Temporally multiplexed imaging of dynamic signaling networks in living cells.

Molecular signals interact in networks to mediate biological processes. To analyze these networks, it would be useful to image many signals at once, in the same living cell, using standard microscopes and genetically encoded fluorescent reporters. Here, we report temporally multiplexed imaging (TMI), which uses genetically encoded fluorescent proteins with different clocklike properties-such as reversibly photoswitchable fluorescent proteins with different switching kinetics-to represent different cellular signals. We linearly decompose a brief (few-second-long) trace of the fluorescence fluctuations, at each point in a cell, into a weighted sum of the traces exhibited by each fluorophore expressed in the cell. The weights then represent the signal amplitudes. We use TMI to analyze relationships between different kinase activities in individual cells, as well as between different cell-cycle signals, pointing toward broad utility throughout biology in the analysis of signal transduction cascades in living systems.

Multiplexed 3D atlas of state transitions and immune interaction in colorectal cancer.

Advanced solid cancers are complex assemblies of tumor, immune, and stromal cells characterized by high intratumoral variation. We use highly multiplexed tissue imaging, 3D reconstruction, spatial statistics, and machine learning to identify cell types and states underlying morphological features of known diagnostic and prognostic significance in colorectal cancer. Quantitation of these features in high-plex marker space reveals recurrent transitions from one tumor morphology to the next, some of which are coincident with long-range gradients in the expression of oncogenes and epigenetic regulators. At the tumor invasive margin, where tumor, normal, and immune cells compete, T cell suppression involves multiple cell types and 3D imaging shows that seemingly localized 2D features such as tertiary lymphoid structures are commonly interconnected and have graded molecular properties. Thus, while cancer genetics emphasizes the importance of discrete changes in tumor state, whole-specimen imaging reveals large-scale morphological and molecular gradients analogous to those in developing tissues.

Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front.

Antitumoral immunity requires organized, spatially nuanced interactions between components of the immune tumor microenvironment (iTME). Understanding this coordinated behavior in effective versus ineffective tumor control will advance immunotherapies. We re-engineered co-detection by indexing (CODEX) for paraffin-embedded tissue microarrays, enabling simultaneous profiling of 140 tissue regions from 35 advanced-stage colorectal cancer (CRC) patients with 56 protein markers. We identified nine conserved, distinct cellular neighborhoods (CNs)-a collection of components characteristic of the CRC iTME. Enrichment of PD-1+CD4+ T cells only within a granulocyte CN positively correlated with survival in a high-risk patient subset. Coupling of tumor and immune CNs, fragmentation of T cell and macrophage CNs, and disruption of inter-CN communication was associated with inferior outcomes. This study provides a framework for interrogating how complex biological processes, such as antitumoral immunity, occur through concerted actions of cells and spatial domains.

Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging.

A highly multiplexed cytometric imaging approach, termed co-detection by indexing (CODEX), is used here to create multiplexed datasets of normal and lupus (MRL/lpr) murine spleens. CODEX iteratively visualizes antibody binding events using DNA barcodes, fluorescent dNTP analogs, and an in situ polymerization-based indexing procedure. An algorithmic pipeline for single-cell antigen quantification in tightly packed tissues was developed and used to overlay well-known morphological features with de novo characterization of lymphoid tissue architecture at a single-cell and cellular neighborhood levels. We observed an unexpected, profound impact of the cellular neighborhood on the expression of protein receptors on immune cells. By comparing normal murine spleen to spleens from animals with systemic autoimmune disease (MRL/lpr), extensive and previously uncharacterized splenic cell-interaction dynamics in the healthy versus diseased state was observed. The fidelity of multiplexed spatial cytometry demonstrated here allows for quantitative systemic characterization of tissue architecture in normal and clinically aberrant samples.

Combined protein and nucleic acid imaging reveals virus-dependent B cell and macrophage immunosuppression of tissue microenvironments.

Understanding the mechanisms of HIV tissue persistence necessitates the ability to visualize tissue microenvironments where infected cells reside; however, technological barriers limit our ability to dissect the cellular components of these HIV reservoirs. Here, we developed protein and nucleic acid in situ imaging (PANINI) to simultaneously quantify DNA, RNA, and protein levels within these tissue compartments. By coupling PANINI with multiplexed ion beam imaging (MIBI), we measured over 30 parameters simultaneously across archival lymphoid tissues from healthy or simian immunodeficiency virus (SIV)-infected nonhuman primates. PANINI enabled the spatial dissection of cellular phenotypes, functional markers, and viral events resulting from infection. SIV infection induced IL-10 expression in lymphoid B cells, which correlated with local macrophage M2 polarization. This highlights a potential viral mechanism for conditioning an immunosuppressive tissue environment for virion production. The spatial multimodal framework here can be extended to decipher tissue responses in other infectious diseases and tumor biology.

Loop stacking organizes genome folding from TADs to chromosomes.

Although population-level analyses revealed significant roles for CTCF and cohesin in mammalian genome organization, their contributions at the single-cell level remain incompletely understood. Here, we used a super-resolution microscopy approach to measure the effects of removal of CTCF or cohesin in mouse embryonic stem cells. Single-chromosome traces revealed cohesin-dependent loops, frequently stacked at their loop anchors forming multi-way contacts (hubs), bridging across TAD boundaries. Despite these bridging interactions, chromatin in intervening TADs was not intermixed, remaining separated in distinct loops around the hub. At the multi-TAD scale, steric effects from loop stacking insulated local chromatin from ultra-long range (>4 Mb) contacts. Upon cohesin removal, the chromosomes were more disordered and increased cell-cell variability in gene expression. Our data revise the TAD-centric understanding of CTCF and cohesin and provide a multi-scale, structural picture of how they organize the genome on the single-cell level through distinct contributions to loop stacking.

cytoviewer: an R/Bioconductor package for interactive visualization and exploration of highly multiplexed imaging data.

BACKGROUND: Highly multiplexed imaging enables single-cell-resolved detection of numerous biological molecules in their spatial tissue context. Interactive visualization of multiplexed imaging data is crucial at any step of data analysis to facilitate quality control and the spatial exploration of single cell features. However, tools for interactive visualization of multiplexed imaging data are not available in the statistical programming language R. RESULTS: Here, we describe cytoviewer, an R/Bioconductor package for interactive visualization and exploration of multi-channel images and segmentation masks. The cytoviewer package supports flexible generation of image composites, allows side-by-side visualization of single channels, and facilitates the spatial visualization of single-cell data in the form of segmentation masks. As such, cytoviewer improves image and segmentation quality control, the visualization of cell phenotyping results and qualitative validation of hypothesis at any step of data analysis. The package operates on standard data classes of the Bioconductor project and therefore integrates with an extensive framework for single-cell and image analysis. The graphical user interface allows intuitive navigation and little coding experience is required to use the package. We showcase the functionality and biological application of cytoviewer by analysis of an imaging mass cytometry dataset acquired from cancer samples. CONCLUSIONS: The cytoviewer package offers a rich set of features for highly multiplexed imaging data visualization in R that seamlessly integrates with the workflow for image and single-cell data analysis. It can be installed from Bioconductor via https://www.bioconductor.org/packages/release/bioc/html/cytoviewer.html . The development version and further instructions can be found on GitHub at https://github.com/BodenmillerGroup/cytoviewer .

Multiplexed Imaging Mass Cytometry Analysis in Preclinical Models of Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers. PDAC is characterized by a complex tumor microenvironment (TME), that plays a pivotal role in disease progression and resistance to therapy. Investigating the spatial distribution and interaction of TME cells with the tumor is the basis for understanding the mechanisms underlying disease progression and represents a current challenge in PDAC research. Imaging mass cytometry (IMC) is the major multiplex imaging technology for the spatial analysis of tumor heterogeneity. However, there is a dearth of reports of multiplexed IMC panels for different preclinical mouse models, including pancreatic cancer. We addressed this gap by utilizing two preclinical models of PDAC: the genetically engineered, bearing KRAS-TP53 mutations in pancreatic cells, and the orthotopic, and developed a 28-marker panel for single-cell IMC analysis to assess the abundance, distribution and phenotypes of cells involved in PDAC progression and their reciprocal functional interactions. Herein, we provide an unprecedented definition of the distribution of TME cells in PDAC and compare the diversity between transplanted and genetic disease models. The results obtained represent an important and customizable tool for unraveling the complexities of PDAC and deciphering the mechanisms behind therapy resistance.

Laboratory Liquid-Jet X-ray Microscopy and X-ray Fluorescence Imaging for Biomedical Applications.

Diffraction-limited resolution and low penetration depth are fundamental constraints in optical microscopy and in vivo imaging. Recently, liquid-jet X-ray technology has enabled the generation of X-rays with high-power intensities in laboratory settings. By allowing the observation of cellular processes in their natural state, liquid-jet soft X-ray microscopy (SXM) can provide morphological information on living cells without staining. Furthermore, X-ray fluorescence imaging (XFI) permits the tracking of contrast agents in vivo with high elemental specificity, going beyond attenuation contrast. In this study, we established a methodology to investigate nanoparticle (NP) interactions in vitro and in vivo, solely based on X-ray imaging. We employed soft (0.5 keV) and hard (24 keV) X-rays for cellular studies and preclinical evaluations, respectively. Our results demonstrated the possibility of localizing NPs in the intracellular environment via SXM and evaluating their biodistribution with in vivo multiplexed XFI. We envisage that laboratory liquid-jet X-ray technology will significantly contribute to advancing our understanding of biological systems in the field of nanomedical research.

Molecular architecture of proliferative lupus nephritis as elucidated using 50-plex imaging mass cytometry proteomics.

Due to unique advantages that allow high-dimensional tissue profiling, we postulated imaging mass cytometry (IMC) may shed novel insights on the molecular makeup of proliferative lupus nephritis (LN). This study interrogates the spatial expression profiles of 50 target proteins in LN and control kidneys. Proliferative LN glomeruli are marked by podocyte loss with immune infiltration dominated by CD45RO+, HLA-DR+ memory CD4 and CD8 T-cells, and CD163+ macrophages, with similar changes in tubulointerstitial regions. Macrophages are the predominant HLA-DR expressing antigen presenting cells with little expression elsewhere, while macrophages and T-cells predominate cellular crescents. End-stage sclerotic glomeruli are encircled by an acellular fibro-epithelial Bowman's space surrounded by immune infiltrates, all enmeshed in fibronectin. Proliferative LN also shows signs indicative of epithelial to mesenchymal plasticity of tubular cells and parietal epithelial cells. IMC enabled proteomics is a powerful tool to delineate the spatial architecture of LN at the protein level.

Pooled genetic screens with image-based profiling.

Spatial structure in biology, spanning molecular, organellular, cellular, tissue, and organismal scales, is encoded through a combination of genetic and epigenetic factors in individual cells. Microscopy remains the most direct approach to exploring the intricate spatial complexity defining biological systems and the structured dynamic responses of these systems to perturbations. Genetic screens with deep single-cell profiling via image features or gene expression programs have the capacity to show how biological systems work in detail by cataloging many cellular phenotypes with one experimental assay. Microscopy-based cellular profiling provides information complementary to next-generation sequencing (NGS) profiling and has only recently become compatible with large-scale genetic screens. Optical screening now offers the scale needed for systematic characterization and is poised for further scale-up. We discuss how these methodologies, together with emerging technologies for genetic perturbation and microscopy-based multiplexed molecular phenotyping, are powering new approaches to reveal genotype-phenotype relationships.

Giving Gold Wings: Ultrabright and Fragmentation Free Mass Spectrometry Reporters for Barcoding, Bioconjugation Monitoring, and Data Storage.

The widespread application of laser desorption/ionization mass spectrometry (LDI-MS) highlights the need for a bright and multiplexable labeling platform. While ligand-capped Au nanoparticles (AuNPs) have emerged as a promising LDI-MS contrast agent, the predominant thiol ligands suffer from low ion yields and extensive fragmentation. In this work, we develop a N-heterocyclic carbene (NHC) ligand platform that enhances AuNP LDI-MS performance. NHC scaffolds are tuned to generate barcoded AuNPs which, when benchmarked against thiol-AuNPs, are bright mass tags and form unfragmented ions in high yield. To illustrate the transformative potential of NHC ligands, the mass tags were employed in three orthogonal applications: monitoring a bioconjugation reaction, performing multiplexed imaging, and storing and reading encoded information. These results demonstrate that NHC-nanoparticle systems are an ideal platform for LDI-MS and greatly broaden the scope of nanoparticle contrast agents.

Shortwave Infrared Fluorofluorophores for Multicolor In Vivo Imaging.

Developing chemical tools to detect and influence biological processes is a cornerstone of chemical biology. Here we combine two tools which rely on orthogonality- perfluorocarbons and multiplexed shortwave infrared (SWIR) fluorescence imaging- to visualize nanoemulsions in real time in living mice. Drawing inspiration from fluorous and SWIR fluorophore development, we prepared two SWIR-emissive, fluorous-soluble chromenylium polymethine dyes. These are the most red-shifted fluorous fluorophores- "fluorofluorophores"-to date. After characterizing the dyes, their utility was demonstrated by tracking perfluorocarbon nanoemulsion biodistribution in vivo. Using an excitation-multiplexed approach to image two variables simultaneously, we gained insight into the importance of size and surfactant identity on biodistribution.

An Extended NIR-II Superior Imaging Window from 1500 to 1900†nm for High-Resolution In Vivo Multiplexed Imaging Based on Lanthanide Nanocrystals.

High-resolution in vivo optical multiplexing in second near-infrared window (NIR-II, 1000-1700 nm) is vital to biomedical research. Presently, limited by bio-tissue scattering, only luminescent probes located at NIR-IIb (1500-1700 nm) window can provide high-resolution in vivo multiplexed imaging. However, the number of available luminescent probes in this narrow NIR-IIb region is limited, which hampers the available multiplexed channels of in vivo imaging. To overcome the above challenges, through theoretical simulation we expanded the conventional NIR-IIb window to NIR-II long-wavelength (NIR-II-L, 1500-1900 nm) window on the basis of photon-scattering and water-absorption. We developed a series of novel lanthanide luminescent nanoprobes with emission wavelengths from 1852 nm to 2842 nm. NIR-II-L nanoprobes enabled high-resolution in vivo dynamic multiplexed imaging on blood vessels and intestines, and provided multi-channels imaging on lymph tubes, tumors and intestines. The proposed NIR-II-L probes without mutual interference are powerful tools for high-contrast in vivo multiplexed detection, which holds promise for revealing physiological process in living body.

CellSeg: a robust, pre-trained nucleus segmentation and pixel quantification software for highly multiplexed fluorescence images.

BACKGROUND: Algorithmic cellular segmentation is an essential step for the quantitative analysis of highly multiplexed tissue images. Current segmentation pipelines often require manual dataset annotation and additional training, significant parameter tuning, or a sophisticated understanding of programming to adapt the software to the researcher's need. Here, we present CellSeg, an open-source, pre-trained nucleus segmentation and signal quantification software based on the Mask region-convolutional neural network (R-CNN) architecture. CellSeg is accessible to users with a wide range of programming skills. RESULTS: CellSeg performs at the level of top segmentation algorithms in the 2018 Kaggle Data Challenge both qualitatively and quantitatively and generalizes well to a diverse set of multiplexed imaged cancer tissues compared to established state-of-the-art segmentation algorithms. Automated segmentation post-processing steps in the CellSeg pipeline improve the resolution of immune cell populations for downstream single-cell analysis. Finally, an application of CellSeg to a highly multiplexed colorectal cancer dataset acquired on the CO-Detection by indEXing (CODEX) platform demonstrates that CellSeg can be integrated into a multiplexed tissue imaging pipeline and lead to accurate identification of validated cell populations. CONCLUSION: CellSeg is a robust cell segmentation software for analyzing highly multiplexed tissue images, accessible to biology researchers of any programming skill level.

Highly multiplexed immunofluorescence of the human kidney using co-detection by indexing.

The human kidney is composed of many cell types that vary in their abundance and distribution from normal to diseased organ. As these cell types perform unique and essential functions, it is important to confidently label each within a single tissue to accurately assess tissue architecture and microenvironments. Towards this goal, we demonstrate the use of co-detection by indexing (CODEX) multiplexed immunofluorescence for visualizing 23 antigens within the human kidney. Using CODEX, many of the major cell types and substructures, such as collecting ducts, glomeruli, and thick ascending limb, were visualized within a single tissue section. Of these antibodies, 19 were conjugated in-house, demonstrating the flexibility and utility of this approach for studying the human kidney using custom and commercially available antibodies. We performed a pilot study that compared both fresh frozen and formalin-fixed paraffin-embedded healthy non-neoplastic and diabetic nephropathy kidney tissues. The largest cellular differences between the two groups was observed in cells labeled with aquaporin 1, cytokeratin 7, and α-smooth muscle actin. Thus, our data show the power of CODEX multiplexed immunofluorescence for surveying the cellular diversity of the human kidney and the potential for applications within pathology, histology, and building anatomical atlases.

Exploring single cells in space and time during tissue development, homeostasis and regeneration.

Complex 3D tissues arise during development following tightly organized events in space and time. In particular, gene regulatory networks and local interactions between single cells lead to emergent properties at the tissue and organism levels. To understand the design principles of tissue organization, we need to characterize individual cells at given times, but we also need to consider the collective behavior of multiple cells across different spatial and temporal scales. In recent years, powerful single cell methods have been developed to characterize cells in tissues and to address the challenging questions of how different tissues are formed throughout development, maintained in homeostasis, and repaired after injury and disease. These approaches have led to a massive increase in data pertaining to both mRNA and protein abundances in single cells. As we review here, these new technologies, in combination with in toto live imaging, now allow us to bridge spatial and temporal information quantitatively at the single cell level and generate a mechanistic understanding of tissue development.

MIRIAM: A machine and deep learning single-cell segmentation and quantification pipeline for multi-dimensional tissue images.

Increasingly, highly multiplexed tissue imaging methods are used to profile protein expression at the single-cell level. However, a critical limitation is the lack of robust cell segmentation tools for tissue sections. We present Multiplexed Image Resegmentation of Internal Aberrant Membranes (MIRIAM) that combines (a) a pipeline for cell segmentation and quantification that incorporates machine learning-based pixel classification to define cellular compartments, (b) a novel method for extending incomplete cell membranes, and (c) a deep learning-based cell shape descriptor. Using human colonic adenomas as an example, we show that MIRIAM is superior to widely utilized segmentation methods and provides a pipeline that is broadly applicable to different imaging platforms and tissue types.

Counterion-Paired Bright Heptamethine Fluorophores with NIR-II Excitation and Emission Enable Multiplexed Biomedical Imaging.

Photon excitation and emission at the NIR-II spectral window enable high-contrast deep-tissue bioimaging. However, multiplexed imaging with NIR-II excitation and emission has been hampered by the limited chemical strategies to develop bright fluorophores with tunable absorption in this spectral regime. Herein, we developed a series of heptamethine cyanines (HCs) with varied absorption/emission maxima spanning from 1100 to 1600 nm through a physical organic approach. A bulky counterion paired to HCs was found to elicit substantial improvements in absorptivity (7-fold), brightness (14-fold), and spectral profiles in water, addressing a notorious quenching problem of NIR-II cyanines due to aggregation and polarization. We demonstrated the utilities of HC1222 and HC1342 for high-contrast dual-color imaging of circulatory system, lymphatic structures, tumor, and organ function in living mice under 1120 nm and 1319 nm excitation, showing HCs as a promising platform for non-invasive bioimaging.

A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids.

Cells react to their microenvironment by integrating external stimuli into phenotypic decisions via an intracellular signaling network. To analyze the interplay of environment, local neighborhood, and internal cell state effects on phenotypic variability, we developed an experimental approach that enables multiplexed mass cytometric imaging analysis of up to 240 pooled spheroid microtissues. We quantified the contributions of environment, neighborhood, and intracellular state to marker variability in single cells of the spheroids. A linear model explained on average more than half of the variability of 34 markers across four cell lines and six growth conditions. The contributions of cell-intrinsic and environmental factors to marker variability are hierarchically interdependent, a finding that we propose has general implications for systems-level studies of single-cell phenotypic variability. By the overexpression of 51 signaling protein constructs in subsets of cells, we also identified proteins that have cell-intrinsic and cell-extrinsic effects. Our study deconvolves factors influencing cellular phenotype in a 3D tissue and provides a scalable experimental system, analytical principles, and rich multiplexed imaging datasets for future studies.