ClampFISH 2.0 enables rapid, scalable amplified RNA detection in situ.

RNA labeling in situ has enormous potential to visualize transcripts and quantify their levels in single cells, but it remains challenging to produce high levels of signal while also enabling multiplexed detection of multiple RNA species simultaneously. Here, we describe clampFISH 2.0, a method that uses an inverted padlock design to efficiently detect many RNA species and exponentially amplify their signals at once, while also reducing the time and cost compared with the prior clampFISH method. We leverage the increased throughput afforded by multiplexed signal amplification and sequential detection to detect 10 different RNA species in more than 1 million cells. We also show that clampFISH 2.0 works in tissue sections. We expect that the advantages offered by clampFISH 2.0 will enable many applications in spatial transcriptomics.

Visualizing allele-specific expression in single cells reveals epigenetic mosaicism in an H19 loss-of-imprinting mutant.

Imprinting is a classic mammalian epigenetic phenomenon that results in expression from a single parental allele. Imprinting defects can lead to inappropriate expression from the normally silenced allele, but it remains unclear whether every cell in a mutant organism follows the population average, which would have profound implications for human imprinting disorders. Here, we apply a new fluorescence in situ hybridization method that measures allele-specific expression in single cells to address this question in mutants exhibiting aberrant H19/Igf2 (insulin-like growth factor 2) imprinting. We show that mutant primary embryonic mouse fibroblasts are comprised of two subpopulations: one expressing both H19 alleles and another expressing only the maternal copy. Only in the latter cell population is Igf2 expression detected. Furthermore, the two subpopulations are stable in that cells do not interconvert between the two expression patterns. Combined small input methylation analysis and transcriptional imaging revealed that these two mutant subpopulations exhibit distinct methylation patterns at their imprinting control regions. Consistently, pharmacological inhibition of DNA methylation reduced the proportion of monoallelic cells. Importantly, we observed that the same two subpopulations are also present in vivo within murine cardiac tissue. Our results establish that imprinting disorders can display striking single-cell heterogeneity in their molecular phenotypes and suggest that such heterogeneity may underlie epigenetic mosaicism in human imprinting disorders.

Retrospective identification of cell-intrinsic factors that mark pluripotency potential in rare somatic cells.

Pluripotency can be induced in somatic cells by the expression of OCT4, KLF4, SOX2, and MYC. Usually only a rare subset of cells reprogram, and the molecular characteristics of this subset remain unknown. We apply retrospective clone tracing to identify and characterize the rare human fibroblasts primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased fibroblast activation. Knockdown of a fibroblast activation factor identified by our analysis increased the reprogramming efficiency. We provide evidence for a unified model in which cells can move into and out of the primed state over time, explaining how reprogramming appears deterministic at short timescales and stochastic at long timescales. Furthermore, inhibiting the activity of LSD1 enlarged the pool of cells that were primed for reprogramming. Thus, even homogeneous cell populations can exhibit heritable molecular variability that can dictate whether individual rare cells will reprogram or not.

ClonoCluster: A method for using clonal origin to inform transcriptome clustering.

Clustering cells based on their high-dimensional profiles is an important data reduction process by which researchers infer distinct cellular states. The advent of cellular barcoding, however, provides an alternative means by which to group cells: by their clonal origin. We developed ClonoCluster, a computational method that combines both clone and transcriptome information to create hybrid clusters that weight both kinds of data with a tunable parameter. We generated hybrid clusters across six independent datasets and found that ClonoCluster generated qualitatively different clusters in all cases. The markers of these hybrid clusters were different but had equivalent fidelity to transcriptome-only clusters. The genes most strongly associated with the rearrangements in hybrid clusters were ribosomal function and extracellular matrix genes. We also developed the complementary tool Warp Factor that incorporates clone information in popular 2D visualization techniques like UMAP. Integrating ClonoCluster and Warp Factor revealed biologically relevant markers of cell identity.

Retrospective identification of intrinsic factors that mark pluripotency potential in rare somatic cells.

Pluripotency can be induced in somatic cells by the expression of the four "Yamanaka" factors OCT4, KLF4, SOX2, and MYC. However, even in homogeneous conditions, usually only a rare subset of cells admit reprogramming, and the molecular characteristics of this subset remain unknown. Here, we apply retrospective clone tracing to identify and characterize the individual human fibroblast cells that are primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased fibroblast activation. Knockdown of a fibroblast activation factor identified by our analysis led to increased reprogramming efficiency, identifying it as a barrier to reprogramming. Changing the frequency of reprogramming by inhibiting the activity of LSD1 led to an enlarging of the pool of cells that were primed for reprogramming. Our results show that even homogeneous cell populations can exhibit heritable molecular variability that can dictate whether individual rare cells will reprogram or not.

Cell type determination for cardiac differentiation occurs soon after seeding of human-induced pluripotent stem cells.

BACKGROUND: Cardiac differentiation of human-induced pluripotent stem (hiPS) cells consistently produces a mixed population of cardiomyocytes and non-cardiac cell types, even when using well-characterized protocols. We sought to determine whether different cell types might result from intrinsic differences in hiPS cells prior to the onset of differentiation. RESULTS: By associating individual differentiated cells that share a common hiPS cell precursor, we tested whether expression variability is predetermined from the hiPS cell state. In a single experiment, cells that shared a progenitor were more transcriptionally similar to each other than to other cells in the differentiated population. However, when the same hiPS cells were differentiated in parallel, we did not observe high transcriptional similarity across differentiations. Additionally, we found that substantial cell death occurs during differentiation in a manner that suggested all cells were equally likely to survive or die, suggesting that there is no intrinsic selection bias for cells descended from particular hiPS cell progenitors. We thus wondered how cells grow spatially during differentiation, so we labeled cells by expression of marker genes and found that cells expressing the same marker tended to occur in patches. Our results suggest that cell type determination across multiple cell types, once initiated, is maintained in a cell-autonomous manner for multiple divisions. CONCLUSIONS: Altogether, our results show that while substantial heterogeneity exists in the initial hiPS cell population, it is not responsible for the variability observed in differentiated outcomes; instead, factors specifying the various cell types likely act during a window that begins shortly after the seeding of hiPS cells for differentiation.

Variability within rare cell states enables multiple paths toward drug resistance.

Molecular differences between individual cells can lead to dramatic differences in cell fate, such as death versus survival of cancer cells upon drug treatment. These originating differences remain largely hidden due to difficulties in determining precisely what variable molecular features lead to which cellular fates. Thus, we developed Rewind, a methodology that combines genetic barcoding with RNA fluorescence in situ hybridization to directly capture rare cells that give rise to cellular behaviors of interest. Applying Rewind to BRAFV600E melanoma, we trace drug-resistant cell fates back to single-cell gene expression differences in their drug-naive precursors (initial frequency of ~1:1,000-1:10,000 cells) and relative persistence of MAP kinase signaling soon after drug treatment. Within this rare subpopulation, we uncover a rich substructure in which molecular differences among several distinct subpopulations predict future differences in phenotypic behavior, such as proliferative capacity of distinct resistant clones after drug treatment. Our results reveal hidden, rare-cell variability that underlies a range of latent phenotypic outcomes upon drug exposure.

Genetic screening for single-cell variability modulators driving therapy resistance.

Cellular plasticity describes the ability of cells to transition from one set of phenotypes to another. In melanoma, transient fluctuations in the molecular state of tumor cells mark the formation of rare cells primed to survive BRAF inhibition and reprogram into a stably drug-resistant fate. However, the biological processes governing cellular priming remain unknown. We used CRISPR-Cas9 genetic screens to identify genes that affect cell fate decisions by altering cellular plasticity. We found that many factors can independently affect cellular priming and fate decisions. We discovered a new plasticity-based mode of increasing resistance to BRAF inhibition that pushes cells towards a more differentiated state. Manipulating cellular plasticity through inhibition of DOT1L before the addition of the BRAF inhibitor resulted in more therapy resistance than concurrent administration. Our results indicate that modulating cellular plasticity can alter cell fate decisions and may prove useful for treating drug resistance in other cancers.

ClampFISH detects individual nucleic acid molecules using click chemistry-based amplification.

Methods for detecting single nucleic acids in cell and tissues, such as fluorescence in situ hybridization (FISH), are limited by relatively low signal intensity and nonspecific probe binding. Here we present click-amplifying FISH (clampFISH), a method for fluorescence detection of nucleic acids that achieves high specificity and high-gain (>400-fold) signal amplification. ClampFISH probes form a 'C' configuration upon hybridization to the sequence of interest in a double helical manner. The ends of the probes are ligated together using bio-orthogonal click chemistry, effectively locking the probes around the target. Iterative rounds of hybridization and click amplify the fluorescence intensity. We show that clampFISH enables the detection of RNA species with low-magnification microscopy and in RNA-based flow cytometry. Additionally, we show that the modular design of clampFISH probes allows multiplexing of RNA and DNA detection, that the locking mechanism prevents probe detachment in expansion microscopy, and that clampFISH can be applied in tissue samples.