SPAtial Cell Exploration ( SPACE ) is a novel subcellular imaging-based method that couples large-scale perturbations with whole transcriptome single-cell multi-omics readout, while preserving spatial context, providing unprecedented insights into tissue organization and microenvironmental interactions at very low cost. As a demonstration, we performed SPACE in hundreds of spheroids and discovered novel biology related to CAF-tumor interactions using unbiased approaches. This scalable, cost-effective technology has broad applications in translational research and drug discovery, offering a transformative approach to high-throughput spatial perturbation studies. ### Competing Interest Statement The following authors participated in this study as employees of Merck & Co., Inc, USA: Mengwei Hu, Qianhui Huang, Khoi Chu, Sharanya Iyengar, Maerjianghan Abuduli, Marianne Spatz, Nandita Joshi, Brendan Miller, Shams Vellarikkal, Iya Khalil, Federica Piccioni, Alex Tamburino, Vanessa Peterson The following authors participated in this study as employees of Bruker Spatial Biology, USA: Yi Cui, Sierra McKinzie, Michael Patrick, Timothy Riordan, Michael Rhodes, Shanshan He, Joseph Beechem The following authors participated in this study as employees of MSD, Czech Republic: Danny Bitton, Jan Lubojacky

Using the world’s first transcriptome-scale spatial imaging of a breast tumor, we assessed what could be learned about one patient’s disease. We cataloged heterogeneity across 3 morphological regions, 9 spatial domains, 37 cell types, and 1692 pathways. Then, employing a new algorithm for spatially stratified differential expression, we tested > 2 million hypotheses about cell types’ behavior across space. We measured how CD8+ T cells change upon entering the tumor, how cancer cells adapt to nutrient-poor microenvironments, how tumor glycolysis impacts nearby healthy cells, and how low-proliferation zones of the tumor are distinct. We found several instances of druggable biology: tumor heterogeneity and invasion programs suggested aggressiveness independent of traditional grading; PDCD1 expression and exhaustion limited T-cell activity; cancer cells exhibited angiogenic signaling but showed reduced proliferation in hypoxic regions; and a malignant subcluster up-regulated lipid metabolism. These findings demonstrate the insights obtainable through spatial profiling of individual tumors.

Analyses of patient-derived cell lines have greatly enhanced discovery of molecular biomarkers and therapeutic targets. However, characterization of cellular morphological properties is limited. We studied cell morphologies of human pancreatic adenocarcinoma (PDAC) cell lines and their associations with drug sensitivity, gene expression, and functional properties. By integrating live cell and spatial messenger RNA imaging, we identified KRAS inhibitor-induced morphological changes specific for drug-resistant cells that correlated with gene expression changes. We then categorized a large panel of patient-derived PDAC cell lines into morphological and organizational subtypes and found differences in gene expression, therapeutic targeting potential, and metastatic proclivity. Patterns of cancer cell organization in human PDAC tissues stratified distinct gene expression signatures with clinical significance. In summary, we highlight the potential of cell morphological information in rapid, cost-effective assays to aid precision oncology efforts leveraging patient-derived in vitro models and tissues.

Current spatial CRISPR screening technologies are limited by targeted readouts and high costs, restricting the scope of biological discovery. Here we present SPAtial Cell Exploration (SPACE), a spatial CRISPR screening platform that integrates whole-transcriptome profiling (~18,000 genes), multiplexed protein detection (~68 markers), and CRISPR perturbation mapping at subcellular resolution. SPACE significantly reduces whole-transcriptome profiling costs compared to sequencing methods while preserving spatial context. We demonstrate SPACE by screening 43 CRISPR knockouts (KOs) across ~100,000 cells in hundreds of cancer-associated fibroblast (CAF)-tumor spheroids, obtaining whole-transcriptome and multiplexed protein readout from the same exact cells. SPACE revealed previously unknown regulatory mechanisms on tumor extracellular matrix (ECM) remodeling, and identified spatially-resolved ligand-receptor interactions and perturbation-specific spatial gene signatures that are not detectable with dissociation-based methods. This scalable, cost-effective platform provides a transformative framework for high-throughput spatial perturbation studies in complex tissue models.

Although metastatic disease is the leading cause of cancer-related deaths, its tumor microenvironment remains poorly characterized due to technical and biospecimen limitations. In this study, we assembled a multi-modal spatial and cellular map of 67 tumor biopsies from 60 patients with metastatic breast cancer across diverse clinicopathological features and nine anatomic sites with detailed clinical annotations. We combined single-cell or single-nucleus RNA sequencing for all biopsies with a panel of four spatial expression assays (Slide-seq, MERFISH, ExSeq and CODEX) and H&E staining of consecutive serial sections from up to 15 of these biopsies. We leveraged the coupled measurements to provide reference points for the utility and integration of different experimental techniques and used them to assess variability in cell type composition and expression as well as emerging spatial expression characteristics across clinicopathological and methodological diversity. Finally, we assessed spatial expression and co-localization features of macrophage populations, characterized three distinct spatial phenotypes of epithelial-to-mesenchymal transition and identified expression programs associated with local T cell infiltration versus exclusion, showcasing the potential of clinically relevant discovery in such maps. Single-nucleus and single-cell RNA sequencing plus spatial profiling with four methods of core biopsies from 60 patients with metastatic breast cancer reveal patient-specific gene expression programs of breast cancer metastases that are maintained across time, site of metastasis and spatial profiling method, with spatial phenotypes correlating with microenvironmental features.

SummaryLipids have been implicated as mediators of insulitis and β-cell death in type 1 diabetes development, but the mechanisms underlying this association are poorly understood. Here, we investigated the changes in islet/β-cell lipid composition using three models of insulitis: human islets and EndoC-βH1 β-cells treated with the cytokines IL-1β and IFN-γ, and islets from non-obese diabetic mice. Across all three models, lipidomic analyses showed a consistent change in abundance of the lysophosphatidylcholine, phosphatidylcholine and triacylglycerol species. We also showed that lysophosphatidylcholine and its biosynthetic enzyme PLA2G6 are enriched in murine islets. We determined that the ADP-ribosyl-acceptor glycohydrolase ARH3 is regulated by cytokines downstream of PLA2G6, which in turn regulates proteins involved in apoptosis, lipid metabolism, antigen processing and presentation and chemokines. ARH3 reduced cytokine-induced apoptosis, which may represent a negative feedback mechanism. Overall, these data show the importance of lipid metabolism in regulating β-cell death in type 1 diabetes.HighlightsLipidomics of 3 insulitis models revealed commonly regulated lipid classes.Identification of 35 proteins regulated by cytokines via PLA2G6 signaling.ARH3 reduces cytokine-induced apoptosis via PLA2G6 regulation.ARH3 regulates the levels of proteins related to insulitis and type 1 diabetes.

Single-cell RNA-seq revolutionized single-cell biology, by providing a complete whole transcriptome view of individual cells. Regrettably, this was accomplished only for individual, tissue-dissociated cells. High-plex spatial biology has begun to recover the x, y, and z-coordinates of single-cells, but typically at the expense of far less than whole transcriptome coverage. To solve this problem, Bruker Spatial Biology has accomplished a commercial-grade panel (CosMx® Spatial Molecular Imager Whole Transcriptome Panel (WTx)), using 37,872 imaging barcodes, capable of sub-cellular imaging of the entire human protein-coding transcriptome. The imaging barcodes are encoded with 156 bits of information (4 on-cycles and 35 dark-cycles per code), at a Hamming Distance of 4 from each other to achieve a very low false-code detection. Key to achieving this high-plex capability was the ability to manufacture imaging barcodes that require no in-tissue amplification (every barcode is manufactured under GMP to contain exactly 30 fluorescent dyes) and uniform, size-exclusion purified, extremely small imaging barcodes (~ 20 nm). A detailed study of six different human FFPE tissue types was performed (Colon, Pancreas, Hippocampus, Skin, Breast, Kidney), yielding over 5.4 billion transcripts from 2.7 million cells. We counted over 1,550 transcripts-per-cell on average and observed 900 unique genes per cell (measured as the median). Single fixed-cells containing well over 10,000 subcellularly imaged transcripts were accomplished. Advancing single-cell imaging to the whole transcriptome level opens a single unified approach to accomplish essentially all single-cell experiments, both imaging and non-imaging. Depending upon the sample type (e.g. fixed-cells, organoids, tissue sections, etc.), the transcripts per cell and genes per cell measured using the whole transcriptome panel often exceeds that obtained by the highest-resolution single-cell RNA-seq, can be performed on a single 5 μm FFPE tissue section, with no dissociation bias (every cell is counted). Pathway analysis within the tumor bed of a colon adenocarcinoma sample found evidence of enrichment in pathways suggestive of an aggressive tumor type, and localized ligand-receptor analysis showed spatially restricted patterns related to adhesion, migration, and proliferation. The high-dimensional whole transcriptome data is streamed directly to a cloud-based Spatial Informatics Platform, allowing for the scalable processing of millions-of-single-cells and billions-of-transcripts per operation. The WTx data are combined with high-resolution antibody-based cell-morphology imaging and data-driven machine-learning cell segmentation algorithms, to generate the most complete view of single cell and sub-cellular spatial biology that has ever been obtained. ### Competing Interest Statement All authors are employees Bruker Spatial Biology

ABSTRACT Aim/hypothesis Growth/differentiation factor 15 (GDF15) is a therapeutic target for a variety of metabolic diseases, including type 1 diabetes (T1D). However, the nausea caused by GDF15 is a challenging point for therapeutic development. In addition, it is unknown why the endogenous GDF15 fails to protect from T1D development. Here, we investigate the GDF15 signaling in pancreatic islets towards opening possibilities for therapeutic targeting in β cells and to understand why this protection fails to occur naturally. Methods GDF15 signaling in islets was determined by proximity-ligation assay, untargeted proteomics, pathway analysis, and treatment of cells with specific inhibitors. To determine if GDF15 levels would increase prior to disease onset, plasma levels of GDF15 were measured in a longitudinal prospective study of children during T1D development (n=132 cases vs. n=40 controls) and in children with islet autoimmunity but normoglycemia (n=47 cases vs. n=40 controls) using targeted mass spectrometry. We also investigated the regulation of GDF15 production in islets by fluorescence microscopy and western blot analysis. Results The proximity-ligation assay identified ERBB2 as the GDF15 receptor in islets, which was confirmed using its specific antagonist, tucatinib. The untargeted proteomics analysis and caspase assay showed that ERBB2 activation by GDF15 reduces β cell apoptosis by downregulating caspase 8. In plasma, GDF15 levels were higher (p=0.0024) during T1D development compared to controls, but not in islet autoimmunity with normoglycemia. However, in the pancreatic islets GDF15 was depleted via sequestration of its mRNA into stress granules, resulting in translation halting. Conclusions/interpretation GDF15 protects against T1D via ERBB2-mediated decrease of caspase 8 expression in pancreatic islets. Circulating levels of GDF15 increases pre-T1D onset, which is insufficient to promote protection due to its localized depletion in the islets. These findings open opportunities for targeting GDF15 downstream signaling for pancreatic β cell protection in T1D and help to explain the lack of natural protection by the endogenous protein.

Expansion microscopy (ExM), by physically enlarging specimens in an isotropic fashion, enables nanoimaging on standard light microscopes. Key to existing ExM protocols is the equipping of different kinds of molecules, with different kinds of anchoring moieties, so they can all be pulled apart from each other by polymer swelling. Here we present a multifunctional anchor, an acrylate epoxide, that enables proteins and RNAs to be equipped with anchors in a single experimental step. This reagent simplifies ExM protocols and reduces cost (by 2-10-fold for a typical multiplexed ExM experiment) compared to previous strategies for equipping RNAs with anchors. We show that this united ExM (uniExM) protocol can be used to preserve and visualize RNA transcripts, proteins in biologically relevant ultrastructures, and sets of RNA transcripts in patient-derived xenograft (PDX) cancer tissues and may support the visualization of other kinds of biomolecular species as well. uniExM may find many uses in the simple, multimodal nanoscale analysis of cells and tissues.

Metastatic breast cancer (MBC) remains incurable due to inevitable development of therapeutic resistance. Although tumor cell intrinsic mechanisms of resistance in MBC are beginning to be elucidated by bulk sequencing studies, the roles of the tumor microenvironment and intratumor heterogeneity in therapeutic resistance remain underexplored due to both technological barriers and limited availability of samples. To comprehensively capture these characteristics we have adapted a research biopsy protocol to collect tissue for an array of single-cell and spatio-molecular assays whose performance we have optimized for MBC, including single-cell and single-nucleus RNA sequencing, Slide-Seq, Multiplexed Error-Robust FISH (MERFISH), Expansion Sequencing (ExSEQ), Co-detection by Indexing (CODEX) and Multiplexed Ion Beam Imaging (MIBI). To date, we have successfully performed single-cell or single-nucleus RNAseq in 67 MBC biopsies and generated detailed accompanying clinical annotations for each. These samples provide a representation of the clinicopathological diversity of MBC including different breast cancer subtypes (44 HR+/HER2-, 3 HR-/HER2+, 3 HR+/HER2+, 16 TNBC, 1 unknown), common anatomic sites of metastasis (37 liver, 9 axilla, 7 breast, 5 bone, 3 chest wall, 3 neck, 1 brain, 1 lung, 1 skin), metastatic presentations (53 recurrent, 14 de novo) and histologic subtypes in the breast (45 IDC, 7 ILC, 6 mixed, 3 DCIS, 1 mucinous, 5 unknown/NA). Following optimization, both single-cell and single-nucleus RNA seq perform well in these MBC biopsies recovering all expected cell types including the malignant, stromal (e.g. fibroblasts, endothelial cells), myeloid (e.g. monocytes, macrophages) and lymphoid compartments (e.g. T cells, B cells, NK cells) as well as relevant oncogenic programs (e.g. cell cycle programs in all compartments; EMT-like and ER signaling programs in the malignant compartment, immune checkpoint programs in the lymphoid compartment; and fibroblast activation and vascular homeostasis programs in the stromal compartment). In addition to differences between the two techniques, these data demonstrate substantial intratumor heterogeneity in cell type composition. For example in liver biopsies the average number of cells per sample compartment by single nucleus RNA-seq was 6745 malignant (56%, SD 4216), 4637 stromal (41%, SD 3727), 1196 lymphoid (8%, SD 1617) and 874 myeloid (6%, SD 852); in breast biopsies the average number of cells per compartment by single nucleus RNA-seq was 6421 malignant (70%, SD 3497), 1628 stromal (24%, SD 117), 333 lymphoid (4%, SD 170) and 213 myeloid (3%, SD 117). Additionally, we find both inter- and intra-tumor heterogeneity in expression patterns and programs including, for example, expression of ER, PR and HER2 within clinical receptor subtypes (log normalized counts for ER expression in tumor cells by single cell RNA-seq: HR+/HER2- 0.921 (SD 0.714); HR+/HER2+ 0.768 (SD 0.624); HR-/HER2+ 0.018 (SD 0.122); and HR-/HER2- 0.005 (SD 0.066). For a subset of 13 biopsies we are also completing the spatiomolecular characterization methods on serial sections of a single adjacent biopsy. This unique experimental setup was designed to enable efficient comparison and integration of these assays. In spite of differences between experimental techniques and readouts, cell typing can be approached by annotation transfer from matching single cell or single nucleus RNAseq data, enabling exploratory analyses including evaluation of spatial phenotypes and cell type colocalization. Overall, these single cell and spatial data afford a comprehensive atlas including cell types, cell states/programs, cell interactions and spatial organization in MBC lesions. Future analyses will include serial biopsies over time and integration of clinicopathologic data including therapeutic response and resistance. Citation Format: Daniel L Abravanel, Johanna Klughammer, Timothy Blosser, Yury Goltsev, Sizun Jiang, Yunjao Bai, Evan Murray, Shahar Alon, Yi Cui, Daniel R Goodwin, Anubhav Sinha, Ofir Cohen, Michal Slyper, Orr Ashenberg, Danielle Dionne, Judit Jané-Valbuena, Caroline BM Porter, Asa Segerstolpe, Julia Waldman, Sébastien Vigneau, Karla Helvie, Allison Frangieh, Laura DelloStritto, Miraj Patel, Jingyi We, Kathleen Pfaff, Nicole Cullen, Ana Lako, Madison Turner, Isaac Wakiro, Sara Napolitano, Abhay Kanodia, Rebecca Ortiz, Colin MacKichan, Stephanie Inga, Judy Chen, Aaron R Thorner, Asaf Rotem, Scott Rodig, Fei Chen, Edward S Boyden, Garry P Nolan, Xiaowei Zhuang, Orit Rozenblatt-Rosen, Bruce E Johnson, Aviv Regev, Nikhil Wagle. Spatio-molecular dissection of the breast cancer metastatic microenvironment [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD6-03.

In situ imaging of biomolecular location with nanoscale resolution enables mapping of the building blocks of life throughout biological systems in normal and disease states. Expansion microscopy (ExM), by physically enlarging specimens in an isotropic fashion, enables nanoimaging on standard light microscopes. Key to ExM is the equipping of different kinds of molecule, with different kinds of anchoring moiety, so they can all be pulled apart by polymer swelling. Here we present a multifunctional anchor, an acrylate epoxide, that enables multiple kinds of molecules ( e.g., proteins and RNAs) to be equipped with anchors in a single experimental step. This reagent simplifies ExM protocols and greatly reduces cost (by 2-10 fold for a typical multiplexed ExM experiment) compared to previous strategies for equipping RNAs with anchors. We show that this unified ExM (uniExM) protocol can be used to preserve and visualize RNA transcripts, proteins in biologically relevant ultrastructure, and sets of RNA transcripts in patient-derived xenograft (PDX) cancer tissues, and can support the visualization of other kinds of biomolecular species as well. Thus, uniExM may find many uses in the simple, multimodal nanoscale analysis of cells and tissues.

Surface properties of engineered nanomaterials (ENMs) have been shown to influence their interaction with biological systems. However, studies to date have largely focused on hydrophilic materials, likely due to biocompatibility concerns and aqueous exposure conditions necessary for many model systems. Therefore, a knowledge gap exists in nanotoxicity literature for impacts of hydrophobic ENMs, with studies of hydrophobic materials largely limited to carbon ENMs. Here we demonstrate testing of hydrophobic quantum dots (QDs) using the nematode C. elegans, a model soil organism cultured on solid media and amenable to hydrophobic exposures. To evaluate the influence of hydrophobicity, we compared CdSe/ZnS QDs functionalized with hydrophobic trioctylphosphine oxide (TOPO) to identical QDs functionalized with hydrophilic dihydrolipoic acid-polyethylene glycol (DHLA-PEG) and alternative hydrophobic CdSe/ZnS QDs functionalized with oleic acid (OA). Results show that hydrophobic TOPO QDs are significantly more toxic than hydrophilic DHLA-PEG QDs, and substitution of TOPO with OA yields relatively non-toxic hydrophobic QDs. Fluorescence microscopy shows TOPO QDs loosely associated with the organism's cuticle, but atomic force microscopy shows no difference in cuticle structure from exposure. Importantly, TOPO ligand alone is as toxic as TOPO QDs, and our data suggests that TOPO may impact neuromuscular function, perhaps upon displacement from the QD surface. This study demonstrates the importance of examining ligand-specific impacts of hydrophobic ENMs and indicates OA-functionalized QDs as a potential alternative to TOPO QDs for reduced toxicity.

Methods for highly multiplexed RNA imaging are limited in spatial resolution and thus in their ability to localize transcripts to nanoscale and subcellular compartments. We adapt expansion microscopy, which physically expands biological specimens, for long-read untargeted and targeted in situ RNA sequencing. We applied untargeted expansion sequencing (ExSeq) to the mouse brain, which yielded the readout of thousands of genes, including splice variants. Targeted ExSeq yielded nanoscale-resolution maps of RNAs throughout dendrites and spines in the neurons of the mouse hippocampus, revealing patterns across multiple cell types, layer-specific cell types across the mouse visual cortex, and the organization and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. Thus, ExSeq enables highly multiplexed mapping of RNAs from nanoscale to system scale.

This protocol collection accompanies accompanies Expansion Sequencing (ExSeq), covering the four key steps of a targeted Expansion Sequencing (targeted ExSeq) experiment: (1) Padlock probe design; (2) tissue preparation and expansion; (3) library preparation; and (4) in situ sequencing with the Illumina chemistry. For further details, consult the relevant protocols within the collection. These protocols were used to profile human metastatic breast cancer biopsies as a part of the Human Tumor Atlas Pilot Project (HTAPP).

This protocol collection accompanies accompanies Expansion Sequencing (ExSeq), covering the four key steps of a targeted Expansion Sequencing (targeted ExSeq) experiment: (1) Padlock probe design; (2) tissue preparation and expansion; (3) library preparation; and (4) in situ sequencing with the Illumina chemistry. For further details, consult the relevant protocols within the collection. These protocols were used to profile human metastatic breast cancer biopsies as a part of the Human Tumor Atlas Pilot Project (HTAPP).

This protocol accompanies Expansion Sequencing (ExSeq), and describes the tissue preparation for Targeted ExSeq. The steps described here are a generalization of the protocols used for figures 4-6 of the paper, and represent our recommendations for future users of the technology. Fig. 1 shows the structure of the protocol schematically. There are three possible tissue preparation routes described in this protocol that are applicable to different experimental systems. Option (A): harvesting tissue from model organisms that can be transcardially perfused with PFA, followed by sectioning using a vibratome. We typically use this workflow for work on mouse brain sections (see figures 4-5 of ExSeq paper). Option (B): transcardially perfusing with PFA, followed by cryoprotection and cryosectioning. We occasionally use this protocol for work on mouse brain sections. Option (C): snap-freezing fresh tissue (i.e., human tumor biopsy samples, or freshly harvested tissue from mice), followed by cryoprotection and cryosectioning (see figures 2 and 6 of ExSeq paper). The final result of options (A), (B), and (C) is the preparation of fixed tissue sections (either on a glass slide or free-floating). The protocols then briefly converge for optional antibody staining, treatment with LabelX, a chemical that enables anchoring of RNA to the expansion microscopy (ExM) hydrogel, followed by casting of the the ExM gel. There are minor differences in these steps between free-floating and slide-mounted tissue sections, which are noted in the individual steps. The next step, digestion, is tissue-type dependent and may require some optimization for your tissue type. We provide two potential options here: (1) a gentle digestion for tissues such as mouse brain, and (2) a harsh digestion for non-brain tissues such as tumor biopies. The protocols then converge again for the rest of the process. After digestion, the gels are expanded and re-embedded within a second non-expanding hydrogel to lock in the sample size. The carboxylates within the expansion gel are then chemically passivated, enabling enzymatic reactions to be performed within the gel. The samples are now ready for library preparation. In more detail: Steps 1-4 describe the preparation of reagents for downstream steps. The protocol begins either along options (A)/(B), the Transcardial PFA perfusion path (Step 5, continuing to vibratome sectioning in Steps 6-7 for option (A), or cryotome sectioning in Steps 9-10 for option (B)), or along option (C), the Fresh Frozen path (Step 8, continuing to cryotome sectioning in Steps 9-10). The protocols then converge for optional antibody staining (Step 11), followed by LabelX anchoring (Step 12), optional sample trimming (Step 13), and formation of the expansion microscopy gel (Step 14). The details of the digestion step are tissue-type dependent (Step 15). The protocol then concludes with expansion (Step 16), re-embedding (Step 17), passivation, and optional trimming (Steps 18-19). This protocol was used to profile human metastatic breast cancer biopsies as a part of the Human Tumor Atlas Pilot Project (HTAPP). The tissue for this work was collected (see HTAPP-specific tissue collection protocol). The tissue sections were then frozen, cryosectioned, post-fixed, and permeabilized (following steps 9-10). No antibody staining was performed (skipping optional step 11). The sections were then treated with LabelX and gelled (steps 12-14). The gels were then digested using the robust digestion option in steps 15-16. The samples were then re-embedded, passivated, and trimmed (following steps 17-19).

This protocol collection accompanies accompanies Expansion Sequencing (ExSeq), covering the four key steps of a targeted Expansion Sequencing (targeted ExSeq) experiment: (1) Padlock probe design; (2) tissue preparation and expansion; (3) library preparation; and (4) in situ sequencing with the Illumina chemistry. For further details, consult the relevant protocols within the collection. These protocols were used to profile human metastatic breast cancer biopsies as a part of the Human Tumor Atlas Pilot Project (HTAPP).

A method for measuring mRNA copies in intact bacterial cells by fluctuation localization imaging-based fluorescence in situ hybridization (fliFISH) is presented. Unlike conventional single-molecule FISH, where the presence of a transcript is determined by fluorescence intensity, fliFISH relies on On-Off duty cycles of photo-switching dyes to set a predetermined threshold for distinguishing true signals from background noise. The method provides a quantitative approach for detecting and counting true mRNA copies and rejecting false signals with high accuracy.