• Atlas of the Immune Cell Repertoire in Mouse Atherosclerosis Defined by Single-Cell RNA-Sequencing and Mass Cytometry.

      Winkels, Holger; Ehinger, Erik; Vassallo, Melanie; Buscher, Konrad; Dinh, Huy Q; Kobiyama, Kouji; Hamers, Anouk A J; Cochain, Clément; Vafadarnejad, Ehsan; Saliba, Antoine-Emmanuel; et al. (Amercan Heart Association, 2018-03-15)
      Using single-cell RNA-sequencing of aortic leukocytes from chow diet- and Western diet-fed Apoe-/- and Ldlr-/- mice, we detected 11 principal leukocyte clusters with distinct phenotypic and spatial characteristics while the cellular repertoire in healthy aortas was less diverse. Gene set enrichment analysis on the single-cell level established that multiple pathways, such as for lipid metabolism, proliferation, and cytokine secretion, were confined to particular leukocyte clusters. Leukocyte populations were differentially regulated in atherosclerotic Apoe-/- and Ldlr-/- mice. We confirmed the phenotypic diversity of these clusters with a novel mass cytometry 35-marker panel with metal-labeled antibodies and conventional flow cytometry. Cell populations retrieved by these protein-based approaches were highly correlated to transcriptionally defined clusters. In an integrated screening strategy of single-cell RNA-sequencing, mass cytometry, and fluorescence-activated cell sorting, we detected 3 principal B-cell subsets with alterations in surface markers, functional pathways, and in vitro cytokine secretion. Leukocyte cluster gene signatures revealed leukocyte frequencies in 126 human plaques by a genetic deconvolution strategy. This approach revealed that human carotid plaques and microdissected mouse plaques were mostly populated by macrophages, T-cells, and monocytes. In addition, the frequency of genetically defined leukocyte populations in carotid plaques predicted cardiovascular events in patients.
    • Einzelzell-RNA-Sequenzierung beleuchtet den Infektionsprozess

      Saliba, Antoine-Emmanuel; Westermann, Alexander J.; Vogel, Jörg; HIRI, Helmholtz-Institut für RNA-basierte Infektionsforschung, Josef-Schneider-Straße 2, 97080 Würzburg. Germany. (2017-10-11)
    • Eleven grand challenges in single-cell data science.

      Lähnemann, David; Köster, Johannes; Szczurek, Ewa; McCarthy, Davis J; Hicks, Stephanie C; Robinson, Mark D; Vallejos, Catalina A; Campbell, Kieran R; Beerenwinkel, Niko; Mahfouz, Ahmed; et al. (BMC, 2020-02-07)
      The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.
    • Genome organization and DNA accessibility control antigenic variation in trypanosomes.

      Müller, Laura S M; Cosentino, Raúl O; Förstner, Konrad U; Guizetti, Julien; Wedel, Carolin; Kaplan, Noam; Janzen, Christian J; Arampatzi, Panagiota; Vogel, Jörg; Steinbiss, Sascha; et al. (2018-01-01)
      Many evolutionarily distant pathogenic organisms have evolved similar survival strategies to evade the immune responses of their hosts. These include antigenic variation, through which an infecting organism prevents clearance by periodically altering the identity of proteins that are visible to the immune system of the host1. Antigenic variation requires large reservoirs of immunologically diverse antigen genes, which are often generated through homologous recombination, as well as mechanisms to ensure the expression of one or very few antigens at any given time. Both homologous recombination and gene expression are affected by three-dimensional genome architecture and local DNA accessibility2,3. Factors that link three-dimensional genome architecture, local chromatin conformation and antigenic variation have, to our knowledge, not yet been identified in any organism. One of the major obstacles to studying the role of genome architecture in antigenic variation has been the highly repetitive nature and heterozygosity of antigen-gene arrays, which has precluded complete genome assembly in many pathogens. Here we report the de novo haplotype-specific assembly and scaffolding of the long antigen-gene arrays of the model protozoan parasite Trypanosoma brucei, using long-read sequencing technology and conserved features of chromosome folding4. Genome-wide chromosome conformation capture (Hi-C) reveals a distinct partitioning of the genome, with antigen-encoding subtelomeric regions that are folded into distinct, highly compact compartments. In addition, we performed a range of analyses—Hi-C, fluorescence in situ hybridization, assays for transposase-accessible chromatin using sequencing and single-cell RNA sequencing—that showed that deletion of the histone variants H3.V and H4.V increases antigen-gene clustering, DNA accessibility across sites of antigen expression and switching of the expressed antigen isoform, via homologous recombination. Our analyses identify histone variants as a molecular link between global genome architecture, local chromatin conformation and antigenic variation.
    • Salmonella persisters undermine host immune defenses during antibiotic treatment.

      Stapels, Daphne A C; Hill, Peter W S; Westermann, Alexander J; Fisher, Robert A; Thurston, Teresa L; Saliba, Antoine-Emmanuel; Blommestein, Isabelle; Vogel, Jörg; Helaine, Sophie; HIRI, Helmholtz-Institut für RNA-basierte Infektionsforschung, Josef-Shneider Strasse 2, 97080 Würzburg, Germany. (American Association for the Advancement of Science, 2018-12-07)
      Many bacterial infections are hard to treat and tend to relapse, possibly due to the presence of antibiotic-tolerant persisters. In vitro, persister cells appear to be dormant. After uptake of Salmonella species by macrophages, nongrowing persisters also occur, but their physiological state is poorly understood. In this work, we show that Salmonella persisters arising during macrophage infection maintain a metabolically active state. Persisters reprogram macrophages by means of effectors secreted by the Salmonella pathogenicity island 2 type 3 secretion system. These effectors dampened proinflammatory innate immune responses and induced anti-inflammatory macrophage polarization. Such reprogramming allowed nongrowing Salmonella cells to survive for extended periods in their host. Persisters undermining host immune defenses might confer an advantage to the pathogen during relapse once antibiotic pressure is relieved.
    • scSLAM-seq reveals core features of transcription dynamics in single cells.

      Erhard, Florian; Baptista, Marisa A P; Krammer, Tobias; Hennig, Thomas; Lange, Marius; Arampatzi, Panagiota; Jürges, Christopher S; Theis, Fabian J; Saliba, Antoine-Emmanuel; Dölken, Lars; et al. (Springer-Nature, 2019-01-01)
      Single-cell RNA sequencing (scRNA-seq) has highlighted the important role of intercellular heterogeneity in phenotype variability in both health and disease1. However, current scRNA-seq approaches provide only a snapshot of gene expression and convey little information on the true temporal dynamics and stochastic nature of transcription. A further key limitation of scRNA-seq analysis is that the RNA profile of each individual cell can be analysed only once. Here we introduce single-cell, thiol-(SH)-linked alkylation of RNA for metabolic labelling sequencing (scSLAM-seq), which integrates metabolic RNA labelling2, biochemical nucleoside conversion3 and scRNA-seq to record transcriptional activity directly by differentiating between new and old RNA for thousands of genes per single cell. We use scSLAM-seq to study the onset of infection with lytic cytomegalovirus in single mouse fibroblasts. The cell-cycle state and dose of infection deduced from old RNA enable dose-response analysis based on new RNA. scSLAM-seq thereby both visualizes and explains differences in transcriptional activity at the single-cell level. Furthermore, it depicts 'on-off' switches and transcriptional burst kinetics in host gene expression with extensive gene-specific differences that correlate with promoter-intrinsic features (TBP-TATA-box interactions and DNA methylation). Thus, gene-specific, and not cell-specific, features explain the heterogeneity in transcriptomes between individual cells and the transcriptional response to perturbations.