Seq-Well: A Portable, Low-Cost Platform for High-Throughput Single-Cell RNA-Seq of Low-Input Samples

Single-cell RNA-Seq can precisely resolve cellular states but application to sparse samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively-parallel single-cell RNA-Seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semi-permeable membrane, enabling efficient cell lysis and transcript capture. We characterize Seq-Well using species-mixing experiments and PBMCs, and profile thousands of primary human macrophages exposed to tuberculosis

Harnessing single-cell genomics to improve the physiological fidelity of organoid-derived cell types

Background: Single-cell genomic methods now provide unprecedented resolution for characterizing the component cell types and states of tissues such as the epithelial subsets of the gastrointestinal tract. Nevertheless, functional studies of these subsets at scale require faithful in vitro models of identified in vivo biology. While intestinal organoids have been invaluable in providing mechanistic insights in vitro, the extent to which organoid-derived cell types recapitulate their in vivo counterparts remains formally untested, with no systematic approach for improving model fidelity. Results: Here, we present a generally applicable framework that utilizes massively parallel single-cell RNA-seq to compare cell types and states found in vivo to those of in vitro models such as organoids. Furthermore, we leverage identified discrepancies to improve model fidelity. Using the Paneth cell (PC), which supports the stem cell niche and produces the largest diversity of antimicrobials in the small intestine, as an exemplar, we uncover fundamental gene expression differences in lineage-defining genes between in vivo PCs and those of the current in vitro organoid model. With this information, we nominate a molecular intervention to rationally improve the physiological fidelity of our in vitro PCs. We then perform transcriptomic, cytometric, morphologic and proteomic characterization, and demonstrate functional (antimicrobial activity, niche support) improvements in PC physiology. Conclusions: Our systematic approach provides a simple workflow for identifying the limitations of in vitro models and enhancing their physiological fidelity. Using adult stem cell-derived PCs within intestinal organoids as a model system, we successfully benchmark organoid representation, relative to that in vivo, of a specialized cell type and use this comparison to generate a functionally improved in vitro PC population. We predict that the generation of rationally improved cellular models will facilitate mechanistic exploration of specific disease-associated genes in their respective cell types. Electronic supplementary material The online version of this article (10.1186/s12915-018-0527-2) contains supplementary material, which is available to authorized users

Marrying microfluidics and microwells for parallel, high-throughput single-cell genomics

An innovative, microwell-based platform for single-cell RNA sequencing (RNA-seq) combines cost efficiency, scalability and parallelizability, and will enable many new avenues of biological inquiry. See related Research article: http://dx.doi.org/10.1186/s13059-015-0684-

Identification of a Master Regulator of Differentiation in Toxoplasma

© 2019 The Author(s) Toxoplasma gondii chronically infects a quarter of the world's population, and its recrudescence can cause life-threatening disease in immunocompromised individuals and recurrent ocular lesions in the immunocompetent. Acute-stage tachyzoites differentiate into chronic-stage bradyzoites, which form intracellular cysts resistant to immune clearance and existing therapies. The molecular basis of this differentiation is unknown, despite being efficiently triggered by stresses in culture. Through Cas9-mediated screening and single-cell profiling, we identify a Myb-like transcription factor (BFD1) necessary for differentiation in cell culture and in mice. BFD1 accumulates during stress and its synthetic expression is sufficient to drive differentiation. Consistent with its function as a transcription factor, BFD1 binds the promoters of many stage-specific genes and represents a counterpoint to the ApiAP2 factors that dominate our current view of parasite gene regulation. BFD1 provides a genetic switch to study and control Toxoplasma differentiation and will inform prevention and treatment of chronic infections

Single-cell analysis of human primary prostate cancer reveals the heterogeneity of tumor-associated epithelial cell states

AbstractProstate cancer is the second most common malignancy in men worldwide and consists of a mixture of tumor and non-tumor cell types. To characterize the prostate cancer tumor microenvironment, we perform single-cell RNA-sequencing on prostate biopsies, prostatectomy specimens, and patient-derived organoids from localized prostate cancer patients. We uncover heterogeneous cellular states in prostate epithelial cells marked by high androgen signaling states that are enriched in prostate cancer and identify a population of tumor-associated club cells that may be associated with prostate carcinogenesis. ERG-negative tumor cells, compared to ERG-positive cells, demonstrate shared heterogeneity with surrounding luminal epithelial cells and appear to give rise to common tumor microenvironment responses. Finally, we show that prostate epithelial organoids harbor tumor-associated epithelial cell states and are enriched with distinct cell types and states from their parent tissues. Our results provide diagnostically relevant insights and advance our understanding of the cellular states associated with prostate carcinogenesis.</jats:p

Single-cell analysis of human primary prostate cancer reveals the heterogeneity of tumor-associated epithelial cell states.

Prostate cancer is the second most common malignancy in men worldwide and consists of a mixture of tumor and non-tumor cell types. To characterize the prostate cancer tumor microenvironment, we perform single-cell RNA-sequencing on prostate biopsies, prostatectomy specimens, and patient-derived organoids from localized prostate cancer patients. We uncover heterogeneous cellular states in prostate epithelial cells marked by high androgen signaling states that are enriched in prostate cancer and identify a population of tumor-associated club cells that may be associated with prostate carcinogenesis. ERG-negative tumor cells, compared to ERG-positive cells, demonstrate shared heterogeneity with surrounding luminal epithelial cells and appear to give rise to common tumor microenvironment responses. Finally, we show that prostate epithelial organoids harbor tumor-associated epithelial cell states and are enriched with distinct cell types and states from their parent tissues. Our results provide diagnostically relevant insights and advance our understanding of the cellular states associated with prostate carcinogenesis

Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies

© 2020 The Authors High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S3 (“Second-Strand Synthesis”), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well S3 increased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S3 to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation