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Weibo Li

Bio: Weibo Li is an academic researcher from Harvard University. The author has contributed to research in topics: Cytotoxic T cell & T cell. The author has an hindex of 6, co-authored 6 publications receiving 3079 citations. Previous affiliations of Weibo Li include Broad Institute & Massachusetts Institute of Technology.

Papers
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Journal ArticleDOI
21 Apr 2017-Science
TL;DR: This refined analysis has identified, among others, a previously unknown dendritic cell population that potently activates T cells and reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability.
Abstract: INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.

1,468 citations

01 Apr 2017
TL;DR: In this paper, the authors performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells, which led them to identify and validate six Dendritic cells (DCs) and four monocyte subtypes.
Abstract: INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.

1,306 citations

Journal ArticleDOI
09 Oct 2009-Science
TL;DR: This study establishes a broadly applicable, comprehensive, and unbiased approach to reveal the wiring and functions of a regulatory network controlling a major transcriptional response in primary mammalian cells.
Abstract: Models of mammalian regulatory networks controlling gene expression have been inferred from genomic data but have largely not been validated. We present an unbiased strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We applied this approach to derive regulatory networks that control the transcriptional response of mouse primary dendritic cells to pathogens. Our approach revealed the regulatory functions of 125 transcription factors, chromatin modifiers, and RNA binding proteins, which enabled the construction of a network model consisting of 24 core regulators and 76 fine-tuners that help to explain how pathogen-sensing pathways achieve specificity. This study establishes a broadly applicable, comprehensive, and unbiased approach to reveal the wiring and functions of a regulatory network controlling a major transcriptional response in primary mammalian cells.

502 citations

Journal ArticleDOI
07 Mar 2014-Science
TL;DR: In this paper, the effects of genetic variation on the induction of pathogen-responsive genes in human dendritic cells were investigated using a set of 121 common genetic variants associated in cis with variation in expression responses to Escherichia coli lipopolysaccharide, influenza, or interferon-β (IFN-β).
Abstract: Little is known about how human genetic variation affects the responses to environmental stimuli in the context of complex diseases. Experimental and computational approaches were applied to determine the effects of genetic variation on the induction of pathogen-responsive genes in human dendritic cells. We identified 121 common genetic variants associated in cis with variation in expression responses to Escherichia coli lipopolysaccharide, influenza, or interferon-β (IFN-β). We localized and validated causal variants to binding sites of pathogen-activated STAT (signal transducer and activator of transcription) and IRF (IFN-regulatory factor) transcription factors. We also identified a common variant in IRF7 that is associated in trans with type I IFN induction in response to influenza infection. Our results reveal common alleles that explain interindividual variation in pathogen sensing and provide functional annotation for genetic variants that alter susceptibility to inflammatory diseases.

420 citations

Journal ArticleDOI
TL;DR: It is found that IAP antagonists can augment human and mouse T cell responses to physiologically relevant stimuli and suggest that targeting IAPs using small molecule antagonists may be a strategy for developing novel immunomodulating therapies against cancer.
Abstract: The inhibitor of apoptosis proteins (IAPs) have recently been shown to modulate nuclear factor κB (NF-κB) signaling downstream of tumor necrosis factor (TNF) family receptors, positioning them as essential survival factors in several cancer cell lines, as indicated by the cytotoxic activity of several novel small molecule IAP antagonists. In addition to roles in cancer, increasing evidence suggests that IAPs have an important function in immunity; however, the impact of IAP antagonists on antitumor immune responses is unknown. In this study, we examine the consequences of IAP antagonism on T cell function in vitro and in the context of a tumor vaccine in vivo. We find that IAP antagonists can augment human and mouse T cell responses to physiologically relevant stimuli. The activity of IAP antagonists depends on the activation of NF-κB2 signaling, a mechanism paralleling that responsible for the cytotoxic activity in cancer cells. We further show that IAP antagonists can augment both prophylactic and therapeutic antitumor vaccines in vivo. These findings indicate an important role for the IAPs in regulating T cell–dependent responses and suggest that targeting IAPs using small molecule antagonists may be a strategy for developing novel immunomodulating therapies against cancer.

119 citations


Cited by
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Journal ArticleDOI
TL;DR: An analytical strategy for integrating scRNA-seq data sets based on common sources of variation is introduced, enabling the identification of shared populations across data sets and downstream comparative analysis.
Abstract: 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.

7,741 citations

Journal ArticleDOI
TL;DR: Recent advances that have been made by research into the role of TLR biology in host defense and disease are described.
Abstract: The discovery of Toll-like receptors (TLRs) as components that recognize conserved structures in pathogens has greatly advanced understanding of how the body senses pathogen invasion, triggers innate immune responses and primes antigen-specific adaptive immunity. Although TLRs are critical for host defense, it has become apparent that loss of negative regulation of TLR signaling, as well as recognition of self molecules by TLRs, are strongly associated with the pathogenesis of inflammatory and autoimmune diseases. Furthermore, it is now clear that the interaction between TLRs and recently identified cytosolic innate immune sensors is crucial for mounting effective immune responses. Here we describe the recent advances that have been made by research into the role of TLR biology in host defense and disease.

7,494 citations

Journal ArticleDOI
19 Mar 2010-Cell
TL;DR: The role of PRRs, their signaling pathways, and how they control inflammatory responses are discussed.

6,987 citations

Journal ArticleDOI
24 Jun 2021-Cell
TL;DR: Weighted-nearest neighbor analysis as mentioned in this paper is an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities.

3,369 citations

Journal ArticleDOI
David E. Gordon, Gwendolyn M. Jang, Mehdi Bouhaddou, Jiewei Xu, Kirsten Obernier, Kris M. White1, Matthew J. O’Meara2, Veronica V. Rezelj3, Jeffrey Z. Guo, Danielle L. Swaney, Tia A. Tummino4, Ruth Hüttenhain, Robyn M. Kaake, Alicia L. Richards, Beril Tutuncuoglu, Helene Foussard, Jyoti Batra, Kelsey M. Haas, Maya Modak, Minkyu Kim, Paige Haas, Benjamin J. Polacco, Hannes Braberg, Jacqueline M. Fabius, Manon Eckhardt, Margaret Soucheray, Melanie J. Bennett, Merve Cakir, Michael McGregor, Qiongyu Li, Bjoern Meyer3, Ferdinand Roesch3, Thomas Vallet3, Alice Mac Kain3, Lisa Miorin1, Elena Moreno1, Zun Zar Chi Naing, Yuan Zhou, Shiming Peng4, Ying Shi, Ziyang Zhang, Wenqi Shen, Ilsa T Kirby, James E. Melnyk, John S. Chorba, Kevin Lou, Shizhong Dai, Inigo Barrio-Hernandez5, Danish Memon5, Claudia Hernandez-Armenta5, Jiankun Lyu4, Christopher J.P. Mathy, Tina Perica4, Kala Bharath Pilla4, Sai J. Ganesan4, Daniel J. Saltzberg4, Rakesh Ramachandran4, Xi Liu4, Sara Brin Rosenthal6, Lorenzo Calviello4, Srivats Venkataramanan4, Jose Liboy-Lugo4, Yizhu Lin4, Xi Ping Huang7, Yongfeng Liu7, Stephanie A. Wankowicz, Markus Bohn4, Maliheh Safari4, Fatima S. Ugur, Cassandra Koh3, Nastaran Sadat Savar3, Quang Dinh Tran3, Djoshkun Shengjuler3, Sabrina J. Fletcher3, Michael C. O’Neal, Yiming Cai, Jason C.J. Chang, David J. Broadhurst, Saker Klippsten, Phillip P. Sharp4, Nicole A. Wenzell4, Duygu Kuzuoğlu-Öztürk4, Hao-Yuan Wang4, Raphael Trenker4, Janet M. Young8, Devin A. Cavero9, Devin A. Cavero4, Joseph Hiatt4, Joseph Hiatt9, Theodore L. Roth, Ujjwal Rathore4, Ujjwal Rathore9, Advait Subramanian4, Julia Noack4, Mathieu Hubert3, Robert M. Stroud4, Alan D. Frankel4, Oren S. Rosenberg, Kliment A. Verba4, David A. Agard4, Melanie Ott, Michael Emerman8, Natalia Jura, Mark von Zastrow, Eric Verdin4, Eric Verdin10, Alan Ashworth4, Olivier Schwartz3, Christophe d'Enfert3, Shaeri Mukherjee4, Matthew P. Jacobson4, Harmit S. Malik8, Danica Galonić Fujimori, Trey Ideker6, Charles S. Craik, Stephen N. Floor4, James S. Fraser4, John D. Gross4, Andrej Sali, Bryan L. Roth7, Davide Ruggero, Jack Taunton4, Tanja Kortemme, Pedro Beltrao5, Marco Vignuzzi3, Adolfo García-Sastre, Kevan M. Shokat, Brian K. Shoichet4, Nevan J. Krogan 
30 Apr 2020-Nature
TL;DR: A human–SARS-CoV-2 protein interaction map highlights cellular processes that are hijacked by the virus and that can be targeted by existing drugs, including inhibitors of mRNA translation and predicted regulators of the sigma receptors.
Abstract: A newly described coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efficacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and efforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins that physically associated with each of the SARS-CoV-2 proteins using affinity-purification mass spectrometry, identifying 332 high-confidence protein–protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. Further studies of these host-factor-targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19. A human–SARS-CoV-2 protein interaction map highlights cellular processes that are hijacked by the virus and that can be targeted by existing drugs, including inhibitors of mRNA translation and predicted regulators of the sigma receptors.

3,319 citations