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.

Robust single-cell matching and multimodal analysis using shared and distinct features.

The ability to align individual cellular information from multiple experimental sources is fundamental for a systems-level understanding of biological processes. However, currently available tools are mainly designed for single-cell transcriptomics matching and integration, and generally rely on a large number of shared features across datasets for cell matching. This approach underperforms when applied to single-cell proteomic datasets due to the limited number of parameters simultaneously accessed and lack of shared markers across these experiments. Here, we introduce a cell-matching algorithm, matching with partial overlap (MARIO) that accounts for both shared and distinct features, while consisting of vital filtering steps to avoid suboptimal matching. MARIO accurately matches and integrates data from different single-cell proteomic and multimodal methods, including spatial techniques and has cross-species capabilities. MARIO robustly matched tissue macrophages identified from COVID-19 lung autopsies via codetection by indexing imaging to macrophages recovered from COVID-19 bronchoalveolar lavage fluid by cellular indexing of transcriptomes and epitopes by sequencing, revealing unique immune responses within the lung microenvironment of patients with COVID.

Highly multiplexed tissue imaging using repeated oligonucleotide exchange reaction.

Multiparameter tissue imaging enables analysis of cell-cell interactions in situ, the cellular basis for tissue structure, and novel cell types that are spatially restricted, giving clues to biological mechanisms behind tissue homeostasis and disease. Here, we streamlined and simplified the multiplexed imaging method CO-Detection by indEXing (CODEX) by validating 58 unique oligonucleotide barcodes that can be conjugated to antibodies. We showed that barcoded antibodies retained their specificity for staining cognate targets in human tissue. Antibodies were visualized one at a time by adding a fluorescently labeled oligonucleotide complementary to oligonucleotide barcode, imaging, stripping, and repeating this cycle. With this we developed a panel of 46 antibodies that was used to stain five human lymphoid tissues: three tonsils, a spleen, and a LN. To analyze the data produced, an image processing and analysis pipeline was developed that enabled single-cell analysis on the data, including unsupervised clustering, that revealed 31 cell types across all tissues. We compared cell-type compositions within and directly surrounding follicles from the different lymphoid organs and evaluated cell-cell density correlations. This sequential oligonucleotide exchange technique enables a facile imaging of tissues that leverages pre-existing imaging infrastructure to decrease the barriers to broad use of multiplexed imaging.

The Effect of Ethanol Consumption on Composition and Morphology of Femur Cortical Bone in Wild-Type and ALDH2*2-Homozygous Mice.

ALDH2 inactivating mutation (ALDH2*2) is the most abundant mutation leading to bone morphological aberration. Osteoporosis has long been associated with changes in bone biomaterial in elderly populations. Such changes can be exacerbated with elevated ethanol consumption and in subjects with impaired ethanol metabolism, such as carriers of aldehyde dehydrogenase 2 (ALDH2)-deficient gene, ALDH2*2. So far, little is known about bone compositional changes besides a decrease in mineralization. Raman spectroscopic imaging has been utilized to study the changes in overall composition of C57BL/6 female femur bone sections, as well as in compound spatial distribution. Raman maps of bone sections were analyzed using multilinear regression with these four isolated components, resulting in maps of their relative distribution. A 15-week treatment of both wild-type (WT) and ALDH2*2/*2 mice with 20% ethanol in the drinking water resulted in a significantly lower mineral content (p < 0.05) in the bones. There was no significant change in mineral and collagen content due to the mutation alone (p > 0.4). Highly localized islets of elongated adipose tissue were observed on most maps. Elevated fat content was found in ALDH2*2 knock-in mice consuming ethanol (p < 0.0001) and this effect appeared cumulative. This work conclusively demonstrates that that osteocytes in femurs of older female mice accumulate fat, as has been previously theorized, and that fat accumulation is likely modulated by levels of acetaldehyde, the ethanol metabolite.

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions.

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts' opinion on the development and application of multiomic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, and prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular, and functional aberrations within the lesion and within individual cells. Single-cell proteomic data will be essential for the establishment of new tools with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included (i) The best way/s to analyze single-cells from fresh and preserved tissue; (ii) Detection and analysis of secreted molecules and from single cells, especially from a tissue slice; (iii) Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment; (iv) Multiomic integration of data to support and inform proteomic measurements; (v) Subcellular organelles-identifying abnormal structure, function, distribution, and location within individual premalignant and malignant cells; (vi) How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post-translational modifications (PTM); (vii) The depth of coverage measured concurrently using single-cell techniques; (viii) Quantitation - absolute or semiquantitative? (ix) Single methodology or multiplexed combinations? (x) Application of analytical methods for identification of biologically significant subsets; (xi) Data visualization of N-dimensional data sets; (xii) How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME); (xiii) Associations between intrinsic cellular processes and extrinsic stimuli; (xiv) How to predict cellular responses to stress-inducing stimuli; (xv) Identification of new markers for prediction of progression from precursor, benign, and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells; (xvi) Identification of new targets for immunoprevention or immunotherapy-identification of neoantigens and surfactome of individual cells within a lesion.

Unipotent Megakaryopoietic Pathway Bridging Hematopoietic Stem Cells and Mature Megakaryocytes.

Recent identification of platelet/megakaryocyte-biased hematopoietic stem/repopulating cells requires revision of the intermediate pathway for megakaryopoiesis. Here, we show a unipotent megakaryopoietic pathway bypassing the bipotent megakaryocyte/erythroid progenitors (biEMPs). Cells purified from mouse bone marrow by CD42b (GPIbα) marking were demonstrated to be unipotent megakaryocytic progenitors (MKPs) by culture and transplantation. A subpopulation of freshly isolated CD41(+) cells in the lineage Sca1(+) cKit(+) (LSK) fraction (subCD41(+) LSK) differentiated only into MKP and mature megakaryocytes in culture. Although CD41(+) LSK cells as a whole were capable of differentiating into all myeloid and lymphoid cells in vivo, they produced unipotent MKP, mature megakaryocytes, and platelets in vitro and in vivo much more efficiently than Flt3(+) CD41(-) LSK cells, especially at the early phase after transplantation. In single cell polymerase chain reaction and thrombopoietin (TPO) signaling analyses, the MKP and a fraction of CD41(+) LSK, but not the biEMP, showed the similarities in mRNA expression profile and visible TPO-mediated phosphorylation. On increased demand of platelet production after 5-FU treatment, a part of CD41(+) LSK population expressed CD42b on the surface, and 90% of them showed unipotent megakaryopoietic capacity in single cell culture and predominantly produced platelets in vivo at the early phase after transplantation. These results suggest that the CD41(+) CD42b(+) LSK are straightforward progenies of megakaryocytes/platelet-biased stem/repopulating cells, but not progenies of biEMP. Consequently, we show a unipotent/highly biased megakaryopoietic pathway interconnecting stem/repopulating cells and mature megakaryocytes, the one that may play physiologic roles especially in emergency megakaryopoiesis.

Clusters of temporal discordances reveal distinct embryonic patterning mechanisms in Drosophila and anopheles.

Evolutionary innovations can be driven by spatial and temporal changes in gene expression. Several such differences have been documented in the embryos of lower and higher Diptera. One example is the reduction of the ancient extraembryonic envelope composed of amnion and serosa as seen in mosquitoes to the single amnioserosa of fruit flies. We used transcriptional datasets collected during the embryonic development of the fruit fly, Drosophila melanogaster, and the malaria mosquito, Anopheles gambiae, to search for whole-genome changes in gene expression underlying differences in their respective embryonic morphologies. We found that many orthologous gene pairs could be clustered based on the presence of coincident discordances in their temporal expression profiles. One such cluster contained genes expressed specifically in the mosquito serosa. As shown previously, this cluster is re-deployed later in development at the time of cuticle synthesis. In addition, there is a striking difference in the temporal expression of a subset of maternal genes. Specifically, maternal transcripts that exhibit a sharp reduction at the time of the maternal-zygotic transition in Drosophila display sustained expression in the Anopheles embryo. We propose that gene clustering by local temporal discordance can be used for the de novo identification of the gene batteries underlying morphological diversity.

T cell-mediated curation and restructuring of tumor tissue coordinates an effective immune response.

Antigen-specific T cells traffic to, are influenced by, and create unique cellular microenvironments. Here we characterize these microenvironments over time with multiplexed imaging in a melanoma model of adoptive T cell therapy and human patients with melanoma treated with checkpoint inhibitor therapy. Multicellular neighborhood analysis reveals dynamic immune cell infiltration and inflamed tumor cell neighborhoods associated with CD8+ T cells. T cell-focused analysis indicates T cells are found along a continuum of neighborhoods that reflect the progressive steps coordinating the anti-tumor immune response. More effective anti-tumor immune responses are characterized by inflamed tumor-T cell neighborhoods, flanked by dense immune infiltration neighborhoods. Conversely, ineffective T cell therapies express anti-inflammatory cytokines, resulting in regulatory neighborhoods, spatially disrupting productive T cell-immune and -tumor interactions. Our study provides in situ mechanistic insights into temporal tumor microenvironment changes, cell interactions critical for response, and spatial correlates of immunotherapy outcomes, informing cellular therapy evaluation and engineering.

Novel mutations in the inhibitory adaptor protein LNK drive JAK-STAT signaling in patients with myeloproliferative neoplasms.

Dysregulated Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling due to activation of tyrosine kinases is a common feature of myeloid malignancies. Here we report the first human disease-related mutations in the adaptor protein LNK, a negative regulator of JAK-STAT signaling, in 2 patients with JAK2 V617F-negative myeloproliferative neoplasms (MPNs). One patient exhibited a 5 base-pair deletion and missense mutation leading to a premature stop codon and loss of the pleckstrin homology (PH) and Src homology 2 (SH2) domains. A second patient had a missense mutation (E208Q) in the PH domain. BaF3-MPL cells transduced with these LNK mutants displayed augmented and sustained thrombopoietin-dependent growth and signaling. Primary samples from MPN patients bearing LNK mutations exhibited aberrant JAK-STAT activation, and cytokine-responsive CD34(+) early progenitors were abnormally abundant in both patients. These findings indicate that JAK-STAT activation due to loss of LNK negative feedback regulation is a novel mechanism of MPN pathogenesis.

Conservation of enhancer location in divergent insects.

Dorsoventral (DV) patterning of the Drosophila embryo is controlled by a concentration gradient of Dorsal, a sequence-specific transcription factor related to mammalian NF-kappaB. The Dorsal gradient generates at least 3 distinct thresholds of gene activity and tissue specification by the differential regulation of target enhancers containing distinctive combinations of binding sites for Dorsal, Twist, Snail, and other DV determinants. To understand the evolution of DV patterning mechanisms, we identified and characterized Dorsal target enhancers from the mosquito Anopheles gambiae and the flour beetle Tribolium castaneum. Putative orthologous enhancers are located in similar positions relative to the target genes they control, even though they lack sequence conservation and sometimes produce divergent patterns of gene expression. The most dramatic example of this conservation is seen for the "shadow" enhancer regulating brinker: It is conserved within the intron of the neighboring Atg5 locus of both flies and mosquitoes. These results suggest that, like exons, an enhancer position might be subject to constraint. Thus, novel patterns of gene expression might arise from the modification of conserved enhancers rather than the invention of new ones. We propose that this enhancer constancy might be a general property of regulatory evolution, and should facilitate enhancer discovery in nonmodel organisms.

A community-based approach to image analysis of cells, tissues and tumors.

Emerging multiplexed imaging platforms provide an unprecedented view of an increasing number of molecular markers at subcellular resolution and the dynamic evolution of tumor cellular composition. As such, they are capable of elucidating cell-to-cell interactions within the tumor microenvironment that impact clinical outcome and therapeutic response. However, the rapid development of these platforms has far outpaced the computational methods for processing and analyzing the data they generate. While being technologically disparate, all imaging assays share many computational requirements for post-collection data processing. As such, our Image Analysis Working Group (IAWG), composed of researchers in the Cancer Systems Biology Consortium (CSBC) and the Physical Sciences - Oncology Network (PS-ON), convened a workshop on "Computational Challenges Shared by Diverse Imaging Platforms" to characterize these common issues and a follow-up hackathon to implement solutions for a selected subset of them. Here, we delineate these areas that reflect major axes of research within the field, including image registration, segmentation of cells and subcellular structures, and identification of cell types from their morphology. We further describe the logistical organization of these events, believing our lessons learned can aid others in uniting the imaging community around self-identified topics of mutual interest, in designing and implementing operational procedures to address those topics and in mitigating issues inherent in image analysis (e.g., sharing exemplar images of large datasets and disseminating baseline solutions to hackathon challenges through open-source code repositories).

A real-time GPU-accelerated parallelized image processor for large-scale multiplexed fluorescence microscopy data.

Highly multiplexed, single-cell imaging has revolutionized our understanding of spatial cellular interactions associated with health and disease. With ever-increasing numbers of antigens, region sizes, and sample sizes, multiplexed fluorescence imaging experiments routinely produce terabytes of data. Fast and accurate processing of these large-scale, high-dimensional imaging data is essential to ensure reliable segmentation and identification of cell types and for characterization of cellular neighborhoods and inference of mechanistic insights. Here, we describe RAPID, a Real-time, GPU-Accelerated Parallelized Image processing software for large-scale multiplexed fluorescence microscopy Data. RAPID deconvolves large-scale, high-dimensional fluorescence imaging data, stitches and registers images with axial and lateral drift correction, and minimizes tissue autofluorescence such as that introduced by erythrocytes. Incorporation of an open source CUDA-driven, GPU-assisted deconvolution produced results similar to fee-based commercial software. RAPID reduces data processing time and artifacts and improves image contrast and signal-to-noise compared to our previous image processing pipeline, thus providing a useful tool for accurate and robust analysis of large-scale, multiplexed, fluorescence imaging data.

Organization of developmental enhancers in the Drosophila embryo.

Most cell-specific enhancers are thought to lack an inherent organization, with critical binding sites distributed in a more or less random fashion. However, there are examples of fixed arrangements of binding sites, such as helical phasing, that promote the formation of higher-order protein complexes on the enhancer DNA template. Here, we investigate the regulatory 'grammar' of nearly 100 characterized enhancers for developmental control genes active in the early Drosophila embryo. The conservation of grammar is examined in seven divergent Drosophila genomes. Linked binding sites are observed for particular combinations of binding motifs, including Bicoid-Bicoid, Hunchback-Hunchback, Bicoid-Dorsal, Bicoid-Caudal and Dorsal-Twist. Direct evidence is presented for the importance of Bicoid-Dorsal linkage in the integration of the anterior-posterior and dorsal-ventral patterning systems. Hunchback-Hunchback interactions help explain unresolved aspects of segmentation, including the differential regulation of the eve stripe 3 + 7 and stripe 4 + 6 enhancers. We also present evidence that there is an under-representation of nucleosome positioning sequences in many enhancers, raising the possibility for a subtle higher-order structure extending across certain enhancers. We conclude that grammar of gene control regions is pervasively used in the patterning of the Drosophila embryo.

Strategies for Accurate Cell Type Identification in CODEX Multiplexed Imaging Data.

Multiplexed imaging is a recently developed and powerful single-cell biology research tool. However, it presents new sources of technical noise that are distinct from other types of single-cell data, necessitating new practices for single-cell multiplexed imaging processing and analysis, particularly regarding cell-type identification. Here we created single-cell multiplexed imaging datasets by performing CODEX on four sections of the human colon (ascending, transverse, descending, and sigmoid) using a panel of 47 oligonucleotide-barcoded antibodies. After cell segmentation, we implemented five different normalization techniques crossed with four unsupervised clustering algorithms, resulting in 20 unique cell-type annotations for the same dataset. We generated two standard annotations: hand-gated cell types and cell types produced by over-clustering with spatial verification. We then compared these annotations at four levels of cell-type granularity. First, increasing cell-type granularity led to decreased labeling accuracy; therefore, subtle phenotype annotations should be avoided at the clustering step. Second, accuracy in cell-type identification varied more with normalization choice than with clustering algorithm. Third, unsupervised clustering better accounted for segmentation noise during cell-type annotation than hand-gating. Fourth, Z-score normalization was generally effective in mitigating the effects of noise from single-cell multiplexed imaging. Variation in cell-type identification will lead to significant differential spatial results such as cellular neighborhood analysis; consequently, we also make recommendations for accurately assigning cell-type labels to CODEX multiplexed imaging.

CODEX multiplexed tissue imaging with DNA-conjugated antibodies.

Advances in multiplexed imaging technologies have drastically improved our ability to characterize healthy and diseased tissues at the single-cell level. Co-detection by indexing (CODEX) relies on DNA-conjugated antibodies and the cyclic addition and removal of complementary fluorescently labeled DNA probes and has been used so far to simultaneously visualize up to 60 markers in situ. CODEX enables a deep view into the single-cell spatial relationships in tissues and is intended to spur discovery in developmental biology, disease and therapeutic design. Herein, we provide optimized protocols for conjugating purified antibodies to DNA oligonucleotides, validating the conjugation by CODEX staining and executing the CODEX multicycle imaging procedure for both formalin-fixed, paraffin-embedded (FFPE) and fresh-frozen tissues. In addition, we describe basic image processing and data analysis procedures. We apply this approach to an FFPE human tonsil multicycle experiment. The hands-on experimental time for antibody conjugation is ~4.5 h, validation of DNA-conjugated antibodies with CODEX staining takes ~6.5 h and preparation for a CODEX multicycle experiment takes ~8 h. The multicycle imaging and data analysis time depends on the tissue size, number of markers in the panel and computational complexity.

SARS-CoV-2 infects human pancreatic ß cells and elicits ß cell impairment.

Emerging evidence points toward an intricate relationship between the pandemic of coronavirus disease 2019 (COVID-19) and diabetes. While preexisting diabetes is associated with severe COVID-19, it is unclear whether COVID-19 severity is a cause or consequence of diabetes. To mechanistically link COVID-19 to diabetes, we tested whether insulin-producing pancreatic ß cells can be infected by SARS-CoV-2 and cause ß cell depletion. We found that the SARS-CoV-2 receptor, ACE2, and related entry factors (TMPRSS2, NRP1, and TRFC) are expressed in ß cells, with selectively high expression of NRP1. We discovered that SARS-CoV-2 infects human pancreatic ß cells in patients who succumbed to COVID-19 and selectively infects human islet ß cells in vitro. We demonstrated that SARS-CoV-2 infection attenuates pancreatic insulin levels and secretion and induces ß cell apoptosis, each rescued by NRP1 inhibition. Phosphoproteomic pathway analysis of infected islets indicates apoptotic ß cell signaling, similar to that observed in type 1 diabetes (T1D). In summary, our study shows SARS-CoV-2 can directly induce ß cell killing.

Immune cell topography predicts response to PD-1 blockade in cutaneous T cell lymphoma.

Cutaneous T cell lymphomas (CTCL) are rare but aggressive cancers without effective treatments. While a subset of patients derive benefit from PD-1 blockade, there is a critically unmet need for predictive biomarkers of response. Herein, we perform CODEX multiplexed tissue imaging and RNA sequencing on 70 tumor regions from 14 advanced CTCL patients enrolled in a pembrolizumab clinical trial (NCT02243579). We find no differences in the frequencies of immune or tumor cells between responders and non-responders. Instead, we identify topographical differences between effector PD-1+ CD4+ T cells, tumor cells, and immunosuppressive Tregs, from which we derive a spatial biomarker, termed the SpatialScore, that correlates strongly with pembrolizumab response in CTCL. The SpatialScore coincides with differences in the functional immune state of the tumor microenvironment, T cell function, and tumor cell-specific chemokine recruitment and is validated using a simplified, clinically accessible tissue imaging platform. Collectively, these results provide a paradigm for investigating the spatial balance of effector and suppressive T cell activity and broadly leveraging this biomarker approach to inform the clinical use of immunotherapies.