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Understanding the rapidly evolving landscape of single-cell and spatial omic technologies is crucial for advancing biomedical research and drug development. We provide a living review of both mature and emerging commercial platforms, highlighting key methodologies and trends shaping the field. This review spans from foundational single-cell technologies such as microfluidics and plate-based methods to newer approaches like combinatorial indexing; on the spatial side, we consider next-generation sequencing and imaging-based spatial transcriptomics. Finally, we highlight emerging methodologies that may fundamentally expand the scope for data generation within pharmaceutical research, creating opportunities to discover and validate novel drug mechanisms. Overall, this review serves as a critical resource for navigating the commercialization and application of single-cell and spatial omic technologies in pharmaceutical and academic research., Competing Interests: Declaration of interests J.D.J., J.W.O., and A.P.C. are inventors on patent applications filed by the University of Cambridge (via Cambridge Enterprise), the University College London Business, and Oxford University Innovations, respectively. J.W.O., A.V.Z., T.G., J.C., L.R.-M., C.E.S.R., A.K.S., and J.P.T.-K. receive compensation from Relation Therapeutics. P.C. and A.P.C. are employees of Caereleus Genomics. B.S.N. and N.D.K. receive compensation from OMAPiX. M.V. and J.L. are scientific consultants for 10× Genomics. J.M. receives compensation from Skyhawk Therapeutics and previously worked as a scientific consultant for Scipio Bioscience. K.S. receives compensation from Roche. D.M. receives compensation from scDiscoveries. H.L., S.M.S., and C.M.L. receive compensation from spatialist. A.K.S. reports compensation for consulting and/or scientific advisory board membership from Honeycomb Biotechnologies, Cellarity, Ochre Bio, Relation Therapeutics, Bio-Rad Laboratories, IntrECate Biotherapeutics, Passkey Therapeutics, Fog Pharma, and Dahlia Biosciences, which are unrelated to this work. D.S. reports funding from Cellzome, a GSK company, and received honorariums from Immunai, Noetik, Alpenglow, and Lunaphore., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Enteroendocrine cells (EECs) are gut epithelial cells that respond to intestinal contents by secreting hormones, including the incretins glucagon-like peptide 1 (GLP-1) and gastric inhibitory protein (GIP), which regulate multiple physiological processes. Hormone release is controlled through metabolite-sensing proteins. Low expression, interspecies differences, and the existence of multiple EEC subtypes have posed challenges to the study of these sensors. We describe differentiation of stomach EECs to complement existing intestinal organoid protocols. CD200 emerged as a pan-EEC surface marker, allowing deep transcriptomic profiling from primary human tissue along the stomach-intestinal tract. We generated loss-of-function mutations in 22 receptors and subjected organoids to ligand-induced secretion experiments. We delineate the role of individual human EEC sensors in the secretion of hormones, including GLP-1. These represent potential pharmacological targets to influence appetite, bowel movement, insulin sensitivity, and mucosal immunity.

Organoid evolution models complemented with integrated single-cell sequencing technology provide a powerful platform to characterize intra-tumor heterogeneity (ITH) and tumor evolution. Here, we conduct a parallel evolution experiment to mimic the tumor evolution process by evolving a colon cancer organoid model over 100 generations, spanning 6 months in time. We use single-cell whole-genome sequencing (WGS) in combination with viral lineage tracing at 12 time points to simultaneously monitor clone size, CNV states, SNV states, and viral lineage barcodes for 1,641 single cells. We integrate these measurements to construct clonal evolution trees with high resolution. We characterize the order of events in which chromosomal aberrations occur and identify aberrations that recur multiple times within the same tumor sub-population. We observe recurrent sequential loss of chromosome 4 after loss of chromosome 18 in four unique tumor clones. SNVs and CNVs identified in our organoid experiments are also frequently reported in colorectal carcinoma samples, and out of 334 patients with chromosome 18 loss in a Memorial Sloan Kettering colorectal cancer cohort, 99 (29.6%) also harbor chromosome 4 loss. Our study reconstructs tumor evolution in a colon cancer organoid model at high resolution, demonstrating an approach to identify potentially clinically relevant genomic aberrations in tumor evolution., Competing Interests: The authors declare no competing financial interests. J.d.R. is founder of Cyclomics B.V., (© 2022 The Authors.)

DNA methylation (5mC) is central to cellular identity. The global erasure of 5mC from the parental genomes during preimplantation mammalian development is critical to reset the methylome of gametes to the cells in the blastocyst. While active and passive modes of demethylation have both been suggested to play a role in this process, the relative contribution of these two mechanisms to 5mC erasure remains unclear. Here, we report a single-cell method (scMspJI-seq) that enables strand-specific quantification of 5mC, allowing us to systematically probe the dynamics of global demethylation. When applied to mouse embryonic stem cells, we identified substantial cell-to-cell strand-specific 5mC heterogeneity, with a small group of cells displaying asymmetric levels of 5mCpG between the two DNA strands of a chromosome suggesting loss of maintenance methylation. Next, in preimplantation mouse embryos, we discovered that methylation maintenance is active till the 16-cell stage followed by passive demethylation in a fraction of cells within the early blastocyst at the 32-cell stage of development. Finally, human preimplantation embryos qualitatively show temporally delayed yet similar demethylation dynamics as mouse embryos. Collectively, these results demonstrate that scMspJI-seq is a sensitive and cost-effective method to map the strand-specific genome-wide patterns of 5mC in single cells.

RNA-binding proteins (RBPs) commonly feature multiple RNA-binding domains (RBDs), which provide these proteins with a modular architecture. Accumulating evidence supports that RBP architectural modularity and adaptability define the specificity of their interactions with RNA. However, how multiple RBDs recognize their cognate single-stranded RNA (ssRNA) sequences in concert remains poorly understood. Here, we use Upstream of N-Ras (Unr) as a model system to address this question. Although reported to contain five ssRNA-binding cold-shock domains (CSDs), we demonstrate that Unr includes an additional four CSDs that do not bind RNA (pseudo-RBDs) but are involved in mediating RNA tertiary structure specificity by reducing the conformational heterogeneity of Unr. Disrupting the interactions between canonical and non-canonical CSDs impacts RNA binding, Unr-mediated translation regulation, and the Unr-dependent RNA interactome. Taken together, our studies reveal a new paradigm in protein-RNA recognition, where interactions between RBDs and pseudo-RBDs select RNA tertiary structures, influence RNP assembly, and define target specificity., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Protein-DNA interactions are essential for establishing cell type-specific chromatin architecture and gene expression. We recently developed scDam&T-seq, a multi-omics method that can simultaneously quantify protein-DNA interactions and the transcriptome in single cells. The method effectively combines two existing methods: DNA adenine methyltransferase identification (DamID) and CEL-Seq2. DamID works through the tethering of a protein of interest (POI) to the Escherichia coli DNA adenine methyltransferase (Dam). Upon expression of this fusion protein, DNA in proximity to the POI is methylated by Dam and can be selectively digested and amplified. CEL-Seq2, in contrast, makes use of poly-dT primers to reverse transcribe mRNA, followed by linear amplification through in vitro transcription. scDam&T-seq is the first technique capable of providing a combined readout of protein-DNA contact and transcription from single-cell samples. Once suitable cell lines have been established, the protocol can be completed in 5 d, with a throughput of hundreds to thousands of cells. The processing of raw sequencing data takes an additional 1-2 d. Our method can be used to understand the transcriptional changes a cell undergoes upon the DNA binding of a POI. It can be performed in any laboratory with access to FACS, robotic and high-throughput-sequencing facilities.

Protein-DNA interactions are critical to the regulation of gene expression, but it remains challenging to define how cell-to-cell heterogeneity in protein-DNA binding influences gene expression variability. Here we report a method for the simultaneous quantification of protein-DNA contacts by combining single-cell DNA adenine methyltransferase identification (DamID) with messenger RNA sequencing of the same cell (scDam&T-seq). We apply scDam&T-seq to reveal how genome-lamina contacts or chromatin accessibility correlate with gene expression in individual cells. Furthermore, we provide single-cell genome-wide interaction data on a polycomb-group protein, RING1B, and the associated transcriptome. Our results show that scDam&T-seq is sensitive enough to distinguish mouse embryonic stem cells cultured under different conditions and their different chromatin landscapes. Our method will enable the analysis of protein-mediated mechanisms that regulate cell-type-specific transcriptional programs in heterogeneous tissues.

The epigenetic DNA modification 5-hydroxymethylcytosine (5hmC) has crucial roles in development and gene regulation. Quantifying the abundance of this epigenetic mark at the single-cell level could enable us to understand its roles. We present a single-cell, genome-wide and strand-specific 5hmC sequencing technology, based on 5hmC glucosylation and glucosylation-dependent digestion of DNA, that reveals pronounced cell-to-cell variability in the abundance of 5hmC on the two DNA strands of a given chromosome. We develop a mathematical model that reproduces the strand bias and use this model to make two predictions. First, the variation in strand bias should decrease when 5hmC turnover increases. Second, the strand bias of two sister cells should be strongly anti-correlated. We validate these predictions experimentally, and use our model to reconstruct lineages of two- and four-cell mouse embryos, showing that single-cell 5hmC sequencing can be used as a lineage reconstruction tool.

We have developed a quantitative technique for sorting cells on the basis of endogenous RNA abundance, with a molecular resolution of 10-20 transcripts. We demonstrate efficient and unbiased RNA extraction from transcriptionally sorted cells and report a high-fidelity transcriptome measurement of mouse induced pluripotent stem cells (iPSCs) isolated from a heterogeneous reprogramming culture. This method is broadly applicable to profiling transcriptionally distinct cellular states without requiring antibodies or transgenic fluorescent proteins.

Variability in gene expression contributes to phenotypic heterogeneity even in isogenic populations. Here, we used the stereotyped, Wnt signaling-dependent development of the Caenorhabditis elegans Q neuroblast to probe endogenous mechanisms that control gene expression variability. We found that the key Hox gene that orients Q neuroblast migration exhibits increased gene expression variability in mutants in which Wnt pathway activity has been perturbed. Distinct features of the gene expression distributions prompted us on a systematic search for regulatory interactions, revealing a network of interlocked positive and negative feedback loops. Interestingly, positive feedback appeared to cooperate with negative feedback to reduce variability while keeping the Hox gene expression at elevated levels. A minimal model correctly predicts the increased gene expression variability across mutants. Our results highlight the influence of gene network architecture on expression variability and implicate feedback regulation as an effective mechanism to ensure developmental robustness., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Genomic imprinting directs the allele-specific marking and expression of loci according to their parental origin. Differential DNA methylation at imprinted control regions (ICRs) is established in gametes and, although largely preserved through development, can be experimentally reset by fusing somatic cells with embryonic germ cell (EGC) lines. Here, we show that the Ten-Eleven Translocation proteins Tet1 and Tet2 participate in the efficient erasure of imprints in this model system. The fusion of B cells with EGCs initiates pluripotent reprogramming, in which rapid re-expression of Oct4 is accompanied by an accumulation of 5-hydroxymethylcytosine (5hmC) at several ICRs. Tet2 was required for the efficient reprogramming capacity of EGCs, whereas Tet1 was necessary to induce 5-methylcytosine oxidation specifically at ICRs. These data show that the Tet1 and Tet2 proteins have discrete roles in cell-fusion-mediated pluripotent reprogramming and imprint erasure in somatic cells., (Copyright © 2013 Elsevier Inc. All rights reserved.)