Comprehensive Analysis of the Mouse Brain Proteome Sampled in Mass Spectrometry Imaging

Pressure Cycling Technology Combined With MicroLC-SWATH Mass Spectrometry for the Analysis of Sex-Related Differences Between Male and Female Cerebella: A Promising Approach to Investigating Proteomics Differences in Psychiatric and Neurodegenerative Diseases

PURPOSE

Pressure cycling technology (PCT) coupled with data-independent sequential window acquisition of all theoretical mass spectra (SWATH-MS) can be a powerful tool for identifying and quantifying biomarkers (e.g., proteins) in complex biological samples. Mouse models are frequently used in brain studies, including those focusing on different neurodevelopmental and psychiatric disorders. More and more pieces of evidence have suggested that sex-related differences in the brain impact the rates, clinical manifestations, and therapy outcomes of these disorders. However, sex-based differences in the proteomic profiles of mouse cerebella have not been widely investigated.

EXPERIMENTAL DESIGN

In this pilot study, we evaluate the applicability of coupling PCT sample preparation with microLC-SWATH-MS analysis to map and identify differences in the proteomes of two female and two male mice cerebellum samples.

RESULTS

We identified and quantified 174 proteins in mice cerebella. A comparison of the proteomic profiles revealed that the levels of 11 proteins in the female and male mice cerebella varied significantly.

CONCLUSIONS AND CLINICAL RELEVANCE

Although this study utilizes a small sample, our results indicate that the studied male and female mice cerebella possessed differing proteome compositions, mainly with respect to energy metabolism processes.

Spatial Multiomics of Lipids, N-Glycans, and Tryptic Peptides on a Single FFPE Tissue Section

Mass spectrometry imaging (MSI) is an emerging technology that is capable of mapping various biomolecules within their native spatial context, and performing spatial multiomics on formalin-fixed paraffin-embedded (FFPE) tissues may further increase the molecular characterization of pathological states. Here we present a novel workflow which enables the sequential MSI of lipids, N-glycans, and tryptic peptides on a single FFPE tissue section and highlight the enhanced molecular characterization that is offered by combining the multiple spatial omics data sets. In murine brain and clear cell renal cell carcinoma (ccRCC) tissue, the three molecular levels provided complementary information and characterized different histological regions. Moreover, when the spatial omics data was integrated, the different histopathological regions of the ccRCC tissue could be better discriminated with respect to the imaging data set of any single omics class. Taken together, these promising findings demonstrate the capability to more comprehensively map the molecular complexity within pathological tissue.

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.

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.

Enhancement of Tryptic Peptide Signals from Tissue Sections Using MALDI IMS Postionization (MALDI-2)

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) allows for highly multiplexed, unlabeled mapping of analytes from tissue sections. However, further work is needed to improve the sensitivity and depth of coverage for protein and peptide IMS. We demonstrate signal enhancement of proteolytic peptides from thin tissue sections of human kidney by conventional MALDI (MALDI-1) augmented using a second ionizing laser (termed MALDI-2). Proteins were digested in situ using trypsin prior to IMS analysis. For tentative identification of peptides and proteins, a tissue homogenate from the same organ used for IMS was analyzed by LC-MS/MS, and data are available via ProteomeXchange with identifier PXD023877. These identified proteins were then digested in silico to generate a database of theoretical peptides to then match to MALDI IMS data sets. Peptides were tentatively identified by matching the MALDI peak list to the database peptide list based on mass accuracy (5 ppm mass error). This resulted in 1337 ± 96 (n = 3) peptides and 2076 ± 362 (n = 3) unique peptides matched to IMS peaks from MALDI-1 and MALDI-2, respectively. Protein identifications requiring two or more peptides per protein resulted in 276 ± 20 proteins with MALDI-1 and 401 ± 60 with MALDI-2. These results demonstrate that MALDI-2 provides enhanced sensitivity for the spatial mapping of tryptic peptides and significantly increases the number of proteins identified in IMS experiments.

Mass Spectrometry Imaging for Glycome in the Brain

Glycans are diverse structured biomolecules that play crucial roles in various biological processes. Glycosylation, an enzymatic system through which various glycans are bound to proteins and lipids, is the most common and functionally crucial post-translational modification process. It is known to be associated with brain development, signal transduction, molecular trafficking, neurodegenerative disorders, psychopathologies, and brain cancers. Glycans in glycoproteins and glycolipids expressed in brain cells are involved in neuronal development, biological processes, and central nervous system maintenance. The composition and expression of glycans are known to change during those physiological processes. Therefore, imaging of glycans and the glycoconjugates in the brain regions has become a “hot” topic nowadays. Imaging techniques using lectins, antibodies, and chemical reporters are traditionally used for glycan detection. However, those techniques offer limited glycome detection. Mass spectrometry imaging (MSI) is an evolving field that combines mass spectrometry with histology allowing spatial and label-free visualization of molecules in the brain. In the last decades, several studies have employed MSI for glycome imaging in brain tissues. The current state of MSI uses on-tissue enzymatic digestion or chemical reaction to facilitate successful glycome imaging. Here, we reviewed the available literature that applied MSI techniques for glycome visualization and characterization in the brain. We also described the general methodologies for glycome MSI and discussed its potential use in the three-dimensional MSI in the brain.

Electroblotting through Enzymatic Membranes to Enhance Molecular Tissue Imaging

MALDI-TOF mass spectrometry imaging (MSI) is a powerful tool for studying biomolecule localization in tissue. Protein distributions in tissue provide important histological information; however, large proteins exhibit a high limit of detection in MALDI-MS when compared to their corresponding smaller proteolytic peptides. As a result, several techniques have emerged to digest proteins into more detectable peptides for imaging. Digestion is typically accomplished through trypsin deposition on the tissue, but this technique increases the complexity of the tissue microenvironment, which can limit the number of detectable species. This proof-of-principle study explores tryptic tissue digestion during electroblotting through a trypsin-containing membrane. This approach actively extracts and enzymatically digests proteins from mouse brain tissue sections while simultaneously reducing the complexity of the tissue microenvironment (compared to trypsin deposition on the surface) to obtain an increased number of detectable peptide fragments. The method does not greatly compromise spatial location or require expensive devices to uniformly deposit trypsin on tissue. Using electrodigestion through membranes, we detected and tentatively identified several tryptic peptides that were not observed after on-tissue digestion. Moreover, the use of pepsin rather than trypsin in digestion membranes allows extraction and digestion at low pH to detect peptides from a complementary subset of tissue proteins. Future studies will aim to further improve the method, including changing the substrate membrane to increase spatial resolution and the number of detected peptides.

Array-Based N-Glycan Profiling of Cells in Culture

N-glycan imaging mass spectrometry (N-glycan IMS) enables the detection and characterization of N-glycans in thin histological tissue sections. N-glycan IMS is used to study N-glycan regulation and localization in tissue-specific regions, such as tumor and normal adjacent to tumor, or by cell type within a tissue. Once a specific tissue-localized N-glycan signature is found to be associated with by a disease state, it has been challenging to study modulation of the same N-glycan signature by conventional molecular biology techniques. Here we describe a protocol that adapts tissue N-glycan IMS analysis workflows to cells grown on glass slides in an array format. Cells are grown under normal conditions in a cell culture chamber, fixed to maintain normal morphology, and sprayed with a thin coating of PNGase F to release N-glycans for imaging mass spectrometry profiling.

Molecular signatures of tumor progression in myxoid liposarcoma identified by N-glycan mass spectrometry imaging

Myxoid liposarcoma (MLS) is the second most common subtype of liposarcoma, accounting for ~6% of all sarcomas. MLS is characterized by a pathognomonic FUS-DDIT3, or rarely EWSR1-DDIT3, gene fusion. The presence of ≥5% hypercellular round cell areas is associated with a worse prognosis for the patient and is considered high grade. The prognostic significance of areas with moderately increased cellularity (intermediate) is currently unknown. Here we have applied matrix-assisted laser desorption/ionization mass spectrometry imaging to analyze the spatial distribution of N-linked glycans on an MLS microarray in order to identify molecular markers for tumor progression. Comparison of the N-glycan profiles revealed that increased relative abundances of high-mannose type glycans were associated with tumor progression. Concomitantly, an increase of the average number of mannoses on high-mannose glycans was observed. Although overall levels of complex-type glycans decreased, an increase of tri- and tetra-antennary N-glycans was observed with morphological tumor progression and increased tumor histological grade. The high abundance of tri-antennary N-glycan species was also associated with poor disease-specific survival. These findings mirror recent observations in colorectal cancer, breast cancer, ovarian cancer, and cholangiocarcinoma, and are in line with a general role of high-mannose glycans and higher-antennary complex-type glycans in cancer progression.

Classification of Thyroid Tumors Based on Mass Spectrometry Imaging of Tissue Microarrays; a Single-Pixel Approach

The primary diagnosis of thyroid tumors based on histopathological patterns can be ambiguous in some cases, so proper classification of thyroid diseases might be improved if molecular biomarkers support cytological and histological assessment. In this work, tissue microarrays representative for major types of thyroid malignancies—papillary thyroid cancer (classical and follicular variant), follicular thyroid cancer, anaplastic thyroid cancer, and medullary thyroid cancer—and benign thyroid follicular adenoma and normal thyroid were analyzed by mass spectrometry imaging (MSI), and then different computation approaches were implemented to test the suitability of the registered profiles of tryptic peptides for tumor classification. Molecular similarity among all seven types of thyroid specimens was estimated, and multicomponent classifiers were built for sample classification using individual MSI spectra that corresponded to small clusters of cells. Moreover, MSI components showing the most significant differences in abundance between the compared types of tissues detected and their putative identity were established by annotation with fragments of proteins identified by liquid chromatography-tandem mass spectrometry in corresponding tissue lysates. In general, high accuracy of sample classification was associated with low inter-tissue similarity index and a high number of components with significant differences in abundance between the tissues. Particularly, high molecular similarity was noted between three types of tumors with follicular morphology (adenoma, follicular cancer, and follicular variant of papillary cancer), whose differentiation represented the major classification problem in our dataset. However, low level of the intra-tissue heterogeneity increased the accuracy of classification despite high inter-tissue similarity (which was exemplified by normal thyroid and benign adenoma). We compared classifiers based on all detected MSI components (n = 1536) and the subset of the most abundant components (n = 147). Despite relatively higher contribution of components with significantly different abundance and lower overall inter-tissue similarity in the latter case, the precision of classification was generally higher using all MSI components. Moreover, the classification model based on individual spectra (a single-pixel approach) outperformed the model based on mean spectra of tissue cores. Our result confirmed the high feasibility of MSI-based approaches to multi-class detection of cancer types and proved the good performance of sample classification based on individual spectra (molecular image pixels) that overcame problems related to small amounts of heterogeneous material, which limit the applicability of classical proteomics.

Proteomic profiling of striatal tissue of a rat model of Parkinson's disease after implantation of collagen-encapsulated human umbilical cord mesenchymal stem cells

Parkinson's disease (PD) is the most common neurodegenerative disorder of movement worldwide. To date, only symptomatic treatments are available. Implantation of collagen‐encapsulated human umbilical cord mesenchymal stem cells (hUC‐MSCs) is being developed as a novel therapeutic approach to potentially modify PD progression. However, implanted collagen scaffolds may induce a host tissue response. To gain insight into such response, hUC‐MSCs were encapsulated into collagen hydrogels and implanted into the striatum of hemi‐Parkinsonian male Sprague–Dawley rats. One or 14 days after implantation, the area of interest was dissected using a cryostat. Total protein extracts were subjected to tryptic digestion and subsequent LC–MS/MS analyses for protein expression profiling. Univariate and multivariate analyses were performed to identify differentially expressed protein profiles with subsequent gene ontology and pathway analysis for biological interpretation of the data; 2,219 proteins were identified by MaxQuant at 1% false discovery rate. A high correlation of label‐free quantification (LFQ) protein values between biological replicates (r = .95) was observed. No significant differences were observed between brains treated with encapsulated hUC‐MSCs compared to appropriate controls. Proteomic data were highly robust and reproducible, indicating the suitability of this approach to map differential protein expression caused by the implants. The lack of differences between conditions suggests that the effects of implantation may be minimal. Alternatively, effects may only have been focal and/or could have been masked by nonrelevant high‐abundant proteins. For follow‐up assessment of local changes, a more accurate dissection technique, such as laser micro dissection, and analysis method are recommended.

Cellular resolution in clinical MALDI mass spectrometry imaging: the latest advancements and current challenges

Mass spectrometry (MS) is the workhorse of metabolomics, proteomics and lipidomics. Mass spectrometry imaging (MSI), its extension to spatially resolved analysis of tissues, is a powerful tool for visualizing molecular information within the histological context of tissue. This review summarizes recent developments in MSI and highlights current challenges that remain to achieve molecular imaging at the cellular level of clinical specimens. We focus on matrix-assisted laser desorption/ionization (MALDI)-MSI. We discuss the current status of each of the analysis steps and remaining challenges to reach the desired level of cellular imaging. Currently, analyte delocalization and degradation, matrix crystal size, laser focus restrictions and detector sensitivity are factors that are limiting spatial resolution. New sample preparation devices and laser optic systems are being developed to push the boundaries of these limitations. Furthermore, we review the processing of cellular MSI data and images, and the systematic integration of these data in the light of available algorithms and databases. We discuss roadblocks in the data analysis pipeline and show how technology from other fields can be used to overcome these. Finally, we conclude with curative and community efforts that are needed to enable contextualization of the information obtained.

Application of Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging for Food Analysis

Food contains various compounds, and there are many methods available to analyze each of these components. However, the large amounts of low-molecular-weight metabolites in food, such as amino acids, organic acids, vitamins, lipids, and toxins, make it difficult to analyze the spatial distribution of these molecules. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) imaging is a two-dimensional ionization technology that allows the detection of small metabolites in tissue sections without requiring purification, extraction, separation, or labeling. The application of MALDI-MS imaging in food analysis improves the visualization of these compounds to identify not only the nutritional content but also the geographical origin of the food. In this review, we provide an overview of some recent applications of MALDI-MS imaging, demonstrating the advantages and prospects of this technology compared to conventional approaches. Further development and enhancement of MALDI-MS imaging is expected to offer great benefits to consumers, researchers, and food producers with respect to breeding improvement, traceability, the development of value-added foods, and improved safety assessments.

Molecular Heterogeneity of Papillary Thyroid Cancer: Comparison of Primary Tumors and Synchronous Metastases in Regional Lymph Nodes by Mass Spectrometry Imaging

Intra-tumor heterogeneity results from both genetic heterogeneity of cancer (sub)clones and phenotypic plasticity of cancer cells that could be induced by different local microenvironments. Here, we used mass spectrometry imaging (MSI) to compare molecular profiles of primary tumors located in the thyroid gland and their synchronous metastases in regional lymph nodes to analyze phenotypic heterogeneity in papillary thyroid cancer. Two types of cancerous (primary tumor and metastasis) and two types of not cancerous (thyroid gland and lymph node) regions of interest (ROIs) were delineated in postoperative material from 11 patients, then the distribution of tryptic peptides (spectral components) was analyzed by MSI in all tissue regions. Moreover, tryptic peptides identified by shotgun proteomics in corresponding tissue lysates were matched to components detected by MSI to enable their hypothetical protein annotation. Unsupervised segmentation of all cancer ROIs revealed that different clusters dominated in tumor ROIs and metastasis ROIs. The intra-patient similarity between thyroid and tumor ROIs was higher than the intra-patient similarity between tumor and metastasis ROIs. Moreover, the similarity between tumor and its metastasis from the same patients was lower than similarities among tumors and among metastases from different patients (inter-patient similarity was higher for metastasis ROIs than for tumor ROIs). Components differentiating between tumor and its metastases were annotated as proteins involved in the organization of the cytoskeleton and chromatin, as well as proteins involved in immunity-related functions. We concluded that phenotypical heterogeneity between primary tumor and lymph node metastases from the same patient was higher than inter-tumor heterogeneity between primary tumors from different patients.

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.

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

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

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

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

Graphical abstract

Round robin study of formalin-fixed paraffin-embedded tissues in mass spectrometry imaging

Mass spectrometry imaging (MSI) has provided many results with translational character, which still have to be proven robust in large patient cohorts and across different centers. Although formalin-fixed paraffin-embedded (FFPE) specimens are most common in clinical practice, no MSI multicenter study has been reported for FFPE samples. Here, we report the results of the first round robin MSI study on FFPE tissues with the goal to investigate the consequences of inter- and intracenter technical variation on masking biological effects. A total of four centers were involved with similar MSI instrumentation and sample preparation equipment. A FFPE multi-organ tissue microarray containing eight different types of tissue was analyzed on a peptide and metabolite level, which enabled investigating different molecular and biological differences. Statistical analyses revealed that peptide intercenter variation was significantly lower and metabolite intercenter variation was significantly higher than the respective intracenter variations. When looking at relative univariate effects of mass signals with statistical discriminatory power, the metabolite data was more reproducible across centers compared to the peptide data. With respect to absolute effects (cross-center common intensity scale), multivariate classifiers were able to reach on average > 90% accuracy for peptides and > 80% for metabolites if trained with sufficient amount of cross-center data. Overall, our study showed that MSI data from FFPE samples could be reproduced to a high degree across centers. While metabolite data exhibited more reproducibility with respect to relative effects, peptide data-based classifiers were more directly transferable between centers and therefore more robust than expected. Graphical abstract ᅟ.

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

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

Mapping Molecular Datasets Back to the Brain Regions They are Extracted from: Remembering the Native Countries of Hypothalamic Expatriates and Refugees

This article focuses on approaches to link transcriptomic, proteomic, and peptidomic datasets mined from brain tissue to the original locations within the brain that they are derived from using digital atlas mapping techniques. We use, as an example, the transcriptomic, proteomic and peptidomic analyses conducted in the mammalian hypothalamus. Following a brief historical overview, we highlight studies that have mined biochemical and molecular information from the hypothalamus and then lay out a strategy for how these data can be linked spatially to the mapped locations in a canonical brain atlas where the data come from, thereby allowing researchers to integrate these data with other datasets across multiple scales. A key methodology that enables atlas-based mapping of extracted datasets-laser-capture microdissection-is discussed in detail, with a view of how this technology is a bridge between systems biology and systems neuroscience.

Plasmonic Thermal Decomposition/Digestion of Proteins: A Rapid On-Surface Protein Digestion Technique for Mass Spectrometry Imaging

A method based on plasmon surface resonance absorption and heating was developed to perform a rapid on-surface protein thermal decomposition and digestion suitable for imaging mass spectrometry (MS) and/or profiling. This photothermal process or plasmonic thermal decomposition/digestion (plasmonic-TDD) method incorporates a continuous wave (CW) laser excitation and gold nanoparticles (Au-NPs) to induce known thermal decomposition reactions that cleave peptides and proteins specifically at the C-terminus of aspartic acid and at the N-terminus of cysteine. These thermal decomposition reactions are induced by heating a solid protein sample to temperatures between 200 and 270 °C for a short period of time (10-50 s per 200 μm segment) and are reagentless and solventless, and thus are devoid of sample product delocalization. In the plasmonic-TDD setup the sample is coated with Au-NPs and irradiated with 532 nm laser radiation to induce thermoplasmonic heating and bring about site-specific thermal decomposition on solid peptide/protein samples. In this manner the Au-NPs act as nanoheaters that result in a highly localized thermal decomposition and digestion of the protein sample that is independent of the absorption properties of the protein, making the method universally applicable to all types of proteinaceous samples (e.g., tissues or protein arrays). Several experimental variables were optimized to maximize product yield, and they include heating time, laser intensity, size of Au-NPs, and surface coverage of Au-NPs. Using optimized parameters, proof-of-principle experiments confirmed the ability of the plasmonic-TDD method to induce both C-cleavage and D-cleavage on several peptide standards and the protein lysozyme by detecting their thermal decomposition products with matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The high spatial specificity of the plasmonic-TDD method was demonstrated by using a mask to digest designated sections of the sample surface with the heating laser and MALDI-MS imaging to map the resulting products. The solventless nature of the plasmonic-TDD method enabled the nonenzymatic on-surface digestion of proteins to proceed with undetectable delocalization of the resulting products from their precursor protein location. The advantages of this novel plasmonic-TDD method include short reaction times (<30 s/200 μm), compatibility with MALDI, universal sample compatibility, high spatial specificity, and localization of the digestion products. These advantages point to potential applications of this method for on-tissue protein digestion and MS-imaging/profiling for the identification of proteins, high-fidelity MS imaging of high molecular weight (>30 kDa) proteins, and the rapid analysis of formalin-fixed paraffin-embedded (FFPE) tissue samples.

Recent advances in applying mass spectrometry and systems biology to determine brain dynamics

INTRODUCTION

Neurological disorders encompass various pathologies which disrupt normal brain physiology and function. Poor understanding of their underlying molecular mechanisms and their societal burden argues for the necessity of novel prevention strategies, early diagnostic techniques and alternative treatment options to reduce the scale of their expected increase. Areas covered: This review scrutinizes mass spectrometry based approaches used to investigate brain dynamics in various conditions, including neurodegenerative and neuropsychiatric disorders. Different proteomics workflows for isolation/enrichment of specific cell populations or brain regions, sample processing; mass spectrometry technologies, for differential proteome quantitation, analysis of post-translational modifications and imaging approaches in the brain are critically deliberated. Future directions, including analysis of cellular sub-compartments, targeted MS platforms (selected/parallel reaction monitoring) and use of mass cytometry are also discussed. Expert commentary: Here, we summarize and evaluate current mass spectrometry based approaches for determining brain dynamics in health and diseases states, with a focus on neurological disorders. Furthermore, we provide insight on current trends and new MS technologies with potential to improve this analysis.

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.

Time, space, and disorder in the expanding proteome universe

Proteins are highly dynamic entities. Their myriad functions require specific structures, but proteins' dynamic nature ranges all the way from the local mobility of their amino acid constituents to mobility within and well beyond single cells. A truly comprehensive view of the dynamic structural proteome includes: (i) alternative sequences, (ii) alternative conformations, (iii) alternative interactions with a range of biomolecules, (iv) cellular localizations, (v) alternative behaviors in different cell types. While these aspects have traditionally been explored one protein at a time, we highlight recently emerging global approaches that accelerate comprehensive insights into these facets of the dynamic nature of protein structure. Computational tools that integrate and expand on multiple orthogonal data types promise to enable the transition from a disjointed list of static snapshots to a structurally explicit understanding of the dynamics of cellular mechanisms.

An Anatomically Resolved Mouse Brain Proteome Reveals Parkinson Disease-relevant Pathways

Here, we present a mouse brain protein atlas that covers 17 surgically distinct neuroanatomical regions of the adult mouse brain, each less than 1 mm³ in size. The protein expression levels are determined for 6,500 to 7,500 gene protein products from each region and over 12,000 gene protein products for the entire brain, documenting the physiological repertoire of mouse brain proteins in an anatomically resolved and comprehensive manner. We explored the utility of our spatially defined protein profiling methods in a mouse model of Parkinson's disease. We compared the proteome from a vulnerable region (substantia nigra pars compacta) of wild type and parkinsonian mice with that of an adjacent, less vulnerable, region (ventral tegmental area) and identified several proteins that exhibited both spatiotemporal- and genotype-restricted changes. We validated the most robustly altered proteins using an alternative profiling method and found that these modifications may highlight potential new pathways for future studies. This proteomic atlas is a valuable resource that offers a practical framework for investigating the molecular intricacies of normal brain function as well as regional vulnerability in neurological diseases. All of the mouse regional proteome profiling data are published on line at http://mbpa.bprc.ac.cn/.

MALDI Imaging Mass Spectrometry of N-glycans and Tryptic Peptides from the Same Formalin-Fixed, Paraffin-Embedded Tissue Section

Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a unique and well developed tool for probing the protein content of formalin-fixed, paraffin-embedded tissue (FFPE). Integral to this approach is the application of trypsin, and more recently peptide N-glycosidase F, to release tryptic peptides or N-glycans from tissue and report localization of distinct species. This is typically done on serial or adjacent tissue sections, and there is an emerging need to understand the colocalized protein population linked to the exact same regions of N-glycans. Here we describe an approach where N-glycans are first imaged from a tissue section followed by reprocessing of the same tissue section for tryptic peptide MALDI IMS. Strategies for colocalizing peptides to target N-glycans or N-glycan regions are described.

Scores for standardization of on-tissue digestion of formalin-fixed paraffin-embedded tissue in MALDI-MS imaging

On-slide digestion of formalin-fixed and paraffin-embedded human biopsy tissue followed by mass spectrometry imaging of resulting peptides may have the potential to become an additional analytical modality in future ePathology. Multiple workflows have been described for dewaxing, antigen retrieval, digestion and imaging in the past decade. However, little is known about suitable statistical scores for method comparison and systematic workflow standardization required for development of processes that would be robust enough to be compatible with clinical routine. To define scores for homogeneity of tissue processing and imaging as well as inter-day repeatability for five different processing methods, we used human liver and gastrointestinal stromal tumor tissue, both judged by an expert pathologist to be >98% histologically homogeneous. For mean spectra-based as well as pixel-wise data analysis, we propose the coefficient of determination R², the natural fold-change (natFC) value and the digest efficiency DE% as readily accessible scores. Moreover, we introduce two scores derived from principal component analysis, the variance of the mean absolute deviation, MAD, and the interclass overlap, J_overlap, as computational scores that may help to avoid user bias during future workflow development. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Multimodal Mass Spectrometry Imaging of N-Glycans and Proteins from the Same Tissue Section

On-tissue digestion matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can be used to record spatially correlated molecular information from formalin-fixed, paraffin-embedded (FFPE) tissue sections. In this work, we present the in situ multimodal analysis of N-linked glycans and proteins from the same FFPE tissue section. The robustness and applicability of the method are demonstrated for several tumors, including epithelial and mesenchymal tumor types. Major analytical aspects, such as lateral diffusion of the analyte molecules and differences in measurement sensitivity due to the additional sample preparation methods, have been investigated for both N-glycans and proteolytic peptides. By combining the MSI approach with extract analysis, we were also able to assess which mass spectral peaks generated by MALDI-MSI could be assigned to unique N-glycan and peptide identities.

Proteomic MALDI-TOF/TOF-IMS examination of peptide expression in the formalin fixed brainstem and changes in sudden infant death syndrome infants

Matrix assisted laser desorption/ionisation imaging mass spectrometry (MALDI-IMS) has not previously been utilised to examine sudden infant death syndrome (SIDS). This study aimed to optimise MALDI IMS for use on archived formalin-fixed-paraffin-embedded human infant medulla tissue (n=6, controls; n=6, SIDS) to evaluate differences between multiple nuclei of the medulla by using high resolution IMS. Profiles were compared between SIDS and age/sex matched controls. LC-MALDI identified 55 proteins based on 321 peptides across all samples; 286 peaks were found using IMS, corresponding to these 55 proteins that were directly compared between controls and SIDS. Control samples were used to identify common peptides for neuronal/non-neuronal structures allowing identification of medullary regions. In SIDS, abnormal expression patterns of 41 peptides (p≤0.05) corresponding to 9 proteins were observed; these changes were confirmed with immunohistochemistry. The protein abnormalities varied amongst nuclei, with the majority of variations in the raphe nuclei, hypoglossal and pyramids. The abnormal proteins are not related to a previously identified neurological disease pathway but consist of developmental neuronal/glial/axonal growth, cell metabolism, cyto-architecture and apoptosis components. This suggests that SIDS infants have abnormal neurological development in the raphe nuclei, hypoglossal and pyramids of the brainstem, which may contribute to the pathogenesis of SIDS.

BIOLOGICAL SIGNIFICANCE

This study is the first to perform an imaging mass spectrometry investigation in the human brainstem and also within sudden infant death syndrome (SIDS). LC MALDI and MALDI IMS identified 55 proteins based on 285 peptides in both control and SIDS tissue; with abnormal expression patterns present for 41/285 and 9/55 proteins in SIDS using IMS. The abnormal proteins are critical for neurological development; with the impairment supporting the hypothesis that SIDS may be due to delayed neurological maturation. The brainstem regions mostly affected included the raphe nuclei, hypoglossal and pyramids. This study highlights that basic cyto-architectural proteins are affected in SIDS and that abnormal expression of these proteins in other CNS disorders should be examined.

KEY SENTENCES

LC MALDI and MALDI IMS identified 55 proteins based on 285 peptides in both control and SIDS tissue. Abnormal expression patterns were present for 41/285 and 9/55 proteins in SIDS using IMS. Brainstem regions mostly affected included the raphe nuclei, hypoglossal and pyramids.

Brain Region-Specific Dynamics of On-Tissue Protein Digestion Using MALDI Mass Spectrometry Imaging

In mass spectrometry imaging (MSI), on-tissue proteolytic digestion is performed to access larger protein species and to assign protein identities through matching the detected peaks with those obtained by LC-MS/MS analyses of tissue extracts. The on-tissue proteolytic digestion also allows the analysis of proteins from formalin-fixed, paraffin-embedded tissues. For these reasons, on-tissue digestion-based MSI is frequently used in clinical investigations, for example, to determine changes in protein content and distribution associated with a disease. In this work, we sought to investigate the completeness and uniformity of the digestion in on-tissue digestion MSI. On the basis of an extensive experiment investigating three groups with varying incubation times: (i) 1.5 h, (ii) 3 h, and (iii) 18 h, we have found that longer incubation times improve the repeatability of the analyses. Furthermore, we discovered morphology-associated differences in the completeness of the proteolysis for short incubation times. These results support the notion that a more complete proteolysis allows better quantitation.

MALDI mass spectrometric imaging meets “omics”: recent advances in the fruitful marriage

Matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI MSI) is a method that allows the investigation of the molecular content of surfaces, in particular, tissues, within its morphological context.