Proteomics in diagnostic pathology: profiling and imaging proteins directly in tissue sections

Protein profile pattern analysis: A multifarious, in vitro diagnosis technique for universal screening

Universal health care is attracting increased attention nowadays, because of the large increase in population all over the world, and a similar increase in life expectancy, leading to an increase in the incidence of non-communicable (various cancers, coronary diseases, neurological and old-age-related diseases) and communicable diseases/pandemics like SARS-COVID 19. This has led to an immediate need for a healthcare technology that should be cost-effective and accessible to all. A technology being considered as a possible one at present is liquid biopsy, which looks for markers in readily available samples like body fluids which can be accessed non- or minimally- invasive manner. Two approaches are being tried now towards this objective. The first involves the identification of suitable, specific markers for each condition, using established methods like various Mass Spectroscopy techniques (Surface-Enhanced Laser Desorption/Ionization Mass Spectroscopy (SELDI-MS), Matrix-Assisted Laser Desorption/Ionization (MALDI-MS), etc., immunoassays (Enzyme-Linked Immunoassay (ELISA), Proximity Extension Assays, etc.) and separation methods like 2-Dimensional Polyacrylamide Gel Electrophoresis (2-D PAGE), Sodium Dodecyl-Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE), Capillary Electrophoresis (CE), etc. In the second approach, no attempt is made the identification of specific markers; rather an efficient separation method like High-Performance Liquid Chromatography/ Ultra-High-Performance Liquid Chromatography (HPLC/UPLC) is used to separate the protein markers, and a profile of the protein pattern is recorded, which is analysed by Artificial Intelligence (AI)/Machine Learning (MI) methods to derive characteristic patterns and use them for identifying the disease condition. The present report gives a summary of the current status of these two approaches and compares the two in the use of their suitability for universal healthcare.

The application of mass spectrometry imaging in traditional Chinese medicine: a review

Mass spectrometry imaging is a frontier technique which connects classical mass spectrometry with ion imaging. Various types of chemicals could be visualized in their native tissues using mass spectrometry imaging. Up to now, the most commonly applied mass spectrometry imaging techniques are matrix assisted laser desorption ionization mass spectrometry imaging, desorption electrospray ionization mass spectrometry imaging and secondary ion mass spectrometry imaging. This review gives an introduction to the principles, development and applications of commonly applied mass spectrometry imaging techniques, and then illustrates the application of mass spectrometry imaging in the investigation of traditional Chinese medicine. Recently, mass spectrometry imaging has been adopted to explore the spatial distribution of endogenous metabolites in traditional Chinese medicine. Data collected from mass spectrometry imaging can be further utilized to search for marker components of traditional Chinese medicine, discover new compounds from traditional herbs, and differentiate between medicinal plants that are similar in botanical features. Moreover, mass spectrometry imaging also plays a role in revealing the pharmacological and toxicological mechanisms of traditional Chinese medicine.

Correlation of in vivo/ex vivo imaging of the posterior eye segment

BACKGROUND

For an understanding of the pathology of retinal diseases, direct comparisons of high-resolution in vivo retinal imaging and ex vivo histological preparations are desirable.

MATERIAL AND METHODS

Multimodal in vivo and ex vivo imaging of a human donor eye with secondary alterations showing atrophic retina due to central retinal arterial occlusion. The subsequent correlation with the histological examination was carried out on identical tissue localizations.

RESULTS

Appropriate custom-built retinal imaging devices facilitate in vivo and ex vivo correlations and the examination of human eye tissue and acquisition of retinal images, e.g. SD-OCT. The precise alignment of the tissue enables a histological analysis on identical sites.

CONCLUSION

The direct correlation of clinical in vivo imaging with ex vivo imaging including histopathology can further enhance our understanding in the pathogenesis of retinal diseases; however, the proposed method is currently limited due to restricted availability of human donor tissue.

Batch Effects in MALDI Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) has become an indispensible tool for spatially resolved molecular investigation of tissues. One of the key application areas is biomedical research, where matrix-assisted laser desorption/ionization (MALDI) MSI is predominantly used due to its high-throughput capability, flexibility in the molecular class to investigate, and ability to achieve single cell spatial resolution. While many of the initial technical challenges have now been resolved, so-called batch effects, a phenomenon already known from other omics fields, appear to significantly impede reliable comparison of data from particular midsized studies typically performed in translational clinical research. This critical insight will discuss at what levels (pixel, section, slide, time, and location) batch effects can manifest themselves in MALDI-MSI data and what consequences this might have for biomarker discovery or multivariate classification. Finally, measures are presented that could be taken to recognize and/or minimize these potentially detrimental effects, and an outlook is provided on what is still needed to ultimately overcome these effects.

[Correlation of in vivo/ex vivo imaging of the posterior eye segment]

BACKGROUND

For an understanding of the pathology of retinal diseases, direct comparisons of high-resolution in vivo retinal imaging and ex vivo histological preparations are desirable.

MATERIAL AND METHODS

Multimodal in vivo and ex vivo imaging of a human donor eye with secondary alterations showing atrophic retina due to central retinal arterial occlusion. The subsequent correlation with the histological examination was carried out on identical tissue localizations.

RESULTS

Appropriate custom-built retinal imaging devices facilitate in vivo and ex vivo correlations and the examination of human eye tissue and acquisition of retinal images, e.g. SD-OCT. The precise alignment of the tissue enables a histological analysis on identical sites.

CONCLUSION

The direct correlation of clinical in vivo imaging with ex vivo imaging including histopathology can further enhance our understanding in the pathogenesis of retinal diseases; however, the proposed method is currently limited due to restricted availability of human donor tissue.

Immune contexture analysis in immuno-oncology: applications and challenges of multiplex fluorescent immunohistochemistry

The tumor microenvironment is an integral player in cancer initiation, tumor progression, response and resistance to anti-cancer therapy. Understanding the complex interactions of tumor immune architecture (referred to as 'immune contexture') has therefore become increasingly desirable to guide our approach to patient selection, clinical trial design, combination therapies, and patient management. Quantitative image analysis based on multiplexed fluorescence immunohistochemistry and deep learning technologies are rapidly developing to enable researchers to interrogate complex information from the tumor microenvironment and find predictive insights into treatment response. Herein, we discuss current developments in multiplexed fluorescence immunohistochemistry for immune contexture analysis, and their application in immuno-oncology, and discuss challenges to effectively use this technology in clinical settings. We also present a multiplexed image analysis workflow to analyse fluorescence multiplexed stained tumor sections using the Vectra Automated Digital Pathology System together with FCS express flow cytometry software. The benefit of this strategy is that the spectral unmixing accurately generates and analyses complex arrays of multiple biomarkers, which can be helpful for diagnosis, risk stratification, and guiding clinical management of oncology patients.

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.

Multiplex bioimaging of single-cell spatial profiles for precision cancer diagnostics and therapeutics

Cancers exhibit functional and structural diversity in distinct patients. In this mass, normal and malignant cells create tumor microenvironment that is heterogeneous among patients. A residue from primary tumors leaks into the bloodstream as cell clusters and single cells, providing clues about disease progression and therapeutic response. The complexity of these hierarchical microenvironments needs to be elucidated. Although tumors comprise ample cell types, the standard clinical technique is still the histology that is limited to a single marker. Multiplexed imaging technologies open new directions in pathology. Spatially resolved proteomic, genomic, and metabolic profiles of human cancers are now possible at the single-cell level. This perspective discusses spatial bioimaging methods to decipher the cascade of microenvironments in solid and liquid biopsies. A unique synthesis of top-down and bottom-up analysis methods is presented. Spatial multi-omics profiles can be tailored to precision oncology through artificial intelligence. Data-driven patient profiling enables personalized medicine and beyond.

Multimodal imaging of biological tissues using combined MALDI and NAPA-LDI mass spectrometry for enhanced molecular coverage

Sequential imaging of a tissue section by MALDI and NAPA-LDI mass spectrometry provides enhanced molecular coverage.

Recent advances in tissue imaging for cancer research

Image analysis in clinical research has evolved at fast pace in the last decade. This review discusses basic concepts ranging from immunohistochemistry to advanced techniques such as multiplex imaging, digital pathology, flow cytometry and intravital microscopy. Tissue imaging ex vivo is still one of the gold-standards in the field due to feasibility. We describe here different protocols and applications of digital analysis providing basic and clinical researchers with an overview on how to analyse tissue images. In vivo imaging is not easily accessible to researchers; however, it provides invaluable dynamic information. Overall, we discuss a plethora of techniques that - when combined - constitute a powerful platform for basic and translational cancer research.

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.

Mass spectrometry imaging: How will it affect clinical research in the future?

INTRODUCTION

Mass spectrometry imaging (MSI) is a label free, multiplex imaging technology able to simultaneously record the distributions of 100's to 1000's of species, and which may be configured to study metabolites, lipids, glycans, peptides, and proteins simply by changing the tissue preparation protocol. Areas covered: The capability of MSI to complement established histopathological practice through the identification of biomarkers for differential diagnosis, patient prognosis, and response to therapy; the capability of MSI to annotate tissues on the basis of each pixel's mass spectral signature; the development of reproducible MSI through multicenter studies. Expert commentary: We discuss how MSI can be combined with microsampling/microdissection technologies in order to investigate, with more depth of coverage, the molecular changes uncovered by MSI.

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.

Applications of Mass Spectrometry Imaging to Cancer

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

In Situ Metabolomics in Cancer by Mass Spectrometry Imaging

Metabolomics is a rapidly evolving and a promising research field with the expectation to improve diagnosis, therapeutic treatment prediction, and prognosis of particular diseases. Among all techniques used to assess the metabolome in biological systems, mass spectrometry imaging is the method of choice to qualitatively and quantitatively analyze metabolite distribution in tissues with a high spatial resolution, thus providing molecular data in relation to cancer histopathology. The technique is ideally suited to study tissues molecular content and is able to provide molecular biomarkers or specific mass signatures which can be used in classification or the prognostic evaluation of tumors. Recently, it was shown that FFPE tissue samples are also suitable for metabolic analyses. This progress in methodology allows access to a highly valuable resource of tissues believed to widen and strengthen metabolic discovery-driven studies.

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.

Visualization of sphingolipids and phospholipids in the fundic gland mucosa of human stomach using imaging mass spectrometry

AIM: To analyze the lipid distribution in gastric mucosae.

METHODS: Imaging mass spectrometry (MS) is a useful tool to survey the distribution of biomolecules in surgical specimens. Here we used the imaging MS apparatus named iMScope to identify the dominant molecules present in the human gastric mucosa near the fundic glands. Five gastric specimens were subjected to iMScope analysis. These specimens were also analyzed by immunohistochemistry using MUC5AC, H(+)-K(+)-ATPaseβ Claudin18 antibodies.

RESULTS: Three major molecules with m/z 725.5, 780.5, and 782.5 detected in the gastric mucosa were identified as sphingomyelin (SM) (d18:1/16:0), phosphatidylcholine (PC) (16:0/18:2), and PC (16:0/18:1), respectively, through MS/MS analyses. Using immunohistological staining, SM (d18:1/16:0) signals were mainly co-localized with the foveolar epithelium marker MUC5AC. In contrast, PC (16:0/18:2) signals were observed in the region testing positive for the fundic gland marker H(+)-K(+)-ATPaseβ. PC (16:0/18:1) signals were uniformly distributed throughout the mucosa.

CONCLUSION: Our basic data will contribute to the studies of lipid species in physical and pathological conditions of the human stomach.

A2E and Lipofuscin

Lipofuscin is highly fluorescent material, formed in several tissues but best studied in the eye. The accumulation of lipofuscin in the retinal pigment epithelium (RPE) is a hallmark of aging in the eye and has been implicated in various retinal degenerations, including age-related macular degeneration. The bis-retinoid N-retinyl-N-retinylidene ethanolamine (A2E), formed from retinal, has been identified as a byproduct of the visual cycle, and numerous in vitro studies have found toxicity associated with this compound. The compound is known to accumulate in the RPE with age and was the first identified compound extracted from lipofuscin. Our studies have correlated the distribution of lipofuscin and A2E across the human and mouse RPE. Lipofuscin fluorescence was imaged in the RPE from human donors of various ages and from assorted mouse models. The spatial distribution of A2E was determined using matrix-assisted laser desorption-ionization imaging mass spectrometry on both flat-mounted and transversally sectioned RPE tissue. Our data support the clinical observations in humans of strong RPE fluorescence, increasing with age, in the central area of the RPE. However, there was no correlation between the distribution of A2E and lipofuscin, as the levels of A2E were highest in the far periphery and decreased toward the central region. Interestingly, in all the mouse models, A2E distribution and lipofuscin fluorescence correlate well. These data demonstrate that the accumulation of A2E is not responsible for the increase in lipofuscin fluorescence observed in the central RPE with aging in humans.

Molecular anatomy of ascending aorta in atherosclerosis by MS Imaging: Specific lipid and protein patterns reflect pathology

The molecular anatomy of healthy and atherosclerotic tissue is pursued here to identify ongoing molecular changes in atherosclerosis development. Subclinical atherosclerosis cannot be predicted and novel therapeutic targets are needed. Mass spectrometry imaging (MSI) is a novel unexplored ex vivo imaging approach in CVD able to provide in-tissue molecular maps. A rabbit model of early atherosclerosis was developed and high-spatial-resolution MALDI-MSI was applied to comparatively analyze histologically-based arterial regions of interest from control and early atherosclerotic aortas. Specific protocols were applied to identify lipids and proteins significantly altered in response to atherosclerosis. Observed protein alterations were confirmed by immunohistochemistry in rabbit tissue, and additionally in human aortas. Molecular features specifically defining different arterial regions were identified. Localized in the intima, increased expression of SFA and lysolipids and intimal spatial organization showing accumulation of PI, PG and SM point to endothelial dysfunction and triggered inflammatory response. TG, PA, SM and PE-Cer were identified specifically located in calcified regions. Thymosin β4 (TMSB4X) protein was upregulated in intima versus media layer and also in response to atherosclerosis. This overexpression and localization was confirmed in human aortas. In conclusion, molecular histology by MS Imaging identifies spatial organization of arterial tissue in response to atherosclerosis.

Mass Spectrometry Imaging and GC-MS Profiling of the Mammalian Peripheral Sensory-Motor Circuit

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has evolved to become an effective discovery tool in science and clinical diagnostics. Here, chemical imaging approaches are applied to well-defined regions of the mammalian peripheral sensory-motor system, including the dorsal root ganglia (DRG) and adjacent nerves. By combining several MSI approaches, analyte coverage is increased and 195 distinct molecular features are observed. Principal component analysis suggests three chemically different regions within the sensory-motor system, with the DRG and adjacent nerve regions being the most distinct. Investigation of these regions using gas chromatography-mass spectrometry corroborate these findings and reveal important metabolic markers related to the observed differences. The heterogeneity of the structurally, physiologically, and functionally connected regions demonstrates the intricate chemical and spatial regulation of their chemical composition.

Advances in tissue section preparation for MALDI imaging MS

Enriched by a decade of remarkable developments, matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) has witnessed a phenomenal expansion. Initially introduced for the mapping of peptides and intact proteins from mammalian tissue sections, MALDI IMS applications now extend to a wide range of molecules including peptides, lipids, metabolites and xenobiotics. Technology and methodology are quickly evolving to push the limits of the technique forward. Within a short period of time, numerous protocols and concepts have been developed and introduced in tissue section preparation, nonexhaustively including in situ tissue chemistries and solvent-free matrix depositions. Considering the past progress and current capabilities, this Review aims to cover the different aspects and challenges of tissue section preparation for MALDI IMS.

MALDI TOF imaging mass spectrometry in clinical pathology: a valuable tool for cancer diagnostics (review)

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) is an evolving technique in cancer diagnostics and combines the advantages of mass spectrometry (proteomics), detection of numerous molecules, and spatial resolution in histological tissue sections and cytological preparations. This method allows the detection of proteins, peptides, lipids, carbohydrates or glycoconjugates and small molecules.Formalin-fixed paraffin-embedded tissue can also be investigated by IMS, thus, this method seems to be an ideal tool for cancer diagnostics and biomarker discovery. It may add information to the identification of tumor margins and tumor heterogeneity. The technique allows tumor typing, especially identification of the tumor of origin in metastatic tissue, as well as grading and may provide prognostic information. IMS is a valuable method for the identification of biomarkers and can complement histology, immunohistology and molecular pathology in various fields of histopathological diagnostics, especially with regard to identification and grading of tumors.

Imaging mass spectrometry in papillary thyroid carcinoma for the identification and validation of biomarker proteins

Direct tissue imaging mass spectrometry (IMS) by matrix-assisted laser desorption ionization and time-of-flight (MALDI-TOF) mass spectrometry has become increasingly important in biology and medicine, because this technology can detect the relative abundance and spatial distribution of interesting proteins in tissues. Five thyroid cancer samples, along with normal tissue, were sliced and transferred onto conductive glass slides. After laser scanning by MALDI-TOF equipped with a smart beam laser, images were created for individual masses and proteins were classified at 200-µm spatial resolution. Based on the spatial distribution, region-specific proteins on a tumor lesion could be identified by protein extraction from tumor tissue and analysis using liquid chromatography with tandem mass spectrometry (LC-MS/MS). Using all the spectral data at each spot, various intensities of a specific peak were detected in the tumor and normal regions of the thyroid. Differences in the molecular weights of expressed proteins between tumor and normal regions were analyzed using unsupervised and supervised clustering. To verify the presence of discovered proteins through IMS, we identified ribosomal protein P2, which is specific for cancer. We have demonstrated the feasibility of IMS as a useful tool for the analysis of tissue sections, and identified the tumor-specific protein ribosomal protein P2.

Human SOD1-G93A specific distribution evidenced in murine brain of a transgenic model for amyotrophic lateral sclerosis by MALDI imaging mass spectrometry

Amyotrophic lateral sclerosis (ALS) is a progressive, fatal neurodegenerative disease caused by the degeneration of motor neurons. The transgenic mouse model carrying the human SOD1G93A mutant gene (hSOD1G93A mouse) represents one of the most reliable and widely used model of this pathology. In the present work, the innovative technique of matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) was applied in the study of pathological alterations at the level of small brain regions such as facial and trigeminal nuclei, which in rodents are extremely small and would be difficult to analyze with classical proteomics approaches. Comparing slices from three mice groups (transgenic hSOD1G93A, transgenic hSOD1WT, and nontransgenic, Ntg), this technique allowed us to evidence the accumulation of hSOD1G93A in the facial and trigeminal nuclei, where it generates aggregates. This phenomenon is likely to be correlated to the degeneration observed in these regions. Moreover, a statistical analysis allowed us to highlight other proteins as differentially expressed among the three mice groups analyzed. Some of them were identified by reverse-phase HPLC fractionation of extracted proteins and mass spectrometric analysis before and after trypsin digestion. In particular, the 40S ribosomal protein S19 (RPS19) was upregulated in the parenkyma and reactive glial cells in facial nuclei of hSOD1G93A mice when compared to transgenic hSOD1WT and nontransgenic ones.

MALDI MS imaging as a tool for biomarker discovery: methodological challenges in a clinical setting

MALDI MS imaging (MSI) is an analytical tool capable of providing spatial distribution and relative abundance of biomolecules directly in tissue. After 15 years of intense efforts to improve the acquisition and quality of molecular images, MSI has matured into an asset of the proteomic toolbox. The power of MSI lies in the ability to differentiate tissue regions that are not histologically distinct but are characterized by different MS profiles. Recently, MSI has been gaining momentum in biomedical research and has found applications in disease diagnosis and prognosis, biomarker discovery, and drug therapy. Although the technology holds great promise, MSI is still faced with a set of methodological challenges presented by the clinical setting. There is a growing awareness regarding this topic and efforts are being taken to develop clear and practical standards to overcome these challenges. This review presents an overview of MALDI MSI as a biomarker discovery tool and recent methodological progress in the field.

Proteomic analysis of colorectal cancer: discovering novel biomarkers

Colorectal cancer is one of the most common cancers in the Western world. When detected at an early stage, the majority of cancers can be cured with current treatment modalities. However, most cancers present at an intermediate stage. The discovery of sensitive and specific biomarkers has the potential to improve preclinical diagnosis of primary and recurrent colorectal cancer, and holds the promise of prognostic and therapeutic application. Current biomarkers such as carcinoembryonic antigen lack sensitivity and specificity for general population screening. This review aims to highlight the role of current proteomic technologies in the discovery and validation of potential biomarkers with a view to translation to the clinic.

Role and challenges of proteomics in pharma and biotech: technical, scientific and commercial perspective

Contemporary proteomics, currently in its exponential growth phase, is a bewildering array of tools. Proteomic methods are the result of a convergence of rapidly improving mass spectrometry technologies, protein chemistry and separation sciences, genomics and bioinformatics. Strides in improving proteomics technologies to map and measure proteomes and subproteomes are being made. However, no single proteomic platform appears ideally suited to address all research needs or accomplish ambitious goals satisfactorily. However, proteomics is in a unique position to contribute to protein discovery and to public health in terms of better biomarkers, diagnostics and treatment of disease. While the potential is great, many challenges and issues remain to be solved. Fundamental issues, such as biological variability, pre-analytic factors and analytical reproducibility, remain to be resolved. Neither an all-genetic approach nor an all-proteomic approach will solve biological complexity. Proteomics will be the foundation for constructing and extracting useful knowledge to pharma and biotech depicted in the following path: data --> structured data --> information --> information architecture --> knowledge --> useful knowledge.

Type 1 diabetes: entering the proteomic era

During the last decade, a major breakthrough in the field of proteomics has been achieved. This review describes available techniques for proteomic analyses, both gel and non-gel based, particularly concentrating on relative quantification techniques. The principle of the different techniques is discussed, highlighting the advantages and drawbacks of recently available visualization methods in gel-based assays. In addition, recent developments for quantitative analysis in non-gel-based approaches are summarized. This review focuses on applications in Type 1 diabetes. These mainly include proteomic studies on pancreatic islets in animal models and in the human situation. Also discussed are mass spectrometry-based studies on T-cells, and studies on the development of diagnostic markers for diabetic nephropathology by capillary electrophoresis coupled to mass spectrometry.

Multicolor multicycle molecular profiling with quantum dots for single-cell analysis

Here we present a detailed protocol for molecular profiling of individual cultured mammalian cells using multicolor multicycle immunofluorescence with quantum dot probes. It includes instructions for cell culture growth and processing (2 h + 48-72 h for cell growth), preparation and characterization of universal quantum dot probes (4.5 h + overnight incubation), cyclic cell staining (∼4.5 h per cycle) and image analysis (varies by application). The use of quantum dot fluorescent probes enables highly multiplexed, robust quantitative molecular imaging with a conventional fluorescence microscopy setup, whereas the probe preparation methodology, using a self-assembly between protein A-decorated universal quantum dots and intact primary antibodies, offers a fast, simple and purification-free route for an on-demand preparation of antibody-functionalized quantum dot libraries. As a result, this protocol can be used by biomedical researchers for a variety of cell staining applications, and, with further optimization, for staining of other biological specimens (e.g., clinical tissue sections).

Accumulated phosphatidylcholine (16:0/16:1) in human colorectal cancer; possible involvement of LPCAT4

The identification of cancer biomarkers is critical for target-linked cancer therapy. The overall level of phosphatidylcholine (PC) is elevated in colorectal cancer (CRC). To investigate which species of PC is overexpressed in colorectal cancer, an imaging mass spectrometry was performed using a panel of non-neoplastic mucosal and CRC tissues. In the present study, we identified a novel biomarker, PC(16:0/16:1), in CRC using imaging mass spectrometry. Specifically, elevated levels of PC(16:0/16:1) expression were observed in the more advanced stage of CRC. Our data further showed that PC(16:0/16:1) was specifically localized in the cancer region when examined using imaging mass spectrometry. Notably, because the ratio of PC(16:0/16:1) to lyso-PC(16:0) was higher in CRC, we postulated that lyso-PC acyltransferase (LPCAT) activity is elevated in CRC. In an in vitro analysis, we showed that LPCAT4 is involved in the deregulation of PC(16:0/16:1) in CRC. In an immunohistochemical analysis, LPCAT4 was shown to be overexpressed in CRC. These data indicate the potential usefulness of PC(16:0/16:1) for the clinical diagnosis of CRC and implicate LPCAT4 in the elevated expression of PC(16:0/16:1) in CRC.

Imaging mass spectrometry for assessing temporal proteomics: analysis of calprotectin in Acinetobacter baumannii pulmonary infection

Imaging MS is routinely used to show spatial localization of proteins within a tissue sample and can also be employed to study temporal protein dynamics. The antimicrobial S100 protein calprotectin, a heterodimer of subunits S100A8 and S100A9, is an abundant cytosolic component of neutrophils. Using imaging MS, calprotectin can be detected as a marker of the inflammatory response to bacterial challenge. In a murine model of Acinetobacter baumannii pneumonia, protein images of S100A8 and S100A9 collected at different time points throughout infection aid in visualization of the innate immune response to this pathogen. Calprotectin is detectable within 6 h of infection as immune cells respond to the invading pathogen. As the bacterial burden decreases, signals from the inflammatory proteins decrease. Calprotectin is no longer detectable 96-144 h post infection, correlating to a lack of detectable bacterial burden in lungs. These experiments provide a label-free, multiplexed approach to study host response to a bacterial threat and eventual clearance of the pathogen over time.

MntABC and MntH contribute to systemic Staphylococcus aureus infection by competing with calprotectin for nutrient manganese

During infection, vertebrates limit access to manganese and zinc, starving invading pathogens, such as Staphylococcus aureus, of these essential metals in a process termed "nutritional immunity." The manganese and zinc binding protein calprotectin is a key component of the nutrient-withholding response, and mice lacking this protein do not sequester manganese from S. aureus liver abscesses. One potential mechanism utilized by S. aureus to minimize host-imposed manganese and zinc starvation is the expression of the metal transporters MntABC and MntH. We performed transcriptional analyses of both mntA and mntH, which revealed increased expression of both systems in response to calprotectin treatment. MntABC and MntH compete with calprotectin for manganese, which enables S. aureus growth and retention of manganese-dependent superoxide dismutase activity. Loss of MntABC and MntH results in reduced staphylococcal burdens in the livers of wild-type but not calprotectin-deficient mice, suggesting that these systems promote manganese acquisition during infection. During the course of these studies, we observed that metal content and the importance of calprotectin varies between murine organs, and infection leads to profound changes in the anatomical distribution of manganese and zinc. In total, these studies provide insight into the mechanisms utilized by bacteria to evade host-imposed nutrient metal starvation and the critical importance of restricting manganese availability during infection.

Efficiency of the dry-wet method for the MALDI-MSI analysis of latent fingermarks

Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) has proven to be a powerful analytical tool to investigate problems in several fields of life science. A novel application is in the field of forensics, particularly in the analysis of latent fingermarks. This technology enables images of the fingermark ridge detail and additional intelligence to be simultaneously obtained. Although several methods are available to deposit the MALDI matrix, to make the technology forensically operational, another deposition approach was devised and reported, namely the 'dry-wet' method. In the present study, the efficiency of the dry-wet method was evaluated and compared with the conventional spray coat methodology. Results indicate that the dry-wet method is superior for all the donors' typologies in terms of ion signal intensity and clarity of the ridge details. To underpin the reasons of this efficiency, scanning electron microscopy analyses were carried out in parallel to MALDI-MSI experiments using matrices of different particle size. Results have confirmed that the particle size plays an important role in the efficiency of the method as higher quality images and higher intensity spectra are produced as the matrix particle size decreases.

Histology-driven data mining of lipid signatures from multiple imaging mass spectrometry analyses: application to human colorectal cancer liver metastasis biopsies

Imaging mass spectrometry (IMS) represents an innovative tool in the cancer research pipeline, which is increasingly being used in clinical and pharmaceutical applications. The unique properties of the technique, especially the amount of data generated, make the handling of data from multiple IMS acquisitions challenging. This work presents a histology-driven IMS approach aiming to identify discriminant lipid signatures from the simultaneous mining of IMS data sets from multiple samples. The feasibility of the developed workflow is evaluated on a set of three human colorectal cancer liver metastasis (CRCLM) tissue sections. Lipid IMS on tissue sections was performed using MALDI-TOF/TOF MS in both negative and positive ionization modes after 1,5-diaminonaphthalene matrix deposition by sublimation. The combination of both positive and negative acquisition results was performed during data mining to simplify the process and interrogate a larger lipidome into a single analysis. To reduce the complexity of the IMS data sets, a sub data set was generated by randomly selecting a fixed number of spectra from a histologically defined region of interest, resulting in a 10-fold data reduction. Principal component analysis confirmed that the molecular selectivity of the regions of interest is maintained after data reduction. Partial least-squares and heat map analyses demonstrated a selective signature of the CRCLM, revealing lipids that are significantly up- and down-regulated in the tumor region. This comprehensive approach is thus of interest for defining disease signatures directly from IMS data sets by the use of combinatory data mining, opening novel routes of investigation for addressing the demands of the clinical setting.

Orthogonal organic and aqueous-based washes of tissue sections to enhance protein sensitivity by MALDI imaging mass spectrometry

Imaging mass spectrometry (IMS) is an emergent and innovative approach for measuring the composition, abundance and regioselectivity of molecules within an investigated area of fixed dimension. Although providing unprecedented molecular information compared with conventional MS techniques, enhancement of protein signature by IMS is still necessary and challenging. This paper demonstrates the combination of conventional organic washes with an optimized aqueous-based buffer for tissue section preparation before matrix-assisted laser desorption/ionization (MALDI) IMS of proteins. Based on a 500 mM ammonium formate in water-acetonitrile (9:1; v/v, 0.1% trifluororacetic acid, 0.1% Triton) solution, this buffer wash has shown to significantly enhance protein signature by profiling and IMS (~fourfold) when used after organic washes (70% EtOH followed by 90% EtOH), improving the quality and number of ion images obtained from mouse kidney and a 14-day mouse fetus whole-body tissue sections, while maintaining a similar reproducibility with conventional tissue rinsing. Even if some protein losses were observed, the data mining has demonstrated that it was primarily low abundant signals and that the number of new peaks found is greater with the described procedure. The proposed buffer has thus demonstrated to be of high efficiency for tissue section preparation providing novel and complementary information for direct on-tissue MALDI analysis compared with solely conventional organic rinsing.

MALDI-imaging segmentation is a powerful tool for spatial functional proteomic analysis of human larynx carcinoma

PURPOSE

For several decades, conventional histological staining and immunohistochemistry (IHC) have been the main tools to visualize and understand tissue morphology and structure. IHC visualizes the spatial distribution of individual protein species directly in tissue. However, a specific antibody is required for each protein, and multiplexing capabilities are extremely limited, rarely visualizing more than two proteins simultaneously. With the recent emergence of matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-imaging), it is becoming possible to study more complex proteomic patterns directly in tissue. However, the analysis and interpretation of large and complex MALDI-imaging data requires advanced computational methods. In this paper, we show how the recently introduced method of spatial segmentation can be applied to analysis and interpretation of a larynx carcinoma section and compare the spatial segmentation with the histological annotation of the same tissue section.

METHODS

Matrix-assisted laser desorption/ionization imaging is a label-free spatially resolved analytical technique, which allows detection and visualization of hundreds of proteins at once. Spatial segmentation of the MALDI-imaging data by clustering of spectra by their similarity was performed, automatically generating a spatial segmentation map of the tissue section, where regions of similar proteomic patterns were highlighted. The tissue was stained with the hematoxylin and eosin (H&E), histopathologically analyzed and annotated. The segmentation map was interpreted after its overlay with the H&E microscopy image.

RESULTS

The automatically generated segmentation map exhibits high correspondence to the detailed histological annotation of the larynx carcinoma tissue section. By superimposing, the segmentation map based on the proteomic profiles with H&E-stained microscopic images, we demonstrate precise localization of complex and histopathologically relevant tissue features in an automated way.

CONCLUSIONS

The combination of MALDI-imaging and automatic spatial segmentation is a useful approach in analyzing carcinoma tissue and provides a deeper insight into the functional proteomic organization of the respective tissue.

Imaging mass spectrometry to visualize biomolecule distributions in mouse brain tissue following hemispheric cortical spreading depression

MALDI mass spectrometry can simultaneously measure hundreds of biomolecules directly from tissue. Using essentially the same technique but different sample preparation strategies, metabolites, lipids, peptides and proteins can be analyzed. Spatially correlated analysis, imaging MS, enables the distributions of these biomolecular ions to be simultaneously measured in tissues. A key advantage of imaging MS is that it can annotate tissues based on their MS profiles and thereby distinguish biomolecularly distinct regions even if they were unexpected or are not distinct using established histological and histochemical methods e.g. neuropeptide and metabolite changes following transient electrophysiological events such as cortical spreading depression (CSD), which are spreading events of massive neuronal and glial depolarisations that occur in one hemisphere of the brain and do not pass to the other hemisphere , enabling the contralateral hemisphere to act as an internal control. A proof-of-principle imaging MS study, including 2D and 3D datasets, revealed substantial metabolite and neuropeptide changes immediately following CSD events which were absent in the protein imaging datasets. The large high dimensionality 3D datasets make even rudimentary contralateral comparisons difficult to visualize. Instead non-negative matrix factorization (NNMF), a multivariate factorization tool that is adept at highlighting latent features, such as MS signatures associated with CSD events, was applied to the 3D datasets. NNMF confirmed that the protein dataset did not contain substantial contralateral differences, while these were present in the neuropeptide dataset.

High speed data processing for imaging MS-based molecular histology using graphical processing units

Imaging MS enables the distributions of hundreds of biomolecular ions to be determined directly from tissue samples. The application of multivariate methods, to identify pixels possessing correlated MS profiles, is referred to as molecular histology as tissues can be annotated on the basis of the MS profiles. The application of imaging MS-based molecular histology to larger tissue series, for clinical applications, requires significantly increased computational capacity in order to efficiently analyze the very large, highly dimensional datasets. Such datasets are highly suited to processing using graphical processor units, a very cost-effective solution for high speed processing. Here we demonstrate up to 13× speed improvements for imaging MS-based molecular histology using off-the-shelf components, and demonstrate equivalence with CPU based calculations. It is then discussed how imaging MS investigations may be designed to fully exploit the high speed of graphical processor units.

Quantitation of spatially-localized proteins in tissue samples using MALDI-MRM imaging

MALDI imaging allows the creation of a "molecular image" of a tissue slice. This image is reconstructed from the ion abundances in spectra obtained while rastering the laser over the tissue. These images can then be correlated with tissue histology to detect potential biomarkers of, for example, aberrant cell types. MALDI, however, is known to have problems with ion suppression, making it difficult to correlate measured ion abundance with concentration. It would be advantageous to have a method which could provide more accurate protein concentration measurements, particularly for screening applications or for precise comparisons between samples. In this paper, we report the development of a novel MALDI imaging method for the localization and accurate quantitation of proteins in tissues. This method involves optimization of in situ tryptic digestion, followed by reproducible and uniform deposition of an isotopically labeled standard peptide from a target protein onto the tissue, using an aerosol-generating device. Data is acquired by MALDI multiple reaction monitoring (MRM) mass spectrometry (MS), and accurate peptide quantitation is determined from the ratio of MRM transitions for the endogenous unlabeled proteolytic peptides to the corresponding transitions from the applied isotopically labeled standard peptides. In a parallel experiment, the quantity of the labeled peptide applied to the tissue was determined using a standard curve generated from MALDI time-of-flight (TOF) MS data. This external calibration curve was then used to determine the quantity of endogenous peptide in a given area. All standard curves generate by this method had coefficients of determination greater than 0.97. These proof-of-concept experiments using MALDI MRM-based imaging show the feasibility for the precise and accurate quantitation of tissue protein concentrations over 2 orders of magnitude, while maintaining the spatial localization information for the proteins.