Cell-cell interactions drive rapid and heterogeneous changes in gene expression, yet most transcriptomic methods either dissociate cells, losing pair identity and interaction timing, or infer communication indirectly from ligand-receptor co-expression. Here we present Cell-Cell-seq, a scalable workflow for profiling defined cell pairs ("dyads") with single-cell transcriptomic resolution. Cell-Cell-seq uses cavity-containing hydrogel microparticles (Nanovials) to confine two cells, synchronize contact onset, protect fragile conjugates during handling and sorting, and interface directly with droplet-based RNA sequencing. Using antigen-matched prostate tumor cells and engineered T cells as a model system, Cell-Cell-seq captured thousands of tumor-T cell dyads and revealed broad functional and transcriptional heterogeneity across interactions. Dyads unmasked transient activation programs that were obscured in standard well-plate co-culture, consistent with asynchronous contact in bulk assays. To distinguish interaction-induced programs from the composite nature of dyad transcriptomes, we developed a pseudo-mixing framework that generates in silico pseudo-dyads to construct an empirical null distribution under "no interaction," enabling statistically robust identification of emergent genes and partner-resolved attribution of responses. Dyad-resolved analysis further revealed coordinated cross-cell programs, including coupled chemokine expression consistent with bidirectional paracrine signaling and inverse coupling between tumor immunoregulatory programs and T cell activation. Finally, we introduce ccRepair to correct compositional dilution in mixed transcriptomes, improving interpretability while preserving genuine cross-cell coordination. Together, Cell-Cell-seq provides a generalizable platform for dissecting immune synapse biology and mapping interaction-dependent programs across heterogeneous cell populations, with applications in profiling tumor-immune communication and functionally screening immunotherapies.

Idiopathic Pulmonary Fibrosis (IPF) is characterized by scarring and remodeling of lung tissue, leading to progressive pulmonary dysfunction. Currently, very little is known about the steps involved in disease initiation and progression because models of IPF poorly replicate these processes. However, understanding the pathogenesis of IPF is essential to developing effective therapies. To address this, we developed a scaffold-based human co-culture alveolar organoid model that utilizes healthy and IPF human primary lung fibroblasts and induced pluripotent stem cell-derived alveolar type 2 (iAT2) cells carrying the surfactant protein C (SFTPC) 173T mutation of familial IPF, or their syngeneic corrected controls, to recapitulate epithelial-mesenchymal cellular communication during fibrosis initiation and progression. We found that the interaction between epithelial cells and fibroblasts plays a key role in inducing fibrotic responses in this model, with the secretion of chemokines, cytokines, TGFβ, and matrix metalloproteinases that mirror those observed in the serum of patients with pulmonary fibrosis. Single-cell RNA sequencing revealed the emergence of many cell subtypes observed in progressive lung fibrosis, along with key cellular interactions that correlated with the initial upregulation of fibrosis pathways, extracellular matrix (ECM) remodeling, inflammation, and changes in lipid metabolism. The anti-fibrotic compounds, Nintedanib and the TGFβ inhibitor, SB431542, demonstrated dose-dependent efficacy in the model, with IC50 values comparable to those observed in the clinic, and significantly reduced secretion of fibrosis-related factors. Overall, this study shows that the three-dimensional cell co-culture organoid effectively models progressive lung fibrosis, facilitating the investigation of epithelial-mesenchymal interactions and serving as a patient-relevant model to better predict the efficacy of therapeutics in the clinic.

Artificial biomolecular condensates have emerged as powerful tools for controlling cellular behaviour. Here we introduce a method to build artificial condensates within living mammalian cells by designing modular RNA motifs composed of a single short RNA strand. These condensates emerge spontaneously, creating RNA-rich compartments that remain separated from their surrounding environment. The RNA sequences include stem-loop domains that fold as the RNA is transcribed, and then condense in the nucleus and cytoplasm through loop-loop interactions. These sequences can be optimized and diversified, enabling the generation of distinct, non-mixing condensate populations and the programmable control of their subcellular localization. The RNA motifs can also be modified to recruit small molecules, proteins and RNA molecules in a sequence-specific manner to the RNA-rich phase. By introducing RNA linkers, we can build condensates with multiple subcompartments, whose organization can be controlled by tuning the linker stoichiometry. These artificial condensates provide a versatile platform for studying and manipulating molecular functions inside living cells.

Cells secrete numerous proteins and other biomolecules into their surroundings to achieve critical functions—from communicating with other cells to blocking the activity of pathogens. Secretion of cytokines, growth factors, extracellular vesicles and even recombinant biologic drugs defines the therapeutic potency of many cell therapies. However, gene expression states that drive specific secretory phenotypes are largely unknown. We provide a protocol that enables the secretion amount of a target protein encoded (SEC) by oligonucleotide barcodes to be linked with transcriptional sequencing (seq) for thousands of single cells. SEC-seq leverages microscale hydrogel particles called Nanovials to isolate cells and capture their secretions in close proximity, oligonucleotide-labeled antibodies to tag secretions on Nanovials and flow cytometry and single-cell RNA-sequencing (scRNA-seq) platforms for readout. Cells on Nanovials can be sorted on the basis of viability, secretion amount or other surface markers without fixation or permeabilization, and cell- and secretion-containing Nanovials are directly introduced into microfluidic droplets-in-oil emulsions for single-cell barcoding of cell transcriptomes and secretions. We have used SEC-seq to link T cell receptor sequences to the relative amount of associated cytokine secretions, surface marker gene expression with a highly secreting and potential regenerative population of mesenchymal stromal cells and the transcriptome with high immunoglobulin secretion from plasma cells. Nanovial modification and cell loading takes <4 h, and once the desired incubation time is over, staining, cell sorting and emulsion generation for scRNA-seq can also be completed in <4 h. Compared to related techniques that link secretions to a cell’s surface, SEC-seq provides a general solution across any secretion target because of the ease with which biotinylated Nanovials can be modified. By linking gene expression and secretory strength, SEC-seq can expand our understanding of cell secretion, how it is regulated and how it can be engineered to make better therapies. SEC-seq is a single-cell method linking the secretion of a target protein to the cell’s transcriptome. Nanovials isolate cells and capture their secretions, and oligonucleotide-labeled antibodies tag them, followed by an scRNA-seq readout.

RATIONALE:Airway submucosal glands (SMGs) house at least two distinct stem populations, namely the duct basal and myoepithelial cells (MECs). Based on studies utilizing severe airway injury modalities in murine models, both populations are seemingly competent to regenerate SMG and surface airway epithelium (SAE). However, equivalent regenerative capacity has not been established for the human counterparts to these stem populations. METHODS:Cell suspensions derived from the SAE or SMGs of human donor tracheae and bronchi were sorted (via fluorescence-activated cell sorting) based on expression of the surface proteins EGFR, NGFR, ITGA2, and TROP2. Sorted SMG duct basal, surface basal, MECs, and unsorted SMG isolates were seeded in Cultrex basement membrane extract to initiate organoid cultures. Organoid-forming efficiencies and organoid area were measured via brightfield microscopy to assess growth dynamics of each sample population. Single-cell gene expression of organoids from each population was interrogated via 10X fixed RNA profiling. RESULTS:Sorted MECs exhibited diminished organoid-forming efficiencies compared to unsorted SMG isolates, sorted duct basal, and sorted surface basal cells. Single-cell fixed RNA profiling revealed that MECs preferentially differentiate into secretory lineages at the expense of stem maintenance, instead generating cycling secretory intermediates that are fate-committed. Conversely, surface basal cells rapidly mobilize under expansion conditions in culture, accounting for the greatest organoid-forming efficiency and total biomass of the sorted populations, whereas duct basal cells demonstrate growth dynamics intermediate between MECs and surface basal cells. Moreover, surface and duct basal cells are more proficient in maintenance of “stemness” compared to MECs and have a more balanced distribution across fate-committed clusters, including progeny that are directed towards surface/duct-like luminal cell types. CONCLUSION:Determination of suitable targets for gene replacement and editing strategies is crucial for long-term correction of the causative mutation. Accordingly, identification of a long-lived airway stem population with broad multipotency would produce an ideal candidate for therapeutic concerns. SMG duct basal cells isolated from human airways demonstrated excellent self-renewal capacity and multipotency in organoid cultures, marking this population as an attractive prospect for advancing regenerative medicine in the respiratory system.

Sample multiplexing has become an increasingly common design choice in droplet-based single-nucleus multi-omic sequencing experiments to reduce costs and remove technical variation. Genotype-based demultiplexing is one popular class of methods that was originally developed for single-cell RNA-seq, but has not been rigorously benchmarked in other assays, such as snATAC-seq and joint snRNA/snATAC assays, especially in the context of variable ambient RNA/DNA contamination. To address this, we develop ambisim, a genotype-aware read-level simulator that can flexibly control ambient molecule proportions and generate realistic joint snRNA/snATAC data. We use ambisim to evaluate demultiplexing methods across several important parameters: doublet rate, number of multiplexed donors, and coverage levels. Our simulations reveal that methods are variably impacted by ambient contamination in both modalities. We then applied the demultiplexing methods to two joint snRNA/snATAC datasets and found highly variable concordance between methods in both modalities. Finally, we develop a new metric, variant consistency, which we show is correlated with cell-level ambient molecule fractions in singlets. Applying our metric to two multiplexed joint snRNA/snATAC datasets reveals variable ambient contamination across experiments and modalities. We conclude that improved modelling of ambient material in demultiplexing algorithms will increase both sensitivity and specificity.

Rationale: Identification and understanding of intercellular signaling and molecular mechanisms that initiate and drive Idiopathic Pulmonary Fibrosis (IPF) are largely unknown. In particular, the specific role of epithelial and mesenchymal cell interactions in the initiation and progression of the disease remains debated. To address this, we have developed a scaffold-based co-culture IPF organoid model that uses healthy and diseased human iPSC-derived alveolar epithelial cells and primary human lung fibroblasts to recapitulate the phenotypic and gene expression changes during progressive fibrosis. Method: We generated microbead scaffolds that structurally mimic alveolar air-sacs and coated them in a rotating bioreactor with primary lung fibroblasts and iPSC-derived type 2 alveolar cells (iAT2s). iAT2s with the surfactant protein C (SFTPC) I73T variant and the syngeneic corrected control iAT2s were cultured with primary healthy and IPF fibroblasts in different combinations. All combinations were scored daily for phenotypic changes (surface area reduction, extracellular matrix deposition) that correlate with the progression of the disease. Single-cell samples from each cell combination at each disease stage were collected, and single-cell-RNA-sequencing was performed to study epithelial-mesenchymal interactions at different stages of the disease. Result: The SFTPC-mutant iAT2s induced a fibrotic phenotype in organoids co-cultured with healthy lung fibroblasts, while the corrected iAT2s did not change the phenotype of organoids co-cultured with healthy lung fibroblasts. This fibrotic phenotype was similar to that seen with IPF lung fibroblasts co-cultured with corrected iAT2s. Single-cell-RNA-sequencing revealed that SFTPC-mutant iAT2s induced gene expression changes in healthy lung fibroblasts. These changes were viewed in Gene Ontology terms and included lung fibrosis program, ferroptosis pathway, extracellular matrices, fatty acid metabolism, and hypoxic stress responses. Time in culture of the organoids had a significant effect on both cell populations. When comparing early vs late-stage cultures, we noted the loss of iAT2 cells in co-cultures with IPF fibroblasts but no loss of iAT2 cells in co-cultures with healthy lung fibroblasts. The model also showed the distribution of key IPF biomarkers like COL1A1, CTHRC1, SFTPC, and KRT17 in fibroblast and iAT2 clusters. The gene expression changes were validated at the protein level with immunofluorescent staining. Conclusion: Our alveolar organoid model of progressive fibrosis reveals critical pathways involved in the initiation and progression of lung fibrosis. By analyzing gene expression changes across various cellular combinations and time points, we can pinpoint essential cell types and pathways in the progression of fibrosis, aiding the development of stage-specific therapeutic strategies.

Cell-based immunotherapy is a promising treatment strategy for cancer. Particularly in the case of solid tumors, however, this strategy only benefits a minority of patients. A critical limitation to immunotherapy is T cell exhaustion, a terminal differentiation state characterized by loss of self-renewal and cytotoxic capacity. For over a decade, regenerative immunology approaches to overcome exhaustion and restore stem-like features of T cells have been pursued. The reprogramming of tumor-specific T cells back to a less-differentiated, stem-like state using induced pluripotent stem cell (iPSC) technology has been viewed as a powerful and highly appealing strategy to overcome the limitations imposed by exhaustion. However, clinical translation of these approaches has been stymied by the requirement for subsequent iPSC-to-T cell re-maturation strategies, vanishingly low efficiencies, and resource-intensive cell culture protocols. In this review, we discuss the emergence of transcription factor reprogramming to iPSCs, contemporary techniques for T cell reprogramming, as well as techniques for re-differentiation into mature T cells. We discuss the potential clinical utility of T cell reprogramming and re-maturation strategies alongside progress and major roadblocks toward clinical translation. If these challenges can be addressed, transcription factor reprogramming of T cells into iPSCs and subsequent re-maturation into tumor-specific stem-like T cells may represent an incredibly efficacious approach to cancer immunotherapy.

Amnion, germline and mesoderm specification at the posterior end of the human embryo occur around the same time in vivo. Similarly, in vitro generation of germline and amnion is associated with mesoderm induction regardless of differentiation platform. Yet, the lineage relationships between amnion, germline and mesoderm remains unresolved. By adding Basement Membrane Extract (BME) to the media, we demonstrate emergence of TFAP2A+/SOX2- epithelial progenitor cells which develop in response to BMP receptor signaling. We track the order of embryonic events that take place from this progenitor pool revealing that amnion-like cells (AMLCs) and primordial germ cell (PGC)-like cells (PGCLCs) are specified first. Shortly after, gastrulating mesoderm-like cells (MeLCs) arise that undergo an epithelial to mesenchymal transition (EMT). These results highlight the interconnected role of basement membrane deposition and BMP receptor signaling in the specification of human germline, amnion and mesoderm from TFAP2A+ embryonic progenitors.

X chromosome inactivation (XCI) serves as a paradigm for RNA-mediated regulation of gene expression, wherein the long non-coding RNA XIST spreads across the X chromosome in cis to mediate gene silencing chromosome-wide. In female naive human pluripotent stem cells (hPSCs), XIST is in a dispersed configuration, and XCI does not occur, raising questions about XIST's function. We found that XIST spreads across the X chromosome and induces dampening of X-linked gene expression in naive hPSCs. Surprisingly, XIST also targets specific autosomal regions, where it induces repressive chromatin changes and gene expression dampening. Thereby, XIST equalizes X-linked gene dosage between male and female cells while inducing differences in autosomes. The dispersed Xist configuration and autosomal localization also occur transiently during XCI initiation in mouse PSCs. Together, our study identifies XIST as the regulator of X chromosome dampening, uncovers an evolutionarily conserved trans-acting role of XIST/Xist, and reveals a correlation between XIST/Xist dispersal and autosomal targeting.

Creation of Cell Lines Targeting RB1 and TP53

This comprehensive Review delves into the chemical principles governing RNA-mediated crowding events, commonly referred to as granules or biological condensates. We explore the pivotal role played by RNA sequence, structure, and chemical modifications in these processes, uncovering their correlation with crowding phenomena under physiological conditions. Additionally, we investigate instances where crowding deviates from its intended function, leading to pathological consequences. By deepening our understanding of the delicate balance that governs molecular crowding driven by RNA and its implications for cellular homeostasis, we aim to shed light on this intriguing area of research. Our exploration extends to the methodologies employed to decipher the composition and structural intricacies of RNA granules, offering a comprehensive overview of the techniques used to characterize them, including relevant computational approaches. Through two detailed examples highlighting the significance of noncoding RNAs, NEAT1 and XIST, in the formation of phase-separated assemblies and their influence on the cellular landscape, we emphasize their crucial role in cellular organization and function. By elucidating the chemical underpinnings of RNA-mediated molecular crowding, investigating the role of modifications, structures, and composition of RNA granules, and exploring both physiological and aberrant phase separation phenomena, this Review provides a multifaceted understanding of the intriguing world of RNA-mediated biological condensates.

To regulate gene expression, the macromolecular components of the mammalian interphase nucleus are spatially organized into a myriad of functional compartments. Over the past decade, increasingly sophisticated genomics, microscopy, and functional approaches have probed this organization in unprecedented detail. These investigations have linked chromatin-associated noncoding RNAs to specific nuclear compartments and uncovered mechanisms by which these RNAs establish such domains. In this review, we focus on the long non-coding RNA Xist and summarize new evidence demonstrating the significance of chromatin reconfiguration in creating the inactive X-chromosome compartment. Differences in chromatin compaction correlate with distinct levels of gene repression on the X-chromosome, potentially explaining how human XIST can induce chromosome-wide dampening and silencing of gene expression at different stages of human development.