Region of Interest analysis using mass spectrometry imaging of mitochondrial and sarcomeric proteins in acute cardiac infarction tissue

eLIMS: Ensemble Learning-Based Spatial Segmentation of Mass Spectrometry Imaging to Explore Metabolic Heterogeneity

Spatial segmentation is an essential processing method for image analysis aiming to identify the characteristic suborgans or microregions from mass spectrometry imaging (MSI) data, which is critical for understanding the spatial heterogeneity of biological information and function and the underlying molecular signatures. Due to the intrinsic characteristics of MSI data including spectral nonlinearity, high-dimensionality, and large data size, the common segmentation methods lack the capability for capturing the accurate microregions associated with biological functions. Here we proposed an ensemble learning-based spatial segmentation strategy, named eLIMS, that combines a randomized unified manifold approximation and projection (r-UMAP) dimensionality reduction module for extracting significant features and an ensemble pixel clustering module for aggregating the clustering maps from r-UMAP. Three MSI datasets are used to evaluate the performance of eLIMS, including mouse fetus, human adenocarcinoma, and mouse brain. Experimental results demonstrate that the proposed method has potential in partitioning the heterogeneous tissues into several subregions associated with anatomical structure, i.e., the suborgans of the brain region in mouse fetus data are identified as dorsal pallium, midbrain, and brainstem. Furthermore, it effectively discovers critical microregions related to physiological and pathological variations offering new insight into metabolic heterogeneity.

Proteomic profiling of FFPE specimens: Discovery of HNRNPA2/B1 and STT3B as biomarkers for determining formalin fixation durations

Recent advancements in proteomics technologies using formalin-fixed paraffin-embedded (FFPE) samples have significantly advanced biomarker discovery. Yet, the effects of varying sample preparation protocols on proteomic analyses remain poorly understood. We analyzed mouse liver FFPE samples that varied in fixatives, fixation duration, and storage temperature using LC/MS. We found that variations in fixation duration significantly affected the abundance of specific proteins, showing that HNRNPA2/B1 demonstrated a significant decrease in abundance in samples fixed for long periods, whereas STT3B exhibited a significant increase in abundance in samples fixed for long durations. These findings were supported by immunohistochemical analysis across liver, spleen, and lung tissues, demonstrating a significant decrease in the nuclear staining of HNRNPA2/B1 in long-duration acid formalin(AF)-fixed FFPE samples, and an increase in cytoplasmic staining of STT3B in long-duration neutral buffered formalin-fixed liver and lung tissues and granular staining in all long-duration AF-fixed FFPE tissue types. Similar trends were observed in the long-duration fixed HeLa cells. These results demonstrate that fixation duration critically affects the proteomic integrity of FFPE samples, emphasizing the urgent need for standardized fixation protocols to ensure consistent and reliable proteomic data. SIGNIFICANCE: The quality of FFPE samples is primarily influenced by the fixation and storage conditions. However, previous studies have mainly focused on their impact on nucleic acids and the extent to which different fixation conditions affect changes in proteins has not been evaluated. In addition, to our knowledge, proteomic research focusing on differences in formalin fixation conditions has not yet been conducted. Here, we analyzed FFPE samples with different formalin fixation and storage conditions using LC/MS and evaluated the impact of different fixation conditions on protein variations. Our study unequivocally established formalin fixation duration as a critical determinant of protein variation in FFPE specimens and successfully identified HNRNPA2/B1 and STT3B as potential biomarkers for predicting formalin fixation duration for the first time. The study findings open new avenues for quality assessment in biomedical research and diagnostics.

Next-generation pathology practices with mass spectrometry imaging

Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology-related research. In this review, we summarize common MSI techniques, including matrix-assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next-generation pathology practices.

Protein Alterations in Cardiac Ischemia/Reperfusion Revealed by Spatial-Omics

Myocardial infarction is the most common cause of death worldwide. An understanding of the alterations in protein pathways is needed in order to develop strategies that minimize myocardial damage. To identify the protein signature of cardiac ischemia/reperfusion (I/R) injury in rats, we combined, for the first time, protein matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and label-free proteomics on the same tissue section placed on a conductive slide. Wistar rats were subjected to I/R surgery and sacrificed after 24 h. Protein MALDI-MSI data revealed ischemia specific regions, and distinct profiles for the infarct core and border. Firstly, the infarct core, compared to histologically unaffected tissue, showed a significant downregulation of cardiac biomarkers, while an upregulation was seen for coagulation and immune response proteins. Interestingly, within the infarct tissue, alterations in the cytoskeleton reorganization and inflammation were found. This work demonstrates that a single tissue section can be used for protein-based spatial-omics, combining MALDI-MSI and label-free proteomics. Our workflow offers a new methodology to investigate the mechanisms of cardiac I/R injury at the protein level for new strategies to minimize damage after MI.

Applications of MALDI-MS/MS-Based Proteomics in Biomedical Research

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is one of the most widely used techniques in proteomics to achieve structural identification and characterization of proteins and peptides, including their variety of proteoforms due to post-translational modifications (PTMs) or protein–protein interactions (PPIs). MALDI-MS and MALDI tandem mass spectrometry (MS/MS) have been developed as analytical techniques to study small and large molecules, offering picomole to femtomole sensitivity and enabling the direct analysis of biological samples, such as biofluids, solid tissues, tissue/cell homogenates, and cell culture lysates, with a minimized procedure of sample preparation. In the last decades, structural identification of peptides and proteins achieved by MALDI-MS/MS helped researchers and clinicians to decipher molecular function, biological process, cellular component, and related pathways of the gene products as well as their involvement in pathogenesis of diseases. In this review, we highlight the applications of MALDI ionization source and tandem approaches for MS for analyzing biomedical relevant peptides and proteins. Furthermore, one of the most relevant applications of MALDI-MS/MS is to provide “molecular pictures”, which offer in situ information about molecular weight proteins without labeling of potential targets. Histology-directed MALDI-mass spectrometry imaging (MSI) uses MALDI-ToF/ToF or other MALDI tandem mass spectrometers for accurate sequence analysis of peptide biomarkers and biological active compounds directly in tissues, to assure complementary and essential spatial data compared with those obtained by LC-ESI-MS/MS technique.

Yi-Xin-Shu capsule ameliorates cardiac hypertrophy by regulating RB/HDAC1/GATA4 signaling pathway based on proteomic and mass spectrometry image analysis

BACKGROUND

Cardiac hypertrophy (CH) forms the main pathological basis of chronic heart failure (CHF). Mitigating and preventing CH is the key strategy for the treatment of ventricular remodeling in CHF. Yi-Xin-Shu capsule (YXS) has been commonly applied in the clinical treatment of CHF in Asian countries for several decades. However, the underlying mechanism of YXS has not been revealed yet.

PURPOSE

To assess the efficiency of YXS in CH and identify its potential therapeutic targets for the managing of CH.

METHOD

Ultrasonic cardiogram was used to evaluate the cardiac function of CH rats. Hematein Eosin (HE)-staining, Masson-staining and transmission electron microscope were used to measure the morphological changes, cardiac fibrosis degree and ultrastructure characteristics of cardiomyocytes, respectively. ELISA was used to detect the myocardial injury biomarkers. Then, the potential targets regulated by YXS were screened out via proteomic analysis and mass spectrometry image analysis. Finally, the targets were validated by real-time quantitative (RT-q) PCR, immunofluorescence, immunohistochemistry, and western-blotting methods.

RESULTS

YXS improved the cardiac function of CH rats and attenuated the injuries in morphology and subcellular structure of cardiomyocytes. A core protein-protein interaction network was established on differentially expressed proteins (DEP) using proteomics analysis. GATA binding protein 4 (GATA4) was identified as the key target regulated by YXS. The results of mass spectrometry image analysis indicated that the expressions of histone deacetylase 1 (HDAC1) and retinoblastoma (RB) could also be regulated by YXS. Further valuative experiments showed that YXS may attenuate CH by regulating the RB/HDAC1/GATA4 signaling pathway.

CONCLUSIONS

For the first time, this study discloses the precise mechanism investigation of the efficacy of YXS against CH. These data demonstrate that YXS may protect against CH by regulating the RB/HDAC1/GATA4 signaling pathway.

MALDI-MSI Towards Multimodal Imaging: Challenges and Perspectives

Multimodal imaging is a powerful strategy for combining information from multiple images. It involves several fields in the acquisition, processing and interpretation of images. As multimodal imaging is a vast subject area with various combinations of imaging techniques, it has been extensively reviewed. Here we focus on Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) coupling other imaging modalities in multimodal approaches. While MALDI-MS images convey a substantial amount of chemical information, they are not readily informative about the morphological nature of the tissue. By providing a supplementary modality, MALDI-MS images can be more informative and better reflect the nature of the tissue. In this mini review, we emphasize the analytical and computational strategies to address multimodal MALDI-MSI.

Short-Term Blockade of Pro-Inflammatory Alarmin S100A9 Favorably Modulates Left Ventricle Proteome and Related Signaling Pathways Involved in Post-Myocardial Infarction Recovery

Prognosis after myocardial infarction (MI) varies greatly depending on the extent of damaged area and the management of biological processes during recovery. Reportedly, the inhibition of the pro-inflammatory S100A9 reduces myocardial damage after MI. We hypothesize that a S100A9 blockade induces changes of major signaling pathways implicated in post-MI healing. Mass spectrometry-based proteomics and gene analyses of infarcted mice left ventricle were performed. The S100A9 blocker (ABR-23890) was given for 3 days after coronary ligation. At 3 and 7 days post-MI, ventricle samples were analyzed versus control and Sham-operated mice. Blockade of S100A9 modulated the expressed proteins involved in five biological processes: leukocyte cell–cell adhesion, regulation of the muscle cell apoptotic process, regulation of the intrinsic apoptotic signaling pathway, sarcomere organization and cardiac muscle hypertrophy. The blocker induced regulation of 36 proteins interacting with or targeted by the cellular tumor antigen p53, prevented myocardial compensatory hypertrophy, and reduced cardiac markers of post-ischemic stress. The blockade effect was prominent at day 7 post-MI when the quantitative features of the ventricle proteome were closer to controls. Blockade of S100A9 restores key biological processes altered post-MI. These processes could be valuable new pharmacological targets for the treatment of ischemic heart. Mass spectrometry data are available via ProteomeXchange with identifier PXD033683.

Cellular Phenotypic Transformation in Heart Failure Caused by Coronary Heart Disease and Dilated Cardiomyopathy: Delineating at Single-Cell Level

Heart failure (HF) is known as the final manifestation of cardiovascular diseases. Although cellular heterogeneity of the heart is well understood, the phenotypic transformation of cardiac cells in progress of HF remains obscure. This study aimed to analyze phenotypic transformation of cardiac cells in HF through human single-cell RNA transcriptome profile. Here, phenotypic transformation of cardiomyocytes (CMs), endothelial cells (ECs), and fibroblasts was identified by data analysis and animal experiments. Abnormal myosin subunits including the decrease in Myosin Heavy Chain 6, Myosin Light Chain 7 and the increase in Myosin Heavy Chain 7 were found in CMs. Two disease phenotypes of ECs named inflammatory ECs and muscularized ECs were identified. In addition, myofibroblast was increased in HF and highly associated with abnormal extracellular matrix. Our study proposed an integrated map of phenotypic transformation of cardiac cells and highlighted the intercellular communication in HF. This detailed definition of cellular transformation will facilitate cell-based mapping of novel interventional targets for the treatment of HF.

Spatial proteomic alterations detected via MALDI-MS imaging implicate neuronal loss in a Huntington's disease mouse (YAC128) brain

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that occurs with the increase of CAG trinucleotide repeats in the huntingtin gene. To understand the mechanisms of HD, powerful proteomics techniques, such as liquid chromatography-tandem mass spectrometry (LC-MS/MS) were employed. However, one major drawback of these methods is loss of the region-specific quantitative information of the proteins due to analysis of total tissue lysates. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a MS-based label-free technique that works directly on tissue sections and gathers m/z values with their respective regional information. In this study, we established a data processing protocol that includes several software programs and methods to determine spatial protein alterations between the brain samples of a 12 month-old YAC128 HD mouse model and their non-transgenic littermates. 22 differentially expressed proteins were revealed with their respective regional information, and possible relationships of several proteins were discussed. As a validation of the MALDI-MSI analysis, a differentially expressed protein (GFAP) was verified using immunohistochemical staining. Furthermore, since several proteins detected in this study have previously been associated with neuronal loss, neuronal loss in the cortical region was demonstrated using an anti-NeuN immunohistochemical staining method. In conclusion, the findings of this research have provided insights into the spatial proteomic changes between HD transgenic and non-transgenic littermates and therefore, we suggest that MALDI-MSI is a powerful technique to determine spatial proteomic alterations between biological samples, and the data processing that we present here can be employed as a complementary tool for the data analysis.

Copper adhesive tape attached to the reverse side of a non-conductive glass slide to achieve protein MALDI-imaging in FFPE-tissue sections

Herein, copper adhesive tape attached to the reverse side of a glass slide was developed as a new method to achieve protein in situ detection and imaging in a formalin fixed paraffin-embedded (FFPE) tissue section on a non-conductive glass slide by MALDI-MSI. The use of this new method led to 223 protein ions being imaged from a rat brain FFPE-tissue section on a non-conductive glass slide by MALDI-MS, compared to only 145 and 163 protein ions detected on an ITO glass slide and an AnchorChip target plate, respectively. This new method has great potential to become standard practice for protein MALDI-imaging in FFPE-tissue sections on non-conductive glass slides.

Detecting early myocardial ischemia in rat heart by MALDI imaging mass spectrometry

Diagnostics of myocardial infarction in human post-mortem hearts can be achieved only if ischemia persisted for at least 6–12 h when certain morphological changes appear in myocardium. The initial 4 h of ischemia is difficult to diagnose due to lack of a standardized method. Developing a panel of molecular tissue markers is a promising approach and can be accelerated by characterization of molecular changes. This study is the first untargeted metabolomic profiling of ischemic myocardium during the initial 4 h directly from tissue section. Ischemic hearts from an ex-vivo Langendorff model were analysed using matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) at 15 min, 30 min, 1 h, 2 h, and 4 h. Region-specific molecular changes were identified even in absence of evident histological lesions and were segregated by unsupervised cluster analysis. Significantly differentially expressed features were detected by multivariate analysis starting at 15 min while their number increased with prolonged ischemia. The biggest significant increase at 15 min was observed for m/z 682.1294 (likely corresponding to S-NADHX—a damage product of nicotinamide adenine dinucleotide (NADH)). Based on the previously reported role of NAD⁺/NADH ratio in regulating localization of the sodium channel (Na_v1.5) at the plasma membrane, Na_v1.5 was evaluated by immunofluorescence. As expected, a fainter signal was observed at the plasma membrane in the predicted ischemic region starting 30 min of ischemia and the change became the most pronounced by 4 h. Metabolomic changes occur early during ischemia, can assist in identifying markers for post-mortem diagnostics and improve understanding of molecular mechanisms.

Spatial Segmentation of Mass Spectrometry Imaging Data by Combining Multivariate Clustering and Univariate Thresholding

Spatial segmentation partitions mass spectrometry imaging (MSI) data into distinct regions, providing a concise visualization of the vast amount of data and identifying regions of interest (ROIs) for downstream statistical analysis. Unsupervised approaches are particularly attractive, as they may be used to discover the underlying subpopulations present in the high-dimensional MSI data without prior knowledge of the properties of the sample. Herein, we introduce an unsupervised spatial segmentation approach, which combines multivariate clustering and univariate thresholding to generate comprehensive spatial segmentation maps of the MSI data. This approach combines matrix factorization and manifold learning to enable high-quality image segmentation without an extensive hyperparameter search. In parallel, some ion images inadequately represented in the multivariate analysis were treated using univariate thresholding to generate complementary spatial segments. The final spatial segmentation map was assembled from segment candidates that were generated using both techniques. We demonstrate the performance and robustness of this approach for two MSI data sets of mouse uterine and kidney tissue sections that were acquired with different spatial resolutions. The resulting segmentation maps are easy to interpret and project onto the known anatomical regions of the tissue.

Multimodal MALDI Imaging Mass Spectrometry Reveals Spatially Correlated Lipid and Protein Changes in Mouse Heart with Acute Myocardial Infarction

Acute myocardial infarction (MI) is a cardiovascular disease that remains a major cause of morbidity and mortality worldwide despite advances in its prevention and treatment. During acute myocardial ischemia, the lack of oxygen switches the cell metabolism to anaerobic respiration, with lactate accumulation, ATP depletion, Na⁺ and Ca²⁺ overload, and inhibition of myocardial contractile function, which drastically modifies the lipid, protein, and small metabolite profile in the myocardium. Imaging mass spectrometry (IMS) is a powerful technique to comprehensively elucidate the spatial distribution patterns of lipids, peptides, and proteins in biological tissue sections. In this work, we demonstrate an application of multimodal chemical imaging using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), which provided comprehensive molecular information in situ within the same mouse heart tissue sections with myocardial infarction. MALDI-IMS (at 30 μm per pixel) revealed infarct-associated spatial alterations of several lipid species of sphingolipids, glycerophospholipids, lysophospholipids, and cardiolipins along with the acyl carnitines. Further, we performed multimodal MALDI-IMS (IMS3) where dual polarity lipid imaging was combined with subsequent protein MALDI-IMS analysis (at 30 μm per pixel) within the same tissue sections, which revealed accumulations of core histone proteins H4, H2A, and H2B along with post-translational modification products, acetylated H4 and H2A, on the borders of the infarcted region. This methodology allowed us to interpret the lipid and protein molecular pathology of the very same infarcted region in a mouse model of myocardial infarction. Therefore, the presented data highlight the potential of multimodal MALDI imaging mass spectrometry of the same tissue sections as a powerful approach for simultaneous investigation of spatial infarct-associated lipid and protein changes of myocardial infarction.

Mass Spectrometric (MS) Analysis of Proteins and Peptides

The human genome is sequenced and comprised of ~30,000 genes, making humans just a little bit more complicated than worms or flies. However, complexity of humans is given by proteins that these genes code for because one gene can produce many proteins mostly through alternative splicing and tissue-dependent expression of particular proteins. In addition, post-translational modifications (PTMs) in proteins greatly increase the number of gene products or protein isoforms. Furthermore, stable and transient interactions between proteins, protein isoforms/proteoforms and PTM-ed proteins (protein-protein interactions, PPI) add yet another level of complexity in humans and other organisms. In the past, all of these proteins were analyzed one at the time. Currently, they are analyzed by a less tedious method: mass spectrometry (MS) for two reasons: 1) because of the complexity of proteins, protein PTMs and PPIs and 2) because MS is the only method that can keep up with such a complex array of features. Here, we discuss the applications of mass spectrometry in protein analysis.

Hierarchical Cluster and Region of Interest Analyses Based on Mass Spectrometry Imaging of Human Brain Tumours

Imaging mass spectrometry (IMS) has been rarely used to examine specimens of human brain tumours. In the current study, high quality brain tumour samples were selected by tissue observation. Further, IMS analysis was combined with a new hierarchical cluster analysis (IMS-HCA) and region of interest analysis (IMS-ROI). IMS-HCA was successful in creating groups consisting of similar signal distribution images of glial fibrillary acidic protein (GFAP) and related multiple proteins in primary brain tumours. This clustering data suggested the relation of GFAP and these identified proteins in the brain tumorigenesis. Also, high levels of histone proteins, haemoglobin subunit α, tubulins, and GFAP were identified in a metastatic brain tumour using IMS-ROI. Our results show that IMS-HCA and IMS-ROI are promising techniques for identifying biomarkers using brain tumour samples.

Single organelle function and organization as estimated from Arabidopsis mitochondrial proteomics

Mitochondria host vital cellular functions, including oxidative phosphorylation and co-factor biosynthesis, which are reflected in their proteome. At the cellular level plant mitochondria are organized into hundreds of discrete functional entities, which undergo dynamic fission and fusion. It is the individual organelle that operates in the living cell, yet biochemical and physiological assessments have exclusively focused on the characteristics of large populations of mitochondria. Here, we explore the protein composition of an individual average plant mitochondrion to deduce principles of functional and structural organisation. We perform proteomics on purified mitochondria from cultured heterotrophic Arabidopsis cells with intensity-based absolute quantification and scale the dataset to the single organelle based on criteria that are justified by experimental evidence and theoretical considerations. We estimate that a total of 1.4 million protein molecules make up a single Arabidopsis mitochondrion on average. Copy numbers of the individual proteins span five orders of magnitude, ranging from >40 000 for Voltage-Dependent Anion Channel 1 to sub-stoichiometric copy numbers, i.e. less than a single copy per single mitochondrion, for several pentatricopeptide repeat proteins that modify mitochondrial transcripts. For our analysis, we consider the physical and chemical constraints of the single organelle and discuss prominent features of mitochondrial architecture, protein biogenesis, oxidative phosphorylation, metabolism, antioxidant defence, genome maintenance, gene expression, and dynamics. While assessing the limitations of our considerations, we exemplify how our understanding of biochemical function and structural organization of plant mitochondria can be connected in order to obtain global and specific insights into how organelles work.

rMSIKeyIon: An Ion Filtering R Package for Untargeted Analysis of Metabolomic LDI-MS Images

Many MALDI-MS imaging experiments make a case versus control studies of different tissue regions in order to highlight significant compounds affected by the variables of study. This is a challenge because the tissue samples to be compared come from different biological entities, and therefore they exhibit high variability. Moreover, the statistical tests available cannot properly compare ion concentrations in two regions of interest (ROIs) within or between images. The high correlation between the ion concentrations due to the existence of different morphological regions in the tissue means that the common statistical tests used in metabolomics experiments cannot be applied. Another difficulty with the reliability of statistical tests is the elevated number of undetected MS ions in a high percentage of pixels. In this study, we report a procedure for discovering the most important ions in the comparison of a pair of ROIs within or between tissue sections. These ROIs were identified by an unsupervised segmentation process, using the popular k-means algorithm. Our ion filtering algorithm aims to find the up or down-regulated ions between two ROIs by using a combination of three parameters: (a) the percentage of pixels in which a particular ion is not detected, (b) the Mann–Whitney U ion concentration test, and (c) the ion concentration fold-change. The undetected MS signals (null peaks) are discarded from the histogram before the calculation of (b) and (c) parameters. With this methodology, we found the important ions between the different segments of a mouse brain tissue sagittal section and determined some lipid compounds (mainly triacylglycerols and phosphatidylcholines) in the liver of mice exposed to thirdhand smoke.

Trends in mass spectrometry imaging for cardiovascular diseases

Mass spectrometry imaging (MSI) is a widely established technology; however, in the cardiovascular research field, its use is still emerging. The technique has the advantage of analyzing multiple molecules without prior knowledge while maintaining the relation with tissue morphology. Particularly, MALDI-based approaches have been applied to obtain in-depth knowledge of cardiac (dys)function. Here, we discuss the different aspects of the MSI protocols, from sample handling to instrumentation used in cardiovascular research, and critically evaluate these methods. The trend towards structural lipid analysis, identification, and “top-down” protein MSI shows the potential for implementation in (pre)clinical research and complementing the diagnostic tests. Moreover, new insights into disease progression are expected and thereby contribute to the understanding of underlying mechanisms related to cardiovascular diseases.

Protein identification strategies in MALDI imaging mass spectrometry: a brief review

Matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a powerful technology used to investigate the spatial distributions of thousands of molecules throughout a tissue section from a single experiment. As proteins represent an important group of functional molecules in tissue and cells, the imaging of proteins has been an important point of focus in the development of IMS technologies and methods. Protein identification is crucial for the biological contextualization of molecular imaging data. However, gas-phase fragmentation efficiency of MALDI generated proteins presents significant challenges, making protein identification directly from tissue difficult. This review highlights methods and technologies specifically related to protein identification that have been developed to overcome these challenges in MALDI IMS experiments.

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.