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  • 1
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 376, No. 6594 ( 2022-05-13)
    Abstract: Although the genome is often called the blueprint of an organism, it is perhaps more accurate to describe it as a parts list composed of the various genes that may or may not be used in the different cell types of a multicellular organism. Although nearly every cell in the body has essentially the same genome, each cell type makes different use of that genome and expresses a subset of all possible genes. This has motivated efforts to characterize the molecular composition of various cell types within humans and multiple model organisms, both by transcriptional and proteomic approaches. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. RATIONALE One caveat to current approaches to make cell atlases is that individual organs are often collected at different locations, collected from different donors, and processed using different protocols. Controlled comparisons of cell types between different tissues and organs are especially difficult when donors differ in genetic background, age, environmental exposure, and epigenetic effects. To address this, we developed an approach to analyzing large numbers of organs from the same individual. RESULTS We collected multiple tissues from individual human donors and performed coordinated single-cell transcriptome analyses on live cells. The donors come from a range of ethnicities, are balanced by gender, have a mean age of 51 years, and have a variety of medical backgrounds. Tissue experts used a defined cell ontology terminology to annotate cell types consistently across the different tissues, leading to a total of 475 distinct cell types with reference transcriptome profiles. The full dataset can be explored online with the cellxgene tool. Data were collected for the bladder, blood, bone marrow, eye, fat, heart, kidney, large intestine, liver, lung, lymph node, mammary, muscle, pancreas, prostate, salivary gland, skin, small intestine, spleen, thymus, tongue, trachea, uterus, and vasculature. Fifty-nine separate specimens in total were collected, processed, and analyzed, and 483,152 cells passed quality control filtering. On a per-compartment basis, the dataset includes 264,824 immune cells, 104,148 epithelial cells, 31,691 endothelial cells, and 82,478 stromal cells. Working with live cells, as opposed to isolated nuclei, ensured that the dataset includes all mRNA transcripts within the cell, including transcripts that have been processed by the cell’s splicing machinery, thereby enabling insight into variation in alternative splicing. The Tabula Sapiens also provided an opportunity to densely and directly sample the human microbiome throughout the gastrointestinal tract. The intestines from two donors were sectioned into five regions: the duodenum, jejunum, ileum, and ascending and sigmoid colon. Each section was transected, and three to nine samples were collected from each location, followed by amplification and sequencing of the 16 S ribosomal RNA gene. CONCLUSION The Tabula Sapiens has revealed discoveries relating to shared behavior and subtle, organ-specific differences across cell types. We found T cell clones shared between organs and characterized organ-dependent hypermutation rates among B cells. Endothelial cells and macrophages are shared across tissues, often showing subtle but clear differences in gene expression. We found an unexpectedly large and diverse amount of cell type–specific RNA splice variant usage and discovered and validated many previously undefined splices. The intestinal microbiome was revealed to have nonuniform species distributions down to the 3-inch (7.62-cm) length scale. These are but a few examples of how the Tabula Sapiens represents a broadly useful reference to deeply understand and explore human biology at cellular resolution. Overview of Tabula Sapiens. Molecular characterization of cell types using single-cell transcriptome sequencing is revolutionizing cell biology and enabling new insights into the physiology of human organs. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This multimodal atlas enabled molecular characterization of more than 400 cell types.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2022
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  • 2
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    American Association for the Advancement of Science (AAAS) ; 2016
    In:  Science Vol. 354, No. 6308 ( 2016-10-07), p. 64-68
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 354, No. 6308 ( 2016-10-07), p. 64-68
    Abstract: Cells of the immune system routinely respond to cues from their local environment and feed back to their surroundings through transient responses, choice of differentiation trajectories, plastic changes in cell state, and malleable adaptation to their tissue of residence. Genomic approaches have opened the way for comprehensive interrogation of such orchestrated responses. Focusing on genomic profiling of transcriptional and epigenetic cell states, we discuss how they are applied to investigate immune cells faced with various environmental cues. We highlight some of the emerging principles on the role of dense regulatory circuitry, epigenetic memory, cell type fluidity, and reuse of regulatory modules in achieving and maintaining appropriate responses to a changing environment. These provide a first step toward a systematic understanding of molecular circuits in complex tissues.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2016
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  • 3
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    Online Resource
    Proceedings of the National Academy of Sciences ; 2013
    In:  Proceedings of the National Academy of Sciences Vol. 110, No. 5 ( 2013-01-29), p. 1815-1820
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 110, No. 5 ( 2013-01-29), p. 1815-1820
    Abstract: Breast tumors lacking expression of human epidermal growth factor receptor 2 (HER2) and the estrogen and the progesterone receptors (triple negative; TNBC) are more aggressive than other disease subtypes, and no molecular targeted agents are currently available for their treatment. Because TNBC commonly displays EGF receptor (EGFR) expression, and combinations of monoclonal antibodies to EGFR effectively inhibit other tumor models, we addressed the relevance of this strategy to treatment of TNBC. Unlike a combination of the clinically approved monoclonal antibodies, cetuximab and panitumumab, which displaced each other and displayed no cooperative effects, several other combinations resulted in enhanced inhibition of TNBC’s cell growth both in vitro and in animals. The ability of certain antibody mixtures to remove EGFR from the cell surface and to promote its intracellular degradation correlated with the inhibitory potential. However, unlike EGF-induced sorting of EGFR to lysosomal degradation, the antibody-induced pathway displayed independence from the intrinsic kinase activity and dimer formation ability of EGFR, and it largely avoided the recycling route. In conclusion, although TNBC clinical trials testing EGFR inhibitors reported lack of benefit, our results offer an alternative strategy that combines noncompetitive antibodies to achieve robust degradation of EGFR and tumor inhibition.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2013
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  • 4
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    Online Resource
    Proceedings of the National Academy of Sciences ; 2013
    In:  Proceedings of the National Academy of Sciences Vol. 110, No. 19 ( 2013-05-07), p. 7802-7807
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 110, No. 19 ( 2013-05-07), p. 7802-7807
    Abstract: IL-27–induced type 1 regulatory T (Tr1) cells suppress autoimmunity by producing IL-10. Signal transducer and activator of transcription (STAT) 1 and STAT3 have been described as key transcription factors that promote IL-10 secretion from Tr1 cells induced by IL-27. However, the molecular pathways for negatively regulating Tr1 cell differentiation remain elusive. Here, we show that IL-27 induces metallothioneins (MTs) that in turn prevent Tr1 cell development. MT expression leads to the reduction of STAT1 and STAT3 phosphorylation under Tr1 differentiation condition, resulting in impaired IL-10 production. Accordingly, Tr1 cells derived from MT-deficient mice showed an increased ability to produce IL-10 and potently suppress experimental autoimmune encephalomyelitis upon adoptive transfer. Moreover, activation of STAT1 and/or STAT3 can overcome the suppression of IL-10 by MTs, indicating a dynamic balance between STATs and MTs in regulating IL-10 during Tr1 cell differentiation.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2013
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  • 5
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 112, No. 13 ( 2015-03-31)
    Abstract: Systematic characterization of intercellular signaling approximating the physiological conditions of stimulation that involve direct cell–cell contact is challenging. We describe a proteomic strategy to analyze physiological signaling mediated by the T-cell costimulatory receptor CD28. We identified signaling pathways activated by CD28 during direct cell–cell contact by global analysis of protein phosphorylation. To define immediate CD28 targets, we used phosphorylated forms of the CD28 cytoplasmic region to obtain the CD28 interactome. The interaction profiles of selected CD28-interacting proteins were further characterized in vivo for amplifying the CD28 interactome. The combination of the global phosphorylation and interactome analyses revealed broad regulation of CD28 and its interactome by phosphorylation. Among the cellular phosphoproteins influenced by CD28 signaling, CapZ-interacting protein (CapZIP), a regulator of the actin cytoskeleton, was implicated by functional studies. The combinatorial approach applied herein is widely applicable for characterizing signaling networks associated with membrane receptors with short cytoplasmic tails.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2015
    detail.hit.zdb_id: 209104-5
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  • 6
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 354, No. 6316 ( 2016-12-02), p. 1165-1169
    Abstract: Exhausted T cells in cancer and chronic viral infection express distinctive patterns of genes, including sustained expression of programmed cell death protein 1 (PD-1). However, the regulation of gene expression in exhausted T cells is poorly understood. Here, we define the accessible chromatin landscape in exhausted CD8 + T cells and show that it is distinct from functional memory CD8 + T cells. Exhausted CD8 + T cells in humans and a mouse model of chronic viral infection acquire a state-specific epigenetic landscape organized into functional modules of enhancers. Genome editing shows that PD-1 expression is regulated in part by an exhaustion-specific enhancer that contains essential RAR, T-bet, and Sox3 motifs. Functional enhancer maps may offer targets for genome editing that alter gene expression preferentially in exhausted CD8 + T cells.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2016
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  • 7
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    Online Resource
    American Association for the Advancement of Science (AAAS) ; 2021
    In:  Science Vol. 371, No. 6532 ( 2021-02-26)
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 371, No. 6532 ( 2021-02-26)
    Abstract: Detailed phylogenies of tumor populations can recount the history and chronology of critical events during cancer progression, such as metastatic dissemination. We applied a Cas9-based, single-cell lineage tracer to study the rates, routes, and drivers of metastasis in a lung cancer xenograft mouse model. We report deeply resolved phylogenies for tens of thousands of cancer cells traced over months of growth and dissemination. This revealed stark heterogeneity in metastatic capacity, arising from preexisting and heritable differences in gene expression. We demonstrate that these identified genes can drive invasiveness and uncovered an unanticipated suppressive role for KRT17 . We also show that metastases disseminated via multidirectional tissue routes and complex seeding topologies. Overall, we demonstrate the power of tracing cancer progression at subclonal resolution and vast scale.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2021
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  • 8
    Online Resource
    Online Resource
    Proceedings of the National Academy of Sciences ; 2006
    In:  Proceedings of the National Academy of Sciences Vol. 103, No. 43 ( 2006-10-24), p. 16003-16008
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 103, No. 43 ( 2006-10-24), p. 16003-16008
    Abstract: Hepatitis B virus (HBV) is a 3.2-kb DNA virus that replicates preferentially in the liver. Liver-enriched nuclear receptors (NRs) play a major role in the HBV life cycle, operating as essential transcription factors for viral gene expression. Notably, these NRs are also key players in metabolic processes that occur in the liver, serving as central transcription factors for key enzymes of gluconeogenesis, fatty acid β-oxidation, and ketogenesis. However, the association between these metabolic events and HBV gene expression is poorly understood. Here we show that peroxisome proliferator-activated receptor-γ coactivator 1α (PGC-1α), a major metabolic regulator and a coactivator of key gluconeogenic genes, robustly coactivates HBV transcription. We further demonstrate that the liver-enriched NR hepatocyte nuclear factor 4α that binds HBV plays an important role in this process. Physiologically, we show that a short-term fast that turns on the gluconeogenic program robustly induces HBV gene expression in vivo . This induction is completely reversible by refeeding and depends on PGC-1α. We conclude that HBV is tightly regulated by changes in the body's nutritional state through the metabolic regulator PGC-1α. Our data provide evidence for nutrition signaling to control viral gene expression and life cycle and thus ascribe to metabolism an important role in virus–host interaction.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2006
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  • 9
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    Online Resource
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 12 ( 2023-03-21)
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 12 ( 2023-03-21)
    Abstract: Lineage-tracing technologies based on Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein 9 (CRISPR-Cas9) genome editing have emerged as a powerful tool for investigating development in single-cell contexts, but exact reconstruction of the underlying clonal relationships in experiment is complicated by features of the data. These complications are functions of the experimental parameters in these systems, such as the Cas9 cutting rate, the diversity of indel outcomes, and the rate of missing data. In this paper, we develop two theoretically grounded algorithms for the reconstruction of the underlying single-cell phylogenetic tree as well as asymptotic bounds for the number of recording sites necessary for exact recapitulation of the ground truth phylogeny at high probability. In doing so, we explore the relationship between the problem difficulty and the experimental parameters, with implications for experimental design. Lastly, we provide simulations showing the empirical performance of these algorithms and showing that the trends in the asymptotic bounds hold empirically. Overall, this work provides a theoretical analysis of phylogenetic reconstruction in single-cell CRISPR-Cas9 lineage-tracing technologies.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2023
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  • 10
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    Online Resource
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 21 ( 2023-05-23)
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 21 ( 2023-05-23)
    Abstract: Detecting differentially expressed genes is important for characterizing subpopulations of cells. In scRNA-seq data, however, nuisance variation due to technical factors like sequencing depth and RNA capture efficiency obscures the underlying biological signal. Deep generative models have been extensively applied to scRNA-seq data, with a special focus on embedding cells into a low-dimensional latent space and correcting for batch effects. However, little attention has been paid to the problem of utilizing the uncertainty from the deep generative model for differential expression (DE). Furthermore, the existing approaches do not allow for controlling for effect size or the false discovery rate (FDR). Here, we present lvm-DE, a generic Bayesian approach for performing DE predictions from a fitted deep generative model, while controlling the FDR. We apply the lvm-DE framework to scVI and scSphere, two deep generative models. The resulting approaches outperform state-of-the-art methods at estimating the log fold change in gene expression levels as well as detecting differentially expressed genes between subpopulations of cells.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
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