Sample preparation for mass spectrometry imaging: Small mistakes can lead to big consequences

What is Normalization? The Strategies Employed in Top-Down and Bottom-Up Proteome Analysis Workflows

The accurate quantification of changes in the abundance of proteins is one of the main applications of proteomics. The maintenance of accuracy can be affected by bias and error that can occur at many points in the experimental process, and normalization strategies are crucial to attempt to overcome this bias and return the sample to its regular biological condition, or normal state. Much work has been published on performing normalization on data post-acquisition with many algorithms and statistical processes available. However, there are many other sources of bias that can occur during experimental design and sample handling that are currently unaddressed. This article aims to cast light on the potential sources of bias and where normalization could be applied to return the sample to its normal state. Throughout we suggest solutions where possible but, in some cases, solutions are not available. Thus, we see this article as a starting point for discussion of the definition of and the issues surrounding the concept of normalization as it applies to the proteomic analysis of biological samples. Specifically, we discuss a wide range of different normalization techniques that can occur at each stage of the sample preparation and analysis process.

Exploring the Fundamental Structures of Life: Non-Targeted, Chemical Analysis of Single Cells and Subcellular Structures

Cells are a basic functional and structural unit of living organisms. Both unicellular communities and multicellular species produce an astonishing chemical diversity, enabling a wide range of divergent functions, yet each cell shares numerous aspects that are common to all living organisms. While there are many approaches for studying this chemical diversity, only a few are non-targeted and capable of analyzing hundreds of different chemicals at cellular resolution. Here, we review the non-targeted approaches used to perform comprehensive chemical analyses, provide chemical imaging information, or obtain high-throughput single-cell profiling data. Single-cell measurement capabilities are rapidly increasing in terms of throughput, limits of detection, and completeness of the chemical analyses; these improvements enable their application to understand ever more complex physiological phenomena, such as learning, memory, and behavior.

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.

Mapping the Surface Microbiome and Metabolome of Brown Seaweed Fucus vesiculosus by Amplicon Sequencing, Integrated Metabolomics and Imaging Techniques

The brown alga Fucus vesiculosus is a keystone marine species, which is subject to heavy surface colonisation. This study was designed to analyse the surface epibiome of F. vesiculosus in conjunction with the composition and spatial distribution of its surface metabolome. The amplicon sequencing, SEM and CARD-FISH imaging studies showed Alphaproteobacteria to predominate the epibiotic bacteria. Fungi of the class Eurotiomycetes were visualised for the first time on an algal surface. An untargeted metabolomics approach using molecular networks, in silico prediction and manual dereplication showed the differential metabolome of the surface and the whole tissue extracts. In total, 50 compounds were putatively dereplicated by UPLC-MS/MS, 37 of which were previously reported from both seaweeds and microorganisms. Untargeted spatial metabolomics by DESI-Imaging MS identified the specific localisation and distribution of various primary and secondary metabolites on surface imprints and in algal cross sections. The UPLC-MS, DESI-IMS and NMR analyses failed to confirm the presence of any surface-associated metabolite, except for mannitol, which were previously reported from F. vesiculosus. This is the first study analysing the seaweed surface microbiome in conjunction with untargeted surface metabolomics and spatial metabolomics approaches.

Mass spectrometry imaging for clinical research - latest developments, applications, and current limitations

Mass spectrometry is being used in many clinical research areas ranging from toxicology to personalized medicine. Of all the mass spectrometry techniques, mass spectrometry imaging (MSI), in particular, has continuously grown towards clinical acceptance. Significant technological and methodological improvements have contributed to enhance the performance of MSI recently, pushing the limits of throughput, spatial resolution, and sensitivity. This has stimulated the spread of MSI usage across various biomedical research areas such as oncology, neurological disorders, cardiology, and rheumatology, just to name a few. After highlighting the latest major developments and applications touching all aspects of translational research (i.e. from early pre-clinical to clinical research), we will discuss the present challenges in translational research performed with MSI: data management and analysis, molecular coverage and identification capabilities, and finally, reproducibility across multiple research centers, which is the largest remaining obstacle in moving MSI towards clinical routine.

Balancing sufficiency and impact in reporting standards for mass spectrometry imaging experiments

Reproducibility, or a lack thereof, is an increasingly important topic across many research fields. A key aspect of reproducibility is accurate reporting of both experiments and the resulting data. Herein, we propose a reporting guideline for mass spectrometry imaging (MSI). Previous standards have laid out guidelines sufficient to guarantee a certain quality of reporting; however, they set a high bar and as a consequence can be exhaustive and broad, thus limiting uptake.To help address this lack of uptake, we propose a reporting supplement-Minimum Information About a Mass Spectrometry Imaging Experiment (MIAMSIE)-and its abbreviated reporting standard version, MSIcheck. MIAMSIE is intended to improve author-driven reporting. It is intentionally not exhaustive, but is rather designed for extensibility and could therefore eventually become analogous to existing standards that aim to guarantee reporting quality. Conversely, its abbreviated form MSIcheck is intended as a diagnostic tool focused on key aspects in MSI reporting.We discuss how existing standards influenced MIAMSIE/MSIcheck and how these new approaches could positively impact reporting quality, followed by test implementation of both standards to demonstrate their use. For MIAMSIE, we report on author reviews of four articles and a dataset. For MSIcheck, we show a snapshot review of a one-month subset of the MSI literature that indicated issues with data provision and the reporting of both data analysis steps and calibration settings for MS systems. Although our contribution is MSI specific, we believe the underlying approach could be considered as a general strategy for improving scientific reporting.

In MALDI-Mass Spectrometry Imaging on Formalin-Fixed Paraffin-Embedded Tissue Specimen Section Thickness Significantly Influences m/z Peak Intensity

BACKGROUND

In matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) standardized sample preparation is important to obtain reliable results. Herein, the impact of section thickness in formalin-fixed paraffin embedded (FFPE) tissue microarrays (TMA) on spectral intensities is investigated.

PATIENTS AND METHODS

TMAs consisting of ten different tissues represented by duplicates of ten patients (n = 200 cores) are cut at 1, 3, and 5 μm. MSI analysis is performed and mean intensities of all evaluable cores are extracted. Measurements are merged and mean m/z intensities are compared.

RESULTS

Visual inspection of spectral intensities between 1, 3, and 5 μm reveals generally higher intensities in thinner tissue sections. Specifically, higher intensities are observed in the vast majority of peaks (98.6%, p < 0.01) in 1 μm compared with 5 μm sections. Note that 28.4% and 2.1% of m/z values exhibit a at least two- and threefold intensity difference (p < 0.01) in 1 μm compared to 5 μm sections, respectively.

CONCLUSION

A section thickness of 1 μm results in higher spectral intensities compared with 5 μm. The results highlight the importance of standardized protocols in light of recent efforts to identify clinically relevant biomarkers using MSI. The use of TMAs for comparative analysis seems advantageous, as section thickness displays less variability.

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.

Sample preparation for mass spectrometry imaging of leaf tissues: a case study on analyte delocalization

Appropriate sample preparation is pivotally important to obtain high-quality mass spectrometry imaging (MSI) data. Unlike mammalian tissues, preparation of cryosections from plant tissues for MSI measurement is quite challenging due to its intrinsic complex texture and cellular structure. This is especially true for leaf samples which are generally thin, water-rich, and fragile. In this work, a systematic study was performed, aiming to evaluate three embedding materials and five mounting approaches for matrix-assisted laser desorption ionization (MALDI) MSI of secondary metabolites in cross sections of the ginkgo leaf. Delocalization of endogenous metabolites was chosen as a major indicator for evaluation of three embedding materials including ice, carboxymethyl cellulose (CMC), and gelatin and different mounting approaches. Image distortion and analyte delocalization were observed when ice was used as an embedding medium. CMC embedding provided better results compared to the ice by using modified mounting approach. Among three embedding materials, no delocalization was observed in specimens embedded with gelatin, and gelatin embedding is the least affected by different mounting approaches. An alternative approach to mitigate analyte delocalization is the removal of embedding media embraced the tissue sections before mounting, which is particularly suitable for ice-embedded samples. Additionally, the extent of analyte delocalization was closely related to their lipophilicity/hydrophilicity properties, and less analyte diffusion was observed for hydrophobic analytes than for the water-soluble compounds.

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.

Tissue imaging with in situ solid-phase extraction micro-funnel based spray ionization mass spectrometry

Current imaging mass spectrometry techniques are faced with a major challenge related to ion suppression effect. Data regarding low-abundance components or low-polarity compounds cannot be normally obtained presumably because of the discrimination effect of easily ionized chemical components on desorption/ionization process. In this study, a new method was proposed to obtain images of chemical components in biological tissues or sections through in situ solid-phase extraction in sorbent mounted micro-funnel based spray ionization mass spectrometry. An imprint of a strawberry section was formed by gently pressing against a 2D array of micro-funnels. The sorbent mounted micro-funnels were then subjected to in situ single-pixel solid-phase extraction to alleviate the matrix-related ion suppression effect. The achievable spatial resolution is approximately 250 µm. The imaging of the spatial distribution of low-abundance or low-polarity chemicals in the strawberry imprint could be obtained by using a gradient elution strategy. Results demonstrated that the "not observed" remark does not necessarily indicate that a specific compound is non-existent when traditional imaging mass spectrometry techniques are used. The proposed method can be applied to conduct low-abundance chemical imaging through in situ single-pixel sample pretreatment.

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.

NanoSIMS for biological applications: Current practices and analyses

Secondary ion mass spectrometry (SIMS) has become an increasingly utilized tool in biologically relevant studies. Of these, high lateral resolution methodologies using the NanoSIMS 50/50L have been especially powerful within many biological fields over the past decade. Here, the authors provide a review of this technology, sample preparation and analysis considerations, examples of recent biological studies, data analyses, and current outlooks. Specifically, the authors offer an overview of SIMS and development of the NanoSIMS. The authors describe the major experimental factors that should be considered prior to NanoSIMS analysis and then provide information on best practices for data analysis and image generation, which includes an in-depth discussion of appropriate colormaps. Additionally, the authors provide an open-source method for data representation that allows simultaneous visualization of secondary electron and ion information within a single image. Finally, the authors present a perspective on the future of this technology and where they think it will have the greatest impact in near future.

Sample Preparation of Corn Seed Tissue to Prevent Analyte Relocations for Mass Spectrometry Imaging

Corn seed tissue sections were prepared by the tape support method using an adhesive tape, and mass spectrometry imaging (MSI) was performed. The effect of heat generated during sample preparation was investigated by time-of-flight secondary mass spectrometry (TOF-SIMS) imaging of corn seed tissue prepared by the tape support and the thaw-mounted methods. Unlike thaw-mounted sample preparation, the tape support method does not cause imaging distortion because of the absence of heat, which can cause migration of the analytes on the sample. By applying the tape-support method, the corn seed tissue was prepared without structural damage and MSI with accurate spatial information of analytes was successfully performed. Graphical Abstract ᅟ.

Recent advances and clinical insights into the use of proteomics in the study of atherosclerosis

INTRODUCTION

The application of new proteomics methods may help to identify new diagnostic/predictive molecular markers in an attempt to improve the clinical management of atherosclerosis. Areas covered: Technological advances in proteomics have enhanced its sensitivity and multiplexing capacity, as well as the possibility of studying protein interactions and tissue structure. These advances will help us better understand the molecular mechanisms at play in atherosclerosis as a biological system. Moreover, this should help identify new predictive/diagnostic biomarkers and therapeutic targets that may facilitate effective risk stratification and early diagnosis, with the ensuing rapid implementation of treatment. This review provides a comprehensive overview of the novel methods in proteomics, including state-of-the-art techniques, novel biological samples and applications for the study of atherosclerosis. Expert commentary: Collaboration between clinicians and researchers is crucial to further validate and introduce new molecular markers to manage atherosclerosis that are identified using the most up to date proteomic approaches.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2011-2012

This review is the seventh update of the original article published in 1999 on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2012. General aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, and fragmentation are covered in the first part of the review and applications to various structural types constitute the remainder. The main groups of compound are oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Much of this material is presented in tabular form. Also discussed are medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:255-422, 2017.

Dopamine-modified TiO2 monolith-assisted LDI MS imaging for simultaneous localization of small metabolites and lipids in mouse brain tissue with enhanced detection selectivity and sensitivity

Localization of metabolites using multiplexed mass spectrometry imaging (MSI) provides important chemical information for biological research. In contrast to matrix-assisted laser desorption/ionization (MALDI), TiO2-assisted laser desorption/ionization (LDI) for MSI improves detection of low molecular mass metabolites (<500 Da) by reducing matrix background. However, the low UV absorption of TiO2 nanoparticles and their ester hydrolysis catalytic activity hinder the detection of phospholipids and many low-abundance molecules. To address these challenges, we evaluated and optimized the material morphology and composition of TiO2. Dopamine (DA) was found to be an efficient ligand for TiO2, resulting in increased UV light absorption, higher surface pH, and formation of monolithic TiO2-DA structures. The sub-micron scale and higher surface pH of the TiO2 particle sizes led to improved detection of phospholipid signals. Compared to unmodified TiO2 sub-micron particles, the DA-modified TiO2 monolith led to 10- to 30-fold increases in the signal-to-noise ratios of a number of compound peaks. The TiO2-DA monolith-assisted LDI MSI approach has higher selectivity and sensitivity for Lewis basic compounds, such as fatty acids, cholesterols, ceramides, diacylglycerols, and phosphatidylethanolamine, when analyzed in positive mode, than traditional MALDI MS. Using this new method, over 100 molecules, including amino acids, alkaloids, free fatty acids, peptides, and lipids, were localized in mouse brain sections. By comparing the presence and localization of those molecules in young and old mouse brains, the approach demonstrated good performance in the determination of aging-related neurochemical changes in the brain.

Mass Spectrometry Imaging of Complex Microbial Communities

In the two decades since mass spectrometry imaging (MSI) was first applied to visualize the distribution of peptides across biological tissues and cells, the technique has become increasingly effective and reliable. MSI excels at providing complementary information to existing methods for molecular analysis—such as genomics, transcriptomics, and metabolomics—and stands apart from other chemical imaging modalities through its capability to generate information that is simultaneously multiplexed and chemically specific. Today a diverse family of MSI approaches are applied throughout the scientific community to study the distribution of proteins, peptides, and small-molecule metabolites across many biological models.

The inherent strengths of MSI make the technique valuable for studying microbial systems. Many microbes reside in surface-attached multicellular and multispecies communities, such as biofilms and motile colonies, where they work together to harness surrounding nutrients, fend off hostile organisms, and shield one another from adverse environmental conditions. These processes, as well as many others essential for microbial survival, are mediated through the production and utilization of a diverse assortment of chemicals. Although bacterial cells are generally only a few microns in diameter, the ecologies they influence can encompass entire ecosystems, and the chemical changes that they bring about can occur over time scales ranging from milliseconds to decades. Because of their incredible complexity, our understanding of and influence over microbial systems requires detailed scientific evaluations that yield both chemical and spatial information. MSI is well-positioned to fulfill these requirements. With small adaptations to existing methods, the technique can be applied to study a wide variety of chemical interactions, including those that occur inside single-species microbial communities, between cohabitating microbes, and between microbes and their hosts.

In recognition of this potential for scientific advancement, researchers have adapted MSI methodologies for the specific needs of the microbiology research community. As a result, workflows exist for imaging microbial systems with many of the common MSI ionization methods. Despite this progress, there is substantial room for improvements in instrumentation, sample preparation, and data interpretation. This Account provides a brief overview of the state of technology in microbial MSI, illuminates selected applications that demonstrate the potential of the technique, and highlights a series of development challenges that are needed to move the field forward. In the coming years, as microbial MSI becomes easier to use and more universally applicable, the technique will evolve into a fundamental tool widely applied throughout many divisions of science, medicine, and industry.

Applications of Mass Spectrometry Imaging to Cancer

Pathologists play an essential role in the diagnosis and prognosis of benign and cancerous tumors. Clinicians provide tissue samples, for example, from a biopsy, which are then processed and thin sections are placed onto glass slides, followed by staining of the tissue with visible dyes. Upon processing and microscopic examination, a pathology report is provided, which relies on the pathologist's interpretation of the phenotypical presentation of the tissue. Targeted analysis of single proteins provide further insight and together with clinical data these results influence clinical decision making. Recent developments in mass spectrometry facilitate the collection of molecular information about such tissue specimens. These relatively new techniques generate label-free mass spectra across tissue sections providing nonbiased, nontargeted molecular information. At each pixel with spatial coordinates (x/y) a mass spectrum is acquired. The acquired mass spectrums can be visualized as intensity maps displaying the distribution of single m/z values of interest. Based on the sample preparation, proteins, peptides, lipids, small molecules, or glycans can be analyzed. The generated intensity maps/images allow new insights into tumor tissues. The technique has the ability to detect and characterize tumor cells and their environment in a spatial context and combined with histological staining, can be used to aid pathologists and clinicians in the diagnosis and management of cancer. Moreover, such data may help classify patients to aid therapy decisions and predict outcomes. The novel complementary mass spectrometry-based methods described in this chapter will contribute to the transformation of pathology services around the world.

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

Mass spectrometry imaging (MSI) is a rapidly evolving field for monitoring the spatial distribution and abundance of analytes in biological tissue sections. It allows for direct and simultaneous analysis of hundreds of different compounds in a label-free manner. In order to obtain a comprehensive metabolite and lipid data, a polarity switching MSI method using infrared matrix assisted laser desorption electrospray ionization (IR-MALDESI) was developed and optimized where the electrospray polarity was alternated from one voxel to the next. Healthy and cancerous ovarian hen tissue sections were analyzed using this method. Distribution and relative abundance of different metabolites and lipids within each tissue section were discerned, and differences between the two were revealed. Additionally, the utility of using mass spectrometry concepts such as spectral accuracy and sulfur counting for confident identification of analytes in an untargeted method are discussed.

Droplet-Based Liquid Extraction for Spatially-Resolved Microproteomics Analysis of Tissue Sections

Obtaining information on protein content while keeping their localization on tissue or organ is of importance in different domains to understand pathophysiological processes. There is increasing interest in studying the microenvironment and heterogeneity of tumors, which currently is difficult with existing proteomics techniques. The advent of new techniques, like MALDI Mass Spectrometry Imaging, made a significant progress in the last decade but is characterized by a number of inherent drawbacks. One of these is the limited identification of proteins. New alternative approaches such as spatially-resolved liquid microextraction have recently been proposed to overcome this limitation. In this chapter, we describe strategies using liquid microjunction to perform extraction of previously digested peptides or of intact proteins from tissue section in a localized manner.

Progress and Potential of Imaging Mass Spectrometry Applied to Biomarker Discovery

Mapping provides a direct means to assess the impact of protein biomarkers and puts into context their relevance in the type of cancer being examined. To this end, mass spectrometry imaging (MSI) was developed to provide the needed spatial information which is missing in traditional liquid-based mass spectrometric proteomics approaches. Aptly described as a "molecular histology" technique, MSI gives an additional dimension in characterizing tumor biopsies, allowing for mapping of hundreds of molecules in a single analysis. A decade of developments focused on improving and standardizing MSI so that the technique can be translated into the clinical setting. This review describes the progress made in addressing the technological development that allows to bridge local protein detection by MSI to its identification and to illustrate its potential in studying various aspects of cancer biomarker discovery.

Mass Spectrometry Imaging in Oncology Drug Discovery

Over the last decade mass spectrometry imaging (MSI) has been integrated in to many areas of drug discovery and development. It can have significant impact in oncology drug discovery as it allows efficacy and safety of compounds to be assessed against the backdrop of the complex tumour microenvironment. We will discuss the roles of MSI in investigating compound and metabolite biodistribution and defining pharmacokinetic -pharmacodynamic relationships, analysis that is applicable to all drug discovery projects. We will then look more specifically at how MSI can be used to understand tumour metabolism and other applications specific to oncology research. This will all be described alongside the challenges of applying MSI to industry research with increased use of metrology for MSI.

Ambient Mass Spectrometry in Cancer Research

Ambient ionization mass spectrometry was developed as a sample preparation-free alternative to traditional MS-based workflows. Desorption electrospray ionization (DESI)-MS methods were demonstrated to allow the direct analysis of a broad range of samples including unaltered biological tissue specimens. In contrast to this advantageous feature, nowadays DESI-MS is almost exclusively used for sample preparation intensive mass spectrometric imaging (MSI) in the area of cancer research. As an alternative to MALDI, DESI-MSI offers matrix deposition-free experiment with improved signal in the lower (<500m/z) range. DESI-MSI enables the spatial mapping of tumor metabolism and has been broadly demonstrated to offer an alternative to frozen section histology for intraoperative tissue identification and surgical margin assessment. Rapid evaporative ionization mass spectrometry (REIMS) was developed exclusively for the latter purpose by the direct combination of electrosurgical devices and mass spectrometry. In case of the REIMS technology, aerosol particles produced by electrosurgical dissection are subjected to MS analysis, providing spectral information on the structural lipid composition of tissues. REIMS technology was demonstrated to give real-time information on the histological nature of tissues being dissected, deeming it an ideal tool for intraoperative tissue identification including surgical margin control. More recently, the method has also been used for the rapid lipidomic phenotyping of cancer cell lines as it was demonstrated in case of the NCI-60 cell line collection.

Electrospray deposition device used to precisely control the matrix crystal to improve the performance of MALDI MSI

MALDI MSI has been recently applied as an innovative tool for detection of molecular distribution within a specific tissue. MALDI MSI requires deposition of an organic compound, known as matrix, on the tissue of interest to assist analyte desorption and ionization, in which the matrix crystal homogeneity and size greatly influence the imaging reproducibility and spatial resolution in MALDI MSI. In this work, a homemade electrospray deposition device was developed for deposition of matrix in MALDI MSI. The device could be used to achieve 1 μm homogeneous matrix crystals in MALDI MSI analysis. Moreover, it was found, for the first time, that the electrospray deposition device could be used to precisely control the matrix crystal size, and the imaging spatial resolution was increased greatly as the matrix crystals size becoming smaller. In addition, the easily-built electrospray deposition device was durable for acid, base or organic solvent, and even could be used for deposition of nanoparticles matrix, which made it unparalleled for MALDI MSI analysis. The feasibility of the electrospray deposition device was investigated by combination with MALDI FTICR MSI to analyze the distributions of lipids in mouse brain and liver cancer tissue section.

A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF

Mass spectrometry imaging (MSI) is a powerful tool to visualize the spatial distribution of molecules on a tissue section. The main limitation of MALDI-MSI of proteins is the lack of direct identification. Therefore, this study focuses on a MSI~LC-MS/MS-LF workflow to link the results from MALDI-MSI with potential peak identification and label-free quantitation, using only one tissue section. At first, we studied the impact of matrix deposition and laser ablation on protein extraction from the tissue section. Then, we did a back-correlation of the m/z of the proteins detected by MALDI-MSI to those identified by label-free quantitation. This allowed us to compare the label-free quantitation of proteins obtained in LC-MS/MS with the peak intensities observed in MALDI-MSI. We managed to link identification to nine peaks observed by MALDI-MSI. The results showed that the MSI~LC-MS/MS-LF workflow (i) allowed us to study a representative muscle proteome compared to a classical bottom-up workflow; and (ii) was sparsely impacted by matrix deposition and laser ablation. This workflow, performed as a proof-of-concept, suggests that a single tissue section can be used to perform MALDI-MSI and protein extraction, identification, and relative quantitation.

Mass spectrometry-based plant metabolomics: Metabolite responses to abiotic stress

Metabolomics is one omics approach that can be used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include analysis of a wide range of chemical species with diverse physical properties, from ionic inorganic compounds to biochemically derived hydrophilic carbohydrates, organic and amino acids, and a range of hydrophobic lipid-related compounds. This complexitiy brings huge challenges to the analytical technologies employed in current plant metabolomics programs, and powerful analytical tools are required for the separation and characterization of this extremely high compound diversity present in biological sample matrices. The use of mass spectrometry (MS)-based analytical platforms to profile stress-responsive metabolites that allow some plants to adapt to adverse environmental conditions is fundamental in current plant biotechnology research programs for the understanding and development of stress-tolerant plants. In this review, we describe recent applications of metabolomics and emphasize its increasing application to study plant responses to environmental (stress-) factors, including drought, salt, low oxygen caused by waterlogging or flooding of the soil, temperature, light and oxidative stress (or a combination of them). Advances in understanding the global changes occurring in plant metabolism under specific abiotic stress conditions are fundamental to enhance plant fitness and increase stress tolerance. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 35:620-649, 2016.

Infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging analysis of biospecimens

Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI) is a technique well suited for analysis of biological specimens. This tutorial review focuses on recent advancements and applications of IR-MALDESI MSI to better understand key biological questions. Through optimization of user-defined source parameters, comprehensive and quantitative MSI data can be obtained for a variety of analytes. The effect of an ice matrix layer is well defined in the context of desorption dynamics and resulting ion abundance. Optimized parameters and careful control of conditions affords quantitative MSI data which provides valuable information for targeted, label-free drug distribution studies and untargeted metabolomic datasets. Challenges and limitations of MSI using IR-MALDESI are addressed in the context of the bioimaging field.

High-mass-resolution MALDI mass spectrometry imaging of metabolites from formalin-fixed paraffin-embedded tissue

Formalin-fixed and paraffin-embedded (FFPE) tissue specimens are the gold standard for histological examination, and they provide valuable molecular information in tissue-based research. Metabolite assessment from archived tissue samples has not been extensively conducted because of a lack of appropriate protocols and concerns about changes in metabolite content or chemical state due to tissue processing. We present a protocol for the in situ analysis of metabolite content from FFPE samples using a high-mass-resolution matrix-assisted laser desorption/ionization fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FT-ICR-MSI) platform. The method involves FFPE tissue sections that undergo deparaffinization and matrix coating by 9-aminoacridine before MALDI-MSI. Using this platform, we previously detected ∼1,500 m/z species in the mass range m/z 50-1,000 in FFPE samples; the overlap compared with fresh frozen samples is 72% of m/z species, indicating that metabolites are largely conserved in FFPE tissue samples. This protocol can be reproducibly performed on FFPE tissues, including small samples such as tissue microarrays and biopsies. The procedure can be completed in a day, depending on the size of the sample measured and raster size used. Advantages of this approach include easy sample handling, reproducibility, high throughput and the ability to demonstrate molecular spatial distributions in situ. The data acquired with this protocol can be used in research and clinical practice.

Machine learning approaches in MALDI-MSI: clinical applications

INTRODUCTION

Despite the unquestionable advantages of Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging in visualizing the spatial distribution and the relative abundance of biomolecules directly on-tissue, the yielded data is complex and high dimensional. Therefore, analysis and interpretation of this huge amount of information is mathematically, statistically and computationally challenging.

AREAS COVERED

This article reviews some of the challenges in data elaboration with particular emphasis on machine learning techniques employed in clinical applications, and can be useful in general as an entry point for those who want to study the computational aspects. Several characteristics of data processing are described, enlightening advantages and disadvantages. Different approaches for data elaboration focused on clinical applications are also provided. Practical tutorial based upon Orange Canvas and Weka software is included, helping familiarization with the data processing. Expert commentary: Recently, MALDI-MSI has gained considerable attention and has been employed for research and diagnostic purposes, with successful results. Data dimensionality constitutes an important issue and statistical methods for information-preserving data reduction represent one of the most challenging aspects. The most common data reduction methods are characterized by collecting independent observations into a single table. However, the incorporation of relational information can improve the discriminatory capability of the data.

On-Tissue Derivatization via Electrospray Deposition for Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging of Endogenous Fatty Acids in Rat Brain Tissues

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is used for the multiplex detection and characterization of diverse analytes over a wide mass range directly from tissues. However, analyte coverage with MALDI MSI is typically limited to the more abundant compounds, which have m/z values that are distinct from MALDI matrix-related ions. On-tissue analyte derivatization addresses these issues by selectively tagging functional groups specific to a class of analytes, while simultaneously changing their molecular masses and improving their desorption and ionization efficiency. We evaluated electrospray deposition of liquid-phase derivatization agents as a means of on-tissue analyte derivatization using 2-picolylamine; we were able to detect a range of endogenous fatty acids with MALDI MSI. When compared with airbrush application, electrospray led to a 3-fold improvement in detection limits and decreased analyte delocalization. Six fatty acids were detected and visualized from rat cerebrum tissue using a MALDI MSI instrument operating in positive mode. MALDI MSI of the hippocampal area allowed targeted fatty acid analysis of the dentate gyrus granule cell layer and the CA1 pyramidal layer with a 20-μm pixel width, without degrading the localization of other lipids during liquid-phase analyte derivatization.

Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology

Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.