Glomeruli filter blood through the coordination of podocytes, mesangial cells, fenestrated endothelial cells, and the glomerular basement membrane. Cellular changes, such as podocyte loss, are associated with pathologies like diabetic kidney disease. However, little is known regarding the in situ molecular profiles of specific cell types and how these profiles change with disease. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is well-suited for untargeted tissue mapping of a wide range of molecular classes. Importantly, additional imaging modalities can be integrated with MALDI IMS to associate these biomolecular distributions to specific cell types. Here, we integrated workflow combining MALDI IMS and multiplexed immunofluorescence (MxIF) microscopy. High spatial resolution MALDI IMS (5 μm) was used to determine lipid distributions within human glomeruli from a normal portion of fresh-frozen kidney cancer nephrectomy tissue revealing intra-glomerular lipid heterogeneity. Mass spectrometric data were linked to specific glomerular cell types and substructures through new methods that enable MxIF microscopy to be performed on the same tissue section following MALDI IMS, without sacrificing signal quality from either modality. Machine learning approaches were combined enabling cell type segmentation and identification based on MxIF data. This was followed by mining of cell type or cluster-associated MALDI IMS signatures using classification and interpretable machine learning. This allowed automated discovery of spatially specific molecular markers for glomerular cell types and substructures as well as lipids correlated to deep and superficial glomeruli. Overall, our work establishes a toolbox for probing molecular signatures of glomerular cell types and substructures within tissue microenvironments providing a framework applicable to other kidney tissue features and organ systems.

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Purpose: Mutations in the gene that encodes the enzyme acid sphingomyelinase (ASMase) are associated with Niemann-Pick disease, a lysosomal storage disorder. Mice that lack ASMase (ASMase-/-) exhibit age-related retinal degeneration and large increases in accumulation of lipofuscin in the retinal pigment epithelium (RPE). We examined which lipid species accumulate in the retina and the RPE of ASMase-/- mice and whether the retinal degeneration is associated with impaired photoreceptor metabolism and retinyl chromophore processing. Methods: NADPH availability and all-trans retinol formation after rhodopsin bleaching were measured in isolated single rod photoreceptors with fluorescence imaging; sphingolipid levels in retinas and RPEs were measured with LC/MS; relative abundances of different lipid species in different retinal layers were measured with MALDI imaging mass spectrometry. Results: There was no detectable difference in the kinetics of all-trans retinol formation or the NADPH-generating capacity between ASMase-/- and wild-type mice. Sphingomyelin levels were much higher in the retinas and RPEs of ASMase-/- animals compared to wild type, but there were no significant differences for ceramides. There was a large increase in the abundance of bis(monoacylglycero)phosphates (BMPs) in ASMase-/- mice, indicative of lysosomal dysfunction, but no substantial changes were detected for the bis-retinoid A2E. Conclusions: Lysosomal dysfunction and retinal degeneration in ASMase-/- mice are not associated with defects in rod photoreceptor metabolism that affect all-trans retinol formation and availability of NADPH. Lysosomal dysfunction in ASMase-/- mice is not associated with bis-retinoid A2E accumulation.

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The lack of standardization in antibody validation remains a major contributor to irreproducibility of human research. To address this, we have applied a standardized approach to validate a panel of antibodies to identify 18 major cell types and 5 extracellular matrix compartments in the human kidney by immunofluorescence (IF) microscopy. We have used these to generate an organ mapping antibody panel for two-dimensional (2-D) and three-dimensional (3-D) cyclical IF (CyCIF) to provide a more detailed method for evaluating tissue segmentation and volumes using a larger panel of markers than would normally be possible using standard fluorescence microscopy. CyCIF also makes it possible to perform multiplexed IF microscopy of whole slide images, which is a distinct advantage over other multiplexed imaging technologies that are applicable to limited fields of view. This enables a broader view of cell distributions across larger anatomical regions, allowing a better chance to capture localized regions of dysfunction in diseased tissues. These methods are broadly accessible to any laboratory with a fluorescence microscope, enabling spatial cellular phenotyping in normal and disease states. We also provide a detailed solution for image alignment between CyCIF cycles that can be used by investigators to perform these studies without programming experience using open-sourced software. This ability to perform multiplexed imaging without specialized instrumentation or computational skills opens the door to integration with more highly dimensional molecular imaging modalities such as spatial transcriptomics and imaging mass spectrometry, enabling the discovery of molecular markers of specific cell types, and how these are altered in disease.NEW & NOTEWORTHY We describe here validation criteria used to define on organ mapping panel of antibodies that can be used to define 18 cell types and five extracellular matrix compartments using cyclical immunofluorescence (CyCIF) microscopy. As CyCIF does not require specialized instrumentation, and image registration required to assemble CyCIF images can be performed by any laboratory without specialized computational skills, this technology is accessible to any laboratory with access to a fluorescence microscope and digital scanner.

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There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. Comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measure dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We establish a spatially-anchored epigenomic atlas to define the kidney’s active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we note distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3, KLF6, and KLF10 regulates the transition between health and injury, while in thick ascending limb cells this transition is regulated by NR2F1. Further, combined perturbation of ELF3, KLF6, and KLF10 distinguishes two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.@en

The glomerulus is a multicellular functional tissue unit (FTU) of the nephron that is responsible for blood filtration. Each glomerulus contains multiple substructures and cell types that are crucial for their function. To understand normal aging and disease in kidneys, methods for high spatial resolution molecular imaging within these FTUs across whole slide images is required. Here we demonstrate a workflow using microscopy-driven selected sampling to enable 5 μm pixel size matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) of all glomeruli within whole slide human kidney tissues. Such high spatial resolution imaging entails large numbers of pixels, increasing the data acquisition times. Automating FTU-specific tissue sampling enables high-resolution analysis of critical tissue structures, while concurrently maintaining throughput. Glomeruli were automatically segmented using coregistered autofluorescence microscopy data, and these segmentations were translated into MALDI IMS measurement regions. This allowed high-throughput acquisition of 268 glomeruli from a single whole slide human kidney tissue section. Unsupervised machine learning methods were used to discover molecular profiles of glomerular subregions and differentiate between healthy and diseased glomeruli. Average spectra for each glomerulus were analyzed using Uniform Manifold Approximation and Projection (UMAP) and k-means clustering, yielding 7 distinct groups of differentiated healthy and diseased glomeruli. Pixel-wise k-means clustering was applied to all glomeruli, showing unique molecular profiles localized to subregions within each glomerulus. Automated microscopy-driven, FTU-targeted acquisition for high spatial resolution molecular imaging maintains high-throughput and enables rapid assessment of whole slide images at cellular resolution and identification of tissue features associated with normal aging and disease.

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Imaging mass spectrometry (IMS) provides untargeted, highly multiplexed maps of molecular distributions in tissue. Ion images are routinely presented as heatmaps and can be overlaid onto complementary microscopy images that provide greater context. However, heatmaps use transparency blending to visualize both images, obscuring subtle quantitative differences and distribution gradients. Here, we developed a contour mapping approach that combines information from IMS ion intensity distributions with that of stained microscopy. As a case study, we applied this approach to imaging data from Staphylococcus aureus-infected murine kidney. In a univariate, or single molecular species, use-case of the contour map representation of IMS data, certain lipids colocalizing with regions of infection were selected using Pearson’s correlation coefficient. Contour maps of these lipids overlaid with stained microscopy showed enhanced visualization of lipid distributions and spatial gradients in and around the bacterial abscess as compared to traditional heatmaps. The full IMS data set comprising hundreds of individual ion images was then grouped into a smaller subset of representative patterns using non-negative matrix factorization (NMF). Contour maps of these multivariate NMF images revealed distinct molecular profiles of the major abscesses and surrounding immune response. This contour mapping workflow also enabled a molecular visualization of the transition zone at the host-pathogen interface, providing potential clues about the spatial molecular dynamics beyond what histological staining alone provides. In summary, we developed a new IMS-based contour mapping approach to augment classical stained microscopy images, providing an enhanced and more interpretable visualization of IMS-microscopy multimodal molecular imaging data sets.

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Introduction: Age related macular degeneration (AMD) causes legal blindness worldwide, with few therapeutic targets in early disease and no treatments for 80% of cases. Extracellular deposits, including drusen and subretinal drusenoid deposits (SDD; also called reticular pseudodrusen), disrupt cone and rod photoreceptor functions and strongly confer risk for advanced disease. Due to the differential cholesterol composition of drusen and SDD, lipid transfer and cycling between photoreceptors and support cells are candidate dysregulated pathways leading to deposit formation. The current study explores this hypothesis through a comprehensive lipid compositional analysis of SDD. Methods: Histology and transmission electron microscopy were used to characterize the morphology of SDD. Highly sensitive tools of imaging mass spectrometry (IMS) and nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) in positive and negative ion modes were used to spatially map and identify SDD lipids, respectively. An interpretable supervised machine learning approach was utilized to compare the lipid composition of SDD to regions of uninvolved retina across 1873 IMS features and to automatically discern candidate markers for SDD. Immunohistochemistry (IHC) was used to localize secretory phospholipase A2 group 5 (PLA2G5). Results: Among the 1873 detected features in IMS data, three lipid classes, including lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE) and lysophosphatidic acid (LysoPA) were observed nearly exclusively in SDD while presumed precursors, including phosphatidylcholine (PC), phosphatidylethanolamine (PE) and phosphatidic acid (PA) lipids were detected in SDD and adjacent photoreceptor outer segments. Molecular signals specific to SDD were found in central retina and elsewhere. IHC results indicated abundant PLA2G5 in photoreceptors and retinal pigment epithelium (RPE). Discussion: The abundance of lysolipids in SDD implicates lipid remodeling or degradation in deposit formation, consistent with ultrastructural evidence of electron dense lipid-containing structures distinct from photoreceptor outer segment disks and immunolocalization of secretory PLA2G5 in photoreceptors and RPE. Further studies are required to understand the role of lipid signals observed in and around SDD.

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Gangliosides are acidic glycosphingolipids, containing ceramide moieties and oligosaccharide chains with one or more sialic acid residue(s) and are highly diverse isomeric structures with distinct biological roles. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) enables the untargeted spatial analysis of gangliosides, among other biomolecules, directly from tissue sections. Integrating trapped ion mobility spectrometry with MALDI IMS allows for the analysis of isomeric lipid structures in situ. Here, we demonstrate the gas-phase separation and identification of disialoganglioside isomers GD1a and GD1b that differ in the position of a sialic acid residue, in multiple samples, including a standard mixture of both isomers, a biological extract, and directly from thin tissue sections. The unique spatial distributions of GD1a/b (d36:1) and GD1a/b (d38:1) isomers were determined in rat hippocampus and spinal cord tissue sections, demonstrating the ability to structurally characterize and spatially map gangliosides based on both the carbohydrate chain and ceramide moieties.

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Introduction: Although Staphylococcus aureus is the leading cause of biofilm-related infections, the lipidomic distributions within these biofilms is poorly understood. Here, lipidomic mapping of S. aureus biofilm cross-sections was performed to investigate heterogeneity between horizontal biofilm layers. Methods: S. aureus biofilms were grown statically, embedded in a mixture of carboxymethylcellulose/gelatin, and prepared for downstream matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS). Trapped ion mobility spectrometry (TIMS) was also applied prior to mass analysis. Results: Implementation of TIMS led to a ∼ threefold increase in the number of lipid species detected. Washing biofilm samples with ammonium formate (150 mM) increased signal intensity for some bacterial lipids by as much as tenfold, with minimal disruption of the biofilm structure. MALDI TIMS IMS revealed that most lipids localize primarily to a single biofilm layer, and species from the same lipid class such as cardiolipins CL(57:0) – CL(66:0) display starkly different localizations, exhibiting between 1.5 and 6.3-fold intensity differences between layers (n = 3, p < 0.03). No horizontal layers were observed within biofilms grown anaerobically, and lipids were distributed homogenously. Conclusions: High spatial resolution analysis of S. aureus biofilm cross-sections by MALDI TIMS IMS revealed stark lipidomic heterogeneity between horizontal S. aureus biofilm layers demonstrating that each layer was molecularly distinct. Finally, this workflow uncovered an absence of layers in biofilms grown under anaerobic conditions, possibly indicating that oxygen contributes to the observed heterogeneity under aerobic conditions. Future applications of this workflow to study spatially localized molecular responses to antimicrobials could provide new therapeutic strategies.

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The search for molecular species that are differentially expressed between biological states is an important step towards discovering promising biomarker candidates. In imaging mass spectrometry (IMS), performing this search manually is often impractical due to the large size and high-dimensionality of IMS datasets. Instead, we propose an interpretable machine learning workflow that automatically identifies biomarker candidates by their mass-to-charge ratios, and that quantitatively estimates their relevance to recognizing a given biological class using Shapley additive explanations (SHAP). The task of biomarker candidate discovery is translated into a feature ranking problem: given a classification model that assigns pixels to different biological classes on the basis of their mass spectra, the molecular species that the model uses as features are ranked in descending order of relative predictive importance such that the top-ranking features have a higher likelihood of being useful biomarkers. Besides providing the user with an experiment-wide measure of a molecular species' biomarker potential, our workflow delivers spatially localized explanations of the classification model's decision-making process in the form of a novel representation called SHAP maps. SHAP maps deliver insight into the spatial specificity of biomarker candidates by highlighting in which regions of the tissue sample each feature provides discriminative information and in which regions it does not. SHAP maps also enable one to determine whether the relationship between a biomarker candidate and a biological state of interest is correlative or anticorrelative. Our automated approach to estimating a molecular species' potential for characterizing a user-provided biological class, combined with the untargeted and multiplexed nature of IMS, allows for the rapid screening of thousands of molecular species and the obtention of a broader biomarker candidate shortlist than would be possible through targeted manual assessment. Our biomarker candidate discovery workflow is demonstrated on mouse-pup and rat kidney case studies.

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We demonstrate the utility of combining silicon nanopost arrays (NAPA) and trapped ion mobility imaging mass spectrometry (TIMS IMS) for high spatial resolution and specificity mapping of neutral lipid classes in tissue. Ionization of neutral lipid species such as triglycerides (TGs), cholestryl esters (CEs), and hexosylceramides (HexCers) from biological tissues has remained a challenge for imaging applications. NAPA, a matrix-free laser desorption ionization substrate, provides enhanced ionization efficiency for the above-mentioned neutral lipid species, providing complementary lipid coverage to matrix-assisted laser desorption ionization (MALDI). The combination of NAPA and TIMS IMS enables imaging of neutral lipid species at 20 μm spatial resolution while also increasing molecular coverage greater than 2-fold using gas-phase ion mobility separations. This is a significant improvement with respect to sensitivity, specificity, and spatial resolution compared to previously reported imaging studies using NAPA alone. Improved specificity for neutral lipid analysis using TIMS IMS was shown using rat kidney tissue to separate TGs, CEs, HexCers, and phospholipids into distinct ion mobility trendlines. Further, this technology allowed for the separation of isomeric species, including mobility resolved isomers of Cer(d42:2) (m/z 686.585) with distinct spatial localizations measured in rat kidney tissue section.

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Here, we describe the preservation and preparation of human kidney tissue for interrogation by histopathology, imaging mass spectrometry, and multiplexed immunofluorescence. Custom image registration and integration techniques are used to create cellular and molecular atlases of this organ system. Through careful optimization, we ensure high-quality and reproducible datasets suitable for cross-patient comparisons that are essential to understanding human health and disease. Moreover, each of these steps can be adapted to other organ systems or diseases, enabling additional atlas efforts.

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Lipids are a structurally diverse class of molecules with important biological functions including cellular signaling and energy storage. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) allows for direct mapping of biomolecules in tissues. Fully characterizing the structural diversity of lipids remains a challenge due to the presence of isobaric and isomeric species, which greatly complicates data interpretation when only m/z information is available. Integrating ion mobility separations aids in deconvoluting these complex mixtures and addressing the challenges of lipid IMS. Here, we demonstrate that a MALDI quadrupole time-of-flight (Q-TOF) mass spectrometer with trapped ion mobility spectrometry (TIMS) enables a >250% increase in the peak capacity during IMS experiments. MALDI TIMS-MS separation of lipid isomer standards, including sn backbone isomers, acyl chain isomers, and double-bond position and stereoisomers, is demonstrated. As a proof of concept, in situ separation and imaging of lipid isomers with distinct spatial distributions were performed using tissue sections from a whole-body mouse pup.

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Low molecular weight metabolites are essential for defining the molecular phenotypes of cells. However, spatial metabolomics tools often lack the sensitivity, specify, and spatial resolution to provide comprehensive descriptions of these species in tissue. MALDI imaging mass spectrometry (IMS) of low molecular weight ions is particularly challenging as MALDI matrix clusters are often nominally isobaric with multiple metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Additional difficulties surrounding low weight metabolite visualization include high resolution imaging, while maintaining sufficient ion numbers for broad and representative analysis of the tissue chemical complement. Here, we use MALDI timsTOF IMS to image low molecular weight metabolites at higher spatial resolution than most metabolite MALDI IMS experiments (20 μm) while maintaining broad coverage within the human kidney. We demonstrate that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different distributions within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for spatial metabolomics experiments. Through this improved sensitivity, we have found >40 low molecular weight metabolites in human kidney tissue, such as argininic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. Future work will involve further exploring metabolomic profiles of human kidneys as a function of age, sex, and race.

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Imaging mass spectrometry (IMS) enables the spatially targeted molecular assessment of biological tissues at cellular resolutions. New developments and technologies are essential for uncovering the molecular drivers of native physiological function and disease. Instrumentation must maximize spatial resolution, throughput, sensitivity, and specificity, because tissue imaging experiments consist of thousands to millions of pixels. Here, we report the development and application of a matrix-assisted laser desorption/ionization (MALDI) trapped ion-mobility spectrometry (TIMS) imaging platform. This prototype MALDI timsTOF instrument is capable of 10 μm spatial resolutions and 20 pixels/s throughput molecular imaging. The MALDI source utilizes a Bruker SmartBeam 3-D laser system that can generate a square burn pattern of <10 × 10 μm at the sample surface. General image performance was assessed using murine kidney and brain tissues and demonstrate that high-spatial-resolution imaging data can be generated rapidly with mass measurement errors <5 ppm and ∼40 000 resolving power. Initial TIMS-based imaging experiments were performed on whole-body mouse pup tissue demonstrating the separation of closely isobaric [PC(32:0) + Na]⁺ and [PC(34:3) + H]⁺ (3 mDa mass difference) in the gas phase. We have shown that the MALDI timsTOF platform can maintain reasonable data acquisition rates (>2 pixels/s) while providing the specificity necessary to differentiate components in complex mixtures of lipid adducts. The combination of high-spatial-resolution and throughput imaging capabilities with high-performance TIMS separations provides a uniquely tunable platform to address many challenges associated with advanced molecular imaging applications. ©

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