Multimodal MALDI imaging mass spectrometry for improved diagnosis of melanoma.

Imaging mass spectrometry (IMS) provides promising avenues to augment histopathological investigation with rich spatio-molecular information. We have previously developed a classification model to differentiate melanoma from nevi lesions based on IMS protein data, a task that is challenging solely by histopathologic evaluation. Most IMS-focused studies collect microscopy in tandem with IMS data, but this microscopy data is generally omitted in downstream data analysis. Microscopy, nevertheless, forms the basis for traditional histopathology and thus contains invaluable morphological information. In this work, we developed a multimodal classification pipeline that uses deep learning, in the form of a pre-trained artificial neural network, to extract the meaningful morphological features from histopathological images, and combine it with the IMS data. To test whether this deep learning-based classification strategy can improve on our previous results in classification of melanocytic neoplasia, we utilized MALDI IMS data with collected serial H&E stained sections for 331 patients, and compared this multimodal classification pipeline to classifiers using either exclusively microscopy or IMS data. The multimodal pipeline achieved the best performance, with ROC-AUCs of 0.968 vs. 0.938 vs. 0.931 for the multimodal, unimodal microscopy and unimodal IMS pipelines respectively. Due to the use of a pre-trained network to perform the morphological feature extraction, this pipeline does not require any training on large amounts of microscopy data. As such, this framework can be readily applied to improve classification performance in other experimental settings where microscopy data is acquired in tandem with IMS experiments.

Multidimensional mass profiles increase confidence in bacterial identification when using low-resolution mass spectrometers.

Field-forward analytical technologies, such as portable mass spectrometry (MS), enable essential capabilities for real-time monitoring and point-of-care diagnostic applications. Significant and recent investments improving the features of miniaturized mass spectrometers enable various new applications outside of small molecule detection. Most notably, the addition of tandem mass spectrometry scans (MS/MS) allows the instrument to isolate and fragment ions and increase the analytical specificity by measuring unique chemical signatures for ions of interest. Notwithstanding these technological advancements, low-cost, portable systems still struggle to confidently identify clinically significant organisms of interest, such as bacteria, viruses, and proteinaceous toxins, due to the limitations in resolving power. To overcome these limitations, we developed a novel multidimensional mass fingerprinting technique that uses tandem mass spectrometry to increase the chemical specificity for low-resolution mass spectral profiles. We demonstrated the method's capabilities for differentiating four different bacteria, including attentuated strains of Yersinia pestis. This approach allowed for the accurate (>92%) identification of each organism at the strain level using de-resolved matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) data to mimic the performance characteristics of miniaturized mass spectrometers. This work demonstrates that low-resolution mass spectrometers, equipped with tandem MS acquisition modes, can accurately identify clinically relevant bacteria. These findings support the future application of these technologies for field-forward and point-of-care applications where high-performance mass spectrometers would be cost-prohibitive or otherwise impractical.

Prospective on Imaging Mass Spectrometry in Clinical Diagnostics.

Imaging mass spectrometry (IMS) is a molecular technology utilized for spatially driven research, providing molecular maps from tissue sections. This article reviews matrix-assisted laser desorption ionization (MALDI) IMS and its progress as a primary tool in the clinical laboratory. MALDI mass spectrometry has been used to classify bacteria and perform other bulk analyses for plate-based assays for many years. However, the clinical application of spatial data within a tissue biopsy for diagnoses and prognoses is still an emerging opportunity in molecular diagnostics. This work considers spatially driven mass spectrometry approaches for clinical diagnostics and addresses aspects of new imaging-based assays that include analyte selection, quality control/assurance metrics, data reproducibility, data classification, and data scoring. It is necessary to implement these tasks for the rigorous translation of IMS to the clinical laboratory; however, this requires detailed standardized protocols for introducing IMS into the clinical laboratory to deliver reliable and reproducible results that inform and guide patient care.

Processes in DNA damage response from a whole-cell multi-omics perspective.

Technological advances have made it feasible to collect multi-condition multi-omic time courses of cellular response to perturbation, but the complexity of these datasets impedes discovery due to challenges in data management, analysis, visualization, and interpretation. Here, we report a whole-cell mechanistic analysis of HL-60 cellular response to bendamustine. We integrate both enrichment and network analysis to show the progression of DNA damage and programmed cell death over time in molecular, pathway, and process-level detail using an interactive analysis framework for multi-omics data. Our framework, Mechanism of Action Generator Involving Network analysis (MAGINE), automates network construction and enrichment analysis across multiple samples and platforms, which can be integrated into our annotated gene-set network to combine the strengths of networks and ontology-driven analysis. Taken together, our work demonstrates how multi-omics integration can be used to explore signaling processes at various resolutions and demonstrates multi-pathway involvement beyond the canonical bendamustine mechanism.

α-Cyano-4-hydroxycinnamic Acid and Tri-Potassium Citrate Salt Pre-Coated Silicon Nanopost Array Provides Enhanced Lipid Detection for High Spatial Resolution MALDI Imaging Mass Spectrometry.

We have developed a pre-coated substrate for matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) that enables high spatial resolution mapping of both phospholipids and neutral lipid classes in positive ion mode as metal cation adducts. The MALDI substrates are constructed by depositing a layer of α-cyano-4-hydroxycinnamic acid (CHCA) and potassium salts onto silicon nanopost arrays (NAPA) prior to tissue mounting. The matrix/salt pre-coated NAPA substrate significantly enhances all detected lipid signals allowing lipids to be detected at lower laser energies than bare NAPA. The improved sensitivity at lower laser energy enabled ion images to be generated at 10 µm spatial resolution from rat retinal tissue. Optimization of matrix pre-coated NAPA consisted of testing lithium, sodium, and potassium salts along with various matrices to investigate the increased sensitivity toward lipids for MALDI IMS experiments. It was determined that pre-coating NAPA with CHCA and potassium salts before thaw-mounting of tissue resulted in a signal intensity increase of at least 5.8 ± 0.1-fold for phospholipids and 2.0 ± 0.1-fold for neutral lipids compared to bare NAPA. Pre-coating NAPA with matrix and salt also reduced the necessary laser power to achieve desorption/ionization by ∼35%. This reduced the effective diameter of the ablation area from 13 ± 2 µm down to 8 ± 1 µm, enabling high spatial resolution MALDI IMS. Using pre-coated NAPA with CHCA and potassium salts offers a MALDI IMS substrate with broad molecular coverage of lipids in a single polarity that eliminates the need for extensive sample preparation after sectioning.

Diagnosis of melanoma by imaging mass spectrometry: Development and validation of a melanoma prediction model.

BACKGROUND: The definitive diagnosis of melanocytic neoplasia using solely histopathologic evaluation can be challenging. Novel techniques that objectively confirm diagnoses are needed. This study details the development and validation of a melanoma prediction model from spatially resolved multivariate protein expression profiles generated by imaging mass spectrometry (IMS). METHODS: Three board-certified dermatopathologists blindly evaluated 333 samples. Samples with triply concordant diagnoses were included in this study, divided into a training set (n = 241) and a test set (n = 92). Both the training and test sets included various representative subclasses of unambiguous nevi and melanomas. A prediction model was developed from the training set using a linear support vector machine classification model. RESULTS: We validated the prediction model on the independent test set of 92 specimens (75 classified correctly, 2 misclassified, and 15 indeterminate). IMS detects melanoma with a sensitivity of 97.6% and a specificity of 96.4% when evaluating each unique spot. IMS predicts melanoma at the sample level with a sensitivity of 97.3% and a specificity of 97.5%. Indeterminate results were excluded from sensitivity and specificity calculations. CONCLUSION: This study provides evidence that IMS-based proteomics results are highly concordant to diagnostic results obtained by careful histopathologic evaluation from a panel of expert dermatopathologists.

An orthogonal methods assessment of topical drug concentrations in skin and the impact for risk assessment in the viable epidermis.

Systemic toxicity assessments for oral or parenteral drugs often utilize the concentration of drug in plasma to enable safety margin calculations for human risk assessment. For topical drugs, there is no standard method for measuring drug concentrations in the stratum basale of the viable epidermis. This is particularly important since the superficial part of the epidermis, the stratum corneum (SC), is nonviable and where most of a topically applied drug remains, never penetrating deeper into the skin. We investigated the relative concentrations of a prototype kinase inhibitor using punch biopsy, laser capture microdissection, and imaging mass spectrometry methods in the SC, stratum basale, and dermis of minipig skin following topical application as a cream formulation. The results highlight the value of laser capture microdissection and mass spectrometry imaging in quantifying the large difference in drug concentration across the skin and even within the epidermis, and supports use of these methods for threshold-based toxicity risk assessments in specific anatomic locations of the skin, like of the stratum basale.

Histopathologic, immunophenotypic, and proteomics characteristics of low-grade phyllodes tumor and fibroadenoma: more similarities than differences.

Distinguishing low-grade phyllodes tumor from fibroadenoma is practically challenging due to their overlapping histologic features. However, the final interpretation is essential to surgeons, who base their management on the final pathology report. Patients who receive a diagnosis of fibroadenoma might not undergo any additional intervention while lumpectomy with wide margins is the standard of care for phyllodes tumor, which can have significant cosmetic consequences. We studied the clinical, immunophenotypic, and proteomics profiles of 31 histologically confirmed low-grade phyllodes tumor and 30 fibroadenomas. Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS) and immunohistochemistry for Ki-67, p53, ß-catenin, and E-cadherin were performed on all cases. After the mass spectra for all 31 cases of low-grade phyllodes tumor and 30 cases of fibroadenoma were collected, an average peak value for all cases was generated. There was no significant difference in the overall mass spectra pattern in any of the peaks identified. There was also overlap in the percentage of cells staining positive for Ki-67, p53, ß-catenin, and E-cadherin. The two groups of patients showed no statistically significant difference in age, tumor size, or disease-free survival. Neither group developed malignant transformation, distant metastases, or disease-related mortality. We have demonstrated low-grade phyllodes tumor and fibroadenoma to show significant overlapping clinical and proteomics features.

Sample Preparation and Analysis of Single Cells Using High Performance MALDI FTICR Mass Spectrometry.

Imaging mass spectrometry is a powerful technology that combines the molecular measurements of mass spectrometry with the spatial information inherent to microscopy. This unique combination of capabilities is ideally suited for the analysis of metabolites and lipids from single cells. This chapter describes a methodology for the sample preparation and analysis of single cells using high performance MALDI FTICR MS. Using this approach, we are able to generate profiles of lipid and metabolite expression from single cells that characterize cellular heterogeneity. This approach also enables the detection of variations in the expression profiles of lipids and metabolites induced by chemical stimulation of the cells. These results demonstrate that MALDI IMS provides an insightful view of lipid and metabolite expression useful in the characterization of a number of biological systems at the single cell level.

A recommended and verified procedure for in situ tryptic digestion of formalin-fixed paraffin-embedded tissues for analysis by matrix-assisted laser desorption/ionization imaging mass spectrometry.

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a molecular imaging technology uniquely capable of untargeted measurement of proteins, lipids, and metabolites while retaining spatial information about their location in situ. This powerful combination of capabilities has the potential to bring a wealth of knowledge to the field of molecular histology. Translation of this innovative research tool into clinical laboratories requires the development of reliable sample preparation protocols for the analysis of proteins from formalin-fixed paraffin-embedded (FFPE) tissues, the standard preservation process in clinical pathology. Although ideal for stained tissue analysis by microscopy, the FFPE process cross-links, disrupts, or can remove proteins from the tissue, making analysis of the protein content challenging. To date, reported approaches differ widely in process and efficacy. This tutorial presents a strategy derived from systematic testing and optimization of key parameters, for reproducible in situ tryptic digestion of proteins in FFPE tissue and subsequent MALDI IMS analysis. The approach describes a generalized method for FFPE tissues originating from virtually any source.

Zinc intoxication induces ferroptosis in A549 human lung cells.

Zinc (Zn) is an essential trace metal required for all forms of life, but is toxic at high concentrations. While the toxic effects of high levels of Zn are well documented, the mechanism of cell death appears to vary based on the study and concentration of Zn. Zn has been proposed as an anti-cancer treatment against non-small cell lung cancer (NSCLC). The goal of this analysis was to determine the effects of Zn on metabolism and cell death in A549 cells. Here, high throughput multi-omics analysis identified the molecular effects of Zn intoxication on the proteome, metabolome, and transcriptome of A549 human NSCLC cells after 5 min to 24 h of Zn exposure. Multi-omics analysis combined with additional experimental evidence suggests Zn intoxication induces ferroptosis, an iron and lipid peroxidation-dependent programmed cell death, demonstrating the utility of multi-omics analysis to identify cellular response to intoxicants.

Imaging mass spectrometry enables molecular profiling of mouse and human pancreatic tissue.

AIMS/HYPOTHESIS: The molecular response and function of pancreatic islet cells during metabolic stress is a complex process. The anatomical location and small size of pancreatic islets coupled with current methodological limitations have prevented the achievement of a complete, coherent picture of the role that lipids and proteins play in cellular processes under normal conditions and in diseased states. Herein, we describe the development of untargeted tissue imaging mass spectrometry (IMS) technologies for the study of in situ protein and, more specifically, lipid distributions in murine and human pancreases. METHODS: We developed matrix-assisted laser desorption/ionisation (MALDI) IMS protocols to study metabolite, lipid and protein distributions in mouse (wild-type and ob/ob mouse models) and human pancreases. IMS allows for the facile discrimination of chemically similar lipid and metabolite isoforms that cannot be distinguished using standard immunohistochemical techniques. Co-registration of MS images with immunofluorescence images acquired from serial tissue sections allowed accurate cross-registration of cell types. By acquiring immunofluorescence images first, this serial section approach guides targeted high spatial resolution IMS analyses (down to 15 µm) of regions of interest and leads to reduced time requirements for data acquisition. RESULTS: MALDI IMS enabled the molecular identification of specific phospholipid and glycolipid isoforms in pancreatic islets with intra-islet spatial resolution. This technology shows that subtle differences in the chemical structure of phospholipids can dramatically affect their distribution patterns and, presumably, cellular function within the islet and exocrine compartments of the pancreas (e.g. 18:1 vs 18:2 fatty acyl groups in phosphatidylcholine lipids). We also observed the localisation of specific GM3 ganglioside lipids [GM3(d34:1), GM3(d36:1), GM3(d38:1) and GM3(d40:1)] within murine islet cells that were correlated with a higher level of GM3 synthase as verified by immunostaining. However, in human pancreas, GM3 gangliosides were equally distributed in both the endocrine and exocrine tissue, with only one GM3 isoform showing islet-specific localisation. CONCLUSIONS/INTERPRETATION: The development of more complete molecular profiles of pancreatic tissue will provide important insight into the molecular state of the pancreas during islet development, normal function, and diseased states. For example, this study demonstrates that these results can provide novel insight into the potential signalling mechanisms involving phospholipids and glycolipids that would be difficult to detect by targeted methods, and can help raise new hypotheses about the types of physiological control exerted on endocrine hormone-producing cells in islets. Importantly, the in situ measurements afforded by IMS do not require a priori knowledge of molecules of interest and are not susceptible to the limitations of immunohistochemistry, providing the opportunity for novel biomarker discovery. Notably, the presence of multiple GM3 isoforms in mouse islets and the differential localisation of lipids in human tissue underscore the important role these molecules play in regulating insulin modulation and suggest species, organ, and cell specificity. This approach demonstrates the importance of both high spatial resolution and high molecular specificity to accurately survey the molecular composition of complex, multi-functional tissues such as the pancreas.

Next Generation Histology-Directed Imaging Mass Spectrometry Driven by Autofluorescence Microscopy.

Histology-directed imaging mass spectrometry (IMS) is a spatially targeted IMS acquisition method informed by expert annotation that provides rapid molecular characterization of select tissue structures. The expert annotations are usually determined on digital whole slide images of histological stains where the staining preparation is incompatible with optimal IMS preparation, necessitating serial sections: one for annotation, one for IMS. Registration is then used to align staining annotations onto the IMS tissue section. Herein, we report a next-generation histology-directed platform implementing IMS-compatible autofluorescence (AF) microscopy taken prior to any staining or IMS. The platform enables two histology-directed workflows, one that improves the registration process between two separate tissue sections using automated, computational monomodal AF-to-AF microscopy image registration, and a registration-free approach that utilizes AF directly to identify ROIs and acquire IMS on the same section. The registration approach is fully automated and delivers state of the art accuracy in histology-directed workflows for transfer of annotations (∼3-10 µm based on 4 organs from 2 species) while the direct AF approach is registration-free, allowing targeting of the finest structures visible by AF microscopy. We demonstrate the platform in biologically relevant case studies of liver stage malaria and human kidney disease with spatially targeted acquisition of sparsely distributed (composing less than one tenth of 1% of the tissue section area) malaria infected mouse hepatocytes and glomeruli in the human kidney case study.

An Integrated, High-Throughput Strategy for Multiomic Systems Level Analysis.

Proteomics, metabolomics, and transcriptomics generate comprehensive data sets, and current biocomputational capabilities allow their efficient integration for systems biology analysis. Published multiomics studies cover methodological advances as well as applications to biological questions. However, few studies have focused on the development of a high-throughput, unified sample preparation approach to complement high-throughput omic analytics. This report details the automation, benchmarking, and application of a strategy for transcriptomic, proteomic, and metabolomic analyses from a common sample. The approach, sample preparation for multi-omics technologies (SPOT), provides equivalent performance to typical individual omic preparation methods but greatly enhances throughput and minimizes the resources required for multiomic experiments. SPOT was applied to a multiomics time course experiment for zinc-treated HL-60 cells. The data reveal Zn effects on NRF2 antioxidant and NFkappaB signaling. High-throughput approaches such as these are critical for the acquisition of temporally resolved, multicondition, large multiomic data sets such as those necessary to assess complex clinical and biological concerns. Ultimately, this type of approach will provide an expanded understanding of challenging scientific questions across many fields.

Novel vacuum stable ketone-based matrices for high spatial resolution MALDI imaging mass spectrometry.

We describe the use of aromatic ketones and cinnamyl ketones that have high vacuum stability for analyzing tissue sections using matrix-assisted laser desorption/ionization imaging mass spectrometry. Specifically, the matrix, (E)-4-(2,5-dihydroxyphenyl)but-3-en-2-one (2,5-cDHA) provides high sensitivity and high vacuum stability while producing small size crystals (1-2 µm). A high throughput and highly reproducible sample preparation method was developed for these matrices that first involves using an organic spray solution for small matrix crystal seeding followed by spraying of the matrix in a 30% acetonitrile/70% water solution on the tissue surface to obtain a homogeneous coating of small crystals, suitable for high spatial resolution imaging.

Micro-Data-Independent Acquisition for High-Throughput Proteomics and Sensitive Peptide Mass Spectrum Identification.

State-of-the-art strategies for proteomics are not able to rapidly interrogate complex peptide mixtures in an untargeted manner with sensitive peptide and protein identification rates. We describe a data-independent acquisition (DIA) approach, microDIA (µDIA), that applies a novel tandem mass spectrometry (MS/MS) mass spectral deconvolution method to increase the specificity of tandem mass spectra acquired during proteomics experiments. Using the µDIA approach with a 10 min liquid chromatography gradient allowed detection of 3.1-fold more HeLa proteins than the results obtained from data-dependent acquisition (DDA) of the same samples. Additionally, we found the µDIA MS/MS deconvolution procedure is critical for resolving modified peptides with relatively small precursor mass shifts that cause the same peptide sequence in modified and unmodified forms to theoretically cofragment in the same raw MS/MS spectra. The µDIA workflow is implemented in the PROTALIZER software tool which fully automates tandem mass spectral deconvolution, queries every peptide with a library-free search algorithm against a user-defined protein database, and confidently identifies multiple peptides in a single tandem mass spectrum. We also benchmarked µDIA against DDA using a 90 min gradient analysis of HeLa and Escherichia coli peptides that were mixed in predefined quantitative ratios, and our results showed µDIA provided 24% more true positives at the same false positive rate.

Single-Cell Mass Spectrometry Reveals Changes in Lipid and Metabolite Expression in RAW 264.7 Cells upon Lipopolysaccharide Stimulation.

It has been widely recognized that individual cells that exist within a large population of cells, even if they are genetically identical, can have divergent molecular makeups resulting from a variety of factors, including local environmental factors and stochastic processes within each cell. Presently, numerous approaches have been described that permit the resolution of these single-cell expression differences for RNA and protein; however, relatively few techniques exist for the study of lipids and metabolites in this manner. This study presents a methodology for the analysis of metabolite and lipid expression at the level of a single cell through the use of imaging mass spectrometry on a high-performance Fourier transform ion cyclotron resonance mass spectrometer. This report provides a detailed description of the overall experimental approach, including sample preparation as well as the data acquisition and analysis strategy for single cells. Applying this approach to the study of cultured RAW264.7 cells, we demonstrate that this method can be used to study the variation in molecular expression with cell populations and is sensitive to alterations in that expression that occurs upon lipopolysaccharide stimulation. Graphical Abstract.

Enhanced Spatially Resolved Proteomics Using On-Tissue Hydrogel-Mediated Protein Digestion.

The identification of proteins from tissue specimens is a challenging area of biological research. Many current techniques for identification forfeit some level of spatial information during the sample preparation process. Recently, hydrogel technologies have been developed that perform spatially localized protein extraction and digestion prior to downstream proteomic analysis. Regiospecific protein identifications acquired using this approach have thus far been limited to 1-2 mm diameter areas. The need to target smaller populations of cells with this technology necessitates the production of smaller diameter hydrogels. Herein, we demonstrate hydrogel fabrication processes that allow hydrogel applications down to a diameter of ∼260 µm, approximately 1/15 of the area of previous approaches. Parameters such as the percent polyacrylamide used in hydrogel construction as well as the concentration of trypsin with which the hydrogel is loaded are investigated to maximize the number of protein identifications from subsequent liquid chromatography tandem MS (LC-MS/MS) analysis of hydrogel extracts. An 18% polyacrylamide concentration is shown to provide for a more rigid polymer network than the conventional 7.5% polyacrylamide concentration and supports the fabrication of individual hydrogels using the small punch biopsies. Over 600 protein identifications are still achieved at the smallest hydrogel diameters of 260 µm. The utility of these small hydrogels is demonstrated through the analysis of sub regions of a rat cerebellum tissue section. While over 900 protein identifications are made from each hydrogel, approximately 20% of the proteins identified are unique to each of the two regions, highlighting the importance of targeting tissue subtypes to accurately characterize tissue biology. These newly improved methods to the hydrogel process will allow researchers to target smaller biological features for robust spatially localized proteomic analyses.

Integrated, High-Throughput, Multiomics Platform Enables Data-Driven Construction of Cellular Responses and Reveals Global Drug Mechanisms of Action.

An understanding of how cells respond to perturbation is essential for biological applications; however, most approaches for profiling cellular response are limited in scope to pre-established targets. Global analysis of molecular mechanism will advance our understanding of the complex networks constituting cellular perturbation and lead to advancements in areas, such as infectious disease pathogenesis, developmental biology, pathophysiology, pharmacology, and toxicology. We have developed a high-throughput multiomics platform for comprehensive, de novo characterization of cellular mechanisms of action. Platform validation using cisplatin as a test compound demonstrates quantification of over 10 000 unique, significant molecular changes in less than 30 days. These data provide excellent coverage of known cisplatin-induced molecular changes and previously unrecognized insights into cisplatin resistance. This proof-of-principle study demonstrates the value of this platform as a resource to understand complex cellular responses in a high-throughput manner.

Trypsin and MALDI matrix pre-coated targets simplify sample preparation for mapping proteomic distributions within biological tissues by imaging mass spectrometry.

Prefabricated surfaces containing α-cyano-4-hydroxycinnamic acid and trypsin have been developed to facilitate enzymatic digestion of endogenous tissue proteins prior to matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS). Tissue sections are placed onto slides that were previously coated with α-cyano-4-hydroxycinnamic acid and trypsin. After incubation to promote enzymatic digestion, the tissue is analyzed by MALDI IMS to determine the spatial distribution of the tryptic fragments. The peptides detected in the MALDI IMS dataset were identified by Liquid chromatography-tandem mass spectrometry/mass spectrometry. Protein identification was further confirmed by correlating the localization of unique tryptic fragments originating from common parent proteins. Using this procedure, proteins with molecular weights as large as 300 kDa were identified and their distributions were imaged in sections of rat brain. In particular, large proteins such as myristoylated alanine-rich C-kinase substrate (29.8 kDa) and spectrin alpha chain, non-erythrocytic 1 (284 kDa) were detected that are not observed without trypsin. The pre-coated targets simplify workflow and increase sample throughput by decreasing the sample preparation time. Further, the approach allows imaging at higher spatial resolution compared with robotic spotters that apply one drop at a time. Copyright © 2016 John Wiley & Sons, Ltd.