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Lin Y, Zhang X, Sun D, Wang Q, Dou S, Zhou Q. Decoding the corneal immune microenvironment in healthy and diabetic mice during corneal wound healing. Ocul Surf 2025; 37:68-79. [PMID: 40023495 DOI: 10.1016/j.jtos.2025.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2024] [Revised: 02/20/2025] [Accepted: 02/24/2025] [Indexed: 03/04/2025]
Abstract
Diabetic keratopathy (DK) is an underdiagnosed ocular complication of diabetes mellitus. The changes of ocular immune microenvironment contribute to the pathogenesis of DK, while precise mechanisms remain inadequately understood. Here, we employed single-cell RNA sequencing (scRNA-seq) to elucidate the transcriptional alterations of immune cells from diabetic and healthy control mouse corneas during homeostasis and wound healing. Unbiased clustering analysis unveiled 3 major cell subsets and 11 subdivided cell clusters, including T cells, monocyte lineages, and neutrophil subpopulations. The further sub-clustering analysis demonstrated that T cells exhibited cytotoxicity characteristics in both homeostasis and wound healing of diabetic cornea. Moreover, dendritic cells preferred the migratory and maturation phenotype and may recruit and maintain cytotoxic T cells. Macrophages in diabetic cornea preferred the pro-inflammatory M1 phenotype. Under injury conditions, diabetic corneal neutrophils exhibited a more mature and functional possession of neutrophil extracellular traps (NETs). Furthermore, cell-cell communication revealed that the immune cells exhibited hyperactivation and pro-inflammatory responses, while the monocyte lineages exhibited the activating effect on T cells in diabetic cornea. This study represents the inaugural effort to establish a comprehensive scRNA-Seq transcriptomic profile of corneal immune cells during wound healing in healthy and diabetic mice, which offers a valuable reference for subsequent investigations into the pathological roles of immune cells in DK.
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Affiliation(s)
- Yujing Lin
- State Key Laboratory Cultivation Base, Shandong Provincial Key Laboratory of Ophthalmology, Eye Institute of Shandong First Medical University, Qingdao, China; Qingdao Eye Hospital of Shandong First Medical University, Qingdao, China
| | - Xiaowen Zhang
- State Key Laboratory Cultivation Base, Shandong Provincial Key Laboratory of Ophthalmology, Eye Institute of Shandong First Medical University, Qingdao, China; Qingdao Eye Hospital of Shandong First Medical University, Qingdao, China
| | - Di Sun
- State Key Laboratory Cultivation Base, Shandong Provincial Key Laboratory of Ophthalmology, Eye Institute of Shandong First Medical University, Qingdao, China; Qingdao Eye Hospital of Shandong First Medical University, Qingdao, China
| | - Qun Wang
- State Key Laboratory Cultivation Base, Shandong Provincial Key Laboratory of Ophthalmology, Eye Institute of Shandong First Medical University, Qingdao, China; Qingdao Eye Hospital of Shandong First Medical University, Qingdao, China
| | - Shengqian Dou
- State Key Laboratory Cultivation Base, Shandong Provincial Key Laboratory of Ophthalmology, Eye Institute of Shandong First Medical University, Qingdao, China; Qingdao Eye Hospital of Shandong First Medical University, Qingdao, China.
| | - Qingjun Zhou
- State Key Laboratory Cultivation Base, Shandong Provincial Key Laboratory of Ophthalmology, Eye Institute of Shandong First Medical University, Qingdao, China; Qingdao Eye Hospital of Shandong First Medical University, Qingdao, China.
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2
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Frenis K, Badalamenti B, Mamigonian O, Weng C, Wang D, Fierstein S, Côté P, Khong H, Li H, Lummertz da Rocha E, Sankaran VG, Rowe RG. Path of differentiation defines human macrophage identity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.24.634694. [PMID: 39896569 PMCID: PMC11785145 DOI: 10.1101/2025.01.24.634694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2025]
Abstract
Macrophages play central roles in immunity, wound healing, and homeostasis - a functional diversity that is underpinned by varying developmental origins. The impact of ontogeny on properties of human macrophages is inadequately understood. We demonstrate that definitive human fetal liver (HFL) hematopoietic stem cells (HSCs) possess two divergent paths of macrophage specification that lead to distinct identities. The monocyte-dependent pathway exists in both prenatal and postnatal hematopoiesis and generates macrophages with adult-like responses properties. We now uncover a fetal-specific pathway of expedited differentiation that generates tissue resident-like macrophages (TRMs) that retain HSC-like self-renewal programs governed by the aryl hydrocarbon receptor (AHR). We show that AHR antagonism promotes TRM expansion and mitigates inflammation in models of atopic dermatitis (AD). Overall, we directly connect path of differentiation with functional properties of macrophages and identify an approach to promote selective expansion of TRMs with direct relevance to inflammation and diseases of macrophage dysfunction.
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3
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Jing R, Falchetti M, Han T, Najia M, Hensch LT, Meader E, Lummertz da Rocha E, Kononov M, Wang S, Bingham T, Li Z, Zhao Y, Frenis K, Kubaczka C, Yang S, Jha D, Rodrigues-Luiz GF, Rowe RG, Schlaeger TM, Maus MV, North TE, Zon LI, Daley GQ. Maturation and persistence of CAR T cells derived from human pluripotent stem cells via chemical inhibition of G9a/GLP. Cell Stem Cell 2025; 32:71-85.e5. [PMID: 39504968 PMCID: PMC11698653 DOI: 10.1016/j.stem.2024.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 08/27/2024] [Accepted: 10/04/2024] [Indexed: 11/08/2024]
Abstract
Elucidating mechanisms of T cell development can guide in vitro T cell differentiation from induced pluripotent stem cells (iPSCs) and facilitate off-the-shelf T cell-based immunotherapies. Using a stroma-free human iPSC-T cell differentiation platform, we screened for epigenetic modulators that influence T cell specification and identified the H3K9-directed histone methyltransferases G9a/GLP as repressors of T cell fate. We show that G9a/GLP inhibition during specific time windows of differentiation of hematopoietic stem and progenitor cells (HSPCs) skews cell fates toward lymphoid lineages. Inhibition of G9a/GLP promotes the production of lymphoid cells during zebrafish embryonic hematopoiesis, demonstrating the evolutionary conservation of G9a/GLP function. Importantly, chemical inhibition of G9a/GLP facilitates the generation of mature iPSC-T cells that bear transcriptional similarity to peripheral blood αβ T cells. When engineered to express chimeric antigen receptors, the epigenetically engineered iPSC-T cells exhibit enhanced effector functions in vitro and durable, persistent antitumor activity in a xenograft tumor-rechallenge model.
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Affiliation(s)
- Ran Jing
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Marcelo Falchetti
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Tianxiao Han
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Mohamad Najia
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Luca T Hensch
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Eleanor Meader
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Edroaldo Lummertz da Rocha
- Department of Microbiology, Immunology and Parasitology, Federal University of Santa Catarina, Florianópolis, SC 88040-900, Brazil
| | - Martin Kononov
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Stephanie Wang
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Trevor Bingham
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Zhiheng Li
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Yunliang Zhao
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Katie Frenis
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Caroline Kubaczka
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Song Yang
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Deepak Jha
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Gabriela F Rodrigues-Luiz
- Graduate Program of Pharmacology, Center for Biological Sciences, Federal University of Santa Catarina, Florianópolis, SC 88040-900, Brazil
| | - R Grant Rowe
- Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA 02115, USA
| | | | - Marcela V Maus
- Cellular Immunotherapy Program, Massachusetts General Hospital Cancer Center, Charlestown, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Trista E North
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Developmental and Regenerative Biology Program, Harvard Medical School, Boston, MA 02115, USA
| | - Leonard I Zon
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, Boston, MA 02115, USA
| | - George Q Daley
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA.
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Leifer VP, Fang F, Song L, Kim J, Papanikolaou JF, Smeeton J, Thomopoulos S. Single-cell RNA-sequencing analysis of immune and mesenchymal cell crosstalk in the developing enthesis. Sci Rep 2024; 14:26839. [PMID: 39500962 PMCID: PMC11538517 DOI: 10.1038/s41598-024-77958-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2024] [Accepted: 10/28/2024] [Indexed: 11/08/2024] Open
Abstract
Autoimmunity underlies many painful disorders, such as enthesopathies, which localize to the enthesis. From infiltration of the synovium and axial skeleton by B cells, to disturbances in the ratio of M1/M2 enthesis macrophages, to CD8 + T cell mediated inflammation, autoimmune dysregulation is becoming increasingly well characterized in enthesopathies. Tissue resident B cells, macrophages, neutrophils, and T cells have also been localized in healthy human entheses. However, the potential developmental origins, presence, and role of immune cells (ICs) in enthesis development is not known. Here, we use single-cell RNA-sequencing analysis to describe IC subtypes present in the enthesis before, during, and after mineralization, and to infer regulatory interactions between ICs and mesenchymal cells (MCs). We report the presence of nine phenotypically distinct IC subtypes, including B cells, macrophages, neutrophils, and T cells. We find that specific IC subtypes may promote MC-proliferation and differentiation, and that MCs may regulate IC phenotype and autoimmunity. Our findings suggest that bidirectional regulatory interactions between ICs and MCs may be important to enthesis mineralization, and suggest that progenitor MCs have a unique ability to limit autoimmunity during development.
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Affiliation(s)
- Valia P Leifer
- Department of Orthopedic Surgery, Columbia University, New York, NY, 10032, USA
| | - Fei Fang
- Department Orthopedics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lee Song
- Department of Orthopedic Surgery, Columbia University, New York, NY, 10032, USA
| | - Jieon Kim
- Department of Orthopedic Surgery, Columbia University, New York, NY, 10032, USA
| | - John F Papanikolaou
- Department of Orthopedic Surgery, Columbia University, New York, NY, 10032, USA
| | - Joanna Smeeton
- Department of Rehabilitation and Regenerative Medicine, Columbia Stem Cell Initiative, Columbia University, New York, NY, 10032, USA
- Department of Genetics and Development, Columbia Stem Cell Initiative, Columbia University, New York, NY, 10032, USA
| | - Stavros Thomopoulos
- Department of Orthopedic Surgery, Columbia University, New York, NY, 10032, USA.
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA.
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Jimenez-Cyrus D, Adusumilli VS, Stempel MH, Maday S, Ming GL, Song H, Bond AM. Molecular cascade reveals sequential milestones underlying hippocampal neural stem cell development into an adult state. Cell Rep 2024; 43:114339. [PMID: 38852158 PMCID: PMC11320877 DOI: 10.1016/j.celrep.2024.114339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 04/16/2024] [Accepted: 05/23/2024] [Indexed: 06/11/2024] Open
Abstract
Quiescent adult neural stem cells (NSCs) in the mammalian brain arise from proliferating NSCs during development. Beyond acquisition of quiescence, an adult NSC hallmark, little is known about the process, milestones, and mechanisms underlying the transition of developmental NSCs to an adult NSC state. Here, we performed targeted single-cell RNA-seq analysis to reveal the molecular cascade underlying NSC development in the early postnatal mouse dentate gyrus. We identified two sequential steps, first a transition to quiescence followed by further maturation, each of which involved distinct changes in metabolic gene expression. Direct metabolic analysis uncovered distinct milestones, including an autophagy burst before NSC quiescence acquisition and cellular reactive oxygen species level elevation along NSC maturation. Functionally, autophagy is important for the NSC transition to quiescence during early postnatal development. Together, our study reveals a multi-step process with defined milestones underlying establishment of the adult NSC pool in the mammalian brain.
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Affiliation(s)
- Dennisse Jimenez-Cyrus
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Vijay S Adusumilli
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Max H Stempel
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sandra Maday
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Guo-Li Ming
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Cell and Developmental Biology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hongjun Song
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Cell and Developmental Biology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; The Epigenetics Institute, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Allison M Bond
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Cell, Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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6
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Boccacino JM, Dos Santos Peixoto R, Fernandes CFDL, Cangiano G, Sola PR, Coelho BP, Prado MB, Melo-Escobar MI, de Sousa BP, Ayyadhury S, Bader GD, Shinjo SMO, Marie SKN, da Rocha EL, Lopes MH. Integrated transcriptomics uncovers an enhanced association between the prion protein gene expression and vesicle dynamics signatures in glioblastomas. BMC Cancer 2024; 24:199. [PMID: 38347462 PMCID: PMC10863147 DOI: 10.1186/s12885-024-11914-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 01/23/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND Glioblastoma (GBM) is an aggressive brain tumor that exhibits resistance to current treatment, making the identification of novel therapeutic targets essential. In this context, cellular prion protein (PrPC) stands out as a potential candidate for new therapies. Encoded by the PRNP gene, PrPC can present increased expression levels in GBM, impacting cell proliferation, growth, migration, invasion and stemness. Nevertheless, the exact molecular mechanisms through which PRNP/PrPC modulates key aspects of GBM biology remain elusive. METHODS To elucidate the implications of PRNP/PrPC in the biology of this cancer, we analyzed publicly available RNA sequencing (RNA-seq) data of patient-derived GBMs from four independent studies. First, we ranked samples profiled by bulk RNA-seq as PRNPhigh and PRNPlow and compared their transcriptomic landscape. Then, we analyzed PRNP+ and PRNP- GBM cells profiled by single-cell RNA-seq to further understand the molecular context within which PRNP/PrPC might function in this tumor. We explored an additional proteomics dataset, applying similar comparative approaches, to corroborate our findings. RESULTS Functional profiling revealed that vesicular dynamics signatures are strongly correlated with PRNP/PrPC levels in GBM. We found a panel of 73 genes, enriched in vesicle-related pathways, whose expression levels are increased in PRNPhigh/PRNP+ cells across all RNA-seq datasets. Vesicle-associated genes, ANXA1, RAB31, DSTN and SYPL1, were found to be upregulated in vitro in an in-house collection of patient-derived GBM. Moreover, proteome analysis of patient-derived samples reinforces the findings of enhanced vesicle biogenesis, processing and trafficking in PRNPhigh/PRNP+ GBM cells. CONCLUSIONS Together, our findings shed light on a novel role for PrPC as a potential modulator of vesicle biology in GBM, which is pivotal for intercellular communication and cancer maintenance. We also introduce GBMdiscovery, a novel user-friendly tool that allows the investigation of specific genes in GBM biology.
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Affiliation(s)
- Jacqueline Marcia Boccacino
- Department of Cell and Developmental Biology, Institute of Biomedical Sciences, University of São Paulo, Av. Prof. Lineu Prestes, 1524 room 431, Sao Paulo, 05508000, Brazil
| | - Rafael Dos Santos Peixoto
- Department of Automation and Systems, Technological Center, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil
| | - Camila Felix de Lima Fernandes
- Department of Cell and Developmental Biology, Institute of Biomedical Sciences, University of São Paulo, Av. Prof. Lineu Prestes, 1524 room 431, Sao Paulo, 05508000, Brazil
| | - Giovanni Cangiano
- Department of Cell and Developmental Biology, Institute of Biomedical Sciences, University of São Paulo, Av. Prof. Lineu Prestes, 1524 room 431, Sao Paulo, 05508000, Brazil
| | - Paula Rodrigues Sola
- Cellular and Molecular Biology Laboratory (LIM 15), Department of Neurology, Faculdade de Medicina (FMUSP), University of Sao Paulo, Sao Paulo, Brazil
| | - Bárbara Paranhos Coelho
- Department of Cell and Developmental Biology, Institute of Biomedical Sciences, University of São Paulo, Av. Prof. Lineu Prestes, 1524 room 431, Sao Paulo, 05508000, Brazil
| | - Mariana Brandão Prado
- Department of Cell and Developmental Biology, Institute of Biomedical Sciences, University of São Paulo, Av. Prof. Lineu Prestes, 1524 room 431, Sao Paulo, 05508000, Brazil
| | - Maria Isabel Melo-Escobar
- Department of Cell and Developmental Biology, Institute of Biomedical Sciences, University of São Paulo, Av. Prof. Lineu Prestes, 1524 room 431, Sao Paulo, 05508000, Brazil
| | - Breno Pereira de Sousa
- Department of Cell and Developmental Biology, Institute of Biomedical Sciences, University of São Paulo, Av. Prof. Lineu Prestes, 1524 room 431, Sao Paulo, 05508000, Brazil
| | - Shamini Ayyadhury
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
| | - Gary D Bader
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Sueli Mieko Oba Shinjo
- Cellular and Molecular Biology Laboratory (LIM 15), Department of Neurology, Faculdade de Medicina (FMUSP), University of Sao Paulo, Sao Paulo, Brazil
| | - Suely Kazue Nagahashi Marie
- Cellular and Molecular Biology Laboratory (LIM 15), Department of Neurology, Faculdade de Medicina (FMUSP), University of Sao Paulo, Sao Paulo, Brazil
| | - Edroaldo Lummertz da Rocha
- Department of Microbiology, Immunology, and Parasitology, Biological Sciences Center, Federal University of Santa Catarina, Florianópolis, Santa Catarina, 88040-900, Brazil.
| | - Marilene Hohmuth Lopes
- Department of Cell and Developmental Biology, Institute of Biomedical Sciences, University of São Paulo, Av. Prof. Lineu Prestes, 1524 room 431, Sao Paulo, 05508000, Brazil.
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Song X, Fu Y, Li C, Jia Q, Ren M, Zhang X, Bie H, Zhou H, Gan X, He S, Wang Y, Zhang S, Pan R, Sun W, Zhou H, Ni Q, Song J, Zhang Q, Chen X, Jia E. Single-cell RNA sequencing atlas of peripheral blood mononuclear cells from subjects with coronary artery disease. BIOCHIMICA ET BIOPHYSICA ACTA. MOLECULAR CELL RESEARCH 2024; 1871:119593. [PMID: 37730128 DOI: 10.1016/j.bbamcr.2023.119593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 09/01/2023] [Accepted: 09/10/2023] [Indexed: 09/22/2023]
Abstract
BACKGROUND The landscape of specific peripheral circulating immune cell subsets at the single-cell level in the occurrence and development of coronary artery disease (CAD) remains poorly understood. METHODS We conducted single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from subjects with CAD (n = 3), and controls (n = 3), as well as downstream analysis including cell- and gene-level approaches. This explored the characteristics of peripheral circulating immune cells between CADs and controls by means of Uniform manifold approximation and projection (UMAP), Monocle3 package, CellPhoneDB, and single-cell regulatory network inference and clustering (SCENIC). PBMCs were used as clinical samples for validating our findings by qRT-PCR. RESULTS We identified 33 cell clusters among 67,447 cells, including monocytes, T cells, B cells, NK cells, and platelets. The significant difference in the abundance of the 33 clusters of cell type between CADs group and controls group was not found. The JUN was shared in cluster 0, 11,13, and 24 from differential expression genes analysis and SCENIC analysis in monocyte clusters between CAD and controls. Besides, JUN was validated to be significantly upregulated in the CAD group (p = 0.018) and may act as a potential diagnostic biomarker and independent predictor of CAD. CONCLUSIONS Our study offered a detailed profiling of single-cell RNA sequencing of PBMCs from subjects with CADs and controls. These data provide a line of evidence that the JUN signaling pathway may be a potential diagnostic and therapeutic molecule target for CAD.
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Affiliation(s)
- Xiaolong Song
- Department of Cardiovascular Medicine, Yancheng TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Yancheng 224000, Jiangsu Province, China
| | - Yahong Fu
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Chengcheng Li
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Qiaowei Jia
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Mengmeng Ren
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Xin Zhang
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Hengjie Bie
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Hanxiao Zhou
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Xiongkang Gan
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Shu He
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Yanjun Wang
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Sheng Zhang
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Renyou Pan
- Department of Cardiovascular Medicine, Yancheng TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Yancheng 224000, Jiangsu Province, China
| | - Weixin Sun
- Department of Cardiovascular Medicine, Yancheng TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Yancheng 224000, Jiangsu Province, China
| | - Haitang Zhou
- Department of Cardiovascular Medicine, Yancheng TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Yancheng 224000, Jiangsu Province, China
| | - Qimeng Ni
- Department of Cardiovascular Medicine, Yancheng TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Yancheng 224000, Jiangsu Province, China
| | - Jun Song
- Department of Cardiovascular Medicine, Yancheng TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Yancheng 224000, Jiangsu Province, China
| | - Qian Zhang
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China.
| | - Xiumei Chen
- Department of Geriatric, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China.
| | - Enzhi Jia
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China.
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8
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Wang P, Wen X, Li H, Lang P, Li S, Lei Y, Shu H, Gao L, Zhao D, Zeng J. Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON. Nat Commun 2023; 14:8459. [PMID: 38123534 PMCID: PMC10733330 DOI: 10.1038/s41467-023-44103-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023] Open
Abstract
Single-cell technologies enable the dynamic analyses of cell fate mapping. However, capturing the gene regulatory relationships and identifying the driver factors that control cell fate decisions are still challenging. We present CEFCON, a network-based framework that first uses a graph neural network with attention mechanism to infer a cell-lineage-specific gene regulatory network (GRN) from single-cell RNA-sequencing data, and then models cell fate dynamics through network control theory to identify driver regulators and the associated gene modules, revealing their critical biological processes related to cell states. Extensive benchmarking tests consistently demonstrated the superiority of CEFCON in GRN construction, driver regulator identification, and gene module identification over baseline methods. When applied to the mouse hematopoietic stem cell differentiation data, CEFCON successfully identified driver regulators for three developmental lineages, which offered useful insights into their differentiation from a network control perspective. Overall, CEFCON provides a valuable tool for studying the underlying mechanisms of cell fate decisions from single-cell RNA-seq data.
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Affiliation(s)
- Peizhuo Wang
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084, Beijing, China
- School of Engineering, Westlake University, 310030, Hangzhou, Zhejiang Province, China
| | - Xiao Wen
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, 100101, Beijing, China
| | - Han Li
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084, Beijing, China
| | - Peng Lang
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084, Beijing, China
| | - Shuya Li
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084, Beijing, China
- School of Engineering, Westlake University, 310030, Hangzhou, Zhejiang Province, China
| | - Yipin Lei
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084, Beijing, China
| | - Hantao Shu
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084, Beijing, China
| | - Lin Gao
- School of Computer Science and Technology, Xidian University, 710071, Xi'an, Shaanxi Province, China
| | - Dan Zhao
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084, Beijing, China.
| | - Jianyang Zeng
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084, Beijing, China.
- School of Engineering, Westlake University, 310030, Hangzhou, Zhejiang Province, China.
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9
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Jani PK, Petkau G, Kawano Y, Klemm U, Guerra GM, Heinz GA, Heinrich F, Durek P, Mashreghi MF, Melchers F. The miR-221/222 cluster regulates hematopoietic stem cell quiescence and multipotency by suppressing both Fos/AP-1/IEG pathway activation and stress-like differentiation to granulocytes. PLoS Biol 2023; 21:e3002015. [PMID: 37983263 PMCID: PMC10695376 DOI: 10.1371/journal.pbio.3002015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 12/04/2023] [Accepted: 10/16/2023] [Indexed: 11/22/2023] Open
Abstract
Throughout life, hematopoietic stem cells (HSCs), residing in bone marrow (BM), continuously regenerate erythroid/megakaryocytic, myeloid, and lymphoid cell lineages. This steady-state hematopoiesis from HSC and multipotent progenitors (MPPs) in BM can be perturbed by stress. The molecular controls of how stress can impact hematopoietic output remain poorly understood. MicroRNAs (miRNAs) as posttranscriptional regulators of gene expression have been found to control various functions in hematopoiesis. We find that the miR-221/222 cluster, which is expressed in HSC and in MPPs differentiating from them, perturbs steady-state hematopoiesis in ways comparable to stress. We compare pool sizes and single-cell transcriptomes of HSC and MPPs in unperturbed or stress-perturbed, miR-221/222-proficient or miR-221/222-deficient states. MiR-221/222 deficiency in hematopoietic cells was induced in C57BL/6J mice by conditional vav-cre-mediated deletion of the floxed miR-221/222 gene cluster. Social stress as well as miR-221/222 deficiency, alone or in combination, reduced HSC pools 3-fold and increased MPPs 1.5-fold. It also enhanced granulopoisis in the spleen. Furthermore, combined stress and miR-221/222 deficiency increased the erythroid/myeloid/granulocytic precursor pools in BM. Differential expression analyses of single-cell RNAseq transcriptomes of unperturbed and stressed, proficient HSC and MPPs detected more than 80 genes, selectively up-regulated in stressed cells, among them immediate early genes (IEGs). The same differential single-cell transcriptome analyses of unperturbed, miR-221/222-proficient with deficient HSC and MPPs identified Fos, Jun, JunB, Klf6, Nr4a1, Ier2, Zfp36-all IEGs-as well as CD74 and Ly6a as potential miRNA targets. Three of them, Klf6, Nr4a1, and Zfp36, have previously been found to influence myelogranulopoiesis. Together with increased levels of Jun, Fos forms increased amounts of the heterodimeric activator protein-1 (AP-1), which is known to control the expression of the selectively up-regulated expression of the IEGs. The comparisons of single-cell mRNA-deep sequencing analyses of socially stressed with miR-221/222-deficient HSC identify 5 of the 7 Fos/AP-1-controlled IEGs, Ier2, Jun, Junb, Klf6, and Zfp36, as common activators of HSC from quiescence. Combined with stress, miR-221/222 deficiency enhanced the Fos/AP-1/IEG pathway, extended it to MPPs, and increased the number of granulocyte precursors in BM, inducing selective up-regulation of genes encoding heat shock proteins Hspa5 and Hspa8, tubulin-cytoskeleton-organizing proteins Tuba1b, Tubb 4b and 5, and chromatin remodeling proteins H3f3b, H2afx, H2afz, and Hmgb2. Up-regulated in HSC, MPP1, and/or MPP2, they appear as potential regulators of stress-induced, miR-221/222-dependent increased granulocyte differentiation. Finally, stress by serial transplantations of miR-221/222-deficient HSC selectively exhausted their lymphoid differentiation capacities, while retaining their ability to home to BM and to differentiate to granulocytes. Thus, miR-221/222 maintains HSC quiescence and multipotency by suppressing Fos/AP-1/IEG-mediated activation and by suppressing enhanced stress-like differentiation to granulocytes. Since miR-221/222 is also expressed in human HSC, controlled induction of miR-221/222 in HSC should improve BM transplantations.
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Affiliation(s)
- Peter K. Jani
- Deutsches Rheuma Forschungszentrum (DRFZ), Berlin, Germany
| | - Georg Petkau
- Deutsches Rheuma Forschungszentrum (DRFZ), Berlin, Germany
| | - Yohei Kawano
- Deutsches Rheuma Forschungszentrum (DRFZ), Berlin, Germany
| | - Uwe Klemm
- Max Planck Institute for Infection Biology, Berlin, Germany
| | | | | | | | - Pawel Durek
- Deutsches Rheuma Forschungszentrum (DRFZ), Berlin, Germany
| | | | - Fritz Melchers
- Deutsches Rheuma Forschungszentrum (DRFZ), Berlin, Germany
- Max Planck Institute for Infection Biology, Berlin, Germany
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10
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Ricciardi-Jorge T, da Rocha EL, Gonzalez-Kozlova E, Rodrigues-Luiz GF, Ferguson BJ, Sweeney T, Irigoyen N, Mansur DS. PKR-mediated stress response enhances dengue and Zika virus replication. mBio 2023; 14:e0093423. [PMID: 37732809 PMCID: PMC10653888 DOI: 10.1128/mbio.00934-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 08/01/2023] [Indexed: 09/22/2023] Open
Abstract
IMPORTANCE One of the fundamental features that make viruses intracellular parasites is the necessity to use cellular translational machinery. Hence, this is a crucial checkpoint for controlling infections. Here, we show that dengue and Zika viruses, responsible for nearly 400 million infections every year worldwide, explore such control for optimal replication. Using immunocompetent cells, we demonstrate that arrest of protein translations happens after sensing of dsRNA and that the information required to avoid this blocking is contained in viral 5'-UTR. Our work, therefore, suggests that the non-canonical translation described for these viruses is engaged when the intracellular stress response is activated.
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Affiliation(s)
- Taissa Ricciardi-Jorge
- Departamento de Microbiologia, Imunologia e Parasitologia, Universidade Federal de Santa Catarina (UFSC), Florianópolis, Brazil
- The Pirbright Institute, Woking, United Kingdom
| | - Edroaldo Lummertz da Rocha
- Departamento de Microbiologia, Imunologia e Parasitologia, Universidade Federal de Santa Catarina (UFSC), Florianópolis, Brazil
| | - Edgar Gonzalez-Kozlova
- Departamento de Microbiologia, Imunologia e Parasitologia, Universidade Federal de Santa Catarina (UFSC), Florianópolis, Brazil
- Icahn School of Medicine, New York, USA
| | - Gabriela Flavia Rodrigues-Luiz
- Departamento de Microbiologia, Imunologia e Parasitologia, Universidade Federal de Santa Catarina (UFSC), Florianópolis, Brazil
| | - Brian J. Ferguson
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | | | - Nerea Irigoyen
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Daniel Santos Mansur
- Departamento de Microbiologia, Imunologia e Parasitologia, Universidade Federal de Santa Catarina (UFSC), Florianópolis, Brazil
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11
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Yang Y, Zhang B, Xie J, Li J, Liu J, Liu R, Zhang L, Zhang J, Su Z, Li F, Zhang L, Hong A, Chen X. CH02 peptide promotes ex vivo expansion of umbilical cord blood-derived CD34 + hematopoietic stem/progenitor cells. Acta Biochim Biophys Sin (Shanghai) 2023; 55:1630-1639. [PMID: 37381672 PMCID: PMC10577473 DOI: 10.3724/abbs.2023047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 02/15/2023] [Indexed: 03/15/2023] Open
Abstract
Umbilical cord blood (UCB) is an advantageous source for hematopoietic stem/progenitor cell (HSPC) transplantation, yet the current strategies for large-scale and cost-effective UCB-HSPC preparation are still unavailable. To overcome these obstacles, we systematically evaluate the feasibility of our newly identified CH02 peptide for ex vivo expansion of CD34 + UCB-HSPCs. We herein report that the CH02 peptide is specifically enriched in HSPC proliferation via activating the FLT3 signaling. Notably, the CH02-based cocktails are adequate for boosting 12-fold ex vivo expansion of UCB-HSPCs. Meanwhile, CH02-preconditioned UCB-HSPCs manifest preferable efficacy upon wound healing in diabetic mice via bidirectional orchestration of proinflammatory and anti-inflammatory factors. Together, our data indicate the advantages of the CH02-based strategy for ex vivo expansion of CD34 + UCB-HSPCs, which will provide new strategies for further development of large-scale HSPC preparation for clinical purposes.
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Affiliation(s)
- Yiqi Yang
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
- The First Affiliated HospitalJi’nan UniversityGuangzhou510630China
| | - Bihui Zhang
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
| | - Junye Xie
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
| | - Jingsheng Li
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
| | - Jia Liu
- The First Affiliated HospitalJi’nan UniversityGuangzhou510630China
| | - Rongzhan Liu
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
| | - Linhao Zhang
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
| | - Jinting Zhang
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
| | - Zijian Su
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
| | - Fu Li
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
| | - Leisheng Zhang
- Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province & NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal TumorGansu Provincial HospitalLanzhou730000China
- Key Laboratory of Radiation Technology and BiophysicsHefei Institute of Physical ScienceChinese Academy of SciencesHefei230031China
| | - An Hong
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
- The First Affiliated HospitalJi’nan UniversityGuangzhou510630China
| | - Xiaojia Chen
- Institute of Biomedicine & Department of Cell BiologyCollege of Life Science and TechnologyGuangdong Province Key Laboratory of Bioengineering MedicineGuangdong Provincial Biotechnology Drug & Engineering Technology Research Center; National Engineering Research Center of Genetic MedicineJi’nan UniversityGuangzhou510632China
- The First Affiliated HospitalJi’nan UniversityGuangzhou510630China
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12
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Herrera-Uribe J, Lim KS, Byrne KA, Daharsh L, Liu H, Corbett RJ, Marco G, Schroyen M, Koltes JE, Loving CL, Tuggle CK. Integrative profiling of gene expression and chromatin accessibility elucidates specific transcriptional networks in porcine neutrophils. Front Genet 2023; 14:1107462. [PMID: 37287538 PMCID: PMC10242145 DOI: 10.3389/fgene.2023.1107462] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 04/27/2023] [Indexed: 06/09/2023] Open
Abstract
Neutrophils are vital components of the immune system for limiting the invasion and proliferation of pathogens in the body. Surprisingly, the functional annotation of porcine neutrophils is still limited. The transcriptomic and epigenetic assessment of porcine neutrophils from healthy pigs was performed by bulk RNA sequencing and transposase accessible chromatin sequencing (ATAC-seq). First, we sequenced and compared the transcriptome of porcine neutrophils with eight other immune cell transcriptomes to identify a neutrophil-enriched gene list within a detected neutrophil co-expression module. Second, we used ATAC-seq analysis to report for the first time the genome-wide chromatin accessible regions of porcine neutrophils. A combined analysis using both transcriptomic and chromatin accessibility data further defined the neutrophil co-expression network controlled by transcription factors likely important for neutrophil lineage commitment and function. We identified chromatin accessible regions around promoters of neutrophil-specific genes that were predicted to be bound by neutrophil-specific transcription factors. Additionally, published DNA methylation data from porcine immune cells including neutrophils were used to link low DNA methylation patterns to accessible chromatin regions and genes with highly enriched expression in porcine neutrophils. In summary, our data provides the first integrative analysis of the accessible chromatin regions and transcriptional status of porcine neutrophils, contributing to the Functional Annotation of Animal Genomes (FAANG) project, and demonstrates the utility of chromatin accessible regions to identify and enrich our understanding of transcriptional networks in a cell type such as neutrophils.
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Affiliation(s)
- Juber Herrera-Uribe
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Kyu-Sang Lim
- Department of Animal Science, Iowa State University, Ames, IA, United States
- Department of Animal Resource Science, Kongju National University, Yesan, Republic of Korea
| | - Kristen A. Byrne
- USDA-Agriculture Research Service, National Animal Disease Center, Food Safety and Enteric Pathogens Research Unit, Ames, IA, United States
| | - Lance Daharsh
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Haibo Liu
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Ryan J. Corbett
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Gianna Marco
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Martine Schroyen
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - James E. Koltes
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Crystal L. Loving
- USDA-Agriculture Research Service, National Animal Disease Center, Food Safety and Enteric Pathogens Research Unit, Ames, IA, United States
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13
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Meharwade T, Joumier L, Parisotto M, Huynh V, Lummertz da Rocha E, Malleshaiah M. Cross-activation of FGF, NODAL, and WNT pathways constrains BMP-signaling-mediated induction of the totipotent state in mouse embryonic stem cells. Cell Rep 2023; 42:112438. [PMID: 37126449 DOI: 10.1016/j.celrep.2023.112438] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 11/11/2022] [Accepted: 04/11/2023] [Indexed: 05/02/2023] Open
Abstract
Embryonic stem cells (ESCs) are an attractive model to study the relationship between signaling and cell fates. Cultured mouse ESCs can exist in multiple states resembling distinct stages of early embryogenesis, such as totipotent, pluripotent, primed, and primitive endoderm. The signaling mechanisms regulating the totipotent state and coexistence of these states are poorly understood. Here we identify bone morphogenetic protein (BMP) signaling as an inducer of the totipotent state. However, we discover that BMP's role is constrained by the cross-activation of FGF, NODAL, and WNT pathways. We exploit this finding to enhance the proportion of totipotent cells by rationally inhibiting the cross-activated pathways. Single-cell mRNA sequencing reveals that induction of the totipotent state is accompanied by suppression of primed and primitive endoderm states. Furthermore, reprogrammed totipotent cells we generate in culture resemble totipotent cells of preimplantation embryo. Our findings reveal a BMP signaling mechanism regulating both the totipotent state and heterogeneity of ESCs.
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Affiliation(s)
- Thulaj Meharwade
- Montreal Clinical Research Institute (IRCM), 110 Pine Avenue West, Montreal, QC H2W 1R7, Canada; Department of Biochemistry and Molecular Medicine, University of Montreal, C.P. 6128, Succursale Centre-ville, Montreal, QC H3C 3J7, Canada
| | - Loïck Joumier
- Montreal Clinical Research Institute (IRCM), 110 Pine Avenue West, Montreal, QC H2W 1R7, Canada; Department of Biochemistry and Molecular Medicine, University of Montreal, C.P. 6128, Succursale Centre-ville, Montreal, QC H3C 3J7, Canada
| | - Maxime Parisotto
- Montreal Clinical Research Institute (IRCM), 110 Pine Avenue West, Montreal, QC H2W 1R7, Canada
| | - Vivian Huynh
- Montreal Clinical Research Institute (IRCM), 110 Pine Avenue West, Montreal, QC H2W 1R7, Canada; Molecular Biology Program, University of Montreal, C.P. 6128, Succursale Centre-ville, Montreal, QC H3C 3J7, Canada
| | - Edroaldo Lummertz da Rocha
- Department of Microbiology, Immunology and Parasitology, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil
| | - Mohan Malleshaiah
- Montreal Clinical Research Institute (IRCM), 110 Pine Avenue West, Montreal, QC H2W 1R7, Canada; Department of Biochemistry and Molecular Medicine, University of Montreal, C.P. 6128, Succursale Centre-ville, Montreal, QC H3C 3J7, Canada; Molecular Biology Program, University of Montreal, C.P. 6128, Succursale Centre-ville, Montreal, QC H3C 3J7, Canada; The Division of Experimental Medicine, McGill University, 1001 Decarie Boulevard, Montreal, QC H4A 3J1, Canada; McGill Regenerative Medicine Network, 1160 Pine Avenue West, Montreal, QC H3A 1A3, Canada.
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14
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Goekeri C, Pennitz P, Groenewald W, Behrendt U, Kirsten H, Zobel CM, Berger S, Heinz GA, Mashreghi MF, Wienhold SM, Dietert K, Dorhoi A, Gruber AD, Scholz M, Rohde G, Suttorp N, CAPNETZ Study Group, Witzenrath M, Nouailles G. MicroRNA-223 Dampens Pulmonary Inflammation during Pneumococcal Pneumonia. Cells 2023; 12:cells12060959. [PMID: 36980300 PMCID: PMC10047070 DOI: 10.3390/cells12060959] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 03/07/2023] [Accepted: 03/16/2023] [Indexed: 03/29/2023] Open
Abstract
Community-acquired pneumonia remains a major contributor to global communicable disease-mediated mortality. Neutrophils play a leading role in trying to contain bacterial lung infection, but they also drive detrimental pulmonary inflammation, when dysregulated. Here we aimed at understanding the role of microRNA-223 in orchestrating pulmonary inflammation during pneumococcal pneumonia. Serum microRNA-223 was measured in patients with pneumococcal pneumonia and in healthy subjects. Pulmonary inflammation in wild-type and microRNA-223-knockout mice was assessed in terms of disease course, histopathology, cellular recruitment and evaluation of inflammatory protein and gene signatures following pneumococcal infection. Low levels of serum microRNA-223 correlated with increased disease severity in pneumococcal pneumonia patients. Prolonged neutrophilic influx into the lungs and alveolar spaces was detected in pneumococci-infected microRNA-223-knockout mice, possibly accounting for aggravated histopathology and acute lung injury. Expression of microRNA-223 in wild-type mice was induced by pneumococcal infection in a time-dependent manner in whole lungs and lung neutrophils. Single-cell transcriptome analyses of murine lungs revealed a unique profile of antimicrobial and cellular maturation genes that are dysregulated in neutrophils lacking microRNA-223. Taken together, low levels of microRNA-223 in human pneumonia patient serum were associated with increased disease severity, whilst its absence provoked dysregulation of the neutrophil transcriptome in murine pneumococcal pneumonia.
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Affiliation(s)
- Cengiz Goekeri
- Department of Infectious Diseases, Respiratory Medicine and Critical Care, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- Faculty of Medicine, Cyprus International University, 99040 Nicosia, Cyprus
- Correspondence: (C.G.); (G.N.)
| | - Peter Pennitz
- Department of Infectious Diseases, Respiratory Medicine and Critical Care, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Wibke Groenewald
- Department of Infectious Diseases, Respiratory Medicine and Critical Care, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Ulrike Behrendt
- Department of Infectious Diseases, Respiratory Medicine and Critical Care, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Holger Kirsten
- Institute for Medical Informatics, Statistics, and Epidemiology, Universität Leipzig, 04107 Leipzig, Germany
| | - Christian M. Zobel
- Department of Internal Medicine, Bundeswehrkrankenhaus Berlin, 10115 Berlin, Germany
| | - Sarah Berger
- Department of Infectious Diseases, Respiratory Medicine and Critical Care, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Gitta A. Heinz
- Therapeutic Gene Regulation, Deutsches Rheuma-Forschungszentrum Berlin (DRFZ), ein Institut der Leibniz-Gemeinschaft, 10117 Berlin, Germany
| | - Mir-Farzin Mashreghi
- Therapeutic Gene Regulation, Deutsches Rheuma-Forschungszentrum Berlin (DRFZ), ein Institut der Leibniz-Gemeinschaft, 10117 Berlin, Germany
- Berlin Institute of Health at Charité—Universitätsmedizin Berlin, BIH Center for Regenerative Therapies (BCRT), 13353 Berlin, Germany
| | - Sandra-Maria Wienhold
- Department of Infectious Diseases, Respiratory Medicine and Critical Care, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Kristina Dietert
- Institute of Veterinary Pathology, Freie Universität Berlin, 14163 Berlin, Germany
- Veterinary Centre for Resistance Research (TZR), Freie Universität Berlin, 14163 Berlin, Germany
| | - Anca Dorhoi
- Institute of Immunology, Friedrich-Loeffler-Institut, 17493 Greifswald-Insel Riems, Germany
- Faculty of Mathematics and Natural Sciences, University of Greifswald, 17489 Greifswald, Germany
| | - Achim D. Gruber
- Institute of Veterinary Pathology, Freie Universität Berlin, 14163 Berlin, Germany
| | - Markus Scholz
- Institute for Medical Informatics, Statistics, and Epidemiology, Universität Leipzig, 04107 Leipzig, Germany
| | - Gernot Rohde
- Department of Respiratory Medicine, Medical Clinic I, Goethe-Universität Frankfurt am Main, 60596 Frankfurt am Main, Germany
- CAPNETZ STIFTUNG, 30625 Hannover, Germany
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), German Center for Lung Research (DZL), 30625 Hannover, Germany
| | - Norbert Suttorp
- Department of Infectious Diseases, Respiratory Medicine and Critical Care, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- CAPNETZ STIFTUNG, 30625 Hannover, Germany
- German Center for Lung Research (DZL), 10117 Berlin, Germany
| | | | - Martin Witzenrath
- Department of Infectious Diseases, Respiratory Medicine and Critical Care, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- CAPNETZ STIFTUNG, 30625 Hannover, Germany
- German Center for Lung Research (DZL), 10117 Berlin, Germany
| | - Geraldine Nouailles
- Department of Infectious Diseases, Respiratory Medicine and Critical Care, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- Correspondence: (C.G.); (G.N.)
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15
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Ding J, Li Y, Larochelle A. De Novo Generation of Human Hematopoietic Stem Cells from Pluripotent Stem Cells for Cellular Therapy. Cells 2023; 12:321. [PMID: 36672255 PMCID: PMC9857267 DOI: 10.3390/cells12020321] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 01/02/2023] [Accepted: 01/11/2023] [Indexed: 01/19/2023] Open
Abstract
The ability to manufacture human hematopoietic stem cells (HSCs) in the laboratory holds enormous promise for cellular therapy of human blood diseases. Several differentiation protocols have been developed to facilitate the emergence of HSCs from human pluripotent stem cells (PSCs). Most approaches employ a stepwise addition of cytokines and morphogens to recapitulate the natural developmental process. However, these protocols globally lack clinical relevance and uniformly induce PSCs to produce hematopoietic progenitors with embryonic features and limited engraftment and differentiation capabilities. This review examines how key intrinsic cues and extrinsic environmental inputs have been integrated within human PSC differentiation protocols to enhance the emergence of definitive hematopoiesis and how advances in genomics set the stage for imminent breakthroughs in this field.
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Affiliation(s)
| | | | - Andre Larochelle
- Cellular and Molecular Therapeutics Branch, National Heart Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, MD 20892, USA
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16
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Ouyang JF, Chothani S, Rackham OJL. Deep learning models will shape the future of stem cell research. Stem Cell Reports 2023; 18:6-12. [PMID: 36630908 PMCID: PMC9860061 DOI: 10.1016/j.stemcr.2022.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 11/10/2022] [Accepted: 11/11/2022] [Indexed: 01/12/2023] Open
Abstract
Our ability to understand and control stem cell biology is being augmented by developments on two fronts, our ability to collect more data describing cell state and our capability to comprehend these data using deep learning models. Here we consider the impact deep learning will have in the future of stem cell research. We explore the importance of generating data suitable for these methods, the requirement for close collaboration between experimental and computational researchers, and the challenges we face to do this fairly and effectively. Achieving this will ensure that the resulting deep learning models are biologically meaningful and computationally tractable.
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Affiliation(s)
- John F Ouyang
- Duke-NUS Medical School, Program in Cardiovascular and Metabolic Disorders (CVMD) and Centre for Computational Biology (CCB), Singapore, Singapore
| | - Sonia Chothani
- Duke-NUS Medical School, Program in Cardiovascular and Metabolic Disorders (CVMD) and Centre for Computational Biology (CCB), Singapore, Singapore
| | - Owen J L Rackham
- Duke-NUS Medical School, Program in Cardiovascular and Metabolic Disorders (CVMD) and Centre for Computational Biology (CCB), Singapore, Singapore; School of Biological Sciences, University of Southampton, Southampton, UK; The Alan Turing Institute, The British Library, London, UK.
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17
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Sugihara R, Kato Y, Mori T, Kawahara Y. Alignment of single-cell trajectory trees with CAPITAL. Nat Commun 2022; 13:5972. [PMID: 36241645 PMCID: PMC9568509 DOI: 10.1038/s41467-022-33681-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 09/26/2022] [Indexed: 12/03/2022] Open
Abstract
Global alignment of complex pseudotime trajectories between different single-cell RNA-seq datasets is challenging, as existing tools mainly focus on linear alignment of single-cell trajectories. Here we present CAPITAL (comparative analysis of pseudotime trajectory inference with tree alignment), a method for comparing single-cell trajectories with tree alignment whereby branching trajectories can be automatically compared. Computational tests on synthetic datasets and authentic bone marrow cells datasets indicate that CAPITAL has achieved accurate and robust alignments of trajectory trees, revealing various gene expression dynamics including gene–gene correlation conservation between different species. Global alignment of complex cell state trajectories between single-cell datasets remains challenging. Here, the authors present a computational method called CAPITAL to compare branching trajectories, and demonstrate that this method achieves accurate and robust alignments.
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Affiliation(s)
- Reiichi Sugihara
- Department of RNA Biology and Neuroscience, Graduate School of Medicine, Osaka University, 2-2 Yamada-oka, Suita, Osaka, 565-0871, Japan
| | - Yuki Kato
- Department of RNA Biology and Neuroscience, Graduate School of Medicine, Osaka University, 2-2 Yamada-oka, Suita, Osaka, 565-0871, Japan. .,Integrated Frontier Research for Medical Science Division, and RNA Frontier Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, 2-2 Yamada-oka, Suita, Osaka, 565-0871, Japan.
| | - Tomoya Mori
- Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611-0011, Japan
| | - Yukio Kawahara
- Department of RNA Biology and Neuroscience, Graduate School of Medicine, Osaka University, 2-2 Yamada-oka, Suita, Osaka, 565-0871, Japan.,Integrated Frontier Research for Medical Science Division, and RNA Frontier Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, 2-2 Yamada-oka, Suita, Osaka, 565-0871, Japan
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18
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Yang XH, Goldstein A, Sun Y, Wang Z, Wei M, Moskowitz I, Cunningham J. Detecting critical transition signals from single-cell transcriptomes to infer lineage-determining transcription factors. Nucleic Acids Res 2022; 50:e91. [PMID: 35640613 PMCID: PMC9458468 DOI: 10.1093/nar/gkac452] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 04/02/2022] [Accepted: 05/13/2022] [Indexed: 12/29/2022] Open
Abstract
Analyzing single-cell transcriptomes promises to decipher the plasticity, heterogeneity, and rapid switches in developmental cellular state transitions. Such analyses require the identification of gene markers for semi-stable transition states. However, there are nontrivial challenges such as unexplainable stochasticity, variable population sizes, and alternative trajectory constructions. By advancing current tipping-point theory-based models with feature selection, network decomposition, accurate estimation of correlations, and optimization, we developed BioTIP to overcome these challenges. BioTIP identifies a small group of genes, called critical transition signal (CTS), to characterize regulated stochasticity during semi-stable transitions. Although methods rooted in different theories converged at the same transition events in two benchmark datasets, BioTIP is unique in inferring lineage-determining transcription factors governing critical transition. Applying BioTIP to mouse gastrulation data, we identify multiple CTSs from one dataset and validated their significance in another independent dataset. We detect the established regulator Etv2 whose expression change drives the haemato-endothelial bifurcation, and its targets together in CTS across three datasets. After comparing to three current methods using six datasets, we show that BioTIP is accurate, user-friendly, independent of pseudo-temporal trajectory, and captures significantly interconnected and reproducible CTSs. We expect BioTIP to provide great insight into dynamic regulations of lineage-determining factors.
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Affiliation(s)
- Xinan H Yang
- Department of Pediatrics, The University of Chicago, Chicago, IL, USA
| | - Andrew Goldstein
- Department of Statistics, The University of Chicago, Chicago IL, USA
| | - Yuxi Sun
- Department of Pediatrics, The University of Chicago, Chicago, IL, USA
| | - Zhezhen Wang
- Department of Pediatrics, The University of Chicago, Chicago, IL, USA
| | - Megan Wei
- Johns Hopkins University, Baltimore, MD, USA
| | - Ivan P Moskowitz
- Department of Pediatrics, The University of Chicago, Chicago, IL, USA
| | - John M Cunningham
- Department of Pediatrics, The University of Chicago, Chicago, IL, USA
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19
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Lin PC, Tsai YS, Yeh YM, Shen MR. Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care. Biomolecules 2022; 12:1133. [PMID: 36009026 PMCID: PMC9405970 DOI: 10.3390/biom12081133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 08/11/2022] [Accepted: 08/15/2022] [Indexed: 11/18/2022] Open
Abstract
To provide precision medicine for better cancer care, researchers must work on clinical patient data, such as electronic medical records, physiological measurements, biochemistry, computerized tomography scans, digital pathology, and the genetic landscape of cancer tissue. To interpret big biodata in cancer genomics, an operational flow based on artificial intelligence (AI) models and medical management platforms with high-performance computing must be set up for precision cancer genomics in clinical practice. To work in the fast-evolving fields of patient care, clinical diagnostics, and therapeutic services, clinicians must understand the fundamentals of the AI tool approach. Therefore, the present article covers the following four themes: (i) computational prediction of pathogenic variants of cancer susceptibility genes; (ii) AI model for mutational analysis; (iii) single-cell genomics and computational biology; (iv) text mining for identifying gene targets in cancer; and (v) the NVIDIA graphics processing units, DRAGEN field programmable gate arrays systems and AI medical cloud platforms in clinical next-generation sequencing laboratories. Based on AI medical platforms and visualization, large amounts of clinical biodata can be rapidly copied and understood using an AI pipeline. The use of innovative AI technologies can deliver more accurate and rapid cancer therapy targets.
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Affiliation(s)
- Peng-Chan Lin
- Department of Oncology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
- Department of Genomic Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Yi-Shan Tsai
- Department of Medical Imaging, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Yu-Min Yeh
- Department of Oncology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Meng-Ru Shen
- Institute of Clinical Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
- Department of Obstetrics and Gynecology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
- Department of Pharmacology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
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20
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Jing R, Scarfo I, Najia MA, Lummertz da Rocha E, Han A, Sanborn M, Bingham T, Kubaczka C, Jha DK, Falchetti M, Schlaeger TM, North TE, Maus MV, Daley GQ. EZH1 repression generates mature iPSC-derived CAR T cells with enhanced antitumor activity. Cell Stem Cell 2022; 29:1181-1196.e6. [PMID: 35931029 PMCID: PMC9386785 DOI: 10.1016/j.stem.2022.06.014] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 05/31/2022] [Accepted: 06/29/2022] [Indexed: 01/12/2023]
Abstract
Human induced pluripotent stem cells (iPSCs) provide a potentially unlimited resource for cell therapies, but the derivation of mature cell types remains challenging. The histone methyltransferase EZH1 is a negative regulator of lymphoid potential during embryonic hematopoiesis. Here, we demonstrate that EZH1 repression facilitates in vitro differentiation and maturation of T cells from iPSCs. Coupling a stroma-free T cell differentiation system with EZH1-knockdown-mediated epigenetic reprogramming, we generated iPSC-derived T cells, termed EZ-T cells, which display a highly diverse T cell receptor (TCR) repertoire and mature molecular signatures similar to those of TCRαβ T cells from peripheral blood. Upon activation, EZ-T cells give rise to effector and memory T cell subsets. When transduced with chimeric antigen receptors (CARs), EZ-T cells exhibit potent antitumor activities in vitro and in xenograft models. Epigenetic remodeling via EZH1 repression allows efficient production of developmentally mature T cells from iPSCs for applications in adoptive cell therapy.
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Affiliation(s)
- Ran Jing
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Irene Scarfo
- Cellular Immunotherapy Program, Massachusetts General Hospital Cancer Center, Charlestown, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Mohamad Ali Najia
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Edroaldo Lummertz da Rocha
- Department of Microbiology, Immunology and Parasitology, Federal University of Santa Catarina, Florianópolis, SC 88040-900, Brazil
| | - Areum Han
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Michael Sanborn
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Trevor Bingham
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Caroline Kubaczka
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Deepak K Jha
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Marcelo Falchetti
- Graduate Program of Pharmacology, Center for Biological Sciences, Federal University of Santa Catarina, Florianópolis, SC 88040-900, Brazil
| | - Thorsten M Schlaeger
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA 02115, USA
| | - Trista E North
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA 02115, USA; Developmental and Regenerative Biology Program, Harvard Medical School, Boston, MA 02115, USA
| | - Marcela V Maus
- Cellular Immunotherapy Program, Massachusetts General Hospital Cancer Center, Charlestown, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - George Q Daley
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA; Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA 02115, USA; Developmental and Regenerative Biology Program, Harvard Medical School, Boston, MA 02115, USA.
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21
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Uthamacumaran A. Dissecting cell fate dynamics in pediatric glioblastoma through the lens of complex systems and cellular cybernetics. BIOLOGICAL CYBERNETICS 2022; 116:407-445. [PMID: 35678918 DOI: 10.1007/s00422-022-00935-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 05/04/2022] [Indexed: 06/15/2023]
Abstract
Cancers are complex dynamic ecosystems. Reductionist approaches to science are inadequate in characterizing their self-organized patterns and collective emergent behaviors. Since current approaches to single-cell analysis in cancer systems rely primarily on single time-point multiomics, many of the temporal features and causal adaptive behaviors in cancer dynamics are vastly ignored. As such, tools and concepts from the interdisciplinary paradigm of complex systems theory are introduced herein to decode the cellular cybernetics of cancer differentiation dynamics and behavioral patterns. An intuition for the attractors and complex networks underlying cancer processes such as cell fate decision-making, multiscale pattern formation systems, and epigenetic state-transitions is developed. The applications of complex systems physics in paving targeted therapies and causal pattern discovery in precision oncology are discussed. Pediatric high-grade gliomas are discussed as a model-system to demonstrate that cancers are complex adaptive systems, in which the emergence and selection of heterogeneous cellular states and phenotypic plasticity are driven by complex multiscale network dynamics. In specific, pediatric glioblastoma (GBM) is used as a proof-of-concept model to illustrate the applications of the complex systems framework in understanding GBM cell fate decisions and decoding their adaptive cellular dynamics. The scope of these tools in forecasting cancer cell fate dynamics in the emerging field of computational oncology and patient-centered systems medicine is highlighted.
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22
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Gan Y, Guo C, Guo W, Xu G, Zou G. Entropy-based inference of transition states and cellular trajectory for single-cell transcriptomics. Brief Bioinform 2022; 23:6607748. [PMID: 35696651 DOI: 10.1093/bib/bbac225] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 05/11/2022] [Accepted: 05/12/2022] [Indexed: 11/12/2022] Open
Abstract
The development of single-cell RNA-seq (scRNA-seq) technology allows researchers to characterize the cell types, states and transitions during dynamic biological processes at single-cell resolution. One of the critical tasks is to infer pseudo-time trajectory. However, the existence of transition cells in the intermediate state of complex biological processes poses a challenge for the trajectory inference. Here, we propose a new single-cell trajectory inference method based on transition entropy, named scTite, to identify transitional states and reconstruct cell trajectory from scRNA-seq data. Taking into account the continuity of cellular processes, we introduce a new metric called transition entropy to measure the uncertainty of a cell belonging to different cell clusters, and then identify cell states and transition cells. Specifically, we adopt different strategies to infer the trajectory for the identified cell states and transition cells, and combine them to obtain a detailed cell trajectory. For the identified cell clusters, we utilize the Wasserstein distance based on the probability distribution to calculate distance between clusters, and construct the minimum spanning tree. Meanwhile, we adopt the signaling entropy and partial correlation coefficient to determine transition paths, which contain a group of transition cells with the largest similarity. Then the transitional paths and the MST are combined to infer a refined cell trajectory. We apply scTite to four real scRNA-seq datasets and an integrated dataset, and conduct extensive performance comparison with nine existing trajectory inference methods. The experimental results demonstrate that the proposed method can reconstruct the cell trajectory more accurately than the compared algorithms. The scTite software package is available at https://github.com/dblab2022/scTite.
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Affiliation(s)
- Yanglan Gan
- School of Computer Science and Technology, Donghua University, 201600, Shanghai, China
| | - Cheng Guo
- School of Computer Science and Technology, Donghua University, 201600, Shanghai, China
| | - Wenjing Guo
- School of Computer Science and Technology, Donghua University, 201600, Shanghai, China
| | - Guangwei Xu
- School of Computer Science and Technology, Donghua University, 201600, Shanghai, China
| | - Guobing Zou
- School of Computer Science and Technology, Shanghai University, 200444, Shanghai, China
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23
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Patel SH, Christodoulou C, Weinreb C, Yu Q, da Rocha EL, Pepe-Mooney BJ, Bowling S, Li L, Osorio FG, Daley GQ, Camargo FD. Lifelong multilineage contribution by embryonic-born blood progenitors. Nature 2022; 606:747-753. [PMID: 35705805 DOI: 10.1038/s41586-022-04804-z] [Citation(s) in RCA: 83] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 04/26/2022] [Indexed: 11/08/2022]
Abstract
Haematopoietic stem cells (HSCs) arise in the embryo from the arterial endothelium through a process known as the endothelial-to-haematopoietic transition (EHT)1-4. This process generates hundreds of blood progenitors, of which a fraction go on to become definitive HSCs. It is generally thought that most adult blood is derived from those HSCs, but to what extent other progenitors contribute to adult haematopoiesis is not known. Here we use in situ barcoding and classical fate mapping to assess the developmental and clonal origins of adult blood in mice. Our analysis uncovers an early wave of progenitor specification-independent of traditional HSCs-that begins soon after EHT. These embryonic multipotent progenitors (eMPPs) predominantly drive haematopoiesis in the young adult, have a decreasing yet lifelong contribution over time and are the predominant source of lymphoid output. Putative eMPPs are specified within intra-arterial haematopoietic clusters and represent one fate of the earliest haematopoietic progenitors. Altogether, our results reveal functional heterogeneity during the definitive wave that leads to distinct sources of adult blood.
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Affiliation(s)
- Sachin H Patel
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
| | | | - Caleb Weinreb
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Qi Yu
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
| | - Edroaldo Lummertz da Rocha
- Department of Microbiology, Immunology and Parasitology, Federal University of Santa Catarina, Florianópolis, Brazil
| | | | - Sarah Bowling
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
| | - Li Li
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
| | | | - George Q Daley
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - Fernando D Camargo
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA.
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.
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24
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Morris V, Wang D, Li Z, Marion W, Hughes T, Sousa P, Harada T, Sui SH, Naumenko S, Kalfon J, Sensharma P, Falchetti M, Vinicius da Silva R, Candelli T, Schneider P, Margaritis T, Holstege FCP, Pikman Y, Harris M, Stam RW, Orkin SH, Koehler AN, Shalek AK, North TE, Pimkin M, Daley GQ, Lummertz da Rocha E, Rowe RG. Hypoxic, glycolytic metabolism is a vulnerability of B-acute lymphoblastic leukemia-initiating cells. Cell Rep 2022; 39:110752. [PMID: 35476984 PMCID: PMC9099058 DOI: 10.1016/j.celrep.2022.110752] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 01/24/2022] [Accepted: 04/07/2022] [Indexed: 02/06/2023] Open
Abstract
High-risk forms of B-acute lymphoblastic leukemia (B-ALL) remain a therapeutic challenge. Leukemia-initiating cells (LICs) self-renew and spark relapse and therefore have been the subject of intensive investigation; however, the properties of LICs in high-risk B-ALL are not well understood. Here, we use single-cell transcriptomics and quantitative xenotransplantation to understand LICs in MLL-rearranged (MLL-r) B-ALL. Compared with reported LIC frequencies in acute myeloid leukemia (AML), engraftable LICs in MLL-r B-ALL are abundant. Although we find that multipotent, self-renewing LICs are enriched among phenotypically undifferentiated B-ALL cells, LICs with the capacity to replenish the leukemic cellular diversity can emerge from more mature fractions. While inhibiting oxidative phosphorylation blunts blast proliferation, this intervention promotes LIC emergence. Conversely, inhibiting hypoxia and glycolysis impairs MLL-r B-ALL LICs, providing a therapeutic benefit in xenotransplantation systems. These findings provide insight into the aggressive nature of MLL-r B-ALL and provide a rationale for therapeutic targeting of hypoxia and glycolysis.
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Affiliation(s)
- Vivian Morris
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Dahai Wang
- Stem Cell Transplantation Program, Department of Hematology, Boston Children's Hospital, Boston, MA 02115, USA
| | - Zhiheng Li
- Stem Cell Transplantation Program, Department of Hematology, Boston Children's Hospital, Boston, MA 02115, USA
| | - William Marion
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Travis Hughes
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Patricia Sousa
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA
| | - Taku Harada
- Cancer and Blood Disorders Center, Dana-Farber Cancer Institute and Boston Children's Hospital, Boston, MA 02115, USA
| | - Shannan Ho Sui
- Harvard Chan Bioinformatics Core, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Sergey Naumenko
- Harvard Chan Bioinformatics Core, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Jérémie Kalfon
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Prerana Sensharma
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Stem Cell Transplantation Program, Department of Hematology, Boston Children's Hospital, Boston, MA 02115, USA
| | - Marcelo Falchetti
- Graduate Program of Pharmacology, Center for Biological Sciences, Federal University of Santa Catarina, Florianópolis, Santa Catarina 88040-900, Brazil
| | - Renan Vinicius da Silva
- Graduate Program of Pharmacology, Center for Biological Sciences, Federal University of Santa Catarina, Florianópolis, Santa Catarina 88040-900, Brazil
| | - Tito Candelli
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Pauline Schneider
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | | | | | - Yana Pikman
- Harvard Medical School, Boston, MA 02115, USA; Cancer and Blood Disorders Center, Dana-Farber Cancer Institute and Boston Children's Hospital, Boston, MA 02115, USA
| | - Marian Harris
- Harvard Medical School, Boston, MA 02115, USA; Department of Pathology, Boston Children's Hospital, Boston, MA 02115, USA
| | - Ronald W Stam
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Stuart H Orkin
- Harvard Medical School, Boston, MA 02115, USA; Cancer and Blood Disorders Center, Dana-Farber Cancer Institute and Boston Children's Hospital, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston, MA 02115, USA
| | - Angela N Koehler
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Alex K Shalek
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Institute for Medical Engineering & Science, Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
| | - Trista E North
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Maxim Pimkin
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Cancer and Blood Disorders Center, Dana-Farber Cancer Institute and Boston Children's Hospital, Boston, MA 02115, USA
| | - George Q Daley
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Edroaldo Lummertz da Rocha
- Department of Microbiology, Immunology and Parasitology, Federal University of Santa Catarina, Florianópolis Santa Catarina 88040-900, Brazil
| | - R Grant Rowe
- Stem Cell Program, Boston Children's Hospital, Boston, MA 02115, USA; Stem Cell Transplantation Program, Department of Hematology, Boston Children's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Cancer and Blood Disorders Center, Dana-Farber Cancer Institute and Boston Children's Hospital, Boston, MA 02115, USA.
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25
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Lummertz da Rocha E, Kubaczka C, Sugden WW, Najia MA, Jing R, Markel A, LeBlanc ZC, Dos Santos Peixoto R, Falchetti M, Collins JJ, North TE, Daley GQ. CellComm infers cellular crosstalk that drives haematopoietic stem and progenitor cell development. Nat Cell Biol 2022; 24:579-589. [PMID: 35414020 PMCID: PMC10123873 DOI: 10.1038/s41556-022-00884-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 03/01/2022] [Indexed: 01/05/2023]
Abstract
Intercellular communication orchestrates a multitude of physiologic and pathologic conditions. Algorithms to infer cell-cell communication and predict downstream signalling and regulatory networks are needed to illuminate mechanisms of stem cell differentiation and tissue development. Here, to fill this gap, we developed and applied CellComm to investigate how the aorta-gonad-mesonephros microenvironment dictates haematopoietic stem and progenitor cell emergence. We identified key microenvironmental signals and transcriptional networks that regulate haematopoietic development, including Stat3, Nr0b2, Ybx1 and App, and confirmed their roles using zebrafish, mouse and human models. Notably, CellComm revealed extensive crosstalk among signalling pathways and convergence on common transcriptional regulators, indicating a resilient developmental programme that ensures dynamic adaptation to changes in the embryonic environment. Our work provides an algorithm and data resource for the scientific community.
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Affiliation(s)
- Edroaldo Lummertz da Rocha
- Department of Microbiology, Immunology and Parasitology, Federal University of Santa Catarina, Florianópolis, Brazil
| | - Caroline Kubaczka
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - Wade W Sugden
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA
| | - Mohamad Ali Najia
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ran Jing
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - Arianna Markel
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - Zachary C LeBlanc
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA
| | - Rafael Dos Santos Peixoto
- Undergraduate program in Automation and Control Engineering, Federal University of Santa Catarina, Florianópolis, Brazil
| | - Marcelo Falchetti
- Graduate Program of Pharmacology, Center for Biological Sciences, Federal University of Santa Catarina, Florianópolis, Brazil
| | - James J Collins
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Trista E North
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA.
- Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA.
| | - George Q Daley
- Stem Cell Program, Boston Children's Hospital, Boston, MA, USA.
- Division of Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Boston, MA, USA.
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA.
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26
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Single cell RNA sequencing reveals differentiation related genes with drawing implications in predicting prognosis and immunotherapy response in gliomas. Sci Rep 2022; 12:1872. [PMID: 35115572 PMCID: PMC8814011 DOI: 10.1038/s41598-022-05686-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 01/17/2022] [Indexed: 11/30/2022] Open
Abstract
Differentiation states of glioma cells correlated with prognosis and tumor-immune microenvironment (TIME) in patients with gliomas. We aimed to identify differentiation related genes (DRGs) for predicting the prognosis and immunotherapy response in patients with gliomas. We identified three differentiation states and the corresponding DRGs in glioma cells through single-cell transcriptomics analysis. Based on the DRGs, we separated glioma patients into three clusters with distinct clinicopathological features in combination with bulk RNA-seq data. Weighted correlation network analysis, univariate cox regression analysis and least absolute shrinkage and selection operator analysis were involved in the construction of the prognostic model based on DRGs. Distinct clinicopathological characteristics, TIME, immunogenomic patterns and immunotherapy responses were identified across three clusters. A DRG signature composing of 12 genes were identified for predicting the survival of glioma patients and nomogram model integrating the risk score and multi-clinicopathological factors were constructed for clinical practice. Patients in high-risk group tended to get shorter overall survival and better response to immune checkpoint blockage therapy. We obtained 9 candidate drugs through comprehensive analysis of the differentially expressed genes between the low and high-risk groups in the model. Our findings indicated that the risk score may not only contribute to the determination of prognosis but also facilitate in the prediction of immunotherapy response in glioma patients.
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27
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Song Q, Liu L. Single-Cell RNA-Seq Technologies and Computational Analysis Tools: Application in Cancer Research. Methods Mol Biol 2022; 2413:245-255. [PMID: 35044670 DOI: 10.1007/978-1-0716-1896-7_23] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The recent maturation of single-cell RNA sequencing (scRNA-seq) provides unique opportunities for researchers to uncover new and potentially unexpected biological discoveries and to understand the complexity of tissues by transcriptomic profiling in individual cells. This review introduces the latest scRNA-seq techniques and platforms as well as their advantages and disadvantages. Moreover, we review computational tools and pipelines for analyzing scRNA-seq data, and their applications in cancer research, highlighting the important role of scRNA-seq techniques in this area.
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Affiliation(s)
- Qianqian Song
- Department of Cancer Biology, Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC, USA
| | - Liang Liu
- Department of Cancer Biology, Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC, USA.
- Center for Cancer Genomics and Precision Oncology, Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC, USA.
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28
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Zhang J, Kaye AP, Wang J, Girgenti MJ. Transcriptomics of the depressed and PTSD brain. Neurobiol Stress 2021; 15:100408. [PMID: 34703849 PMCID: PMC8524242 DOI: 10.1016/j.ynstr.2021.100408] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 10/07/2021] [Accepted: 10/09/2021] [Indexed: 12/13/2022] Open
Abstract
Stress is the response of an organism to demands for change, yet excessive or chronic stress contributes to nearly all psychiatric disorders. The advent of high-throughput transcriptomic methods such as single cell RNA sequencing poses new opportunities to understand the neurobiology of stress, yet substantial barriers to understanding stress remain. Stress adaptation is an organismal survival mechanism conserved across all organisms, yet there is an infinity of potential stressful experiences. Unraveling shared and separate transcriptional programs for adapting to stressful experience remains a challenge, despite methodological and analytic advances. Here we review the state of the field focusing on the technologies used to study the transcriptome for the stress neurobiologist, and also attempt to identify central questions about the heterogeneity of stress for those applying transcriptomic approaches. We further explore how postmortem transcriptome studies aided by preclinical animal models are converging on common molecular pathways for adaptation to aversive experience. Finally, we discuss approaches to integrate large genomic datasets with human neuroimaging and other datasets.
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Affiliation(s)
- Jing Zhang
- Department of Computer Science, University of California- Irvine, Irvine, CA, USA
| | - Alfred P. Kaye
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Jiawei Wang
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Matthew J. Girgenti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- National Center for PTSD, U.S. Department of Veterans Affairs, USA
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29
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Sugden WW, North TE. Making Blood from the Vessel: Extrinsic and Environmental Cues Guiding the Endothelial-to-Hematopoietic Transition. Life (Basel) 2021; 11:life11101027. [PMID: 34685398 PMCID: PMC8539454 DOI: 10.3390/life11101027] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 09/25/2021] [Accepted: 09/27/2021] [Indexed: 01/10/2023] Open
Abstract
It is increasingly recognized that specialized subsets of endothelial cells carry out unique functions in specific organs and regions of the vascular tree. Perhaps the most striking example of this specialization is the ability to contribute to the generation of the blood system, in which a distinct population of “hemogenic” endothelial cells in the embryo transforms irreversibly into hematopoietic stem and progenitor cells that produce circulating erythroid, myeloid and lymphoid cells for the lifetime of an animal. This review will focus on recent advances made in the zebrafish model organism uncovering the extrinsic and environmental factors that facilitate hemogenic commitment and the process of endothelial-to-hematopoietic transition that produces blood stem cells. We highlight in particular biomechanical influences of hemodynamic forces and the extracellular matrix, metabolic and sterile inflammatory cues present during this developmental stage, and outline new avenues opened by transcriptomic-based approaches to decipher cell–cell communication mechanisms as examples of key signals in the embryonic niche that regulate hematopoiesis.
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Affiliation(s)
- Wade W. Sugden
- Stem Cell Program, Department of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115, USA;
- Developmental and Regenerative Biology Program, Harvard Medical School, Boston, MA 02115, USA
| | - Trista E. North
- Stem Cell Program, Department of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115, USA;
- Developmental and Regenerative Biology Program, Harvard Medical School, Boston, MA 02115, USA
- Correspondence:
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30
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Guo WF, Zhang SW, Zeng T, Akutsu T, Chen L. Network control principles for identifying personalized driver genes in cancer. Brief Bioinform 2021; 21:1641-1662. [PMID: 31711128 DOI: 10.1093/bib/bbz089] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 06/26/2019] [Accepted: 06/27/2019] [Indexed: 02/02/2023] Open
Abstract
To understand tumor heterogeneity in cancer, personalized driver genes (PDGs) need to be identified for unraveling the genotype-phenotype associations corresponding to particular patients. However, most of the existing driver-focus methods mainly pay attention on the cohort information rather than on individual information. Recent developing computational approaches based on network control principles are opening a new way to discover driver genes in cancer, particularly at an individual level. To provide comprehensive perspectives of network control methods on this timely topic, we first considered the cancer progression as a network control problem, in which the expected PDGs are altered genes by oncogene activation signals that can change the individual molecular network from one health state to the other disease state. Then, we reviewed the network reconstruction methods on single samples and introduced novel network control methods on single-sample networks to identify PDGs in cancer. Particularly, we gave a performance assessment of the network structure control-based PDGs identification methods on multiple cancer datasets from TCGA, for which the data and evaluation package also are publicly available. Finally, we discussed future directions for the application of network control methods to identify PDGs in cancer and diverse biological processes.
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Affiliation(s)
- Wei-Feng Guo
- Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Shao-Wu Zhang
- Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Tao Zeng
- Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Tatsuya Akutsu
- Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, 611-0011, Japan
| | - Luonan Chen
- Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi'an 710072, China.,Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China.,School of Life Science and Technology, ShanghaiTech University, 201210 Shanghai, China.,Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai 201210, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
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31
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Roles of the Immune/Methylation/Autophagy Landscape on Single-Cell Genotypes and Stroke Risk in Breast Cancer Microenvironment. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2021; 2021:5633514. [PMID: 34457116 PMCID: PMC8397558 DOI: 10.1155/2021/5633514] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/29/2021] [Accepted: 07/14/2021] [Indexed: 12/16/2022]
Abstract
This study sought to perform integrative analysis of the immune/methylation/autophagy landscape on breast cancer prognosis and single-cell genotypes. Breast Cancer Recurrence Risk Score (BCRRS) and Breast Cancer Prognostic Risk Score (BCPRS) were determined based on 6 prognostic IMAAGs obtained from the TCGA-BRCA cohort. BCRRS and BCPRS, respectively, were used to construct a risk prediction model of overall survival and progression-free survival. Predictive capacity of the model was evaluated using clinical data. Analysis showed that BCRRS is associated with a high risk of stroke. In addition, PPI and drug-ceRNA networks based on differences in BCPRS were constructed. Single cells were genotyped through integrated scRNA-seq of the TNBC samples based on clustering results of BCPRS-related genes. The findings of this study show the potential regulatory effects of IMAAGs on breast cancer tumor microenvironment. High AUCs of 0.856 and 0.842 were obtained for the OS and PFS prognostic models, respectively. scRNA-seq analysis showed high expression levels of adipocytes and adipose tissue macrophages (ATMs) in high BCPRS clusters. Moreover, analysis of ligand-receptor interactions and potential regulatory mechanisms were performed. The LINC00276&MALAT1/miR-206/FZD4-Wnt7b pathway was also identified which may be useful in future research on targets against breast cancer metastasis and recurrence. Neural network-based deep learning models using BCPRS-related genes showed that these genes can be used to map the tumor microenvironment. In summary, analysis of IMAAGs, BCPRS, and BCRRS provides information on the breast cancer microenvironment at both the macro- and microlevels and provides a basis for development of personalized treatment therapy.
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32
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Chen Y, Zhang Y, Li JYH, Ouyang Z. LISA2: Learning Complex Single-Cell Trajectory and Expression Trends. Front Genet 2021; 12:681206. [PMID: 34512717 PMCID: PMC8428276 DOI: 10.3389/fgene.2021.681206] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 06/01/2021] [Indexed: 12/20/2022] Open
Abstract
Single-cell transcriptional and epigenomics profiles have been applied in a variety of tissues and diseases for discovering new cell types, differentiation trajectories, and gene regulatory networks. Many methods such as Monocle 2/3, URD, and STREAM have been developed for tree-based trajectory building. Here, we propose a fast and flexible trajectory learning method, LISA2, for single-cell data analysis. This new method has two distinctive features: (1) LISA2 utilizes specified leaves and root to reduce the complexity for building the developmental trajectory, especially for some special cases such as rare cell populations and adjacent terminal cell states; and (2) LISA2 is applicable for both transcriptomics and epigenomics data. LISA2 visualizes complex trajectories using 3D Landmark ISOmetric feature MAPping (L-ISOMAP). We apply LISA2 to simulation and real datasets in cerebellum, diencephalon, and hematopoietic stem cells including both single-cell transcriptomics data and single-cell assay for transposase-accessible chromatin data. LISA2 is efficient in estimating single-cell trajectory and expression trends for different kinds of molecular state of cells.
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Affiliation(s)
- Yang Chen
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, United States
| | - Yuping Zhang
- Department of Statistics, University of Connecticut, Storrs, CT, United States
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, United States
| | - James Y. H. Li
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, United States
- Department of Genetics and Genome Sciences, School of Medicine, University of Connecticut, Farmington, CT, United States
| | - Zhengqing Ouyang
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, United States
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33
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Cannoodt R, Saelens W, Deconinck L, Saeys Y. Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells. Nat Commun 2021; 12:3942. [PMID: 34168133 PMCID: PMC8225657 DOI: 10.1038/s41467-021-24152-2] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 05/27/2021] [Indexed: 02/05/2023] Open
Abstract
We present dyngen, a multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution. dyngen is more flexible than current single-cell simulation engines, and allows better method development and benchmarking, thereby stimulating development and testing of computational methods. We demonstrate its potential for spearheading computational methods on three applications: aligning cell developmental trajectories, cell-specific regulatory network inference and estimation of RNA velocity.
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Affiliation(s)
- Robrecht Cannoodt
- grid.11486.3a0000000104788040Data Mining and Modelling for Biomedicine group, VIB Center for Inflammation Research, Ghent, Belgium ,grid.5342.00000 0001 2069 7798Department of Applied Mathematics, Computer Science, and Statistics, Ghent University, Ghent, Belgium ,Data Intuitive, Lebbeke, Belgium
| | - Wouter Saelens
- grid.11486.3a0000000104788040Data Mining and Modelling for Biomedicine group, VIB Center for Inflammation Research, Ghent, Belgium ,grid.5342.00000 0001 2069 7798Department of Applied Mathematics, Computer Science, and Statistics, Ghent University, Ghent, Belgium ,grid.5333.60000000121839049Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Louise Deconinck
- grid.11486.3a0000000104788040Data Mining and Modelling for Biomedicine group, VIB Center for Inflammation Research, Ghent, Belgium ,grid.5342.00000 0001 2069 7798Department of Applied Mathematics, Computer Science, and Statistics, Ghent University, Ghent, Belgium
| | - Yvan Saeys
- grid.11486.3a0000000104788040Data Mining and Modelling for Biomedicine group, VIB Center for Inflammation Research, Ghent, Belgium ,grid.5342.00000 0001 2069 7798Department of Applied Mathematics, Computer Science, and Statistics, Ghent University, Ghent, Belgium
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34
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Liu J, Xu T, Jin Y, Huang B, Zhang Y. Progress and Clinical Application of Single-Cell Transcriptional Sequencing Technology in Cancer Research. Front Oncol 2021; 10:593085. [PMID: 33614479 PMCID: PMC7886993 DOI: 10.3389/fonc.2020.593085] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Accepted: 12/21/2020] [Indexed: 12/15/2022] Open
Abstract
Cancer has been a daunting challenge for human beings because of its clonal heterogeneity and compositional complexity. Tumors are composed of cancer cells and a variety of non-cancer cells, which together with the extracellular matrix form the tumor microenvironment. These cancer-related cells and components and immune mechanisms can affect the development and progression of cancer and are associated with patient diagnosis, treatment and prognosis. As the first choice for the study of complex biological systems, single-cell transcriptional sequencing (scRNA-seq) has been widely used in cancer research. ScRNA-seq has made breakthrough discoveries in tumor heterogeneity, tumor evolution, metastasis and spread, development of chemoresistance, and the relationship between the tumor microenvironment and the immune system. These results will guide clinical cancer treatment and promote personalized and highly accurate cancer treatment. In this paper, we summarize the latest research progress of scRNA-seq and its guiding significance for clinical treatment.
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Affiliation(s)
- Jian Liu
- Department of Gynaecology and Obstetrics, Jilin University Second Hospital, ChangChun, China
| | - Tianmin Xu
- Department of Gynaecology and Obstetrics, Jilin University Second Hospital, ChangChun, China
| | - Yuemei Jin
- Department of Gynaecology and Obstetrics, Jilin University Second Hospital, ChangChun, China
| | - Bingyu Huang
- Department of Gynaecology and Obstetrics, Jilin University Second Hospital, ChangChun, China
| | - Yan Zhang
- Department of Breast Surgery, Jilin University Second Hospital, ChangChun, China
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35
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Wang YXR, Li L, Li JJ, Huang H. Network Modeling in Biology: Statistical Methods for Gene and Brain Networks. Stat Sci 2021; 36:89-108. [PMID: 34305304 PMCID: PMC8296984 DOI: 10.1214/20-sts792] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The rise of network data in many different domains has offered researchers new insight into the problem of modeling complex systems and propelled the development of numerous innovative statistical methodologies and computational tools. In this paper, we primarily focus on two types of biological networks, gene networks and brain networks, where statistical network modeling has found both fruitful and challenging applications. Unlike other network examples such as social networks where network edges can be directly observed, both gene and brain networks require careful estimation of edges using covariates as a first step. We provide a discussion on existing statistical and computational methods for edge esitimation and subsequent statistical inference problems in these two types of biological networks.
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Affiliation(s)
- Y X Rachel Wang
- School of Mathematics and Statistics, University of Sydney, Australia
| | - Lexin Li
- Department of Biostatistics and Epidemiology, School of Public Health, University of California, Berkeley
| | | | - Haiyan Huang
- Department of Statistics, University of California, Berkeley
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36
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Qin P, Pang Y, Hou W, Fu R, Zhang Y, Wang X, Meng G, Liu Q, Zhu X, Hong N, Cheng T, Jin W. Integrated decoding hematopoiesis and leukemogenesis using single-cell sequencing and its medical implication. Cell Discov 2021; 7:2. [PMID: 33408321 PMCID: PMC7788081 DOI: 10.1038/s41421-020-00223-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 10/01/2020] [Indexed: 12/30/2022] Open
Abstract
Single-cell RNA sequencing provides exciting opportunities to unbiasedly study hematopoiesis. However, our understanding of leukemogenesis was limited due to the high individual differences. Integrated analyses of hematopoiesis and leukemogenesis potentially provides new insights. Here we analyzed ~200,000 single-cell transcriptomes of bone marrow mononuclear cells (BMMCs) and its subsets from 23 clinical samples. We constructed a comprehensive cell atlas as hematopoietic reference. We developed counterpart composite index (CCI; available at GitHub: https://github.com/pengfeeei/cci) to search for the healthy counterpart of each leukemia cell subpopulation, by integrating multiple statistics to map leukemia cells onto reference hematopoietic cells. Interestingly, we found leukemia cell subpopulations from each patient had different healthy counterparts. Analysis showed the trajectories of leukemia cell subpopulations were similar to that of their healthy counterparts, indicating that developmental termination of leukemia initiating cells at different phases leads to different leukemia cell subpopulations thus explained the origin of leukemia heterogeneity. CCI further predicts leukemia subtypes, cellular heterogeneity, and cellular stemness of each leukemia patient. Analyses of leukemia patient at diagnosis, refractory, remission and relapse vividly presented dynamics of cell population during leukemia treatment. CCI analyses showed the healthy counterparts of relapsed leukemia cells were closer to the root of hematopoietic tree than that of other leukemia cells, although single-cell transcriptomic genetic variants and haplotype tracing analyses showed the relapsed leukemia cell were derived from an early minor leukemia cell population. In summary, this study developed a unified framework for understanding leukemogenesis with hematopoiesis reference, which provided novel biological and medical implication.
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Affiliation(s)
- Pengfei Qin
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Yakun Pang
- State Key Laboratory of Experimental Hematology & National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine & Department of Stem Cell and Regenerative Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Wenhong Hou
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Ruiqing Fu
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Yingchi Zhang
- State Key Laboratory of Experimental Hematology & National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine & Department of Stem Cell and Regenerative Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Pediatric Hematology, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Xuefei Wang
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Guofeng Meng
- Institute of Interdisciplinary Integrative Biomedical Research, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Qifa Liu
- Department of Hematology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Xiaofan Zhu
- State Key Laboratory of Experimental Hematology & National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine & Department of Stem Cell and Regenerative Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Pediatric Hematology, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Ni Hong
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong, China.
| | - Tao Cheng
- State Key Laboratory of Experimental Hematology & National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China. .,Center for Stem Cell Medicine & Department of Stem Cell and Regenerative Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
| | - Wenfei Jin
- Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong, China.
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37
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Ge W, Wang JJ, Zhang RQ, Tan SJ, Zhang FL, Liu WX, Li L, Sun XF, Cheng SF, Dyce PW, De Felici M, Shen W. Dissecting the initiation of female meiosis in the mouse at single-cell resolution. Cell Mol Life Sci 2021; 78:695-713. [PMID: 32367190 PMCID: PMC11072979 DOI: 10.1007/s00018-020-03533-8] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 03/22/2020] [Accepted: 04/17/2020] [Indexed: 01/22/2023]
Abstract
Meiosis is one of the most finely orchestrated events during gametogenesis with distinct developmental patterns in males and females. However, the molecular mechanisms involved in this process remain not well known. Here, we report detailed transcriptome analyses of cell populations present in the mouse female gonadal ridges (E11.5) and the embryonic ovaries from E12.5 to E14.5 using single-cell RNA sequencing (scRNA seq). These periods correspond with the initiation and progression of meiosis throughout the first stage of prophase I. We identified 13 transcriptionally distinct cell populations and 7 transcriptionally distinct germ cell subclusters that correspond to mitotic (3 clusters) and meiotic (4 clusters) germ cells. By analysing cluster-specific gene expression profiles, we found four cell clusters correspond to different cell stages en route to meiosis and characterized their detailed transcriptome dynamics. Our scRNA seq analysis here represents a new important resource for deciphering the molecular pathways driving female meiosis initiation.
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Affiliation(s)
- Wei Ge
- College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109, China
| | - Jun-Jie Wang
- College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109, China
| | - Rui-Qian Zhang
- College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109, China
| | - Shao-Jing Tan
- College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109, China
| | - Fa-Li Zhang
- College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109, China
| | - Wen-Xiang Liu
- College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109, China
| | - Lan Li
- College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109, China
| | - Xiao-Feng Sun
- College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109, China
| | - Shun-Feng Cheng
- College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109, China
| | - Paul W Dyce
- Department of Animal Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Massimo De Felici
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Wei Shen
- College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109, China.
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38
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Lieberman B, Kusi M, Hung CN, Chou CW, He N, Ho YY, Taverna JA, Huang THM, Chen CL. Toward uncharted territory of cellular heterogeneity: advances and applications of single-cell RNA-seq. JOURNAL OF TRANSLATIONAL GENETICS AND GENOMICS 2021; 5:1-21. [PMID: 34322662 PMCID: PMC8315474 DOI: 10.20517/jtgg.2020.51] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Among single-cell analysis technologies, single-cell RNA-seq (scRNA-seq) has been one of the front runners in technical inventions. Since its induction, scRNA-seq has been well received and undergone many fast-paced technical improvements in cDNA synthesis and amplification, processing and alignment of next generation sequencing reads, differentially expressed gene calling, cell clustering, subpopulation identification, and developmental trajectory prediction. scRNA-seq has been exponentially applied to study global transcriptional profiles in all cell types in humans and animal models, healthy or with diseases, including cancer. Accumulative novel subtypes and rare subpopulations have been discovered as potential underlying mechanisms of stochasticity, differentiation, proliferation, tumorigenesis, and aging. scRNA-seq has gradually revealed the uncharted territory of cellular heterogeneity in transcriptomes and developed novel therapeutic approaches for biomedical applications. This review of the advancement of scRNA-seq methods provides an exploratory guide of the quickly evolving technical landscape and insights of focused features and strengths in each prominent area of progress.
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Affiliation(s)
- Brandon Lieberman
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Meena Kusi
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Chia-Nung Hung
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Chih-Wei Chou
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Ning He
- Department of Nursing, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Yen-Yi Ho
- Department of Statistics, University of South Carolina, Columbia, SC 29208, USA
| | - Josephine A. Taverna
- Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
- Mays Cancer Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Tim H. M. Huang
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
- Mays Cancer Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Chun-Liang Chen
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
- Mays Cancer Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
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Abstract
Application of nonlinear dynamics to cancer ecosystems. Chemical turbulence and strange attractor models in tumor growth, invasion and pattern formation are investigated. Computational algorithms for detecting such structures are proposed. Complex systems applications to cancer dynamics. Cancers are complex, adaptive ecosystems. They remain the leading cause of disease-related death among children in North America. As we approach computational oncology and Deep Learning Healthcare, our mathematical models of cancer dynamics must be revised. Recent findings support the perspective that cancer-microenvironment interactions may consist of chaotic gene expressions and turbulent protein flows during pattern formation. As such, cancer pattern formation, protein-folding and metastatic invasion are discussed herein as processes driven by chemical turbulence within the framework of complex systems theory. To conclude, cancer stem cells are presented as strange attractors of the Waddington landscape.
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Hall MS, Decker JT, Shea LD. Towards systems tissue engineering: Elucidating the dynamics, spatial coordination, and individual cells driving emergent behaviors. Biomaterials 2020; 255:120189. [PMID: 32569865 PMCID: PMC7396312 DOI: 10.1016/j.biomaterials.2020.120189] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 04/20/2020] [Accepted: 06/09/2020] [Indexed: 12/11/2022]
Abstract
Biomaterial systems have enabled the in vitro production of complex, emergent tissue behaviors that were not possible with conventional two-dimensional culture systems, allowing for analysis of both normal development and disease processes. We propose that the path towards developing the design parameters for biomaterial systems lies with identifying the molecular drivers of emergent behavior through leveraging technological advances in systems biology, including single cell omics, genetic engineering, and high content imaging. This growing research opportunity at the intersection of the fields of tissue engineering and systems biology - systems tissue engineering - can uniquely interrogate the mechanisms by which complex tissue behaviors emerge with the potential to capture the contribution of i) dynamic regulation of tissue development and dysregulation, ii) single cell heterogeneity and the function of rare cell types, and iii) the spatial distribution and structure of individual cells and cell types within a tissue. By leveraging advances in both biological and materials data science, systems tissue engineering can facilitate the identification of biomaterial design parameters that will accelerate basic science discovery and translation.
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Affiliation(s)
- Matthew S Hall
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Joseph T Decker
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Lonnie D Shea
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
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41
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Wang Z, Guo X, Gao L, Wang Y, Ma W, Xing B. Glioblastoma cell differentiation trajectory predicts the immunotherapy response and overall survival of patients. Aging (Albany NY) 2020; 12:18297-18321. [PMID: 32957084 PMCID: PMC7585071 DOI: 10.18632/aging.103695] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 06/25/2020] [Indexed: 01/24/2023]
Abstract
Glioblastoma (GBM) is the most common and lethal primary brain tumor. In this study, we aimed to investigate the differentiation states of GBM cells and their clinical relevance. Integrated single-cell RNA-sequencing (scRNA-seq) data and bulk RNA-seq data from GBM samples were used for analysis. Two subsets of GBM cells in distinct differentiation states were characterized, and 498 GBM cell differentiation-related genes (GDRGs) were identified. GDRGs were significantly correlated with immune regulation and metabolic pathways. We classified the GBM patients into two groups based on the expression of GDRGs in tumors and found that the cell differentiation-based classification successfully predicted patient overall survival (OS), immune checkpoint expression and likelihood of immunotherapy response in GBMs. FN1, APOE, RPL7A and GSTM2 were the 4 most significant survival-predicting GDRGs, and patients with different expression levels of each of these genes had distinct survival outcomes. Finally, a nomogram composed of the GDRG signature, age, pharmacotherapy, radiotherapy, IDH mutations and MGMT promoter methylation was generated and validated in two large GBM cohorts to predict GBM prognosis. This study highlights the significant roles of cell differentiation in predicting the clinical outcomes of GBM patients and their potential response to immunotherapy, suggesting promising therapeutic targets for GBM.
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Affiliation(s)
- Zihao Wang
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, P. R. China
| | - Xiaopeng Guo
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, P. R. China
| | - Lu Gao
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, P. R. China
| | - Yu Wang
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, P. R. China
| | - Wenbin Ma
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, P. R. China
| | - Bing Xing
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, P. R. China
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Abstract
PURPOSE OF REVIEW In this review, we highlight key recent insights into hematopoiesis and hematological malignancies through the application of novel single-cell approaches. We particularly focus on biological insights made through the study of stem/progenitors cells in myeloid malignancy at single-cell resolution. RECENT FINDINGS Bulk molecular profiling of hematological malignancies by next generation sequencing techniques has provided major insights into the molecular pathogenesis of blood cancers. This technology is now routinely implemented in advanced clinical diagnostics, leading to the development of novel targeted therapies. However, bulk genetic analysis can obscure key aspects of intratumoral heterogeneity which underlies critical disease events, such as treatment resistance and clonal evolution. The past few years have seen an explosion of novel techniques to analyze RNA, DNA, and protein expression at the single-cell level, providing unprecedented insight into cellular heterogeneity. SUMMARY Given the ease of accessibility of liquid tumor biopsies, hematology is well positioned to move novel single-cell techniques towards routine application in the clinic. The present review sets out to discuss current and potential future applications for this technology in the management of patients with hematological cancers.
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Liu X, Chen W, Li W, Li Y, Priest JR, Zhou B, Wang J, Zhou Z. Single-Cell RNA-Seq of the Developing Cardiac Outflow Tract Reveals Convergent Development of the Vascular Smooth Muscle Cells. Cell Rep 2020; 28:1346-1361.e4. [PMID: 31365875 DOI: 10.1016/j.celrep.2019.06.092] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 04/17/2019] [Accepted: 06/25/2019] [Indexed: 02/07/2023] Open
Abstract
Cardiac outflow tract (OFT) is a major hotspot for congenital heart diseases. A thorough understanding of the cellular diversity, transitions, and regulatory networks of normal OFT development is essential to decipher the etiology of OFT malformations. We performed single-cell transcriptomic sequencing of 55,611 mouse OFT cells from three developmental stages that generally correspond to the early, middle, and late stages of OFT remodeling and septation. Known cellular transitions, such as endothelial-to-mesenchymal transition, have been recapitulated. In particular, we identified convergent development of the vascular smooth muscle cell (VSMC) lineage where intermediate cell subpopulations were found to be involved in either myocardial-to-VSMC trans-differentiation or mesenchymal-to-VSMC transition. Finally, we uncovered transcriptional regulators potentially governing cellular transitions. Our study provides a single-cell reference map of cell states for normal OFT development and paves the way for further studies of the etiology of OFT malformations at the single-cell level.
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Affiliation(s)
- Xuanyu Liu
- State Key Laboratory of Cardiovascular Disease, Beijing Key Laboratory for Molecular Diagnostics of Cardiovascular Diseases, Center of Laboratory Medicine, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Wen Chen
- State Key Laboratory of Cardiovascular Disease, Beijing Key Laboratory for Molecular Diagnostics of Cardiovascular Diseases, Center of Laboratory Medicine, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Wenke Li
- State Key Laboratory of Cardiovascular Disease, Beijing Key Laboratory for Molecular Diagnostics of Cardiovascular Diseases, Center of Laboratory Medicine, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Yan Li
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - James R Priest
- Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Bin Zhou
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Regenerative Medicine of Ministry of Education, Jinan University. School of Life Science and Technology, ShanghaiTech University, Shanghai 200031, China
| | - Jikui Wang
- Henan Key Laboratory for Medical Tissue Regeneration, School of Basic Medical Sciences, Xinxiang Medical University. Xinxiang 453003, China.
| | - Zhou Zhou
- State Key Laboratory of Cardiovascular Disease, Beijing Key Laboratory for Molecular Diagnostics of Cardiovascular Diseases, Center of Laboratory Medicine, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
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Hou R, Denisenko E, Forrest ARR. scMatch: a single-cell gene expression profile annotation tool using reference datasets. Bioinformatics 2020; 35:4688-4695. [PMID: 31028376 PMCID: PMC6853649 DOI: 10.1093/bioinformatics/btz292] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 03/28/2019] [Accepted: 04/21/2019] [Indexed: 12/17/2022] Open
Abstract
MOTIVATION Single-cell RNA sequencing (scRNA-seq) measures gene expression at the resolution of individual cells. Massively multiplexed single-cell profiling has enabled large-scale transcriptional analyses of thousands of cells in complex tissues. In most cases, the true identity of individual cells is unknown and needs to be inferred from the transcriptomic data. Existing methods typically cluster (group) cells based on similarities of their gene expression profiles and assign the same identity to all cells within each cluster using the averaged expression levels. However, scRNA-seq experiments typically produce low-coverage sequencing data for each cell, which hinders the clustering process. RESULTS We introduce scMatch, which directly annotates single cells by identifying their closest match in large reference datasets. We used this strategy to annotate various single-cell datasets and evaluated the impacts of sequencing depth, similarity metric and reference datasets. We found that scMatch can rapidly and robustly annotate single cells with comparable accuracy to another recent cell annotation tool (SingleR), but that it is quicker and can handle larger reference datasets. We demonstrate how scMatch can handle large customized reference gene expression profiles that combine data from multiple sources, thus empowering researchers to identify cell populations in any complex tissue with the desired precision. AVAILABILITY AND IMPLEMENTATION scMatch (Python code) and the FANTOM5 reference dataset are freely available to the research community here https://github.com/forrest-lab/scMatch. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Rui Hou
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA 6009, Australia
| | - Elena Denisenko
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA 6009, Australia
| | - Alistair R R Forrest
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA 6009, Australia
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Putative regulators for the continuum of erythroid differentiation revealed by single-cell transcriptome of human BM and UCB cells. Proc Natl Acad Sci U S A 2020; 117:12868-12876. [PMID: 32457162 DOI: 10.1073/pnas.1915085117] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Fine-resolution differentiation trajectories of adult human hematopoietic stem cells (HSCs) involved in the generation of red cells is critical for understanding dynamic developmental changes that accompany human erythropoiesis. Using single-cell RNA sequencing (scRNA-seq) of primary human terminal erythroid cells (CD34-CD235a+) isolated directly from adult bone marrow (BM) and umbilical cord blood (UCB), we documented the transcriptome of terminally differentiated human erythroblasts at unprecedented resolution. The insights enabled us to distinguish polychromatic erythroblasts (PolyEs) at the early and late stages of development as well as the different development stages of orthochromatic erythroblasts (OrthoEs). We further identified a set of putative regulators of terminal erythroid differentiation and functionally validated three of the identified genes, AKAP8L, TERF2IP, and RNF10, by monitoring cell differentiation and apoptosis. We documented that knockdown of AKAP8L suppressed the commitment of HSCs to erythroid lineage and cell proliferation and delayed differentiation of colony-forming unit-erythroid (CFU-E) to the proerythroblast stage (ProE). In contrast, the knockdown of TERF2IP and RNF10 delayed differentiation of PolyE to OrthoE stage. Taken together, the convergence and divergence of the transcriptional continuums at single-cell resolution underscore the transcriptional regulatory networks that underlie human fetal and adult terminal erythroid differentiation.
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46
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Chen MJ, Lummertz da Rocha E, Cahan P, Kubaczka C, Hunter P, Sousa P, Mullin NK, Fujiwara Y, Nguyen M, Tan Y, Landry S, Han A, Yang S, Lu YF, Jha DK, Vo LT, Zhou Y, North TE, Zon LI, Daley GQ, Schlaeger TM. Transcriptome Dynamics of Hematopoietic Stem Cell Formation Revealed Using a Combinatorial Runx1 and Ly6a Reporter System. Stem Cell Reports 2020; 14:956-971. [PMID: 32302558 PMCID: PMC7220988 DOI: 10.1016/j.stemcr.2020.03.020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2017] [Revised: 03/18/2020] [Accepted: 03/19/2020] [Indexed: 01/01/2023] Open
Abstract
Studies of hematopoietic stem cell (HSC) development from pre-HSC-producing hemogenic endothelial cells (HECs) are hampered by the rarity of these cells and the presence of other cell types with overlapping marker expression profiles. We generated a Tg(Runx1-mKO2; Ly6a-GFP) dual reporter mouse to visualize hematopoietic commitment and study pre-HSC emergence and maturation. Runx1-mKO2 marked all intra-arterial HECs and hematopoietic cluster cells (HCCs), including pre-HSCs, myeloid- and lymphoid progenitors, and HSCs themselves. However, HSC and lymphoid potential were almost exclusively found in reporter double-positive (DP) cells. Robust HSC activity was first detected in DP cells of the placenta, reflecting the importance of this niche for (pre-)HSC maturation and expansion before the fetal liver stage. A time course analysis by single-cell RNA sequencing revealed that as pre-HSCs mature into fetal liver stage HSCs, they show signs of interferon exposure, exhibit signatures of multi-lineage differentiation gene expression, and develop a prolonged cell cycle reminiscent of quiescent adult HSCs.
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Affiliation(s)
- Michael J Chen
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA.
| | - Edroaldo Lummertz da Rocha
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Patrick Cahan
- Department of Biomedical Engineering, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Caroline Kubaczka
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Phoebe Hunter
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Patricia Sousa
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Nathaniel K Mullin
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Yuko Fujiwara
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Minh Nguyen
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Yuqi Tan
- Department of Biomedical Engineering, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Samuel Landry
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Areum Han
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Song Yang
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Yi-Fen Lu
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Deepak Kumar Jha
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Linda T Vo
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Yi Zhou
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Trista E North
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA; Harvard Stem Cell Institute, Harvard University, Boston, MA, USA
| | - Leonard I Zon
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Harvard Stem Cell Institute, Harvard University, Boston, MA, USA; Howard Hughes Medical Institute, Harvard University, Boston, MA, USA; Stem Cell and Regenerative Biology Department, Harvard University, Boston, MA, USA
| | - George Q Daley
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA; Harvard Stem Cell Institute, Harvard University, Boston, MA, USA
| | - Thorsten M Schlaeger
- Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Stem Cell Program, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA; Harvard Stem Cell Institute, Harvard University, Boston, MA, USA.
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47
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Lin C, Ding J, Bar-Joseph Z. Inferring TF activation order in time series scRNA-Seq studies. PLoS Comput Biol 2020; 16:e1007644. [PMID: 32069291 PMCID: PMC7048296 DOI: 10.1371/journal.pcbi.1007644] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 02/28/2020] [Accepted: 01/09/2020] [Indexed: 12/11/2022] Open
Abstract
Methods for the analysis of time series single cell expression data (scRNA-Seq) either do not utilize information about transcription factors (TFs) and their targets or only study these as a post-processing step. Using such information can both, improve the accuracy of the reconstructed model and cell assignments, while at the same time provide information on how and when the process is regulated. We developed the Continuous-State Hidden Markov Models TF (CSHMM-TF) method which integrates probabilistic modeling of scRNA-Seq data with the ability to assign TFs to specific activation points in the model. TFs are assumed to influence the emission probabilities for cells assigned to later time points allowing us to identify not just the TFs controlling each path but also their order of activation. We tested CSHMM-TF on several mouse and human datasets. As we show, the method was able to identify known and novel TFs for all processes, assigned time of activation agrees with both expression information and prior knowledge and combinatorial predictions are supported by known interactions. We also show that CSHMM-TF improves upon prior methods that do not utilize TF-gene interaction. An important attribute of time series single cell RNA-Seq (scRNA-Seq) data, is the ability to infer continuous trajectories of genes based on orderings of the cells. While several methods have been developed for ordering cells and inferring such trajectories, to date it was not possible to use these to infer the temporal activity of several key TFs. These TFs are are only post-transcriptionally regulated and so their expression does not provide complete information on their activity. To address this we developed the Continuous-State Hidden Markov Models TF (CSHMM-TF) methods that assigns continuous activation time to TFs based on both, their expression and the expression of their targets. Applying our method to several time series scRNA-Seq datasets we show that it correctly identifies the key regulators for the processes being studied. We analyze the temporal assignments for these TFs and show that they provide new insights about combinatorial regulation and the ordering of TF activation. We used several complementary sources to validate some of these predictions and discuss a number of other novel suggestions based on the method. As we show, the method is able to scale to large and noisy datasets and so is appropriate for several studies utilizing time series scRNA-Seq data.
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Affiliation(s)
- Chieh Lin
- Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Jun Ding
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Ziv Bar-Joseph
- Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- * E-mail:
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48
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Zhang J, Nie Q, Zhou T. Revealing Dynamic Mechanisms of Cell Fate Decisions From Single-Cell Transcriptomic Data. Front Genet 2019; 10:1280. [PMID: 31921315 PMCID: PMC6935941 DOI: 10.3389/fgene.2019.01280] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Accepted: 11/21/2019] [Indexed: 02/05/2023] Open
Abstract
Cell fate decisions play a pivotal role in development, but technologies for dissecting them are limited. We developed a multifunction new method, Topographer, to construct a "quantitative" Waddington's landscape of single-cell transcriptomic data. This method is able to identify complex cell-state transition trajectories and to estimate complex cell-type dynamics characterized by fate and transition probabilities. It also infers both marker gene networks and their dynamic changes as well as dynamic characteristics of transcriptional bursting along the cell-state transition trajectories. Applying this method to single-cell RNA-seq data on the differentiation of primary human myoblasts, we not only identified three known cell types, but also estimated both their fate probabilities and transition probabilities among them. We found that the percent of genes expressed in a bursty manner is significantly higher at (or near) the branch point (~97%) than before or after branch (below 80%), and that both gene-gene and cell-cell correlation degrees are apparently lower near the branch point than away from the branching. Topographer allows revealing of cell fate mechanisms in a coherent way at three scales: cell lineage (macroscopic), gene network (mesoscopic), and gene expression (microscopic).
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Affiliation(s)
- Jiajun Zhang
- School of Mathematics, Sun Yat-Sen University, Guangzhou, China
- Guangdong Province Key Laboratory of Computational Science and School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, China
| | - Qing Nie
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, United States
- Department of Mathematics, University of California, Irvine, Irvine, CA, United States
| | - Tianshou Zhou
- School of Mathematics, Sun Yat-Sen University, Guangzhou, China
- Guangdong Province Key Laboratory of Computational Science and School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, China
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Qi Z, Barrett T, Parikh AS, Tirosh I, Puram SV. Single-cell sequencing and its applications in head and neck cancer. Oral Oncol 2019; 99:104441. [PMID: 31689639 PMCID: PMC6981283 DOI: 10.1016/j.oraloncology.2019.104441] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 10/01/2019] [Indexed: 01/22/2023]
Abstract
Head and neck squamous cell carcinoma (HNSCC), like many tumors, is characterized by significant intra-tumoral heterogeneity, namely transcriptional, genetic, and epigenetic differences that define distinct cellular subpopulations. While it has been established that intra-tumoral heterogeneity may have prognostic significance in HNSCC, we are only beginning to describe and define such heterogeneity at a cellular resolution. Recent advances in single-cell sequencing technologies have been critical in this regard, opening new avenues in our understanding of more nuanced tumor biology by identifying distinct cellular subpopulations, dissecting signaling within the tumor microenvironment, and characterizing cellular genomic mutations and copy number aberrations. The combined effect of these insights is likely to be robust and meaningful changes in existing diagnostic and treatment algorithms through the application of novel biomarkers as well as targeted therapeutics. Here, we review single-cell technological and computational advances at the genomic, transcriptomic, and epigenomic levels, and discuss their applications in cancer research and clinical practice, with a specific focus on HNSCC.
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Affiliation(s)
- Zongtai Qi
- Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, USA; Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - Thomas Barrett
- Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, USA; Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - Anuraag S Parikh
- Department of Otolaryngology, Massachusetts Eye and Ear, Boston, MA, USA; Department of Otolaryngology, Harvard Medical School, Boston, MA, USA
| | - Itay Tirosh
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Sidharth V Puram
- Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, USA; Department of Genetics, Washington University School of Medicine, St. Louis, USA.
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Grubman A, Chew G, Ouyang JF, Sun G, Choo XY, McLean C, Simmons RK, Buckberry S, Vargas-Landin DB, Poppe D, Pflueger J, Lister R, Rackham OJL, Petretto E, Polo JM. A single-cell atlas of entorhinal cortex from individuals with Alzheimer's disease reveals cell-type-specific gene expression regulation. Nat Neurosci 2019; 22:2087-2097. [PMID: 31768052 DOI: 10.1038/s41593-019-0539-4] [Citation(s) in RCA: 589] [Impact Index Per Article: 98.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
There is currently little information available about how individual cell types contribute to Alzheimer's disease. Here we applied single-nucleus RNA sequencing to entorhinal cortex samples from control and Alzheimer's disease brains (n = 6 per group), yielding a total of 13,214 high-quality nuclei. We detail cell-type-specific gene expression patterns, unveiling how transcriptional changes in specific cell subpopulations are associated with Alzheimer's disease. We report that the Alzheimer's disease risk gene APOE is specifically repressed in Alzheimer's disease oligodendrocyte progenitor cells and astrocyte subpopulations and upregulated in an Alzheimer's disease-specific microglial subopulation. Integrating transcription factor regulatory modules with Alzheimer's disease risk loci revealed drivers of cell-type-specific state transitions towards Alzheimer's disease. For example, transcription factor EB, a master regulator of lysosomal function, regulates multiple disease genes in a specific Alzheimer's disease astrocyte subpopulation. These results provide insights into the coordinated control of Alzheimer's disease risk genes and their cell-type-specific contribution to disease susceptibility. These results are available at http://adsn.ddnetbio.com.
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Affiliation(s)
- Alexandra Grubman
- Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Clayton, Victoria, Australia
- Australian Regenerative Medicine Institute, Monash University, Clayton, Victoria, Australia
| | - Gabriel Chew
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - John F Ouyang
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Guizhi Sun
- Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Clayton, Victoria, Australia
- Australian Regenerative Medicine Institute, Monash University, Clayton, Victoria, Australia
| | - Xin Yi Choo
- Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Clayton, Victoria, Australia
- Australian Regenerative Medicine Institute, Monash University, Clayton, Victoria, Australia
- Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Catriona McLean
- Victorian Brain Bank, Florey Institute of Neurosciences, Parkville, Victoria, Australia
| | - Rebecca K Simmons
- ARC Center of Excellence in Plant Energy Biology, The University of Western Australia, Perth, Western Australia, Australia
- The Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
| | - Sam Buckberry
- ARC Center of Excellence in Plant Energy Biology, The University of Western Australia, Perth, Western Australia, Australia
- The Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
| | - Dulce B Vargas-Landin
- ARC Center of Excellence in Plant Energy Biology, The University of Western Australia, Perth, Western Australia, Australia
- The Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
| | - Daniel Poppe
- ARC Center of Excellence in Plant Energy Biology, The University of Western Australia, Perth, Western Australia, Australia
- The Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
| | - Jahnvi Pflueger
- ARC Center of Excellence in Plant Energy Biology, The University of Western Australia, Perth, Western Australia, Australia
- The Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
| | - Ryan Lister
- ARC Center of Excellence in Plant Energy Biology, The University of Western Australia, Perth, Western Australia, Australia
- The Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
| | - Owen J L Rackham
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore Medical School, Singapore, Singapore.
| | - Enrico Petretto
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore Medical School, Singapore, Singapore.
| | - Jose M Polo
- Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia.
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Clayton, Victoria, Australia.
- Australian Regenerative Medicine Institute, Monash University, Clayton, Victoria, Australia.
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