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1.
Nat Immunol ; 21(12): 1597-1610, 2020 12.
Artigo em Inglês | MEDLINE | ID: mdl-33046889

RESUMO

The dynamics of CD4+ T cell memory development remain to be examined at genome scale. In malaria-endemic regions, antimalarial chemoprevention protects long after its cessation and associates with effects on CD4+ T cells. We applied single-cell RNA sequencing and computational modelling to track memory development during Plasmodium infection and treatment. In the absence of central memory precursors, two trajectories developed as T helper 1 (TH1) and follicular helper T (TFH) transcriptomes contracted and partially coalesced over three weeks. Progeny of single clones populated TH1 and TFH trajectories, and fate-mapping suggested that there was minimal lineage plasticity. Relationships between TFH and central memory were revealed, with antimalarials modulating these responses and boosting TH1 recall. Finally, single-cell epigenomics confirmed that heterogeneity among effectors was partially reset in memory. Thus, the effector-to-memory transition in CD4+ T cells is gradual during malaria and is modulated by antiparasitic drugs. Graphical user interfaces are presented for examining gene-expression dynamics and gene-gene correlations ( http://haquelab.mdhs.unimelb.edu.au/cd4_memory/ ).


Assuntos
Linfócitos T CD4-Positivos/imunologia , Linfócitos T CD4-Positivos/metabolismo , Memória Imunológica , Malária/imunologia , Plasmodium/imunologia , Transcriptoma , Transferência Adotiva , Animais , Antimaláricos/farmacologia , Biomarcadores , Cromatina/genética , Modelos Animais de Doenças , Perfilação da Expressão Gênica , Humanos , Malária/parasitologia , Malária/terapia , Camundongos , Plasmodium/efeitos dos fármacos
2.
Mol Cell ; 72(1): 7-9, 2018 10 04.
Artigo em Inglês | MEDLINE | ID: mdl-30290149

RESUMO

Applying a kinetic model of RNA transcription and splicing, La Manno et al. (2018) predict changes in mRNA levels of individual cells from single-cell RNA-seq data.


Assuntos
Splicing de RNA , RNA , Cinética , RNA Mensageiro
3.
Mol Cell ; 58(4): 610-20, 2015 May 21.
Artigo em Inglês | MEDLINE | ID: mdl-26000846

RESUMO

The differences between individual cells can have profound functional consequences, in both unicellular and multicellular organisms. Recently developed single-cell mRNA-sequencing methods enable unbiased, high-throughput, and high-resolution transcriptomic analysis of individual cells. This provides an additional dimension to transcriptomic information relative to traditional methods that profile bulk populations of cells. Already, single-cell RNA-sequencing methods have revealed new biology in terms of the composition of tissues, the dynamics of transcription, and the regulatory relationships between genes. Rapid technological developments at the level of cell capture, phenotyping, molecular biology, and bioinformatics promise an exciting future with numerous biological and medical applications.


Assuntos
Perfilação da Expressão Gênica/métodos , Redes Reguladoras de Genes , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Processamento Alternativo , Animais , Linhagem da Célula/genética , Variação Genética , Humanos , Modelos Genéticos
4.
Nat Methods ; 15(5): 343-346, 2018 05.
Artigo em Inglês | MEDLINE | ID: mdl-29553579

RESUMO

Technological advances have made it possible to measure spatially resolved gene expression at high throughput. However, methods to analyze these data are not established. Here we describe SpatialDE, a statistical test to identify genes with spatial patterns of expression variation from multiplexed imaging or spatial RNA-sequencing data. SpatialDE also implements 'automatic expression histology', a spatial gene-clustering approach that enables expression-based tissue histology.


Assuntos
Transporte Proteico/fisiologia , Análise de Célula Única/métodos , Neoplasias da Mama/metabolismo , Feminino , Regulação Neoplásica da Expressão Gênica/fisiologia , Humanos , Modelos Biológicos
5.
Bioinformatics ; 36(11): 3418-3421, 2020 06 01.
Artigo em Inglês | MEDLINE | ID: mdl-32176273

RESUMO

MOTIVATION: Single-cell RNA-seq makes possible the investigation of variability in gene expression among cells, and dependence of variation on cell type. Statistical inference methods for such analyses must be scalable, and ideally interpretable. RESULTS: We present an approach based on a modification of a recently published highly scalable variational autoencoder framework that provides interpretability without sacrificing much accuracy. We demonstrate that our approach enables identification of gene programs in massive datasets. Our strategy, namely the learning of factor models with the auto-encoding variational Bayes framework, is not domain specific and may be useful for other applications. AVAILABILITY AND IMPLEMENTATION: The factor model is available in the scVI package hosted at https://github.com/YosefLab/scVI/. CONTACT: v@nxn.se. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
RNA-Seq , Análise de Célula Única , Teorema de Bayes , Análise de Sequência de RNA , Software , Sequenciamento do Exoma
6.
Nat Methods ; 14(4): 381-387, 2017 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-28263961

RESUMO

Single-cell RNA sequencing (scRNA-seq) has become an established and powerful method to investigate transcriptomic cell-to-cell variation, thereby revealing new cell types and providing insights into developmental processes and transcriptional stochasticity. A key question is how the variety of available protocols compare in terms of their ability to detect and accurately quantify gene expression. Here, we assessed the protocol sensitivity and accuracy of many published data sets, on the basis of spike-in standards and uniform data processing. For our workflow, we developed a flexible tool for counting the number of unique molecular identifiers (https://github.com/vals/umis/). We compared 15 protocols computationally and 4 protocols experimentally for batch-matched cell populations, in addition to investigating the effects of spike-in molecular degradation. Our analysis provides an integrated framework for comparing scRNA-seq protocols.


Assuntos
Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Animais , Células-Tronco Embrionárias/fisiologia , Congelamento , Camundongos , Poli A , RNA Mensageiro , Sensibilidade e Especificidade , Análise de Sequência de RNA/normas , Análise de Sequência de RNA/estatística & dados numéricos , Análise de Célula Única/normas , Análise de Célula Única/estatística & dados numéricos , Fluxo de Trabalho
8.
Database (Oxford) ; 20202020 11 28.
Artigo em Inglês | MEDLINE | ID: mdl-33247933

RESUMO

The more than 1000 single-cell transcriptomics studies that have been published to date constitute a valuable and vast resource for biological discovery. While various 'atlas' projects have collated some of the associated datasets, most questions related to specific tissue types, species or other attributes of studies require identifying papers through manual and challenging literature search. To facilitate discovery with published single-cell transcriptomics data, we have assembled a near exhaustive, manually curated database of single-cell transcriptomics studies with key information: descriptions of the type of data and technologies used, along with descriptors of the biological systems studied. Additionally, the database contains summarized information about analysis in the papers, allowing for analysis of trends in the field. As an example, we show that the number of cell types identified in scRNA-seq studies is proportional to the number of cells analysed. Database URL: www.nxn.se/single-cell-studies/gui.


Assuntos
Transcriptoma , Bases de Dados Factuais , Transcriptoma/genética
9.
Genome Biol ; 21(1): 39, 2020 02 18.
Artigo em Inglês | MEDLINE | ID: mdl-32070398

RESUMO

The simultaneous quantification of protein and RNA makes possible the inference of past, present, and future cell states from single experimental snapshots. To enable such temporal analysis from multimodal single-cell experiments, we introduce an extension of the RNA velocity method that leverages estimates of unprocessed transcript and protein abundances to extrapolate cell states. We apply the model to six datasets and demonstrate consistency among cell landscapes and phase portraits. The analysis software is available as the protaccel Python package.


Assuntos
Genômica/métodos , Proteoma/genética , Análise de Célula Única/métodos , Transcriptoma , Algoritmos , Humanos , Monócitos/metabolismo , Proteoma/metabolismo , Splicing de RNA
10.
JCI Insight ; 5(13)2020 07 09.
Artigo em Inglês | MEDLINE | ID: mdl-32484791

RESUMO

Acute gastrointestinal (GI) graft-versus-host disease (GVHD) is a primary determinant of mortality after allogeneic hematopoietic stem cell transplantation (alloSCT). The condition is mediated by alloreactive donor CD4+ T cells that differentiate into pathogenic subsets expressing IFN-γ, IL-17A, or GM-CSF and is regulated by subsets expressing IL-10 and/or Foxp3. Developmental relationships between Th cell states during priming in mesenteric lymph nodes (mLNs) and effector function in the GI tract remain undefined at genome scale. We applied scRNA-Seq and computational modeling to a mouse model of donor DC-mediated GVHD exacerbation, creating an atlas of putative CD4+ T cell differentiation pathways in vivo. Computational trajectory inference suggested emergence of pathogenic and regulatory states along a single developmental trajectory in mLNs. Importantly, we inferred an unexpected second trajectory, categorized by little proliferation or cytokine expression, reduced glycolysis, and high tcf7 expression. TCF1hi cells upregulated α4ß7 before gut migration and failed to express cytokines. These cells exhibited recall potential and plasticity following secondary transplantation, including cytokine or Foxp3 expression, but reduced T cell factor 1 (TCF1). Thus, scRNA-Seq suggested divergence of alloreactive CD4+ T cells into quiescent and effector states during gut GVHD exacerbation by donor DC, reflecting putative heterogeneous priming in vivo. These findings, which are potentially the first at a single-cell level during GVHD over time, may assist in examination of T cell differentiation in patients undergoing alloSCT.


Assuntos
Linfócitos T CD4-Positivos/imunologia , Doença Enxerto-Hospedeiro/imunologia , Doença Enxerto-Hospedeiro/patologia , Ativação Linfocitária/imunologia , Transcriptoma/genética , Animais , Microbioma Gastrointestinal/genética , Doença Enxerto-Hospedeiro/genética , Camundongos Endogâmicos BALB C , Camundongos Endogâmicos C57BL , Transplante Homólogo/métodos
11.
Nat Commun ; 11(1): 586, 2020 Jan 29.
Artigo em Inglês | MEDLINE | ID: mdl-31996681

RESUMO

The endothelial to haematopoietic transition (EHT) is the process whereby haemogenic endothelium differentiates into haematopoietic stem and progenitor cells (HSPCs). The intermediary steps of this process are unclear, in particular the identity of endothelial cells that give rise to HSPCs is unknown. Using single-cell transcriptome analysis and antibody screening, we identify CD44 as a marker of EHT enabling us to isolate robustly the different stages of EHT in the aorta-gonad-mesonephros (AGM) region. This allows us to provide a detailed phenotypical and transcriptional profile of CD44-positive arterial endothelial cells from which HSPCs emerge. They are characterized with high expression of genes related to Notch signalling, TGFbeta/BMP antagonists, a downregulation of genes related to glycolysis and the TCA cycle, and a lower rate of cell cycle. Moreover, we demonstrate that by inhibiting the interaction between CD44 and its ligand hyaluronan, we can block EHT, identifying an additional regulator of HSPC development.


Assuntos
Biomarcadores , Endotélio/metabolismo , Células-Tronco Hematopoéticas/metabolismo , Receptores de Hialuronatos/metabolismo , Transcriptoma , Animais , Aorta , Artérias , Ciclo Celular , Ciclo do Ácido Cítrico/genética , Biologia Computacional , Subunidade alfa 2 de Fator de Ligação ao Core/genética , Regulação para Baixo , Glicólise/genética , Gônadas , Hematopoese/fisiologia , Receptores de Hialuronatos/sangue , Receptores de Hialuronatos/genética , Ácido Hialurônico , Mesonefro , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Knockout , Fator de Crescimento Transformador beta/metabolismo
12.
Nat Protoc ; 13(4): 599-604, 2018 04.
Artigo em Inglês | MEDLINE | ID: mdl-29494575

RESUMO

Measurement of the transcriptomes of single cells has been feasible for only a few years, but it has become an extremely popular assay. While many types of analysis can be carried out and various questions can be answered by single-cell RNA-seq, a central focus is the ability to survey the diversity of cell types in a sample. Unbiased and reproducible cataloging of gene expression patterns in distinct cell types requires large numbers of cells. Technological developments and protocol improvements have fueled consistent and exponential increases in the number of cells that can be studied in single-cell RNA-seq analyses. In this Perspective, we highlight the key technological developments that have enabled this growth in the data obtained from single-cell RNA-seq experiments.


Assuntos
Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Perfilação da Expressão Gênica/história , Perfilação da Expressão Gênica/tendências , História do Século XXI , Análise de Sequência de RNA/história , Análise de Sequência de RNA/tendências , Análise de Célula Única/história , Análise de Célula Única/tendências
13.
Sci Rep ; 8(1): 685, 2018 01 12.
Artigo em Inglês | MEDLINE | ID: mdl-29330484

RESUMO

The crucial capability of T cells for discrimination between self and non-self peptides is based on negative selection of developing thymocytes by medullary thymic epithelial cells (mTECs). The mTECs purge autoreactive T cells by expression of cell-type specific genes referred to as tissue-restricted antigens (TRAs). Although the autoimmune regulator (AIRE) protein is known to promote the expression of a subset of TRAs, its mechanism of action is still not fully understood. The expression of TRAs that are not under the control of AIRE also needs further characterization. Furthermore, expression patterns of TRA genes have been suggested to change over the course of mTEC development. Herein we have used single-cell RNA-sequencing to resolve patterns of TRA expression during mTEC development. Our data indicated that mTEC development consists of three distinct stages, correlating with previously described jTEC, mTEChi and mTEClo phenotypes. For each subpopulation, we have identified marker genes useful in future studies. Aire-induced TRAs were switched on during jTEC-mTEC transition and were expressed in genomic clusters, while otherwise the subsets expressed largely overlapping sets of TRAs. Moreover, population-level analysis of TRA expression frequencies suggested that such differences might not be necessary to achieve efficient thymocyte selection.


Assuntos
Autoantígenos/genética , Células Epiteliais/metabolismo , RNA/metabolismo , Animais , Autoantígenos/metabolismo , Diferenciação Celular , Células Epiteliais/citologia , Feminino , Fase G1 , Redes Reguladoras de Genes/genética , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Análise de Componente Principal , RNA/química , RNA/isolamento & purificação , Análise de Sequência de RNA , Análise de Célula Única , Timo/citologia , Fatores de Transcrição/metabolismo , Transcriptoma , Proteína AIRE
14.
FEBS Lett ; 591(15): 2213-2225, 2017 08.
Artigo em Inglês | MEDLINE | ID: mdl-28524227

RESUMO

The recent developments in high-throughput single-cell RNA sequencing technology (scRNA-seq) have enabled the generation of vast amounts of transcriptomic data at cellular resolution. With these advances come new modes of data analysis, building on high-dimensional data mining techniques. Here, we consider biological questions for which scRNA-seq data is used, both at a cell and gene level, and describe tools available for these types of analyses. This is an exciting and rapidly evolving field, where clustering, pseudotime inference, branching inference and gene-level analyses are particularly informative areas of computational analysis.


Assuntos
Biologia Computacional/métodos , Expressão Gênica , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Animais , Análise por Conglomerados , Humanos
15.
Sci Immunol ; 2(9)2017 Mar 03.
Artigo em Inglês | MEDLINE | ID: mdl-28345074

RESUMO

Differentiation of naïve CD4+ T cells into functionally distinct T helper subsets is crucial for the orchestration of immune responses. Due to extensive heterogeneity and multiple overlapping transcriptional programs in differentiating T cell populations, this process has remained a challenge for systematic dissection in vivo. By using single-cell transcriptomics and computational analysis using a temporal mixtures of Gaussian processes model, termed GPfates, we reconstructed the developmental trajectories of Th1 and Tfh cells during blood-stage Plasmodium infection in mice. By tracking clonality using endogenous TCR sequences, we first demonstrated that Th1/Tfh bifurcation had occurred at both population and single-clone levels. Next, we identified genes whose expression was associated with Th1 or Tfh fates, and demonstrated a T-cell intrinsic role for Galectin-1 in supporting a Th1 differentiation. We also revealed the close molecular relationship between Th1 and IL-10-producing Tr1 cells in this infection. Th1 and Tfh fates emerged from a highly proliferative precursor that upregulated aerobic glycolysis and accelerated cell cycling as cytokine expression began. Dynamic gene expression of chemokine receptors around bifurcation predicted roles for cell-cell in driving Th1/Tfh fates. In particular, we found that precursor Th cells were coached towards a Th1 but not a Tfh fate by inflammatory monocytes. Thus, by integrating genomic and computational approaches, our study has provided two unique resources, a database www.PlasmoTH.org, which facilitates discovery of novel factors controlling Th1/Tfh fate commitment, and more generally, GPfates, a modelling framework for characterizing cell differentiation towards multiple fates.

18.
Cell Rep ; 14(4): 966-977, 2016 Feb 02.
Artigo em Inglês | MEDLINE | ID: mdl-26804912

RESUMO

The transcriptional programs that govern hematopoiesis have been investigated primarily by population-level analysis of hematopoietic stem and progenitor cells, which cannot reveal the continuous nature of the differentiation process. Here we applied single-cell RNA-sequencing to a population of hematopoietic cells in zebrafish as they undergo thrombocyte lineage commitment. By reconstructing their developmental chronology computationally, we were able to place each cell along a continuum from stem cell to mature cell, refining the traditional lineage tree. The progression of cells along this continuum is characterized by a highly coordinated transcriptional program, displaying simultaneous suppression of genes involved in cell proliferation and ribosomal biogenesis as the expression of lineage specific genes increases. Within this program, there is substantial heterogeneity in the expression of the key lineage regulators. Overall, the total number of genes expressed, as well as the total mRNA content of the cell, decreases as the cells undergo lineage commitment.


Assuntos
Regulação da Expressão Gênica no Desenvolvimento , Hematopoese , Células-Tronco Hematopoéticas/metabolismo , Transcriptoma , Animais , Linhagem da Célula , Simulação por Computador , Células-Tronco Hematopoéticas/citologia , Análise de Sequência de RNA , Análise de Célula Única , Peixe-Zebra
19.
Cell Rep ; 17(1): 179-192, 2016 09 27.
Artigo em Inglês | MEDLINE | ID: mdl-27681430

RESUMO

Mouse embryonic stem cells are dynamic and heterogeneous. For example, rare cells cycle through a state characterized by decondensed chromatin and expression of transcripts, including the Zscan4 cluster and MERVL endogenous retrovirus, which are usually restricted to preimplantation embryos. Here, we further characterize the dynamics and consequences of this transient cell state. Single-cell transcriptomics identified the earliest upregulated transcripts as cells enter the MERVL/Zscan4 state. The MERVL/Zscan4 transcriptional network was also upregulated during induced pluripotent stem cell reprogramming. Genome-wide DNA methylation and chromatin analyses revealed global DNA hypomethylation accompanying increased chromatin accessibility. This transient DNA demethylation was driven by a loss of DNA methyltransferase proteins in the cells and occurred genome-wide. While methylation levels were restored once cells exit this state, genomic imprints remained hypomethylated, demonstrating a potential global and enduring influence of endogenous retroviral activation on the epigenome.


Assuntos
Retrovirus Endógenos/genética , Epigênese Genética , Genoma , Células-Tronco Embrionárias Murinas/metabolismo , Fatores de Transcrição/genética , Transcriptoma , Animais , Ciclo Celular/genética , Reprogramação Celular , Cromatina/química , Cromatina/metabolismo , Metilação de DNA , Metilases de Modificação do DNA/deficiência , Metilases de Modificação do DNA/genética , Retrovirus Endógenos/metabolismo , Impressão Genômica , Células-Tronco Pluripotentes Induzidas/citologia , Células-Tronco Pluripotentes Induzidas/metabolismo , Camundongos , Células-Tronco Embrionárias Murinas/citologia , Família Multigênica , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , Análise de Célula Única , Fatores de Transcrição/metabolismo , Ativação Transcricional
20.
Genome Biol ; 17: 103, 2016 May 12.
Artigo em Inglês | MEDLINE | ID: mdl-27176874

RESUMO

BACKGROUND: Differentiation of lymphocytes is frequently accompanied by cell cycle changes, interplay that is of central importance for immunity but is still incompletely understood. Here, we interrogate and quantitatively model how proliferation is linked to differentiation in CD4+ T cells. RESULTS: We perform ex vivo single-cell RNA-sequencing of CD4+ T cells during a mouse model of infection that elicits a type 2 immune response and infer that the differentiated, cytokine-producing cells cycle faster than early activated precursor cells. To dissect this phenomenon quantitatively, we determine expression profiles across consecutive generations of differentiated and undifferentiated cells during Th2 polarization in vitro. We predict three discrete cell states, which we verify by single-cell quantitative PCR. Based on these three states, we extract rates of death, division and differentiation with a branching state Markov model to describe the cell population dynamics. From this multi-scale modelling, we infer a significant acceleration in proliferation from the intermediate activated cell state to the mature cytokine-secreting effector state. We confirm this acceleration both by live imaging of single Th2 cells and in an ex vivo Th1 malaria model by single-cell RNA-sequencing. CONCLUSION: The link between cytokine secretion and proliferation rate holds both in Th1 and Th2 cells in vivo and in vitro, indicating that this is likely a general phenomenon in adaptive immunity.


Assuntos
Linfócitos T CD4-Positivos/citologia , Diferenciação Celular , Proliferação de Células , Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Animais , Linfócitos T CD4-Positivos/metabolismo , Linfócitos T CD4-Positivos/fisiologia , Células Cultivadas , Citocinas/genética , Citocinas/metabolismo , Feminino , Malária/genética , Camundongos , Camundongos Endogâmicos C57BL , Modelos Biológicos , Transcriptoma
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