fundamental molecular noise), and gene-extrinsic kinds, with the last mentioned capturing both cell-intrinsic features (e

fundamental molecular noise), and gene-extrinsic kinds, with the last mentioned capturing both cell-intrinsic features (e.g. viral (VSV-g pseudotyped HIV-1) publicity. (XLSX 39 kb) 13059_2017_1385_MOESM5_ESM.xlsx (40K) GUID:?F69B343C-73BC-492F-B10F-10FA283949DD Extra file 6: Desk S5: IPA. Canonical pathways and upstream evaluation for DE outcomes: contrasts for c1 vs c3C5, c2 vs c3C5, c1 vs c2. (XLSX 203 Cladribine kb) 13059_2017_1385_MOESM6_ESM.xlsx (204K) GUID:?F15F417D-B8AD-4DCD-8B2E-92787316409C Extra file 7: AOM. Extra online components. (PDF 243 kb) 13059_2017_1385_MOESM7_ESM.pdf (244K) GUID:?4AB09450-EA32-4698-B66E-B158F633F3F9 Data Availability StatementSingle-cell and bulk RNA-seq data can be found through the Gene Appearance Omnibus (GEO accession “type”:”entrez-geo”,”attrs”:”text”:”GSE108445″,”term_id”:”108445″GSE108445) [56]. This research used two publicly obtainable appearance datasets: (1) Amit et al. 2009 [33], available via GEO accession “type”:”entrez-geo”,”attrs”:”text”:”GSE1772″,”term_id”:”1772″GSE1772; and (2) Chevrier et al. 2011, available via Supplemental Information S7 and S2 provided in [32]. Personal analyses relied on expression signatures defined in MSigDB (http://software.broadinstitute.org/gsea/msigdb). The package is available on GitHub (https://github.com/YosefLab/scRAD) under Artistic License 2.0. Normalized scRNA-seq expression data, meta data, Cladribine and average bulk expression profiles from the TLR induction study are available as data objects in the package. Abstract Background Human immunity relies on the coordinated responses of many cellular subsets and functional states. Inter-individual variations in cellular composition and communication could thus potentially alter host protection. Here, we explore this hypothesis by applying single-cell RNA-sequencing to examine Rabbit Polyclonal to ARBK1 viral responses among the dendritic cells (DCs) of three elite controllers (ECs) of HIV-1 contamination. Results To overcome the potentially confounding effects of donor-to-donor variability, we present a generally applicable computational framework for identifying reproducible patterns in gene expression across donors who share a unifying classification. Applying it, we discover a highly functional antiviral DC state in ECs whose fractional abundance after in vitro exposure to HIV-1 correlates with higher CD4+ T cell counts and lower HIV-1 viral loads, and that effectively primes polyfunctional T cell responses in vitro. By integrating information from existing genomic databases into our reproducibility-based analysis, we identify and validate select immunomodulators that increase Cladribine the fractional abundance of this state in primary peripheral blood mononuclear cells from healthy individuals in vitro. Conclusions Overall, our results demonstrate how single-cell approaches can reveal previously unappreciated, yet important, immune behaviors and empower rational frameworks for modulating systems-level immune responses that may prove therapeutically and prophylactically useful. Electronic supplementary material The online version Cladribine of this article (10.1186/s13059-017-1385-x) contains supplementary material, which is available to authorized users. locus to reduced risk [14]. Similarly, studies of elite controllers (ECs)a rare (~?0.5%) subset of HIV-1 infected individuals who naturally suppress viral replication without combination antiretroviral therapy (cART) [15, 16]have highlighted the importance of specific variants and enhanced cytotoxic CD8+ T cell responses [17, 18]. Although compelling, these findings have confirmed insufficient to explain the frequency of viral control in the general population; additional cellular components or interactions could be implicated in coordinating effective host defense. Moreover, these studies have not suggested clinically actionable targets for eliciting an EC-like phenotype in other HIV-1-infected individuals. Further work has exhibited improved crosstalk between the innate and adaptive immune systems of ECs [19C21]. For example, we recently reported that enhanced cell-intrinsic responses to HIV-1 in primary myeloid dendritic cells (mDCs) from ECs lead to effective priming of HIV-1-specific CD8+ T cell responses in vitro [20]. Nevertheless, the grasp regulators driving this mDC functional state, the fraction of EC mDCs that assume it, its biomarkers, and how to potentially enrich for it are unknown. The recent emergence of single-cell RNA-sequencing (scRNA-seq) affords a direct means of identifying and comprehensively characterizing functionally important subsets of cells and their complex underlying biology. As scRNA-seq has matured into a mainstream technology, new questions about how to model single-cell variation continue to arise. To date, computational modeling approaches have typically described single-cell heterogeneity as a combination of gene-intrinsic effects (i.e. fundamental molecular noise), and gene-extrinsic ones, with the latter capturing both cell-intrinsic features (e.g. differences in intracellular protein levels, epigenetic state, mutation status, extracellular environment) and library-intrinsic technical artifacts (e.g. drop-out effects). Yet, in single-cell studies that utilize samples from across multiple donors (e.g. EC patients), these gene-extrinsic sources can be further subdivided into those that are unique to specific donors and those that are shared. The category of donor-dependent variation ranges from donor-specific cell subsets or large differences in cell-type composition to more subtle expression differences in constituent cell types. If the goal of a study is usually to generate hypotheses relating.