Travis K. Hughes

Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq

Single-cell expression profiles of melanoma Tumors harbor multiple cell types that are thought to play a role in the development of resistance to drug treatments. Tirosh et al. used single-cell sequencing to investigate the distribution of these differing genetic profiles within melanomas. Many cells harbored heterogeneous genetic programs that reflected two different states of genetic expression, one of which was linked to resistance development. Following drug treatment, the resistance-linked expression state was found at a much higher level. Furthermore, the environment of the melanoma cells affected their gene expression programs. Science, this issue p. 189 Melanoma cells show transcriptional heterogeneity. To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug-resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single-cell genomics offers insights with implications for both targeted and immune therapies.

Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput

Single-cell RNA-seq can precisely resolve cellular states, but applying this method to low-input 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 semipermeable membrane, enabling efficient cell lysis and transcript capture. We use Seq-Well to profile thousands of primary human macrophages exposed to Mycobacterium tuberculosis.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

BackgroundSingle-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.ResultsHere, 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.ConclusionsOur 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.

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/s13059-015-0684-3

Reduced cellular diversity and an altered basal progenitor cell state inform epithelial barrier dysfunction in human type 2 immunity

Tissue barrier dysfunction is a poorly defined feature hypothesized to drive chronic human inflammatory disease1,2. The epithelium of the upper respiratory tract represents one such barrier, responsible for separating inhaled agents, such as pathogens and allergens, from the underlying submucosa. Specialized epithelial subsets—including secretory, glandular, and ciliated cells—differentiate from basal progenitors to collectively realize this role3-5. Allergic inflammation in the upper airway barrier can develop from persistent activation of Type 2 immunity (T2I), resulting in the disease spectrum known as chronic rhinosinusitis (CRS), ranging from rhinitis to severe nasal polyps6-8. Whether recently identified epithelial progenitor subsets, and their differentiation trajectory, contribute to the clinical presentation and barrier dysfunction in T2I-mediated disease in humans remains unexplored3,9,10. Profiling twelve primary human samples spanning the range of clinical severity with the Seq-Well platform11 for massively-parallel single-cell RNA-sequencing (scRNA-seq), we report the first single-cell transcriptomes for human respiratory epithelial cell subsets, immune cells, and parenchymal cells (18,036 total cells) from a T2I inflammatory disease, and map key mediators. We find striking differences between non-polyp and polyp tissues within the epithelial compartments of human T2I cellular ecosystems. More specifically, across 10,383 epithelial cells, we identify a global reduction in epithelial diversity in polyps characterized by basal cell hyperplasia, a concomitant decrease in glandular and ciliated cells, and phenotypic shifts in secretory cell function. We validate these findings through flow cytometry, histology, and bulk tissue RNA-seq of an independent cohort. Furthermore, we detect an aberrant basal progenitor differentiation trajectory in polyps, and uncover cell-intrinsic and extrinsic factors that may lock polyp basal cells into an uncommitted state. Overall, our data define severe T2I barrier dysfunction as a reduction in epithelial diversity, characterized by profound functional shifts stemming from basal cell defects, and nominate a cellular mechanism for the persistence and chronicity of severe human respiratory disease.

Abstract CN07-04: Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq

A single tumor is composed of malignant cells in diverse genetic and epigenetic states, and this diversity presents a significant barrier for targeted therapies. Furthermore, diverse non-malignant cells, such as immune, fibroblasts and endothelial cells shape the tumor microenvironment and are emerging as important drug targets. However, the diversity of cellular states among malignant and non-malignant cells within any tumor remains poorly understood. To begin to address these challenges we applied single-cell RNA-seq to profile >3,000 single cells isolated from 16 fresh human melanomas, and characterized distinct cell types and cell states. We found that malignant cells within the same tumor display transcriptional heterogeneity associated with multiple biological processes. In particular, subpopulations of cells in treatment-naive tumors expressed a transcriptional program associated with resistance to RAF/MEK inhibition, and these were enriched in post-relapsed samples. Among several non-malignant cell types that were identified we focused on tumor-infiltrating T-cells and identified multiple profiles of exhaustion which differed among patients and could be linked to prior immunotherapies. Finally, we used our single cell–derived profiles of cell types within melanoma to deconvolve publicly available bulk tumor profiles and infer interactions between cells in the tumor microenvironment. This work demonstrates the capacity of single cell transcriptomics to offer new insights with implications for both targeted and immune therapies and will be broadly applicable to other tumor types. Citation Format: Itay Tirosh, Benjamin Izar, Sanjay M. Prakadan, Marc H. Wadsworth II, Daniel Treacy, John J. Trombetta, Diana Lu, Asaf Rotem, Christine Lian, George Murphy, Ofir Cohen, Eli van Allen, Monica Bertagnolli, Alex Genshaft, Travis K. Hughes, Carly G. K. Ziegler, Samuel W. Kazer, Aleth Gaillard, Kellie E. Kolb, Judit Valbuena1, Charles Yoon, Orit Rozenblatt-Rosen, Alex K. Shalek, Aviv Regev and Levi Garraway. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr CN07-04.