properties and existing over an extensive dynamic range in biological samples. Diverse analytical techniques are needed to achieve higher coverage of metabolites. The application of mass spectrometry (MS) in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques. Significant advances have also occurred in separation-based MS techniques (gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and ion mobility-mass spectrometry), as well as separation-free MS techniques (direct infusion-mass spectrometry, matrix-assisted laser desorption ionization-mass spectrometry, mass spectrometry imaging, and direct analysis in real time mass spectrometry) in the past decades. This review presents a brief overview of the recent advanced MS techniques and their latest applications in metabolomics. The software/websites for MS result analyses are also reviewed.

Metabolomics is the systematic study of all the metabolites present within a biological system, supply functional information and has received extensive attention in the field of life sciences.

Application of matrix-assisted laser desorption/ionization mass spectrometry imaging in combination with LC–MS in pharmacokinetic study of metformin

Aim: To demonstrate and discuss the pros and cons of various conventional and innovative analytical approaches. Methodology & results: Matrix-assisted laser desorption/ionization mass spectrometry imaging (MSI) of tissue sections as well as the extraction of tissue homogenates, blood plasma and dried blood spots coupled with LC–MS were employed to monitor the pharmacokinetics of metformin in mice. The time profile of metformin measured by matrix-assisted laser desorption/ionization MSI correlated well with the results found by LC–MS. Repeatability of the preparation of tissue sections for MSI was very good. Conclusion: MSI provided valuable information on the spatial distribution and relative concentration of the analyte within tissue sections. The analysis of the extracts of tissue homogenates, blood plasma and blood spots provided quantitative data on metformin. The dried blood spot approach is a progressive method of sampling, especially in studies where the amount of available blood is limited.

Linking nanomaterial properties to biological outcomes: analytical chemistry challenges in nanotoxicology for the next decade

This article provides our perspective on the analytical challenges in nanotoxicology as the field is entering its third decade.

Dean flow assisted cell ordering system for lipid profiling in single-cells using mass spectrometry

A Dean flow assisted ordering system connected to an ESI-MS to identify single-cells in a subpopulation by lipid profiling.

Matrix-Assisted Laser Desorption/Ionisation Mass Spectrometry Imaging in the Study of Gastric Cancer: A Mini Review

Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide and the disease outcome commonly depends upon the tumour stage at the time of diagnosis. However, this cancer can often be asymptomatic during the early stages and remain undetected until the later stages of tumour development, having a significant impact on patient prognosis. However, our comprehension of the mechanisms underlying the development of gastric malignancies is still lacking. For these reasons, the search for new diagnostic and prognostic markers for gastric cancer is an ongoing pursuit. Modern mass spectrometry imaging (MSI) techniques, in particular matrix-assisted laser desorption/ionisation (MALDI), have emerged as a plausible tool in clinical pathology as a whole. More specifically, MALDI-MSI is being increasingly employed in the study of gastric cancer and has already elucidated some important disease checkpoints that may help us to better understand the molecular mechanisms underpinning this aggressive cancer. Here we report the state of the art of MALDI-MSI approaches, ranging from sample preparation to statistical analysis, and provide a complete review of the key findings that have been reported in the literature thus far.

Visualizing molecular distributions for biomaterials applications with mass spectrometry imaging: a review

Mass spectrometry imaging (MSI) is a rapidly emerging field that is continually finding applications in new and exciting areas. The ability of MSI to measure the spatial distribution of molecules at or near the surface of complex substrates makes it an ideal candidate for many applications, including those in the sphere of materials chemistry. Continual development and optimization of both ionization sources and analyzer technologies have resulted in a wide array of MSI tools available, both commercially available and custom-built, with each configuration possessing inherent strengths and limitations. Despite the unique potential of MSI over other chemical imaging methods, their potential and application to (bio)materials science remains in our view a largely underexplored avenue. This review will discuss these techniques enabling high parallel molecular detection, focusing on those with reported uses in (bio)materials chemistry applications and highlighted with select applications. Different technologies are presented in three main sections; secondary ion mass spectrometry (SIMS) imaging, matrix-assisted laser desorption ionization (MALDI) MSI, and emerging MSI technologies with potential for biomaterial analysis. The first two sections (SIMS and MALDI) discuss well-established methods that are continually evolving both in technological advancements and in experimental versatility. In the third section, relatively new and versatile technologies capable of performing measurements under ambient conditions will be introduced, with reported applications in materials chemistry or potential applications discussed. The aim of this review is to provide a concise resource for those interested in utilizing MSI for applications such as biomimetic materials, biological/synthetic material interfaces, polymer formulation and bulk property characterization, as well as the spatial and chemical distributions of nanoparticles, or any other molecular imaging application requiring broad chemical speciation.

MALDI-TOF MS as a Novel Tool for the Estimation of Postmortem Interval in Liver Tissue Samples

Estimation of the postmortem interval (PMI) is a complicated task in forensic medicine, especially during homicide and unwitnessed death investigations. Many biological, chemical, and physical indicators can be used to determine the postmortem interval, but most are not accurate. Here, we present a novel matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) method that can be used for the estimation of PMI using molecular images and multivariate analyses. In this study, we demonstrate that both rat and human liver tissues of various PMIs (0, 2, 4, and 6days) can be discriminated using MALDI imaging and principal component analysis (PCA). Using genetic algorithm (GA), supervised neural network (SNN), and quick classifier (QC) methods, we built 6 classification models, which showed high recognition capability and good cross-validation. The histological changes in all the samples at different time points were also consistent with the changes seen in MALDI imaging. Our work suggests that MALDI-TOF MS, along with multivariate analysis, can be used to determine intermediate PMIs.