Comprehensive identification of proteins from MALDI imaging

Untargeted Spatial Metabolomics and Spatial Proteomics on the Same Tissue Section

An increasing number of spatial multiomic workflows have recently been developed. Some of these approaches have leveraged initial mass spectrometry imaging (MSI)-based spatial metabolomics to inform the region of interest (ROI) selection for downstream spatial proteomics. However, these workflows have been limited by varied substrate requirements between modalities or have required analyzing serial sections (i.e., one section per modality). To mitigate these issues, we present a new multiomic workflow that uses desorption electrospray ionization (DESI)-MSI to identify representative spatial metabolite patterns on-tissue prior to spatial proteomic analyses on the same tissue section. This workflow is demonstrated here with a model mammalian tissue (coronal rat brain section) mounted on a poly(ethylene naphthalate)-membrane slide. Initial DESI-MSI resulted in 160 annotations (SwissLipids) within the METASPACE platform (≤20% false discovery rate). A segmentation map from the annotated ion images informed the downstream ROI selection for spatial proteomics characterization from the same sample. The unspecific substrate requirements and minimal sample disruption inherent to DESI-MSI allowed for an optimized, downstream spatial proteomics assay, resulting in 3888 ± 240 to 4717 ± 48 proteins being confidently directed per ROI (200 μm × 200 μm). Finally, we demonstrate the integration of multiomic information, where we found ceramide localization to be correlated with SMPD3 abundance (ceramide synthesis protein), and we also utilized protein abundance to resolve metabolite isomeric ambiguity. Overall, the integration of DESI-MSI into the multiomic workflow allows for complementary spatial- and molecular-level information to be achieved from optimized implementations of each MS assay inherent to the workflow itself.

Proteomic analysis of granulomas from cattle and pigs naturally infected with Mycobacterium tuberculosis complex by MALDI imaging

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has recently gained prominence for its ability to provide molecular and spatial information in tissue sections. This technology has the potential to uncover novel insights into proteins and other molecules in biological and immunological pathways activated along diseases with a complex host-pathogen interaction, such as animal tuberculosis. Thus, the present study conducted a data analysis of protein signature in granulomas of cattle and pigs naturally infected with the Mycobacterium tuberculosis complex (MTC), identifying biological and immunological signaling pathways activated throughout the disease. Lymph nodes from four pigs and four cattle, positive for the MTC by bacteriological culture and/or real-time PCR, were processed for histopathological examination and MALDI-MSI. Protein identities were assigned using the MaTisse database, and protein-protein interaction networks were visualized using the STRING database. Gene Ontology (GO) analysis was carried out to determine biological and immunological signaling pathways in which these proteins could participate together with Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Distinct proteomic profiles between cattle and pig granulomas were displayed. Noteworthy, the GO analysis revealed also common pathways among both species, such as "Complement activation, alternative pathway" and "Tricarboxylic acid cycle", which highlight pathways that are conserved among different species infected by the MTC. In addition, species-specific terms were identified in the current study, such as "Natural killer cell degranulation" in cattle or those related to platelet and neutrophil recruitment and activation in pigs. Overall, this study provides insights into the immunopathogenesis of tuberculosis in cattle and pigs, opening new areas of research and highlighting the importance, among others, of the complement activation pathway and the regulation of natural killer cell- and neutrophil-mediated immunity in this disease.

Enhancing mass spectrometry imaging accessibility using convolutional autoencoders for deriving hypoxia-associated peptides from tumors

Mass spectrometry imaging (MSI) allows to study cancer's intratumoral heterogeneity through spatially-resolved peptides, metabolites and lipids. Yet, in biomedical research MSI is rarely used for biomarker discovery. Besides its high dimensionality and multicollinearity, mass spectrometry (MS) technologies typically output mass-to-charge ratio values but not the biochemical compounds of interest. Our framework makes particularly low-abundant signals in MSI more accessible. We utilized convolutional autoencoders to aggregate features associated with tumor hypoxia, a parameter with significant spatial heterogeneity, in cancer xenograft models. We highlight that MSI captures these low-abundant signals and that autoencoders can preserve them in their latent space. The relevance of individual hyperparameters is demonstrated through ablation experiments, and the contribution from original features to latent features is unraveled. Complementing MSI with tandem MS from the same tumor model, multiple hypoxia-associated peptide candidates were derived. Compared to random forests alone, our autoencoder approach yielded more biologically relevant insights for biomarker discovery.

Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.

Spatial and Temporal Protein Modules Signatures Associated with Alzheimer Disease in 3xTg-AD Mice Are Restored by Early Ubiquinol Supplementation

Despite its robust proteopathic nature, the spatiotemporal signature of disrupted protein modules in sporadic Alzheimer’s disease (AD) brains remains poorly understood. This considered oxidative stress contributes to AD progression and early intervention with coenzyme Q10 or its reduced form, ubiquinol, delays the progression of the disease. Using MALDI–MSI and functional bioinformatic analysis, we have developed a protocol to express how deregulated protein modules arise from hippocampus and cortex in the AD mice model 3xTG-AD in an age-dependent manner. This strategy allowed us to identify which modules can be efficiently restored to a non-pathological condition by early intervention with ubiquinol. Indeed, an early deregulation of proteostasis-related protein modules, oxidative stress and metabolism has been observed in the hippocampus of 6-month mice (early AD) and the mirrored in cortical regions of 12-month mice (middle/late AD). This observation has been validated by IHC using mouse and human brain sections, suggesting that these protein modules are also affected in humans. The emergence of disrupted protein modules with AD signature can be prevented by early dietary intervention with ubiquinol in the 3xTG-AD mice model.

ImShot: An Open-Source Software for Probabilistic Identification of Proteins In Situ and Visualization of Proteomics Data

Imaging mass spectrometry (IMS) has developed into a powerful tool allowing label-free detection of numerous biomolecules in situ. In contrast to shotgun proteomics, proteins/peptides can be detected directly from biological tissues and correlated to its morphology leading to a gain of crucial clinical information. However, direct identification of the detected molecules is currently challenging for MALDI-IMS, thereby compelling researchers to use complementary techniques and resource intensive experimental setups. Despite these strategies, sufficient information could not be extracted because of lack of an optimum data combination strategy/software. Here, we introduce a new open-source software ImShot that aims at identifying peptides obtained in MALDI-IMS. This is achieved by combining information from IMS and shotgun proteomics (LC-MS) measurements of serial sections of the same tissue. The software takes advantage of a two-group comparison to determine the search space of IMS masses after deisotoping the corresponding spectra. Ambiguity in annotations of IMS peptides is eliminated by introduction of a novel scoring system that identifies the most likely parent protein of a detected peptide in the corresponding IMS dataset. Thanks to its modular structure, the software can also handle LC-MS data separately and display interactive enrichment plots and enriched Gene Ontology terms or cellular pathways. The software has been built as a desktop application with a conveniently designed graphic user interface to provide users with a seamless experience in data analysis. ImShot can run on all the three major desktop operating systems and is freely available under Massachusetts Institute of Technology license.

Evolution, expression patterns and distribution of novel ribbon worm predatory and defensive toxins

Ribbon worms are active predators that use an eversible proboscis to inject venom into their prey and defend themselves with toxic epidermal secretions. Previous work on nemertean venom has largely focused on just a few species and has not investigated the different predatory and defensive secretions in detail. Consequently, our understanding of the composition and evolution of ribbon worm venoms is still very limited. Here, we present a comparative study of nemertean venom combining RNA-seq differential gene expression analyses of venom-producing tissues, tandem mass spectrometry-based proteomics of toxic secretions, and mass spectrometry imaging of proboscis sections, to shed light onto the composition and evolution of predatory and defensive toxic secretions in Antarctonemertes valida. Our analyses reveal a wide diversity of putative defensive and predatory toxins with tissue-specific gene expression patterns and restricted distributions to the mucus and proboscis proteomes respectively, suggesting that ribbon worms produce distinct toxin cocktails for predation and defense. Our results also highlight the presence of numerous lineage-specific toxins, indicating that venom evolution is highly divergent across nemerteans, producing toxin cocktails that might be finely tuned to subdue different prey. Our data also suggest that the hoplonemertean proboscis is a highly specialized predatory organ that seems to be involved in a variety of biological functions besides predation, including secretion and sensory perception. Overall, our results advance our knowledge into the diversity and evolution of nemertean venoms and highlight the importance of combining different types of data to characterize toxin composition in understudied venomous organisms.

Spatial omics: Navigating to the golden era of cancer research

The idea that tumour microenvironment (TME) is organised in a spatial manner will not surprise many cancer biologists; however, systematically capturing spatial architecture of TME is still not possible until recent decade. The past five years have witnessed a boom in the research of high-throughput spatial techniques and algorithms to delineate TME at an unprecedented level. Here, we review the technological progress of spatial omics and how advanced computation methods boost multi-modal spatial data analysis. Then, we discussed the potential clinical translations of spatial omics research in precision oncology, and proposed a transfer of spatial ecological principles to cancer biology in spatial data interpretation. So far, spatial omics is placing us in the golden age of spatial cancer research. Further development and application of spatial omics may lead to a comprehensive decoding of the TME ecosystem and bring the current spatiotemporal molecular medical research into an entirely new paradigm.

Proteomic Analysis Identifies FNDC1, A1BG, and Antigen Processing Proteins Associated with Tumor Heterogeneity and Malignancy in a Canine Model of Breast Cancer

New insights into the underlying biological processes of breast cancer are needed for the development of improved markers and treatments. The complex nature of mammary cancer in dogs makes it a great model to study cancer biology since they present a high degree of tumor heterogeneity. In search of disease-state biomarkers candidates, we applied proteomic mass spectrometry imaging in order to simultaneously detect histopathological and molecular alterations whilst preserving morphological integrity, comparing peptide expression between intratumor populations in distinct levels of differentiation. Peptides assigned to FNDC1, A1BG, and double-matching keratins 18 and 19 presented a higher intensity in poorly differentiated regions. In contrast, we observed a lower intensity of peptides matching calnexin, PDIA3, and HSPA5 in poorly differentiated cells, which enriched for protein folding in the endoplasmic reticulum and antigen processing, assembly, and loading of class I MHC. Over-representation of collagen metabolism, coagulation cascade, extracellular matrix components, cadherin-binding and cell adhesion pathways also distinguished cell populations. Finally, an independent validation showed FNDC1, A1BG, PDIA3, HSPA5, and calnexin as significant prognostic markers for human breast cancer patients. Thus, through a spatially correlated characterization of spontaneous carcinomas, we described key proteins which can be further validated as potential prognostic biomarkers.

Automated annotation and visualisation of high-resolution spatial proteomic mass spectrometry imaging data using HIT-MAP

Spatial proteomics has the potential to significantly advance our understanding of biology, physiology and medicine. Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) is a powerful tool in the spatial proteomics field, enabling direct detection and registration of protein abundance and distribution across tissues. MALDI-MSI preserves spatial distribution and histology allowing unbiased analysis of complex, heterogeneous tissues. However, MALDI-MSI faces the challenge of simultaneous peptide quantification and identification. To overcome this, we develop and validate HIT-MAP (High-resolution Informatics Toolbox in MALDI-MSI Proteomics), an open-source bioinformatics workflow using peptide mass fingerprint analysis and a dual scoring system to computationally assign peptide and protein annotations to high mass resolution MSI datasets and generate customisable spatial distribution maps. HIT-MAP will be a valuable resource for the spatial proteomics community for analysing newly generated and retrospective datasets, enabling robust peptide and protein annotation and visualisation in a wide array of normal and disease contexts.

Strong additive and synergistic effects of polyoxyethylene nonionic surfactant-assisted protein MALDI imaging mass spectrometry

Protein MALDI imaging mass spectrometry (MALDI-IMS) holds a great promise to acquire spatial distribution information of proteins on biological tissue, but it suffers from the small number of proteins detected by direct MALDI-IMS detection. Ionic surfactants have been extensively used for protein extraction to improve the number of proteins detected in tissue samples by LC-MS analysis, but seldom by direct MALDI-IMS detection. Nonionic surfactants are milder than ionic surfactants and protein native structures are remained after extraction, which favors the spatial resolution of direct MALDI-IMS. However, nonionic surfactants are less effective than ionic surfactants. In this report, we utilized polyoxyethylene nonionic surfactants (PNS) to pre-incubate the tissue section, followed by the on-tissue trypsin digestion and then direct MALDI detection of in-situ formed peptides. For the first time, we observed that the additive effect of PNS and the synergistic effect of the mixed PNS in improving the number of peptides detected. Specifically, the peptides detected were 73.0-90.7% distinct when the different PNS (Tween 80 or Triton X-100 alone or their mixture) was used. Taking advantage of this additive effect, the 96 proteins including 12 transmembrane proteins were detected, corresponding to a ~10-fold improvement compared to MALDI-IMS without surfactant. When the mixed surfactants were used to replace Tween 80 and Triton X-100 alone, the optimized surfactant concentration decreased 20-100-fold and the number of peptides detected with m/z > 2500 Da was improved 15-fold. The additive and synergistic effects of PNS suggested that the interaction mode between each PNS and proteins is highly variable. Benefiting from the strong additive effect and diversity of PNS, further improvement of the number of proteins detected by MALDI-IMS is clearly feasible.

Collagen analysis with mass spectrometry

Mass spectrometry-based techniques can be applied to investigate collagen with respect to identification, quantification, supramolecular organization, and various post-translational modifications. The continuous interest in collagen research has led to a shift from techniques to analyze the physical characteristics of collagen to methods to study collagen abundance and modifications. In this review, we illustrate the potential of mass spectrometry for in-depth analyses of collagen.

Implementation of MALDI Mass Spectrometry Imaging in Cancer Proteomics Research: Applications and Challenges

Studying the proteome–the entire set of proteins in cells, tissues, organs and body fluids—is of great relevance in cancer research, as differential forms of proteins are expressed in response to specific intrinsic and extrinsic signals. Discovering protein signatures/pathways responsible for cancer transformation may lead to a better understanding of tumor biology and to a more effective diagnosis, prognosis, recurrence and response to therapy. Moreover, proteins can act as a biomarker or potential drug targets. Hence, it is of major importance to implement proteomic, particularly mass spectrometric, approaches in cancer research, to provide new crucial insights into tumor biology. Recently, mass spectrometry imaging (MSI) approaches were implemented in cancer research, to provide individual molecular characteristics of each individual tumor while retaining molecular spatial distribution, essential in the context of personalized disease management and medicine.

Derangements of amino acids in cachectic skeletal muscle are caused by mitochondrial dysfunction

BACKGROUND

Cachexia is the direct cause of at least 20% of cancer-associated deaths. Muscle wasting in skeletal muscle results in weakness, immobility, and death secondary to impaired respiratory muscle function. Muscle proteins are massively degraded in cachexia; nevertheless, the molecular mechanisms related to this process are poorly understood. Previous studies have reported conflicting results regarding the amino acid abundances in cachectic skeletal muscle tissues. There is a clear need to identify the molecular processes of muscle metabolism in the context of cachexia, especially how different types of molecules are involved in the muscle wasting process.

METHODS

New in situ -omics techniques were used to produce a more comprehensive picture of amino acid metabolism in cachectic muscles by determining the quantities of amino acids, proteins, and cellular metabolites. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging, we determined the in situ concentrations of amino acids and proteins, as well as energy and other cellular metabolites, in skeletal muscle tissues from genetic mouse cancer models (n = 21) and from patients with cancer (n = 6). Combined results from three individual MALDI mass spectrometry imaging methods were obtained and interpreted. Immunohistochemistry staining for mitochondrial proteins and myosin heavy chain expression, digital image analysis, and transmission electron microscopy complemented the MALDI mass spectrometry imaging results.

RESULTS

Metabolic derangements in cachectic mouse muscle tissues were detected, with significantly increased quantities of lysine, arginine, proline, and tyrosine (P = 0.0037, P = 0.0048, P = 0.0430, and P = 0.0357, respectively) and significantly reduced quantities of glutamate and aspartate (P = 0.0008 and P = 0.0124). Human skeletal muscle tissues revealed similar tendencies. A majority of altered amino acids were released by the breakdown of proteins involved in oxidative phosphorylation. Decreased energy charge was observed in cachectic muscle tissues (P = 0.0101), which was related to the breakdown of specific proteins. Additionally, expression of the cationic amino acid transporter CAT1 was significantly decreased in the mitochondria of cachectic mouse muscles (P = 0.0133); this decrease may play an important role in the alterations of cationic amino acid metabolism and decreased quantity of glutamate observed in cachexia.

CONCLUSIONS

Our results suggest that mitochondrial dysfunction has a substantial influence on amino acid metabolism in cachectic skeletal muscles, which appears to be triggered by diminished CAT1 expression, as well as the degradation of mitochondrial proteins. These findings provide new insights into the pathobiochemistry of muscle wasting.

Cardioprotective effect of ranolazine in nondiabetic and diabetic male rats subjected to isoprenaline-induced acute myocardial infarction involves modulation of AMPK and inhibition of apoptosis

Diabetes increases the sensitivity of myocardium to ischemic damage and impairs response of the myocardium to cardioprotective interventions. The present study aimed to elucidate the potential cardioprotective effect provided by ranolazine during myocardial infarction in nondiabetic and diabetic male rats. As AMP-activated protein kinase (AMPK) has been shown to be involved in the cellular response to ischemic injury, in this context, the present animal study evaluated the modulating role of ranolazine in the AMPK expression in isoprenaline-induced myocardial ischemic rat model. Male rats were divided into 2 experiments: experiment I and II (nondiabetic and diabetic rats) and assigned to normal control, saline control for isoprenaline, isoprenaline control, and ranolazine-treated groups. Ranolazine administration revealed effectiveness in attenuating the severity of isoprenaline-induced myocardial injury in both nondiabetic and diabetic rats as revealed by ECG signs, histopathological score, and apoptotic markers via abrogating the increments in the inflammatory and oxidative stress markers and modulating AMPK expression. Therefore, the current cardioprotective effect of ranolazine was, at least in part, mediated through inhibition of apoptosis and modulation of AMPK expression, encouraging considering the utility of ranolazine in protection from acute myocardial infarction.

MicroLESA: Integrating Autofluorescence Microscopy, In Situ Micro-Digestions, and Liquid Extraction Surface Analysis for High Spatial Resolution Targeted Proteomic Studies

The ability to target discrete features within tissue using liquid surface extractions enables the identification of proteins while maintaining the spatial integrity of the sample. Here, we present a liquid extraction surface analysis (LESA) workflow, termed microLESA, that allows proteomic profiling from discrete tissue features of ∼110 μm in diameter by integrating nondestructive autofluorescence microscopy and spatially targeted liquid droplet micro-digestion. Autofluorescence microscopy provides the visualization of tissue foci without the need for chemical stains or the use of serial tissue sections. Tryptic peptides are generated from tissue foci by applying small volume droplets (∼250 pL) of enzyme onto the surface prior to LESA. The microLESA workflow reduced the diameter of the sampled area almost 5-fold compared to previous LESA approaches. Experimental parameters, such as tissue thickness, trypsin concentration, and enzyme incubation duration, were tested to maximize proteomics analysis. The microLESA workflow was applied to the study of fluorescently labeled Staphylococcus aureus infected murine kidney to identify unique proteins related to host defense and bacterial pathogenesis. Proteins related to nutritional immunity and host immune response were identified by performing microLESA at the infectious foci and surrounding abscess. These identifications were then used to annotate specific proteins observed in infected kidney tissue by MALDI FT-ICR IMS through accurate mass matching.

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.

Integrative Clustering in Mass Spectrometry Imaging for Enhanced Patient Stratification

SCOPE

In biomedical research, mass spectrometry imaging (MSI) can obtain spatially-resolved molecular information from tissue sections. Especially matrix-assisted laser desorption/ionization (MALDI) MSI offers, depending on the type of matrix, the detection of a broad variety of molecules ranging from metabolites to proteins, thereby facilitating the collection of multilevel molecular data. Lately, integrative clustering techniques have been developed that make use of the complementary information of multilevel molecular data in order to better stratify patient cohorts, but which have not yet been applied in the field of MSI.

MATERIALS AND METHODS

In this study, the potential of integrative clustering is investigated for multilevel molecular MSI data to subdivide cancer patients into different prognostic groups. Metabolomic and peptidomic data are obtained by MALDI-MSI from a tissue microarray containing material of 46 esophageal cancer patients. The integrative clustering methods Similarity Network Fusion, iCluster, and moCluster are applied and compared to non-integrated clustering.

CONCLUSION

The results show that the combination of multilevel molecular data increases the capability of integrative algorithms to detect patient subgroups with different clinical outcome, compared to the single level or concatenated data. This underlines the potential of multilevel molecular data from the same subject using MSI for subsequent integrative clustering.

Spatially resolved metabolomics to discover tumor-associated metabolic alterations

Tumor cells reprogram their metabolism to support cell growth, proliferation, and differentiation, thus driving cancer progression. Profiling of the metabolic signatures in heterogeneous tumors facilitates the understanding of tumor metabolism and introduces potential metabolic vulnerabilities that might be targeted therapeutically. We proposed a spatially resolved metabolomics method for high-throughput discovery of tumor-associated metabolite and enzyme alterations using ambient mass spectrometry imaging. Metabolic pathway-related metabolites and metabolic enzymes that are associated with tumor metabolism were efficiently discovered and visualized in heterogeneous esophageal cancer tissues. Spatially resolved metabolic alterations hold the key to defining the dependencies of metabolism that are most limiting for cancer growth and exploring metabolic targeted strategies for better cancer treatment.

Characterization of tumor metabolism with spatial information contributes to our understanding of complex cancer metabolic reprogramming, facilitating the discovery of potential metabolic vulnerabilities that might be targeted for tumor therapy. However, given the metabolic variability and flexibility of tumors, it is still challenging to characterize global metabolic alterations in heterogeneous cancer. Here, we propose a spatially resolved metabolomics approach to discover tumor-associated metabolites and metabolic enzymes directly in their native state. A variety of metabolites localized in different metabolic pathways were mapped by airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) in tissues from 256 esophageal cancer patients. In combination with in situ metabolomics analysis, this method provided clues into tumor-associated metabolic pathways, including proline biosynthesis, glutamine metabolism, uridine metabolism, histidine metabolism, fatty acid biosynthesis, and polyamine biosynthesis. Six abnormally expressed metabolic enzymes that are closely associated with the altered metabolic pathways were further discovered in esophageal squamous cell carcinoma (ESCC). Notably, pyrroline-5-carboxylate reductase 2 (PYCR2) and uridine phosphorylase 1 (UPase1) were found to be altered in ESCC. The spatially resolved metabolomics reveal what occurs in cancer at the molecular level, from metabolites to enzymes, and thus provide insights into the understanding of cancer metabolic reprogramming.

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.

MALDI mass spectrometry imaging and in situ microproteomics of Listeria monocytogenes biofilms

MALDI-TOF Mass spectrometry Imaging (MSI) is a surface-sampling technology that can determine spatial information and relative abundance of analytes directly from biological samples. Human listeriosis cases are due to the ingestion of contaminated foods with the pathogenic bacteria Listeria monocytogenes. The reduction of water availability in food workshops by decreasing the air relative humidity (RH) is one strategy to improve the control of bacterial contamination. This study aims to develop and implement an MSI approach on L. monocytogenes biofilms and proof of concept using a dehumidified stress condition. MSI allowed examining the distribution of low molecular weight proteins within the biofilms subjected to a dehumidification environment, mimicking the one present in a food workshop (10 °C, 75% RH). Furthermore, a LC-MS/MS approach was made to link the dots between MSI and protein identification. Five identified proteins were assigned to registered MSI m/z, including two cold-shock proteins and a ligase involved in cell wall biogenesis. These data demonstrate how imaging can be used to dissect the proteome of an intact bacterial biofilm giving new insights into protein expression relating to a dehumidification stress adaptation. Data are available via ProteomeXchange with identifier PXD010444.

BIOLOGICAL SIGNIFICANCE

The ready-to-eat food processing industry has the daily challenge of controlling the contamination of surfaces and machines with spoilage and pathogenic microorganisms. In some cases, it is a lost cause due to these microorganisms' capacity to withstand the cleaning treatments, like desiccation procedures. Such a case is the ubiquitous Gram-positive Bacterium Listeria monocytogenes. Its surface proteins have particular importance for the interaction with its environment, being important factors contributing to adaptation to stress conditions. There are few reproducibly techniques to obtain the surface proteins of Gram-positive cells. Here, we developed a workflow that enables the use of MALDI imaging on Gram-positive bacterium biofilms to study the impact of dehumidification on sessile cells. It will be of the most interest to test this workflow with different environmental conditions and potentially apply it to other biofilm-forming bacteria.

Protein moonlighting elucidates the essential human pathway catalyzing lipoic acid assembly on its cognate enzymes

The lack of attachment of lipoic acid to its cognate enzyme proteins results in devastating human metabolic disorders. These mitochondrial disorders are evident soon after birth and generally result in early death. The mutations causing specific defects in lipoyl assembly map in three genes, LIAS, LIPT1, and LIPT2 Although physiological roles have been proposed for the encoded proteins, only the LIPT1 protein had been studied at the enzyme level. LIPT1 was reported to catalyze only the second partial reaction of the classical lipoate ligase mechanism. We report that the physiologically relevant LIPT1 enzyme activity is transfer of lipoyl moieties from the H protein of the glycine cleavage system to the E2 subunits of the 2-oxoacid dehydrogenases required for respiration (e.g., pyruvate dehydrogenase) and amino acid degradation. We also report that LIPT2 encodes an octanoyl transferase that initiates lipoyl group assembly. The human pathway is now biochemically defined.

Protein identification in imaging mass spectrometry through spatially targeted liquid micro-extractions

RATIONALE

Liquid extraction surface analysis (LESA) can be used to generate spatially directed protein identifications in an imaging mass spectrometry (IMS) workflow. This approach involves the use of robotic micro-extractions coupled to online liquid chromatography (LC). We have characterized the extraction efficiency of this method as well as its ability to identify proteins from a matrix assisted laser/desorption ionization (MALDI) IMS experiment.

METHODS

Proteins and peptides were extracted from transverse sections of a rat brain and sagittal sections of a mouse pup using liquid surface extractions. Extracts were either analyzed by online LC coupled to a high mass resolution Fourier transform ion cyclotron resonance (FTICR) mass spectrometer or collected offline and analyzed by traditional LC/MS methods. Identifications were made using both top-down and bottom-up methodologies. MALDI images were acquired on a 15T FTICR mass spectrometer at 125 μm spatial resolution.

RESULTS

Robotic liquid surface extractions are reproducible across various tissue types, providing significantly improved spatial resolution, with respect to extractions, while still allowing for a robust number of protein identifications. A single 2-μL extract can provide identification of over 14,000 peptides with little sample preparation, increasing throughput for spatially targeted workflows. Surface extractions from tissue were coupled directly to LC to gather spatially relevant proteomics data.

CONCLUSIONS

Robotic liquid surface extractions can be used to interrogate discrete regions of tissue to provide protein identifications with high throughput, accuracy, and robustness. The direct coupling of tissue surface extractions and LC offers a new and effective approach to provide spatial proteomics data in an imaging experiment.

Anatomical-Molecular Distribution of EphrinA1 in Infarcted Mouse Heart Using MALDI Mass Spectrometry Imaging

EphrinA1 is a tyrosine kinase receptor localized in the cellular membrane of healthy cardiomyocytes, the expression of which is lost upon myocardial infarction (MI). Intra-cardiac injection of the recombinant form of ephrinA1 (ephrinA1-Fc) at the time of ligation in mice has shown beneficial effects by reducing infarct size and myocardial necrosis post-MI. To date, immunohistochemistry and Western blotting comprise the only experimental approaches utilized to localize and quantify relative changes of ephrinA1 in sections and homogenates of whole left ventricle, respectively. Herein, we used matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) coupled with a time-of-flight mass spectrometer (MALDI/TOF MS) to identify intact as well as tryptic fragments of ephrinA1 in healthy controls and acutely infarcted murine hearts. The purpose of the present study was 3-fold: (1) to spatially resolve the molecular distribution of endogenous ephrinA1, (2) to determine the anatomical expression profile of endogenous ephrinA1 after acute MI, and (3) to identify molecular targets of ephrinA1-Fc action post-MI. The tryptic fragments detected were identified as the ephrinA1-isoform with 38% and 34% sequence coverage and Mascot scores of 25 for the control and MI hearts, respectively. By using MALDI-MSI, we have been able to simultaneously measure the distribution and spatial localization of ephrinA1, as well as additional cardiac proteins, thus offering valuable information for the elucidation of molecular partners, mediators, and targets of ephrinA1 action in cardiac muscle. Graphical Abstract ᅟ.

Spatially-Resolved Top-down Proteomics Bridged to MALDI MS Imaging Reveals the Molecular Physiome of Brain Regions

Tissue spatially-resolved proteomics was performed on 3 brain regions, leading to the characterization of 123 reference proteins. Moreover, 8 alternative proteins from alternative open reading frames (AltORF) were identified. Some proteins display specific post-translational modification profiles or truncation linked to the brain regions and their functions. Systems biology analysis performed on the proteome identified in each region allowed to associate sub-networks with the functional physiology of each brain region. Back correlation of the proteins identified by spatially-resolved proteomics at a given tissue localization with the MALDI MS imaging data, was then performed. As an example, mapping of the distribution of the matrix metallopeptidase 3-cleaved C-terminal fragment of α-synuclein (aa 95–140) identified its specific distribution along the hippocampal dentate gyrus. Taken together, we established the molecular physiome of 3 rat brain regions through reference and hidden proteome characterization.

High-grade sarcoma diagnosis and prognosis: Biomarker discovery by mass spectrometry imaging

The combination of high heterogeneity, both intratumoral and intertumoral, with their rarity has made diagnosis, prognosis of high-grade sarcomas difficult. There is an urgent need for more objective molecular biomarkers, to differentiate between the many different subtypes, and to also provide new treatment targets. Mass spectrometry imaging (MSI) has amply demonstrated its ability to identify potential new markers for patient diagnosis, survival, metastasis and response to therapy in cancer research. In this study, we investigated the ability of MALDI-MSI of proteins to distinguish between high-grade osteosarcoma (OS), leiomyosarcoma (LMS), myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) (Ntotal = 53). We also investigated if there are individual proteins or protein signatures that are statistically associated with patient survival. Twenty diagnostic protein signals were found characteristic for specific tumors (p ≤ 0.05), amongst them acyl-CoA-binding protein (m/z 11 162), macrophage migration inhibitory factor (m/z 12 350), thioredoxin (m/z 11 608) and galectin-1 (m/z 14 633) were assigned. Another nine protein signals were found to be associated with overall survival (p ≤ 0.05), including proteasome activator complex subunit 1 (m/z 9753), indicative for non-OS patients with poor survival; and two histone H4 variants (m/z 11 314 and 11 355), indicative of poor survival for LMS patients.

Functional imaging in combination with mutation status aids prediction of response to inhibiting B-cell receptor signaling in lymphoma

Aberrant B-cell receptor (BCR) signaling is known to contribute to malignant transformation. Two small molecule inhibitors targeting BCR pathway signaling include ibrutinib, a Bruton’s tyrosine kinase (BTK) inhibitor, and idelalisib, a specific Phosphatidylinositol-4,5-bisphosphate 3-kinase delta (PI3Kδ) inhibitor, both of which have been approved for use in haematological malignancies. Despite the identification of various diffuse large B-cell lymphoma (DLBCL) subtypes, mutation status alone is not sufficient to predict patient response and therapeutic resistance can arise. Herein we apply early molecular imaging across alternative activated B-cell (ABC) and germinal center B-cell (GCB) DLBCL subtypes to investigate the effects of BCR pathway inhibition. Treatment with both inhibitors adversely affected cell growth and viability. These effects were partially predictable based upon mutation status. Accordingly, very early 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography (¹⁸F-FDG-PET) and 3’-deoxy-3’[18F]-fluorothymidine positron emission tomography (¹⁸F-FLT-PET) reported tumour regression and reductions in tumour metabolism and proliferation upon treatment. Furthermore, matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) identified alterations in the proteome of a model of ABC DLBCL upon treatment with ibrutinib or idelalisib. In conclusion we demonstrate that very early molecular imaging adds predictive value in addition to mutational status of DLBCL that may be useful in directing patient therapy.

N-acyl Taurines and Acylcarnitines Cause an Imbalance in Insulin Synthesis and Secretion Provoking β Cell Dysfunction in Type 2 Diabetes

The processes contributing to β cell dysfunction in type 2 diabetes (T2D) are uncertain, largely because it is difficult to access β cells in their intact immediate environment. We examined the pathophysiology of β cells under T2D progression directly in pancreatic tissues. We used MALDI imaging of Langerhans islets (LHIs) within mouse tissues or from human tissues to generate in situ-omics data, which we supported with in vitro experiments. Molecular interaction networks provided information on functional pathways and molecules. We found that stearoylcarnitine accumulated in β cells, leading to arrest of insulin synthesis and energy deficiency via excessive β-oxidation and depletion of TCA cycle and oxidative phosphorylation metabolites. Acetylcarnitine and an accumulation of N-acyl taurines, a group not previously detected in β cells, provoked insulin secretion. Thus, β cell dysfunction results from enhanced insulin secretion combined with an arrest of insulin synthesis.

Microenvironment Tumor Metabolic Interactions Highlighted by qMSI: Application to the Tryptophan-Kynurenine Pathway in Immuno-Oncology

Inhibition of NK and effector T-cell functions and activation of regulatory cell populations are the main immunosuppressive effects of indoleamine-2,3-dioxygenase1 (IDO1). By converting tryptophan (Trp) into kynurenine (Kyn), IDO1 is involved in the immune response homeostasis, and its dysregulated expression is described in immune-related pathologies, as tumors that hijack it to evade immune destruction. Thereby, IDO1 inhibitors are being developed to stimulate antitumor immune responses. Existing and standard quantitation methods of IDO1 substrate and metabolite(s) are based on the total level of Trp and its metabolites determined by liquid chromatography tandem mass spectrometry analysis in human plasma, cerebrospinal fluid, and brain. Here, we describe the detection, localization, and absolute quantitation of Trp and Kyn by quantitative mass spectrometry imaging (qMSI) in transfected murine tumor models expressing various levels of IDO1. Myeloid, glycolysis metabolic signatures, and correlation between IDO1 expression and Trp to Kyn conversion are also shown. High-definition IDO1 and GCN2 immunostainings overlaid with Kyn molecular images underline the tumor metabolism and heterogeneity. The development of immunotherapies such as IDO1 inhibitors requires a deep understanding of the immune system, the interplay of cancer cells, and biomarker characterization. Our data underline that qMSI allows the study of the spatial distribution and quantitation of endogenous immune metabolites for biology and pharmacology studies.

Improving the analyte ion signal in matrix-assisted laser desorption/ionization imaging mass spectrometry via electrospray deposition by enhancing incorporation of the analyte in the matrix

RATIONALE

Matrix-assisted laser desorption/ionization (MALDI) is widely used as the ionization method in high-resolution chemical imaging studies that seek to visualize the distribution of analytes within sectioned biological tissues. This work extends the use of electrospray deposition (ESD) to apply matrix with an additional solvent spray to incorporate and homogenize analyte within the matrix overlayer.

METHODS

Analytes and matrix are sequentially and independently applied by ESD to create a sample from which spectra are collected, mimicking a MALDI imaging mass spectrometry (IMS) experiment. Subsequently, an incorporation spray consisting of methanol is applied by ESD to the sample and another set of spectra are collected. The spectra prior to and after the incorporation spray are compared to evaluate the improvement in the analyte signal.

RESULTS

Prior to the incorporation spray, samples prepared using α-cyano-4-hydroxycinnamic acid (CHCA) and 2,5-dihydroxybenzoic acid (DHB) as the matrix showed low signal while the sample using sinapinic acid (SA) initially exhibited good signal. Following the incorporation spray, the sample using SA did not show an increase in signal; the sample using DHB showed moderate gain factors of 2-5 (full ablation spectra) and 12-336 (raster spectra), while CHCA samples saw large increases in signal, with gain factors of 14-172 (full ablation spectra) and 148-1139 (raster spectra).

CONCLUSIONS

The use of an incorporation spray to apply solvent by ESD to a matrix layer already deposited by ESD provides an increase in signal by both promoting incorporation of the analyte within and homogenizing the distribution of the incorporated analyte throughout the matrix layer. Copyright © 2017 John Wiley & Sons, Ltd.

Ultra-High Mass Resolution MALDI Imaging Mass Spectrometry of Proteins and Metabolites in a Mouse Model of Glioblastoma

MALDI mass spectrometry imaging is able to simultaneously determine the spatial distribution of hundreds of molecules directly from tissue sections, without labeling and without prior knowledge. Ultra-high mass resolution measurements based on Fourier-transform mass spectrometry have been utilized to resolve isobaric lipids, metabolites and tryptic peptides. Here we demonstrate the potential of 15T MALDI-FTICR MSI for molecular pathology in a mouse model of high-grade glioma. The high mass accuracy and resolving power of high field FTICR MSI enabled tumor specific proteoforms, and tumor-specific proteins with overlapping and isobaric isotopic distributions to be clearly resolved. The protein ions detected by MALDI MSI were assigned to proteins identified by region-specific microproteomics (0.8 mm2 regions isolated using laser capture microdissection) on the basis of exact mass and isotopic distribution. These label free quantitative experiments also confirmed the protein expression changes observed by MALDI MSI and revealed changes in key metabolic proteins, which were supported by in-situ metabolite MALDI MSI.

Advances in MALDI imaging mass spectrometry of proteins in cardiac tissue, including the heart valve

Significant progress has been made for tissue imaging of proteins using matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS). These advancements now facilitate mapping of a wide range of proteins, peptides, and post-translational modifications in a wide variety of tissues; however, the use of MALDI IMS to detect proteins from cardiac tissue is limited. This review discusses the most recent advances in protein imaging and demonstrates application to cardiac tissue, including the heart valve. Protein imaging by MALDI IMS allows multiplexed histological mapping of proteins and protein components that are inaccessible by antibodies and should be considered an important tool for basic and clinical cardiovascular research. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

MALDI IMS and Cancer Tissue Microarrays

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) technology creates a link between the molecular assessment of numerous molecules and the morphological information about their special distribution. The application of MALDI IMS on formalin-fixed paraffin-embedded (FFPE) tissue microarrays (TMAs) is suitable for large-scale discovery analyses. Data acquired from FFPE TMA cancer samples in current research are very promising, and applications for routine diagnostics are under development. With the current rapid advances in both technology and applications, MALDI IMS technology is expected to enter into routine diagnostics soon. This chapter is intended to be comprehensive with respect to all aspects and considerations for the application of MALDI IMS on FFPE cancer TMAs with in-depth notes on technical aspects.

MALDI imaging mass spectrometry - From bench to bedside

Today, pathologists face many challenges in defining the precise morphomolecular diagnosis and in guiding clinicians to the optimal patients' treatment. To achieve this goal, increasingly, classical histomorphological methods have to be supplemented by high throughput molecular assays. Since MALDI imaging mass spectrometry (IMS) enables the assessment of spatial molecular arrangements in tissue sections, it goes far beyond microscopy in providing hundreds of different molecular images from a single scan without the need of target-specific reagents. Thus, this technology has the potential to uncover new markers for diagnostic purposes or markers that correlate with disease severity as well as prognosis and therapeutic response. Additionally, in the future MALDI IMS based classifiers measured with this technology in real time in the diagnostic setting might be applicable in the routine diagnostic setting. In this review, recently published studies that show the usefulness, advantages, and applicability of MALDI IMS in different fields of pathology (diagnosis, prognosis and treatment response) are highlighted. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

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.

MALDI mass spectrometry imaging in rheumatic diseases

Mass spectrometry imaging (MSI) is a technique used to visualize the spatial distribution of biomolecules such as peptides, proteins, lipids or other organic compounds by their molecular masses. Among the different MSI strategies, MALDI-MSI provides a sensitive and label-free approach for imaging of a wide variety of protein or peptide biomarkers from the surface of tissue sections, being currently used in an increasing number of biomedical applications such as biomarker discovery and tissue classification. In the field of rheumatology, MALDI-MSI has been applied to date for the analysis of joint tissues such as synovial membrane or cartilage. This review summarizes the studies and key achievements obtained using MALDI-MSI to increase understanding on rheumatic pathologies and to describe potential diagnostic or prognostic biomarkers of these diseases. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

An experimental guideline for the analysis of histologically heterogeneous tumors by MALDI-TOF mass spectrometry imaging

Mass spectrometry imaging (MSI) has been widely used for the direct molecular assessment of tissue samples and has demonstrated great potential to complement current histopathological methods in cancer research. It is now well established that tissue preparation is key to a successful MSI experiment; for histologically heterogeneous tumor tissues, other parts of the workflow are equally important to the experiment's success. To demonstrate these facets here we describe a matrix-assisted laser desorption/ionization MSI biomarker discovery investigation of high-grade, complex karyotype sarcomas, which often have histological overlap and moderate response to chemo-/radio-therapy. Multiple aspects of the workflow had to be optimized, ranging from the tissue preparation and data acquisition protocols, to the post-MSI histological staining method, data quality control, histology-defined data selection, data processing and statistical analysis. Only as a result of developing every step of the biomarker discovery workflow was it possible to identify a panel of protein signatures that could distinguish between different subtypes of sarcomas or could predict patient survival outcome. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

MALDI-imaging reveals thymosin beta-4 as an independent prognostic marker for colorectal cancer

DNA aneuploidy has been identified as a prognostic factor for epithelial malignancies. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a powerful tool for direct analysis of multiple proteins in tissue sections while maintaining the cellular and molecular integrity. We compared diploid and aneuploid colon cancer tissues against normal mucosa of the colon by means of IMS.

DNA image cytometry determined the ploidy status of tissue samples that were subsequently subjected to MALDI-IMS. After obtaining protein profiles through direct analysis of tissue sections, a discovery and independent validation set were used to predict ploidy status by applying proteomic classification algorithms [Supervised Neural Network (SNN) and Receiver Operating Characteristic (ROC)]. Five peaks (m/z 2,395 and 4,977 for diploid vs. aneuploid comparison as well as m/z 3,376, 6,663, and 8,581 for normal mucosa vs. carcinoma comparison) were significant in both SNN and ROC analysis. Among these, m/z 4,977 was identified as thymosin beta 4 (Tβ-4). Tβ-4 was subsequently validated in clinical samples using a tissue microarray to predict overall survival in colon cancer patients.

MALDI mass spectrometry imaging: A cutting-edge tool for fundamental and clinical histopathology

Histopathological diagnoses have been done in the last century based on hematoxylin and eosin staining. These methods were complemented by histochemistry, electron microscopy, immunohistochemistry (IHC), and molecular techniques. Mass spectrometry (MS) methods allow the thorough examination of various biocompounds in extracts and tissue sections. Today, mass spectrometry imaging (MSI), and especially matrix-assisted laser desorption ionization (MALDI) imaging links classical histology and molecular analyses. Direct mapping is a major advantage of the combination of molecular profiling and imaging. MSI can be considered as a cutting edge approach for molecular detection of proteins, peptides, carbohydrates, lipids, and small molecules in tissues. This review covers the detection of various biomolecules in histopathological sections by MSI. Proteomic methods will be introduced into clinical histopathology within the next few years.

Rapid Diagnosis of Lung Tumors, a Feasability Study Using Maldi-Tof Mass Spectrometry

OBJECTIVE

Despite recent advances in imaging and core or endoscopic biopsies, a percentage of patients have a major lung resection without diagnosis. We aimed to assess the feasibility of a rapid tissue preparation/analysis to discriminate cancerous from non-cancerous lung tissue.

METHODS

Fresh sample preparations were analyzed with the Microflex LTTM MALDI-TOF analyzer. Each main reference spectra (MSP) was consecutively included in a database. After definitive pathological diagnosis, each MSP was labeled as either cancerous or non-cancerous (normal, inflammatory, infectious nodules). A strategy was constructed based on the number of concordant responses of a mass spectrometry scoring algorithm. A 3-step evaluation included an internal and blind validation of a preliminary database (n = 182 reference spectra from the 100 first patients), followed by validation on a whole cohort database (n = 300 reference spectra from 159 patients). Diagnostic performance indicators were calculated.

RESULTS

127 cancerous and 173 non-cancerous samples (144 peripheral biopsies and 29 inflammatory or infectious lesions) were processed within 30 minutes after biopsy sampling. At the most discriminatory level, the samples were correctly classified with a sensitivity, specificity and global accuracy of 92.1%, 97.1% and 95%, respectively.

CONCLUSIONS

The feasibility of rapid MALDI-TOF analysis, coupled with a very simple lung preparation procedure, appears promising and should be tested in several surgical settings where rapid on-site evaluation of abnormal tissue is required. In the operating room, it appears promising in case of tumors with an uncertain preoperative diagnosis and should be tested as a complementary approach to frozen-biopsy analysis.

Protein biomarkers on tissue as imaged via MALDI mass spectrometry: A systematic approach to study the limits of detection

MALDI mass spectrometry imaging (MSI) is emerging as a tool for protein and peptide imaging across tissue sections. Despite extensive study, there does not yet exist a baseline study evaluating the potential capabilities for this technique to detect diverse proteins in tissue sections. In this study, we developed a systematic approach for characterizing MALDI-MSI workflows in terms of limits of detection, coefficients of variation, spatial resolution, and the identification of endogenous tissue proteins. Our goal was to quantify these figures of merit for a number of different proteins and peptides, in order to gain more insight in the feasibility of protein biomarker discovery efforts using this technique. Control proteins and peptides were deposited in serial dilutions on thinly sectioned mouse xenograft tissue. Using our experimental setup, coefficients of variation were <30% on tissue sections and spatial resolution was 200 μm (or greater). Limits of detection for proteins and peptides on tissue were in the micromolar to millimolar range. Protein identification was only possible for proteins present in high abundance in the tissue. These results provide a baseline for the application of MALDI-MSI towards the discovery of new candidate biomarkers and a new benchmarking strategy that can be used for comparing diverse MALDI-MSI workflows.

Potential of MALDI imaging for the toxicological evaluation of environmental pollutants

Risk assessment related to the exposure of humans to chemicals released into the environment is a major concern of our modern societies. In this context, toxicology plays a crucial role to characterize the effects of this exposure on health and identify the targets of these molecules. MALDI imaging mass spectrometry (IMS) is an enabling technology for biodistribution studies of chemicals. Although the majority of published studies are presented in a pharmacological context, the concepts discussed in this review can be applied to the toxicological evaluation of chemicals released into the environment. The major asset of IMS is the simultaneous localization and identification of a parent molecule and its metabolites without labeling and without any prior knowledge. Quantification methods developed in IMS are presented with application to an environmental pollutant. IMS is effective in the localization of chemicals and endogenous species. This opens unique perspectives for the discovery of molecular alterations in metabolites and protein biomarkers that could help for a better understanding of toxicity mechanisms. Distribution studies of agrochemicals in plants by IMS can contribute to a better understanding of their mode of action and to a more effective use of these chemicals, avoiding the current concern of environmental damage.

In situ detection of histone variants and modifications in mouse brain using imaging mass spectrometry

Histone posttranslational modifications and histone variants control the epigenetic regulation of gene expression and affect a wide variety of biological processes. A complex pattern of such modifications and variants defines the identity of cells within complex organ systems and can therefore be used to characterize cells at a molecular level. However, their detection and identification in situ has been limited so far due to lack of specificity, selectivity, and availability of antihistone antibodies. Here, we describe a novel MALDI imaging MS based workflow, which enables us to detect and characterize histones by their intact mass and their correlation with cytological properties of the tissue using novel statistical and image analysis tools. The workflow allows us to characterize the in situ distribution of the major histone variants and their modification in the mouse brain. This new analysis tool is particularly useful for the investigation of expression patterns of the linker histone H1 variants for which suitable antibodies are so far not available.

Proteomic Profiling in the Brain of CLN1 Disease Model Reveals Affected Functional Modules

Neuronal ceroid lipofuscinoses (NCL) are the most commonly inherited progressive encephalopathies of childhood. Pathologically, they are characterized by endolysosomal storage with different ultrastructural features and biochemical compositions. The molecular mechanisms causing progressive neurodegeneration and common molecular pathways linking expression of different NCL genes are largely unknown. We analyzed proteome alterations in the brains of a mouse model of human infantile CLN1 disease-palmitoyl-protein thioesterase 1 (Ppt1) gene knockout and its wild-type age-matched counterpart at different stages: pre-symptomatic, symptomatic and advanced. For this purpose, we utilized a combination of laser capture microdissection-based quantitative liquid chromatography tandem mass spectrometry (MS) and matrix-assisted laser desorption/ionization time-of-flight MS imaging to quantify/visualize the changes in protein expression in disease-affected brain thalamus and cerebral cortex tissue slices, respectively. Proteomic profiling of the pre-symptomatic stage thalamus revealed alterations mostly in metabolic processes and inhibition of various neuronal functions, i.e., neuritogenesis. Down-regulation in dynamics associated with growth of plasma projections and cellular protrusions was further corroborated by findings from RNA sequencing of CLN1 patients' fibroblasts. Changes detected at the symptomatic stage included: mitochondrial functions, synaptic vesicle transport, myelin proteome and signaling cascades, such as RhoA signaling. Considerable dysregulation of processes related to mitochondrial cell death, RhoA/Huntington's disease signaling and myelin sheath breakdown were observed at the advanced stage of the disease. The identified changes in protein levels were further substantiated by bioinformatics and network approaches, immunohistochemistry on brain tissues and literature knowledge, thus identifying various functional modules affected in the CLN1 childhood encephalopathy.