Three-dimensional imaging mass cytometry for highly multiplexed molecular and cellular mapping of tissues and the tumor microenvironment

MALDI-IHC-Guided In-Depth Spatial Proteomics: Targeted and Untargeted MSI Combined

Recently, a novel technology was published, utilizing the strengths of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) and immunohistochemistry (IHC), achieving highly multiplexed, targeted imaging of biomolecules in tissue. This new technique, called MALDI-IHC, opened up workflows to target molecules of interest using MALDI-MSI that are usually targeted by standard IHC. In this paper, the utility of targeted MALDI-IHC and its complementarity with untargeted on-tissue bottom-up spatial proteomics is explored using breast cancer tissue. Furthermore, the MALDI-2 effect was investigated and demonstrated to improve MALDI-IHC. Formalin-fixed paraffin-embedded (FFPE) human breast cancer tissue sections were stained for multiplex MALDI-IHC with six photocleavable mass-tagged (PC-MT) antibodies constituting a breast cancer antibody panel (CD20, actin-αSM, HER2, CD68, vimentin, and panCK). K-means spatial clusters were created based on the MALDI-IHC images and cut out using laser-capture microdissection (LMD) for further untargeted LC-MS-based bottom-up proteomics analyses. Numerous peptides could be tentatively assigned to multiple proteins, of which three proteins were also part of the antibody panel (vimentin, keratins, and actin). Post-ionization with MALDI-2 showed an increased intensity of the PC-MTs and suggests options for the development of new mass-tags. Although the on-tissue digestion covered a wider range of proteins, the MALDI-IHC allowed for easy and straightforward identification of proteins that were not detected in untargeted approaches. The combination of the multiplexed MALDI-IHC with image-guided proteomics showed great potential to further investigate diseases by providing complementary information from the same tissue section and without the need for customized instrumentation.

Multimodal Mass Spectrometry Imaging of an Aggregated 3D Cell Culture Model

Multimodal mass spectrometry imaging (MSI) is a leading approach for investigating the molecular processes within biological samples. The parallel detection of compounds including metabolites, lipids, proteins, and metal isotopes allows for a more holistic understanding of tissue microenvironments. Universal sample preparation is a primary enabler for samples of the same set to be run across multiple modalities. Using the same method and materials for a cohort of samples reduces any potential variability during sample preparation and allows for comparable analysis across analytical imaging techniques. Here, the MSI workflow is describing a sample preparation protocol for the analysis of three-dimensional (3D) cell culture models. The analysis of biologically relevant cultures by multimodal MSI offers a method in which models of cancer and disease can be studied for the use in early-stage drug development.

Single-cell high-dimensional imaging mass cytometry: one step beyond in oncology

Solid tumors have a dynamic ecosystem in which malignant and non-malignant (endothelial, stromal, and immune) cell types constantly interact. Importantly, the abundance, localization, and functional orientation of each cell component within the tumor microenvironment vary significantly over time and in response to treatment. Such intratumoral heterogeneity influences the tumor course and its sensitivity to treatments. Recently, high-dimensional imaging mass cytometry (IMC) has been developed to explore the tumor ecosystem at the single-cell level. In the last years, several studies demonstrated that IMC is a powerful tool to decipher the tumor complexity. In this review, we summarize the potential of this technology and how it may be useful for cancer research (from preclinical to clinical studies).

MALDI HiPLEX-IHC: multiomic and multimodal imaging of targeted intact proteins in tissues

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is one of the most widely used methods for imaging the spatial distribution of unlabeled small molecules such as metabolites, lipids and drugs in tissues. Recent progress has enabled many improvements including the ability to achieve single cell spatial resolution, 3D-tissue image reconstruction, and the precise identification of different isomeric and isobaric molecules. However, MALDI-MSI of high molecular weight intact proteins in biospecimens has thus far been difficult to achieve. Conventional methods normally require in situ proteolysis and peptide mass fingerprinting, have low spatial resolution, and typically detect only the most highly abundant proteins in an untargeted manner. In addition, MSI-based multiomic and multimodal workflows are needed which can image both small molecules and intact proteins from the same tissue. Such a capability can provide a more comprehensive understanding of the vast complexity of biological systems at the organ, tissue, and cellular levels of both normal and pathological function. A recently introduced top-down spatial imaging approach known as MALDI HiPLEX-IHC (MALDI-IHC for short) provides a basis for achieving this high-information content imaging of tissues and even individual cells. Based on novel photocleavable mass-tags conjugated to antibody probes, high-plex, multimodal and multiomic MALDI-based workflows have been developed to image both small molecules and intact proteins on the same tissue sample. Dual-labeled antibody probes enable multimodal mass spectrometry and fluorescent imaging of targeted intact proteins. A similar approach using the same photocleavable mass-tags can be applied to lectin and other probes. We detail here several examples of MALDI-IHC workflows designed to enable high-plex, multiomic and multimodal imaging of tissues at a spatial resolution as low as 5 µm. This approach is compared to other existing high-plex methods such as imaging mass cytometry, MIBI-TOF, GeoMx and CODEX. Finally, future applications of MALDI-IHC are discussed.

Capabilities of Single Cell ICP-MS for the Analysis of Cell Suspensions from Solid Tissues

Single cell elemental (SC) analysis of isogenic cell cultures can be done using inductively coupled plasma (ICP-MS) detection. However, 2D cell cultures are just models to simplify the complexity of real tissue samples. Here, we show for the first time the capabilities of the technique (SC-ICP-MS) to analyze single cell suspensions of isolated cells from tissues. An optimized cocktail of proteolytic and collagenolytic enzymes was applied in a single preparation step with cellular yields up to 28% using 0.5 g of fresh rat spleen and liver, respectively. The retrieved cells revealed adequate morphology and stability to be examined by SC-ICP-MS. Quantitative elemental analysis of P, S, Cu, and Fe from disaggregated cells from rat spleen and liver tissues revealed levels of Fe of 7-16 fg/cell in the spleen and 8-12 fg/cell in the liver, while Cu was about 3-5 fg/cell in the spleen and 1.5-2.5 fg/cell in the liver. Evaluation of the transmembrane protein transferrin receptor 1 (TfR1) expression levels in disaggregated cells was also conducted by using a Nd-labelled antibody against this cell surface biomarker. Quantitative results showed significantly lower expression in the disaggregated cells than in the cell model HepG2, in agreement with the overexpression of this biomarker in tumor cells. In this proof of concept study, the tissue disaggregation protocol has shown to maintain the elemental intracellular content of cells as well as the presence of relevant antigens. This opens a completely new area of research for SC-ICP-MS in tissue samples as a complementary strategy with validation capabilities.

Unsupervised discovery of tissue architecture in multiplexed imaging

Multiplexed imaging and spatial transcriptomics enable highly resolved spatial characterization of cellular phenotypes, but still largely depend on laborious manual annotation to understand higher-order patterns of tissue organization. As a result, higher-order patterns of tissue organization are poorly understood and not systematically connected to disease pathology or clinical outcomes. To address this gap, we developed an approach called UTAG to identify and quantify microanatomical tissue structures in multiplexed images without human intervention. Our method combines information on cellular phenotypes with the physical proximity of cells to accurately identify organ-specific microanatomical domains in healthy and diseased tissue. We apply our method to various types of images across healthy and disease states to show that it can consistently detect higher-level architectures in human tissues, quantify structural differences between healthy and diseased tissue, and reveal tissue organization patterns at the organ scale.

Spatial multi-omics analyses of the tumor immune microenvironment

In the past decade, single-cell technologies have revealed the heterogeneity of the tumor-immune microenvironment at the genomic, transcriptomic, and proteomic levels and have furthered our understanding of the mechanisms of tumor development. Single-cell technologies have also been used to identify potential biomarkers. However, spatial information about the tumor-immune microenvironment such as cell locations and cell–cell interactomes is lost in these approaches. Recently, spatial multi-omics technologies have been used to study transcriptomes, proteomes, and metabolomes of tumor-immune microenvironments in several types of cancer, and the data obtained from these methods has been combined with immunohistochemistry and multiparameter analysis to yield markers of cancer progression. Here, we review numerous cutting-edge spatial ‘omics techniques, their application to study of the tumor-immune microenvironment, and remaining technical challenges.

CODA: quantitative 3D reconstruction of large tissues at cellular resolution

A central challenge in biology is obtaining high-content, high-resolution information while analyzing tissue samples at volumes relevant to disease progression. We address this here with CODA, a method to reconstruct exceptionally large (up to multicentimeter cubed) tissues at subcellular resolution using serially sectioned hematoxylin and eosin-stained tissue sections. Here we demonstrate CODA's ability to reconstruct three-dimensional (3D) distinct microanatomical structures in pancreas, skin, lung and liver tissues. CODA allows creation of readily quantifiable tissue volumes amenable to biological research. As a testbed, we assess the microanatomy of the human pancreas during tumorigenesis within the branching pancreatic ductal system, labeling ten distinct structures to examine heterogeneity and structural transformation during neoplastic progression. We show that pancreatic precancerous lesions develop into distinct 3D morphological phenotypes and that pancreatic cancer tends to spread far from the bulk tumor along collagen fibers that are highly aligned to the 3D curves of ductal, lobular, vascular and neural structures. Thus, CODA establishes a means to transform broadly the structural study of human diseases through exploration of exhaustively labeled 3D microarchitecture.

Immune-Triggered Forms of Plasticity Across Brain Regions

Immune cells play numerous roles in the host defense against the invasion of microorganisms and pathogens, which induces the release of inflammatory mediators (e.g., cytokines and chemokines). In the CNS, microglia is the major resident immune cell. Recent efforts have revealed the diversity of the cell types and the heterogeneity of their functions. The refinement of the synapse structure was a hallmark feature of the microglia, while they are also involved in the myelination and capillary dynamics. Another promising feature is the modulation of the synaptic transmission as synaptic plasticity and the intrinsic excitability of neurons as non-synaptic plasticity. Those modulations of physiological properties of neurons are considered induced by both transient and chronic exposures to inflammatory mediators, which cause behavioral disorders seen in mental illness. It is plausible for astrocytes and pericytes other than microglia and macrophage to induce the immune-triggered plasticity of neurons. However, current understanding has yet achieved to unveil what inflammatory mediators from what immune cells or glia induce a form of plasticity modulating pre-, post-synaptic functions and intrinsic excitability of neurons. It is still unclear what ion channels and intracellular signaling of what types of neurons in which brain regions of the CNS are involved. In this review, we introduce the ubiquitous modulation of the synaptic efficacy and the intrinsic excitability across the brain by immune cells and related inflammatory cytokines with the mechanism for induction. Specifically, we compare neuro-modulation mechanisms by microglia of the intrinsic excitability of cerebellar Purkinje neurons with cerebral pyramidal neurons, stressing the inverted directionality of the plasticity. We also discuss the suppression and augmentation of the extent of plasticity by inflammatory mediators, as the meta-plasticity by immunity. Lastly, we sum up forms of immune-triggered plasticity in the different brain regions with disease relevance. Together, brain immunity influences our cognition, sense, memory, and behavior via immune-triggered plasticity.

Immuno Tomography (IT) and Imaging Mass Cytometry (IMC) for constructing spatially resolved, multiplexed 3D IMC data sets

PURPOSE

We have previously used Immuno Tomography (IT) to identify label-retaining stem cell populations in the cornea and meibomian gland. While this method provides the unique ability to quantify stem cell populations comprised of 1-4 cells, the number of antigens that can be sequentially used to characterize these unique cells is limited by antigen stability after antibody stripping and re-probing. To address this deficiency, we have evaluated the capability of Imaging Mass Cytometry™ (IMC™) to generate multiplexed images using metal-conjugated antibodies to label IT plastic sections and generate 3-dimensional IMC data sets (3D IMC).

METHODS

K5-H2B-GFP mice, 56 days after doxycycline chase, were sacrificed and eyelid tissue processed for IT. A total of 400 serial, plastic sections, 2 μm thick, were then probed using metal-tagged antibodies specific for sox 9, collagen type I, E-cadherin, Ki67, GFP, αSMA, vimentin, and DNA intercalator. Multiplexed images were then generated using an Imaging Mass Cytometry system (Fluidigm®), and 3D reconstructions were assembled.

RESULTS

All 8 metal-labeled tags were detected and their images were successfully assembled into 3D IMC data sets. GFP-labeled nuclei were identified within the meibomian glands in comparable numbers to those previously reported for slow-cycling meibomian gland stem cells.

CONCLUSIONS

These findings demonstrate that IMC can be used on plastic sections to generate multiplexed, 3D data sets that can be reconstructed to show the spatial localization of meibomian gland stem cells. We propose that 3D IMC might prove valuable in more fully characterizing stem cell populations in different tissues.

Unbiased spatial proteomics with single-cell resolution in tissues

Mass spectrometry (MS)-based proteomics has become a powerful technology to quantify the entire complement of proteins in cells or tissues. Here, we review challenges and recent advances in the LC-MS-based analysis of minute protein amounts, down to the level of single cells. Application of this technology revealed that single-cell transcriptomes are dominated by stochastic noise due to the very low number of transcripts per cell, whereas the single-cell proteome appears to be complete. The spatial organization of cells in tissues can be studied by emerging technologies, including multiplexed imaging and spatial transcriptomics, which can now be combined with ultra-sensitive proteomics. Combined with high-content imaging, artificial intelligence and single-cell laser microdissection, MS-based proteomics provides an unbiased molecular readout close to the functional level. Potential applications range from basic biological questions to precision medicine.

Spatiotemporal behavior of T cells in vaccination

Vaccines are the most cost-effective resource to contain and eliminate infectious diseases. Despite decades of research in the field, several pathogens have eluded the effect of conventional vaccines mostly due their failure in inducing strong T cell responses. There is a need for new vaccine technologies that can surpass this problem. Recent advances in imaging techniques have allowed the study of T cell dynamics within their surrounding cellular niches. This information is invaluable to elucidate the main cellular mechanisms to target in order to optimize vaccine efficiency. In this review, we summarize the most recent key discoveries in T cell behavior in the context of vaccination and immunization.

Bioinformatics and the Metaverse: Are We Ready?

COVID-19 forced humanity to think about new ways of working globally without physically being present with other people, and eXtended Reality (XR) systems (defined as Virtual Reality, Augmented Reality and Mixed Reality) offer a potentially elegant solution. Previously seen as mainly for gaming, commercial and research institutions are investigating XR solutions to solve real world problems from training, simulation, mental health, data analysis, and studying disease progression. More recently large corporations such as Microsoft and Meta have announced they are developing the Metaverse as a new paradigm to interact with the digital world. This article will look at how visualization can leverage the Metaverse in bioinformatics research, the pros and cons of this technology, and what the future may hold.

Spatially mapping the immune landscape of melanoma using imaging mass cytometry

Melanoma is an immunogenic cancer with a high response rate to immune checkpoint inhibitors (ICIs). It harbors a high mutation burden compared with other cancers and, as a result, has abundant tumor-infiltrating lymphocytes (TILs) within its microenvironment. However, understanding the complex interplay between the stroma, tumor cells, and distinct TIL subsets remains a substantial challenge in immune oncology. To properly study this interplay, quantifying spatial relationships of multiple cell types within the tumor microenvironment is crucial. To address this, we used cytometry time-of-flight (CyTOF) imaging mass cytometry (IMC) to simultaneously quantify the expression of 35 protein markers, characterizing the microenvironment of 5 benign nevi and 67 melanomas. We profiled more than 220,000 individual cells to identify melanoma, lymphocyte subsets, macrophage/monocyte, and stromal cell populations, allowing for in-depth spatial quantification of the melanoma microenvironment. We found that within pretreatment melanomas, the abundance of proliferating antigen-experienced cytotoxic T cells (CD8⁺CD45RO⁺Ki67⁺) and the proximity of antigen-experienced cytotoxic T cells to melanoma cells were associated with positive response to ICIs. Our study highlights the potential of multiplexed single-cell technology to quantify spatial cell-cell interactions within the tumor microenvironment to understand immune therapy responses.

Application of High-Throughput Imaging Mass Cytometry Hyperion in Cancer Research

Imaging mass cytometry (IMC) enables the in situ analysis of in-depth-phenotyped cells in their native microenvironment within the preserved architecture of a single tissue section. To date, it permits the simultaneous analysis of up to 50 different protein- markers targeted by metal-conjugated antibodies. The application of IMC in the field of cancer research may notably help 1) to define biomarkers of prognostic and theragnostic significance for current and future treatments against well-established and novel therapeutic targets and 2) to improve our understanding of cancer progression and its resistance mechanisms to immune system and how to overcome them. In the present article, we not only provide a literature review on the use of the IMC in cancer-dedicated studies but we also present the IMC method and discuss its advantages and limitations among methods dedicated to deciphering the complexity of cancer tissue.

Spatial-CITE-seq: spatially resolved high-plex protein and whole transcriptome co-mapping

We present spatial-CITE-seq for high-plex protein and whole transcriptome co-mapping, which was firstly demonstrated for profiling 198 proteins and transcriptome in multiple mouse tissue types. It was then applied to human tissues to measure 283 proteins and transcriptome that revealed spatially distinct germinal center reaction in tonsil and early immune activation in skin at the COVID-19 mRNA vaccine injection site. Spatial-CITE-seq may find a range of applications in biomedical research.