抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.

/pdf/integrating-single-cell-transcriptomic-data-across-different-3dtsi5w7ob.pdf

Integrating single-cell transcriptomic data across different conditions, technologies, and species.

https://www.cell.com/cell/pdf/S0092-8674(15)00549-8.pdf

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets

We describe an assay for transposase-accessible chromatin using sequencing (ATAC-seq), based on direct in vitro transposition of sequencing adaptors into native chromatin, as a rapid and sensitive method for integrative epigenomic analysis. ATAC-seq captures open chromatin sites using a simple two-step protocol with 500-50,000 cells and reveals the interplay between genomic locations of open chromatin, DNA-binding proteins, individual nucleosomes and chromatin compaction at nucleotide resolution. We discovered classes of DNA-binding factors that strictly avoided, could tolerate or tended to overlap with nucleosomes. Using ATAC-seq maps of human CD4(+) T cells from a proband obtained on consecutive days, we demonstrated the feasibility of analyzing an individual's epigenome on a timescale compatible with clinical decision-making.

Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

Nature 516, 56–61 (2014); doi:10.1038/nature13920 In this Letter, owing to a production error, in Fig. 3e the sixth bar from the left was inadvertently labelled ‘Dgcr8−/− FF’ instead of ‘Dicer−/− FF’. This has now been corrected in the online versions of the paper.

/pdf/erratum-deconstructing-transcriptional-heterogeneity-in-3vqqydh5hv.pdf

Erratum: Deconstructing transcriptional heterogeneity in pluripotent stem cells

Tumors are heterogeneous ecosystems composed of genetically and epigenetically distinct cancer cell populations embedded in an intricate tumor microenvironment. The complexity and cell-to-cell interactions within this system pose a tremendous therapeutic challenge and opportunity. Due to technical constraints, current profiling technologies only provide average signals that do not reflect this intrinsic genetic and phenotypic variability. Here, we applied single-cell RNA-sequencing to examine 4,645 single cells isolated from 19 freshly procured melanomas, profiling malignant, immune and stromal cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, stem-like cells, spatial context, and a drug treatment resistance program. All tumors harbored malignant cells from two distinct transcriptional cell states, such that treatment-sensitive “MITF-high” tumors also contained drug-resistant “AXL-high” tumor cells; similar heterogeneity was present in 18 established melanoma cell lines. The frequency of AXL-high cells increased in post-relapse resistant tumors following treatment with BRAF/MEK inhibitors. Using multiplexed, quantitative single-cell immunofluorescence analysis and FACS, we validated these observations in melanoma cell lines treated with BRAF±MEK inhibitors. Signatures of cell types identified from single-cell analysis revealed distinct patterns of the tumor microenvironment. We inferred cell-to-cell interactions between stromal, immune and malignant cells, and identified factors, including known secreted gene products (e.g. CXCL12) and several complement factors. We validated the association between cancer-associated fibroblast (CAF)-expressed complement factor 3 (C3) and TIL infiltration in an independent set of 308 melanomas. Finally, analysis of TILs revealed T-cell activation dependent and independent exhaustion programs that varied among patients dependent on their exposure to treatment with immune checkpoint-inhibitors. In addition to co-expression of several known co-inhibitory receptors, including PD1, CTLA-4, and TIM-3, we identified common markers associated with cytotoxicity-independent T-cell exhaustion across patients. To identify potential T-cell clones, we classified single T-cells by their isoforms of the V and J segments of the alpha and beta TCR chains, allowing us to identify expanded T-cell clones. We found that clonally expanded T-cells expressed a strong exhaustion program, while non-expanded T-cells lacked this phenotype. This study represents the most comprehensive single-cell genomics analysis in humans to date and begins to unravel the cellular ecosystem of tumors. Single-cell genomics offer new insights with implications for both targeted and immune therapies by simultaneously profiling numerous aspects of a tumor with a single assay. Citation Format: Benjamin Izar, Itay Tirsh, Sanjay Prakadan, Marc Wadsworth, Daniel Treacy, John Trombetta, Asaf Rotem, Christine Lian, George Murphy, Mohammad Fallahi-Sichani, Ken Dutton-Regester, Jia-Ren Lin, Judit Jane-Valbuena, Orit Rozenblatt-Rosen, Charles Yoon, Alex Shalek, Aviv Regev, Levi Garraway. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-sequencing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4380.

John J. Trombetta

Papers

Erratum: Deconstructing transcriptional heterogeneity in pluripotent stem cells

Abstract 4380: Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-sequencing

Pathogen Cell-to-Cell Variability Drives Heterogeneity in Host Immune Responses